</noscript><div id="__next"><header class="header_headerContainer__cnwRR"><div class="page_container__IibMw header_desktopHeaderWrapper__HEBG_"><a title="Zilliz logo" class="header_logoWrapper__0doBt" href="/"><svg width="97" height="40" viewBox="0 0 97 40" fill="none" xmlns="http://www.w3.org/2000/svg"><g clip-path="url(#clip0_4874_3768)"><rect width="97" height="40" fill="transparent"></rect><path fill-rule="evenodd" clip-rule="evenodd" d="M18.6541 27.0547V39.7949H21.1413V24.5393L27.7546 35.9938C28.503 35.6278 29.2221 35.2111 29.9074 34.7483L22.6675 22.2084L30.641 25.1105C31.0007 24.3705 31.2862 23.5877 31.4879 22.7719L27.007 21.141H39.7949V18.6538H24.5381L35.9936 12.04C35.6276 11.2916 35.2109 10.5725 34.748 9.8872L22.2832 17.0838L25.1605 9.1786C24.4221 8.81536 23.6406 8.52618 22.8259 8.32075L21.1413 12.9492V0H18.6541V15.257L12.04 3.80101C11.2916 4.16702 10.5725 4.58369 9.88716 5.04654L17.0968 17.534L9.17163 14.6495C8.80943 15.3884 8.52133 16.1702 8.31702 16.9852L12.9015 18.6538H1.08717e-07L0 21.141H15.2559L3.80081 27.7546C4.16682 28.503 4.58348 29.2221 5.04633 29.9074L17.6089 22.6545L14.6995 30.6478C15.44 31.0066 16.2231 31.291 17.0392 31.4915L18.6541 27.0547Z" fill="url(#desktop-logo)"></path><rect x="46.0625" y="12.4359" width="11.3415" height="2.48718" fill="#000"></rect><rect x="85.3599" y="12.4359" width="11.3415" height="2.48718" fill="#000"></rect><rect x="67.0542" y="6.66563" width="2.68615" height="20.6933" fill="#000"></rect><rect x="61.085" y="12.4359" width="2.68615" height="14.9231" fill="#000"></rect><rect width="2.68615" height="2.68615" transform="matrix(1 0 0 -1 61.085 9.35179)" fill="#000"></rect><rect x="45.7642" y="24.8718" width="11.9385" height="2.48718" fill="#000"></rect><path d="M45.7642 24.8718L54.2216 14.9231L57.4042 14.9231L48.9467 24.8718L45.7642 24.8718Z" fill="#000"></path><path d="M85.0615 24.8718L93.519 14.9231L96.7015 14.9231L88.2441 24.8718L85.0615 24.8718Z" fill="#000"></path><rect x="73.0234" y="6.66563" width="2.68615" height="20.6933" fill="#000"></rect><rect x="85.0615" y="24.8718" width="11.9385" height="2.48718" fill="#000"></rect><rect x="78.9927" y="12.4359" width="2.68615" height="14.9231" fill="#000"></rect><rect width="2.68615" height="2.68615" transform="matrix(1 0 0 -1 78.9927 9.35179)" fill="#000"></rect></g><defs><linearGradient id="desktop-logo" x1="8.45641" y1="4.2282" x2="29.0503" y2="37.6061" gradientUnits="userSpaceOnUse"><stop stop-color="#9D41FF"></stop><stop offset="0.468794" stop-color="#2858FF"></stop><stop offset="0.770884" stop-color="#29B8FF"></stop><stop offset="1" stop-color="#00F0FF"></stop></linearGradient><clipPath id="clip0_4874_3768"><rect width="97" height="40" fill="white"></rect></clipPath></defs></svg></a><div class="header_rightSection__wt8UV"><ul class="header_navsWrapper__bq2UF"><li class="header_menuItem__mBXHj">Products<svg width="13" height="12" viewBox="0 0 13 12" fill="none" xmlns="http://www.w3.org/2000/svg" class="header_verticalArrow__q0f2B"><path d="M2.5 4L6.5 8L10.5 4" stroke="#475467" stroke-width="2"></path></svg><div class="header_menuTransitionWrapper__eM91e" style="width:0px"><div class="header_subMenuWrapper__wGcsK"><div class="header_partWrapper__wFjH4 header_leftPart__PjZlt"><div class="header_cloudsContainer__inoV3"><div class=""><a class="header_cloudWrapper__MZqZI" href="/cloud"><svg width="40" height="40" viewBox="0 0 40 40" fill="none" xmlns="http://www.w3.org/2000/svg"><g clip-path="url(#clip0_4566_5716)"><path fill-rule="evenodd" clip-rule="evenodd" d="M40 19.8776C40 27.5419 33.7868 33.7551 26.1224 33.7551C26.1224 33.7551 26.1223 33.7551 26.1222 33.7551V33.7552H9.84091C9.82593 33.7553 9.81094 33.7553 9.79593 33.7553C4.38579 33.7553 0 29.3695 0 23.9594C0 18.5492 4.38579 14.1634 9.79593 14.1634C10.9977 14.1634 12.1489 14.3798 13.2127 14.7758C15.2456 9.63583 20.2594 6 26.1224 6C33.7868 6 40 12.2132 40 19.8776Z" fill="url(#paint0_linear_4566_5716)"></path></g><defs><linearGradient id="paint0_linear_4566_5716" x1="43.5833" y1="3.43409" x2="-7.67604" y2="6.91206" gradientUnits="userSpaceOnUse"><stop stop-color="#3542B7"></stop><stop offset="1" stop-color="#00CFDE"></stop></linearGradient><clipPath id="clip0_4566_5716"><rect width="40" height="40" fill="white"></rect></clipPath></defs></svg><p class="header_cloudName__FKCnE">Zilliz Cloud<svg width="16" height="17" viewBox="0 0 16 17" fill="none" xmlns="http://www.w3.org/2000/svg"><path d="M10.7817 8.15636L7.20566 4.58036L8.14833 3.6377L13.3337 8.82303L8.14833 14.0084L7.20566 13.0657L10.7817 9.4897H2.66699V8.15636H10.7817Z" fill="black"></path></svg></p><p class="header_description__PJAok">Fully-managed vector database service designed for speed, scale and high performance.</p></a><a class="header_zillizVsMilvus__xq9eR" href="/zilliz-vs-milvus">Zilliz Cloud vs. Milvus<svg width="16" height="17" viewBox="0 0 16 17" fill="none" xmlns="http://www.w3.org/2000/svg"><path d="M10.7817 8.15636L7.20566 4.58036L8.14833 3.6377L13.3337 8.82303L8.14833 14.0084L7.20566 13.0657L10.7817 9.4897H2.66699V8.15636H10.7817Z" fill="black"></path></svg></a></div><a class="header_cloudWrapper__MZqZI" href="/what-is-milvus"><svg width="40" height="40" viewBox="0 0 40 40" fill="none" xmlns="http://www.w3.org/2000/svg"><path d="M27.4365 11.5932C22.6628 6.80225 14.922 6.80225 10.1483 11.5932L2.34592 19.4238C1.88469 19.8871 1.88469 20.6333 2.34592 21.0967L10.1483 28.9272C14.922 33.7182 22.6628 33.7182 27.4365 28.935C32.2179 24.1519 32.2179 16.3842 27.4365 11.5932ZM25.5916 26.6338C22.0863 30.1524 16.3979 30.1524 12.8926 26.6338L7.15033 20.8768C6.8121 20.539 6.8121 19.9893 7.15033 19.6437L12.8849 13.8945C16.3902 10.3759 22.0786 10.3759 25.5839 13.8945C29.0969 17.4131 29.0969 23.1152 25.5916 26.6338Z" fill="#00B3FF"></path><path d="M37.6599 19.4316L34.2238 15.9208C34.0162 15.7088 33.6703 15.9051 33.7395 16.1957C34.3314 18.8739 34.3314 21.67 33.7395 24.3482C33.678 24.6388 34.0239 24.8273 34.2238 24.6231L37.6599 21.1124C38.1134 20.6411 38.1134 19.895 37.6599 19.4316Z" fill="#00B3FF"></path><path d="M19.2802 26.4217C22.6044 26.4217 25.2992 23.6684 25.2992 20.272C25.2992 16.8756 22.6044 14.1222 19.2802 14.1222C15.956 14.1222 13.2612 16.8756 13.2612 20.272C13.2612 23.6684 15.956 26.4217 19.2802 26.4217Z" fill="#00B3FF"></path></svg><p class="header_cloudName__FKCnE">Milvus<svg width="16" height="17" viewBox="0 0 16 17" fill="none" xmlns="http://www.w3.org/2000/svg"><path d="M10.7817 8.15636L7.20566 4.58036L8.14833 3.6377L13.3337 8.82303L8.14833 14.0084L7.20566 13.0657L10.7817 9.4897H2.66699V8.15636H10.7817Z" fill="black"></path></svg></p><p class="header_description__PJAok">Open-source vector database built for billion-scale vector similarity search.</p></a></div></div><ul class="header_partWrapper__wFjH4 header_midPart__DU60V"><li class=""><a class="header_linkTitle__rhULA" href="/bring-your-own-cloud">BYOC</a></li><li class=""><a class="header_linkTitle__rhULA" href="/zilliz-migration-service">Migration</a></li><li class=""><a rel="noopener noreferrer" target="_blank" class="header_linkTitle__rhULA" href="/vector-database-benchmark-tool">Benchmark</a></li><li class=""><a class="header_linkTitle__rhULA" href="/product/integrations">Integrations</a></li><li class=""><a class="header_linkTitle__rhULA" href="/product/open-source-vector-database">Open Source</a></li><li class=""><a rel="noopener noreferrer" target="_blank" class="header_linkTitle__rhULA" href="https://support.zilliz.com/hc/en-us">Support Portal</a></li></ul><div class="header_partWrapper__wFjH4 header_rightPart__mJ5rk"><div class="header_imgWrapper__acXaO" style="background-image:url(https://assets.zilliz.com/medium_serverless_page_cover_d8d3872318.png)"></div><a class="header_linkTitle__rhULA" href="/serverless">High-Performance Vector Database Made Serverless.</a></div></div></div></li><li class="header_menuItem__mBXHj">Pricing<svg width="13" height="12" viewBox="0 0 13 12" fill="none" xmlns="http://www.w3.org/2000/svg" class="header_verticalArrow__q0f2B"><path d="M2.5 4L6.5 8L10.5 4" stroke="#475467" stroke-width="2"></path></svg><div class="header_menuTransitionWrapper__eM91e" style="width:0px"><div class="header_subMenuWrapper__wGcsK"><ul class="header_partWrapper__wFjH4 header_midPart__DU60V"><li class=""><a class="header_linkTitle__rhULA" href="/pricing">Pricing Plan<span class="header_linkTip__MOCQ1">Flexible pricing options for every team on any budget</span></a></li><li class=""><a class="header_linkTitle__rhULA" href="/pricing#calculator">Calculator<span class="header_linkTip__MOCQ1">Estimate your cost</span></a></li></ul><div class="header_partWrapper__wFjH4 header_rightPart__mJ5rk"><div class="header_imgWrapper__acXaO" style="background-image:url(https://assets.zilliz.com/medium_success_b_6ae4050db7.png)"></div><a class="header_linkTitle__rhULA" href="/zilliz-cloud-free-tier">Free Tier</a></div></div></div></li><li class="header_menuItem__mBXHj">Developers<svg width="13" height="12" viewBox="0 0 13 12" fill="none" xmlns="http://www.w3.org/2000/svg" class="header_verticalArrow__q0f2B"><path d="M2.5 4L6.5 8L10.5 4" stroke="#475467" stroke-width="2"></path></svg><div class="header_menuTransitionWrapper__eM91e" style="width:0px"><div class="header_subMenuWrapper__wGcsK"><div class="header_partWrapper__wFjH4 header_leftPart__PjZlt"><a rel="noopener noreferrer" target="_blank" class="header_documentContainer__BAe5n" href="https://docs.zilliz.com/docs/home"><svg width="50" height="50" viewBox="0 0 50 50" fill="none" xmlns="http://www.w3.org/2000/svg" class="header_docIcon__xGEVK"><path d="M22.6667 38.6667H4C1.79087 38.6667 0 36.8759 0 34.6667V13.3333C0 12.597 0.59696 12 1.33333 12H20C20.7364 12 21.3333 12.597 21.3333 13.3333V29.3333H26.6667V34.6667C26.6667 36.8759 24.8759 38.6667 22.6667 38.6667ZM21.3333 32V34.6667C21.3333 35.4031 21.9303 36 22.6667 36C23.4031 36 24 35.4031 24 34.6667V32H21.3333ZM18.6667 36V14.6667H2.66667V34.6667C2.66667 35.4031 3.26363 36 4 36H18.6667ZM5.33333 18.6667H16V21.3333H5.33333V18.6667ZM5.33333 24H16V26.6667H5.33333V24ZM5.33333 29.3333H12V32H5.33333V29.3333Z" fill="black"></path></svg><p class="header_title__UKGc7">Documentation</p><p class="header_description__PJAok">The Zilliz Cloud Developer Hub where you can find all the information to work with Zilliz Cloud</p><p class="header_linkBtn__MlnDS">Learn More<svg width="16" height="17" viewBox="0 0 16 17" fill="none" xmlns="http://www.w3.org/2000/svg"><path d="M10.7817 8.15636L7.20566 4.58036L8.14833 3.6377L13.3337 8.82303L8.14833 14.0084L7.20566 13.0657L10.7817 9.4897H2.66699V8.15636H10.7817Z" fill="black"></path></svg></p></a></div><ul class="header_partWrapper__wFjH4 header_midPart__DU60V"><li class=""><a class="header_linkTitle__rhULA" href="/learn">Learn</a></li><li class=""><a class="header_linkTitle__rhULA" href="/learn/generative-ai">GenAI Resource Hub</a></li><li class=""><a class="header_linkTitle__rhULA" href="/learn/milvus-notebooks">Notebooks</a></li><li class=""><a class="header_linkTitle__rhULA" href="/ai-models">AI Models</a></li><li class=""><a class="header_linkTitle__rhULA" href="/community">Community</a></li><li class=""><a class="header_linkTitle__rhULA" href="/milvus-downloads">Download Milvus</a></li></ul><div class="header_partWrapper__wFjH4 header_rightPart__mJ5rk"><div class="header_imgWrapper__acXaO" style="background-image:url(https://assets.zilliz.com/medium_office_hours_ed5a5d384c.png)"></div><a rel="noopener noreferrer" target="_blank" class="header_linkTitle__rhULA" href="https://discord.com/invite/8uyFbECzPX">Join the Milvus Discord Community</a></div></div></div></li><li class="header_menuItem__mBXHj">Resources<svg width="13" height="12" viewBox="0 0 13 12" fill="none" xmlns="http://www.w3.org/2000/svg" class="header_verticalArrow__q0f2B"><path d="M2.5 4L6.5 8L10.5 4" stroke="#475467" stroke-width="2"></path></svg><div class="header_menuTransitionWrapper__eM91e" style="width:0px"><div class="header_subMenuWrapper__wGcsK"><ul class="header_partWrapper__wFjH4 header_midPart__DU60V"><li class=""><a class="header_linkTitle__rhULA" href="/blog">Blog</a></li><li class=""><a class="header_linkTitle__rhULA" href="/resources?tag=5">Guides</a></li><li class=""><a class="header_linkTitle__rhULA" href="/resources?tag=1">Research</a></li><li class=""><a class="header_linkTitle__rhULA" href="/resources?tag=4">Analyst Reports</a></li><li class=""><a class="header_linkTitle__rhULA" href="/resources?tag=2">Webinars</a></li><li class=""><a class="header_linkTitle__rhULA" href="/resources?tag=3">Trainings</a></li><li class=""><a class="header_linkTitle__rhULA" href="/resources?tag=6">Podcasts</a></li><li class=""><a class="header_linkTitle__rhULA" href="/event">Events</a></li><li class=""><a class="header_linkTitle__rhULA" href="/trust-center">Trust Center</a></li></ul><div class="header_partWrapper__wFjH4 header_rightPart__mJ5rk"><div class="header_imgWrapper__acXaO" style="background-image:url(https://assets.zilliz.com/thumbnail_5fde5817_93e0_4b5f_a63b_4ba02cb51b99_d3d836e307.png)"></div><a class="header_linkTitle__rhULA" href="/resources/guide/definitive-guide-choosing-vector-database">Definitive Guide to Choosing a Vector Database </a></div></div></div></li><li class="header_menuItem__mBXHj">Customers<svg width="13" height="12" viewBox="0 0 13 12" fill="none" xmlns="http://www.w3.org/2000/svg" class="header_verticalArrow__q0f2B"><path d="M2.5 4L6.5 8L10.5 4" stroke="#475467" stroke-width="2"></path></svg><div class="header_menuTransitionWrapper__eM91e" style="width:0px"><div class="header_subMenuWrapper__wGcsK"><div class="header_partWrapper__wFjH4 header_leftPart__PjZlt"><div class="header_solutionsContainer__iViF3"><span class="header_title__UKGc7">By Use Case</span><a class="header_linkTitle__rhULA" href="/vector-database-use-cases/llm-retrieval-augmented-generation">Retrieval Augmented Generation</a><a class="header_linkBtn__MlnDS" href="/vector-database-use-cases">View all use cases<svg width="16" height="17" viewBox="0 0 16 17" fill="none" xmlns="http://www.w3.org/2000/svg"><path d="M10.7817 8.15636L7.20566 4.58036L8.14833 3.6377L13.3337 8.82303L8.14833 14.0084L7.20566 13.0657L10.7817 9.4897H2.66699V8.15636H10.7817Z" fill="black"></path></svg></a><a class="header_linkBtn__MlnDS" href="/industry">View by industry<svg width="16" height="17" viewBox="0 0 16 17" fill="none" xmlns="http://www.w3.org/2000/svg"><path d="M10.7817 8.15636L7.20566 4.58036L8.14833 3.6377L13.3337 8.82303L8.14833 14.0084L7.20566 13.0657L10.7817 9.4897H2.66699V8.15636H10.7817Z" fill="black"></path></svg></a><a class="header_linkBtn__MlnDS" href="/customers">View all customer stories<svg width="16" height="17" viewBox="0 0 16 17" fill="none" xmlns="http://www.w3.org/2000/svg"><path d="M10.7817 8.15636L7.20566 4.58036L8.14833 3.6377L13.3337 8.82303L8.14833 14.0084L7.20566 13.0657L10.7817 9.4897H2.66699V8.15636H10.7817Z" fill="black"></path></svg></a></div></div><div class="header_partWrapper__wFjH4 header_rightPart__mJ5rk"><div class="header_imgWrapper__acXaO" style="background-image:url(https://assets.zilliz.com/medium_Group_13397_084d85124a.png)"></div><a class="header_linkTitle__rhULA" href="/customers/beni">Beni Revolutionizes Sustainable Fashion with Zilliz Cloud&#x27;s Vector Search</a></div></div></div></li></ul><div class="header_btnsWrapper__r9jQ0"><div class="header_languageSelector__MZ0jb"><button class="header_languageBtn__687U2"><svg width="24" height="24" viewBox="0 0 24 24" fill="none" xmlns="http://www.w3.org/2000/svg"><path d="M12 21C10.7613 21 9.59467 20.7633 8.5 20.29C7.40533 19.8167 6.452 19.1733 5.64 18.36C4.82667 17.5487 4.18333 16.5953 3.71 15.5C3.23667 14.4053 3 13.2387 3 12C3 10.758 3.23667 9.59033 3.71 8.497C4.184 7.40367 4.82733 6.451 5.64 5.639C6.45133 4.827 7.40467 4.18433 8.5 3.711C9.59467 3.237 10.7613 3 12 3C13.242 3 14.4097 3.23667 15.503 3.71C16.5963 4.184 17.549 4.82733 18.361 5.64C19.173 6.452 19.8157 7.40433 20.289 8.497C20.763 9.59033 21 10.758 21 12C21 13.2387 20.7633 14.4053 20.29 15.5C19.8167 16.5947 19.1733 17.548 18.36 18.36C17.548 19.1727 16.5957 19.816 15.503 20.29C14.4097 20.7633 13.242 21 12 21ZM12 20.008C12.5867 19.254 13.0707 18.5137 13.452 17.787C13.8327 17.0603 14.1423 16.247 14.381 15.347H9.619C9.883 16.2977 10.199 17.1363 10.567 17.863C10.935 18.5897 11.4127 19.3047 12 20.008ZM10.727 19.858C10.2603 19.308 9.83433 18.628 9.449 17.818C9.06367 17.0087 8.777 16.1847 8.589 15.346H4.753C5.32633 16.59 6.13867 17.61 7.19 18.406C8.242 19.202 9.42067 19.686 10.726 19.858M13.272 19.858C14.5773 19.686 15.756 19.202 16.808 18.406C17.86 17.61 18.6723 16.59 19.245 15.346H15.411C15.1577 16.1973 14.8387 17.028 14.454 17.838C14.0687 18.6473 13.6747 19.3207 13.272 19.858ZM4.345 14.346H8.38C8.304 13.936 8.25067 13.5363 8.22 13.147C8.188 12.7577 8.172 12.3753 8.172 12C8.172 11.6247 8.18767 11.2423 8.219 10.853C8.25033 10.4637 8.30367 10.0637 8.379 9.653H4.347C4.23833 9.99967 4.15333 10.3773 4.092 10.786C4.03067 11.1947 4 11.5993 4 12C4 12.4013 4.03033 12.806 4.091 13.214C4.15233 13.6227 4.23733 14 4.346 14.346M9.381 14.346H14.619C14.695 13.936 14.7483 13.5427 14.779 13.166C14.811 12.79 14.827 12.4013 14.827 12C14.827 11.5987 14.8113 11.21 14.78 10.834C14.7487 10.4573 14.6953 10.064 14.62 9.654H9.38C9.30467 10.064 9.25133 10.4573 9.22 10.834C9.18867 11.21 9.173 11.5987 9.173 12C9.173 12.4013 9.18867 12.79 9.22 13.166C9.25133 13.5427 9.30567 13.936 9.381 14.346ZM15.62 14.346H19.654C19.7627 13.9993 19.8477 13.622 19.909 13.214C19.9703 12.806 20.0007 12.4013 20 12C20 11.5987 19.9697 11.194 19.909 10.786C19.8477 10.3773 19.7627 10 19.654 9.654H15.619C15.695 10.064 15.7483 10.4637 15.779 10.853C15.811 11.2423 15.827 11.6247 15.827 12C15.827 12.3753 15.8113 12.7577 15.78 13.147C15.7487 13.5363 15.6953 13.9363 15.62 14.347M15.412 8.654H19.246C18.66 7.38467 17.8573 6.36467 16.838 5.594C15.818 4.82333 14.6297 4.33333 13.273 4.124C13.7397 4.73733 14.1593 5.43933 14.532 6.23C14.904 7.02 15.1973 7.828 15.412 8.654ZM9.619 8.654H14.381C14.117 7.71533 13.7913 6.86667 13.404 6.108C13.0173 5.34867 12.5493 4.64333 12 3.992C11.4513 4.64333 10.9833 5.34867 10.596 6.108C10.2093 6.86667 9.88367 7.71533 9.619 8.654ZM4.754 8.654H8.588C8.80267 7.828 9.096 7.02 9.468 6.23C9.84067 5.43933 10.2603 4.737 10.727 4.123C9.35767 4.333 8.16633 4.82633 7.153 5.603C6.13967 6.38033 5.33967 7.397 4.753 8.653" fill="#1D2939"></path></svg></button><div class="header_dropdownWrapper__Y8x_9"><button class="BaseButton_root__SFmw5 BaseButton_contained__2JisA header_langButton__YmBJV">English</button><button class="BaseButton_root__SFmw5 BaseButton_contained__2JisA header_langButton__YmBJV">日本語</button><button class="BaseButton_root__SFmw5 BaseButton_contained__2JisA header_langButton__YmBJV">한국어</button><button class="BaseButton_root__SFmw5 BaseButton_contained__2JisA header_langButton__YmBJV">Español</button><button class="BaseButton_root__SFmw5 BaseButton_contained__2JisA header_langButton__YmBJV">Français</button><button class="BaseButton_root__SFmw5 BaseButton_contained__2JisA header_langButton__YmBJV">Deutsch</button><button class="BaseButton_root__SFmw5 BaseButton_contained__2JisA header_langButton__YmBJV">Italiano</button><button class="BaseButton_root__SFmw5 BaseButton_contained__2JisA header_langButton__YmBJV">Português</button><button class="BaseButton_root__SFmw5 BaseButton_contained__2JisA header_langButton__YmBJV">Русский</button></div></div><a class="header_linkBtn__MlnDS" href="/contact-sales">Contact us</a><a rel="noopener noreferrer" target="_blank" class="header_linkBtn__MlnDS" href="https://cloud.zilliz.com/login">Log in</a><a rel="noreferrer noopener" target="_blank" title="" class="BaseButton_root__SFmw5 BaseButton_contained__2JisA" href="https://cloud.zilliz.com/signup?utm_page=blog&amp;utm_button=nav_right">Get Started Free</a></div></div></div></header><header class="mobileHeader_headerContainer__voi8M"><div class="page_container__IibMw"><div class="mobileHeader_header__Xap_i"><a title="Zilliz logo" href="/"><svg width="97" height="40" viewBox="0 0 97 40" fill="none" xmlns="http://www.w3.org/2000/svg"><g clip-path="url(#clip0_4874_3768)"><rect width="97" height="40" fill="transparent"></rect><path fill-rule="evenodd" clip-rule="evenodd" d="M18.6541 27.0547V39.7949H21.1413V24.5393L27.7546 35.9938C28.503 35.6278 29.2221 35.2111 29.9074 34.7483L22.6675 22.2084L30.641 25.1105C31.0007 24.3705 31.2862 23.5877 31.4879 22.7719L27.007 21.141H39.7949V18.6538H24.5381L35.9936 12.04C35.6276 11.2916 35.2109 10.5725 34.748 9.8872L22.2832 17.0838L25.1605 9.1786C24.4221 8.81536 23.6406 8.52618 22.8259 8.32075L21.1413 12.9492V0H18.6541V15.257L12.04 3.80101C11.2916 4.16702 10.5725 4.58369 9.88716 5.04654L17.0968 17.534L9.17163 14.6495C8.80943 15.3884 8.52133 16.1702 8.31702 16.9852L12.9015 18.6538H1.08717e-07L0 21.141H15.2559L3.80081 27.7546C4.16682 28.503 4.58348 29.2221 5.04633 29.9074L17.6089 22.6545L14.6995 30.6478C15.44 31.0066 16.2231 31.291 17.0392 31.4915L18.6541 27.0547Z" fill="url(#mobile-logo)"></path><rect x="46.0625" y="12.4359" width="11.3415" height="2.48718" fill="#000"></rect><rect x="85.3599" y="12.4359" width="11.3415" height="2.48718" fill="#000"></rect><rect x="67.0542" y="6.66563" width="2.68615" height="20.6933" fill="#000"></rect><rect x="61.085" y="12.4359" width="2.68615" height="14.9231" fill="#000"></rect><rect width="2.68615" height="2.68615" transform="matrix(1 0 0 -1 61.085 9.35179)" fill="#000"></rect><rect x="45.7642" y="24.8718" width="11.9385" height="2.48718" fill="#000"></rect><path d="M45.7642 24.8718L54.2216 14.9231L57.4042 14.9231L48.9467 24.8718L45.7642 24.8718Z" fill="#000"></path><path d="M85.0615 24.8718L93.519 14.9231L96.7015 14.9231L88.2441 24.8718L85.0615 24.8718Z" fill="#000"></path><rect x="73.0234" y="6.66563" width="2.68615" height="20.6933" fill="#000"></rect><rect x="85.0615" y="24.8718" width="11.9385" height="2.48718" fill="#000"></rect><rect x="78.9927" y="12.4359" width="2.68615" height="14.9231" fill="#000"></rect><rect width="2.68615" height="2.68615" transform="matrix(1 0 0 -1 78.9927 9.35179)" fill="#000"></rect></g><defs><linearGradient id="mobile-logo" x1="8.45641" y1="4.2282" x2="29.0503" y2="37.6061" gradientUnits="userSpaceOnUse"><stop stop-color="#9D41FF"></stop><stop offset="0.468794" stop-color="#2858FF"></stop><stop offset="0.770884" stop-color="#29B8FF"></stop><stop offset="1" stop-color="#00F0FF"></stop></linearGradient><clipPath id="clip0_4874_3768"><rect width="97" height="40" fill="white"></rect></clipPath></defs></svg></a><div class="mobileHeader_menu__3CNGu"><div class="mobileHeader_languageSelector__zLvyD"><button class="mobileHeader_languageBtn__q35Ut"><svg width="24" height="24" viewBox="0 0 24 24" fill="none" xmlns="http://www.w3.org/2000/svg"><path d="M12 21C10.7613 21 9.59467 20.7633 8.5 20.29C7.40533 19.8167 6.452 19.1733 5.64 18.36C4.82667 17.5487 4.18333 16.5953 3.71 15.5C3.23667 14.4053 3 13.2387 3 12C3 10.758 3.23667 9.59033 3.71 8.497C4.184 7.40367 4.82733 6.451 5.64 5.639C6.45133 4.827 7.40467 4.18433 8.5 3.711C9.59467 3.237 10.7613 3 12 3C13.242 3 14.4097 3.23667 15.503 3.71C16.5963 4.184 17.549 4.82733 18.361 5.64C19.173 6.452 19.8157 7.40433 20.289 8.497C20.763 9.59033 21 10.758 21 12C21 13.2387 20.7633 14.4053 20.29 15.5C19.8167 16.5947 19.1733 17.548 18.36 18.36C17.548 19.1727 16.5957 19.816 15.503 20.29C14.4097 20.7633 13.242 21 12 21ZM12 20.008C12.5867 19.254 13.0707 18.5137 13.452 17.787C13.8327 17.0603 14.1423 16.247 14.381 15.347H9.619C9.883 16.2977 10.199 17.1363 10.567 17.863C10.935 18.5897 11.4127 19.3047 12 20.008ZM10.727 19.858C10.2603 19.308 9.83433 18.628 9.449 17.818C9.06367 17.0087 8.777 16.1847 8.589 15.346H4.753C5.32633 16.59 6.13867 17.61 7.19 18.406C8.242 19.202 9.42067 19.686 10.726 19.858M13.272 19.858C14.5773 19.686 15.756 19.202 16.808 18.406C17.86 17.61 18.6723 16.59 19.245 15.346H15.411C15.1577 16.1973 14.8387 17.028 14.454 17.838C14.0687 18.6473 13.6747 19.3207 13.272 19.858ZM4.345 14.346H8.38C8.304 13.936 8.25067 13.5363 8.22 13.147C8.188 12.7577 8.172 12.3753 8.172 12C8.172 11.6247 8.18767 11.2423 8.219 10.853C8.25033 10.4637 8.30367 10.0637 8.379 9.653H4.347C4.23833 9.99967 4.15333 10.3773 4.092 10.786C4.03067 11.1947 4 11.5993 4 12C4 12.4013 4.03033 12.806 4.091 13.214C4.15233 13.6227 4.23733 14 4.346 14.346M9.381 14.346H14.619C14.695 13.936 14.7483 13.5427 14.779 13.166C14.811 12.79 14.827 12.4013 14.827 12C14.827 11.5987 14.8113 11.21 14.78 10.834C14.7487 10.4573 14.6953 10.064 14.62 9.654H9.38C9.30467 10.064 9.25133 10.4573 9.22 10.834C9.18867 11.21 9.173 11.5987 9.173 12C9.173 12.4013 9.18867 12.79 9.22 13.166C9.25133 13.5427 9.30567 13.936 9.381 14.346ZM15.62 14.346H19.654C19.7627 13.9993 19.8477 13.622 19.909 13.214C19.9703 12.806 20.0007 12.4013 20 12C20 11.5987 19.9697 11.194 19.909 10.786C19.8477 10.3773 19.7627 10 19.654 9.654H15.619C15.695 10.064 15.7483 10.4637 15.779 10.853C15.811 11.2423 15.827 11.6247 15.827 12C15.827 12.3753 15.8113 12.7577 15.78 13.147C15.7487 13.5363 15.6953 13.9363 15.62 14.347M15.412 8.654H19.246C18.66 7.38467 17.8573 6.36467 16.838 5.594C15.818 4.82333 14.6297 4.33333 13.273 4.124C13.7397 4.73733 14.1593 5.43933 14.532 6.23C14.904 7.02 15.1973 7.828 15.412 8.654ZM9.619 8.654H14.381C14.117 7.71533 13.7913 6.86667 13.404 6.108C13.0173 5.34867 12.5493 4.64333 12 3.992C11.4513 4.64333 10.9833 5.34867 10.596 6.108C10.2093 6.86667 9.88367 7.71533 9.619 8.654ZM4.754 8.654H8.588C8.80267 7.828 9.096 7.02 9.468 6.23C9.84067 5.43933 10.2603 4.737 10.727 4.123C9.35767 4.333 8.16633 4.82633 7.153 5.603C6.13967 6.38033 5.33967 7.397 4.753 8.653" fill="#1D2939"></path></svg></button><div class="mobileHeader_dropdownWrapper__0DLyM"><button class="BaseButton_root__SFmw5 BaseButton_contained__2JisA mobileHeader_langButton__YkCt_">English</button><button class="BaseButton_root__SFmw5 BaseButton_contained__2JisA mobileHeader_langButton__YkCt_">日本語</button><button class="BaseButton_root__SFmw5 BaseButton_contained__2JisA mobileHeader_langButton__YkCt_">한국어</button><button class="BaseButton_root__SFmw5 BaseButton_contained__2JisA mobileHeader_langButton__YkCt_">Español</button><button class="BaseButton_root__SFmw5 BaseButton_contained__2JisA mobileHeader_langButton__YkCt_">Français</button><button class="BaseButton_root__SFmw5 BaseButton_contained__2JisA mobileHeader_langButton__YkCt_">Deutsch</button><button class="BaseButton_root__SFmw5 BaseButton_contained__2JisA mobileHeader_langButton__YkCt_">Italiano</button><button class="BaseButton_root__SFmw5 BaseButton_contained__2JisA mobileHeader_langButton__YkCt_">Português</button><button class="BaseButton_root__SFmw5 BaseButton_contained__2JisA mobileHeader_langButton__YkCt_">Русский</button></div></div><svg width="24" height="24" viewBox="0 0 24 24"><rect x="2" y="5" width="20" height="2" fill="black"></rect><rect x="2" y="11" width="20" height="2" fill="black"></rect><rect x="2" y="17" width="20" height="2" fill="black"></rect></svg></div></div></div></header><main class="blog_blogPageContainer__laO9w"><section class="globalPageHeader_headerContainer__prKdy globalPageHeader_lightMode__mxx5o globalPageHeader_centerLayout__3x4Xd"><div class="globalPageHeader_centerLayoutContent__ymQSe"><h1 class="globalPageHeader_title__wEJ6h globalPageHeader_lightModeTitle__r5k74">Vector Database Stories</h1><p class="globalPageHeader_desc__zcPFG globalPageHeader_lightModeDesc__pZnH3">From company news to technical tutorials – explore the most popular content on the Zilliz blog.</p><div class="globalPageHeader_headBgPart__a9vJY"></div><div class="globalPageHeader_headBgPart__a9vJY"></div></div></section><div class="page_container__IibMw blog_storiesWrapper__Oxa3R"><div class="blog_tabRowWrapper__DN_wD"><div class="globalSearchInput_searchBar__wE8G3 blog_searchBarRoot__9N6Nd"><input type="text" placeholder="Search anything about vector databases" value=""/><button class="globalSearchInput_iconWrapper__RmhgD"><svg width="14" height="14" viewBox="0 0 14 14" fill="none" xmlns="http://www.w3.org/2000/svg"><rect width="14" height="14" fill="white"></rect><path d="M6.08871 10.1774C8.34684 10.1774 10.1774 8.34684 10.1774 6.08871C10.1774 3.83058 8.34684 2 6.08871 2C3.83058 2 2 3.83058 2 6.08871C2 8.34684 3.83058 10.1774 6.08871 10.1774Z" stroke="#647489" stroke-linecap="round" stroke-linejoin="round"></path><path d="M11.3969 12.102L11.7504 12.4556L12.4575 11.7485L12.104 11.3949L11.3969 12.102ZM9.90238 9.19332L9.54883 8.83977L8.84172 9.54688L9.19527 9.90043L9.90238 9.19332ZM12.104 11.3949L9.90238 9.19332L9.19527 9.90043L11.3969 12.102L12.104 11.3949Z" fill="#647489"></path></svg></button></div><div><div class="globalTabFilter_tabContainer__R7CgF"><div class="globalTabFilter_tabsWrapper__l2_Ui globalTabFilter_horizontalTabs__F3ssy"><a class="globalTabFilter_tabItem__F_Hsm tab-item globalTabFilter_horizontalTabItem__aB3GF globalTabFilter_horizontalActiveItem__km_X9 " href="/blog?tag=-1">All</a><a class="globalTabFilter_tabItem__F_Hsm tab-item globalTabFilter_horizontalTabItem__aB3GF" href="/blog?tag=39">VectorDB 101</a><a class="globalTabFilter_tabItem__F_Hsm tab-item globalTabFilter_horizontalTabItem__aB3GF" href="/blog?tag=72">Community</a><a class="globalTabFilter_tabItem__F_Hsm tab-item globalTabFilter_horizontalTabItem__aB3GF" href="/blog?tag=5">Engineering</a><a class="globalTabFilter_tabItem__F_Hsm tab-item globalTabFilter_horizontalTabItem__aB3GF" href="/blog?tag=4">Company</a><a class="globalTabFilter_tabItem__F_Hsm tab-item globalTabFilter_horizontalTabItem__aB3GF" href="/blog?tag=2">Product</a><a class="globalTabFilter_tabItem__F_Hsm tab-item globalTabFilter_horizontalTabItem__aB3GF" href="/blog?tag=1">Case Study</a><a class="globalTabFilter_tabItem__F_Hsm tab-item globalTabFilter_horizontalTabItem__aB3GF" href="/blog?tag=73">Paper Reading</a></div></div></div></div><div class="blog_blogsWrapper___rxux"><a class="blogCard_blogCardWrapper__e3RHx blog_customRootClass__tVmIQ" href="/blog/expanding-our-global-reach-zilliz-cloud-launches-in-azure-central-india"><span class="blogCard_coverWrapper__TgiXF blog_customCoverClass__aLy8o"><img src="https://assets.zilliz.com/india_cover_c05a1e649d.jpeg" alt="Expanding Our Global Reach: Zilliz Cloud Launches in Azure Central India"/></span><div class="blogCard_contentWrapper__PjBcf"><div class="blogCard_contentBox__7EnV8"><p class="blogCard_tag__0QSND">Product</p><p class="blogCard_title__4hrD5">Expanding Our Global Reach: Zilliz Cloud Launches in Azure Central India</p><p class="blogCard_subTitle__PU2nS">Zilliz Cloud now operates in Azure Central India, offering AI and vector workloads with reduced latency, enhanced data sovereignty, and cost efficiency, empowering businesses to scale AI applications seamlessly in India. Ask ChatGPT </p></div><div class="blogCard_bottomBlock__VjEpS"><span class="blogCard_displayTime__9T2Ii">Jul 15, 2025</span><span class="blogCard_readTime__dimU7">4<!-- --> min read</span></div></div></a><a class="blogCard_blogCardWrapper__e3RHx blog_customRootClass__tVmIQ" href="/blog/vdbbench-1-0-benchmarking-with-your-real-world-production-workloads"><span class="blogCard_coverWrapper__TgiXF blog_customCoverClass__aLy8o"><img src="https://assets.zilliz.com/20250704_193742_feaa43d666.jpeg" alt="Announcing VDBBench 1.0: Open-Source VectorDB Benchmarking with Your Real-World Production Workloads"/></span><div class="blogCard_contentWrapper__PjBcf"><div class="blogCard_contentBox__7EnV8"><p class="blogCard_tag__0QSND">Product</p><p class="blogCard_title__4hrD5">Announcing VDBBench 1.0: Open-Source VectorDB Benchmarking with Your Real-World Production Workloads</p><p class="blogCard_subTitle__PU2nS">VDBBench 1.0 offers an open-source benchmarking solution for vector databases, emphasizing real-world production conditions, including streaming data and concurrent workloads. </p></div><div class="blogCard_bottomBlock__VjEpS"><span class="blogCard_displayTime__9T2Ii">Jul 04, 2025</span><span class="blogCard_readTime__dimU7">9<!-- --> min read</span></div></div></a><a class="blogCard_blogCardWrapper__e3RHx blog_customRootClass__tVmIQ" href="/blog/introducing-zilliz-mcp-server"><span class="blogCard_coverWrapper__TgiXF blog_customCoverClass__aLy8o"><img src="https://assets.zilliz.com/Introducing_Zilliz_MCP_Server_Natural_Language_Access_to_Your_Vector_Database_beae36f92f.png" alt="Introducing Zilliz MCP Server: Natural Language Access to Your Vector Database"/></span><div class="blogCard_contentWrapper__PjBcf"><div class="blogCard_contentBox__7EnV8"><p class="blogCard_tag__0QSND">Product</p><p class="blogCard_title__4hrD5">Introducing Zilliz MCP Server: Natural Language Access to Your Vector Database</p><p class="blogCard_subTitle__PU2nS">The Zilliz MCP Server enables developers to manage vector databases using natural language, simplifying database operations and AI workflows.</p></div><div class="blogCard_bottomBlock__VjEpS"><span class="blogCard_displayTime__9T2Ii">Jul 03, 2025</span><span class="blogCard_readTime__dimU7">5<!-- --> min read</span></div></div></a><a class="blogCard_blogCardWrapper__e3RHx blog_customRootClass__tVmIQ" href="/blog/zilliz-named-highest-performer-and-easiest-to-use-in-g2-summer-2025"><span class="blogCard_coverWrapper__TgiXF blog_customCoverClass__aLy8o"><img src="https://assets.zilliz.com/20250703_125604_1af4abe7ad.png" alt="Zilliz Named &quot;Highest Performer&quot; and &quot;Easiest to Use&quot; in G2&#x27;s Summer 2025 Grid® Report for Vector Databases"/></span><div class="blogCard_contentWrapper__PjBcf"><div class="blogCard_contentBox__7EnV8"><p class="blogCard_tag__0QSND">Company</p><p class="blogCard_title__4hrD5">Zilliz Named "Highest Performer" and "Easiest to Use" in G2's Summer 2025 Grid® Report for Vector Databases</p><p class="blogCard_subTitle__PU2nS">This dual recognition shows that Zilliz solved a challenge that has long defined the database industry—delivering enterprise-grade performance without the complexity typically associated with it.</p></div><div class="blogCard_bottomBlock__VjEpS"><span class="blogCard_displayTime__9T2Ii">Jul 02, 2025</span><span class="blogCard_readTime__dimU7">3<!-- --> min read</span></div></div></a><a class="blogCard_blogCardWrapper__e3RHx blog_customRootClass__tVmIQ" href="/blog/journey-to-35k-github-stars-story-of-building-milvus-from-scratch"><span class="blogCard_coverWrapper__TgiXF blog_customCoverClass__aLy8o"><img src="https://assets.zilliz.com/Github_star_30_K_1_4fc1f3ca73.png" alt="Our Journey to 35K+ GitHub Stars: The Real Story of Building Milvus from Scratch "/></span><div class="blogCard_contentWrapper__PjBcf"><div class="blogCard_contentBox__7EnV8"><p class="blogCard_tag__0QSND">Product</p><p class="blogCard_title__4hrD5">Our Journey to 35K+ GitHub Stars: The Real Story of Building Milvus from Scratch </p><p class="blogCard_subTitle__PU2nS">Join us in celebrating Milvus, the vector database that hit 35.5K stars on GitHub. Discover our story and how we’re making AI solutions easier for developers.</p></div><div class="blogCard_bottomBlock__VjEpS"><span class="blogCard_displayTime__9T2Ii">Jun 27, 2025</span><span class="blogCard_readTime__dimU7">10<!-- --> min read</span></div></div></a><a class="blogCard_blogCardWrapper__e3RHx blog_customRootClass__tVmIQ" href="/blog/why-not-all-vectordbs-are-agent-ready"><span class="blogCard_coverWrapper__TgiXF blog_customCoverClass__aLy8o"><img src="https://assets.zilliz.com/Chat_GPT_Image_Jun_20_2025_02_53_26_PM_5809db39f2.png" alt="Why Not All VectorDBs Are Agent-Ready"/></span><div class="blogCard_contentWrapper__PjBcf"><div class="blogCard_contentBox__7EnV8"><p class="blogCard_tag__0QSND">Community</p><p class="blogCard_title__4hrD5">Why Not All VectorDBs Are Agent-Ready</p><p class="blogCard_subTitle__PU2nS">Explore why choosing the right vector database is critical for scaling AI agents, and why traditional solutions fall short in production.</p></div><div class="blogCard_bottomBlock__VjEpS"><span class="blogCard_displayTime__9T2Ii">Jun 20, 2025</span><span class="blogCard_readTime__dimU7">7<!-- --> min read</span></div></div></a><a class="blogCard_blogCardWrapper__e3RHx blog_customRootClass__tVmIQ" href="/blog/creating-collections-in-zilliz-cloud-just-got-way-easier"><span class="blogCard_coverWrapper__TgiXF blog_customCoverClass__aLy8o"><img src="https://assets.zilliz.com/Creating_Collections_in_Zilliz_Cloud_Just_Got_Way_Easier_1_13e7f06af4.png" alt="Creating Collections in Zilliz Cloud Just Got Way Easier"/></span><div class="blogCard_contentWrapper__PjBcf"><div class="blogCard_contentBox__7EnV8"><p class="blogCard_tag__0QSND">Product</p><p class="blogCard_title__4hrD5">Creating Collections in Zilliz Cloud Just Got Way Easier</p><p class="blogCard_subTitle__PU2nS">We've enhanced the entire collection creation experience to bring advanced capabilities directly into the interface, making it faster and easier to build production-ready schemas without switching tools.</p></div><div class="blogCard_bottomBlock__VjEpS"><span class="blogCard_displayTime__9T2Ii">Jun 20, 2025</span><span class="blogCard_readTime__dimU7">6<!-- --> min read</span></div></div></a><a class="blogCard_blogCardWrapper__e3RHx blog_customRootClass__tVmIQ" href="/blog/announcing-the-general-availability-of-zilliz-cloud-byoc-on-google-cloud-platform"><span class="blogCard_coverWrapper__TgiXF blog_customCoverClass__aLy8o"><img src="https://assets.zilliz.com/Announcing_the_General_Availability_of_Zilliz_Cloud_BYOC_on_Google_Cloud_Platform_77bad32d0b.png" alt="Announcing the General Availability of Zilliz Cloud BYOC on Google Cloud Platform"/></span><div class="blogCard_contentWrapper__PjBcf"><div class="blogCard_contentBox__7EnV8"><p class="blogCard_tag__0QSND">Product</p><p class="blogCard_title__4hrD5">Announcing the General Availability of Zilliz Cloud BYOC on Google Cloud Platform</p><p class="blogCard_subTitle__PU2nS">Zilliz Cloud BYOC on GCP offers enterprise vector search with full data sovereignty and seamless integration.</p></div><div class="blogCard_bottomBlock__VjEpS"><span class="blogCard_displayTime__9T2Ii">Jun 19, 2025</span><span class="blogCard_readTime__dimU7">3<!-- --> min read</span></div></div></a><a class="blogCard_blogCardWrapper__e3RHx blog_customRootClass__tVmIQ" href="/blog/why-ai-agent-startups-should-build-scalable-infrastructure-early"><span class="blogCard_coverWrapper__TgiXF blog_customCoverClass__aLy8o"><img src="https://assets.zilliz.com/Why_AI_Agent_Startups_Should_Build_Scalable_Infrastructure_Early_cd5c3c7a98.png" alt="Build for the Boom: Why AI Agent Startups Should Build Scalable Infrastructure Early"/></span><div class="blogCard_contentWrapper__PjBcf"><div class="blogCard_contentBox__7EnV8"><p class="blogCard_tag__0QSND">Engineering</p><p class="blogCard_title__4hrD5">Build for the Boom: Why AI Agent Startups Should Build Scalable Infrastructure Early</p><p class="blogCard_subTitle__PU2nS">Explore strategies for developing AI agents that can handle rapid growth. Don't let inadequate systems undermine your success during critical breakthrough moments.</p></div><div class="blogCard_bottomBlock__VjEpS"><span class="blogCard_displayTime__9T2Ii">Jun 16, 2025</span><span class="blogCard_readTime__dimU7">7<!-- --> min read</span></div></div></a></div></div><ul class="rc-pagination globalPagination_pagination__e3sGA"><li title="Previous Page" class="rc-pagination-prev rc-pagination-disabled" aria-disabled="true"><span class="globalPagination_prevIcon__2xF6T" disabled=""><svg width="14" height="14" viewBox="0 0 14 14"><path d="M4.57574 2.42426L4.15147 2L5 1.15147L5.42426 1.57574L4.57574 2.42426ZM5.42426 12.4243L5 12.8485L4.15147 12L4.57574 11.5757L5.42426 12.4243ZM10 7L10.4243 6.57574L10.8485 7L10.4243 7.42426L10 7ZM4.57574 11.5757L9.57574 6.57574L10.4243 7.42426L5.42426 12.4243L4.57574 11.5757ZM9.57574 7.42426L4.57574 2.42426L5.42426 1.57574L10.4243 6.57574L9.57574 7.42426Z"></path></svg></span></li><li title="1" class="rc-pagination-item rc-pagination-item-1 rc-pagination-item-active" tabindex="0"><a rel="nofollow">1</a></li><li title="2" class="rc-pagination-item rc-pagination-item-2" tabindex="0"><a rel="nofollow">2</a></li><li title="3" class="rc-pagination-item rc-pagination-item-3 rc-pagination-item-before-jump-next" tabindex="0"><a rel="nofollow">3</a></li><li title="Next 3 Page" tabindex="0" class="rc-pagination-jump-next rc-pagination-jump-next-custom-icon"><span class="globalPagination_jumpIcon__uBClN">...</span></li><li title="73" class="rc-pagination-item rc-pagination-item-73" tabindex="0"><a rel="nofollow">73</a></li><li title="Next Page" tabindex="0" class="rc-pagination-next" aria-disabled="false"><span class="globalPagination_nextIcon__SiYty"><svg width="14" height="14" viewBox="0 0 14 14"><path d="M4.57574 2.42426L4.15147 2L5 1.15147L5.42426 1.57574L4.57574 2.42426ZM5.42426 12.4243L5 12.8485L4.15147 12L4.57574 11.5757L5.42426 12.4243ZM10 7L10.4243 6.57574L10.8485 7L10.4243 7.42426L10 7ZM4.57574 11.5757L9.57574 6.57574L10.4243 7.42426L5.42426 12.4243L4.57574 11.5757ZM9.57574 7.42426L4.57574 2.42426L5.42426 1.57574L10.4243 6.57574L9.57574 7.42426Z"></path></svg></span></li></ul></main><footer class="footer_footerContainer__nClkK"><div class="page_container__IibMw"><section class="footer_navsWrapper__d8Hxa"><div class="footer_subscribePart__bj0xX"><div class="footer_socialMediaWrapper__v0YIi"><img src="/images/home/homepage-footer-logo.svg" alt="Zilliz Logo"/><div class="footer_socialMediaIcons__xqbMo"><a rel="noopener noreferrer" target="_blank" title="Youtube" class="footer_linkButton__e7vEY" href="https://www.youtube.com/c/MilvusVectorDatabase"><svg width="24" height="24" viewBox="0 0 24 24" fill="none"><path fill-rule="evenodd" clip-rule="evenodd" d="M20.184 4.13849C21.6225 4.21949 22.329 4.43249 22.98 5.59049C23.658 6.74699 24 8.73899 24 12.2475V12.252V12.2595C24 15.7515 23.658 17.7585 22.9815 18.903C22.3305 20.061 21.624 20.271 20.1855 20.3685C18.747 20.451 15.1335 20.5005 12.003 20.5005C8.8665 20.5005 5.2515 20.451 3.8145 20.367C2.379 20.2695 1.6725 20.0595 1.0155 18.9015C0.345 17.757 0 15.75 0 12.258V12.255V12.2505V12.246C0 8.73899 0.345 6.74699 1.0155 5.59049C1.6725 4.43099 2.3805 4.21949 3.816 4.13699C5.2515 4.04099 8.8665 4.00049 12.003 4.00049C15.1335 4.00049 18.747 4.04099 20.184 4.13849ZM16.5 12.2505L9 7.75049V16.7505L16.5 12.2505Z" fill="black"></path></svg></a><a rel="noopener noreferrer" target="_blank" title="LinkedIn" class="footer_linkButton__e7vEY" href="https://www.linkedin.com/company/zilliz"><svg width="24" height="24" viewBox="0 0 24 24" fill="none"><path fill-rule="evenodd" clip-rule="evenodd" d="M5.8125 2.40625C5.8125 3.73519 4.73519 4.8125 3.40625 4.8125C2.07731 4.8125 1 3.73519 1 2.40625C1 1.07731 2.07731 0 3.40625 0C4.73519 0 5.8125 1.07731 5.8125 2.40625ZM1 6.875H5.91975V22H1V6.875ZM19.3205 7.05237C19.3031 7.04688 19.286 7.04122 19.2689 7.03557L19.2688 7.03556C19.2346 7.02426 19.2004 7.01296 19.1637 7.00287C19.0977 6.98775 19.0317 6.97538 18.9644 6.96438C18.7031 6.91213 18.4171 6.875 18.0816 6.875C15.2134 6.875 13.3942 8.96088 12.7948 9.76663V6.875H7.875V22H12.7948V13.75C12.7948 13.75 16.5127 8.57175 18.0816 12.375V22H23V11.7934C23 9.50813 21.4339 7.60375 19.3205 7.05237Z" fill="black"></path></svg></a><a rel="noopener noreferrer" target="_blank" title="Twitter" class="footer_linkButton__e7vEY" href="https://twitter.com/zilliz_universe"><svg height="24" width="24" viewBox="0 0 24 24" fill="none" xmlns="http://www.w3.org/2000/svg"><path d="M18.244 2.25h3.308l-7.227 8.26 8.502 11.24H16.17l-5.214-6.817L4.99 21.75H1.68l7.73-8.835L1.254 2.25H8.08l4.713 6.231zm-1.161 17.52h1.833L7.084 4.126H5.117z" fill="black"></path></svg></a><a rel="noopener noreferrer" target="_blank" title="GitHub" class="footer_linkButton__e7vEY" href="https://github.com/zilliztech"><svg width="24" height="24" viewBox="0 0 24 24" fill="none"><path fill-rule="evenodd" clip-rule="evenodd" d="M12.3036 1C6.0724 1 1.02539 6.04701 1.02539 12.2782C1.02539 17.2688 4.25378 21.4841 8.73688 22.9785C9.30079 23.0771 9.51226 22.7388 9.51226 22.4427C9.51226 22.1749 9.49816 21.2867 9.49816 20.3422C6.66451 20.8638 5.93142 19.6514 5.70586 19.017C5.57898 18.6927 5.02916 17.6918 4.54984 17.4239C4.1551 17.2125 3.59119 16.6908 4.53574 16.6767C5.4239 16.6626 6.0583 17.4944 6.26977 17.8328C7.28481 19.5386 8.90606 19.0593 9.55455 18.7632C9.65324 18.0301 9.94929 17.5367 10.2735 17.2548C7.76413 16.9728 5.14195 16 5.14195 11.6861C5.14195 10.4596 5.57898 9.44458 6.29796 8.6551C6.18518 8.37314 5.79044 7.21713 6.41075 5.66637C6.41075 5.66637 7.3553 5.37031 9.51226 6.82239C10.4145 6.56863 11.3732 6.44175 12.3318 6.44175C13.2905 6.44175 14.2491 6.56863 15.1514 6.82239C17.3083 5.35622 18.2529 5.66637 18.2529 5.66637C18.8732 7.21713 18.4785 8.37314 18.3657 8.6551C19.0847 9.44458 19.5217 10.4455 19.5217 11.6861C19.5217 16.0141 16.8854 16.9728 14.376 17.2548C14.7848 17.6072 15.1373 18.2839 15.1373 19.3412C15.1373 20.8497 15.1232 22.0621 15.1232 22.4427C15.1232 22.7388 15.3346 23.0912 15.8986 22.9785C20.3535 21.4841 23.5819 17.2548 23.5819 12.2782C23.5819 6.04701 18.5348 1 12.3036 1V1Z" fill="black"></path></svg></a><a rel="noopener noreferrer" target="_blank" title="Discord" class="footer_linkButton__e7vEY" href="https://discord.com/invite/8uyFbECzPX"><svg width="24" height="24" viewBox="0 0 24 24" fill="none" xmlns="http://www.w3.org/2000/svg"><path d="M20.3303 4.19247C18.7767 3.45861 17.1156 2.92527 15.3789 2.62158C15.1656 3.0109 14.9164 3.53454 14.7446 3.9511C12.8985 3.67079 11.0693 3.67079 9.25714 3.9511C9.08537 3.53454 8.83053 3.0109 8.61534 2.62158C6.87679 2.92527 5.21374 3.46057 3.66017 4.19636C0.526624 8.9771 -0.32283 13.6391 0.101898 18.2349C2.18023 19.8019 4.19439 20.7537 6.17456 21.3766C6.66347 20.6973 7.09951 19.9751 7.47516 19.214C6.75973 18.9395 6.07451 18.6008 5.42705 18.2076C5.59882 18.0792 5.76684 17.9448 5.92916 17.8066C9.87818 19.6714 14.1689 19.6714 18.0707 17.8066C18.2349 17.9448 18.4029 18.0792 18.5728 18.2076C17.9235 18.6028 17.2364 18.9415 16.5209 19.216C16.8966 19.9751 17.3307 20.6992 17.8215 21.3786C19.8036 20.7557 21.8196 19.8038 23.898 18.2349C24.3963 12.9072 23.0466 8.28801 20.3303 4.19247ZM8.01316 15.4085C6.8277 15.4085 5.85553 14.2912 5.85553 12.9305C5.85553 11.5699 6.80694 10.4506 8.01316 10.4506C9.2194 10.4506 10.1915 11.5679 10.1708 12.9305C10.1727 14.2912 9.2194 15.4085 8.01316 15.4085ZM15.9867 15.4085C14.8013 15.4085 13.8291 14.2912 13.8291 12.9305C13.8291 11.5699 14.7805 10.4506 15.9867 10.4506C17.1929 10.4506 18.1651 11.5679 18.1443 12.9305C18.1443 14.2912 17.1929 15.4085 15.9867 15.4085Z" fill="black"></path></svg></a><a rel="noopener noreferrer" target="_blank" title="G2" class="footer_linkButton__e7vEY" href="https://www.g2.com/products/zilliz/reviews"><svg width="24" height="25" viewBox="0 0 24 25" fill="none" xmlns="http://www.w3.org/2000/svg"><g id="Icon/Social/Instagram Copy 6"><g id="Layer 1"><path id="Vector" d="M15.708 16.8491C16.4437 18.1257 17.1712 19.3879 17.8981 20.6487C14.6791 23.1131 9.67095 23.4109 5.96349 20.5729C1.69701 17.3044 0.995778 11.7274 3.27998 7.71278C5.90715 3.09514 10.8234 2.07392 13.9888 2.82274C13.9032 3.00872 12.0074 6.9418 12.0074 6.9418C12.0074 6.9418 11.8575 6.95165 11.7727 6.95329C10.8371 6.99295 10.1403 7.21065 9.39335 7.59682C8.57389 8.02442 7.87164 8.64623 7.34797 9.40789C6.8243 10.1696 6.49516 11.0479 6.38932 11.9661C6.27888 12.8973 6.40764 13.8414 6.76345 14.709C7.06429 15.4425 7.48985 16.0939 8.06035 16.6439C8.93553 17.4885 9.97698 18.0114 11.1842 18.1845C12.3274 18.3486 13.4268 18.1862 14.4571 17.6684C14.8435 17.4745 15.1722 17.2604 15.5565 16.9667C15.6055 16.9349 15.6489 16.8947 15.708 16.8491Z" fill="black"></path><path id="Vector_2" d="M15.715 5.65256C15.5282 5.46878 15.3551 5.29921 15.1828 5.12855C15.0799 5.02681 14.9809 4.92097 14.8756 4.82169C14.8379 4.78587 14.7936 4.73691 14.7936 4.73691C14.7936 4.73691 14.8294 4.66088 14.8447 4.6297C15.0463 4.22521 15.3622 3.92956 15.7369 3.69436C16.1512 3.4323 16.6339 3.29896 17.124 3.3112C17.7511 3.32351 18.3342 3.47967 18.8262 3.9003C19.1894 4.21071 19.3757 4.60454 19.4085 5.07468C19.4632 5.8678 19.135 6.47523 18.4833 6.89914C18.1004 7.14857 17.6874 7.34138 17.2733 7.56974C17.045 7.69582 16.8497 7.80659 16.6265 8.03468C16.4302 8.26359 16.4206 8.47938 16.4206 8.47938L19.3872 8.47555V9.79679H14.8081C14.8081 9.79679 14.8081 9.70654 14.8081 9.66907C14.7906 9.0198 14.8663 8.40882 15.1636 7.81917C15.4371 7.2782 15.8621 6.88218 16.3727 6.57724C16.766 6.34231 17.1801 6.14239 17.5742 5.90855C17.8173 5.76442 17.9891 5.55301 17.9877 5.24643C17.9877 4.98333 17.7962 4.74949 17.5228 4.67647C16.8779 4.50253 16.2215 4.78012 15.8802 5.37032C15.8304 5.45647 15.7795 5.54207 15.715 5.65256Z" fill="black"></path><path id="Vector_3" d="M21.4533 15.4447L18.9533 11.1273H14.0061L11.49 15.4892H16.4736L18.9328 19.7861L21.4533 15.4447Z" fill="black"></path></g></g></svg></a><a rel="noopener noreferrer" target="_blank" title="Bluesky" class="footer_linkButton__e7vEY" href="https://bsky.app/profile/zilliz-universe.bsky.social"><svg width="24" height="24" viewBox="0 0 24 24" fill="none" xmlns="http://www.w3.org/2000/svg"><g id="Icon/Social/Instagram Copy 7"><path id="Vector" d="M5.76879 3.30387C8.29104 5.19742 11.004 9.03674 12.0001 11.0971C12.9962 9.03689 15.709 5.19738 18.2313 3.30387C20.0513 1.93757 23 0.8804 23 4.24437C23 4.9162 22.6148 9.8881 22.3889 10.6953C21.6036 13.5015 18.7421 14.2173 16.1967 13.7841C20.646 14.5413 21.7778 17.0496 19.3335 19.5579C14.6911 24.3216 12.661 18.3627 12.1406 16.8358C12.0453 16.5559 12.0007 16.4249 12 16.5363C11.9993 16.4249 11.9547 16.5559 11.8594 16.8358C11.3392 18.3627 9.30916 24.3218 4.66654 19.5579C2.22213 17.0496 3.35395 14.5412 7.80331 13.7841C5.25785 14.2173 2.39627 13.5015 1.6111 10.6953C1.38518 9.88802 1 4.91612 1 4.24437C1 0.8804 3.94882 1.93757 5.76866 3.30387H5.76879Z" fill="black"></path></g></svg></a></div></div><div class="subscribeFooter_container__V07MM footer_subscribeRoot__ni93s"><strong class="subscribeFooter_title__LHQsP">Sign up for the Zilliz newsletter</strong><div class="subscribeFooter_inputContainer__tnxFu"><input class="subscribeFooter_inputEle__oP0t0" placeholder="Email address" value=""/><button class="BaseButton_root__SFmw5 BaseButton_contained__2JisA subscribeFooter_btn__Hk7zt" style="cursor:pointer">Subscribe</button></div><p class="subscribeFooter_address__cI4er">201 Redwood Shores Pkwy, Suite 330 Redwood City, California 94065</p></div></div><ul class="footer_navs__0biPd"><li class="footer_navColumn__kADYe"><h5 class="footer_cat___oPg7">Products</h5><ul><li class="footer_titleGroup__v56YT"><a title="Zilliz Cloud" target="_self" class="footer_linkButton__e7vEY" href="/cloud">Zilliz Cloud</a></li><li class="footer_titleGroup__v56YT"><a title="Zilliz Cloud BYOC" target="_self" class="footer_linkButton__e7vEY" href="/bring-your-own-cloud">Zilliz Cloud BYOC</a></li><li class="footer_titleGroup__v56YT"><a title="Zilliz Cloud Free Tier" target="_self" class="footer_linkButton__e7vEY" href="/zilliz-cloud-free-tier">Zilliz Cloud Free Tier</a></li><li class="footer_titleGroup__v56YT"><a title="ZIlliz Migration Service" target="_self" class="footer_linkButton__e7vEY" href="/zilliz-migration-service">ZIlliz Migration Service</a></li><li class="footer_titleGroup__v56YT"><a title="Milvus" target="_self" class="footer_linkButton__e7vEY" href="/what-is-milvus">Milvus</a></li><li class="footer_titleGroup__v56YT"><a rel="noopener noreferrer" target="_blank" title="DeepSearcher" class="footer_linkButton__e7vEY" href="https://github.com/zilliztech/deep-searcher">DeepSearcher<svg width="12" height="12" viewBox="0 0 12 12" fill="none" xmlns="http://www.w3.org/2000/svg"><path d="M7.86391 4L2.70712 4L2.70712 3L9.57108 3V9.86396L8.57108 9.86396L8.57108 4.70704L2.70712 10.571L2.00002 9.86389L7.86391 4Z" fill="black"></path></svg></a></li><li class="footer_titleGroup__v56YT"><a title="GPTCache" target="_self" class="footer_linkButton__e7vEY" href="/what-is-gptcache">GPTCache</a></li><li class="footer_titleGroup__v56YT"><a title="Attu" target="_self" class="footer_linkButton__e7vEY" href="/attu">Attu</a></li><li class="footer_titleGroup__v56YT"><a rel="noopener noreferrer" target="_blank" title="Milvus CLI" class="footer_linkButton__e7vEY" href="https://github.com/zilliztech/milvus_cli">Milvus CLI<svg width="12" height="12" viewBox="0 0 12 12" fill="none" xmlns="http://www.w3.org/2000/svg"><path d="M7.86391 4L2.70712 4L2.70712 3L9.57108 3V9.86396L8.57108 9.86396L8.57108 4.70704L2.70712 10.571L2.00002 9.86389L7.86391 4Z" fill="black"></path></svg></a></li><li class="footer_titleGroup__v56YT"><a title="Vector Transport Service" target="_self" class="footer_linkButton__e7vEY" href="/vector-transport-service">Vector Transport Service</a></li></ul></li><li class="footer_navColumn__kADYe"><h5 class="footer_cat___oPg7">Developers</h5><ul><li class="footer_titleGroup__v56YT"><a rel="noopener noreferrer" target="_blank" title="Documentation" class="footer_linkButton__e7vEY" href="https://docs.zilliz.com/docs/home">Documentation<svg width="12" height="12" viewBox="0 0 12 12" fill="none" xmlns="http://www.w3.org/2000/svg"><path d="M7.86391 4L2.70712 4L2.70712 3L9.57108 3V9.86396L8.57108 9.86396L8.57108 4.70704L2.70712 10.571L2.00002 9.86389L7.86391 4Z" fill="black"></path></svg></a></li><li class="footer_titleGroup__v56YT"><a title="Open-Source Projects" target="_self" class="footer_linkButton__e7vEY" href="/product/open-source-vector-database">Open-Source Projects</a></li><li class="footer_titleGroup__v56YT"><a rel="noopener noreferrer" target="_self" title="VectorDB Benchmark" class="footer_linkButton__e7vEY" href="/vector-database-benchmark-tool">VectorDB Benchmark</a></li><li class="footer_titleGroup__v56YT"><a title="Free RAG Cost Calculator" target="_self" class="footer_linkButton__e7vEY" href="/rag-cost-calculator">Free RAG Cost Calculator</a></li><li class="footer_titleGroup__v56YT"><a title="RAG Tutorials" target="_self" class="footer_linkButton__e7vEY" href="/tutorials/rag">RAG Tutorials</a></li><li class="footer_titleGroup__v56YT"><a title="Milvus Notebooks" target="_self" class="footer_linkButton__e7vEY" href="/learn/milvus-notebooks">Milvus Notebooks</a></li></ul></li><li class="footer_navColumn__kADYe"><h5 class="footer_cat___oPg7">Resources</h5><ul><li class="footer_titleGroup__v56YT"><a title="Blog" target="_self" class="footer_linkButton__e7vEY" href="/blog">Blog</a></li><li class="footer_titleGroup__v56YT"><a title="Learning Center" target="_self" class="footer_linkButton__e7vEY" href="/learn">Learning Center</a></li><li class="footer_titleGroup__v56YT"><a title="GenAI Resource Hub" target="_self" class="footer_linkButton__e7vEY" href="/learn/generative-ai">GenAI Resource Hub</a></li><li class="footer_titleGroup__v56YT"><a title="VectorDB Comparison" target="_self" class="footer_linkButton__e7vEY" href="/comparison">VectorDB Comparison</a></li><li class="footer_titleGroup__v56YT"><a title="Guides &amp; Whitepapers" target="_self" class="footer_linkButton__e7vEY" href="/resources">Guides &amp; Whitepapers</a></li><li class="footer_titleGroup__v56YT"><a title="Popular Embedding Models" target="_self" class="footer_linkButton__e7vEY" href="/ai-models">Popular Embedding Models</a></li><li class="footer_titleGroup__v56YT"><a title="Data Connectors" target="_self" class="footer_linkButton__e7vEY" href="/data-connectors">Data Connectors</a></li><li class="footer_titleGroup__v56YT"><a title="Glossary" target="_self" class="footer_linkButton__e7vEY" href="/glossary">Glossary</a></li><li class="footer_titleGroup__v56YT"><a title="What is RAG?" target="_self" class="footer_linkButton__e7vEY" href="/learn/Retrieval-Augmented-Generation">What is RAG?</a></li><li class="footer_titleGroup__v56YT"><a title="What is a Vector Database?" target="_self" class="footer_linkButton__e7vEY" href="/learn/what-is-vector-database">What is a Vector Database?</a></li><li class="footer_titleGroup__v56YT"><a title="Trust Center" target="_self" class="footer_linkButton__e7vEY" href="/trust-center">Trust Center</a></li><li class="footer_titleGroup__v56YT"><a title="AI Reference Guide" target="_self" class="footer_linkButton__e7vEY footer_faqEntry__udaD3" href="/ai-faq">AI Reference Guide</a></li></ul></li><li class="footer_navColumn__kADYe"><h5 class="footer_cat___oPg7">Company</h5><ul><li class="footer_titleGroup__v56YT"><a title="About" target="_self" class="footer_linkButton__e7vEY" href="/about">About</a></li><li class="footer_titleGroup__v56YT"><a title="Careers" target="_self" class="footer_linkButton__e7vEY" href="/careers">Careers</a><span class="footer_highlightItem__lwUcw"></span></li><li class="footer_titleGroup__v56YT"><a title="News" target="_self" class="footer_linkButton__e7vEY" href="/news">News</a></li><li class="footer_titleGroup__v56YT"><a title="Partners" target="_self" class="footer_linkButton__e7vEY" href="/partners">Partners</a></li><li class="footer_titleGroup__v56YT"><a title="Events" target="_self" class="footer_linkButton__e7vEY" href="/event">Events</a></li><li class="footer_titleGroup__v56YT"><a title="Contact Sales" target="_self" class="footer_linkButton__e7vEY" href="/contact-sales">Contact Sales</a></li><li class="footer_titleGroup__v56YT"><a title="Brand Assets" target="_self" class="footer_linkButton__e7vEY" href="/brand-assets">Brand Assets</a></li></ul></li></ul></section><div class="footer_bottom__0Qj7r"><div class="footer_leftPart__k5npK"><div><a href="/terms-and-conditions">Terms of Service</a><a href="/privacy-policy">Privacy Policy</a><a href="/security">Security</a><a rel="noopener noreferrer" target="_blank" href="https://status.zilliz.com/">System Status</a><button class="footer_cookieBtn__KJDjM">Cookie Settings</button><div class="footer_mark__p3pFH">LF AI, LF AI &amp; data, Milvus, and associated open-source project names are trademarks of the Linux Foundation.</div><div class="footer_copyright__AUuel">© Zilliz 2025 All rights reserved.</div></div></div><div class="footer_logoSection__gXPke"><img src="/images/layout/soc-logo.png" alt="aicpa"/><img src="/images/layout/iso-logo.png" alt="ISO"/></div></div></div></footer><div class="inkeep_inkeepChatButtonContainer__sEQtK"><div class="inkeep_inkeepButtonBgWrapper__Mqwne"><button class="inkeep_inkeepChatButton__q9V8P"><svg width="15" height="16" viewBox="0 0 15 16" fill="none" xmlns="http://www.w3.org/2000/svg"><path d="M4.06875 3.7094C4.37476 3.7094 4.64788 3.90089 4.7525 4.18846L7.66377 12.1945L7.68581 12.2655C7.77631 12.6232 7.58293 12.9981 7.22879 13.127C6.87469 13.2557 6.4852 13.093 6.3247 12.7609L6.29627 12.692L5.74259 11.1695H2.39491L1.84123 12.692C1.70382 13.0697 1.28644 13.2643 0.908711 13.127C0.531024 12.9896 0.336372 12.5722 0.473726 12.1945L3.385 4.18846L3.43191 4.0854C3.55849 3.8561 3.80098 3.7094 4.06875 3.7094ZM2.93296 9.68974L2.92443 9.7139H5.21307L5.20454 9.68974L4.06875 6.56595L2.93296 9.68974Z" fill="url(#paint0_linear_11477_442303)"></path><path d="M10.6191 12.4432V10.2598C10.6191 9.8578 10.945 9.53195 11.3469 9.53195C11.7489 9.53195 12.0747 9.8578 12.0747 10.2598V12.4432C12.0747 12.8452 11.7489 13.171 11.3469 13.171C10.945 13.171 10.6191 12.8452 10.6191 12.4432Z" fill="url(#paint1_linear_11477_442303)"></path><path d="M11.0201 2.37198C11.1338 2.11266 11.5601 2.11266 11.6738 2.37198C11.8986 2.88469 12.2258 3.5124 12.6127 3.89927C12.9996 4.28613 13.6273 4.61338 14.14 4.83817C14.3993 4.95185 14.3993 5.37821 14.14 5.4919C13.6273 5.71669 12.9996 6.04395 12.6127 6.43081C12.2258 6.81768 11.8986 7.44539 11.6738 7.95811C11.5601 8.21743 11.1338 8.21743 11.0201 7.95811C10.7953 7.4454 10.468 6.81768 10.0812 6.43081C9.69429 6.04395 9.06658 5.71669 8.55386 5.4919C8.29454 5.37821 8.29454 4.95186 8.55386 4.83817C9.06658 4.61338 9.69429 4.28613 10.0812 3.89927C10.468 3.5124 10.7953 2.88469 11.0201 2.37198Z" fill="url(#paint2_linear_11477_442303)"></path><defs><linearGradient id="paint0_linear_11477_442303" x1="0.429688" y1="2.33714" x2="10.9766" y2="9.53844" gradientUnits="userSpaceOnUse"><stop stop-color="#00EF8B"></stop><stop offset="0.505" stop-color="#0044E4"></stop><stop offset="1" stop-color="#CD3FFF"></stop></linearGradient><linearGradient id="paint1_linear_11477_442303" x1="0.429688" y1="2.33714" x2="10.9766" y2="9.53844" gradientUnits="userSpaceOnUse"><stop stop-color="#00EF8B"></stop><stop offset="0.505" stop-color="#0044E4"></stop><stop offset="1" stop-color="#CD3FFF"></stop></linearGradient><linearGradient id="paint2_linear_11477_442303" x1="0.429688" y1="2.33714" x2="10.9766" y2="9.53844" gradientUnits="userSpaceOnUse"><stop stop-color="#00EF8B"></stop><stop offset="0.505" stop-color="#0044E4"></stop><stop offset="1" stop-color="#CD3FFF"></stop></linearGradient></defs></svg>Ask AI</button></div></div><div class="inkeep_inkeepChatModalContainer__dB5kW inkeep_hiddenEle__sZZ1h"><div class="inkeep_inkeepChatModalContent___AcLJ"><div class="inkeep_inkeepChatModalHeader__Z5g4t"><h3 class="inkeep_inkeepChatModalTitle__RNvS2">AI Assistant</h3><button class="inkeep_inkeepChatModalCloseButton__DKIqe"><svg width="24" height="24" viewBox="0 0 24 24"><path d="M5 5L19 19" stroke="#1D2939" stroke-width="2"></path><path d="M19 5L5 19" stroke="#1D2939" stroke-width="2"></path></svg></button></div><div class="inkeep_chatModal__EZkCw"></div></div><div class="inkeep_closeButtonWrapper__Cw9No"><button class="inkeep_closeButton__tJl6d"><svg width="37" height="36" viewBox="0 0 37 36" fill="none" xmlns="http://www.w3.org/2000/svg"><circle cx="18.3965" cy="18" r="17.5" fill="white" stroke="#5D6D85"></circle><path d="M18.3975 0C28.3384 0.000263882 36.3975 8.05904 36.3975 18C36.3975 27.941 28.3384 35.9997 18.3975 36C8.45634 36 0.397461 27.9411 0.397461 18C0.397461 8.05887 8.45634 0 18.3975 0ZM18.3975 1.5C9.28476 1.5 1.89746 8.8873 1.89746 18C1.89746 27.1127 9.28476 34.5 18.3975 34.5C27.5099 34.4997 34.8975 27.1125 34.8975 18C34.8975 8.88746 27.5099 1.50026 18.3975 1.5ZM24.0732 15.248L24.9482 16.3174L25.1699 16.5879L24.8994 16.8096C24.4326 17.1915 22.8576 18.4233 21.4053 19.5547C20.678 20.1212 19.9794 20.6641 19.4629 21.0654C19.2046 21.2661 18.991 21.4318 18.8428 21.5469C18.7691 21.6041 18.7112 21.6491 18.6719 21.6797C18.6522 21.6949 18.6361 21.707 18.626 21.7148C18.6213 21.7185 18.6177 21.7217 18.6152 21.7236C18.6142 21.7244 18.6129 21.7251 18.6123 21.7256L18.6113 21.7266L18.3955 21.8936L18.1807 21.7256L11.8994 16.8145L11.6182 16.5938L11.8447 16.3174L12.7188 15.248L12.9404 14.9775L13.2119 15.1992L18.3965 19.4404L23.5811 15.1992L23.8516 14.9775L24.0732 15.248Z" fill="url(#paint0_linear_11620_448113)"></path><defs><linearGradient id="paint0_linear_11620_448113" x1="0.397461" y1="0.522786" x2="31.3993" y2="17.2587" gradientUnits="userSpaceOnUse"><stop stop-color="#00EF8B"></stop><stop offset="0.505" stop-color="#0044E4"></stop><stop offset="1" stop-color="#CD3FFF"></stop></linearGradient></defs></svg></button></div></div></div><script id="__NEXT_DATA__" type="application/json">{"props":{"pageProps":{"blogs":[{"id":"blog-1688","title":"Expanding Our Global Reach: Zilliz Cloud Launches in Azure Central India","image":{"id":6911,"url":"https://assets.zilliz.com/india_cover_c05a1e649d.jpeg"},"display_time":"Jul 15, 2025","deploy_time":null,"url":"expanding-our-global-reach-zilliz-cloud-launches-in-azure-central-india","abstract":"Zilliz Cloud now operates in Azure Central India, offering AI and vector workloads with reduced latency, enhanced data sovereignty, and cost efficiency, empowering businesses to scale AI applications seamlessly in India.\n\n\n\n\n\n\n\n\n\nAsk ChatGPT\n","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":36,"name":"Chris Churilo","author_tags":"VP of Marketing","published_at":"2023-04-11T16:51:05.002Z","created_by":18,"updated_by":53,"created_at":"2023-04-11T16:42:46.067Z","updated_at":"2025-01-16T22:35:53.011Z","home_page":"GitHub","home_page_link":"https://github.com/ChrisChurilo","self_intro":"Chris Churilo is the VP of Marketing \u0026 Community at Zilliz where she leads all community, developer relations, and marketing efforts. Prior to Zilliz, Chris was a founding member of the InfluxData’s go to market efforts and helped propel the time series database platform to dominance in the market. In earlier roles she defined and designed a SaaS monitoring solution at Centroid, and prior to that she was the VP of product management at iPass and was the LOB for several cloud services that required her to track the business and operational metrics and analytics to help identify and resolve issues.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":4,"localizations":[],"invisible":false,"backgroundImage":"https://assets.zilliz.com/india_cover_c05a1e649d.jpeg","belong":"blog","authorNames":["Chris Churilo"]},{"id":"blog-1701","title":"Announcing VDBBench 1.0: Open-Source VectorDB Benchmarking with Your Real-World Production Workloads","image":{"id":6880,"url":"https://assets.zilliz.com/20250704_193742_feaa43d666.jpeg"},"display_time":"Jul 04, 2025","deploy_time":null,"url":"vdbbench-1-0-benchmarking-with-your-real-world-production-workloads","abstract":"VDBBench 1.0 offers an open-source benchmarking solution for vector databases, emphasizing real-world production conditions, including streaming data and concurrent workloads. ","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":120,"name":"Min Tian","author_tags":"Software Engineer","published_at":"2024-03-16T05:39:39.262Z","created_by":18,"updated_by":18,"created_at":"2024-03-16T05:39:37.087Z","updated_at":"2024-07-18T16:00:37.188Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/min-tian-92b997237/","self_intro":"Software Engineer at Zilliz","repost_to_medium":null,"repost_state":null,"meta_description":"Min Tian, Software Engineer at Zilliz","locale":"en"}],"read_time":9,"localizations":[],"invisible":false,"backgroundImage":"https://assets.zilliz.com/20250704_193742_feaa43d666.jpeg","belong":"blog","authorNames":["Min Tian"]},{"id":"blog-1700","title":"Introducing Zilliz MCP Server: Natural Language Access to Your Vector Database","image":{"id":6877,"url":"https://assets.zilliz.com/Introducing_Zilliz_MCP_Server_Natural_Language_Access_to_Your_Vector_Database_beae36f92f.png"},"display_time":"Jul 03, 2025","deploy_time":null,"url":"introducing-zilliz-mcp-server","abstract":"The Zilliz MCP Server enables developers to manage vector databases using natural language, simplifying database operations and AI workflows.","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":45,"name":"Fendy Feng","author_tags":"Technical Marketing Writer","published_at":"2023-05-16T01:36:15.102Z","created_by":18,"updated_by":18,"created_at":"2023-05-16T00:04:12.065Z","updated_at":"2024-04-25T08:37:19.712Z","home_page":"GitHub","home_page_link":"https://www.linkedin.com/in/fendy311/","self_intro":"Fendy Feng is the Technical Marketing Writer at Zilliz. She has extensive experience developing and enhancing the impact of open-source projects in various global markets by producing high-quality, tailored content. Before joining Zilliz, Fendy worked as a Content Strategist at PingCAP, a fast-growing E-Series startup renowned for its open-source distributed SQL database.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":5,"localizations":[],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Introducing_Zilliz_MCP_Server_Natural_Language_Access_to_Your_Vector_Database_beae36f92f.png","belong":"blog","authorNames":["Fendy Feng"]},{"id":"blog-1699","title":"Zilliz Named \"Highest Performer\" and \"Easiest to Use\" in G2's Summer 2025 Grid® Report for Vector Databases","image":{"id":6869,"url":"https://assets.zilliz.com/20250703_125604_1af4abe7ad.png"},"display_time":"Jul 02, 2025","deploy_time":null,"url":"zilliz-named-highest-performer-and-easiest-to-use-in-g2-summer-2025","abstract":"This dual recognition shows that Zilliz solved a challenge that has long defined the database industry—delivering enterprise-grade performance without the complexity typically associated with it.","tags":[{"id":4,"name":"Company","published_at":"2021-01-21T02:28:23.551Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:20.676Z","updated_at":"2021-01-21T02:28:23.824Z","locale":"en"}],"authors":[{"id":45,"name":"Fendy Feng","author_tags":"Technical Marketing Writer","published_at":"2023-05-16T01:36:15.102Z","created_by":18,"updated_by":18,"created_at":"2023-05-16T00:04:12.065Z","updated_at":"2024-04-25T08:37:19.712Z","home_page":"GitHub","home_page_link":"https://www.linkedin.com/in/fendy311/","self_intro":"Fendy Feng is the Technical Marketing Writer at Zilliz. She has extensive experience developing and enhancing the impact of open-source projects in various global markets by producing high-quality, tailored content. Before joining Zilliz, Fendy worked as a Content Strategist at PingCAP, a fast-growing E-Series startup renowned for its open-source distributed SQL database.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":3,"localizations":[],"invisible":false,"backgroundImage":"https://assets.zilliz.com/20250703_125604_1af4abe7ad.png","belong":"blog","authorNames":["Fendy Feng"]},{"id":"blog-1698","title":"Our Journey to 35K+ GitHub Stars: The Real Story of Building Milvus from Scratch ","image":{"id":6855,"url":"https://assets.zilliz.com/Github_star_30_K_1_4fc1f3ca73.png"},"display_time":"Jun 27, 2025","deploy_time":null,"url":"journey-to-35k-github-stars-story-of-building-milvus-from-scratch","abstract":"Join us in celebrating Milvus, the vector database that hit 35.5K stars on GitHub. Discover our story and how we’re making AI solutions easier for developers.","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":1,"name":"Zilliz","author_tags":"Vector database","published_at":"2021-12-14T06:36:41.397Z","created_by":18,"updated_by":18,"created_at":"2021-12-14T06:28:27.154Z","updated_at":"2023-04-11T16:54:05.275Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":10,"localizations":[],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Github_star_30_K_1_4fc1f3ca73.png","belong":"blog","authorNames":["Zilliz"]},{"id":"blog-1696","title":"Why Not All VectorDBs Are Agent-Ready","image":{"id":6838,"url":"https://assets.zilliz.com/Chat_GPT_Image_Jun_20_2025_02_53_26_PM_5809db39f2.png"},"display_time":"Jun 20, 2025","deploy_time":null,"url":"why-not-all-vectordbs-are-agent-ready","abstract":"Explore why choosing the right vector database is critical for scaling AI agents, and why traditional solutions fall short in production.","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":45,"name":"Fendy Feng","author_tags":"Technical Marketing Writer","published_at":"2023-05-16T01:36:15.102Z","created_by":18,"updated_by":18,"created_at":"2023-05-16T00:04:12.065Z","updated_at":"2024-04-25T08:37:19.712Z","home_page":"GitHub","home_page_link":"https://www.linkedin.com/in/fendy311/","self_intro":"Fendy Feng is the Technical Marketing Writer at Zilliz. She has extensive experience developing and enhancing the impact of open-source projects in various global markets by producing high-quality, tailored content. Before joining Zilliz, Fendy worked as a Content Strategist at PingCAP, a fast-growing E-Series startup renowned for its open-source distributed SQL database.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":7,"localizations":[],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Chat_GPT_Image_Jun_20_2025_02_53_26_PM_5809db39f2.png","belong":"blog","authorNames":["Fendy Feng"]},{"id":"blog-1697","title":"Creating Collections in Zilliz Cloud Just Got Way Easier","image":{"id":6845,"url":"https://assets.zilliz.com/Creating_Collections_in_Zilliz_Cloud_Just_Got_Way_Easier_1_13e7f06af4.png"},"display_time":"Jun 20, 2025","deploy_time":null,"url":"creating-collections-in-zilliz-cloud-just-got-way-easier","abstract":"We've enhanced the entire collection creation experience to bring advanced capabilities directly into the interface, making it faster and easier to build production-ready schemas without switching tools.","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":39,"name":"Sarah Tang","author_tags":"Senior Product Manager","published_at":"2023-04-12T03:08:03.943Z","created_by":18,"updated_by":18,"created_at":"2023-04-12T02:56:07.784Z","updated_at":"2023-04-12T03:11:53.050Z","home_page":"linkedin","home_page_link":"https://www.linkedin.com/in/xue-tang-070734169/","self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":6,"localizations":[],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Creating_Collections_in_Zilliz_Cloud_Just_Got_Way_Easier_1_13e7f06af4.png","belong":"blog","authorNames":["Sarah Tang"]},{"id":"blog-1695","title":"Announcing the General Availability of Zilliz Cloud BYOC on Google Cloud Platform","image":{"id":6837,"url":"https://assets.zilliz.com/Announcing_the_General_Availability_of_Zilliz_Cloud_BYOC_on_Google_Cloud_Platform_77bad32d0b.png"},"display_time":"Jun 19, 2025","deploy_time":null,"url":"announcing-the-general-availability-of-zilliz-cloud-byoc-on-google-cloud-platform","abstract":"Zilliz Cloud BYOC on GCP offers enterprise vector search with full data sovereignty and seamless integration.","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":430,"name":"Allen Mo","author_tags":"Product Manager at Zilliz","published_at":"2025-06-20T05:49:38.867Z","created_by":125,"updated_by":60,"created_at":"2025-06-20T05:49:37.147Z","updated_at":"2025-06-20T10:02:24.796Z","home_page":null,"home_page_link":null,"self_intro":"Allen Mo is the Product Manager at Zilliz. With a master's degree in information systems from New York University. He has extensive experience in database and big data area.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":3,"localizations":[],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Announcing_the_General_Availability_of_Zilliz_Cloud_BYOC_on_Google_Cloud_Platform_77bad32d0b.png","belong":"blog","authorNames":["Allen Mo"]},{"id":"blog-1694","title":"Build for the Boom: Why AI Agent Startups Should Build Scalable Infrastructure Early","image":{"id":6822,"url":"https://assets.zilliz.com/Why_AI_Agent_Startups_Should_Build_Scalable_Infrastructure_Early_cd5c3c7a98.png"},"display_time":"Jun 16, 2025","deploy_time":null,"url":"why-ai-agent-startups-should-build-scalable-infrastructure-early","abstract":"Explore strategies for developing AI agents that can handle rapid growth. Don't let inadequate systems undermine your success during critical breakthrough moments.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":45,"name":"Fendy Feng","author_tags":"Technical Marketing Writer","published_at":"2023-05-16T01:36:15.102Z","created_by":18,"updated_by":18,"created_at":"2023-05-16T00:04:12.065Z","updated_at":"2024-04-25T08:37:19.712Z","home_page":"GitHub","home_page_link":"https://www.linkedin.com/in/fendy311/","self_intro":"Fendy Feng is the Technical Marketing Writer at Zilliz. She has extensive experience developing and enhancing the impact of open-source projects in various global markets by producing high-quality, tailored content. Before joining Zilliz, Fendy worked as a Content Strategist at PingCAP, a fast-growing E-Series startup renowned for its open-source distributed SQL database.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":7,"localizations":[],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Why_AI_Agent_Startups_Should_Build_Scalable_Infrastructure_Early_cd5c3c7a98.png","belong":"blog","authorNames":["Fendy Feng"]},{"id":"blog-1693","title":"Democratizing AI: Making Vector Search Powerful and Affordable","image":{"id":6809,"url":"https://assets.zilliz.com/What_is_New_in_Milvus_2_6_91d26f4ff3.png"},"display_time":"Jun 12, 2025","deploy_time":null,"url":"democratizing-ai-making-vector-search-powerful-and-affordable","abstract":"Zilliz democratizes AI vector search with Milvus 2.6 and Zilliz Cloud for powerful, affordable scalability, cutting costs in infrastructure, operations, and development.","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":114,"name":"Charles Xie","author_tags":"Founder \u0026 CEO of Zilliz","published_at":"2024-02-07T19:12:09.772Z","created_by":18,"updated_by":18,"created_at":"2024-02-07T19:11:20.296Z","updated_at":"2024-02-07T19:12:09.793Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/chaoxie/","self_intro":"Charles Xie is the founder and CEO of Zilliz, focusing on building next-generation databases and search technologies for AI and LLMs applications. At Zilliz, he also invented Milvus, the world's most popular open-source vector database for production-ready AI. He is currently a board member of LF AI \u0026 Data Foundation and served as the board's chairperson in 2020 and 2021. Charles previously worked at Oracle as a founding engineer of the Oracle 12c cloud database project. Charles holds a master’s degree in computer science from the University of Wisconsin-Madison.\n","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":4,"localizations":[],"invisible":false,"backgroundImage":"https://assets.zilliz.com/What_is_New_in_Milvus_2_6_91d26f4ff3.png","belong":"blog","authorNames":["Charles Xie"]},{"id":"blog-1692","title":"8 Latest RAG Advancements Every Developer Should Know","image":{"id":6801,"url":"https://assets.zilliz.com/8_Latest_Advancements_of_RAG_220cba6447.png"},"display_time":"Jun 06, 2025","deploy_time":null,"url":"8-latest-rag-advancements-every-developer-should-know","abstract":"Explore eight advanced RAG variants that can solve real problems you might be facing: slow retrieval, poor context understanding, multimodal data handling, and resource optimization.\n","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":310,"name":"Wania Shafqat","author_tags":"AI Developer \u0026 Technical Writer\n","published_at":"2025-02-25T23:50:41.682Z","created_by":82,"updated_by":82,"created_at":"2025-02-25T23:50:39.840Z","updated_at":"2025-02-25T23:50:41.710Z","home_page":null,"home_page_link":null,"self_intro":"Wania is a Computer Science graduate specializing in Artificial Intelligence and Cyber Security. Her work reflects her passion for adversarial machine learning and the AI ecosystem. When she’s not coding, you’ll find her writing articles to help fellow developers.\n\n","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":8,"localizations":[],"invisible":false,"backgroundImage":"https://assets.zilliz.com/8_Latest_Advancements_of_RAG_220cba6447.png","belong":"blog","authorNames":["Wania Shafqat"]},{"id":"blog-1689","title":"Why AI Databases Don't Need SQL","image":{"id":6781,"url":"https://assets.zilliz.com/why_ai_databases_don_t_need_SQL_2d12f615df.png"},"display_time":"May 30, 2025","deploy_time":null,"url":"why-ai-databases-do-not-need-sql","abstract":"Whether you like it or not, here's the truth: SQL is destined for decline in the era of AI. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":34,"name":"James Luan","author_tags":"VP of Engineering at Zilliz","published_at":"2022-05-18T03:15:15.255Z","created_by":18,"updated_by":18,"created_at":"2022-05-18T03:14:35.112Z","updated_at":"2024-01-12T21:01:29.192Z","home_page":"GitHub","home_page_link":"https://github.com/xiaofan-luan","self_intro":"James Luan is the VP of Engineering at Zilliz. With a master's degree in computer engineering from Cornell University, he has extensive experience as a Database Engineer at Oracle, Hedvig, and Alibaba Cloud. James played a crucial role in developing HBase, Alibaba Cloud's open-source database, and Lindorm, a self-developed NoSQL database. He is also a respected member of the Technical Advisory Committee of LF AI \u0026 Data Foundation, contributing his expertise to shaping the future of AI and data technologies.\n","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":6,"localizations":[],"invisible":false,"backgroundImage":"https://assets.zilliz.com/why_ai_databases_don_t_need_SQL_2d12f615df.png","belong":"blog","authorNames":["James Luan"]},{"id":"blog-1687","title":"Zero-Downtime Migration Now Available in Zilliz Cloud Private Preview","image":{"id":6759,"url":"https://assets.zilliz.com/Zero_Downtime_Migration_Now_Available_in_Zilliz_Cloud_Private_Preview_9c97088f83.png"},"display_time":"May 29, 2025","deploy_time":null,"url":"zilliz-cloud-zero-downtime-migration-seamless-data-transfer-with-minimal-service-interruption","abstract":"Zero-Downtime Migration enables seamless cluster-to-cluster migrations within Zilliz Cloud while maintaining full service availability. ","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":429,"name":"Yuqi Wang","author_tags":"Product Manager at Zilliz","published_at":"2025-05-29T12:26:41.343Z","created_by":60,"updated_by":60,"created_at":"2025-05-29T12:26:39.292Z","updated_at":"2025-05-30T05:52:06.270Z","home_page":null,"home_page_link":null,"self_intro":"Yuqi Wang is a Product Manager at Zilliz, where she leads product development for Zilliz Cloud offerings, cloud migration services, and vector lake solutions that power AI-native workloads. She brings a strong background across the modern data stack—from ingestion and warehousing to BI—as well as hands-on experience building generative AI products. Yuqi is passionate about transforming complex data and AI technologies into simple, scalable, and user-centric solutions.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":3,"localizations":[],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Zero_Downtime_Migration_Now_Available_in_Zilliz_Cloud_Private_Preview_9c97088f83.png","belong":"blog","authorNames":["Yuqi Wang"]},{"id":"learn-530","title":"Popular Video AI Models Every Developer Should Know","image":{"id":6674,"url":"https://assets.zilliz.com/Popular_Video_AI_Models_Every_Developer_Should_Know_566364e3ae.png"},"display_time":"May 09, 2025","url":"top-six-video-ai-models-every-developer-should-know","abstract":"Discover how Video AI models transform industries by enabling real-time analysis of visual data. Explore their impact on sports, security, and content creation.\n","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":170,"name":"Yesha Shastri","author_tags":"Freelance Technical Writer in AI/ML","published_at":"2024-07-29T08:44:59.761Z","created_by":18,"updated_by":18,"created_at":"2024-07-29T08:44:38.291Z","updated_at":"2024-07-29T08:44:59.820Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/yeshashastri/","self_intro":"Yesha Shastri, Freelance Technical Writer in AI/ML","repost_to_medium":null,"repost_state":null,"meta_description":"Yesha Shastri, Freelance Technical Writer","locale":"en"}],"read_time":10,"localizations":[],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Popular_Video_AI_Models_Every_Developer_Should_Know_566364e3ae.png","belong":"learn","authorNames":["Yesha Shastri"]},{"id":"blog-1685","title":"AI Agents Are Quietly Transforming E-Commerce — Here’s How","image":{"id":6645,"url":"https://assets.zilliz.com/AI_Agents_Are_Quietly_Transforming_E_Commerce_Here_s_How_ef7866d406.png"},"display_time":"Apr 29, 2025","deploy_time":null,"url":"ai-agents-are-quietly-transforming-e-commerce-heres-how","abstract":"Discover how AI agents transform e-commerce with autonomous decision-making, enhanced product discovery, and vector search capabilities for today's retailers.\n","tags":[],"authors":[{"id":36,"name":"Chris Churilo","author_tags":"VP of Marketing","published_at":"2023-04-11T16:51:05.002Z","created_by":18,"updated_by":53,"created_at":"2023-04-11T16:42:46.067Z","updated_at":"2025-01-16T22:35:53.011Z","home_page":"GitHub","home_page_link":"https://github.com/ChrisChurilo","self_intro":"Chris Churilo is the VP of Marketing \u0026 Community at Zilliz where she leads all community, developer relations, and marketing efforts. Prior to Zilliz, Chris was a founding member of the InfluxData’s go to market efforts and helped propel the time series database platform to dominance in the market. In earlier roles she defined and designed a SaaS monitoring solution at Centroid, and prior to that she was the VP of product management at iPass and was the LOB for several cloud services that required her to track the business and operational metrics and analytics to help identify and resolve issues.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":4,"localizations":[],"invisible":false,"backgroundImage":"https://assets.zilliz.com/AI_Agents_Are_Quietly_Transforming_E_Commerce_Here_s_How_ef7866d406.png","belong":"blog","authorNames":["Chris Churilo"]},{"id":"blog-1683","title":"Zilliz Cloud Introduces Advanced BYOC-I Solution for Ultimate Enterprise Data Sovereignty","image":{"id":6638,"url":"https://assets.zilliz.com/Zilliz_Cloud_Introduces_Advanced_BYOC_I_Solution_for_Ultimate_Enterprise_Data_Sovereignty_0736314efd.png"},"display_time":"Apr 28, 2025","deploy_time":null,"url":"zilliz-cloud-sets-new-standard-for-enterprise-ai-data-sovereignty-with-byoc-i","abstract":"Explore Zilliz Cloud BYOC-I, the solution that balances AI innovation with data control, enabling secure deployments in finance, healthcare, and education sectors.","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":45,"name":"Fendy Feng","author_tags":"Technical Marketing Writer","published_at":"2023-05-16T01:36:15.102Z","created_by":18,"updated_by":18,"created_at":"2023-05-16T00:04:12.065Z","updated_at":"2024-04-25T08:37:19.712Z","home_page":"GitHub","home_page_link":"https://www.linkedin.com/in/fendy311/","self_intro":"Fendy Feng is the Technical Marketing Writer at Zilliz. She has extensive experience developing and enhancing the impact of open-source projects in various global markets by producing high-quality, tailored content. Before joining Zilliz, Fendy worked as a Content Strategist at PingCAP, a fast-growing E-Series startup renowned for its open-source distributed SQL database.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":5,"localizations":[],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Zilliz_Cloud_Introduces_Advanced_BYOC_I_Solution_for_Ultimate_Enterprise_Data_Sovereignty_0736314efd.png","belong":"blog","authorNames":["Fendy Feng"]},{"id":"blog-1684","title":"The Great AI Agent Protocol Race: Function Calling vs. MCP vs. A2A","image":{"id":6627,"url":"https://assets.zilliz.com/Function_Calling_vs_MCP_vs_A2_A_df958dd873.png"},"display_time":"Apr 25, 2025","deploy_time":null,"url":"function-calling-vs-mcp-vs-a2a-developers-guide-to-ai-agent-protocols","abstract":"Compare Function Calling, MCP, and A2A protocols for AI agents. Learn which standard best fits your development needs and future-proof your applications.","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":45,"name":"Fendy Feng","author_tags":"Technical Marketing Writer","published_at":"2023-05-16T01:36:15.102Z","created_by":18,"updated_by":18,"created_at":"2023-05-16T00:04:12.065Z","updated_at":"2024-04-25T08:37:19.712Z","home_page":"GitHub","home_page_link":"https://www.linkedin.com/in/fendy311/","self_intro":"Fendy Feng is the Technical Marketing Writer at Zilliz. She has extensive experience developing and enhancing the impact of open-source projects in various global markets by producing high-quality, tailored content. Before joining Zilliz, Fendy worked as a Content Strategist at PingCAP, a fast-growing E-Series startup renowned for its open-source distributed SQL database.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":7,"localizations":[],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Function_Calling_vs_MCP_vs_A2_A_df958dd873.png","belong":"blog","authorNames":["Fendy Feng"]},{"id":"learn-529","title":"From Pixels to Embeddings: How Video AI Represents Visual Data","image":{"id":6644,"url":"https://assets.zilliz.com/From_Pixels_to_Embeddings_How_Video_AI_Represents_Visual_Data_d15c7a0a89.png"},"display_time":"Apr 24, 2025","url":"from-pixels-to-embeddings-how-video-ai-represents-visual-data","abstract":"Discover how video AI transforms raw footage into meaningful embeddings, enabling efficient scene search and action recognition. Explore the technology behind the magic.","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":178,"name":"Benito Martin","author_tags":null,"published_at":"2024-09-10T18:31:20.152Z","created_by":82,"updated_by":82,"created_at":"2024-09-10T18:30:36.499Z","updated_at":"2024-10-02T17:35:02.538Z","home_page":null,"home_page_link":null,"self_intro":"Freelance Technical Writer","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":15,"localizations":[],"invisible":false,"backgroundImage":"https://assets.zilliz.com/From_Pixels_to_Embeddings_How_Video_AI_Represents_Visual_Data_d15c7a0a89.png","belong":"learn","authorNames":["Benito Martin"]},{"id":"blog-1682","title":"What Exactly Are AI Agents? Why OpenAI and LangChain Are Fighting Over Their Definition?","image":{"id":6599,"url":"https://assets.zilliz.com/20250423_120608_74dca6ef51.jpeg"},"display_time":"Apr 22, 2025","deploy_time":null,"url":"what-exactly-are-ai-agents-why-openai-and-langchain-are-fighting-over-their-definition","abstract":"AI agents are software programs powered by artificial intelligence that can perceive their environment, make decisions, and take actions to achieve a goal—often autonomously. ","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":45,"name":"Fendy Feng","author_tags":"Technical Marketing Writer","published_at":"2023-05-16T01:36:15.102Z","created_by":18,"updated_by":18,"created_at":"2023-05-16T00:04:12.065Z","updated_at":"2024-04-25T08:37:19.712Z","home_page":"GitHub","home_page_link":"https://www.linkedin.com/in/fendy311/","self_intro":"Fendy Feng is the Technical Marketing Writer at Zilliz. She has extensive experience developing and enhancing the impact of open-source projects in various global markets by producing high-quality, tailored content. Before joining Zilliz, Fendy worked as a Content Strategist at PingCAP, a fast-growing E-Series startup renowned for its open-source distributed SQL database.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":19,"localizations":[],"invisible":false,"backgroundImage":"https://assets.zilliz.com/20250423_120608_74dca6ef51.jpeg","belong":"blog","authorNames":["Fendy Feng"]},{"id":"learn-528","title":"Chain of Agents (COA): Large Language Models Collaborating on Long-Context Tasks","image":{"id":6567,"url":"https://assets.zilliz.com/Chain_of_Agents_Large_Language_Models_Collaborating_on_Long_Context_Tasks_1_9922ee46c6.png"},"display_time":"Apr 11, 2025","url":"chain-of-agents-large-language-models-collaborating-on-long-context-tasks","abstract":"Discover how Chain-of-Agents enhances Large Language Models by effectively managing context injection, improving response quality while addressing token limitations.\n","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":125,"name":"Ruben Winastwan","author_tags":"Freelance Technical Writer","published_at":"2024-03-26T09:16:27.310Z","created_by":18,"updated_by":18,"created_at":"2024-03-26T09:16:24.498Z","updated_at":"2024-07-03T07:56:29.256Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Ruben Winastwan, Freelance Technical Writer","locale":"en"}],"read_time":11,"localizations":[],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Chain_of_Agents_Large_Language_Models_Collaborating_on_Long_Context_Tasks_1_9922ee46c6.png","belong":"learn","authorNames":["Ruben Winastwan"]},{"id":"blog-392","title":"Demystifying the Milvus Sizing Tool","image":{"id":6672,"url":"https://assets.zilliz.com/Dec_04_Sizing_Tool_Milvus_b2cd5a5d7d.png"},"display_time":"Apr 10, 2025","deploy_time":null,"url":"demystify-milvus-sizing-tool","abstract":"Explore how to use the Sizing Tool to select the optimal configuration for your Milvus deployment. ","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":45,"name":"Fendy Feng","author_tags":"Technical Marketing Writer","published_at":"2023-05-16T01:36:15.102Z","created_by":18,"updated_by":18,"created_at":"2023-05-16T00:04:12.065Z","updated_at":"2024-04-25T08:37:19.712Z","home_page":"GitHub","home_page_link":"https://www.linkedin.com/in/fendy311/","self_intro":"Fendy Feng is the Technical Marketing Writer at Zilliz. She has extensive experience developing and enhancing the impact of open-source projects in various global markets by producing high-quality, tailored content. Before joining Zilliz, Fendy worked as a Content Strategist at PingCAP, a fast-growing E-Series startup renowned for its open-source distributed SQL database.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"},{"id":157,"name":"Ken Zhang","author_tags":"Senior Product Manager","published_at":"2024-04-29T11:13:18.206Z","created_by":18,"updated_by":18,"created_at":"2024-04-29T03:36:01.335Z","updated_at":"2024-07-03T07:47:25.978Z","home_page":null,"home_page_link":null,"self_intro":"Ken Zhang is a Senior Product Manager at Zilliz, leading the development of the Milvus vector database by setting its strategic direction and key features. Prior to Zilliz, he served as a kernel engineer at SAP HANA and enhanced his product management skills at PingCAP. Ken holds a master's degree from Fudan University and has over eight years of experience specializing in database development and big data infrastructure management.","repost_to_medium":null,"repost_state":null,"meta_description":"Ken Zhang is a Senior Product Manager at Zilliz","locale":"en"}],"read_time":5,"localizations":[{"id":911,"locale":"ja-JP","published_at":"2024-04-28T04:49:20.289Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Dec_04_Sizing_Tool_Milvus_b2cd5a5d7d.png","belong":"blog","authorNames":["Fendy Feng","Ken Zhang"]},{"id":"blog-1681","title":"Balancing Precision and Performance: How Zilliz Cloud's New Parameters Help You Optimize Vector Search","image":{"id":6551,"url":"https://assets.zilliz.com/Perfect_Balance_Precision_Tuning_and_Recall_Estimation_with_Zilliz_Cloud_f086c3e7dd.png"},"display_time":"Apr 09, 2025","deploy_time":null,"url":"balancing-precision-and-performance-how-zilliz-cloud-new-parameters-help-you-optimize-vector-search","abstract":"Optimize vector search with Zilliz Cloud’s level and recall features to tune accuracy, balance performance, and power AI applications.","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":427,"name":"Chris Gao","author_tags":"Senior software engineer at Zilliz","published_at":"2025-04-09T03:53:53.311Z","created_by":125,"updated_by":60,"created_at":"2025-04-09T03:53:48.838Z","updated_at":"2025-04-11T05:49:08.460Z","home_page":null,"home_page_link":null,"self_intro":"Chris Gao is a senior software engineer at Zilliz, focusing on the vector search engine optimization in the Milvus vector database and Zilliz Cloud. Prior to Zilliz, he served as a software engineer at Bytedance and optimized the execution of Spark ETL jobs. Chris holds a master's degree from Shanghai Jiao Tong University.","repost_to_medium":null,"repost_state":null,"meta_description":"Senior software engineer at Zilliz","locale":"en"},{"id":157,"name":"Ken Zhang","author_tags":"Senior Product Manager","published_at":"2024-04-29T11:13:18.206Z","created_by":18,"updated_by":18,"created_at":"2024-04-29T03:36:01.335Z","updated_at":"2024-07-03T07:47:25.978Z","home_page":null,"home_page_link":null,"self_intro":"Ken Zhang is a Senior Product Manager at Zilliz, leading the development of the Milvus vector database by setting its strategic direction and key features. Prior to Zilliz, he served as a kernel engineer at SAP HANA and enhanced his product management skills at PingCAP. Ken holds a master's degree from Fudan University and has over eight years of experience specializing in database development and big data infrastructure management.","repost_to_medium":null,"repost_state":null,"meta_description":"Ken Zhang is a Senior Product Manager at Zilliz","locale":"en"}],"read_time":7,"localizations":[],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Perfect_Balance_Precision_Tuning_and_Recall_Estimation_with_Zilliz_Cloud_f086c3e7dd.png","belong":"blog","authorNames":["Chris Gao","Ken Zhang"]},{"id":"blog-1674","title":"Milvus/Zilliz + Surveillance: How Vector Databases Transform Multi-Camera Tracking","image":{"id":6550,"url":"https://assets.zilliz.com/Milvus_Surveillance_How_Vector_Databases_Transform_Multi_Camera_Tracking_2_1535808775.png"},"display_time":"Apr 02, 2025","deploy_time":null,"url":"milvus-and-surveillance-how-vector-dbs-transform-multi-camera-tracking","abstract":"See how Milvus vector database enhances multi-camera tracking with similarity-based matching for better surveillance in retail, warehouses and transport hubs.\n","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":36,"name":"Chris Churilo","author_tags":"VP of Marketing","published_at":"2023-04-11T16:51:05.002Z","created_by":18,"updated_by":53,"created_at":"2023-04-11T16:42:46.067Z","updated_at":"2025-01-16T22:35:53.011Z","home_page":"GitHub","home_page_link":"https://github.com/ChrisChurilo","self_intro":"Chris Churilo is the VP of Marketing \u0026 Community at Zilliz where she leads all community, developer relations, and marketing efforts. Prior to Zilliz, Chris was a founding member of the InfluxData’s go to market efforts and helped propel the time series database platform to dominance in the market. In earlier roles she defined and designed a SaaS monitoring solution at Centroid, and prior to that she was the VP of product management at iPass and was the LOB for several cloud services that required her to track the business and operational metrics and analytics to help identify and resolve issues.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":6,"localizations":[],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Milvus_Surveillance_How_Vector_Databases_Transform_Multi_Camera_Tracking_2_1535808775.png","belong":"blog","authorNames":["Chris Churilo"]},{"id":"blog-1673","title":"ColPali + Milvus: Redefining Document Retrieval with Vision-Language Models","image":{"id":6499,"url":"https://assets.zilliz.com/Col_Pali_Milvus_Redefining_Document_Retrieval_with_Vision_Language_Models_8a25f8769f.png"},"display_time":"Mar 27, 2025","deploy_time":null,"url":"colpali-milvus-redefine-document-retrieval-with-vision-language-models","abstract":"When combined with Milvus's powerful vector search capabilities, ColPali becomes a practical solution for real-world document retrieval challenges. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":115,"name":"Stephen Batifol","author_tags":"Developer Advocate ","published_at":"2024-03-07T03:46:04.655Z","created_by":18,"updated_by":18,"created_at":"2024-03-07T03:46:02.457Z","updated_at":"2024-07-18T15:56:42.529Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/stephen-batifol/","self_intro":"Stephen Batifol is a Developer Advocate at Zilliz. He previously worked as a Machine Learning Engineer at Wolt, where he was working on the ML Platform and as a Data Scientist at Brevo. Stephen studied Computer Science and Artificial Intelligence. He enjoys dancing and surfing. \n","repost_to_medium":null,"repost_state":null,"meta_description":"Stephen Batifol is a Developer Advocate at Zilliz.","locale":"en"}],"read_time":7,"localizations":[],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Col_Pali_Milvus_Redefining_Document_Retrieval_with_Vision_Language_Models_8a25f8769f.png","belong":"blog","authorNames":["Stephen Batifol"]},{"id":"blog-1453","title":"How to Build RAG with Milvus, QwQ-32B and Ollama","image":{"id":6275,"url":"https://assets.zilliz.com/0bc9cc85_ee08_4816_a54a_8ba2fa7e82b0_5577074ad1.png"},"display_time":"Mar 25, 2025","deploy_time":"2025-03-17T04:00:00.000Z","url":"how-to-build-rag-with-milvus-qwq-32b-and-ollama","abstract":"Hands-on tutorial on how to create a streamlined, powerful RAG pipeline that balances efficiency, accuracy, and scalability using the QwQ-32B model and Milvus.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":314,"name":"Lumina Wang","author_tags":"Social Media Advocate","published_at":"2025-03-17T09:57:25.504Z","created_by":125,"updated_by":125,"created_at":"2025-03-17T09:39:50.444Z","updated_at":"2025-03-17T10:42:01.398Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":11,"localizations":[],"invisible":false,"backgroundImage":"https://assets.zilliz.com/0bc9cc85_ee08_4816_a54a_8ba2fa7e82b0_5577074ad1.png","belong":"blog","authorNames":["Lumina Wang"]},{"id":"learn-506","title":"Chain-of-Retrieval Augmented Generation","image":{"id":6504,"url":"https://assets.zilliz.com/Chain_of_Retrieval_Augmented_Generation_1_6c3388bc43.png"},"display_time":"Mar 19, 2025","url":"chain-of-retrieval-augmented-generation","abstract":"Explore CoRAG, a novel retrieval-augmented generation method that refines queries iteratively to improve multi-hop reasoning and factual answers.\n","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":118,"name":" Haziqa Sajid","author_tags":"Freelance Technical Writer","published_at":"2024-03-12T10:25:34.265Z","created_by":18,"updated_by":18,"created_at":"2024-03-12T10:25:31.148Z","updated_at":"2024-07-03T07:58:27.010Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/haziqa-sajid-22b53245/","self_intro":"Digital Storytelling for Data, AI, B2B \u0026 SaaS","repost_to_medium":null,"repost_state":null,"meta_description":" Haziqa Sajid, Freelance Technical Writer","locale":"en"}],"read_time":11,"localizations":[],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Chain_of_Retrieval_Augmented_Generation_1_6c3388bc43.png","belong":"learn","authorNames":[" Haziqa Sajid"]},{"id":"blog-1671","title":"Cosmos World Foundation Model Platform for Physical AI","image":{"id":6476,"url":"https://assets.zilliz.com/Cosmos_World_Foundation_Model_Platform_for_Physical_AI_2_8fe753cca5.png"},"display_time":"Mar 18, 2025","deploy_time":null,"url":"cosmos-world-foundation-model-platform-for-physical-ai","abstract":"NVIDIA’s Cosmos platform pioneers GenAI for physical applications by enabling safe digital twin training to overcome data and safety challenges in physical AI modeling.","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":125,"name":"Ruben Winastwan","author_tags":"Freelance Technical Writer","published_at":"2024-03-26T09:16:27.310Z","created_by":18,"updated_by":18,"created_at":"2024-03-26T09:16:24.498Z","updated_at":"2024-07-03T07:56:29.256Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Ruben Winastwan, Freelance Technical Writer","locale":"en"}],"read_time":14,"localizations":[],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Cosmos_World_Foundation_Model_Platform_for_Physical_AI_2_8fe753cca5.png","belong":"blog","authorNames":["Ruben Winastwan"]},{"id":"blog-1670","title":"1 Table = 1000 Words? Foundation Models for Tabular Data","image":{"id":6464,"url":"https://assets.zilliz.com/1_Table_1000_Words_Foundation_Models_for_Tabular_Data_731658adcd.png"},"display_time":"Mar 17, 2025","deploy_time":null,"url":"1-table-1000-words-foundation-models-for-tabular-data","abstract":"TableGPT2 automates tabular data insights, overcoming schema variability, while Milvus accelerates vector search for efficient, scalable decision-making.","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":179,"name":"Simon Mwaniki ","author_tags":null,"published_at":"2024-09-11T00:44:07.918Z","created_by":82,"updated_by":82,"created_at":"2024-09-11T00:44:06.462Z","updated_at":"2024-09-27T22:42:13.512Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":13,"localizations":[],"invisible":false,"backgroundImage":"https://assets.zilliz.com/1_Table_1000_Words_Foundation_Models_for_Tabular_Data_731658adcd.png","belong":"blog","authorNames":["Simon Mwaniki "]},{"id":"blog-1675","title":"Vector Databases vs. Object-Relational Databases","image":{"id":6547,"url":"https://assets.zilliz.com/Vector_Databases_vs_Object_Relational_Databases_e54ad10974.png"},"display_time":"Mar 15, 2025","deploy_time":null,"url":"vector-database-vs-object-relational-databases","abstract":"Use a vector database for AI-powered similarity search; use an object-relational database for complex data modeling with both relational integrity and object-oriented features.","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":176,"name":"Chloe Williams","author_tags":"Technical Writer","published_at":"2024-09-05T07:58:16.265Z","created_by":60,"updated_by":60,"created_at":"2024-09-05T07:58:14.700Z","updated_at":"2024-09-05T07:58:16.284Z","home_page":"","home_page_link":"","self_intro":"Chloe Williams is a technical writer at Zilliz. ","repost_to_medium":null,"repost_state":null,"meta_description":"Chloe Williams, Technical Writer at Zilliz. ","locale":"en"}],"read_time":18,"localizations":[],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Vector_Databases_vs_Object_Relational_Databases_e54ad10974.png","belong":"blog","authorNames":["Chloe Williams"]},{"id":"blog-1667","title":"Vector Databases vs. Document Databases","image":{"id":6422,"url":"https://assets.zilliz.com/Vector_Databases_vs_Document_Databases_e7f80d9dd8.png"},"display_time":"Mar 14, 2025","deploy_time":null,"url":"vector-database-vs-document-databases","abstract":"Use a vector database for similarity search and AI-powered applications; use a document database for flexible schema and JSON-like data storage.","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":176,"name":"Chloe Williams","author_tags":"Technical Writer","published_at":"2024-09-05T07:58:16.265Z","created_by":60,"updated_by":60,"created_at":"2024-09-05T07:58:14.700Z","updated_at":"2024-09-05T07:58:16.284Z","home_page":"","home_page_link":"","self_intro":"Chloe Williams is a technical writer at Zilliz. ","repost_to_medium":null,"repost_state":null,"meta_description":"Chloe Williams, Technical Writer at Zilliz. ","locale":"en"}],"read_time":17,"localizations":[],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Vector_Databases_vs_Document_Databases_e7f80d9dd8.png","belong":"blog","authorNames":["Chloe Williams"]},{"id":"blog-1451","title":"How to Use Anthropic MCP Server with Milvus","image":{"id":6226,"url":"https://assets.zilliz.com/How_to_Use_Anthropic_MCP_Server_with_Milvus_155f989e10.png"},"display_time":"Mar 13, 2025","deploy_time":null,"url":"how-to-use-anthropic-mcp-server-with-milvus","abstract":"Discover how Model Context Protocol (MCP) pairs with Milvus to eliminate AI integration hassles, enabling smarter agents with seamless data access and flexibility.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":115,"name":"Stephen Batifol","author_tags":"Developer Advocate ","published_at":"2024-03-07T03:46:04.655Z","created_by":18,"updated_by":18,"created_at":"2024-03-07T03:46:02.457Z","updated_at":"2024-07-18T15:56:42.529Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/stephen-batifol/","self_intro":"Stephen Batifol is a Developer Advocate at Zilliz. He previously worked as a Machine Learning Engineer at Wolt, where he was working on the ML Platform and as a Data Scientist at Brevo. Stephen studied Computer Science and Artificial Intelligence. He enjoys dancing and surfing. \n","repost_to_medium":null,"repost_state":null,"meta_description":"Stephen Batifol is a Developer Advocate at Zilliz.","locale":"en"}],"read_time":4,"localizations":[],"invisible":false,"backgroundImage":"https://assets.zilliz.com/How_to_Use_Anthropic_MCP_Server_with_Milvus_155f989e10.png","belong":"blog","authorNames":["Stephen Batifol"]},{"id":"blog-1672","title":"VidTok: Rethinking Video Processing with Compact Tokenization","image":{"id":6496,"url":"https://assets.zilliz.com/Video_Tokenizer_65ba2cb2dc.png"},"display_time":"Mar 12, 2025","deploy_time":null,"url":"vidtok-rethinking-video-processing-with-compact-tokenization","abstract":"VidTok tokenizes videos to reduce redundancy while preserving spatial and temporal details for efficient processing.","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":158,"name":"Denis Kuria","author_tags":"Freelance Technical Writer","published_at":"2024-05-01T00:39:32.350Z","created_by":18,"updated_by":18,"created_at":"2024-05-01T00:39:30.888Z","updated_at":"2024-07-03T06:50:56.660Z","home_page":null,"home_page_link":null,"self_intro":"Denis is a machine learning engineer who enjoys writing guides to help other developers. He has a bachelor's in computer science and loves hiking and exploring the world.\n","repost_to_medium":null,"repost_state":null,"meta_description":"Denis Kuria is a freelance technical writer at Zilliz. ","locale":"en"}],"read_time":11,"localizations":[],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Video_Tokenizer_65ba2cb2dc.png","belong":"blog","authorNames":["Denis Kuria"]},{"id":"blog-308","title":"Similarity Metrics for Vector Search","image":{"id":6534,"url":"https://assets.zilliz.com/Nov_27_Similarity_Metrics_for_Vector_Search_238a1ff4bd.png"},"display_time":"Mar 11, 2025","deploy_time":"2023-12-15T04:00:00.000Z","url":"similarity-metrics-for-vector-search","abstract":"Exploring five similarity metrics for vector search: L2 or Euclidean distance, cosine distance, inner product, and hamming distance. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":41,"name":"Yujian Tang","author_tags":"Developer Advocate at Zilliz","published_at":"2023-04-20T21:52:47.479Z","created_by":18,"updated_by":18,"created_at":"2023-04-20T21:52:45.859Z","updated_at":"2024-07-18T16:02:07.497Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/yujiantang/","self_intro":"Yujian Tang is a Developer Advocate at Zilliz. He has a background as a software engineer working on AutoML at Amazon. Yujian studied Computer Science, Statistics, and Neuroscience with research papers published to conferences including IEEE Big Data. He enjoys drinking bubble tea, spending time with family, and being near water.","repost_to_medium":null,"repost_state":null,"meta_description":"Yujian Tang, Developer Advocate at Zilliz. ","locale":"en"}],"read_time":16,"localizations":[{"id":1484,"locale":"es","published_at":"2023-12-15T07:18:10.380Z"},{"id":1592,"locale":"it","published_at":"2023-12-15T07:18:10.380Z"},{"id":859,"locale":"ja-JP","published_at":"2023-12-15T07:18:10.380Z"},{"id":1565,"locale":"ko","published_at":"2023-12-15T07:18:10.380Z"},{"id":1619,"locale":"fr","published_at":"2023-12-15T07:18:10.380Z"},{"id":1457,"locale":"de","published_at":"2023-12-15T07:18:10.380Z"},{"id":1511,"locale":"pt","published_at":"2023-12-15T07:18:10.380Z"},{"id":1538,"locale":"ru","published_at":"2023-12-15T07:18:10.380Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Nov_27_Similarity_Metrics_for_Vector_Search_238a1ff4bd.png","belong":"blog","authorNames":["Yujian Tang"]},{"id":"blog-1665","title":"Optimizing Embedding Model Selection with TDA Clustering: A Strategic Guide for Vector Databases","image":{"id":6331,"url":"https://assets.zilliz.com/How_to_Optimize_Your_Embedding_Model_Selection_and_Development_1cf06e0564.png"},"display_time":"Mar 10, 2025","deploy_time":null,"url":"how-to-optimize-your-embedding-model-selection-and-development","abstract":"Discover how Topological Data Analysis (TDA) reveals hidden embedding model weaknesses and helps optimize vector database performance.\n","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":310,"name":"Wania Shafqat","author_tags":"AI Developer \u0026 Technical Writer\n","published_at":"2025-02-25T23:50:41.682Z","created_by":82,"updated_by":82,"created_at":"2025-02-25T23:50:39.840Z","updated_at":"2025-02-25T23:50:41.710Z","home_page":null,"home_page_link":null,"self_intro":"Wania is a Computer Science graduate specializing in Artificial Intelligence and Cyber Security. Her work reflects her passion for adversarial machine learning and the AI ecosystem. When she’s not coding, you’ll find her writing articles to help fellow developers.\n\n","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":7,"localizations":[],"invisible":false,"backgroundImage":"https://assets.zilliz.com/How_to_Optimize_Your_Embedding_Model_Selection_and_Development_1cf06e0564.png","belong":"blog","authorNames":["Wania Shafqat"]},{"id":"blog-1666","title":"Vector Databases vs. Time Series Databases","image":{"id":6412,"url":"https://assets.zilliz.com/Time_Series_Databases_vs_Vector_Databases_ca0d8bb38a.png"},"display_time":"Mar 06, 2025","deploy_time":null,"url":"vector-database-vs-time-series-databases","abstract":"Use a vector database for similarity search and semantic relationships; use a time series database for tracking value changes over time.","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":176,"name":"Chloe Williams","author_tags":"Technical Writer","published_at":"2024-09-05T07:58:16.265Z","created_by":60,"updated_by":60,"created_at":"2024-09-05T07:58:14.700Z","updated_at":"2024-09-05T07:58:16.284Z","home_page":"","home_page_link":"","self_intro":"Chloe Williams is a technical writer at Zilliz. ","repost_to_medium":null,"repost_state":null,"meta_description":"Chloe Williams, Technical Writer at Zilliz. ","locale":"en"}],"read_time":18,"localizations":[],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Time_Series_Databases_vs_Vector_Databases_ca0d8bb38a.png","belong":"blog","authorNames":["Chloe Williams"]},{"id":"learn-505","title":"Top 10 RAG \u0026 LLM Evaluation Tools You Don't Want To Miss","image":{"id":6299,"url":"https://assets.zilliz.com/Top_10_RAG_and_LLM_Evaluation_Tools_You_Don_t_Want_to_Miss_cb3936dbfe.png"},"display_time":"Mar 05, 2025","url":"top-ten-rag-and-llm-evaluation-tools-you-dont-want-to-miss","abstract":"Discover the best RAG evaluation tools to improve AI app reliability, prevent hallucinations, and boost performance across different frameworks.\n","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":170,"name":"Yesha Shastri","author_tags":"Freelance Technical Writer in AI/ML","published_at":"2024-07-29T08:44:59.761Z","created_by":18,"updated_by":18,"created_at":"2024-07-29T08:44:38.291Z","updated_at":"2024-07-29T08:44:59.820Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/yeshashastri/","self_intro":"Yesha Shastri, Freelance Technical Writer in AI/ML","repost_to_medium":null,"repost_state":null,"meta_description":"Yesha Shastri, Freelance Technical Writer","locale":"en"}],"read_time":9,"localizations":[],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Top_10_RAG_and_LLM_Evaluation_Tools_You_Don_t_Want_to_Miss_cb3936dbfe.png","belong":"learn","authorNames":["Yesha Shastri"]},{"id":"blog-1419","title":"Bringing AI to Legal Tech: The Role of Vector Databases in Enhancing LLM Guardrails","image":{"id":6205,"url":"https://assets.zilliz.com/AI_Integration_in_the_Legal_Industry_Revolutionizing_Legal_Practice_with_Data_Driven_Solutions_713fd1ce5f.png"},"display_time":"Mar 04, 2025","deploy_time":null,"url":"bringing-ai-to-legal-tech-role-of-vector-databases-in-enhancing-llm-guardrails","abstract":"Discover how vector databases enhance AI reliability in legal tech, ensuring accurate, compliant, and trustworthy AI-powered legal solutions.\n","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":36,"name":"Chris Churilo","author_tags":"VP of Marketing","published_at":"2023-04-11T16:51:05.002Z","created_by":18,"updated_by":53,"created_at":"2023-04-11T16:42:46.067Z","updated_at":"2025-01-16T22:35:53.011Z","home_page":"GitHub","home_page_link":"https://github.com/ChrisChurilo","self_intro":"Chris Churilo is the VP of Marketing \u0026 Community at Zilliz where she leads all community, developer relations, and marketing efforts. Prior to Zilliz, Chris was a founding member of the InfluxData’s go to market efforts and helped propel the time series database platform to dominance in the market. In earlier roles she defined and designed a SaaS monitoring solution at Centroid, and prior to that she was the VP of product management at iPass and was the LOB for several cloud services that required her to track the business and operational metrics and analytics to help identify and resolve issues.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":6,"localizations":[{"id":1445,"locale":"ja-JP","published_at":"2025-03-05T00:40:28.325Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/AI_Integration_in_the_Legal_Industry_Revolutionizing_Legal_Practice_with_Data_Driven_Solutions_713fd1ce5f.png","belong":"blog","authorNames":["Chris Churilo"]},{"id":"blog-1668","title":"Vector Databases vs. Key-Value Databases","image":{"id":6421,"url":"https://assets.zilliz.com/Vector_Databases_vs_Key_Value_Databases_01c58414d4.png"},"display_time":"Mar 03, 2025","deploy_time":null,"url":"vector-database-vs-key-value-databases","abstract":"Use a vector database for AI-powered similarity search; use a key-value database for high-throughput, low-latency simple data lookups.","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":176,"name":"Chloe Williams","author_tags":"Technical Writer","published_at":"2024-09-05T07:58:16.265Z","created_by":60,"updated_by":60,"created_at":"2024-09-05T07:58:14.700Z","updated_at":"2024-09-05T07:58:16.284Z","home_page":"","home_page_link":"","self_intro":"Chloe Williams is a technical writer at Zilliz. ","repost_to_medium":null,"repost_state":null,"meta_description":"Chloe Williams, Technical Writer at Zilliz. ","locale":"en"}],"read_time":18,"localizations":[],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Vector_Databases_vs_Key_Value_Databases_01c58414d4.png","belong":"blog","authorNames":["Chloe Williams"]},{"id":"blog-108","title":"What is the K-Nearest Neighbors (KNN) Algorithm in Machine Learning?","image":{"id":1119,"url":"https://assets.zilliz.com/Zilliz_Blog_14_Oct_fdd705c5ee.png"},"display_time":"Mar 02, 2025","deploy_time":null,"url":"k-nearest-neighbor-algorithm-for-machine-learning","abstract":"KNN is a supervised machine learning technique and algorithm for classification and regression. This post is the ultimate guide to KNN. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":1,"name":"Zilliz","author_tags":"Vector database","published_at":"2021-12-14T06:36:41.397Z","created_by":18,"updated_by":18,"created_at":"2021-12-14T06:28:27.154Z","updated_at":"2023-04-11T16:54:05.275Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":18,"localizations":[{"id":1337,"locale":"ja-JP","published_at":"2022-10-17T02:12:27.610Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Zilliz_Blog_14_Oct_fdd705c5ee.png","belong":"blog","authorNames":["Zilliz"]},{"id":"blog-1452","title":"Milvus WebUI: A Visual Management Tool for Your Vector Database","image":{"id":6276,"url":"https://assets.zilliz.com/Milvus_Web_UI_A_Visual_Management_Tool_for_Your_Vector_Database_3e1b24e106.png"},"display_time":"Mar 01, 2025","deploy_time":null,"url":"milvus-webui-visual-management-tool-for-your-vectordb","abstract":"Milvus WebUI is a built-in GUI introduced in Milvus v2.5 for system observability. WebUI comes pre-installed with your Milvus instance and offers immediate access to critical system metrics and management features.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":115,"name":"Stephen Batifol","author_tags":"Developer Advocate ","published_at":"2024-03-07T03:46:04.655Z","created_by":18,"updated_by":18,"created_at":"2024-03-07T03:46:02.457Z","updated_at":"2024-07-18T15:56:42.529Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/stephen-batifol/","self_intro":"Stephen Batifol is a Developer Advocate at Zilliz. He previously worked as a Machine Learning Engineer at Wolt, where he was working on the ML Platform and as a Data Scientist at Brevo. Stephen studied Computer Science and Artificial Intelligence. He enjoys dancing and surfing. \n","repost_to_medium":null,"repost_state":null,"meta_description":"Stephen Batifol is a Developer Advocate at Zilliz.","locale":"en"}],"read_time":4,"localizations":[{"id":1664,"locale":"ja-JP","published_at":"2025-03-14T00:12:36.096Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Milvus_Web_UI_A_Visual_Management_Tool_for_Your_Vector_Database_3e1b24e106.png","belong":"blog","authorNames":["Stephen Batifol"]},{"id":"learn-5","title":"What is a Vector Database and how does it work: Implementation, Optimization \u0026 Scaling for Production Applications","image":{"id":6450,"url":"https://assets.zilliz.com/Vector_Database_A_Complete_Introduction_2_349ba97031.png"},"display_time":"Mar 01, 2025","url":"what-is-vector-database","abstract":"A vector database stores, indexes, and searches vector embeddings generated by machine learning models for fast information retrieval and similarity search. ","tags":[{"id":39,"name":"VectorDB 101","published_at":"2022-09-30T05:56:34.554Z","created_by":18,"updated_by":18,"created_at":"2022-09-30T05:56:31.633Z","updated_at":"2024-07-10T07:12:04.155Z","locale":"en"}],"authors":[{"id":3,"name":"Frank Liu","author_tags":"Director of Operations \u0026 ML Architect at Zilliz","published_at":"2021-12-23T11:08:08.015Z","created_by":18,"updated_by":18,"created_at":"2021-12-23T10:40:59.821Z","updated_at":"2023-04-21T22:30:10.416Z","home_page":"GitHub","home_page_link":"https://github.com/fzliu","self_intro":"Frank Liu is the Director of Operations \u0026 ML Architect at Zilliz, where he serves as a maintainer for the Towhee open-source project. Prior to Zilliz, Frank co-founded Orion Innovations, an ML-powered indoor positioning startup based in Shanghai and worked as an ML engineer at Yahoo in San Francisco. In his free time, Frank enjoys playing chess, swimming, and powerlifting. Frank holds MS and BS degrees in Electrical Engineering from Stanford University. ","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":20,"localizations":[{"id":292,"locale":"ja-JP","published_at":"2025-01-22T06:59:03.303Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Vector_Database_A_Complete_Introduction_2_349ba97031.png","belong":"learn","authorNames":["Frank Liu"]},{"id":"blog-1420","title":"Legal Document Analysis: Harnessing Zilliz Cloud's Semantic Search and RAG for Legal Insights","image":{"id":6206,"url":"https://assets.zilliz.com/Legal_Document_Analysis_Harnessing_Zilliz_Cloud_s_Semantic_Search_and_RAG_for_Legal_Insights_1_076bda1796.png"},"display_time":"Feb 28, 2025","deploy_time":null,"url":"legal-doc-analysis-harness-zilliz-cloud-semantic-search-and-rag-for-legal-insights","abstract":"Zilliz Cloud transforms legal document analysis with AI-driven Semantic Search and Retrieval-Augmented Generation (RAG). By combining keyword and vector search, it enables faster, more accurate contract analysis, case law research, and regulatory tracking.\n\n\n\n\n\n\n\n\n","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":36,"name":"Chris Churilo","author_tags":"VP of Marketing","published_at":"2023-04-11T16:51:05.002Z","created_by":18,"updated_by":53,"created_at":"2023-04-11T16:42:46.067Z","updated_at":"2025-01-16T22:35:53.011Z","home_page":"GitHub","home_page_link":"https://github.com/ChrisChurilo","self_intro":"Chris Churilo is the VP of Marketing \u0026 Community at Zilliz where she leads all community, developer relations, and marketing efforts. Prior to Zilliz, Chris was a founding member of the InfluxData’s go to market efforts and helped propel the time series database platform to dominance in the market. In earlier roles she defined and designed a SaaS monitoring solution at Centroid, and prior to that she was the VP of product management at iPass and was the LOB for several cloud services that required her to track the business and operational metrics and analytics to help identify and resolve issues.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":5,"localizations":[{"id":1444,"locale":"ja-JP","published_at":"2025-03-05T05:48:16.539Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Legal_Document_Analysis_Harnessing_Zilliz_Cloud_s_Semantic_Search_and_RAG_for_Legal_Insights_1_076bda1796.png","belong":"blog","authorNames":["Chris Churilo"]},{"id":"blog-1669","title":"Vector Databases vs. Graph Databases","image":{"id":6420,"url":"https://assets.zilliz.com/Vector_Databases_vs_Graph_Databases_10b99421e6.png"},"display_time":"Feb 27, 2025","deploy_time":null,"url":"vector-database-vs-graph-databases","abstract":"Use a vector database for AI-powered similarity search; use a graph database for complex relationship-based queries and network analysis.","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":176,"name":"Chloe Williams","author_tags":"Technical Writer","published_at":"2024-09-05T07:58:16.265Z","created_by":60,"updated_by":60,"created_at":"2024-09-05T07:58:14.700Z","updated_at":"2024-09-05T07:58:16.284Z","home_page":"","home_page_link":"","self_intro":"Chloe Williams is a technical writer at Zilliz. ","repost_to_medium":null,"repost_state":null,"meta_description":"Chloe Williams, Technical Writer at Zilliz. ","locale":"en"}],"read_time":18,"localizations":[],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Vector_Databases_vs_Graph_Databases_10b99421e6.png","belong":"blog","authorNames":["Chloe Williams"]},{"id":"blog-1417","title":"Selecting the Right ETL Tools for Unstructured Data to Prepare for AI","image":{"id":6204,"url":"https://assets.zilliz.com/Selecting_the_Right_ETL_Tools_for_Unstructured_Data_to_Prepare_for_AI_c775129e9f.png"},"display_time":"Feb 27, 2025","deploy_time":null,"url":"selecting-the-right-etl-tools-for-unstructured-data-to-prepare-for-ai","abstract":"Learn the right ETL tools for unstructured data to power AI. Explore key challenges, tool comparisons, and integrations with Milvus for vector search.\n","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":118,"name":" Haziqa Sajid","author_tags":"Freelance Technical Writer","published_at":"2024-03-12T10:25:34.265Z","created_by":18,"updated_by":18,"created_at":"2024-03-12T10:25:31.148Z","updated_at":"2024-07-03T07:58:27.010Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/haziqa-sajid-22b53245/","self_intro":"Digital Storytelling for Data, AI, B2B \u0026 SaaS","repost_to_medium":null,"repost_state":null,"meta_description":" Haziqa Sajid, Freelance Technical Writer","locale":"en"}],"read_time":9,"localizations":[{"id":1440,"locale":"ja-JP","published_at":"2025-02-28T22:00:09.783Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Selecting_the_Right_ETL_Tools_for_Unstructured_Data_to_Prepare_for_AI_c775129e9f.png","belong":"blog","authorNames":[" Haziqa Sajid"]},{"id":"blog-1416","title":"OpenAI o1: What Developers Need to Know","image":{"id":6158,"url":"https://assets.zilliz.com/Open_AI_o1_What_Developers_Need_to_Know_That_Open_AI_Didn_t_Tell_You_1_66eee4b218.png"},"display_time":"Feb 26, 2025","deploy_time":null,"url":"openai-o1-what-developers-need-to-know","abstract":"In this article, we will talk about the o1 series from a developer's perspective, exploring how these models can be implemented for sophisticated use cases. ","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":125,"name":"Ruben Winastwan","author_tags":"Freelance Technical Writer","published_at":"2024-03-26T09:16:27.310Z","created_by":18,"updated_by":18,"created_at":"2024-03-26T09:16:24.498Z","updated_at":"2024-07-03T07:56:29.256Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Ruben Winastwan, Freelance Technical Writer","locale":"en"}],"read_time":17,"localizations":[{"id":1439,"locale":"ja-JP","published_at":"2025-02-28T21:32:31.480Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Open_AI_o1_What_Developers_Need_to_Know_That_Open_AI_Didn_t_Tell_You_1_66eee4b218.png","belong":"blog","authorNames":["Ruben Winastwan"]},{"id":"learn-493","title":"Enhancing Multimodal AI: Bridging Audio, Text, and Vector Search","image":{"id":6208,"url":"https://assets.zilliz.com/Enhancing_Multimodal_AI_Bridging_Audio_Text_and_Vector_Search_06b19aac47.png"},"display_time":"Feb 26, 2025","url":"enhancing-multimodal-ai-bridging-audio-text-and-vector-search","abstract":"In this article, we will explore how multimodal AI enhances AI systems by bridging audio, text, and vector search. ","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":158,"name":"Denis Kuria","author_tags":"Freelance Technical Writer","published_at":"2024-05-01T00:39:32.350Z","created_by":18,"updated_by":18,"created_at":"2024-05-01T00:39:30.888Z","updated_at":"2024-07-03T06:50:56.660Z","home_page":null,"home_page_link":null,"self_intro":"Denis is a machine learning engineer who enjoys writing guides to help other developers. He has a bachelor's in computer science and loves hiking and exploring the world.\n","repost_to_medium":null,"repost_state":null,"meta_description":"Denis Kuria is a freelance technical writer at Zilliz. ","locale":"en"}],"read_time":13,"localizations":[{"id":504,"locale":"ja-JP","published_at":"2025-02-28T19:51:40.649Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Enhancing_Multimodal_AI_Bridging_Audio_Text_and_Vector_Search_06b19aac47.png","belong":"learn","authorNames":["Denis Kuria"]},{"id":"blog-1409","title":"DeepSeek Always Busy? Deploy It Locally with Milvus in Just 10 Minutes—No More Waiting!","image":{"id":6122,"url":"https://assets.zilliz.com/Deep_Seek_Always_Busy_Deploy_It_Locally_with_Milvus_in_Just_10_Minutes_No_More_Waiting_2_2ca8630b24.png"},"display_time":"Feb 25, 2025","deploy_time":null,"url":"deploy-deepseek-locally-with-milvus-in-ten-minutes","abstract":"Learn how to set up DeepSeek-R1 on your local machine using Ollama, AnythingLLM, and Milvus in just 10 minutes. Bypass busy servers and enhance AI responses with custom data.\n","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":158,"name":"Denis Kuria","author_tags":"Freelance Technical Writer","published_at":"2024-05-01T00:39:32.350Z","created_by":18,"updated_by":18,"created_at":"2024-05-01T00:39:30.888Z","updated_at":"2024-07-03T06:50:56.660Z","home_page":null,"home_page_link":null,"self_intro":"Denis is a machine learning engineer who enjoys writing guides to help other developers. He has a bachelor's in computer science and loves hiking and exploring the world.\n","repost_to_medium":null,"repost_state":null,"meta_description":"Denis Kuria is a freelance technical writer at Zilliz. ","locale":"en"}],"read_time":10,"localizations":[{"id":1434,"locale":"ja-JP","published_at":"2025-02-25T23:01:49.775Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Deep_Seek_Always_Busy_Deploy_It_Locally_with_Milvus_in_Just_10_Minutes_No_More_Waiting_2_2ca8630b24.png","belong":"blog","authorNames":["Denis Kuria"]},{"id":"learn-490","title":"From Text to Speech: A Deep Dive into TTS Technologies","image":{"id":6203,"url":"https://assets.zilliz.com/From_Text_to_Speech_A_Deep_Dive_into_TTS_Technologies_0940e9caad.png"},"display_time":"Feb 24, 2025","url":"from-text-to-speech-deep-dive-into-tts-technologies","abstract":"Explore the evolution of Text-to-Speech technology from mechanical devices to neural networks. Learn how TTS works, compare popular models, and implement it using Google Cloud Platform.\n","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":178,"name":"Benito Martin","author_tags":null,"published_at":"2024-09-10T18:31:20.152Z","created_by":82,"updated_by":82,"created_at":"2024-09-10T18:30:36.499Z","updated_at":"2024-10-02T17:35:02.538Z","home_page":null,"home_page_link":null,"self_intro":"Freelance Technical Writer","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":13,"localizations":[{"id":500,"locale":"ja-JP","published_at":"2025-02-25T23:46:53.091Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/From_Text_to_Speech_A_Deep_Dive_into_TTS_Technologies_0940e9caad.png","belong":"learn","authorNames":["Benito Martin"]},{"id":"blog-1413","title":"Building RAG Pipelines for Real-Time Data with Cloudera and Milvus","image":{"id":6111,"url":"https://assets.zilliz.com/RAG_Pipelines_with_Real_Time_Data_2_b102b09dfc.png"},"display_time":"Feb 23, 2025","deploy_time":null,"url":"build-rag-for-real-time-data-with-cloudera-and-milvus","abstract":"explore how Cloudera can be integrated with Milvus to effectively implement some of the key functionalities of RAG pipelines. ","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":170,"name":"Yesha Shastri","author_tags":"Freelance Technical Writer in AI/ML","published_at":"2024-07-29T08:44:59.761Z","created_by":18,"updated_by":18,"created_at":"2024-07-29T08:44:38.291Z","updated_at":"2024-07-29T08:44:59.820Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/yeshashastri/","self_intro":"Yesha Shastri, Freelance Technical Writer in AI/ML","repost_to_medium":null,"repost_state":null,"meta_description":"Yesha Shastri, Freelance Technical Writer","locale":"en"}],"read_time":7,"localizations":[{"id":1435,"locale":"ja-JP","published_at":"2025-02-26T12:15:25.833Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/RAG_Pipelines_with_Real_Time_Data_2_b102b09dfc.png","belong":"blog","authorNames":["Yesha Shastri"]},{"id":"learn-489","title":"Choosing the Right Audio Transformer: An In-depth Comparison","image":{"id":6202,"url":"https://assets.zilliz.com/Choosing_the_Right_Audio_Transformer_An_In_depth_Comparison_2d2dce4a77.png"},"display_time":"Feb 22, 2025","url":"choosing-the-right-audio-transformer-in-depth-comparison","abstract":"Discover how audio transformers enhance sound processing. Explore their principles, selection criteria, popular models, applications, and key challenges.\n","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":118,"name":" Haziqa Sajid","author_tags":"Freelance Technical Writer","published_at":"2024-03-12T10:25:34.265Z","created_by":18,"updated_by":18,"created_at":"2024-03-12T10:25:31.148Z","updated_at":"2024-07-03T07:58:27.010Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/haziqa-sajid-22b53245/","self_intro":"Digital Storytelling for Data, AI, B2B \u0026 SaaS","repost_to_medium":null,"repost_state":null,"meta_description":" Haziqa Sajid, Freelance Technical Writer","locale":"en"}],"read_time":8,"localizations":[{"id":501,"locale":"ja-JP","published_at":"2025-02-25T23:19:57.299Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Choosing_the_Right_Audio_Transformer_An_In_depth_Comparison_2d2dce4a77.png","belong":"learn","authorNames":[" Haziqa Sajid"]},{"id":"blog-1407","title":"Introducing DeepSearcher: A Local Open Source Deep Research","image":{"id":6031,"url":"https://assets.zilliz.com/Introducing_Deep_Searcher_A_Local_Open_Source_Deep_Research_613cbb07b9.png"},"display_time":"Feb 21, 2025","deploy_time":null,"url":"introduce-deepsearcher-a-local-open-source-deep-research","abstract":"In contrast to OpenAI’s Deep Research, this example ran locally, using only open-source models and tools like Milvus and LangChain.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":183,"name":"Stefan Webb","author_tags":"Developer Advocate, Zilliz","published_at":"2024-09-25T22:53:17.678Z","created_by":82,"updated_by":82,"created_at":"2024-09-25T18:15:43.954Z","updated_at":"2024-09-25T22:53:17.714Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/stefan-webb/","self_intro":"Stefan Webb is a Developer Advocate at Zilliz, where he advocates for the open-source vector database, Milvus. Prior to this, he spent three years in industry as an Applied ML Researcher at Twitter and Meta, collaborating with product teams to tackle their most complex challenges.\nStefan holds a PhD from the University of Oxford and has published papers at prestigious machine learning conferences such as NeurIPS, ICLR, and ICML. He is passionate about generative AI and is eager to leverage his deep technical expertise to contribute to the open-source community.\n","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":9,"localizations":[{"id":1641,"locale":"fr","published_at":"2025-02-21T03:49:00.692Z"},{"id":1506,"locale":"es","published_at":"2025-02-21T03:49:00.692Z"},{"id":1479,"locale":"de","published_at":"2025-02-21T03:49:00.692Z"},{"id":1533,"locale":"pt","published_at":"2025-02-21T03:49:00.692Z"},{"id":1432,"locale":"ja-JP","published_at":"2025-02-21T03:49:00.692Z"},{"id":1587,"locale":"ko","published_at":"2025-02-21T03:49:00.692Z"},{"id":1614,"locale":"it","published_at":"2025-02-21T03:49:00.692Z"},{"id":1560,"locale":"ru","published_at":"2025-02-21T03:49:00.692Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Introducing_Deep_Searcher_A_Local_Open_Source_Deep_Research_613cbb07b9.png","belong":"blog","authorNames":["Stefan Webb"]},{"id":"blog-1408","title":"Proactive Monitoring for Vector Database: Zilliz Cloud Integrates with Datadog","image":{"id":6277,"url":"https://assets.zilliz.com/Proactive_Observability_for_Vector_Database_Zilliz_Cloud_Integrates_with_Datadog_ada4726505.png"},"display_time":"Feb 20, 2025","deploy_time":null,"url":"proactive-observability-for-vector-database-zilliz-cloud-integrates-with-datadog","abstract":"we're excited to announce Zilliz Cloud's integration with Datadog, enabling comprehensive monitoring and observability for your vector database deployments with your favorite monitoring tool.","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":76,"name":"Steffi Li","author_tags":"Director of Product Marketing","published_at":"2023-07-13T17:18:42.023Z","created_by":18,"updated_by":18,"created_at":"2023-07-13T17:16:54.449Z","updated_at":"2023-07-13T17:18:42.070Z","home_page":null,"home_page_link":null,"self_intro":"Steffi is the Director of Product Marketing at Zilliz, with prior experience leading the GTM strategies for open-source data technologies such as Apache Kafka and Apache Airflow. Passionate about travel, yoga, and non-fiction reading, she brings a balanced and enriched worldview to her professional pursuits.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":3,"localizations":[{"id":1433,"locale":"ja-JP","published_at":"2025-02-21T10:54:05.378Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Proactive_Observability_for_Vector_Database_Zilliz_Cloud_Integrates_with_Datadog_ada4726505.png","belong":"blog","authorNames":["Steffi Li"]},{"id":"blog-1406","title":"AI Integration in Video Surveillance Tools: Transforming the Industry with Vector Databases","image":{"id":6278,"url":"https://assets.zilliz.com/AI_Integration_in_Video_Surveillance_Tools_Transforming_the_Industry_with_Vector_Databases_cc3df78101.png"},"display_time":"Feb 19, 2025","deploy_time":null,"url":"ai-integration-in-video-surveillance-tools-transforming-the-industry-with-vector-databases","abstract":"Discover how AI and vector databases are revolutionizing video surveillance with real-time analysis, faster threat detection, and intelligent search capabilities for enhanced security.","tags":[{"id":1,"name":"Case Study","published_at":"2021-01-15T10:34:37.316Z","created_by":18,"updated_by":18,"created_at":"2021-01-15T10:34:34.857Z","updated_at":"2021-01-25T10:31:22.499Z","locale":"en"}],"authors":[{"id":36,"name":"Chris Churilo","author_tags":"VP of Marketing","published_at":"2023-04-11T16:51:05.002Z","created_by":18,"updated_by":53,"created_at":"2023-04-11T16:42:46.067Z","updated_at":"2025-01-16T22:35:53.011Z","home_page":"GitHub","home_page_link":"https://github.com/ChrisChurilo","self_intro":"Chris Churilo is the VP of Marketing \u0026 Community at Zilliz where she leads all community, developer relations, and marketing efforts. Prior to Zilliz, Chris was a founding member of the InfluxData’s go to market efforts and helped propel the time series database platform to dominance in the market. In earlier roles she defined and designed a SaaS monitoring solution at Centroid, and prior to that she was the VP of product management at iPass and was the LOB for several cloud services that required her to track the business and operational metrics and analytics to help identify and resolve issues.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":8,"localizations":[{"id":1431,"locale":"ja-JP","published_at":"2025-02-19T19:13:22.177Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/AI_Integration_in_Video_Surveillance_Tools_Transforming_the_Industry_with_Vector_Databases_cc3df78101.png","belong":"blog","authorNames":["Chris Churilo"]},{"id":"learn-491","title":"Getting Started with Audio Data: Processing Techniques and Key Challenges","image":{"id":6323,"url":"https://assets.zilliz.com/Getting_Started_with_Audio_Data_Processing_Techniques_and_Key_Challenges_Learn_More_f57b2d6299.png"},"display_time":"Feb 18, 2025","url":"getting-started-with-audio-data","abstract":"Discover audio data, its characteristics, processing techniques, and key challenges. Learn how to tackle them effectively in AI applications.\n","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":118,"name":" Haziqa Sajid","author_tags":"Freelance Technical Writer","published_at":"2024-03-12T10:25:34.265Z","created_by":18,"updated_by":18,"created_at":"2024-03-12T10:25:31.148Z","updated_at":"2024-07-03T07:58:27.010Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/haziqa-sajid-22b53245/","self_intro":"Digital Storytelling for Data, AI, B2B \u0026 SaaS","repost_to_medium":null,"repost_state":null,"meta_description":" Haziqa Sajid, Freelance Technical Writer","locale":"en"}],"read_time":12,"localizations":[{"id":497,"locale":"ja-JP","published_at":"2025-02-28T18:21:24.562Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Getting_Started_with_Audio_Data_Processing_Techniques_and_Key_Challenges_Learn_More_f57b2d6299.png","belong":"learn","authorNames":[" Haziqa Sajid"]},{"id":"learn-492","title":"Everything You Need to Know About LLM Guardrails","image":{"id":6324,"url":"https://assets.zilliz.com/Everything_You_Need_to_Know_About_LLM_Guardrails_1f7ca14a43.png"},"display_time":"Feb 17, 2025","url":"everything-you-need-to-know-about-llm-guardrails","abstract":"In this blog, we'll examine LLM guardrails, technical systems, and processes designed to ensure LLMs' safe and reliable operation.","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":179,"name":"Simon Mwaniki ","author_tags":null,"published_at":"2024-09-11T00:44:07.918Z","created_by":82,"updated_by":82,"created_at":"2024-09-11T00:44:06.462Z","updated_at":"2024-09-27T22:42:13.512Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":15,"localizations":[{"id":502,"locale":"ja-JP","published_at":"2025-02-28T18:47:04.005Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Everything_You_Need_to_Know_About_LLM_Guardrails_1f7ca14a43.png","belong":"learn","authorNames":["Simon Mwaniki "]},{"id":"blog-1415","title":"Why Deepseek is Waking up AI Giants Like OpenAI And Why You Should Care","image":{"id":6156,"url":"https://assets.zilliz.com/Why_Deepseek_is_Scaring_AI_Giants_Like_Open_AI_And_Why_You_Should_Care_f69522c4e6.png"},"display_time":"Feb 16, 2025","deploy_time":null,"url":"why-deepseek-is-scaring-ai-giants-like-openai","abstract":"Discover how DeepSeek R1's open-source AI model with superior reasoning capabilities and lower costs is disrupting the AI landscape and challenging tech giants like OpenAI.\n","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":158,"name":"Denis Kuria","author_tags":"Freelance Technical Writer","published_at":"2024-05-01T00:39:32.350Z","created_by":18,"updated_by":18,"created_at":"2024-05-01T00:39:30.888Z","updated_at":"2024-07-03T06:50:56.660Z","home_page":null,"home_page_link":null,"self_intro":"Denis is a machine learning engineer who enjoys writing guides to help other developers. He has a bachelor's in computer science and loves hiking and exploring the world.\n","repost_to_medium":null,"repost_state":null,"meta_description":"Denis Kuria is a freelance technical writer at Zilliz. ","locale":"en"}],"read_time":12,"localizations":[{"id":1442,"locale":"ja-JP","published_at":"2025-02-28T21:17:52.105Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Why_Deepseek_is_Scaring_AI_Giants_Like_Open_AI_And_Why_You_Should_Care_f69522c4e6.png","belong":"blog","authorNames":["Denis Kuria"]},{"id":"blog-1414","title":"DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced Multimodal Understanding","image":{"id":6153,"url":"https://assets.zilliz.com/Deep_Seek_VL_2_Mixture_of_Experts_Vision_Language_Models_for_Advanced_Multimodal_Understanding_78a04b44e9.png"},"display_time":"Feb 15, 2025","deploy_time":"2025-02-15T20:00:00.000Z","url":"deepseek-vl2-mixture-of-experts-vision-language-models-for-advanced-multimodal-understanding","abstract":"Explore DeepSeek-VL2, the open-source MoE vision-language model. Discover its architecture, efficient training pipeline, and top-tier performance.\n","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":118,"name":" Haziqa Sajid","author_tags":"Freelance Technical Writer","published_at":"2024-03-12T10:25:34.265Z","created_by":18,"updated_by":18,"created_at":"2024-03-12T10:25:31.148Z","updated_at":"2024-07-03T07:58:27.010Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/haziqa-sajid-22b53245/","self_intro":"Digital Storytelling for Data, AI, B2B \u0026 SaaS","repost_to_medium":null,"repost_state":null,"meta_description":" Haziqa Sajid, Freelance Technical Writer","locale":"en"}],"read_time":13,"localizations":[{"id":1441,"locale":"ja-JP","published_at":"2025-02-28T20:02:46.061Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Deep_Seek_VL_2_Mixture_of_Experts_Vision_Language_Models_for_Advanced_Multimodal_Understanding_78a04b44e9.png","belong":"blog","authorNames":[" Haziqa Sajid"]},{"id":"blog-1412","title":"DeepRAG: Thinking to Retrieval Step by Step for Large Language Models","image":{"id":6279,"url":"https://assets.zilliz.com/Deep_RAG_Thinking_to_Retrieval_Step_by_Step_for_Large_Language_Models_4313ac29bd.png"},"display_time":"Feb 14, 2025","deploy_time":null,"url":"deeprag-thinking-to-retrieval-step-by-step-for-large-language-models","abstract":"In this article, we’ll explore how DeepRAG works, unpack its key components, and show how vector databases like Milvus and Zilliz Cloud can further enhance its retrieval capabilities.\n","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":158,"name":"Denis Kuria","author_tags":"Freelance Technical Writer","published_at":"2024-05-01T00:39:32.350Z","created_by":18,"updated_by":18,"created_at":"2024-05-01T00:39:30.888Z","updated_at":"2024-07-03T06:50:56.660Z","home_page":null,"home_page_link":null,"self_intro":"Denis is a machine learning engineer who enjoys writing guides to help other developers. He has a bachelor's in computer science and loves hiking and exploring the world.\n","repost_to_medium":null,"repost_state":null,"meta_description":"Denis Kuria is a freelance technical writer at Zilliz. ","locale":"en"}],"read_time":15,"localizations":[{"id":1438,"locale":"ja-JP","published_at":"2025-02-26T01:58:28.368Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Deep_RAG_Thinking_to_Retrieval_Step_by_Step_for_Large_Language_Models_4313ac29bd.png","belong":"blog","authorNames":["Denis Kuria"]},{"id":"blog-1676","title":"Vector Databases vs. Hierarchical Databases","image":{"id":6548,"url":"https://assets.zilliz.com/Vector_Databases_vs_Hierarchical_Databases_ec243c68b2.png"},"display_time":"Feb 12, 2025","deploy_time":null,"url":"vector-database-vs-hierarchical-databases","abstract":"Use a vector database for AI-powered similarity search; use a hierarchical database for organizing data in parent-child relationships with efficient top-down access patterns.","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":176,"name":"Chloe Williams","author_tags":"Technical Writer","published_at":"2024-09-05T07:58:16.265Z","created_by":60,"updated_by":60,"created_at":"2024-09-05T07:58:14.700Z","updated_at":"2024-09-05T07:58:16.284Z","home_page":"","home_page_link":"","self_intro":"Chloe Williams is a technical writer at Zilliz. ","repost_to_medium":null,"repost_state":null,"meta_description":"Chloe Williams, Technical Writer at Zilliz. ","locale":"en"}],"read_time":18,"localizations":[],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Vector_Databases_vs_Hierarchical_Databases_ec243c68b2.png","belong":"blog","authorNames":["Chloe Williams"]},{"id":"blog-1404","title":"Zilliz Cloud BYOC Upgrades: Bring Enterprise-Grade Security, Networking Isolation, and More","image":{"id":6280,"url":"https://assets.zilliz.com/Zilliz_Cloud_BYOC_Upgrades_Bring_Enterprise_Grade_Security_Networking_Isolation_and_More_09ee7c32b1.png"},"display_time":"Feb 11, 2025","deploy_time":"2025-02-11T13:00:00.000Z","url":"zilliz-cloud-byoc-upgrades","abstract":"Discover how Zilliz Cloud BYOC brings enterprise-grade security, networking isolation, and infrastructure automation to vector database deployments in AWS","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":76,"name":"Steffi Li","author_tags":"Director of Product Marketing","published_at":"2023-07-13T17:18:42.023Z","created_by":18,"updated_by":18,"created_at":"2023-07-13T17:16:54.449Z","updated_at":"2023-07-13T17:18:42.070Z","home_page":null,"home_page_link":null,"self_intro":"Steffi is the Director of Product Marketing at Zilliz, with prior experience leading the GTM strategies for open-source data technologies such as Apache Kafka and Apache Airflow. Passionate about travel, yoga, and non-fiction reading, she brings a balanced and enriched worldview to her professional pursuits.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":5,"localizations":[{"id":1428,"locale":"ja-JP","published_at":"2025-02-10T17:18:07.662Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Zilliz_Cloud_BYOC_Upgrades_Bring_Enterprise_Grade_Security_Networking_Isolation_and_More_09ee7c32b1.png","belong":"blog","authorNames":["Steffi Li"]},{"id":"blog-1411","title":"Top 5 AI Search Engines to Know in 2025","image":{"id":6117,"url":"https://assets.zilliz.com/Top_5_AI_Search_Engines_to_Know_in_2025_1_6ce958482c.png"},"display_time":"Feb 08, 2025","deploy_time":null,"url":"top-five-ai-search-engines-to-know-in-2025","abstract":"Discover the top AI-powered search engines of 2025, including OpenAI, Google AI, Bing, Perplexity, and Arc Search. Compare features, strengths, and limitations.","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":147,"name":"ShriVarsheni R","author_tags":"Freelance Technical Writer","published_at":"2024-04-24T21:21:57.571Z","created_by":18,"updated_by":18,"created_at":"2024-04-24T21:21:55.818Z","updated_at":"2024-07-03T07:50:17.617Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"ShriVarsheni, Freelance Technical Writer","locale":"en"}],"read_time":10,"localizations":[{"id":1437,"locale":"ja-JP","published_at":"2025-02-26T01:27:24.786Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Top_5_AI_Search_Engines_to_Know_in_2025_1_6ce958482c.png","belong":"blog","authorNames":["ShriVarsheni R"]},{"id":"blog-1677","title":"Vector Databases vs. Spatial Databases","image":{"id":6536,"url":"https://assets.zilliz.com/Vector_DB_vs_Spatial_DB_09b538b4d0.png"},"display_time":"Feb 07, 2025","deploy_time":null,"url":"vector-database-vs-spatial-databases","abstract":"Use a vector database for AI-powered similarity search; use a spatial database for geographic and geometric data analysis and querying.\n","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":176,"name":"Chloe Williams","author_tags":"Technical Writer","published_at":"2024-09-05T07:58:16.265Z","created_by":60,"updated_by":60,"created_at":"2024-09-05T07:58:14.700Z","updated_at":"2024-09-05T07:58:16.284Z","home_page":"","home_page_link":"","self_intro":"Chloe Williams is a technical writer at Zilliz. ","repost_to_medium":null,"repost_state":null,"meta_description":"Chloe Williams, Technical Writer at Zilliz. ","locale":"en"}],"read_time":19,"localizations":[],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Vector_DB_vs_Spatial_DB_09b538b4d0.png","belong":"blog","authorNames":["Chloe Williams"]},{"id":"learn-488","title":"Unlocking Pre-trained Models: A Developer’s Guide to Audio AI Tasks","image":{"id":6325,"url":"https://assets.zilliz.com/Unlocking_Pre_trained_Models_A_Developer_s_Guide_to_Audio_AI_7a56008431.png"},"display_time":"Feb 07, 2025","url":"unlocking-pre-trained-models-developers-guide-to-audio-ai-tasks","abstract":"Learn how to implement pre-trained models for audio AI applications. Explore speech recognition, audio classification, and TTS with practical code examples.","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":178,"name":"Benito Martin","author_tags":null,"published_at":"2024-09-10T18:31:20.152Z","created_by":82,"updated_by":82,"created_at":"2024-09-10T18:30:36.499Z","updated_at":"2024-10-02T17:35:02.538Z","home_page":null,"home_page_link":null,"self_intro":"Freelance Technical Writer","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":12,"localizations":[{"id":498,"locale":"ja-JP","published_at":"2025-02-07T23:26:11.332Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Unlocking_Pre_trained_Models_A_Developer_s_Guide_to_Audio_AI_7a56008431.png","belong":"learn","authorNames":["Benito Martin"]},{"id":"blog-1418","title":"DeepSeek vs. OpenAI: A Battle of Innovation in Modern AI","image":{"id":6168,"url":"https://assets.zilliz.com/Deep_Seek_vs_Open_AI_A_Battle_of_Innovation_in_Modern_AI_f5f6282a7a.png"},"display_time":"Feb 06, 2025","deploy_time":null,"url":"deepseek-vs-openai-battle-of-innovation-in-modern-ai","abstract":"Compare OpenAI's o1 and o3-mini with DeepSeek R1's open-source alternative. Discover which AI model offers the best balance of reasoning capabilities and cost efficiency.\n","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":178,"name":"Benito Martin","author_tags":null,"published_at":"2024-09-10T18:31:20.152Z","created_by":82,"updated_by":82,"created_at":"2024-09-10T18:30:36.499Z","updated_at":"2024-10-02T17:35:02.538Z","home_page":null,"home_page_link":null,"self_intro":"Freelance Technical Writer","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":9,"localizations":[{"id":1443,"locale":"ja-JP","published_at":"2025-02-28T22:26:21.860Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Deep_Seek_vs_Open_AI_A_Battle_of_Innovation_in_Modern_AI_f5f6282a7a.png","belong":"blog","authorNames":["Benito Martin"]},{"id":"learn-487","title":"Top 10 Most Used Embedding Models for Audio Data ","image":{"id":6009,"url":"https://assets.zilliz.com/Top_10_Most_Used_Embedding_Models_for_Audio_Data_3_53cb746b73.png"},"display_time":"Feb 06, 2025","url":"top-10-most-used-embedding-models-for-audio-data","abstract":"Explore the 10 most popular audio embedding models including Wav2Vec 2.0, VGGish, and OpenL3. Learn how they transform sound into vectors for AI applications","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":158,"name":"Denis Kuria","author_tags":"Freelance Technical Writer","published_at":"2024-05-01T00:39:32.350Z","created_by":18,"updated_by":18,"created_at":"2024-05-01T00:39:30.888Z","updated_at":"2024-07-03T06:50:56.660Z","home_page":null,"home_page_link":null,"self_intro":"Denis is a machine learning engineer who enjoys writing guides to help other developers. He has a bachelor's in computer science and loves hiking and exploring the world.\n","repost_to_medium":null,"repost_state":null,"meta_description":"Denis Kuria is a freelance technical writer at Zilliz. ","locale":"en"}],"read_time":15,"localizations":[{"id":499,"locale":"ja-JP","published_at":"2025-02-07T02:02:59.846Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Top_10_Most_Used_Embedding_Models_for_Audio_Data_3_53cb746b73.png","belong":"learn","authorNames":["Denis Kuria"]},{"id":"learn-486","title":"Building RAG with Dify and Milvus","image":{"id":6326,"url":"https://assets.zilliz.com/Building_RAG_with_Dify_and_Milvus_d823ca333b.png"},"display_time":"Feb 05, 2025","url":"building-rag-with-dify-and-milvus","abstract":"Learn how to build Retrieval Augmented Generation (RAG) applications using Dify for orchestration and Milvus for vector storage in this step-by-step guide.","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":125,"name":"Ruben Winastwan","author_tags":"Freelance Technical Writer","published_at":"2024-03-26T09:16:27.310Z","created_by":18,"updated_by":18,"created_at":"2024-03-26T09:16:24.498Z","updated_at":"2024-07-03T07:56:29.256Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Ruben Winastwan, Freelance Technical Writer","locale":"en"}],"read_time":11,"localizations":[{"id":496,"locale":"ja-JP","published_at":"2025-02-06T23:53:44.102Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Building_RAG_with_Dify_and_Milvus_d823ca333b.png","belong":"learn","authorNames":["Ruben Winastwan"]},{"id":"blog-1402","title":"Knowledge Injection in LLMs: Fine-Tuning and RAG","image":{"id":5982,"url":"https://assets.zilliz.com/Fine_Tuning_or_Retrieval_Comparing_Knowledge_Injection_in_LL_Ms_f68137f006.png"},"display_time":"Feb 04, 2025","deploy_time":null,"url":"knowledge-injection-in-llms-fine-tuning-and-rag","abstract":"Explore knowledge injection techniques like fine-tuning and RAG. Compare their effectiveness in improving accuracy, knowledge retention, and task performance.\n","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":118,"name":" Haziqa Sajid","author_tags":"Freelance Technical Writer","published_at":"2024-03-12T10:25:34.265Z","created_by":18,"updated_by":18,"created_at":"2024-03-12T10:25:31.148Z","updated_at":"2024-07-03T07:58:27.010Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/haziqa-sajid-22b53245/","self_intro":"Digital Storytelling for Data, AI, B2B \u0026 SaaS","repost_to_medium":null,"repost_state":null,"meta_description":" Haziqa Sajid, Freelance Technical Writer","locale":"en"}],"read_time":15,"localizations":[{"id":1426,"locale":"ja-JP","published_at":"2025-02-07T01:01:59.280Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Fine_Tuning_or_Retrieval_Comparing_Knowledge_Injection_in_LL_Ms_f68137f006.png","belong":"blog","authorNames":[" Haziqa Sajid"]},{"id":"blog-1405","title":"Why DeepSeek V3 is Taking the AI World by Storm: A Developer’s Perspective","image":{"id":6010,"url":"https://assets.zilliz.com/Why_Deep_Seek_is_Taking_the_AI_World_by_Storm_e417aeb805.png"},"display_time":"Feb 03, 2025","deploy_time":null,"url":"why-deepseek-v3-is-taking-the-ai-world-by-storm","abstract":"Explore how DeepSeek V3 achieves GPT-4 level performance at fraction of the cost. Learn about MLA, MoE, and MTP innovations driving this open-source breakthrough.","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":125,"name":"Ruben Winastwan","author_tags":"Freelance Technical Writer","published_at":"2024-03-26T09:16:27.310Z","created_by":18,"updated_by":18,"created_at":"2024-03-26T09:16:24.498Z","updated_at":"2024-07-03T07:56:29.256Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Ruben Winastwan, Freelance Technical Writer","locale":"en"}],"read_time":12,"localizations":[{"id":1429,"locale":"ja-JP","published_at":"2025-02-08T00:06:25.770Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Why_Deep_Seek_is_Taking_the_AI_World_by_Storm_e417aeb805.png","belong":"blog","authorNames":["Ruben Winastwan"]},{"id":"blog-1680","title":"Vector Databases vs. NoSQL Databases","image":{"id":6549,"url":"https://assets.zilliz.com/Vector_Databases_vs_No_SQL_Databases_e724b3261a.png"},"display_time":"Feb 03, 2025","deploy_time":null,"url":"vector-database-vs-nosql-databases","abstract":"Use a vector database for AI-powered similarity search; use NoSQL databases for flexibility, scalability, and diverse non-relational data storage needs.","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":176,"name":"Chloe Williams","author_tags":"Technical Writer","published_at":"2024-09-05T07:58:16.265Z","created_by":60,"updated_by":60,"created_at":"2024-09-05T07:58:14.700Z","updated_at":"2024-09-05T07:58:16.284Z","home_page":"","home_page_link":"","self_intro":"Chloe Williams is a technical writer at Zilliz. ","repost_to_medium":null,"repost_state":null,"meta_description":"Chloe Williams, Technical Writer at Zilliz. ","locale":"en"}],"read_time":18,"localizations":[],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Vector_Databases_vs_No_SQL_Databases_e724b3261a.png","belong":"blog","authorNames":["Chloe Williams"]},{"id":"blog-1410","title":"Long List of Awesome DeepSeek Integrations You Should Know","image":{"id":6119,"url":"https://assets.zilliz.com/Long_List_Of_Awesome_Deepseek_Integrations_You_Should_Know_1_b4f8cfea6d.png"},"display_time":"Feb 02, 2025","deploy_time":null,"url":"long-list-of-awesome-deepseek-integrations-you-should-know","abstract":"Discover how DeepSeek's affordable AI ecosystem challenges Silicon Valley giants with powerful integrations for developers and businesses—from RAG systems to productivity tools, all at 90% lower cost.\n","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":310,"name":"Wania Shafqat","author_tags":"AI Developer \u0026 Technical Writer\n","published_at":"2025-02-25T23:50:41.682Z","created_by":82,"updated_by":82,"created_at":"2025-02-25T23:50:39.840Z","updated_at":"2025-02-25T23:50:41.710Z","home_page":null,"home_page_link":null,"self_intro":"Wania is a Computer Science graduate specializing in Artificial Intelligence and Cyber Security. Her work reflects her passion for adversarial machine learning and the AI ecosystem. When she’s not coding, you’ll find her writing articles to help fellow developers.\n\n","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":8,"localizations":[{"id":1436,"locale":"ja-JP","published_at":"2025-02-26T00:05:50.748Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Long_List_Of_Awesome_Deepseek_Integrations_You_Should_Know_1_b4f8cfea6d.png","belong":"blog","authorNames":["Wania Shafqat"]},{"id":"learn-494","title":"Scaling Audio Similarity Search with Vector Databases","image":{"id":6327,"url":"https://assets.zilliz.com/Scaling_Audio_Similarity_Search_with_Vector_Databases_8927243091.png"},"display_time":"Feb 02, 2025","url":"scaling-audio-similarity-search-with-vector-databases","abstract":"Discover how vector databases like Milvus and Zilliz Cloud enable efficient audio similarity search at scale, transforming music recommendations and audio retrieval applications.\n","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":170,"name":"Yesha Shastri","author_tags":"Freelance Technical Writer in AI/ML","published_at":"2024-07-29T08:44:59.761Z","created_by":18,"updated_by":18,"created_at":"2024-07-29T08:44:38.291Z","updated_at":"2024-07-29T08:44:59.820Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/yeshashastri/","self_intro":"Yesha Shastri, Freelance Technical Writer in AI/ML","repost_to_medium":null,"repost_state":null,"meta_description":"Yesha Shastri, Freelance Technical Writer","locale":"en"}],"read_time":9,"localizations":[{"id":503,"locale":"ja-JP","published_at":"2025-02-28T22:36:15.152Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Scaling_Audio_Similarity_Search_with_Vector_Databases_8927243091.png","belong":"learn","authorNames":["Yesha Shastri"]},{"id":"blog-1398","title":"Empowering Innovation: Highlights from the Women in AI RAG Hackathon","image":{"id":5925,"url":"https://assets.zilliz.com/Women_in_AI_RAG_hackathon_2_d805e71eaa.png"},"display_time":"Jan 30, 2025","deploy_time":null,"url":"2025-women-in-ai-rag-hackathon-highlights","abstract":"Over the course of the day, teams built working RAG-powered applications using the Milvus vector database—many of them solving real-world problems in healthcare, legal access, sustainability, and more—all within just a few hours.\n","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":37,"name":"Emily Kurze","author_tags":"Director of Marketing Operations","published_at":"2023-04-11T16:55:11.838Z","created_by":18,"updated_by":18,"created_at":"2023-04-11T16:55:07.625Z","updated_at":"2024-04-29T03:28:13.160Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/emilykurze/","self_intro":"Emily Kurze is the Director of Marketing at Zilliz. ","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":5,"localizations":[{"id":1422,"locale":"ja-JP","published_at":"2025-01-31T17:19:11.436Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Women_in_AI_RAG_hackathon_2_d805e71eaa.png","belong":"blog","authorNames":["Emily Kurze"]},{"id":"blog-1403","title":"Multimodal Pipelines for AI Applications","image":{"id":6281,"url":"https://assets.zilliz.com/Multimodal_Pipelines_for_AI_Apps_Journey_To_Day_2_c9542444a8.png"},"display_time":"Jan 29, 2025","deploy_time":null,"url":"multimodal-pipelines-for-ai-applications","abstract":"Learn how to build scalable multimodal AI pipelines using Datavolo and Milvus. Discover best practices for handling unstructured data and implementing RAG systems.","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":118,"name":" Haziqa Sajid","author_tags":"Freelance Technical Writer","published_at":"2024-03-12T10:25:34.265Z","created_by":18,"updated_by":18,"created_at":"2024-03-12T10:25:31.148Z","updated_at":"2024-07-03T07:58:27.010Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/haziqa-sajid-22b53245/","self_intro":"Digital Storytelling for Data, AI, B2B \u0026 SaaS","repost_to_medium":null,"repost_state":null,"meta_description":" Haziqa Sajid, Freelance Technical Writer","locale":"en"}],"read_time":13,"localizations":[{"id":1427,"locale":"ja-JP","published_at":"2025-02-07T01:10:05.900Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Multimodal_Pipelines_for_AI_Apps_Journey_To_Day_2_c9542444a8.png","belong":"blog","authorNames":[" Haziqa Sajid"]},{"id":"blog-1678","title":"Vector Databases vs. In-Memory Databases","image":{"id":6545,"url":"https://assets.zilliz.com/Vector_DB_vs_In_Memory_DB_d4a5b93459.png"},"display_time":"Jan 27, 2025","deploy_time":null,"url":"vector-database-vs-in-memory-databases","abstract":"Use a vector database for AI-powered similarity search; use an in-memory database for ultra-low latency and high-throughput data access.","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":176,"name":"Chloe Williams","author_tags":"Technical Writer","published_at":"2024-09-05T07:58:16.265Z","created_by":60,"updated_by":60,"created_at":"2024-09-05T07:58:14.700Z","updated_at":"2024-09-05T07:58:16.284Z","home_page":"","home_page_link":"","self_intro":"Chloe Williams is a technical writer at Zilliz. ","repost_to_medium":null,"repost_state":null,"meta_description":"Chloe Williams, Technical Writer at Zilliz. ","locale":"en"}],"read_time":19,"localizations":[],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Vector_DB_vs_In_Memory_DB_d4a5b93459.png","belong":"blog","authorNames":["Chloe Williams"]},{"id":"blog-1401","title":"Enhancing AI Reliability Through Fine-Grained Hallucination Detection and Correction with FAVA","image":{"id":5946,"url":"https://assets.zilliz.com/Fine_grained_Hallucination_Detection_and_Editing_for_Language_Models_1_fd0954c7a5.png"},"display_time":"Jan 23, 2025","deploy_time":null,"url":"enhancing-ai-reliability-through-fine-grained-hallucination-detection-and-correction-with-fava","abstract":"In this blog, we will explore the nature of hallucinations, the taxonomy that provides a framework for categorizing them, the FAVABENCH dataset designed for evaluation, and how FAVA detects and corrects errors. \n","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":158,"name":"Denis Kuria","author_tags":"Freelance Technical Writer","published_at":"2024-05-01T00:39:32.350Z","created_by":18,"updated_by":18,"created_at":"2024-05-01T00:39:30.888Z","updated_at":"2024-07-03T06:50:56.660Z","home_page":null,"home_page_link":null,"self_intro":"Denis is a machine learning engineer who enjoys writing guides to help other developers. He has a bachelor's in computer science and loves hiking and exploring the world.\n","repost_to_medium":null,"repost_state":null,"meta_description":"Denis Kuria is a freelance technical writer at Zilliz. ","locale":"en"}],"read_time":13,"localizations":[{"id":1423,"locale":"ja-JP","published_at":"2025-02-03T22:22:29.847Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Fine_grained_Hallucination_Detection_and_Editing_for_Language_Models_1_fd0954c7a5.png","belong":"blog","authorNames":["Denis Kuria"]},{"id":"blog-1400","title":"How to Calculate the Total Cost of Your RAG-Based Solutions","image":{"id":6282,"url":"https://assets.zilliz.com/How_to_Calculate_the_Total_Cost_of_Your_RAG_Based_Solutions_8e8dc55a32.png"},"display_time":"Jan 22, 2025","deploy_time":null,"url":"how-to-calculate-the-total-cost-of-your-rag-based-solutions","abstract":"In this guide, we’ll break down the main components of RAG costs, show you how to calculate these expenses using the Zilliz RAG Cost Calculator, and explore strategies to manage spending efficiently.\n","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":158,"name":"Denis Kuria","author_tags":"Freelance Technical Writer","published_at":"2024-05-01T00:39:32.350Z","created_by":18,"updated_by":18,"created_at":"2024-05-01T00:39:30.888Z","updated_at":"2024-07-03T06:50:56.660Z","home_page":null,"home_page_link":null,"self_intro":"Denis is a machine learning engineer who enjoys writing guides to help other developers. He has a bachelor's in computer science and loves hiking and exploring the world.\n","repost_to_medium":null,"repost_state":null,"meta_description":"Denis Kuria is a freelance technical writer at Zilliz. ","locale":"en"}],"read_time":13,"localizations":[{"id":1425,"locale":"ja-JP","published_at":"2025-02-03T22:10:10.810Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/How_to_Calculate_the_Total_Cost_of_Your_RAG_Based_Solutions_8e8dc55a32.png","belong":"blog","authorNames":["Denis Kuria"]},{"id":"blog-1399","title":"How AI and Vector Databases Are Transforming the Consumer and Retail Sector","image":{"id":6283,"url":"https://assets.zilliz.com/How_AI_and_Vector_Databases_Are_Transforming_the_Consumer_and_Retail_Sector_6d08dc5326.png"},"display_time":"Jan 21, 2025","deploy_time":null,"url":"how-ai-vector-databases-are-transforming-consumer-retail","abstract":"AI and vector databases are transforming retail, enhancing personalization, search, customer service, and operations. Discover how Zilliz Cloud helps drive growth and innovation.\n\n\n\n\n\n\n\n\n","tags":[],"authors":[{"id":36,"name":"Chris Churilo","author_tags":"VP of Marketing","published_at":"2023-04-11T16:51:05.002Z","created_by":18,"updated_by":53,"created_at":"2023-04-11T16:42:46.067Z","updated_at":"2025-01-16T22:35:53.011Z","home_page":"GitHub","home_page_link":"https://github.com/ChrisChurilo","self_intro":"Chris Churilo is the VP of Marketing \u0026 Community at Zilliz where she leads all community, developer relations, and marketing efforts. Prior to Zilliz, Chris was a founding member of the InfluxData’s go to market efforts and helped propel the time series database platform to dominance in the market. In earlier roles she defined and designed a SaaS monitoring solution at Centroid, and prior to that she was the VP of product management at iPass and was the LOB for several cloud services that required her to track the business and operational metrics and analytics to help identify and resolve issues.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":6,"localizations":[{"id":1424,"locale":"ja-JP","published_at":"2025-02-02T22:50:29.373Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/How_AI_and_Vector_Databases_Are_Transforming_the_Consumer_and_Retail_Sector_6d08dc5326.png","belong":"blog","authorNames":["Chris Churilo"]},{"id":"blog-1397","title":"How AI Is Transforming Information Retrieval and What’s Next for You","image":{"id":6006,"url":"https://assets.zilliz.com/How_AI_Is_Transforming_Information_Retrieval_and_What_s_Next_for_You_1_a396cabd27.png"},"display_time":"Jan 20, 2025","deploy_time":null,"url":"how-ai-is-transforming-information-retrieval-and-whats-next-for-you","abstract":"This blog will summarize the monumental changes AI brought to Information Retrieval (IR) in 2024.\n","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":101,"name":"Jiang Chen","author_tags":"Head of Ecosystem and Developer Relations","published_at":"2023-10-16T07:05:20.176Z","created_by":18,"updated_by":82,"created_at":"2023-10-16T07:05:18.702Z","updated_at":"2024-09-10T17:33:55.053Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/jiang-0616/","self_intro":"Jiang is currently Head of Ecosystem and Developer Relations at Zilliz. He has years of experience in data infrastructures and cloud security. Before joining Zilliz, he had previously served as a tech lead and product manager at Google, where he led the development of web-scale semantic understanding and search indexing that powers innovative search products such as short video search. He has extensive industry experience handling massive unstructured data and multimedia content retrieval. He has also worked on cloud authorization systems and research on data privacy technologies. Jiang holds a Master's degree in Computer Science from the University of Michigan.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":7,"localizations":[{"id":1430,"locale":"ja-JP","published_at":"2025-01-29T22:29:55.863Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/How_AI_Is_Transforming_Information_Retrieval_and_What_s_Next_for_You_1_a396cabd27.png","belong":"blog","authorNames":["Jiang Chen"]},{"id":"blog-1396","title":"3 Key Patterns to Building Multimodal RAG: A Comprehensive Guide ","image":{"id":6284,"url":"https://assets.zilliz.com/3_Key_Patterns_to_Building_Multimodal_RAG_A_Comprehensive_Guide_3_98e228cef7.png"},"display_time":"Jan 19, 2025","deploy_time":null,"url":"three-key-patterns-to-building-multimodal-rag-comprehensive-guide","abstract":"These multimodal RAG patterns include grounding all modalities into a primary modality, embedding them into a unified vector space, or employing hybrid retrieval with raw data access. \n","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":125,"name":"Ruben Winastwan","author_tags":"Freelance Technical Writer","published_at":"2024-03-26T09:16:27.310Z","created_by":18,"updated_by":18,"created_at":"2024-03-26T09:16:24.498Z","updated_at":"2024-07-03T07:56:29.256Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Ruben Winastwan, Freelance Technical Writer","locale":"en"}],"read_time":12,"localizations":[{"id":1421,"locale":"ja-JP","published_at":"2025-01-29T20:06:52.585Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/3_Key_Patterns_to_Building_Multimodal_RAG_A_Comprehensive_Guide_3_98e228cef7.png","belong":"blog","authorNames":["Ruben Winastwan"]},{"id":"blog-1395","title":"The AI Revolution in Marketing: How Vector Databases Are Unlocking True Personalization","image":{"id":6328,"url":"https://assets.zilliz.com/AI_Marketing_Software_90995c42cf.png"},"display_time":"Jan 19, 2025","deploy_time":null,"url":"ai-marketing-vector-databases-personalization","abstract":"Explore how vector databases and AI are transforming marketing platforms, enabling real-time personalization and predictive analytics while balancing automation with creativity.\n\n","tags":[],"authors":[{"id":36,"name":"Chris Churilo","author_tags":"VP of Marketing","published_at":"2023-04-11T16:51:05.002Z","created_by":18,"updated_by":53,"created_at":"2023-04-11T16:42:46.067Z","updated_at":"2025-01-16T22:35:53.011Z","home_page":"GitHub","home_page_link":"https://github.com/ChrisChurilo","self_intro":"Chris Churilo is the VP of Marketing \u0026 Community at Zilliz where she leads all community, developer relations, and marketing efforts. Prior to Zilliz, Chris was a founding member of the InfluxData’s go to market efforts and helped propel the time series database platform to dominance in the market. In earlier roles she defined and designed a SaaS monitoring solution at Centroid, and prior to that she was the VP of product management at iPass and was the LOB for several cloud services that required her to track the business and operational metrics and analytics to help identify and resolve issues.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":8,"localizations":[{"id":1448,"locale":"ja-JP","published_at":"2025-01-29T02:39:23.532Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/AI_Marketing_Software_90995c42cf.png","belong":"blog","authorNames":["Chris Churilo"]},{"id":"blog-1393","title":"Producing Structured Outputs from LLMs with Constrained Sampling","image":{"id":6285,"url":"https://assets.zilliz.com/Constrained_Sampling_from_Large_Language_Models_Producing_Structured_Output_7987eb34c7.png"},"display_time":"Jan 18, 2025","deploy_time":null,"url":"producing-structured-outputs-from-llms-with-constrained-sampling","abstract":"Discuss the role of semantic search in processing unstructured data, how finite state machines enable reliable generation, and practical implementations using modern tools for structured outputs from LLMs. \n","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":179,"name":"Simon Mwaniki ","author_tags":null,"published_at":"2024-09-11T00:44:07.918Z","created_by":82,"updated_by":82,"created_at":"2024-09-11T00:44:06.462Z","updated_at":"2024-09-27T22:42:13.512Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":9,"localizations":[{"id":1449,"locale":"ja-JP","published_at":"2025-01-24T19:16:33.589Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Constrained_Sampling_from_Large_Language_Models_Producing_Structured_Output_7987eb34c7.png","belong":"blog","authorNames":["Simon Mwaniki "]},{"id":"blog-1392","title":"Insights into LLM Security from the World’s Largest Red Team","image":{"id":6286,"url":"https://assets.zilliz.com/Insights_into_LLM_Security_from_the_World_s_Largest_Red_Team_6f3e75a804.png"},"display_time":"Jan 17, 2025","deploy_time":null,"url":"insights-into-llm-security-from-the-worlds-largest-red-team","abstract":"We will discuss how the Gandalf project revealed LLMs' vulnerabilities to adversarial attacks. Additionally, we will address the role of vector databases in AI security.\n","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":118,"name":" Haziqa Sajid","author_tags":"Freelance Technical Writer","published_at":"2024-03-12T10:25:34.265Z","created_by":18,"updated_by":18,"created_at":"2024-03-12T10:25:31.148Z","updated_at":"2024-07-03T07:58:27.010Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/haziqa-sajid-22b53245/","self_intro":"Digital Storytelling for Data, AI, B2B \u0026 SaaS","repost_to_medium":null,"repost_state":null,"meta_description":" Haziqa Sajid, Freelance Technical Writer","locale":"en"}],"read_time":8,"localizations":[{"id":1446,"locale":"ja-JP","published_at":"2025-01-24T18:40:23.600Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Insights_into_LLM_Security_from_the_World_s_Largest_Red_Team_6f3e75a804.png","belong":"blog","authorNames":[" Haziqa Sajid"]},{"id":"learn-485","title":"Teaching LLMs to Rank Better: The Power of Fine-Grained Relevance Scoring","image":{"id":5875,"url":"https://assets.zilliz.com/Teaching_LL_Ms_to_Rank_Better_The_Power_of_Fine_Grained_Relevance_Scoring_25ed3a9913.png"},"display_time":"Jan 16, 2025","url":"teaching-llms-to-rank-better-the-power-of-fine-grained-relevance-scoring","abstract":"We’ll explore the limitations of binary relevance labels, how fine-grained relevance scoring works, and why it’s a game-changer for zero-shot text rankers\n","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":158,"name":"Denis Kuria","author_tags":"Freelance Technical Writer","published_at":"2024-05-01T00:39:32.350Z","created_by":18,"updated_by":18,"created_at":"2024-05-01T00:39:30.888Z","updated_at":"2024-07-03T06:50:56.660Z","home_page":null,"home_page_link":null,"self_intro":"Denis is a machine learning engineer who enjoys writing guides to help other developers. He has a bachelor's in computer science and loves hiking and exploring the world.\n","repost_to_medium":null,"repost_state":null,"meta_description":"Denis Kuria is a freelance technical writer at Zilliz. ","locale":"en"}],"read_time":10,"localizations":[{"id":495,"locale":"ja-JP","published_at":"2025-01-24T17:49:10.176Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Teaching_LL_Ms_to_Rank_Better_The_Power_of_Fine_Grained_Relevance_Scoring_25ed3a9913.png","belong":"learn","authorNames":["Denis Kuria"]},{"id":"blog-813","title":"Empowering Women in AI: RAG Hackathon at Stanford","image":{"id":5853,"url":"https://assets.zilliz.com/Women_in_AI_RAG_hackathon_1_16c7377649.png"},"display_time":"Jan 15, 2025","deploy_time":null,"url":"2025-women-in-ai-rag-hackathon-stanford","abstract":"Empower and celebrate women in AI at the Women in AI RAG Hackathon at Stanford. Engage with experts, build innovative AI projects, and compete for prizes. \n","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":37,"name":"Emily Kurze","author_tags":"Director of Marketing Operations","published_at":"2023-04-11T16:55:11.838Z","created_by":18,"updated_by":18,"created_at":"2023-04-11T16:55:07.625Z","updated_at":"2024-04-29T03:28:13.160Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/emilykurze/","self_intro":"Emily Kurze is the Director of Marketing at Zilliz. ","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":3,"localizations":[{"id":886,"locale":"ja-JP","published_at":"2025-01-21T22:07:39.744Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Women_in_AI_RAG_hackathon_1_16c7377649.png","belong":"blog","authorNames":["Emily Kurze"]},{"id":"blog-814","title":"RocketQA: Optimized Dense Passage Retrieval for Open-Domain Question Answering","image":{"id":6287,"url":"https://assets.zilliz.com/Rocket_QA_An_Optimized_Training_Approach_to_Dense_Passage_Retrieval_for_Open_Domain_Question_Answering_202f7cd451.png"},"display_time":"Jan 14, 2025","deploy_time":null,"url":"rocketqa-optimized-dense-passage-retrieval-for-open-domain-question-answering","abstract":"RocketQA is a highly optimized dense passage retrieval framework designed to enhance open-domain question-answering (QA) systems. ","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":158,"name":"Denis Kuria","author_tags":"Freelance Technical Writer","published_at":"2024-05-01T00:39:32.350Z","created_by":18,"updated_by":18,"created_at":"2024-05-01T00:39:30.888Z","updated_at":"2024-07-03T06:50:56.660Z","home_page":null,"home_page_link":null,"self_intro":"Denis is a machine learning engineer who enjoys writing guides to help other developers. He has a bachelor's in computer science and loves hiking and exploring the world.\n","repost_to_medium":null,"repost_state":null,"meta_description":"Denis Kuria is a freelance technical writer at Zilliz. ","locale":"en"}],"read_time":10,"localizations":[{"id":893,"locale":"ja-JP","published_at":"2025-01-21T22:15:52.867Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Rocket_QA_An_Optimized_Training_Approach_to_Dense_Passage_Retrieval_for_Open_Domain_Question_Answering_202f7cd451.png","belong":"blog","authorNames":["Denis Kuria"]},{"id":"blog-811","title":"Beyond PGVector: When Your Vector Database Needs a Formula 1 Upgrade","image":{"id":6288,"url":"https://assets.zilliz.com/Beyond_PG_Vector_When_Your_Vector_Database_Needs_a_Formula_1_Upgrade_bd75d834fc.png"},"display_time":"Jan 13, 2025","deploy_time":null,"url":"beyond-pgvector-when-your-vectordb-need-a-formula-one-upgrade","abstract":"This blog explores why Postgres, with its vector search add-on, pgvector, works well for smaller projects and simpler use cases but reaches its limits for large-scale vector search. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":115,"name":"Stephen Batifol","author_tags":"Developer Advocate ","published_at":"2024-03-07T03:46:04.655Z","created_by":18,"updated_by":18,"created_at":"2024-03-07T03:46:02.457Z","updated_at":"2024-07-18T15:56:42.529Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/stephen-batifol/","self_intro":"Stephen Batifol is a Developer Advocate at Zilliz. He previously worked as a Machine Learning Engineer at Wolt, where he was working on the ML Platform and as a Data Scientist at Brevo. Stephen studied Computer Science and Artificial Intelligence. He enjoys dancing and surfing. \n","repost_to_medium":null,"repost_state":null,"meta_description":"Stephen Batifol is a Developer Advocate at Zilliz.","locale":"en"}],"read_time":6,"localizations":[{"id":836,"locale":"ja-JP","published_at":"2025-01-13T08:03:26.123Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Beyond_PG_Vector_When_Your_Vector_Database_Needs_a_Formula_1_Upgrade_bd75d834fc.png","belong":"blog","authorNames":["Stephen Batifol"]},{"id":"blog-810","title":"Semantic Search vs. Lexical Search vs. Full-text Search","image":{"id":5810,"url":"https://assets.zilliz.com/Semantic_search_vs_full_text_search_vs_lexical_search_531a82400c.png"},"display_time":"Jan 10, 2025","deploy_time":null,"url":"semantic-search-vs-lexical-search-vs-full-text-search","abstract":"Lexical search offers exact term matching; full-text search allows for fuzzy matching; semantic search understands context and intent.","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":125,"name":"Ruben Winastwan","author_tags":"Freelance Technical Writer","published_at":"2024-03-26T09:16:27.310Z","created_by":18,"updated_by":18,"created_at":"2024-03-26T09:16:24.498Z","updated_at":"2024-07-03T07:56:29.256Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Ruben Winastwan, Freelance Technical Writer","locale":"en"}],"read_time":10,"localizations":[{"id":830,"locale":"ja-JP","published_at":"2025-01-13T07:54:20.968Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Semantic_search_vs_full_text_search_vs_lexical_search_531a82400c.png","belong":"blog","authorNames":["Ruben Winastwan"]},{"id":"blog-809","title":"GPL: Generative Pseudo Labeling for Unsupervised Domain Adaptation of Dense Retrieval","image":{"id":5922,"url":"https://assets.zilliz.com/GPL_Generative_Pseudo_Labeling_for_Unsupervised_Domain_Adaptation_of_Dense_Retrieval_1adcb59bf2.png"},"display_time":"Jan 09, 2025","deploy_time":null,"url":"generative-pseudo-labeling-for-unsupervised-domain-adaptation-of-dense-retrieval","abstract":"GPL is an unsupervised domain adaptation technique for dense retrieval models that combines a query generator with pseudo-labeling. \n","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":118,"name":" Haziqa Sajid","author_tags":"Freelance Technical Writer","published_at":"2024-03-12T10:25:34.265Z","created_by":18,"updated_by":18,"created_at":"2024-03-12T10:25:31.148Z","updated_at":"2024-07-03T07:58:27.010Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/haziqa-sajid-22b53245/","self_intro":"Digital Storytelling for Data, AI, B2B \u0026 SaaS","repost_to_medium":null,"repost_state":null,"meta_description":" Haziqa Sajid, Freelance Technical Writer","locale":"en"}],"read_time":13,"localizations":[{"id":825,"locale":"ja-JP","published_at":"2025-01-11T01:39:45.596Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/GPL_Generative_Pseudo_Labeling_for_Unsupervised_Domain_Adaptation_of_Dense_Retrieval_1adcb59bf2.png","belong":"blog","authorNames":[" Haziqa Sajid"]},{"id":"blog-799","title":"Advancing LLMs: Exploring Native, Advanced, and Modular RAG Approaches","image":{"id":6329,"url":"https://assets.zilliz.com/Advancing_LL_Ms_Exploring_Native_Advanced_and_Modular_RAG_Approaches_2eafab5337.png"},"display_time":"Jan 08, 2025","deploy_time":null,"url":"advancing-llms-native-advanced-modular-rag-approaches","abstract":"This post explores the key components of RAG, its evolution, technical implementation, evaluation methods, and potential for real-world applications. \n","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":158,"name":"Denis Kuria","author_tags":"Freelance Technical Writer","published_at":"2024-05-01T00:39:32.350Z","created_by":18,"updated_by":18,"created_at":"2024-05-01T00:39:30.888Z","updated_at":"2024-07-03T06:50:56.660Z","home_page":null,"home_page_link":null,"self_intro":"Denis is a machine learning engineer who enjoys writing guides to help other developers. He has a bachelor's in computer science and loves hiking and exploring the world.\n","repost_to_medium":null,"repost_state":null,"meta_description":"Denis Kuria is a freelance technical writer at Zilliz. ","locale":"en"}],"read_time":12,"localizations":[{"id":1034,"locale":"ja-JP","published_at":"2025-01-10T22:10:44.590Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Advancing_LL_Ms_Exploring_Native_Advanced_and_Modular_RAG_Approaches_2eafab5337.png","belong":"blog","authorNames":["Denis Kuria"]},{"id":"blog-798","title":"Building Secure RAG Workflows with Chunk-Level Data Partitioning","image":{"id":6330,"url":"https://assets.zilliz.com/Beyond_RAG_Partitions_Per_User_Per_Chunk_Access_Policy_c357e5d373.png"},"display_time":"Jan 07, 2025","deploy_time":null,"url":"beyond-rag-partitions-per-user-per-chunk-access-policy","abstract":"Rob Quiros shared how integrating permissions and authorization into partitions can secure data at the chunk level, addressing privacy concerns.\n","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":170,"name":"Yesha Shastri","author_tags":"Freelance Technical Writer in AI/ML","published_at":"2024-07-29T08:44:59.761Z","created_by":18,"updated_by":18,"created_at":"2024-07-29T08:44:38.291Z","updated_at":"2024-07-29T08:44:59.820Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/yeshashastri/","self_intro":"Yesha Shastri, Freelance Technical Writer in AI/ML","repost_to_medium":null,"repost_state":null,"meta_description":"Yesha Shastri, Freelance Technical Writer","locale":"en"}],"read_time":7,"localizations":[{"id":1028,"locale":"ja-JP","published_at":"2025-01-10T21:10:50.363Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Beyond_RAG_Partitions_Per_User_Per_Chunk_Access_Policy_c357e5d373.png","belong":"blog","authorNames":["Yesha Shastri"]},{"id":"blog-1679","title":"Vector Databases vs. NewSQL Databases","image":{"id":6542,"url":"https://assets.zilliz.com/Vector_DB_vs_New_SQL_DB_ff96d9eb4c.png"},"display_time":"Jan 06, 2025","deploy_time":null,"url":"vector-database-vs-newsql-databases","abstract":"Use a vector database for AI-powered similarity search; use a NewSQL database for scalable transactional workloads requiring strong consistency and relational capabilities. ","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":176,"name":"Chloe Williams","author_tags":"Technical Writer","published_at":"2024-09-05T07:58:16.265Z","created_by":60,"updated_by":60,"created_at":"2024-09-05T07:58:14.700Z","updated_at":"2024-09-05T07:58:16.284Z","home_page":"","home_page_link":"","self_intro":"Chloe Williams is a technical writer at Zilliz. ","repost_to_medium":null,"repost_state":null,"meta_description":"Chloe Williams, Technical Writer at Zilliz. ","locale":"en"}],"read_time":18,"localizations":[],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Vector_DB_vs_New_SQL_DB_ff96d9eb4c.png","belong":"blog","authorNames":["Chloe Williams"]},{"id":"learn-285","title":"What is Annoy?","image":{"id":6339,"url":"https://assets.zilliz.com/What_is_Annoy_f6457acf5f.png"},"display_time":"Jan 06, 2025","url":"what-is-annoy","abstract":"Annoy is a lightweight, open-source library designed for fast, approximate nearest-neighbor searches in high-dimensional vector spaces.\n","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":147,"name":"ShriVarsheni R","author_tags":"Freelance Technical Writer","published_at":"2024-04-24T21:21:57.571Z","created_by":18,"updated_by":18,"created_at":"2024-04-24T21:21:55.818Z","updated_at":"2024-07-03T07:50:17.617Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"ShriVarsheni, Freelance Technical Writer","locale":"en"},{"id":45,"name":"Fendy Feng","author_tags":"Technical Marketing Writer","published_at":"2023-05-16T01:36:15.102Z","created_by":18,"updated_by":18,"created_at":"2023-05-16T00:04:12.065Z","updated_at":"2024-04-25T08:37:19.712Z","home_page":"GitHub","home_page_link":"https://www.linkedin.com/in/fendy311/","self_intro":"Fendy Feng is the Technical Marketing Writer at Zilliz. She has extensive experience developing and enhancing the impact of open-source projects in various global markets by producing high-quality, tailored content. Before joining Zilliz, Fendy worked as a Content Strategist at PingCAP, a fast-growing E-Series startup renowned for its open-source distributed SQL database.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":8,"localizations":[{"id":302,"locale":"ja-JP","published_at":"2025-01-10T19:56:54.424Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/What_is_Annoy_f6457acf5f.png","belong":"learn","authorNames":["ShriVarsheni R","Fendy Feng"]},{"id":"learn-284","title":"Spotting LLMs With Binoculars: Zero-Shot Detection of Machine-Generated Text","image":{"id":5761,"url":"https://assets.zilliz.com/Spotting_LL_Ms_With_Binoculars_Zero_Shot_Detection_of_Machine_Generated_Text_5025ca03a7.png"},"display_time":"Jan 05, 2025","url":"spotting-llms-with-binoculars-zero-shot-detection-of-machine-generated-text","abstract":"This blog will discuss the growing need to detect machine-generated text, past detection methods, and a new approach: Binoculars. ","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":118,"name":" Haziqa Sajid","author_tags":"Freelance Technical Writer","published_at":"2024-03-12T10:25:34.265Z","created_by":18,"updated_by":18,"created_at":"2024-03-12T10:25:31.148Z","updated_at":"2024-07-03T07:58:27.010Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/haziqa-sajid-22b53245/","self_intro":"Digital Storytelling for Data, AI, B2B \u0026 SaaS","repost_to_medium":null,"repost_state":null,"meta_description":" Haziqa Sajid, Freelance Technical Writer","locale":"en"}],"read_time":13,"localizations":[{"id":298,"locale":"ja-JP","published_at":"2025-01-10T19:32:01.804Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Spotting_LL_Ms_With_Binoculars_Zero_Shot_Detection_of_Machine_Generated_Text_5025ca03a7.png","belong":"learn","authorNames":[" Haziqa Sajid"]},{"id":"blog-797","title":"Augmented SBERT: A Data Augmentation Method to Enhance Bi-Encoders for Pairwise Sentence Scoring","image":{"id":6423,"url":"https://assets.zilliz.com/Augmented_SBERT_Data_Augmentation_Method_for_Improving_Bi_Encoders_for_Pairwise_Sentence_Scoring_Tasks_5e4e135439.png"},"display_time":"Jan 04, 2025","deploy_time":null,"url":"augmented-sbert-data-augmentation-method-for-improving-bi-encoders","abstract":"Discover how Augmented SBERT uses data augmentation to enhance the bi-encoder for pairwise sentence scoring. ","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":118,"name":" Haziqa Sajid","author_tags":"Freelance Technical Writer","published_at":"2024-03-12T10:25:34.265Z","created_by":18,"updated_by":18,"created_at":"2024-03-12T10:25:31.148Z","updated_at":"2024-07-03T07:58:27.010Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/haziqa-sajid-22b53245/","self_intro":"Digital Storytelling for Data, AI, B2B \u0026 SaaS","repost_to_medium":null,"repost_state":null,"meta_description":" Haziqa Sajid, Freelance Technical Writer","locale":"en"}],"read_time":15,"localizations":[{"id":1023,"locale":"ja-JP","published_at":"2025-01-10T19:12:57.433Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Augmented_SBERT_Data_Augmentation_Method_for_Improving_Bi_Encoders_for_Pairwise_Sentence_Scoring_Tasks_5e4e135439.png","belong":"blog","authorNames":[" Haziqa Sajid"]},{"id":"blog-1394","title":"Beyond the Pitch: Vector Databases and AI are Rewriting the Sales Playbook","image":{"id":6332,"url":"https://assets.zilliz.com/Beyond_the_pitch_bc699a676a.png"},"display_time":"Jan 04, 2025","deploy_time":null,"url":"beyond-the-pitch-vector-databases-and-ai-are-rewriting-the-sales-playbook","abstract":"Discover how AI and vector databases are transforming sales platforms with intelligent lead matching, automated workflows, and real-time insights. Learn why 43% of sales teams use AI in 2024.","tags":[],"authors":[{"id":36,"name":"Chris Churilo","author_tags":"VP of Marketing","published_at":"2023-04-11T16:51:05.002Z","created_by":18,"updated_by":53,"created_at":"2023-04-11T16:42:46.067Z","updated_at":"2025-01-16T22:35:53.011Z","home_page":"GitHub","home_page_link":"https://github.com/ChrisChurilo","self_intro":"Chris Churilo is the VP of Marketing \u0026 Community at Zilliz where she leads all community, developer relations, and marketing efforts. Prior to Zilliz, Chris was a founding member of the InfluxData’s go to market efforts and helped propel the time series database platform to dominance in the market. In earlier roles she defined and designed a SaaS monitoring solution at Centroid, and prior to that she was the VP of product management at iPass and was the LOB for several cloud services that required her to track the business and operational metrics and analytics to help identify and resolve issues.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":7,"localizations":[{"id":1450,"locale":"ja-JP","published_at":"2025-01-25T22:40:07.876Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Beyond_the_pitch_bc699a676a.png","belong":"blog","authorNames":["Chris Churilo"]},{"id":"blog-1391","title":"AI Video Editing Software: Revolutionizing Video Tech Through Intelligent Search and Automation","image":{"id":6333,"url":"https://assets.zilliz.com/How_AI_and_Vector_Databases_Are_Transforming_the_Video_Editing_Software_Industry_663ef50b64.png"},"display_time":"Jan 03, 2025","deploy_time":null,"url":"revolutionizing-video-tech-through-intelligent-search-and-automation","abstract":"Learn how to build AI-powered video editing tools using CLIP, ResNet, and vector databases. Discover implementation steps for intelligent search, automated tagging, and scalable video processing.","tags":[],"authors":[{"id":36,"name":"Chris Churilo","author_tags":"VP of Marketing","published_at":"2023-04-11T16:51:05.002Z","created_by":18,"updated_by":53,"created_at":"2023-04-11T16:42:46.067Z","updated_at":"2025-01-16T22:35:53.011Z","home_page":"GitHub","home_page_link":"https://github.com/ChrisChurilo","self_intro":"Chris Churilo is the VP of Marketing \u0026 Community at Zilliz where she leads all community, developer relations, and marketing efforts. Prior to Zilliz, Chris was a founding member of the InfluxData’s go to market efforts and helped propel the time series database platform to dominance in the market. In earlier roles she defined and designed a SaaS monitoring solution at Centroid, and prior to that she was the VP of product management at iPass and was the LOB for several cloud services that required her to track the business and operational metrics and analytics to help identify and resolve issues.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":10,"localizations":[{"id":1447,"locale":"ja-JP","published_at":"2025-01-23T21:11:11.350Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/How_AI_and_Vector_Databases_Are_Transforming_the_Video_Editing_Software_Industry_663ef50b64.png","belong":"blog","authorNames":["Chris Churilo"]},{"id":"blog-796","title":"Top 10 AI Agents to Watch in 2025 🚀","image":{"id":5729,"url":"https://assets.zilliz.com/Top_10_AI_Agents_to_Watch_in_2025_a64d112b6d.png"},"display_time":"Jan 03, 2025","deploy_time":null,"url":"top-10-ai-agents-to-watch-in-2025","abstract":"AI agents are like having a supercharged assistant by your side—analyzing data, making decisions, and seamlessly integrating with tools and environments. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":45,"name":"Fendy Feng","author_tags":"Technical Marketing Writer","published_at":"2023-05-16T01:36:15.102Z","created_by":18,"updated_by":18,"created_at":"2023-05-16T00:04:12.065Z","updated_at":"2024-04-25T08:37:19.712Z","home_page":"GitHub","home_page_link":"https://www.linkedin.com/in/fendy311/","self_intro":"Fendy Feng is the Technical Marketing Writer at Zilliz. She has extensive experience developing and enhancing the impact of open-source projects in various global markets by producing high-quality, tailored content. Before joining Zilliz, Fendy worked as a Content Strategist at PingCAP, a fast-growing E-Series startup renowned for its open-source distributed SQL database.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":10,"localizations":[{"id":1600,"locale":"it","published_at":"2025-01-06T07:01:06.314Z"},{"id":1546,"locale":"ru","published_at":"2025-01-06T07:01:06.314Z"},{"id":1573,"locale":"ko","published_at":"2025-01-06T07:01:06.314Z"},{"id":1627,"locale":"fr","published_at":"2025-01-06T07:01:06.314Z"},{"id":1492,"locale":"es","published_at":"2025-01-06T07:01:06.314Z"},{"id":1465,"locale":"de","published_at":"2025-01-06T07:01:06.314Z"},{"id":1519,"locale":"pt","published_at":"2025-01-06T07:01:06.314Z"},{"id":1018,"locale":"ja-JP","published_at":"2025-01-06T07:01:06.314Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Top_10_AI_Agents_to_Watch_in_2025_a64d112b6d.png","belong":"blog","authorNames":["Fendy Feng"]},{"id":"blog-795","title":"10 Open-Source LLM Frameworks Developers Can’t Ignore in 2025","image":{"id":5700,"url":"https://assets.zilliz.com/Top_10_Open_source_LLM_Frameworks_in_2024_ca4fc3649b.png"},"display_time":"Jan 02, 2025","deploy_time":null,"url":"10-open-source-llm-frameworks-developers-cannot-ignore-in-2025","abstract":"LLM frameworks simplify workflows, enhance performance, and integrate seamlessly with existing systems, helping developers unlock the full potential of LLMs with less effort.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":45,"name":"Fendy Feng","author_tags":"Technical Marketing Writer","published_at":"2023-05-16T01:36:15.102Z","created_by":18,"updated_by":18,"created_at":"2023-05-16T00:04:12.065Z","updated_at":"2024-04-25T08:37:19.712Z","home_page":"GitHub","home_page_link":"https://www.linkedin.com/in/fendy311/","self_intro":"Fendy Feng is the Technical Marketing Writer at Zilliz. She has extensive experience developing and enhancing the impact of open-source projects in various global markets by producing high-quality, tailored content. Before joining Zilliz, Fendy worked as a Content Strategist at PingCAP, a fast-growing E-Series startup renowned for its open-source distributed SQL database.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":13,"localizations":[{"id":1485,"locale":"es","published_at":"2025-01-02T13:51:37.883Z"},{"id":1620,"locale":"fr","published_at":"2025-01-02T13:51:37.883Z"},{"id":916,"locale":"ja-JP","published_at":"2025-01-02T13:51:37.883Z"},{"id":1458,"locale":"de","published_at":"2025-01-02T13:51:37.883Z"},{"id":1512,"locale":"pt","published_at":"2025-01-02T13:51:37.883Z"},{"id":1593,"locale":"it","published_at":"2025-01-02T13:51:37.883Z"},{"id":1566,"locale":"ko","published_at":"2025-01-02T13:51:37.883Z"},{"id":1539,"locale":"ru","published_at":"2025-01-02T13:51:37.883Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Top_10_Open_source_LLM_Frameworks_in_2024_ca4fc3649b.png","belong":"blog","authorNames":["Fendy Feng"]},{"id":"blog-812","title":"AI Integration in the Legal Industry: Revolutionizing Legal Practice with Data-Driven Solutions","image":{"id":6334,"url":"https://assets.zilliz.com/AI_Integration_in_the_Legal_Industry_Revolutionizing_Legal_Practice_with_Data_Driven_Solutions_9b0ab78645.png"},"display_time":"Jan 01, 2025","deploy_time":null,"url":"optimizing-legal-tech-ocr-vector-databases-rag-systems","abstract":"Discover how AI and vector databases are revolutionizing legal work through advanced document processing, semantic search, and contract analysis capabilities.","tags":[{"id":1,"name":"Case Study","published_at":"2021-01-15T10:34:37.316Z","created_by":18,"updated_by":18,"created_at":"2021-01-15T10:34:34.857Z","updated_at":"2021-01-25T10:31:22.499Z","locale":"en"}],"authors":[{"id":36,"name":"Chris Churilo","author_tags":"VP of Marketing","published_at":"2023-04-11T16:51:05.002Z","created_by":18,"updated_by":53,"created_at":"2023-04-11T16:42:46.067Z","updated_at":"2025-01-16T22:35:53.011Z","home_page":"GitHub","home_page_link":"https://github.com/ChrisChurilo","self_intro":"Chris Churilo is the VP of Marketing \u0026 Community at Zilliz where she leads all community, developer relations, and marketing efforts. Prior to Zilliz, Chris was a founding member of the InfluxData’s go to market efforts and helped propel the time series database platform to dominance in the market. In earlier roles she defined and designed a SaaS monitoring solution at Centroid, and prior to that she was the VP of product management at iPass and was the LOB for several cloud services that required her to track the business and operational metrics and analytics to help identify and resolve issues.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":9,"localizations":[{"id":1582,"locale":"ko","published_at":"2025-01-16T20:43:14.416Z"},{"id":1501,"locale":"es","published_at":"2025-01-16T20:43:14.416Z"},{"id":846,"locale":"ja-JP","published_at":"2025-01-16T20:43:14.416Z"},{"id":1636,"locale":"fr","published_at":"2025-01-16T20:43:14.416Z"},{"id":1474,"locale":"de","published_at":"2025-01-16T20:43:14.416Z"},{"id":1609,"locale":"it","published_at":"2025-01-16T20:43:14.416Z"},{"id":1528,"locale":"pt","published_at":"2025-01-16T20:43:14.416Z"},{"id":1555,"locale":"ru","published_at":"2025-01-16T20:43:14.416Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/AI_Integration_in_the_Legal_Industry_Revolutionizing_Legal_Practice_with_Data_Driven_Solutions_9b0ab78645.png","belong":"blog","authorNames":["Chris Churilo"]},{"id":"learn-283","title":"Enhancing RAG with RA-DIT: A Fine-Tuning Approach to Minimize LLM Hallucinations","image":{"id":6335,"url":"https://assets.zilliz.com/RA_DIT_Retrieval_Augmented_Dual_Instruction_Tuning_489e690a23.png"},"display_time":"Dec 23, 2024","url":"enhance-rag-with-radit-fine-tune-approach-to-minimize-llm-hallucinations","abstract":"RA-DIT, or Retrieval-Augmented Dual Instruction Tuning, is a method for fine-tuning both the LLM and the retriever in a RAG setup to enhance overall response quality.","tags":[{"id":73,"name":"Paper Reading","published_at":"2024-08-10T14:40:10.906Z","created_by":60,"updated_by":60,"created_at":"2024-08-10T14:40:09.192Z","updated_at":"2024-08-10T14:40:10.914Z","locale":"en"}],"authors":[{"id":125,"name":"Ruben Winastwan","author_tags":"Freelance Technical Writer","published_at":"2024-03-26T09:16:27.310Z","created_by":18,"updated_by":18,"created_at":"2024-03-26T09:16:24.498Z","updated_at":"2024-07-03T07:56:29.256Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Ruben Winastwan, Freelance Technical Writer","locale":"en"}],"read_time":9,"localizations":[{"id":295,"locale":"ja-JP","published_at":"2025-01-04T15:30:05.674Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/RA_DIT_Retrieval_Augmented_Dual_Instruction_Tuning_489e690a23.png","belong":"learn","authorNames":["Ruben Winastwan"]},{"id":"blog-785","title":"Building RAG Applications with Milvus, Qwen, and vLLM","image":{"id":6336,"url":"https://assets.zilliz.com/Building_RAG_with_Milvus_Qwen_and_v_LLM_2bc2ded69a.png"},"display_time":"Dec 20, 2024","deploy_time":null,"url":"build-rag-app-with-milvus-qwen-and-vllm","abstract":" In this blog, we will explore Qwen and vLLM and how combining both with the Milvus vector database can be used to build a robust RAG system.","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":178,"name":"Benito Martin","author_tags":null,"published_at":"2024-09-10T18:31:20.152Z","created_by":82,"updated_by":82,"created_at":"2024-09-10T18:30:36.499Z","updated_at":"2024-10-02T17:35:02.538Z","home_page":null,"home_page_link":null,"self_intro":"Freelance Technical Writer","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":11,"localizations":[{"id":917,"locale":"ja-JP","published_at":"2024-12-23T04:01:00.213Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Building_RAG_with_Milvus_Qwen_and_v_LLM_2bc2ded69a.png","belong":"blog","authorNames":["Benito Martin"]},{"id":"learn-282","title":"What is Voyager?","image":{"id":6337,"url":"https://assets.zilliz.com/What_is_Voyager_c07dcdc9b0.png"},"display_time":"Dec 19, 2024","url":"what-is-voyager","abstract":"Voyager is an Approximate Nearest Neighbor (ANN) search library optimized for high-dimensional vector data.","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":179,"name":"Simon Mwaniki ","author_tags":null,"published_at":"2024-09-11T00:44:07.918Z","created_by":82,"updated_by":82,"created_at":"2024-09-11T00:44:06.462Z","updated_at":"2024-09-27T22:42:13.512Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":8,"localizations":[{"id":337,"locale":"ja-JP","published_at":"2024-12-20T12:42:41.434Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/What_is_Voyager_c07dcdc9b0.png","belong":"learn","authorNames":["Simon Mwaniki "]},{"id":"blog-753","title":"Leveraging Milvus and Friendli Serverless Endpoints for Advanced RAG and Multi-Modal Queries","image":{"id":6340,"url":"https://assets.zilliz.com/Leveraging_Milvus_and_Friendli_Serverless_Endpoints_for_Advanced_RAG_and_Multi_Modal_Queries_4fc8766c91.png"},"display_time":"Dec 18, 2024","deploy_time":null,"url":"leverage-milvus-and-friendli-ai-for-advanced-rag-and-multi-modal-query","abstract":"This tutorial has demonstrated how to leverage Milvus and Friendli Serverless Endpoints to implement advanced RAG and multi-modal queries. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":194,"name":"Wonook Song","author_tags":"Ph.D.Researcher at FriendliAI\n","published_at":"2024-12-19T03:53:09.376Z","created_by":60,"updated_by":60,"created_at":"2024-12-19T03:52:49.469Z","updated_at":"2024-12-19T03:53:09.401Z","home_page":null,"home_page_link":null,"self_intro":"Wonook is currently doing research and software engineering at FriendliAI. His recent research interest lies in systems for efficiently processing AI workloads, especially for LLM inference, through techniques like parallelization, batching, caching, kernel optimizations, and quantization. Before joining FriendliAI, he received his PhD degree in Computer Science from Seoul National University based on his publications and works on distributed systems for data processing and ML applications, with its focus on resource optimizations in diverse environments.","repost_to_medium":null,"repost_state":null,"meta_description":"Wonook is currently doing research and software engineering at FriendliAI. ","locale":"en"}],"read_time":6,"localizations":[{"id":1032,"locale":"ja-JP","published_at":"2024-12-19T04:02:43.656Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Leveraging_Milvus_and_Friendli_Serverless_Endpoints_for_Advanced_RAG_and_Multi_Modal_Queries_4fc8766c91.png","belong":"blog","authorNames":["Wonook Song"]},{"id":"blog-754","title":"Introducing Milvus 2.5: Built-in Full-Text Search, Advanced Query Optimization, and More 🚀","image":{"id":5570,"url":"https://assets.zilliz.com/What_is_New_in_Milvus_2_5_c4b410d369.png"},"display_time":"Dec 17, 2024","deploy_time":null,"url":"milvus-2-5-built-in-full-text-search-advanced-query-optimization-and-more","abstract":"We're thrilled to announce the release of Milvus 2.5, a significant step in our journey to build the world's most complete solution for all search workloads. ","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":76,"name":"Steffi Li","author_tags":"Director of Product Marketing","published_at":"2023-07-13T17:18:42.023Z","created_by":18,"updated_by":18,"created_at":"2023-07-13T17:16:54.449Z","updated_at":"2023-07-13T17:18:42.070Z","home_page":null,"home_page_link":null,"self_intro":"Steffi is the Director of Product Marketing at Zilliz, with prior experience leading the GTM strategies for open-source data technologies such as Apache Kafka and Apache Airflow. Passionate about travel, yoga, and non-fiction reading, she brings a balanced and enriched worldview to her professional pursuits.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":3,"localizations":[{"id":995,"locale":"ja-JP","published_at":"2024-12-17T09:08:15.790Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/What_is_New_in_Milvus_2_5_c4b410d369.png","belong":"blog","authorNames":["Steffi Li"]},{"id":"learn-281","title":"Unlocking the Power of Many-Shot In-Context Learning in LLMs","image":{"id":5615,"url":"https://assets.zilliz.com/Many_Shot_In_Context_Learning_f540832c7e.png"},"display_time":"Dec 16, 2024","url":"unlock-power-of-many-shot-in-context-learning-in-llms","abstract":"Many-Shot In-Context Learning is an NLP technique where a model generates predictions by observing multiple examples within the input context. ","tags":[{"id":73,"name":"Paper Reading","published_at":"2024-08-10T14:40:10.906Z","created_by":60,"updated_by":60,"created_at":"2024-08-10T14:40:09.192Z","updated_at":"2024-08-10T14:40:10.914Z","locale":"en"}],"authors":[{"id":118,"name":" Haziqa Sajid","author_tags":"Freelance Technical Writer","published_at":"2024-03-12T10:25:34.265Z","created_by":18,"updated_by":18,"created_at":"2024-03-12T10:25:31.148Z","updated_at":"2024-07-03T07:58:27.010Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/haziqa-sajid-22b53245/","self_intro":"Digital Storytelling for Data, AI, B2B \u0026 SaaS","repost_to_medium":null,"repost_state":null,"meta_description":" Haziqa Sajid, Freelance Technical Writer","locale":"en"}],"read_time":13,"localizations":[{"id":335,"locale":"ja-JP","published_at":"2024-12-19T12:46:20.268Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Many_Shot_In_Context_Learning_f540832c7e.png","belong":"learn","authorNames":[" Haziqa Sajid"]},{"id":"blog-762","title":"Build RAG with LangChainJS, Milvus, and Strapi","image":{"id":6341,"url":"https://assets.zilliz.com/Build_RAG_with_Lang_Chain_Milvus_and_Strapi_7034758cd8.png"},"display_time":"Dec 13, 2024","deploy_time":null,"url":"build-rag-with-langchain-milvus-and-strapi","abstract":"A step-by-step guide to building an AI-powered FAQ system using Milvus as the vector database, LangChain.js for workflow coordination, and Strapi for content management","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":158,"name":"Denis Kuria","author_tags":"Freelance Technical Writer","published_at":"2024-05-01T00:39:32.350Z","created_by":18,"updated_by":18,"created_at":"2024-05-01T00:39:30.888Z","updated_at":"2024-07-03T06:50:56.660Z","home_page":null,"home_page_link":null,"self_intro":"Denis is a machine learning engineer who enjoys writing guides to help other developers. He has a bachelor's in computer science and loves hiking and exploring the world.\n","repost_to_medium":null,"repost_state":null,"meta_description":"Denis Kuria is a freelance technical writer at Zilliz. ","locale":"en"}],"read_time":22,"localizations":[{"id":1101,"locale":"ja-JP","published_at":"2024-12-19T12:10:17.985Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Build_RAG_with_Lang_Chain_Milvus_and_Strapi_7034758cd8.png","belong":"blog","authorNames":["Denis Kuria"]},{"id":"blog-761","title":"Matryoshka Representation Learning Explained: The Method Behind OpenAI’s Efficient Text Embeddings","image":{"id":6342,"url":"https://assets.zilliz.com/Matryoshka_Representation_Learning_2cb8ec25e1.png"},"display_time":"Dec 12, 2024","deploy_time":null,"url":"matryoshka-representation-learning-method-behind-openai-text-embeddings","abstract":"Matryoshka Representation Learning (MRL) is a method for generating hierarchical, nested embeddings that capture information at multiple levels of abstraction. ","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":125,"name":"Ruben Winastwan","author_tags":"Freelance Technical Writer","published_at":"2024-03-26T09:16:27.310Z","created_by":18,"updated_by":18,"created_at":"2024-03-26T09:16:24.498Z","updated_at":"2024-07-03T07:56:29.256Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Ruben Winastwan, Freelance Technical Writer","locale":"en"}],"read_time":11,"localizations":[{"id":1098,"locale":"ja-JP","published_at":"2024-12-19T10:06:36.081Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Matryoshka_Representation_Learning_2cb8ec25e1.png","belong":"blog","authorNames":["Ruben Winastwan"]},{"id":"blog-760","title":"Introducing IBM Data Prep Kit for Streamlined LLM Workflows","image":{"id":6343,"url":"https://assets.zilliz.com/Data_Prep_Kit_for_LL_Ms_caf54d85bd.png"},"display_time":"Dec 11, 2024","deploy_time":null,"url":"ibm-data-prep-kit-for-streamlined-llm-workflows","abstract":"The Data Prep Kit (DPK) is an open-source toolkit by IBM Research designed to streamline unstructured data preparation for building AI applications. ","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":170,"name":"Yesha Shastri","author_tags":"Freelance Technical Writer in AI/ML","published_at":"2024-07-29T08:44:59.761Z","created_by":18,"updated_by":18,"created_at":"2024-07-29T08:44:38.291Z","updated_at":"2024-07-29T08:44:59.820Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/yeshashastri/","self_intro":"Yesha Shastri, Freelance Technical Writer in AI/ML","repost_to_medium":null,"repost_state":null,"meta_description":"Yesha Shastri, Freelance Technical Writer","locale":"en"}],"read_time":8,"localizations":[{"id":1038,"locale":"ja-JP","published_at":"2024-12-19T09:50:43.678Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Data_Prep_Kit_for_LL_Ms_caf54d85bd.png","belong":"blog","authorNames":["Yesha Shastri"]},{"id":"blog-759","title":"Building a RAG Application with Milvus and Databricks DBRX","image":{"id":6344,"url":"https://assets.zilliz.com/Building_RAG_with_Milvus_and_Databricks_DBRX_0823423a9e.png"},"display_time":"Dec 10, 2024","deploy_time":null,"url":"build-rag-with-milvus-and-databricks-dbrx","abstract":"In this tutorial, we will explore how to build a robust RAG application by combining the capabilities of Milvus, a scalable vector database optimized for similarity search, and DBRX. ","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":178,"name":"Benito Martin","author_tags":null,"published_at":"2024-09-10T18:31:20.152Z","created_by":82,"updated_by":82,"created_at":"2024-09-10T18:30:36.499Z","updated_at":"2024-10-02T17:35:02.538Z","home_page":null,"home_page_link":null,"self_intro":"Freelance Technical Writer","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":9,"localizations":[{"id":1029,"locale":"ja-JP","published_at":"2024-12-18T22:57:44.175Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Building_RAG_with_Milvus_and_Databricks_DBRX_0823423a9e.png","belong":"blog","authorNames":["Benito Martin"]},{"id":"learn-280","title":"Be like a Goldfish, Don't Memorize! Mitigating Memorization in Generative LLMs","image":{"id":6345,"url":"https://assets.zilliz.com/Be_like_a_Goldfish_Don_t_Memorize_Mitigating_Memorization_in_Generative_LL_Ms_3374850429.png"},"display_time":"Dec 09, 2024","url":"mitigate-memorization-in-generative-LLMs","abstract":"The Goldfish Loss technique prevents the verbatim reproduction of training data in LLM output by modifying the standard next-token prediction training objective.","tags":[{"id":73,"name":"Paper Reading","published_at":"2024-08-10T14:40:10.906Z","created_by":60,"updated_by":60,"created_at":"2024-08-10T14:40:09.192Z","updated_at":"2024-08-10T14:40:10.914Z","locale":"en"}],"authors":[{"id":118,"name":" Haziqa Sajid","author_tags":"Freelance Technical Writer","published_at":"2024-03-12T10:25:34.265Z","created_by":18,"updated_by":18,"created_at":"2024-03-12T10:25:31.148Z","updated_at":"2024-07-03T07:58:27.010Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/haziqa-sajid-22b53245/","self_intro":"Digital Storytelling for Data, AI, B2B \u0026 SaaS","repost_to_medium":null,"repost_state":null,"meta_description":" Haziqa Sajid, Freelance Technical Writer","locale":"en"}],"read_time":12,"localizations":[{"id":332,"locale":"ja-JP","published_at":"2024-12-11T14:40:05.736Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Be_like_a_Goldfish_Don_t_Memorize_Mitigating_Memorization_in_Generative_LL_Ms_3374850429.png","belong":"learn","authorNames":[" Haziqa Sajid"]},{"id":"learn-279","title":"Prover-Verifier Games Improve Legibility of LLM Outputs","image":{"id":6346,"url":"https://assets.zilliz.com/Prover_Verifier_Games_Improve_Legibility_of_LLM_Outputs_3c30b3ba27.png"},"display_time":"Dec 07, 2024","url":"prover-verifier-games-improve-legibility-of-llm-outputs","abstract":"We discussed the checkability training approach to help LLMs generate accurate answers that humans can easily understand and verify. \n","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":125,"name":"Ruben Winastwan","author_tags":"Freelance Technical Writer","published_at":"2024-03-26T09:16:27.310Z","created_by":18,"updated_by":18,"created_at":"2024-03-26T09:16:24.498Z","updated_at":"2024-07-03T07:56:29.256Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Ruben Winastwan, Freelance Technical Writer","locale":"en"}],"read_time":12,"localizations":[{"id":327,"locale":"ja-JP","published_at":"2024-12-11T01:04:19.502Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Prover_Verifier_Games_Improve_Legibility_of_LLM_Outputs_3c30b3ba27.png","belong":"learn","authorNames":["Ruben Winastwan"]},{"id":"blog-722","title":"Deliver RAG Applications 10x Faster with Zilliz and Vectorize","image":{"id":6347,"url":"https://assets.zilliz.com/Deliver_RAG_Applications_10x_Faster_with_Zilliz_and_Vectorize_6592f8f58c.png"},"display_time":"Dec 06, 2024","deploy_time":null,"url":"deliver-rag-apps-10x-faster-with-zilliz-and-vectorize","abstract":"Zilliz Cloud delivers reliable vector storage and search, while Vectorize automates your RAG pipelines and keeps your embeddings up-to-date. ","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":193,"name":"Jamie Ferguson","author_tags":"Jamie Ferguson, Vectorize","published_at":"2024-12-05T05:20:50.425Z","created_by":60,"updated_by":60,"created_at":"2024-12-05T05:20:40.550Z","updated_at":"2024-12-05T05:20:50.449Z","home_page":null,"home_page_link":null,"self_intro":"Jamie Ferguson focuses on shaping the product strategy and driving growth at Vectorize, drawing on her technical background in AI and engineering. She brings a user-centric perspective to help AI engineers build and scale their RAG solutions, making it easier for them to put their unstructured data to work.","repost_to_medium":null,"repost_state":null,"meta_description":"Jamie Ferguson focuses on shaping the product strategy and driving growth at Vectorize, drawing on her technical background in AI and engineering.","locale":"en"}],"read_time":3,"localizations":[{"id":1017,"locale":"ja-JP","published_at":"2024-12-09T03:23:47.566Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Deliver_RAG_Applications_10x_Faster_with_Zilliz_and_Vectorize_6592f8f58c.png","belong":"blog","authorNames":["Jamie Ferguson"]},{"id":"learn-278","title":"Next-Gen Retrieval: How Cross-Encoders and Sparse Matrix Factorization Redefine k-NN Search","image":{"id":6348,"url":"https://assets.zilliz.com/Adaptive_Retrieval_and_Scalable_Indexing_for_k_NN_Search_with_Cross_Encoders_e173adb0fb.png"},"display_time":"Dec 05, 2024","url":"how-cross-encoders-and-sparse-matrix-factorization-redefine-knn-search","abstract":"AXN (Adaptive Cross-Encoder Nearest Neighbor Search) uses a sparse matrix of CE scores to approximate k-NN results, reducing computation while maintaining high accuracy.","tags":[{"id":73,"name":"Paper Reading","published_at":"2024-08-10T14:40:10.906Z","created_by":60,"updated_by":60,"created_at":"2024-08-10T14:40:09.192Z","updated_at":"2024-08-10T14:40:10.914Z","locale":"en"}],"authors":[{"id":118,"name":" Haziqa Sajid","author_tags":"Freelance Technical Writer","published_at":"2024-03-12T10:25:34.265Z","created_by":18,"updated_by":18,"created_at":"2024-03-12T10:25:31.148Z","updated_at":"2024-07-03T07:58:27.010Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/haziqa-sajid-22b53245/","self_intro":"Digital Storytelling for Data, AI, B2B \u0026 SaaS","repost_to_medium":null,"repost_state":null,"meta_description":" Haziqa Sajid, Freelance Technical Writer","locale":"en"}],"read_time":11,"localizations":[{"id":322,"locale":"ja-JP","published_at":"2024-12-09T03:53:28.119Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Adaptive_Retrieval_and_Scalable_Indexing_for_k_NN_Search_with_Cross_Encoders_e173adb0fb.png","belong":"learn","authorNames":[" Haziqa Sajid"]},{"id":"blog-723","title":"Designing Multi-Tenancy RAG with Milvus: Best Practices for Scalable Enterprise Knowledge Bases","image":{"id":6349,"url":"https://assets.zilliz.com/Designing_Multi_Tenancy_RAG_with_Milvus_Best_Practices_for_Scalable_Enterprise_Knowledge_Bases_250996f06b.png"},"display_time":"Dec 04, 2024","deploy_time":null,"url":"build-multi-tenancy-rag-with-milvus-best-practices-part-one","abstract":"We’ve explored how multi-tenancy frameworks play a critical role in the scalability, security, and performance of RAG-powered knowledge bases. ","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":68,"name":"Robert Guo","author_tags":"Director of Product Management","published_at":"2023-06-13T18:34:37.794Z","created_by":18,"updated_by":18,"created_at":"2023-06-08T17:01:36.444Z","updated_at":"2024-04-16T02:44:46.685Z","home_page":"GitHub","home_page_link":"https://github.com/GuoRentong","self_intro":"Robert Guo is a Partner and Director of Product Management at Zilliz and one of the architects behind Milvus, an open-source vector database revolutionizing AI data analysis. With a Ph.D. in Computer Software and Theory from Huazhong University of Science and Technology, he has presented influential work at prestigious conferences and journals, including SIGMOD, VLDB, USENIX ATC, ICS, DATE, and IEEE TPDS. Previously a key developer for Huawei's ModelArts platform, Robert is skilled at crafting efficient and scalable AI data solutions.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":10,"localizations":[{"id":1026,"locale":"ja-JP","published_at":"2024-12-09T03:41:02.589Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Designing_Multi_Tenancy_RAG_with_Milvus_Best_Practices_for_Scalable_Enterprise_Knowledge_Bases_250996f06b.png","belong":"blog","authorNames":["Robert Guo"]},{"id":"blog-717","title":"Evaluating Retrieval-Augmented Generation (RAG): Everything You Should Know","image":{"id":6350,"url":"https://assets.zilliz.com/Evaluating_Retrieval_Augmented_Generation_RAG_Everything_You_Should_Know_00c914f513.png"},"display_time":"Dec 03, 2024","deploy_time":null,"url":"evaluating-rag-everything-you-should-know","abstract":"An overview of various RAG pipeline architectures, retrieval and evaluation frameworks, and examples of biases and failures in LLMs.\n","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":178,"name":"Benito Martin","author_tags":null,"published_at":"2024-09-10T18:31:20.152Z","created_by":82,"updated_by":82,"created_at":"2024-09-10T18:30:36.499Z","updated_at":"2024-10-02T17:35:02.538Z","home_page":null,"home_page_link":null,"self_intro":"Freelance Technical Writer","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":12,"localizations":[{"id":983,"locale":"ja-JP","published_at":"2024-12-06T18:32:29.702Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Evaluating_Retrieval_Augmented_Generation_RAG_Everything_You_Should_Know_00c914f513.png","belong":"blog","authorNames":["Benito Martin"]},{"id":"blog-716","title":"Elasticsearch Was Great, But Vector Databases Are the Future","image":{"id":5439,"url":"https://assets.zilliz.com/Elasticsearch_Was_Great_But_Vector_Databases_Are_the_Future_a037ed531e.png"},"display_time":"Dec 02, 2024","deploy_time":null,"url":"elasticsearch-was-great-but-vector-databases-are-the-future","abstract":"Purpose-built vector databases outperform dual-system setups by unifying Sparse-BM25 and semantic search in a single, efficient implementation.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":101,"name":"Jiang Chen","author_tags":"Head of Ecosystem and Developer Relations","published_at":"2023-10-16T07:05:20.176Z","created_by":18,"updated_by":82,"created_at":"2023-10-16T07:05:18.702Z","updated_at":"2024-09-10T17:33:55.053Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/jiang-0616/","self_intro":"Jiang is currently Head of Ecosystem and Developer Relations at Zilliz. He has years of experience in data infrastructures and cloud security. Before joining Zilliz, he had previously served as a tech lead and product manager at Google, where he led the development of web-scale semantic understanding and search indexing that powers innovative search products such as short video search. He has extensive industry experience handling massive unstructured data and multimedia content retrieval. He has also worked on cloud authorization systems and research on data privacy technologies. Jiang holds a Master's degree in Computer Science from the University of Michigan.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":5,"localizations":[{"id":979,"locale":"ja-JP","published_at":"2024-12-03T09:36:04.651Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Elasticsearch_Was_Great_But_Vector_Databases_Are_the_Future_a037ed531e.png","belong":"blog","authorNames":["Jiang Chen"]},{"id":"blog-719","title":"GLiNER: Generalist Model for Named Entity Recognition Using Bidirectional Transformer","image":{"id":6351,"url":"https://assets.zilliz.com/G_Li_NER_Generalist_Model_for_Named_Entity_Recognition_Using_Bidirectional_Transformer_4bb8f98b01.png"},"display_time":"Nov 30, 2024","deploy_time":null,"url":"gliner-generalist-model-for-named-entity-recognition-using-bidirectional-transformer","abstract":"GLiNER is an open-source NER model using a bidirectional transformer encoder. \n","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":118,"name":" Haziqa Sajid","author_tags":"Freelance Technical Writer","published_at":"2024-03-12T10:25:34.265Z","created_by":18,"updated_by":18,"created_at":"2024-03-12T10:25:31.148Z","updated_at":"2024-07-03T07:58:27.010Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/haziqa-sajid-22b53245/","self_intro":"Digital Storytelling for Data, AI, B2B \u0026 SaaS","repost_to_medium":null,"repost_state":null,"meta_description":" Haziqa Sajid, Freelance Technical Writer","locale":"en"}],"read_time":12,"localizations":[{"id":994,"locale":"ja-JP","published_at":"2024-12-06T19:15:28.555Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/G_Li_NER_Generalist_Model_for_Named_Entity_Recognition_Using_Bidirectional_Transformer_4bb8f98b01.png","belong":"blog","authorNames":[" Haziqa Sajid"]},{"id":"blog-718","title":"Mixture-of-Agents (MoA): How Collective Intelligence Elevates LLM Performance","image":{"id":6352,"url":"https://assets.zilliz.com/Mixture_of_Agents_Mo_A_How_Collective_Intelligence_Elevates_LLM_Performance_43c4eb668b.png"},"display_time":"Nov 29, 2024","deploy_time":null,"url":"mixture-of-agents-how-collective-intelligence-elevates-llm-performance","abstract":"Mixture-of-Agents (MoA) is a framework where multiple specialized LLMs, or \"agents,\" collaborate to solve tasks by leveraging their unique strengths. \n","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":125,"name":"Ruben Winastwan","author_tags":"Freelance Technical Writer","published_at":"2024-03-26T09:16:27.310Z","created_by":18,"updated_by":18,"created_at":"2024-03-26T09:16:24.498Z","updated_at":"2024-07-03T07:56:29.256Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Ruben Winastwan, Freelance Technical Writer","locale":"en"}],"read_time":10,"localizations":[{"id":989,"locale":"ja-JP","published_at":"2024-12-06T18:50:08.151Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Mixture_of_Agents_Mo_A_How_Collective_Intelligence_Elevates_LLM_Performance_43c4eb668b.png","belong":"blog","authorNames":["Ruben Winastwan"]},{"id":"learn-277","title":"RouteLLM: An Open-Source Framework for Navigating Cost-Quality Trade-Offs in LLM Deployment","image":{"id":6353,"url":"https://assets.zilliz.com/Route_LLM_Learning_to_Route_LL_Ms_with_Preference_Data_56156c50b6.png"},"display_time":"Nov 28, 2024","url":"routellm-open-source-framework-for-navigate-cost-quality-trade-offs-in-llm-deployment","abstract":"RouteLLM is an open-source framework that enables developers to efficiently route tasks to the most suitable LLMs based on cost, latency, and accuracy.","tags":[{"id":73,"name":"Paper Reading","published_at":"2024-08-10T14:40:10.906Z","created_by":60,"updated_by":60,"created_at":"2024-08-10T14:40:09.192Z","updated_at":"2024-08-10T14:40:10.914Z","locale":"en"}],"authors":[{"id":125,"name":"Ruben Winastwan","author_tags":"Freelance Technical Writer","published_at":"2024-03-26T09:16:27.310Z","created_by":18,"updated_by":18,"created_at":"2024-03-26T09:16:24.498Z","updated_at":"2024-07-03T07:56:29.256Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Ruben Winastwan, Freelance Technical Writer","locale":"en"}],"read_time":15,"localizations":[{"id":320,"locale":"ja-JP","published_at":"2024-12-02T02:55:11.598Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Route_LLM_Learning_to_Route_LL_Ms_with_Preference_Data_56156c50b6.png","belong":"learn","authorNames":["Ruben Winastwan"]},{"id":"blog-694","title":"Making Sense of the Vector Database Landscape","image":{"id":6354,"url":"https://assets.zilliz.com/Making_Sense_of_the_Vector_Database_Landscape_e1d6bb35e1.png"},"display_time":"Nov 27, 2024","deploy_time":null,"url":"making-sense-of-the-vector-database-landscape","abstract":"Compare top vector database vendors, run benchmarks, and choose the right solution for your AI-driven applications. Download the guide now!\n","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":37,"name":"Emily Kurze","author_tags":"Director of Marketing Operations","published_at":"2023-04-11T16:55:11.838Z","created_by":18,"updated_by":18,"created_at":"2023-04-11T16:55:07.625Z","updated_at":"2024-04-29T03:28:13.160Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/emilykurze/","self_intro":"Emily Kurze is the Director of Marketing at Zilliz. ","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":1,"localizations":[{"id":840,"locale":"ja-JP","published_at":"2024-11-27T17:55:37.371Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Making_Sense_of_the_Vector_Database_Landscape_e1d6bb35e1.png","belong":"blog","authorNames":["Emily Kurze"]},{"id":"blog-693","title":"LLaVA: Advancing Vision-Language Models Through Visual Instruction Tuning","image":{"id":6355,"url":"https://assets.zilliz.com/Visual_Instruction_Tuning_3cd3d48bd7.png"},"display_time":"Nov 25, 2024","deploy_time":null,"url":"llava-visual-instruction-training","abstract":"LaVA is a multimodal model that combines text-based LLMs with visual processing capabilities through visual instruction tuning. \n","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":125,"name":"Ruben Winastwan","author_tags":"Freelance Technical Writer","published_at":"2024-03-26T09:16:27.310Z","created_by":18,"updated_by":18,"created_at":"2024-03-26T09:16:24.498Z","updated_at":"2024-07-03T07:56:29.256Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Ruben Winastwan, Freelance Technical Writer","locale":"en"}],"read_time":12,"localizations":[{"id":1590,"locale":"it","published_at":"2024-11-27T17:36:50.493Z"},{"id":1563,"locale":"ko","published_at":"2024-11-27T17:36:50.493Z"},{"id":833,"locale":"ja-JP","published_at":"2024-11-27T17:36:50.493Z"},{"id":1482,"locale":"es","published_at":"2024-11-27T17:36:50.493Z"},{"id":1536,"locale":"ru","published_at":"2024-11-27T17:36:50.493Z"},{"id":1455,"locale":"de","published_at":"2024-11-27T17:36:50.493Z"},{"id":1509,"locale":"pt","published_at":"2024-11-27T17:36:50.493Z"},{"id":1617,"locale":"fr","published_at":"2024-11-27T17:36:50.493Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Visual_Instruction_Tuning_3cd3d48bd7.png","belong":"blog","authorNames":["Ruben Winastwan"]},{"id":"blog-691","title":"Advanced RAG Techniques: Bridging Text and Visuals for More Accurate Responses","image":{"id":6356,"url":"https://assets.zilliz.com/Advanced_RAG_Techniques_Bridging_Text_and_Visuals_for_More_Accurate_Responses_456826d282.png"},"display_time":"Nov 24, 2024","deploy_time":null,"url":"advanced-rag-techniques-bridging-text-and-visuals-for-accurate-responses","abstract":"This blog explores how RAG works, RAG challenges, and advanced RAG techniques like Small to Slide RAG and ColPali. \n","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":45,"name":"Fendy Feng","author_tags":"Technical Marketing Writer","published_at":"2023-05-16T01:36:15.102Z","created_by":18,"updated_by":18,"created_at":"2023-05-16T00:04:12.065Z","updated_at":"2024-04-25T08:37:19.712Z","home_page":"GitHub","home_page_link":"https://www.linkedin.com/in/fendy311/","self_intro":"Fendy Feng is the Technical Marketing Writer at Zilliz. She has extensive experience developing and enhancing the impact of open-source projects in various global markets by producing high-quality, tailored content. Before joining Zilliz, Fendy worked as a Content Strategist at PingCAP, a fast-growing E-Series startup renowned for its open-source distributed SQL database.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"},{"id":179,"name":"Simon Mwaniki ","author_tags":null,"published_at":"2024-09-11T00:44:07.918Z","created_by":82,"updated_by":82,"created_at":"2024-09-11T00:44:06.462Z","updated_at":"2024-09-27T22:42:13.512Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":11,"localizations":[{"id":818,"locale":"ja-JP","published_at":"2024-11-26T17:48:20.519Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Advanced_RAG_Techniques_Bridging_Text_and_Visuals_for_More_Accurate_Responses_456826d282.png","belong":"blog","authorNames":["Fendy Feng","Simon Mwaniki "]},{"id":"blog-683","title":"Stop Waiting, Start Building: Voice Assistant With Milvus and Llama 3.2","image":{"id":6424,"url":"https://assets.zilliz.com/Voice_Assistant_With_Milvus_and_Llama_3_2_67353b957c.png"},"display_time":"Nov 23, 2024","deploy_time":null,"url":"build-your-voice-assistant-agentic-rag-with-milvus-and-llama-3-2","abstract":"We'll learn to build a Voice Assistant, a specialized Agentic RAG system designed for voice interactions, with Milvus, Llama 3.2, and other GenAI tools. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":115,"name":"Stephen Batifol","author_tags":"Developer Advocate ","published_at":"2024-03-07T03:46:04.655Z","created_by":18,"updated_by":18,"created_at":"2024-03-07T03:46:02.457Z","updated_at":"2024-07-18T15:56:42.529Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/stephen-batifol/","self_intro":"Stephen Batifol is a Developer Advocate at Zilliz. He previously worked as a Machine Learning Engineer at Wolt, where he was working on the ML Platform and as a Data Scientist at Brevo. Stephen studied Computer Science and Artificial Intelligence. He enjoys dancing and surfing. \n","repost_to_medium":null,"repost_state":null,"meta_description":"Stephen Batifol is a Developer Advocate at Zilliz.","locale":"en"}],"read_time":6,"localizations":[{"id":928,"locale":"ja-JP","published_at":"2024-11-23T09:11:36.654Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Voice_Assistant_With_Milvus_and_Llama_3_2_67353b957c.png","belong":"blog","authorNames":["Stephen Batifol"]},{"id":"learn-273","title":"Unlocking the Power of Vector Quantization: Techniques for Efficient Data Compression and Retrieval","image":{"id":6425,"url":"https://assets.zilliz.com/Unlocking_the_Power_of_Vector_Quantization_Techniques_for_Efficient_Data_Compression_and_Retrieval_05ff1f07e8.png"},"display_time":"Nov 22, 2024","url":"unlock-power-of-vector-quantization-techniques-for-efficient-data-compression-and-retrieval","abstract":"Vector Quantization (VQ) is a data compression technique representing a large set of similar data points with a smaller set of representative vectors, known as centroids. ","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":178,"name":"Benito Martin","author_tags":null,"published_at":"2024-09-10T18:31:20.152Z","created_by":82,"updated_by":82,"created_at":"2024-09-10T18:30:36.499Z","updated_at":"2024-10-02T17:35:02.538Z","home_page":null,"home_page_link":null,"self_intro":"Freelance Technical Writer","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":15,"localizations":[{"id":308,"locale":"ja-JP","published_at":"2024-11-22T00:27:54.948Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Unlocking_the_Power_of_Vector_Quantization_Techniques_for_Efficient_Data_Compression_and_Retrieval_05ff1f07e8.png","belong":"learn","authorNames":["Benito Martin"]},{"id":"blog-208","title":"How to Select the Most Appropriate CU Type and Size for Your Business?","image":{"id":6426,"url":"https://assets.zilliz.com/June_30_How_to_Select_the_Most_Appropriate_CU_Type_and_Size_for_Your_Zilliz_Cloud_9cc1fcf9a9.png"},"display_time":"Nov 21, 2024","deploy_time":"2023-06-30T04:00:00.000Z","url":"how-to-choose-the-right-cu-type-and-size","abstract":"Explore Zilliz Cloud’s three CU options and learn how to choose the most suitable one for your business","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":68,"name":"Robert Guo","author_tags":"Director of Product Management","published_at":"2023-06-13T18:34:37.794Z","created_by":18,"updated_by":18,"created_at":"2023-06-08T17:01:36.444Z","updated_at":"2024-04-16T02:44:46.685Z","home_page":"GitHub","home_page_link":"https://github.com/GuoRentong","self_intro":"Robert Guo is a Partner and Director of Product Management at Zilliz and one of the architects behind Milvus, an open-source vector database revolutionizing AI data analysis. With a Ph.D. in Computer Software and Theory from Huazhong University of Science and Technology, he has presented influential work at prestigious conferences and journals, including SIGMOD, VLDB, USENIX ATC, ICS, DATE, and IEEE TPDS. Previously a key developer for Huawei's ModelArts platform, Robert is skilled at crafting efficient and scalable AI data solutions.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":6,"localizations":[{"id":1008,"locale":"ja-JP","published_at":"2023-06-30T12:23:18.123Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/June_30_How_to_Select_the_Most_Appropriate_CU_Type_and_Size_for_Your_Zilliz_Cloud_9cc1fcf9a9.png","belong":"blog","authorNames":["Robert Guo"]},{"id":"blog-682","title":"Zilliz Cloud’s Redesigned UI: A Streamlined and Intuitive User Experience","image":{"id":5305,"url":"https://assets.zilliz.com/Introducing_the_Redesigned_UI_for_Zilliz_Cloud_56d16b4edf.png"},"display_time":"Nov 20, 2024","deploy_time":null,"url":"introduce-zilliz-cloud-redesigned-ui-a-streamlined-and-intuitive-user-experience","abstract":"This new UI is cleaner, more intuitive, and specifically designed to streamline workflows, reduce cognitive load, and boost productivity","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":69,"name":"Koko Lv","author_tags":"Design Lead","published_at":"2023-06-14T03:27:04.616Z","created_by":18,"updated_by":18,"created_at":"2023-06-14T03:27:03.009Z","updated_at":"2023-06-14T03:27:04.636Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/lvling/","self_intro":"Design Lead at Zilliz","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":12,"localizations":[{"id":920,"locale":"ja-JP","published_at":"2024-11-23T08:36:09.685Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Introducing_the_Redesigned_UI_for_Zilliz_Cloud_56d16b4edf.png","belong":"blog","authorNames":["Koko Lv"]},{"id":"blog-655","title":"New for Zilliz Cloud: 10X Performance Boost and Enhanced Enterprise Features","image":{"id":5280,"url":"https://assets.zilliz.com/New_for_Zilliz_Cloud_10_X_Performance_Boost_and_Enhanced_Enterprise_Features_1_45de4fb589.png"},"display_time":"Nov 19, 2024","deploy_time":null,"url":"zilliz-nov-24-launch","abstract":"A 10x faster Performance with Cardinal vector search engine, production-ready features including Multi-replica, Data Migration, Authentication, and more \n","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":76,"name":"Steffi Li","author_tags":"Director of Product Marketing","published_at":"2023-07-13T17:18:42.023Z","created_by":18,"updated_by":18,"created_at":"2023-07-13T17:16:54.449Z","updated_at":"2023-07-13T17:18:42.070Z","home_page":null,"home_page_link":null,"self_intro":"Steffi is the Director of Product Marketing at Zilliz, with prior experience leading the GTM strategies for open-source data technologies such as Apache Kafka and Apache Airflow. Passionate about travel, yoga, and non-fiction reading, she brings a balanced and enriched worldview to her professional pursuits.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":2,"localizations":[{"id":681,"locale":"ja-JP","published_at":"2024-11-19T09:19:36.719Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/New_for_Zilliz_Cloud_10_X_Performance_Boost_and_Enhanced_Enterprise_Features_1_45de4fb589.png","belong":"blog","authorNames":["Steffi Li"]},{"id":"learn-274","title":"What is ScaNN (Scalable Nearest Neighbors)?","image":{"id":6427,"url":"https://assets.zilliz.com/What_is_Sca_NN_ea4493dd1d.png"},"display_time":"Nov 18, 2024","url":"what-is-scann-scalable-nearest-neighbors-google","abstract":"ScaNN is an open-source library developed by Google for fast, approximate nearest neighbor searches in large-scale datasets. \n","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":179,"name":"Simon Mwaniki ","author_tags":null,"published_at":"2024-09-11T00:44:07.918Z","created_by":82,"updated_by":82,"created_at":"2024-09-11T00:44:06.462Z","updated_at":"2024-09-27T22:42:13.512Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"},{"id":45,"name":"Fendy Feng","author_tags":"Technical Marketing Writer","published_at":"2023-05-16T01:36:15.102Z","created_by":18,"updated_by":18,"created_at":"2023-05-16T00:04:12.065Z","updated_at":"2024-04-25T08:37:19.712Z","home_page":"GitHub","home_page_link":"https://www.linkedin.com/in/fendy311/","self_intro":"Fendy Feng is the Technical Marketing Writer at Zilliz. She has extensive experience developing and enhancing the impact of open-source projects in various global markets by producing high-quality, tailored content. Before joining Zilliz, Fendy worked as a Content Strategist at PingCAP, a fast-growing E-Series startup renowned for its open-source distributed SQL database.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":11,"localizations":[{"id":310,"locale":"ja-JP","published_at":"2024-11-23T07:09:51.653Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/What_is_Sca_NN_ea4493dd1d.png","belong":"learn","authorNames":["Simon Mwaniki ","Fendy Feng"]},{"id":"learn-276","title":"Getting Started with ScaNN","image":{"id":6428,"url":"https://assets.zilliz.com/Getting_Started_with_Sca_NN_bac08a4d63.png"},"display_time":"Nov 17, 2024","url":"getting-started-with-scann","abstract":"Google’s ScaNN is a library for ANNS. This guide walks you you through implementing ScaNN and demonstrate how to integrate it with Milvus. \n","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":179,"name":"Simon Mwaniki ","author_tags":null,"published_at":"2024-09-11T00:44:07.918Z","created_by":82,"updated_by":82,"created_at":"2024-09-11T00:44:06.462Z","updated_at":"2024-09-27T22:42:13.512Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":8,"localizations":[{"id":316,"locale":"ja-JP","published_at":"2024-11-27T17:47:44.590Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Getting_Started_with_Sca_NN_bac08a4d63.png","belong":"learn","authorNames":["Simon Mwaniki "]},{"id":"blog-695","title":"Enabling Fine-Grained Access Control with Milvus Row-Level RBAC","image":{"id":6429,"url":"https://assets.zilliz.com/Enabling_Fine_Grained_Access_Control_with_Milvus_Row_Level_RBAC_1f95af04b8.png"},"display_time":"Nov 16, 2024","deploy_time":null,"url":"enabling-fine-grained-access-control-with-milvus-row-level-rbac","abstract":"Milvus offers row-level RBAC (Role-Based Access Control) which is a robust solution for managing data access with precision and efficiency. \n","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":157,"name":"Ken Zhang","author_tags":"Senior Product Manager","published_at":"2024-04-29T11:13:18.206Z","created_by":18,"updated_by":18,"created_at":"2024-04-29T03:36:01.335Z","updated_at":"2024-07-03T07:47:25.978Z","home_page":null,"home_page_link":null,"self_intro":"Ken Zhang is a Senior Product Manager at Zilliz, leading the development of the Milvus vector database by setting its strategic direction and key features. Prior to Zilliz, he served as a kernel engineer at SAP HANA and enhanced his product management skills at PingCAP. Ken holds a master's degree from Fudan University and has over eight years of experience specializing in database development and big data infrastructure management.","repost_to_medium":null,"repost_state":null,"meta_description":"Ken Zhang is a Senior Product Manager at Zilliz","locale":"en"}],"read_time":10,"localizations":[{"id":845,"locale":"ja-JP","published_at":"2024-11-27T18:44:29.392Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Enabling_Fine_Grained_Access_Control_with_Milvus_Row_Level_RBAC_1f95af04b8.png","belong":"blog","authorNames":["Ken Zhang"]},{"id":"blog-654","title":"Learn Llama 3.2 and How to Build a RAG Pipeline with Llama and Milvus","image":{"id":6430,"url":"https://assets.zilliz.com/Introduction_to_Llama_3_1_6dbe90af9f.png"},"display_time":"Nov 15, 2024","deploy_time":null,"url":"learn-llama-3-2-and-how-to-build-rag-with-llama-with-milvus","abstract":"introduce Llama 3.1 and 3.2 and explore how to build a RAG app with Llama 3.2 and Milvus. ","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":178,"name":"Benito Martin","author_tags":null,"published_at":"2024-09-10T18:31:20.152Z","created_by":82,"updated_by":82,"created_at":"2024-09-10T18:30:36.499Z","updated_at":"2024-10-02T17:35:02.538Z","home_page":null,"home_page_link":null,"self_intro":"Freelance Technical Writer","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":13,"localizations":[{"id":821,"locale":"ja-JP","published_at":"2024-11-15T07:49:25.580Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Introduction_to_Llama_3_1_6dbe90af9f.png","belong":"blog","authorNames":["Benito Martin"]},{"id":"learn-269","title":"LoRA Explained: Low-Rank Adaptation for Fine-Tuning LLMs","image":{"id":6431,"url":"https://assets.zilliz.com/Lo_RA_Low_Rank_Adaptation_of_Large_Language_Models_18a8f10749.png"},"display_time":"Nov 14, 2024","url":"lora-explained-low-rank-adaptation-for-fine-tuning-llms","abstract":"LoRA (Low-Rank Adaptation) is a technique for efficiently fine-tuning LLMs by introducing low-rank trainable weight matrices into specific model layers.","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":125,"name":"Ruben Winastwan","author_tags":"Freelance Technical Writer","published_at":"2024-03-26T09:16:27.310Z","created_by":18,"updated_by":18,"created_at":"2024-03-26T09:16:24.498Z","updated_at":"2024-07-03T07:56:29.256Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Ruben Winastwan, Freelance Technical Writer","locale":"en"}],"read_time":14,"localizations":[{"id":299,"locale":"ja-JP","published_at":"2024-11-15T08:11:46.695Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Lo_RA_Low_Rank_Adaptation_of_Large_Language_Models_18a8f10749.png","belong":"learn","authorNames":["Ruben Winastwan"]},{"id":"blog-652","title":"Deploying a Multimodal RAG System Using vLLM and Milvus","image":{"id":6433,"url":"https://assets.zilliz.com/Deploying_a_Multimodal_RAG_System_Using_v_LLM_and_Milvus_45c68987dc.png"},"display_time":"Nov 13, 2024","deploy_time":null,"url":"deploy-multimodal-rag-using-vllm-and-milvus","abstract":"This blog will guide you through creating a Multimodal RAG with Milvus and vLLM. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":115,"name":"Stephen Batifol","author_tags":"Developer Advocate ","published_at":"2024-03-07T03:46:04.655Z","created_by":18,"updated_by":18,"created_at":"2024-03-07T03:46:02.457Z","updated_at":"2024-07-18T15:56:42.529Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/stephen-batifol/","self_intro":"Stephen Batifol is a Developer Advocate at Zilliz. He previously worked as a Machine Learning Engineer at Wolt, where he was working on the ML Platform and as a Data Scientist at Brevo. Stephen studied Computer Science and Artificial Intelligence. He enjoys dancing and surfing. \n","repost_to_medium":null,"repost_state":null,"meta_description":"Stephen Batifol is a Developer Advocate at Zilliz.","locale":"en"}],"read_time":7,"localizations":[{"id":1633,"locale":"fr","published_at":"2024-11-13T07:38:37.427Z"},{"id":1525,"locale":"pt","published_at":"2024-11-13T07:38:37.427Z"},{"id":1606,"locale":"it","published_at":"2024-11-13T07:38:37.427Z"},{"id":1552,"locale":"ru","published_at":"2024-11-13T07:38:37.427Z"},{"id":1471,"locale":"de","published_at":"2024-11-13T07:38:37.427Z"},{"id":1579,"locale":"ko","published_at":"2024-11-13T07:38:37.427Z"},{"id":1498,"locale":"es","published_at":"2024-11-13T07:38:37.427Z"},{"id":1209,"locale":"ja-JP","published_at":"2024-11-13T07:38:37.427Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Deploying_a_Multimodal_RAG_System_Using_v_LLM_and_Milvus_45c68987dc.png","belong":"blog","authorNames":["Stephen Batifol"]},{"id":"blog-653","title":"Transformers4Rec: Bringing NLP Power to Modern Recommendation Systems","image":{"id":5211,"url":"https://assets.zilliz.com/Transformers4rec_Harnessing_NLP_Advancements_for_Cutting_Edge_Recommender_Systems_e29a24da8b.png"},"display_time":"Nov 12, 2024","deploy_time":null,"url":"transformer4rec-bring-nlp-power-to-modern-recommendation-systems","abstract":"Transformers4Rec is a powerful and flexible library designed for creating sequential and session-based recommendation systems with PyTorch.","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":147,"name":"ShriVarsheni R","author_tags":"Freelance Technical Writer","published_at":"2024-04-24T21:21:57.571Z","created_by":18,"updated_by":18,"created_at":"2024-04-24T21:21:55.818Z","updated_at":"2024-07-03T07:50:17.617Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"ShriVarsheni, Freelance Technical Writer","locale":"en"}],"read_time":8,"localizations":[{"id":1214,"locale":"ja-JP","published_at":"2024-11-13T07:47:52.504Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Transformers4rec_Harnessing_NLP_Advancements_for_Cutting_Edge_Recommender_Systems_e29a24da8b.png","belong":"blog","authorNames":["ShriVarsheni R"]},{"id":"learn-275","title":"Knowledge Distillation: Transferring Knowledge from Large, Computationally Expensive LLMs to Smaller Ones Without Sacrificing Validity","image":{"id":5322,"url":"https://assets.zilliz.com/Knowledge_Distillation_of_Large_Language_Models_20241122_101853_562807feda.png"},"display_time":"Nov 11, 2024","url":"knowledge-distillation-from-large-language-models-deep-dive","abstract":"Knowledge distillation is a machine learning technique in which the knowledge of a large, complex model (teacher) is transferred to a smaller, simpler model (student). ","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":118,"name":" Haziqa Sajid","author_tags":"Freelance Technical Writer","published_at":"2024-03-12T10:25:34.265Z","created_by":18,"updated_by":18,"created_at":"2024-03-12T10:25:31.148Z","updated_at":"2024-07-03T07:58:27.010Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/haziqa-sajid-22b53245/","self_intro":"Digital Storytelling for Data, AI, B2B \u0026 SaaS","repost_to_medium":null,"repost_state":null,"meta_description":" Haziqa Sajid, Freelance Technical Writer","locale":"en"}],"read_time":13,"localizations":[{"id":312,"locale":"ja-JP","published_at":"2024-11-23T09:55:22.127Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Knowledge_Distillation_of_Large_Language_Models_20241122_101853_562807feda.png","belong":"learn","authorNames":[" Haziqa Sajid"]},{"id":"blog-651","title":"How Inkeep and Milvus Built a RAG-driven AI Assistant for Smarter Interaction","image":{"id":5182,"url":"https://assets.zilliz.com/How_Inkeep_and_Zilliz_built_an_AI_assistant_20241023_061518_6ccaac665f.png"},"display_time":"Nov 08, 2024","deploy_time":null,"url":"how-inkeep-and-milvus-built-rag-driven-ai-assisstant-for-smarter-interaction","abstract":"Robert Tran, the Co-founder and CTO of Inkeep, shared how Inkeep and Zilliz built an AI-powered assistant for their documentation site. ","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":125,"name":"Ruben Winastwan","author_tags":"Freelance Technical Writer","published_at":"2024-03-26T09:16:27.310Z","created_by":18,"updated_by":18,"created_at":"2024-03-26T09:16:24.498Z","updated_at":"2024-07-03T07:56:29.256Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Ruben Winastwan, Freelance Technical Writer","locale":"en"}],"read_time":10,"localizations":[{"id":1497,"locale":"es","published_at":"2024-11-08T02:25:33.891Z"},{"id":1551,"locale":"ru","published_at":"2024-11-08T02:25:33.891Z"},{"id":1470,"locale":"de","published_at":"2024-11-08T02:25:33.891Z"},{"id":1578,"locale":"ko","published_at":"2024-11-08T02:25:33.891Z"},{"id":1632,"locale":"fr","published_at":"2024-11-08T02:25:33.891Z"},{"id":1524,"locale":"pt","published_at":"2024-11-08T02:25:33.891Z"},{"id":1605,"locale":"it","published_at":"2024-11-08T02:25:33.891Z"},{"id":1197,"locale":"ja-JP","published_at":"2024-11-08T02:25:33.891Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/How_Inkeep_and_Zilliz_built_an_AI_assistant_20241023_061518_6ccaac665f.png","belong":"blog","authorNames":["Ruben Winastwan"]},{"id":"blog-650","title":"Safe RAG with HydroX AI and Zilliz: PII Masking for Responsible GenAI","image":{"id":6434,"url":"https://assets.zilliz.com/Building_Safe_RAG_with_Hydro_X_AI_and_Zilliz_1f23cf5d11.png"},"display_time":"Nov 07, 2024","deploy_time":null,"url":"safe-rag-with-hydrox-ai-and-zilliz-pii-masking-for-responsible-genai","abstract":"Organizations can ensure privacy at every layer of their data pipeline by anonymizing or masking PII using the PII Marker before data reaches the vector database. ","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":190,"name":"Victor Bian","author_tags":"Chief of Staff, HydroX AI, ","published_at":"2024-11-06T06:36:54.336Z","created_by":60,"updated_by":60,"created_at":"2024-11-06T06:36:51.745Z","updated_at":"2024-11-06T06:36:54.374Z","home_page":null,"home_page_link":null,"self_intro":"Chief of Staff, HydroX AI","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"},{"id":101,"name":"Jiang Chen","author_tags":"Head of Ecosystem and Developer Relations","published_at":"2023-10-16T07:05:20.176Z","created_by":18,"updated_by":82,"created_at":"2023-10-16T07:05:18.702Z","updated_at":"2024-09-10T17:33:55.053Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/jiang-0616/","self_intro":"Jiang is currently Head of Ecosystem and Developer Relations at Zilliz. He has years of experience in data infrastructures and cloud security. Before joining Zilliz, he had previously served as a tech lead and product manager at Google, where he led the development of web-scale semantic understanding and search indexing that powers innovative search products such as short video search. He has extensive industry experience handling massive unstructured data and multimedia content retrieval. He has also worked on cloud authorization systems and research on data privacy technologies. Jiang holds a Master's degree in Computer Science from the University of Michigan.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":3,"localizations":[{"id":1193,"locale":"ja-JP","published_at":"2024-11-07T09:00:22.378Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Building_Safe_RAG_with_Hydro_X_AI_and_Zilliz_1f23cf5d11.png","belong":"blog","authorNames":["Victor Bian","Jiang Chen"]},{"id":"learn-271","title":"Getting Started with Voyager: Spotify's Nearest-Neighbor Search Library","image":{"id":6435,"url":"https://assets.zilliz.com/Getting_Started_with_Voyager_659d16344f.png"},"display_time":"Nov 05, 2024","url":"getting-started-with-voyager-spotify-nearest-neighbor-search-library","abstract":"Voyager: a new open-source library for fast nearest-neighbor searches. Voyager uses the HNSW algorithm, outperforming its previous library, Annoy. ","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":118,"name":" Haziqa Sajid","author_tags":"Freelance Technical Writer","published_at":"2024-03-12T10:25:34.265Z","created_by":18,"updated_by":18,"created_at":"2024-03-12T10:25:31.148Z","updated_at":"2024-07-03T07:58:27.010Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/haziqa-sajid-22b53245/","self_intro":"Digital Storytelling for Data, AI, B2B \u0026 SaaS","repost_to_medium":null,"repost_state":null,"meta_description":" Haziqa Sajid, Freelance Technical Writer","locale":"en"}],"read_time":8,"localizations":[{"id":305,"locale":"ja-JP","published_at":"2024-11-15T08:41:14.477Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Getting_Started_with_Voyager_659d16344f.png","belong":"learn","authorNames":[" Haziqa Sajid"]},{"id":"learn-270","title":"XLNet Explained: Generalized Autoregressive Pretraining for Enhanced Language Understanding","image":{"id":6436,"url":"https://assets.zilliz.com/XL_Net_Generalized_Autoregressive_Pretraining_for_Language_Understanding_1979cb909e.png"},"display_time":"Nov 04, 2024","url":"xlnet-explained-generalized-autoregressive-pretraining-for-enhanced-language-understanding","abstract":"XLNet is a transformer-based language model that builds on BERT's limitations by introducing a new approach called permutation-based training. ","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":158,"name":"Denis Kuria","author_tags":"Freelance Technical Writer","published_at":"2024-05-01T00:39:32.350Z","created_by":18,"updated_by":18,"created_at":"2024-05-01T00:39:30.888Z","updated_at":"2024-07-03T06:50:56.660Z","home_page":null,"home_page_link":null,"self_intro":"Denis is a machine learning engineer who enjoys writing guides to help other developers. He has a bachelor's in computer science and loves hiking and exploring the world.\n","repost_to_medium":null,"repost_state":null,"meta_description":"Denis Kuria is a freelance technical writer at Zilliz. ","locale":"en"}],"read_time":12,"localizations":[{"id":272,"locale":"ja-JP","published_at":"2024-11-20T03:59:21.083Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/XL_Net_Generalized_Autoregressive_Pretraining_for_Language_Understanding_1979cb909e.png","belong":"learn","authorNames":["Denis Kuria"]},{"id":"learn-268","title":"ALIGN Explained: Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision","image":{"id":6437,"url":"https://assets.zilliz.com/Scaling_Up_Visual_and_Vision_Language_Representation_Learning_With_Noisy_Text_Supervision_c69b0350c5.png"},"display_time":"Nov 01, 2024","url":"align-explained-scaling-up-visual-and-vision-language-representation-learning-with-noisy-text-supervision","abstract":"ALIGN model is designed to learn visual and language representations from noisy image-alt-text pairs.","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":118,"name":" Haziqa Sajid","author_tags":"Freelance Technical Writer","published_at":"2024-03-12T10:25:34.265Z","created_by":18,"updated_by":18,"created_at":"2024-03-12T10:25:31.148Z","updated_at":"2024-07-03T07:58:27.010Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/haziqa-sajid-22b53245/","self_intro":"Digital Storytelling for Data, AI, B2B \u0026 SaaS","repost_to_medium":null,"repost_state":null,"meta_description":" Haziqa Sajid, Freelance Technical Writer","locale":"en"}],"read_time":8,"localizations":[{"id":294,"locale":"ja-JP","published_at":"2024-11-15T07:16:48.793Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Scaling_Up_Visual_and_Vision_Language_Representation_Learning_With_Noisy_Text_Supervision_c69b0350c5.png","belong":"learn","authorNames":[" Haziqa Sajid"]},{"id":"blog-644","title":"Catch a Cute Ghost this Halloween with Milvus","image":{"id":5111,"url":"https://assets.zilliz.com/Cute_ghost_halloween_341032d9f6.png"},"display_time":"Oct 31, 2024","deploy_time":"2024-10-31T16:00:00.000Z","url":"multimodal-rag-halloween-ghosts","abstract":"Run ghastly multimodal analytics and Retrieval Augmented Generation with our \"ghosts\" collections in the open-source Milvus vector database.\n","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":164,"name":"Tim Spann","author_tags":"Principal Developer Advocate","published_at":"2024-05-29T06:54:05.034Z","created_by":18,"updated_by":18,"created_at":"2024-05-29T06:54:02.718Z","updated_at":"2024-07-18T15:55:19.267Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/timothyspann/","self_intro":"Tim Spann is a Principal Developer Advocate at Zilliz. ","repost_to_medium":null,"repost_state":null,"meta_description":"Tim Spann is the Principal Developer Advocate at Zilliz. ","locale":"en"}],"read_time":7,"localizations":[{"id":1150,"locale":"ja-JP","published_at":"2024-10-31T20:05:42.766Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Cute_ghost_halloween_341032d9f6.png","belong":"blog","authorNames":["Tim Spann"]},{"id":"learn-267","title":"Understanding HNSWlib: A Graph-based Library for Fast Approximate Nearest Neighbor Search","image":{"id":6438,"url":"https://assets.zilliz.com/What_is_HNS_Wlib_f34e095576.png"},"display_time":"Oct 29, 2024","url":"learn-hnswlib-graph-based-library-for-fast-anns","abstract":"HNSWlib is an open-source C++ and Python library implementation of the HNSW algorithm, which is used for fast approximate nearest neighbor search. ","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":125,"name":"Ruben Winastwan","author_tags":"Freelance Technical Writer","published_at":"2024-03-26T09:16:27.310Z","created_by":18,"updated_by":18,"created_at":"2024-03-26T09:16:24.498Z","updated_at":"2024-07-03T07:56:29.256Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Ruben Winastwan, Freelance Technical Writer","locale":"en"}],"read_time":14,"localizations":[{"id":428,"locale":"ja-JP","published_at":"2024-10-31T14:15:23.027Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/What_is_HNS_Wlib_f34e095576.png","belong":"learn","authorNames":["Ruben Winastwan"]},{"id":"learn-266","title":"Florence: An Advanced Foundation Model for Computer Vision by Microsoft ","image":{"id":6439,"url":"https://assets.zilliz.com/Florence_A_New_Foundation_Model_for_Computer_Vision_a48c84fc24.png"},"display_time":"Oct 28, 2024","url":"florence-novel-vision-foundation-model-by-microsoft","abstract":"Florence is a large-scale vision-language model developed by Microsoft, particularly effective for applications requiring multimodal capabilities. ","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":158,"name":"Denis Kuria","author_tags":"Freelance Technical Writer","published_at":"2024-05-01T00:39:32.350Z","created_by":18,"updated_by":18,"created_at":"2024-05-01T00:39:30.888Z","updated_at":"2024-07-03T06:50:56.660Z","home_page":null,"home_page_link":null,"self_intro":"Denis is a machine learning engineer who enjoys writing guides to help other developers. He has a bachelor's in computer science and loves hiking and exploring the world.\n","repost_to_medium":null,"repost_state":null,"meta_description":"Denis Kuria is a freelance technical writer at Zilliz. ","locale":"en"}],"read_time":12,"localizations":[{"id":346,"locale":"ja-JP","published_at":"2024-10-31T14:06:33.998Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Florence_A_New_Foundation_Model_for_Computer_Vision_a48c84fc24.png","belong":"learn","authorNames":["Denis Kuria"]},{"id":"blog-643","title":"The Role of LLMs in Modern Travel: Opportunities and Challenges Ahead","image":{"id":5081,"url":"https://assets.zilliz.com/The_Journey_of_Large_Language_Models_at_Get_Your_Guide_20241009_120101_900a997b0b.png"},"display_time":"Oct 25, 2024","deploy_time":null,"url":"role-of-llms-in-modern-travel-getyourguide","abstract":"Explore How GetYourGuide use LLMs to improve customer experiences and How RAG address common LLM issues ","tags":[{"id":1,"name":"Case Study","published_at":"2021-01-15T10:34:37.316Z","created_by":18,"updated_by":18,"created_at":"2021-01-15T10:34:34.857Z","updated_at":"2021-01-25T10:31:22.499Z","locale":"en"}],"authors":[{"id":45,"name":"Fendy Feng","author_tags":"Technical Marketing Writer","published_at":"2023-05-16T01:36:15.102Z","created_by":18,"updated_by":18,"created_at":"2023-05-16T00:04:12.065Z","updated_at":"2024-04-25T08:37:19.712Z","home_page":"GitHub","home_page_link":"https://www.linkedin.com/in/fendy311/","self_intro":"Fendy Feng is the Technical Marketing Writer at Zilliz. She has extensive experience developing and enhancing the impact of open-source projects in various global markets by producing high-quality, tailored content. Before joining Zilliz, Fendy worked as a Content Strategist at PingCAP, a fast-growing E-Series startup renowned for its open-source distributed SQL database.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"},{"id":170,"name":"Yesha Shastri","author_tags":"Freelance Technical Writer in AI/ML","published_at":"2024-07-29T08:44:59.761Z","created_by":18,"updated_by":18,"created_at":"2024-07-29T08:44:38.291Z","updated_at":"2024-07-29T08:44:59.820Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/yeshashastri/","self_intro":"Yesha Shastri, Freelance Technical Writer in AI/ML","repost_to_medium":null,"repost_state":null,"meta_description":"Yesha Shastri, Freelance Technical Writer","locale":"en"}],"read_time":7,"localizations":[{"id":1119,"locale":"ja-JP","published_at":"2024-10-31T14:00:41.305Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/The_Journey_of_Large_Language_Models_at_Get_Your_Guide_20241009_120101_900a997b0b.png","belong":"blog","authorNames":["Fendy Feng","Yesha Shastri"]},{"id":"blog-641","title":"The Practical Guide to Self-Hosting Compound LLM Systems","image":{"id":5041,"url":"https://assets.zilliz.com/A_Guide_to_Compound_AI_Systems_2229de0fa1.png"},"display_time":"Oct 23, 2024","deploy_time":null,"url":"guide-to-self-hosting-compound-llm-systems","abstract":"BentoML shares its research insights in AI orchestration, demonstrating solutions for optimizing performance issues when self-hosting AI models. ","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":188,"name":"Trevor Trinh","author_tags":"Student at UC Berkeley ","published_at":"2024-10-25T17:35:49.396Z","created_by":82,"updated_by":82,"created_at":"2024-10-25T17:35:12.126Z","updated_at":"2024-10-25T17:35:49.416Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/trevortrinh/","self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":8,"localizations":[{"id":1106,"locale":"ja-JP","published_at":"2024-10-25T13:08:59.832Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/A_Guide_to_Compound_AI_Systems_2229de0fa1.png","belong":"blog","authorNames":["Trevor Trinh"]},{"id":"blog-642","title":"Combining Images and Text Together: How Multimodal Retrieval Transforms Search","image":{"id":6440,"url":"https://assets.zilliz.com/Combining_Images_and_Text_How_Multimodal_Retrieval_Changes_Search_8f7833fff1.png"},"display_time":"Oct 22, 2024","deploy_time":null,"url":"combine-image-and-text-how-multimodal-retrieval-transforms-search","abstract":"Discuss multimodal retrieval and composed image retrieval (CIR) techniques, including Pic2Word, CompoDiff, CIReVL, and MagicLens. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":102,"name":"David Wang","author_tags":"Algorithm Engineer at Zilliz","published_at":"2023-10-27T08:41:57.519Z","created_by":18,"updated_by":18,"created_at":"2023-10-27T08:41:55.636Z","updated_at":"2024-04-16T02:43:37.282Z","home_page":"GitHub","home_page_link":"https://github.com/wxywb","self_intro":"David Wang, Algorithm Engineer at Zilliz, brings extensive expertise in computer vision and natural language processing. His contributions to advanced embedding algorithm research, including projects like Towhee and GPTCache, reflect his commitment to advancing AI technologies. Before joining Zilliz, he worked at Alibaba Cloud for large-scale object recognition and classification projects. David holds a Master's degree from Dalian University of Technology.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":16,"localizations":[{"id":1176,"locale":"ja-JP","published_at":"2024-10-31T13:54:49.921Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Combining_Images_and_Text_How_Multimodal_Retrieval_Changes_Search_8f7833fff1.png","belong":"blog","authorNames":["David Wang"]},{"id":"learn-265","title":"The Potential Transformer Replacement: Mamba","image":{"id":6441,"url":"https://assets.zilliz.com/Mamba_Linear_Time_Sequence_Modeling_with_Selective_State_Spaces_abb069b2b8.png"},"display_time":"Oct 22, 2024","url":"mamba-architecture-potential-transformer-replacement","abstract":"Mamba is a new architecture for sequence modeling, designed to offer an alternative to the Transformer models commonly used in machine learning. ","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":118,"name":" Haziqa Sajid","author_tags":"Freelance Technical Writer","published_at":"2024-03-12T10:25:34.265Z","created_by":18,"updated_by":18,"created_at":"2024-03-12T10:25:31.148Z","updated_at":"2024-07-03T07:58:27.010Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/haziqa-sajid-22b53245/","self_intro":"Digital Storytelling for Data, AI, B2B \u0026 SaaS","repost_to_medium":null,"repost_state":null,"meta_description":" Haziqa Sajid, Freelance Technical Writer","locale":"en"}],"read_time":12,"localizations":[{"id":452,"locale":"ja-JP","published_at":"2024-11-01T15:32:05.246Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Mamba_Linear_Time_Sequence_Modeling_with_Selective_State_Spaces_abb069b2b8.png","belong":"learn","authorNames":[" Haziqa Sajid"]},{"id":"blog-640","title":"Best Practices in Implementing Retrieval-Augmented Generation (RAG) Applications ","image":{"id":6442,"url":"https://assets.zilliz.com/Searching_for_Best_Practices_in_Retrieval_Augmented_Generation_d7f3d503f0.png"},"display_time":"Oct 21, 2024","deploy_time":null,"url":"best-practice-in-implementing-rag-apps","abstract":"In this article, we explored various RAG components and discussed the approaches with optimal performance in each component. ","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":125,"name":"Ruben Winastwan","author_tags":"Freelance Technical Writer","published_at":"2024-03-26T09:16:27.310Z","created_by":18,"updated_by":18,"created_at":"2024-03-26T09:16:24.498Z","updated_at":"2024-07-03T07:56:29.256Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Ruben Winastwan, Freelance Technical Writer","locale":"en"}],"read_time":15,"localizations":[{"id":1336,"locale":"ja-JP","published_at":"2024-10-22T13:04:42.724Z"},{"id":1611,"locale":"it","published_at":"2024-10-22T13:04:42.724Z"},{"id":1476,"locale":"de","published_at":"2024-10-22T13:04:42.724Z"},{"id":1557,"locale":"ru","published_at":"2024-10-22T13:04:42.724Z"},{"id":1530,"locale":"pt","published_at":"2024-10-22T13:04:42.724Z"},{"id":1584,"locale":"ko","published_at":"2024-10-22T13:04:42.724Z"},{"id":1638,"locale":"fr","published_at":"2024-10-22T13:04:42.724Z"},{"id":1503,"locale":"es","published_at":"2024-10-22T13:04:42.724Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Searching_for_Best_Practices_in_Retrieval_Augmented_Generation_d7f3d503f0.png","belong":"blog","authorNames":["Ruben Winastwan"]},{"id":"learn-264","title":"Understanding CoCa: Advancing Image-Text Foundation Models with Contrastive Captioners","image":{"id":6443,"url":"https://assets.zilliz.com/Co_Ca_Contrastive_Captioners_are_Image_Text_Foundation_Models_98a2459b0c.png"},"display_time":"Oct 19, 2024","url":"understand-coca-advance-image-text-foundation-models-with-contrastive-captioners","abstract":"Contrastive Captioners (CoCa) is an AI model developed by Microsoft that is designed to bridge the capabilities of language models and vision models.","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":158,"name":"Denis Kuria","author_tags":"Freelance Technical Writer","published_at":"2024-05-01T00:39:32.350Z","created_by":18,"updated_by":18,"created_at":"2024-05-01T00:39:30.888Z","updated_at":"2024-07-03T06:50:56.660Z","home_page":null,"home_page_link":null,"self_intro":"Denis is a machine learning engineer who enjoys writing guides to help other developers. He has a bachelor's in computer science and loves hiking and exploring the world.\n","repost_to_medium":null,"repost_state":null,"meta_description":"Denis Kuria is a freelance technical writer at Zilliz. ","locale":"en"}],"read_time":17,"localizations":[{"id":435,"locale":"ja-JP","published_at":"2024-10-17T07:37:47.242Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Co_Ca_Contrastive_Captioners_are_Image_Text_Foundation_Models_98a2459b0c.png","belong":"learn","authorNames":["Denis Kuria"]},{"id":"blog-632","title":"The Importance of Data Engineering for Successful AI with Airbyte and Zilliz","image":{"id":6444,"url":"https://assets.zilliz.com/The_Importance_of_Data_Engineering_for_Successful_AI_with_Airbyte_and_Zilliz_96819295e8.png"},"display_time":"Oct 18, 2024","deploy_time":"2024-10-17T19:00:00.000Z","url":"importance-of-data-engineering-for-successful-ai","abstract":"Learn how data engineering can resolve common challenges associated with deploying and scaling effective AI usage.","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":187,"name":"Sydney Blanchard","author_tags":null,"published_at":"2024-10-18T16:32:29.843Z","created_by":82,"updated_by":82,"created_at":"2024-10-18T16:32:28.432Z","updated_at":"2024-10-18T16:32:29.893Z","home_page":null,"home_page_link":null,"self_intro":"Sydney Blanchard is the Editorial Assistant at Database Trends and Applications, a division of Information Today, Inc","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":2,"localizations":[{"id":1054,"locale":"ja-JP","published_at":"2024-10-18T16:34:45.091Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/The_Importance_of_Data_Engineering_for_Successful_AI_with_Airbyte_and_Zilliz_96819295e8.png","belong":"blog","authorNames":["Sydney Blanchard"]},{"id":"blog-262","title":"How to Choose a Vector Database: Qdrant Cloud vs. Zilliz Cloud","image":{"id":1986,"url":"https://assets.zilliz.com/Zilliz_Cloud_vs_Qdrant_71008cbada.png"},"display_time":"Oct 17, 2024","deploy_time":null,"url":"qdrant-cloud-vs-zilliz","abstract":"Compare Qdrant Cloud and Zilliz Cloud (fully managed Milvus) in this in-depth benchmark, cost, and features comparison.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":76,"name":"Steffi Li","author_tags":"Director of Product Marketing","published_at":"2023-07-13T17:18:42.023Z","created_by":18,"updated_by":18,"created_at":"2023-07-13T17:16:54.449Z","updated_at":"2023-07-13T17:18:42.070Z","home_page":null,"home_page_link":null,"self_intro":"Steffi is the Director of Product Marketing at Zilliz, with prior experience leading the GTM strategies for open-source data technologies such as Apache Kafka and Apache Airflow. Passionate about travel, yoga, and non-fiction reading, she brings a balanced and enriched worldview to her professional pursuits.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":9,"localizations":[{"id":1390,"locale":"ja-JP","published_at":"2023-10-13T16:51:02.143Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Zilliz_Cloud_vs_Qdrant_71008cbada.png","belong":"blog","authorNames":["Steffi Li"]},{"id":"blog-624","title":"Unlocking Rich Visual Insights with RGB-X Models","image":{"id":6445,"url":"https://assets.zilliz.com/Unlocking_Rich_Visual_Insights_with_RGB_X_Models_c1956d8006.png"},"display_time":"Oct 16, 2024","deploy_time":null,"url":"unlock-rich-visual-insights-with-rgb-x-models","abstract":"RGB-X models: advanced ML models in computer vision that extend traditional RGB data by combining additional depth, infrared, or surface normals data. ","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":179,"name":"Simon Mwaniki ","author_tags":null,"published_at":"2024-09-11T00:44:07.918Z","created_by":82,"updated_by":82,"created_at":"2024-09-11T00:44:06.462Z","updated_at":"2024-09-27T22:42:13.512Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":17,"localizations":[{"id":1219,"locale":"ja-JP","published_at":"2024-10-17T07:25:55.814Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Unlocking_Rich_Visual_Insights_with_RGB_X_Models_c1956d8006.png","belong":"blog","authorNames":["Simon Mwaniki "]},{"id":"blog-623","title":"Securing AI: Advanced Privacy Strategies with PrivateGPT and Milvus","image":{"id":4944,"url":"https://assets.zilliz.com/Securing_AI_Advanced_Privacy_Strategies_with_Private_GPT_and_Milvus_9df1567457.png"},"display_time":"Oct 15, 2024","deploy_time":null,"url":"secure-ai-advanced-privacy-strategy-with-privategpt-and-milvus","abstract":"Explore AI privacy challenges and solutions like PrivateGPT, discussing their benefits, security features, and practical setup suggestions. ","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":147,"name":"ShriVarsheni R","author_tags":"Freelance Technical Writer","published_at":"2024-04-24T21:21:57.571Z","created_by":18,"updated_by":18,"created_at":"2024-04-24T21:21:55.818Z","updated_at":"2024-07-03T07:50:17.617Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"ShriVarsheni, Freelance Technical Writer","locale":"en"},{"id":45,"name":"Fendy Feng","author_tags":"Technical Marketing Writer","published_at":"2023-05-16T01:36:15.102Z","created_by":18,"updated_by":18,"created_at":"2023-05-16T00:04:12.065Z","updated_at":"2024-04-25T08:37:19.712Z","home_page":"GitHub","home_page_link":"https://www.linkedin.com/in/fendy311/","self_intro":"Fendy Feng is the Technical Marketing Writer at Zilliz. She has extensive experience developing and enhancing the impact of open-source projects in various global markets by producing high-quality, tailored content. Before joining Zilliz, Fendy worked as a Content Strategist at PingCAP, a fast-growing E-Series startup renowned for its open-source distributed SQL database.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":10,"localizations":[{"id":1208,"locale":"ja-JP","published_at":"2024-10-17T07:15:24.223Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Securing_AI_Advanced_Privacy_Strategies_with_Private_GPT_and_Milvus_9df1567457.png","belong":"blog","authorNames":["ShriVarsheni R","Fendy Feng"]},{"id":"learn-263","title":"The Evolution of Multi-Agent Systems: From Early Neural Networks to Modern Distributed Learning (Methodological)","image":{"id":6447,"url":"https://assets.zilliz.com/The_Evolution_of_Multi_Agent_Systems_From_Early_Neural_Networks_to_Modern_Distributed_Learning_Part_II_7463a9817b.png"},"display_time":"Oct 14, 2024","url":"evolution-of-multi-agent-systems-from-early-neural-networks-to-modern-distributed-learning-methodological-part-2","abstract":"In this article, we'll explore the evolution of MAS from a methodological or approach-based perspective.","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":125,"name":"Ruben Winastwan","author_tags":"Freelance Technical Writer","published_at":"2024-03-26T09:16:27.310Z","created_by":18,"updated_by":18,"created_at":"2024-03-26T09:16:24.498Z","updated_at":"2024-07-03T07:56:29.256Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Ruben Winastwan, Freelance Technical Writer","locale":"en"}],"read_time":11,"localizations":[{"id":484,"locale":"ja-JP","published_at":"2024-10-14T05:58:08.487Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/The_Evolution_of_Multi_Agent_Systems_From_Early_Neural_Networks_to_Modern_Distributed_Learning_Part_II_7463a9817b.png","belong":"learn","authorNames":["Ruben Winastwan"]},{"id":"learn-262","title":"The Evolution of Multi-Agent Systems: From Early Neural Networks to Modern Distributed Learning (Algorithmic) ","image":{"id":6446,"url":"https://assets.zilliz.com/The_Evolution_of_Multi_Agent_Systems_From_Early_Neural_Networks_to_Modern_Distributed_Learning_Part_I_d146b91425.png"},"display_time":"Oct 13, 2024","url":"evolution-of-multi-agent-systems-from-early-neural-networks-to-modern-distributed-learning-algorithmic-part-1","abstract":"In this article, we'll discuss the evolution of MAS from its early days to the most recent developments from an algorithmic perspective. ","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":125,"name":"Ruben Winastwan","author_tags":"Freelance Technical Writer","published_at":"2024-03-26T09:16:27.310Z","created_by":18,"updated_by":18,"created_at":"2024-03-26T09:16:24.498Z","updated_at":"2024-07-03T07:56:29.256Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Ruben Winastwan, Freelance Technical Writer","locale":"en"}],"read_time":12,"localizations":[{"id":319,"locale":"ja-JP","published_at":"2024-10-14T05:50:11.415Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/The_Evolution_of_Multi_Agent_Systems_From_Early_Neural_Networks_to_Modern_Distributed_Learning_Part_I_d146b91425.png","belong":"learn","authorNames":["Ruben Winastwan"]},{"id":"blog-607","title":"ColPali: Enhanced Document Retrieval with Vision Language Models and ColBERT Embedding Strategy","image":{"id":4993,"url":"https://assets.zilliz.com/Col_Pali_Visual_Retriever_with_Col_BERT_strategy_d258c79a05.png"},"display_time":"Oct 12, 2024","deploy_time":null,"url":"colpali-enhanced-doc-retrieval-with-vision-language-models-and-colbert-strategy","abstract":"ColPali is an advanced document retrieval model designed to index and retrieve information directly from the visual features of documents, particularly PDFs. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":115,"name":"Stephen Batifol","author_tags":"Developer Advocate ","published_at":"2024-03-07T03:46:04.655Z","created_by":18,"updated_by":18,"created_at":"2024-03-07T03:46:02.457Z","updated_at":"2024-07-18T15:56:42.529Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/stephen-batifol/","self_intro":"Stephen Batifol is a Developer Advocate at Zilliz. He previously worked as a Machine Learning Engineer at Wolt, where he was working on the ML Platform and as a Data Scientist at Brevo. Stephen studied Computer Science and Artificial Intelligence. He enjoys dancing and surfing. \n","repost_to_medium":null,"repost_state":null,"meta_description":"Stephen Batifol is a Developer Advocate at Zilliz.","locale":"en"}],"read_time":7,"localizations":[{"id":1548,"locale":"ru","published_at":"2024-10-12T04:03:04.381Z"},{"id":1086,"locale":"ja-JP","published_at":"2024-10-12T04:03:04.381Z"},{"id":1602,"locale":"it","published_at":"2024-10-12T04:03:04.381Z"},{"id":1521,"locale":"pt","published_at":"2024-10-12T04:03:04.381Z"},{"id":1494,"locale":"es","published_at":"2024-10-12T04:03:04.381Z"},{"id":1629,"locale":"fr","published_at":"2024-10-12T04:03:04.381Z"},{"id":1575,"locale":"ko","published_at":"2024-10-12T04:03:04.381Z"},{"id":1467,"locale":"de","published_at":"2024-10-12T04:03:04.381Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Col_Pali_Visual_Retriever_with_Col_BERT_strategy_d258c79a05.png","belong":"blog","authorNames":["Stephen Batifol"]},{"id":"blog-606","title":"Scaling Search for AI: How Milvus Outperforms OpenSearch","image":{"id":4914,"url":"https://assets.zilliz.com/Scaling_Search_for_AI_How_Milvus_Outperforms_Open_Search_af64f898ad.png"},"display_time":"Oct 11, 2024","deploy_time":null,"url":"scale-search-for-ai-how-milvus-outperforms-opensearch","abstract":"Explore how Milvus matches OpenSearch in speed and scalability and surpasses it with its specialized vector search capabilities ","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":115,"name":"Stephen Batifol","author_tags":"Developer Advocate ","published_at":"2024-03-07T03:46:04.655Z","created_by":18,"updated_by":18,"created_at":"2024-03-07T03:46:02.457Z","updated_at":"2024-07-18T15:56:42.529Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/stephen-batifol/","self_intro":"Stephen Batifol is a Developer Advocate at Zilliz. He previously worked as a Machine Learning Engineer at Wolt, where he was working on the ML Platform and as a Data Scientist at Brevo. Stephen studied Computer Science and Artificial Intelligence. He enjoys dancing and surfing. \n","repost_to_medium":null,"repost_state":null,"meta_description":"Stephen Batifol is a Developer Advocate at Zilliz.","locale":"en"}],"read_time":5,"localizations":[{"id":1072,"locale":"ja-JP","published_at":"2024-10-11T13:59:52.010Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Scaling_Search_for_AI_How_Milvus_Outperforms_Open_Search_af64f898ad.png","belong":"blog","authorNames":["Stephen Batifol"]},{"id":"learn-261","title":"What is Mixture of Experts (MoE)? ","image":{"id":6448,"url":"https://assets.zilliz.com/What_is_Mixture_of_Experts_Mo_E_377a685c52.png"},"display_time":"Oct 10, 2024","url":"what-is-mixture-of-experts","abstract":"Mixture of Experts (MoE): a neural network architecture to improve model efficiency and scalability by selecting specialized experts for different tasks.\n","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":118,"name":" Haziqa Sajid","author_tags":"Freelance Technical Writer","published_at":"2024-03-12T10:25:34.265Z","created_by":18,"updated_by":18,"created_at":"2024-03-12T10:25:31.148Z","updated_at":"2024-07-03T07:58:27.010Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/haziqa-sajid-22b53245/","self_intro":"Digital Storytelling for Data, AI, B2B \u0026 SaaS","repost_to_medium":null,"repost_state":null,"meta_description":" Haziqa Sajid, Freelance Technical Writer","locale":"en"}],"read_time":12,"localizations":[{"id":483,"locale":"ja-JP","published_at":"2024-10-10T21:39:12.780Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/What_is_Mixture_of_Experts_Mo_E_377a685c52.png","belong":"learn","authorNames":[" Haziqa Sajid"]},{"id":"blog-605","title":"Industrial Problem-Solving through Domain-Specific Models and Agentic AI: A Semiconductor Manufacturing Case Study","image":{"id":5026,"url":"https://assets.zilliz.com/Industrial_Problem_Solving_through_Domain_Specific_Models_and_Agentic_AI_A_Semiconductor_Manufacturing_Case_Study_086844c3a6.png"},"display_time":"Oct 09, 2024","deploy_time":null,"url":"industrial-problem-solving-through-domain-specific-models-and-agentic-ai-in-semiconductor-manufacturing","abstract":"Exploring how domain-specific models and agentic AI systems can capture, share, and apply specialized knowledge for problem-solving in the semiconductor manufacturing industry.","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":179,"name":"Simon Mwaniki ","author_tags":null,"published_at":"2024-09-11T00:44:07.918Z","created_by":82,"updated_by":82,"created_at":"2024-09-11T00:44:06.462Z","updated_at":"2024-09-27T22:42:13.512Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":13,"localizations":[{"id":1367,"locale":"ja-JP","published_at":"2024-10-08T10:10:30.984Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Industrial_Problem_Solving_through_Domain_Specific_Models_and_Agentic_AI_A_Semiconductor_Manufacturing_Case_Study_086844c3a6.png","belong":"blog","authorNames":["Simon Mwaniki "]},{"id":"learn-260","title":"What is Object Detection? A Comprehensive Guide","image":{"id":6449,"url":"https://assets.zilliz.com/What_is_Object_Detection_A_Comprehensive_Guide_8344282427.png"},"display_time":"Oct 08, 2024","url":"what-is-object-detection","abstract":"Object detection is a computer vision technique that uses neural networks to classify and locate objects, such as humans, buildings, or cars, in images or video. ","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":118,"name":" Haziqa Sajid","author_tags":"Freelance Technical Writer","published_at":"2024-03-12T10:25:34.265Z","created_by":18,"updated_by":18,"created_at":"2024-03-12T10:25:31.148Z","updated_at":"2024-07-03T07:58:27.010Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/haziqa-sajid-22b53245/","self_intro":"Digital Storytelling for Data, AI, B2B \u0026 SaaS","repost_to_medium":null,"repost_state":null,"meta_description":" Haziqa Sajid, Freelance Technical Writer","locale":"en"}],"read_time":11,"localizations":[{"id":448,"locale":"ja-JP","published_at":"2024-10-08T09:54:07.283Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/What_is_Object_Detection_A_Comprehensive_Guide_8344282427.png","belong":"learn","authorNames":[" Haziqa Sajid"]},{"id":"blog-248","title":"How to Choose A Vector Database: Weaviate Cloud vs. Zilliz Cloud","image":{"id":1819,"url":"https://assets.zilliz.com/Zilliz_Cloud_vs_Weaviate_Cloud_fb004765cd.png"},"display_time":"Oct 07, 2024","deploy_time":"2023-09-21T13:30:00.000Z","url":"Weaviate-cloud-vs-zilliz","abstract":"Compare Weaviate Cloud vs. Zilliz Cloud and Milvus in this in-depth benchmark, cost, and features comparison.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":76,"name":"Steffi Li","author_tags":"Director of Product Marketing","published_at":"2023-07-13T17:18:42.023Z","created_by":18,"updated_by":18,"created_at":"2023-07-13T17:16:54.449Z","updated_at":"2023-07-13T17:18:42.070Z","home_page":null,"home_page_link":null,"self_intro":"Steffi is the Director of Product Marketing at Zilliz, with prior experience leading the GTM strategies for open-source data technologies such as Apache Kafka and Apache Airflow. Passionate about travel, yoga, and non-fiction reading, she brings a balanced and enriched worldview to her professional pursuits.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":8,"localizations":[{"id":1053,"locale":"ja-JP","published_at":"2023-09-22T04:44:44.125Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Zilliz_Cloud_vs_Weaviate_Cloud_fb004765cd.png","belong":"blog","authorNames":["Steffi Li"]},{"id":"blog-604","title":"A Different Angle: Retrieval Optimized Embedding Models","image":{"id":6508,"url":"https://assets.zilliz.com/A_Different_Angle_Retrieval_Optimized_Embedding_Models_21cc11e653.png"},"display_time":"Oct 07, 2024","deploy_time":null,"url":"a-different-angle-retrieval-optimized-embedding-models","abstract":"This blog will demonstrate how GCL can be integrated with Milvus, a leading vector database, to create optimized Retrieval-Augmented Generation (RAG) systems.","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":158,"name":"Denis Kuria","author_tags":"Freelance Technical Writer","published_at":"2024-05-01T00:39:32.350Z","created_by":18,"updated_by":18,"created_at":"2024-05-01T00:39:30.888Z","updated_at":"2024-07-03T06:50:56.660Z","home_page":null,"home_page_link":null,"self_intro":"Denis is a machine learning engineer who enjoys writing guides to help other developers. He has a bachelor's in computer science and loves hiking and exploring the world.\n","repost_to_medium":null,"repost_state":null,"meta_description":"Denis Kuria is a freelance technical writer at Zilliz. ","locale":"en"}],"read_time":13,"localizations":[{"id":1013,"locale":"ja-JP","published_at":"2024-10-07T22:22:09.034Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/A_Different_Angle_Retrieval_Optimized_Embedding_Models_21cc11e653.png","belong":"blog","authorNames":["Denis Kuria"]},{"id":"blog-603","title":"Modern Analytics \u0026 Reporting with Milvus Vector DB and GenAI","image":{"id":4882,"url":"https://assets.zilliz.com/Modern_Analytics_and_Reporting_with_Milvus_Vector_DB_and_Gen_AI_6f8d833f91.png"},"display_time":"Oct 06, 2024","deploy_time":null,"url":"modern-analytics-and-reporting-with-milvus-vector-db-genai","abstract":"Understand the role of vector databases such as Milvus, how Qarbine simplifies the analytics process, and how Milvus and Qarbine can be integrated to create advanced GenAI applications. \n","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":170,"name":"Yesha Shastri","author_tags":"Freelance Technical Writer in AI/ML","published_at":"2024-07-29T08:44:59.761Z","created_by":18,"updated_by":18,"created_at":"2024-07-29T08:44:38.291Z","updated_at":"2024-07-29T08:44:59.820Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/yeshashastri/","self_intro":"Yesha Shastri, Freelance Technical Writer in AI/ML","repost_to_medium":null,"repost_state":null,"meta_description":"Yesha Shastri, Freelance Technical Writer","locale":"en"}],"read_time":7,"localizations":[{"id":1046,"locale":"ja-JP","published_at":"2024-10-07T18:49:53.601Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Modern_Analytics_and_Reporting_with_Milvus_Vector_DB_and_Gen_AI_6f8d833f91.png","belong":"blog","authorNames":["Yesha Shastri"]},{"id":"learn-259","title":"Efficient Memory Management for Large Language Model Serving with PagedAttention","image":{"id":5027,"url":"https://assets.zilliz.com/Efficient_Memory_Management_for_Large_Language_Model_Serving_with_Paged_Attention_1_69d839bc77.png"},"display_time":"Oct 05, 2024","url":"efficient-memory-management-for-llm-serving-pagedattention","abstract":"PagedAttention and vLLM solve important challenges in serving LLMs, particularly the high costs and inefficiencies in GPU memory usage when using it for inference. \n","tags":[{"id":73,"name":"Paper Reading","published_at":"2024-08-10T14:40:10.906Z","created_by":60,"updated_by":60,"created_at":"2024-08-10T14:40:09.192Z","updated_at":"2024-08-10T14:40:10.914Z","locale":"en"}],"authors":[{"id":125,"name":"Ruben Winastwan","author_tags":"Freelance Technical Writer","published_at":"2024-03-26T09:16:27.310Z","created_by":18,"updated_by":18,"created_at":"2024-03-26T09:16:24.498Z","updated_at":"2024-07-03T07:56:29.256Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Ruben Winastwan, Freelance Technical Writer","locale":"en"}],"read_time":15,"localizations":[{"id":345,"locale":"ja-JP","published_at":"2024-10-07T18:33:48.400Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Efficient_Memory_Management_for_Large_Language_Model_Serving_with_Paged_Attention_1_69d839bc77.png","belong":"learn","authorNames":["Ruben Winastwan"]},{"id":"blog-602","title":"Evaluating Safety \u0026 Alignment of LLM in Specific Domains","image":{"id":6451,"url":"https://assets.zilliz.com/Evaluating_Safety_and_Alignment_of_LLM_in_Specific_Domains_73f8dea409.png"},"display_time":"Oct 04, 2024","deploy_time":null,"url":"evaluating-safety-and-alignment-of-llm-in-specific-domains","abstract":"In this blog, we’ll explore how companies like Hydrox AI and AI Alliance are tackling the critical challenges of AI safety and evaluation.\n","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":178,"name":"Benito Martin","author_tags":null,"published_at":"2024-09-10T18:31:20.152Z","created_by":82,"updated_by":82,"created_at":"2024-09-10T18:30:36.499Z","updated_at":"2024-10-02T17:35:02.538Z","home_page":null,"home_page_link":null,"self_intro":"Freelance Technical Writer","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":8,"localizations":[{"id":1250,"locale":"ja-JP","published_at":"2024-10-07T18:16:03.172Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Evaluating_Safety_and_Alignment_of_LLM_in_Specific_Domains_73f8dea409.png","belong":"blog","authorNames":["Benito Martin"]},{"id":"blog-582","title":"Contributing to Open Source Milvus: A Beginner’s Guide","image":{"id":6455,"url":"https://assets.zilliz.com/Contributing_to_Open_Source_Milvus_fc74e90958.png"},"display_time":"Oct 03, 2024","deploy_time":null,"url":"contributing-to-open-source-milvus-beginners-guide","abstract":"Contributing to open source software is a rewarding way to improve your programming skills, collaborate with others, and give back to the development community. Learn how to contribute to Milvus with this beginner guide!\n","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":183,"name":"Stefan Webb","author_tags":"Developer Advocate, Zilliz","published_at":"2024-09-25T22:53:17.678Z","created_by":82,"updated_by":82,"created_at":"2024-09-25T18:15:43.954Z","updated_at":"2024-09-25T22:53:17.714Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/stefan-webb/","self_intro":"Stefan Webb is a Developer Advocate at Zilliz, where he advocates for the open-source vector database, Milvus. Prior to this, he spent three years in industry as an Applied ML Researcher at Twitter and Meta, collaborating with product teams to tackle their most complex challenges.\nStefan holds a PhD from the University of Oxford and has published papers at prestigious machine learning conferences such as NeurIPS, ICLR, and ICML. He is passionate about generative AI and is eager to leverage his deep technical expertise to contribute to the open-source community.\n","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":5,"localizations":[{"id":1116,"locale":"ja-JP","published_at":"2024-10-03T21:45:50.942Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Contributing_to_Open_Source_Milvus_fc74e90958.png","belong":"blog","authorNames":["Stefan Webb"]},{"id":"blog-574","title":"Top 5 Reasons to Migrate from Open Source Milvus to Zilliz Cloud","image":{"id":6510,"url":"https://assets.zilliz.com/Top_5_Reasons_05c453a577.png"},"display_time":"Oct 02, 2024","deploy_time":null,"url":"top-5-reasons-to-migrate-milvus-to-zilliz-cloud","abstract":"This article will cover five reasons to migrate from Milvus to Zilliz Cloud. We will focus on performance, scalability, security, availability and cost. ","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":76,"name":"Steffi Li","author_tags":"Director of Product Marketing","published_at":"2023-07-13T17:18:42.023Z","created_by":18,"updated_by":18,"created_at":"2023-07-13T17:16:54.449Z","updated_at":"2023-07-13T17:18:42.070Z","home_page":null,"home_page_link":null,"self_intro":"Steffi is the Director of Product Marketing at Zilliz, with prior experience leading the GTM strategies for open-source data technologies such as Apache Kafka and Apache Airflow. Passionate about travel, yoga, and non-fiction reading, she brings a balanced and enriched worldview to her professional pursuits.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":11,"localizations":[{"id":823,"locale":"ja-JP","published_at":"2024-10-02T21:44:28.334Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Top_5_Reasons_05c453a577.png","belong":"blog","authorNames":["Steffi Li"]},{"id":"blog-581","title":"From CLIP to JinaCLIP: General Text-Image Representation Learning for Search and Multimodal RAG","image":{"id":6509,"url":"https://assets.zilliz.com/From_CLIP_to_Jina_CLIP_General_Text_Image_Representation_Learning_for_Search_and_Multimodal_RAG_6a697fad61.png"},"display_time":"Oct 01, 2024","deploy_time":null,"url":"clip-to-jinaclip-general-text-image-search-multimodal-rag","abstract":"In this blog, we will implement a multimodal similarity search system. This system will use JinaCLIP to generate multimodal embeddings and the Milvus vector database to store and retrieve similar embeddings given a certain query. ","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":179,"name":"Simon Mwaniki ","author_tags":null,"published_at":"2024-09-11T00:44:07.918Z","created_by":82,"updated_by":82,"created_at":"2024-09-11T00:44:06.462Z","updated_at":"2024-09-27T22:42:13.512Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":15,"localizations":[{"id":992,"locale":"ja-JP","published_at":"2024-10-02T18:03:25.766Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/From_CLIP_to_Jina_CLIP_General_Text_Image_Representation_Learning_for_Search_and_Multimodal_RAG_6a697fad61.png","belong":"blog","authorNames":["Simon Mwaniki "]},{"id":"blog-570","title":"Building a GraphRAG Agent With Neo4j and Milvus","image":{"id":6511,"url":"https://assets.zilliz.com/Building_a_Graph_RAG_Agent_with_Neo4j_and_Milvus_bf92e29f2c.png"},"display_time":"Sep 30, 2024","deploy_time":"2024-09-30T19:00:00.000Z","url":"build-graphrag-agent-with-neo4j-and-milvus","abstract":"In this blog post, we explain how to build a GraphRAG Agent using Neo4j and Milvus. By combining the strengths of graph databases and vector search, this agent provides accurate and relevant answers to user queries. \n","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":185,"name":"Jason Koo","author_tags":"Developer Advocate, Neo4j","published_at":"2024-09-30T23:41:13.172Z","created_by":82,"updated_by":82,"created_at":"2024-09-30T23:41:11.551Z","updated_at":"2024-09-30T23:41:13.212Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/jason-koo-usa/","self_intro":"Jason Koo is a Developer Advocate at Neo4j","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"},{"id":115,"name":"Stephen Batifol","author_tags":"Developer Advocate ","published_at":"2024-03-07T03:46:04.655Z","created_by":18,"updated_by":18,"created_at":"2024-03-07T03:46:02.457Z","updated_at":"2024-07-18T15:56:42.529Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/stephen-batifol/","self_intro":"Stephen Batifol is a Developer Advocate at Zilliz. He previously worked as a Machine Learning Engineer at Wolt, where he was working on the ML Platform and as a Data Scientist at Brevo. Stephen studied Computer Science and Artificial Intelligence. He enjoys dancing and surfing. \n","repost_to_medium":null,"repost_state":null,"meta_description":"Stephen Batifol is a Developer Advocate at Zilliz.","locale":"en"}],"read_time":7,"localizations":[{"id":1126,"locale":"ja-JP","published_at":"2024-10-01T00:09:30.318Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Building_a_Graph_RAG_Agent_with_Neo4j_and_Milvus_bf92e29f2c.png","belong":"blog","authorNames":["Jason Koo","Stephen Batifol"]},{"id":"learn-258","title":"Decoding Transformer Models: A Study of Their Architecture and Underlying Principles","image":{"id":4666,"url":"https://assets.zilliz.com/Decoding_Transformer_Models_A_Study_of_Their_Architecture_and_Underlying_Principles_62070f2522.png"},"display_time":"Sep 28, 2024","url":"decoding-transformer-models-a-study-of-their-architecture-and-underlying-principles","abstract":"A Transformer model is a type of architecture for processing sequences, primarily used in natural language processing (NLP). ","tags":[{"id":73,"name":"Paper Reading","published_at":"2024-08-10T14:40:10.906Z","created_by":60,"updated_by":60,"created_at":"2024-08-10T14:40:09.192Z","updated_at":"2024-08-10T14:40:10.914Z","locale":"en"}],"authors":[{"id":102,"name":"David Wang","author_tags":"Algorithm Engineer at Zilliz","published_at":"2023-10-27T08:41:57.519Z","created_by":18,"updated_by":18,"created_at":"2023-10-27T08:41:55.636Z","updated_at":"2024-04-16T02:43:37.282Z","home_page":"GitHub","home_page_link":"https://github.com/wxywb","self_intro":"David Wang, Algorithm Engineer at Zilliz, brings extensive expertise in computer vision and natural language processing. His contributions to advanced embedding algorithm research, including projects like Towhee and GPTCache, reflect his commitment to advancing AI technologies. Before joining Zilliz, he worked at Alibaba Cloud for large-scale object recognition and classification projects. David holds a Master's degree from Dalian University of Technology.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":16,"localizations":[{"id":347,"locale":"ja-JP","published_at":"2024-09-28T03:19:30.456Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Decoding_Transformer_Models_A_Study_of_Their_Architecture_and_Underlying_Principles_62070f2522.png","belong":"learn","authorNames":["David Wang"]},{"id":"blog-564","title":"Zilliz is named a Leader in the Forrester Wave™ Vector Database Report","image":{"id":6500,"url":"https://assets.zilliz.com/Forrester_8f93a81f25.png"},"display_time":"Sep 27, 2024","deploy_time":null,"url":"zilliz-named-a-leader-in-the-forrester-wave-vector-database-report","abstract":"Forrester, one of the most well-known research firms in tech, has just published their 2024 Wave™ report for Vector Database Providers, and we’re a Leader! 🎉","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"},{"id":4,"name":"Company","published_at":"2021-01-21T02:28:23.551Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:20.676Z","updated_at":"2021-01-21T02:28:23.824Z","locale":"en"}],"authors":[{"id":36,"name":"Chris Churilo","author_tags":"VP of Marketing","published_at":"2023-04-11T16:51:05.002Z","created_by":18,"updated_by":53,"created_at":"2023-04-11T16:42:46.067Z","updated_at":"2025-01-16T22:35:53.011Z","home_page":"GitHub","home_page_link":"https://github.com/ChrisChurilo","self_intro":"Chris Churilo is the VP of Marketing \u0026 Community at Zilliz where she leads all community, developer relations, and marketing efforts. Prior to Zilliz, Chris was a founding member of the InfluxData’s go to market efforts and helped propel the time series database platform to dominance in the market. In earlier roles she defined and designed a SaaS monitoring solution at Centroid, and prior to that she was the VP of product management at iPass and was the LOB for several cloud services that required her to track the business and operational metrics and analytics to help identify and resolve issues.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":2,"localizations":[{"id":1216,"locale":"ja-JP","published_at":"2024-09-27T04:02:50.725Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Forrester_8f93a81f25.png","belong":"blog","authorNames":["Chris Churilo"]},{"id":"blog-563","title":"Garbage In, Garbage Out: Why Poor Data Curation Is Killing Your AI Models","image":{"id":4634,"url":"https://assets.zilliz.com/Garbage_In_Garbage_Out_Why_poor_data_curation_is_killing_your_AI_models_07b41b1094.png"},"display_time":"Sep 26, 2024","deploy_time":null,"url":"why-poor-data-curation-is-killing-your-ai-models","abstract":"Encord highlighted the importance of data quality and market trends, presenting a roadmap to help organizations establish high-quality data production pipelines. ","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":45,"name":"Fendy Feng","author_tags":"Technical Marketing Writer","published_at":"2023-05-16T01:36:15.102Z","created_by":18,"updated_by":18,"created_at":"2023-05-16T00:04:12.065Z","updated_at":"2024-04-25T08:37:19.712Z","home_page":"GitHub","home_page_link":"https://www.linkedin.com/in/fendy311/","self_intro":"Fendy Feng is the Technical Marketing Writer at Zilliz. She has extensive experience developing and enhancing the impact of open-source projects in various global markets by producing high-quality, tailored content. Before joining Zilliz, Fendy worked as a Content Strategist at PingCAP, a fast-growing E-Series startup renowned for its open-source distributed SQL database.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"},{"id":147,"name":"ShriVarsheni R","author_tags":"Freelance Technical Writer","published_at":"2024-04-24T21:21:57.571Z","created_by":18,"updated_by":18,"created_at":"2024-04-24T21:21:55.818Z","updated_at":"2024-07-03T07:50:17.617Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"ShriVarsheni, Freelance Technical Writer","locale":"en"}],"read_time":8,"localizations":[{"id":1206,"locale":"ja-JP","published_at":"2024-09-26T23:33:35.879Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Garbage_In_Garbage_Out_Why_poor_data_curation_is_killing_your_AI_models_07b41b1094.png","belong":"blog","authorNames":["Fendy Feng","ShriVarsheni R"]},{"id":"blog-562","title":"Stefan Webb: Why I Joined Zilliz","image":{"id":6501,"url":"https://assets.zilliz.com/Why_I_joined_Zilliz_Stefan_4bbbede4ad.png"},"display_time":"Sep 25, 2024","deploy_time":null,"url":"why-i-joined-zilliz-stefan-webb","abstract":"Why Stefan Webb joined Zilliz","tags":[{"id":4,"name":"Company","published_at":"2021-01-21T02:28:23.551Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:20.676Z","updated_at":"2021-01-21T02:28:23.824Z","locale":"en"}],"authors":[{"id":183,"name":"Stefan Webb","author_tags":"Developer Advocate, Zilliz","published_at":"2024-09-25T22:53:17.678Z","created_by":82,"updated_by":82,"created_at":"2024-09-25T18:15:43.954Z","updated_at":"2024-09-25T22:53:17.714Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/stefan-webb/","self_intro":"Stefan Webb is a Developer Advocate at Zilliz, where he advocates for the open-source vector database, Milvus. Prior to this, he spent three years in industry as an Applied ML Researcher at Twitter and Meta, collaborating with product teams to tackle their most complex challenges.\nStefan holds a PhD from the University of Oxford and has published papers at prestigious machine learning conferences such as NeurIPS, ICLR, and ICML. He is passionate about generative AI and is eager to leverage his deep technical expertise to contribute to the open-source community.\n","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":2,"localizations":[{"id":1203,"locale":"ja-JP","published_at":"2024-09-25T22:58:51.132Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Why_I_joined_Zilliz_Stefan_4bbbede4ad.png","belong":"blog","authorNames":["Stefan Webb"]},{"id":"learn-256","title":"Deep Residual Learning for Image Recognition","image":{"id":4720,"url":"https://assets.zilliz.com/Deep_Residual_Learning_for_Image_Recognition_3d7890a9be.png"},"display_time":"Sep 24, 2024","url":"deep-residual-learning-for-image-recognition","abstract":"Deep residual learning solves the degradation problem, allowing us to train a neural network while still potentially improving its performance.","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":125,"name":"Ruben Winastwan","author_tags":"Freelance Technical Writer","published_at":"2024-03-26T09:16:27.310Z","created_by":18,"updated_by":18,"created_at":"2024-03-26T09:16:24.498Z","updated_at":"2024-07-03T07:56:29.256Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Ruben Winastwan, Freelance Technical Writer","locale":"en"}],"read_time":10,"localizations":[{"id":330,"locale":"ja-JP","published_at":"2024-09-26T06:55:10.244Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Deep_Residual_Learning_for_Image_Recognition_3d7890a9be.png","belong":"learn","authorNames":["Ruben Winastwan"]},{"id":"blog-559","title":"Unlock AI-powered search with Fivetran and Milvus","image":{"id":6512,"url":"https://assets.zilliz.com/Sep_9_Introducing_Fivetran_Connector_Streamlined_Unstructured_Data_Integration_from_500_Sources_766d9fa6ea.png"},"display_time":"Sep 23, 2024","deploy_time":null,"url":"unlock-ai-powered-search-with-fivetran-and-milvus","abstract":"Fivetran supports the Milvus vector database as a destination, making it easier to onboard every data source for RAG and AI-powered search.\n","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":101,"name":"Jiang Chen","author_tags":"Head of Ecosystem and Developer Relations","published_at":"2023-10-16T07:05:20.176Z","created_by":18,"updated_by":82,"created_at":"2023-10-16T07:05:18.702Z","updated_at":"2024-09-10T17:33:55.053Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/jiang-0616/","self_intro":"Jiang is currently Head of Ecosystem and Developer Relations at Zilliz. He has years of experience in data infrastructures and cloud security. Before joining Zilliz, he had previously served as a tech lead and product manager at Google, where he led the development of web-scale semantic understanding and search indexing that powers innovative search products such as short video search. He has extensive industry experience handling massive unstructured data and multimedia content retrieval. He has also worked on cloud authorization systems and research on data privacy technologies. Jiang holds a Master's degree in Computer Science from the University of Michigan.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"},{"id":181,"name":"Charles Wang","author_tags":"Lead Product Evangelist, Fivetran","published_at":"2024-09-23T21:43:13.713Z","created_by":82,"updated_by":82,"created_at":"2024-09-23T21:43:10.420Z","updated_at":"2024-09-24T00:19:57.910Z","home_page":null,"home_page_link":null,"self_intro":"Lead Product Evangelist, Fivetran","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":4,"localizations":[{"id":1180,"locale":"ja-JP","published_at":"2024-09-23T21:49:18.508Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Sep_9_Introducing_Fivetran_Connector_Streamlined_Unstructured_Data_Integration_from_500_Sources_766d9fa6ea.png","belong":"blog","authorNames":["Jiang Chen","Charles Wang"]},{"id":"learn-257","title":"DistilBERT: A Distilled Version of BERT","image":{"id":6513,"url":"https://assets.zilliz.com/Distil_BERT_a_distilled_version_of_BERT_smaller_faster_cheaper_and_lighter_26e01d2771.png"},"display_time":"Sep 22, 2024","url":"distilbert-distilled-version-of-bert","abstract":"DistilBERT was introduced as a smaller, faster, and distilled version of BERT. It maintains 97% of BERT's language understanding capabilities while being 40% small and 60% faster. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":118,"name":" Haziqa Sajid","author_tags":"Freelance Technical Writer","published_at":"2024-03-12T10:25:34.265Z","created_by":18,"updated_by":18,"created_at":"2024-03-12T10:25:31.148Z","updated_at":"2024-07-03T07:58:27.010Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/haziqa-sajid-22b53245/","self_intro":"Digital Storytelling for Data, AI, B2B \u0026 SaaS","repost_to_medium":null,"repost_state":null,"meta_description":" Haziqa Sajid, Freelance Technical Writer","locale":"en"}],"read_time":10,"localizations":[{"id":349,"locale":"ja-JP","published_at":"2024-09-26T23:53:06.484Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Distil_BERT_a_distilled_version_of_BERT_smaller_faster_cheaper_and_lighter_26e01d2771.png","belong":"learn","authorNames":[" Haziqa Sajid"]},{"id":"blog-580","title":"Challenges in Structured Document Data Extraction at Scale with LLMs","image":{"id":6514,"url":"https://assets.zilliz.com/Challenges_in_Structured_Document_Data_Extraction_at_Scale_with_LL_Ms_9dbf7095dd.png"},"display_time":"Sep 21, 2024","deploy_time":null,"url":"challenges-in-structured-document-data-extraction-at-scale-llms","abstract":"In this blog, we’ll dive into the primary challenges of structured document data extraction. We'll also explore how Unstract tackles various scenarios, including its integration with vector databases like Milvus, to bring structure to previously unmanageable data.\n","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":178,"name":"Benito Martin","author_tags":null,"published_at":"2024-09-10T18:31:20.152Z","created_by":82,"updated_by":82,"created_at":"2024-09-10T18:30:36.499Z","updated_at":"2024-10-02T17:35:02.538Z","home_page":null,"home_page_link":null,"self_intro":"Freelance Technical Writer","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":5,"localizations":[{"id":958,"locale":"ja-JP","published_at":"2024-10-02T16:56:01.325Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Challenges_in_Structured_Document_Data_Extraction_at_Scale_with_LL_Ms_9dbf7095dd.png","belong":"blog","authorNames":["Benito Martin"]},{"id":"blog-575","title":"How Testcontainers Streamlines the Development of AI-Powered Applications","image":{"id":6515,"url":"https://assets.zilliz.com/How_Testcontainers_Streamlines_the_Development_of_AI_Powered_Applications_a67578b476.png"},"display_time":"Sep 20, 2024","deploy_time":null,"url":"how-testcontainers-streamlines-the-development-of-ai-powered-apps","abstract":"In this article, we explore the concept of containerization and one of its essential tools, Docker, and how they decrease the complexity of the application development process. ","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":150,"name":"Tim Mugabi","author_tags":"Freelance Technical Writer","published_at":"2024-04-24T21:23:34.511Z","created_by":18,"updated_by":18,"created_at":"2024-04-24T21:23:32.810Z","updated_at":"2024-07-03T07:49:21.138Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Tim Mugabi, Freelance Technical Writer","locale":"en"}],"read_time":9,"localizations":[{"id":1083,"locale":"ja-JP","published_at":"2024-10-02T16:27:34.108Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/How_Testcontainers_Streamlines_the_Development_of_AI_Powered_Applications_a67578b476.png","belong":"blog","authorNames":["Tim Mugabi"]},{"id":"blog-560","title":"Unstructured Data Processing from Cloud to Edge","image":{"id":5319,"url":"https://assets.zilliz.com/Unstructured_Data_Processing_from_Cloud_to_Edge_715585eebd.png"},"display_time":"Sep 19, 2024","deploy_time":null,"url":"unstructured-data-processing-from-cloud-to-edge","abstract":"Edge computing brings data processing closer to the source on small devices; vectorDBs empower them to handle the growing unstructured data in real-time.","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":158,"name":"Denis Kuria","author_tags":"Freelance Technical Writer","published_at":"2024-05-01T00:39:32.350Z","created_by":18,"updated_by":18,"created_at":"2024-05-01T00:39:30.888Z","updated_at":"2024-07-03T06:50:56.660Z","home_page":null,"home_page_link":null,"self_intro":"Denis is a machine learning engineer who enjoys writing guides to help other developers. He has a bachelor's in computer science and loves hiking and exploring the world.\n","repost_to_medium":null,"repost_state":null,"meta_description":"Denis Kuria is a freelance technical writer at Zilliz. ","locale":"en"}],"read_time":20,"localizations":[{"id":931,"locale":"ja-JP","published_at":"2024-09-24T11:26:33.326Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Unstructured_Data_Processing_from_Cloud_to_Edge_715585eebd.png","belong":"blog","authorNames":["Denis Kuria"]},{"id":"blog-561","title":"Multimodal RAG: Expanding Beyond Text for Smarter AI","image":{"id":4599,"url":"https://assets.zilliz.com/Multimodal_RAG_Expanding_Beyond_Text_for_Smarter_AI_ea4faab01b.png"},"display_time":"Sep 19, 2024","deploy_time":null,"url":"multimodal-rag-expanding-beyond-text-for-smarter-ai","abstract":"Multimodal RAG systems provide a comprehensive solution for leveraging the full spectrum of available information, providing better context to LLMs. ","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":115,"name":"Stephen Batifol","author_tags":"Developer Advocate ","published_at":"2024-03-07T03:46:04.655Z","created_by":18,"updated_by":18,"created_at":"2024-03-07T03:46:02.457Z","updated_at":"2024-07-18T15:56:42.529Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/stephen-batifol/","self_intro":"Stephen Batifol is a Developer Advocate at Zilliz. He previously worked as a Machine Learning Engineer at Wolt, where he was working on the ML Platform and as a Data Scientist at Brevo. Stephen studied Computer Science and Artificial Intelligence. He enjoys dancing and surfing. \n","repost_to_medium":null,"repost_state":null,"meta_description":"Stephen Batifol is a Developer Advocate at Zilliz.","locale":"en"}],"read_time":6,"localizations":[{"id":1195,"locale":"ja-JP","published_at":"2024-09-24T11:59:54.638Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Multimodal_RAG_Expanding_Beyond_Text_for_Smarter_AI_ea4faab01b.png","belong":"blog","authorNames":["Stephen Batifol"]},{"id":"blog-550","title":"Ensuring Secure and Permission-Aware RAG Deployments","image":{"id":6516,"url":"https://assets.zilliz.com/Ensuring_Secure_and_Permission_Aware_RAG_Deployments_37a12bf485.png"},"display_time":"Sep 18, 2024","deploy_time":null,"url":"ensure-secure-and-permission-aware-rag-deployments","abstract":"This blog introduces key security considerations for RAG deployments, including data anonymization, strong encryption, input/output validation, and robust access controls, among other critical security measures.","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":178,"name":"Benito Martin","author_tags":null,"published_at":"2024-09-10T18:31:20.152Z","created_by":82,"updated_by":82,"created_at":"2024-09-10T18:30:36.499Z","updated_at":"2024-10-02T17:35:02.538Z","home_page":null,"home_page_link":null,"self_intro":"Freelance Technical Writer","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":12,"localizations":[{"id":1261,"locale":"ja-JP","published_at":"2024-09-19T06:19:58.508Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Ensuring_Secure_and_Permission_Aware_RAG_Deployments_37a12bf485.png","belong":"blog","authorNames":["Benito Martin"]},{"id":"blog-549","title":"Harnessing Function Calling to Build Smarter LLM Applications","image":{"id":4883,"url":"https://assets.zilliz.com/Harnessing_Function_Calling_to_Build_Smarter_LLM_Applications_3465e52f88.png"},"display_time":"Sep 17, 2024","deploy_time":null,"url":"harnessing-function-calling-to-build-smarter-llm-apps","abstract":"Function calling allows LLMs to go beyond the limitations of their static training data by querying live databases, executing commands, or performing real-time calculations.","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":179,"name":"Simon Mwaniki ","author_tags":null,"published_at":"2024-09-11T00:44:07.918Z","created_by":82,"updated_by":82,"created_at":"2024-09-11T00:44:06.462Z","updated_at":"2024-09-27T22:42:13.512Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":13,"localizations":[{"id":1133,"locale":"ja-JP","published_at":"2024-09-19T06:04:03.354Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Harnessing_Function_Calling_to_Build_Smarter_LLM_Applications_3465e52f88.png","belong":"blog","authorNames":["Simon Mwaniki "]},{"id":"blog-543","title":"Tame High-Cardinality Categorical Data in Agentic SQL Generation with VectorDBs","image":{"id":6517,"url":"https://assets.zilliz.com/Tame_High_Cardinality_Categorical_Data_in_Agentic_SQL_Generation_with_Vector_D_Bs_f77a5869d9.png"},"display_time":"Sep 16, 2024","deploy_time":null,"url":"tame-high-cardinality-categorical-data-in-agentic-sql-generation-with-vectordbs","abstract":"This article explores how integrating vector databases with agentic text-to-SQL systems can address High-Cardinality Categorical Data problems. \n","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":180,"name":"Gunther Hagleitner","author_tags":"CEO and co-founder of Waii. ","published_at":"2024-09-13T02:54:59.766Z","created_by":60,"updated_by":60,"created_at":"2024-09-13T02:54:58.186Z","updated_at":"2024-09-13T02:54:59.810Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/hagleitn/","self_intro":"Gunther Hagleitner is the current CEO and co-founder of Waii. He is a seasoned product and engineering leader with a 20+ year track record in SQL and analytics. Previously, as SVP at Cribl and CVP at Cloudera, he focused on simplifying data through innovation and open-source. Gunther excels at both scaling products and teams as well as new product introductions. He is passionate about creating user-centric solutions that solve real-world problems.","repost_to_medium":null,"repost_state":null,"meta_description":"Gunther Hagleitner is the current CEO and co-founder of Waii. ","locale":"en"},{"id":101,"name":"Jiang Chen","author_tags":"Head of Ecosystem and Developer Relations","published_at":"2023-10-16T07:05:20.176Z","created_by":18,"updated_by":82,"created_at":"2023-10-16T07:05:18.702Z","updated_at":"2024-09-10T17:33:55.053Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/jiang-0616/","self_intro":"Jiang is currently Head of Ecosystem and Developer Relations at Zilliz. He has years of experience in data infrastructures and cloud security. Before joining Zilliz, he had previously served as a tech lead and product manager at Google, where he led the development of web-scale semantic understanding and search indexing that powers innovative search products such as short video search. He has extensive industry experience handling massive unstructured data and multimedia content retrieval. He has also worked on cloud authorization systems and research on data privacy technologies. Jiang holds a Master's degree in Computer Science from the University of Michigan.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":8,"localizations":[{"id":1069,"locale":"ja-JP","published_at":"2024-09-16T17:15:25.625Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Tame_High_Cardinality_Categorical_Data_in_Agentic_SQL_Generation_with_Vector_D_Bs_f77a5869d9.png","belong":"blog","authorNames":["Gunther Hagleitner","Jiang Chen"]},{"id":"blog-544","title":"Up to 50x Cost Savings for Building GenAI Apps Using Zilliz Cloud Serverless","image":{"id":4490,"url":"https://assets.zilliz.com/Up_to_50x_Cost_Savings_for_Building_Gen_AI_Apps_Using_Zilliz_Cloud_Serverless_1_8b086da909.png"},"display_time":"Sep 15, 2024","deploy_time":null,"url":"build-gen-ai-apps-using-zilliz-cloud-serverless","abstract":"Zilliz Cloud Serverless allows users to store, index, and query massive amounts of vectors at only a fraction of the cost while keeping a competitive level of performance. \n","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":125,"name":"Ruben Winastwan","author_tags":"Freelance Technical Writer","published_at":"2024-03-26T09:16:27.310Z","created_by":18,"updated_by":18,"created_at":"2024-03-26T09:16:24.498Z","updated_at":"2024-07-03T07:56:29.256Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Ruben Winastwan, Freelance Technical Writer","locale":"en"}],"read_time":10,"localizations":[{"id":1078,"locale":"ja-JP","published_at":"2024-09-16T22:13:54.102Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Up_to_50x_Cost_Savings_for_Building_Gen_AI_Apps_Using_Zilliz_Cloud_Serverless_1_8b086da909.png","belong":"blog","authorNames":["Ruben Winastwan"]},{"id":"blog-545","title":"Advanced Video Search: Leveraging Twelve Labs and Milvus for Semantic Retrieval","image":{"id":4580,"url":"https://assets.zilliz.com/Advanced_Video_Search_Leveraging_Twelve_Labs_and_Milvus_for_Semantic_Retrieval_3_9185d3b020.png"},"display_time":"Sep 14, 2024","deploy_time":null,"url":"advanced-video-search-twelve-labs-milvus-semantic-retrieval","abstract":"In August 2024, Twelve Labs and Milvus (vector database by Zilliz) joined hands to create powerful video search applications. ","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":170,"name":"Yesha Shastri","author_tags":"Freelance Technical Writer in AI/ML","published_at":"2024-07-29T08:44:59.761Z","created_by":18,"updated_by":18,"created_at":"2024-07-29T08:44:38.291Z","updated_at":"2024-07-29T08:44:59.820Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/yeshashastri/","self_intro":"Yesha Shastri, Freelance Technical Writer in AI/ML","repost_to_medium":null,"repost_state":null,"meta_description":"Yesha Shastri, Freelance Technical Writer","locale":"en"}],"read_time":8,"localizations":[{"id":1082,"locale":"ja-JP","published_at":"2024-09-17T17:36:20.714Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Advanced_Video_Search_Leveraging_Twelve_Labs_and_Milvus_for_Semantic_Retrieval_3_9185d3b020.png","belong":"blog","authorNames":["Yesha Shastri"]},{"id":"blog-538","title":"Introducing Comprehensive Monitoring \u0026 Observability in Zilliz Cloud","image":{"id":4442,"url":"https://assets.zilliz.com/Sep_9_An_Overview_of_Zilliz_Cloud_Monitoring_Metrics_67950b7ff2.png"},"display_time":"Sep 13, 2024","deploy_time":null,"url":"introducing-monitoring-and-observability-in-zilliz-cloud","abstract":"This powerful addition to Zilliz Cloud enables users to monitor their clusters' performance, set up custom alerts, and quickly respond to potential issues.","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":76,"name":"Steffi Li","author_tags":"Director of Product Marketing","published_at":"2023-07-13T17:18:42.023Z","created_by":18,"updated_by":18,"created_at":"2023-07-13T17:16:54.449Z","updated_at":"2023-07-13T17:18:42.070Z","home_page":null,"home_page_link":null,"self_intro":"Steffi is the Director of Product Marketing at Zilliz, with prior experience leading the GTM strategies for open-source data technologies such as Apache Kafka and Apache Airflow. Passionate about travel, yoga, and non-fiction reading, she brings a balanced and enriched worldview to her professional pursuits.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":4,"localizations":[{"id":1213,"locale":"ja-JP","published_at":"2024-09-13T02:27:14.409Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Sep_9_An_Overview_of_Zilliz_Cloud_Monitoring_Metrics_67950b7ff2.png","belong":"blog","authorNames":["Steffi Li"]},{"id":"blog-542","title":"Milvus on GPUs with NVIDIA RAPIDS cuVS ","image":{"id":4722,"url":"https://assets.zilliz.com/Milvus_on_GP_Us_with_NVIDIA_RAPIDS_cu_VS_58eab7154f.png"},"display_time":"Sep 12, 2024","deploy_time":null,"url":"milvus-on-gpu-with-nvidia-rapids-cuvs","abstract":"GPU-accelerated vector search through NVIDIA's cuVS library and CAGRA algorithm are highly beneficial for optimizing AI app performance in production. ","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":125,"name":"Ruben Winastwan","author_tags":"Freelance Technical Writer","published_at":"2024-03-26T09:16:27.310Z","created_by":18,"updated_by":18,"created_at":"2024-03-26T09:16:24.498Z","updated_at":"2024-07-03T07:56:29.256Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Ruben Winastwan, Freelance Technical Writer","locale":"en"}],"read_time":11,"localizations":[{"id":1545,"locale":"ru","published_at":"2024-09-12T08:40:14.201Z"},{"id":1518,"locale":"pt","published_at":"2024-09-12T08:40:14.201Z"},{"id":1626,"locale":"fr","published_at":"2024-09-12T08:40:14.201Z"},{"id":1599,"locale":"it","published_at":"2024-09-12T08:40:14.201Z"},{"id":1491,"locale":"es","published_at":"2024-09-12T08:40:14.201Z"},{"id":1014,"locale":"ja-JP","published_at":"2024-09-12T08:40:14.201Z"},{"id":1464,"locale":"de","published_at":"2024-09-12T08:40:14.201Z"},{"id":1572,"locale":"ko","published_at":"2024-09-12T08:40:14.201Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Milvus_on_GP_Us_with_NVIDIA_RAPIDS_cu_VS_58eab7154f.png","belong":"blog","authorNames":["Ruben Winastwan"]},{"id":"blog-536","title":"Introducing Migration Services: Efficiently Move Unstructured Data Across Platforms","image":{"id":4430,"url":"https://assets.zilliz.com/Sep_9_Introducing_Migration_Services_Efficiently_Move_Unstructured_Data_Across_Platforms_0166a8d393.png"},"display_time":"Sep 11, 2024","deploy_time":"0000-09-09T15:54:17.000Z","url":"zilliz-introduces-migration-services","abstract":"Zilliz has developed and open-sourced the Migration Services based on Apache Seatunnel to efficiently move vector data across platforms. ","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":34,"name":"James Luan","author_tags":"VP of Engineering at Zilliz","published_at":"2022-05-18T03:15:15.255Z","created_by":18,"updated_by":18,"created_at":"2022-05-18T03:14:35.112Z","updated_at":"2024-01-12T21:01:29.192Z","home_page":"GitHub","home_page_link":"https://github.com/xiaofan-luan","self_intro":"James Luan is the VP of Engineering at Zilliz. With a master's degree in computer engineering from Cornell University, he has extensive experience as a Database Engineer at Oracle, Hedvig, and Alibaba Cloud. James played a crucial role in developing HBase, Alibaba Cloud's open-source database, and Lindorm, a self-developed NoSQL database. He is also a respected member of the Technical Advisory Committee of LF AI \u0026 Data Foundation, contributing his expertise to shaping the future of AI and data technologies.\n","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":5,"localizations":[{"id":1248,"locale":"ja-JP","published_at":"2024-09-11T03:07:42.049Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Sep_9_Introducing_Migration_Services_Efficiently_Move_Unstructured_Data_Across_Platforms_0166a8d393.png","belong":"blog","authorNames":["James Luan"]},{"id":"blog-535","title":"New for Zilliz Cloud: Migration Service, Fivetran Connector, Multi-replica, and More","image":{"id":4418,"url":"https://assets.zilliz.com/new_for_zilliz_cloud_65ae4d76e3.jpeg"},"display_time":"Sep 10, 2024","deploy_time":"2024-09-10T09:30:00.000Z","url":"zilliz-sep-24-launch","abstract":"We're excited to announce new features in Zilliz Cloud designed to enhance support for running AI workloads in production environments. ","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":76,"name":"Steffi Li","author_tags":"Director of Product Marketing","published_at":"2023-07-13T17:18:42.023Z","created_by":18,"updated_by":18,"created_at":"2023-07-13T17:16:54.449Z","updated_at":"2023-07-13T17:18:42.070Z","home_page":null,"home_page_link":null,"self_intro":"Steffi is the Director of Product Marketing at Zilliz, with prior experience leading the GTM strategies for open-source data technologies such as Apache Kafka and Apache Airflow. Passionate about travel, yoga, and non-fiction reading, she brings a balanced and enriched worldview to her professional pursuits.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":5,"localizations":[{"id":1207,"locale":"ja-JP","published_at":"2024-09-10T03:30:25.467Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/new_for_zilliz_cloud_65ae4d76e3.jpeg","belong":"blog","authorNames":["Steffi Li"]},{"id":"blog-540","title":"The Critical Role of VectorDBs in Building Intelligent AI Agents","image":{"id":4724,"url":"https://assets.zilliz.com/The_Critical_Role_of_Vector_D_Bs_in_Building_Intelligent_Agents_120c416088.png"},"display_time":"Sep 09, 2024","deploy_time":null,"url":"critical-role-of-vectordbs-in-building-intelligent-ai-agents","abstract":"Unlocking AI agents' full potential and taking AI interactions to the next level with VectorDBs like Milvus. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":115,"name":"Stephen Batifol","author_tags":"Developer Advocate ","published_at":"2024-03-07T03:46:04.655Z","created_by":18,"updated_by":18,"created_at":"2024-03-07T03:46:02.457Z","updated_at":"2024-07-18T15:56:42.529Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/stephen-batifol/","self_intro":"Stephen Batifol is a Developer Advocate at Zilliz. He previously worked as a Machine Learning Engineer at Wolt, where he was working on the ML Platform and as a Data Scientist at Brevo. Stephen studied Computer Science and Artificial Intelligence. He enjoys dancing and surfing. \n","repost_to_medium":null,"repost_state":null,"meta_description":"Stephen Batifol is a Developer Advocate at Zilliz.","locale":"en"}],"read_time":5,"localizations":[{"id":1235,"locale":"ja-JP","published_at":"2024-09-11T14:33:13.902Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/The_Critical_Role_of_Vector_D_Bs_in_Building_Intelligent_Agents_120c416088.png","belong":"blog","authorNames":["Stephen Batifol"]},{"id":"blog-541","title":"How to Load Test an LLM API with Gatling","image":{"id":4429,"url":"https://assets.zilliz.com/How_to_Load_Test_an_LLM_API_with_Gatling_e738336bdc.png"},"display_time":"Sep 08, 2024","deploy_time":null,"url":"how-to-load-test-an-llm-api-with-gatling","abstract":"Load testing simulates real-world traffic to evaluate your API's performance under different conditions. Learn how to load-test LLM or RAG apps with Gatling. \n","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":179,"name":"Simon Mwaniki ","author_tags":null,"published_at":"2024-09-11T00:44:07.918Z","created_by":82,"updated_by":82,"created_at":"2024-09-11T00:44:06.462Z","updated_at":"2024-09-27T22:42:13.512Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":11,"localizations":[{"id":1241,"locale":"ja-JP","published_at":"2024-09-11T00:44:24.944Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/How_to_Load_Test_an_LLM_API_with_Gatling_e738336bdc.png","belong":"blog","authorNames":["Simon Mwaniki "]},{"id":"blog-548","title":"Improving Analytics with Time Series and Vector Databases","image":{"id":4753,"url":"https://assets.zilliz.com/Improving_Analytics_with_Time_Series_and_Vector_Databases_1_35cf97ef0f.png"},"display_time":"Sep 07, 2024","deploy_time":null,"url":"improving-analytics-with-time-series-and-vector-databases","abstract":"In this article, we'll explore time series databases in detail and walk you through a use case where we'll store time-series data in InfluxDB, query the data, transform it into vector embeddings, store the embeddings in Milvus, and finally perform a similarity search with Milvus. ","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":125,"name":"Ruben Winastwan","author_tags":"Freelance Technical Writer","published_at":"2024-03-26T09:16:27.310Z","created_by":18,"updated_by":18,"created_at":"2024-03-26T09:16:24.498Z","updated_at":"2024-07-03T07:56:29.256Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Ruben Winastwan, Freelance Technical Writer","locale":"en"}],"read_time":12,"localizations":[{"id":1253,"locale":"ja-JP","published_at":"2024-09-17T20:23:44.810Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Improving_Analytics_with_Time_Series_and_Vector_Databases_1_35cf97ef0f.png","belong":"blog","authorNames":["Ruben Winastwan"]},{"id":"blog-547","title":"Evaluating Multimodal RAG Systems Using Trulens ","image":{"id":4516,"url":"https://assets.zilliz.com/June_24_Evaluating_Multimodal_RA_Gs_in_practice_642dadcd3d.png"},"display_time":"Sep 06, 2024","deploy_time":null,"url":"evaluating-multimodal-rags-in-practice-trulens","abstract":"Understand multimodal models and multimodal RAG as well as learn how to evaluate multimodal RAG systems using Trulens \n","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":45,"name":"Fendy Feng","author_tags":"Technical Marketing Writer","published_at":"2023-05-16T01:36:15.102Z","created_by":18,"updated_by":18,"created_at":"2023-05-16T00:04:12.065Z","updated_at":"2024-04-25T08:37:19.712Z","home_page":"GitHub","home_page_link":"https://www.linkedin.com/in/fendy311/","self_intro":"Fendy Feng is the Technical Marketing Writer at Zilliz. She has extensive experience developing and enhancing the impact of open-source projects in various global markets by producing high-quality, tailored content. Before joining Zilliz, Fendy worked as a Content Strategist at PingCAP, a fast-growing E-Series startup renowned for its open-source distributed SQL database.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":8,"localizations":[{"id":1095,"locale":"ja-JP","published_at":"2024-09-17T18:11:00.979Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/June_24_Evaluating_Multimodal_RA_Gs_in_practice_642dadcd3d.png","belong":"blog","authorNames":["Fendy Feng"]},{"id":"blog-546","title":"Harnessing Embedding Models for AI-Powered Search","image":{"id":5025,"url":"https://assets.zilliz.com/Harnessing_Embedding_Models_for_AI_Powered_Search_3_19abac89ce.png"},"display_time":"Sep 05, 2024","deploy_time":null,"url":"harnessing-embedding-models-for-ai-powered-search","abstract":"Building state-of-the-art embedding models for high-quality RAG systems needs careful attention to pretraining, fine-tuning, and scalability. Zilliz Cloud and Milvus help manage embeddings at scale and create more intelligent and responsive neural search systems.\n\n","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":118,"name":" Haziqa Sajid","author_tags":"Freelance Technical Writer","published_at":"2024-03-12T10:25:34.265Z","created_by":18,"updated_by":18,"created_at":"2024-03-12T10:25:31.148Z","updated_at":"2024-07-03T07:58:27.010Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/haziqa-sajid-22b53245/","self_intro":"Digital Storytelling for Data, AI, B2B \u0026 SaaS","repost_to_medium":null,"repost_state":null,"meta_description":" Haziqa Sajid, Freelance Technical Writer","locale":"en"}],"read_time":10,"localizations":[{"id":1087,"locale":"ja-JP","published_at":"2024-09-17T17:56:14.266Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Harnessing_Embedding_Models_for_AI_Powered_Search_3_19abac89ce.png","belong":"blog","authorNames":[" Haziqa Sajid"]},{"id":"blog-539","title":"Implementing Agentic RAG Using Claude 3.5 Sonnet, LlamaIndex, and Milvus","image":{"id":4723,"url":"https://assets.zilliz.com/Implementing_Agentic_RAG_Using_Claude_3_5_Sonnet_Llama_Index_and_Milvus_f4368ef436.png"},"display_time":"Sep 04, 2024","deploy_time":null,"url":"agentic-rag-using-claude-3.5-sonnet-llamaindex-and-milvus","abstract":"Learn Agentic RAG, its challenges and benefits, and a guide to building an Agentic RAG with Claude 3.4 Sonnet, LlamaIndex, and Milvus. \n","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":178,"name":"Benito Martin","author_tags":null,"published_at":"2024-09-10T18:31:20.152Z","created_by":82,"updated_by":82,"created_at":"2024-09-10T18:30:36.499Z","updated_at":"2024-10-02T17:35:02.538Z","home_page":null,"home_page_link":null,"self_intro":"Freelance Technical Writer","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":11,"localizations":[{"id":1229,"locale":"ja-JP","published_at":"2024-09-11T14:24:44.176Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Implementing_Agentic_RAG_Using_Claude_3_5_Sonnet_Llama_Index_and_Milvus_f4368ef436.png","belong":"blog","authorNames":["Benito Martin"]},{"id":"learn-255","title":"Top 10 Best Multimodal AI Models You Should Know","image":{"id":4426,"url":"https://assets.zilliz.com/Building_a_Multimodal_Product_Recommender_Demo_Using_Milvus_and_Streamlit_1_eb0b36bea0.png"},"display_time":"Sep 03, 2024","url":"top-10-best-multimodal-ai-models-you-should-know","abstract":"Multimodal models are AI systems that simultaneously process and integrate multiple data types. ","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":150,"name":"Tim Mugabi","author_tags":"Freelance Technical Writer","published_at":"2024-04-24T21:23:34.511Z","created_by":18,"updated_by":18,"created_at":"2024-04-24T21:23:32.810Z","updated_at":"2024-07-03T07:49:21.138Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Tim Mugabi, Freelance Technical Writer","locale":"en"}],"read_time":16,"localizations":[{"id":301,"locale":"ja-JP","published_at":"2024-09-10T10:18:44.448Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Building_a_Multimodal_Product_Recommender_Demo_Using_Milvus_and_Streamlit_1_eb0b36bea0.png","belong":"learn","authorNames":["Tim Mugabi"]},{"id":"learn-252","title":"What is BERT (Bidirectional Encoder Representations from Transformers)?","image":{"id":4326,"url":"https://assets.zilliz.com/What_is_BERT_Bidirectional_Encoder_Representations_from_Transformers_b5f811ed2f.png"},"display_time":"Aug 30, 2024","url":"what-is-bert","abstract":"BERT, or Bidirectional Encoder Representations from Transformers, has dramatically reshaped the landscape of natural language processing (NLP) since its debut by Google in 2018.","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":143,"name":"Daniella Pontes","author_tags":"Freelance Technical Writer","published_at":"2024-04-19T03:52:05.346Z","created_by":18,"updated_by":18,"created_at":"2024-04-19T03:52:03.759Z","updated_at":"2024-07-03T07:58:01.528Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Daniella Pontes, Freelance Technical Writer","locale":"en"}],"read_time":12,"localizations":[{"id":482,"locale":"ja-JP","published_at":"2024-08-30T17:21:13.345Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/What_is_BERT_Bidirectional_Encoder_Representations_from_Transformers_b5f811ed2f.png","belong":"learn","authorNames":["Daniella Pontes"]},{"id":"learn-254","title":"What is Computer Vision? ","image":{"id":4337,"url":"https://assets.zilliz.com/What_is_Computer_Vision_ccfca00fad.png"},"display_time":"Aug 28, 2024","url":"what-is-computer-vision","abstract":"Computer Vision is a field of Artificial Intelligence that enables machines to capture and interpret visual information from the world just like humans do. ","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":170,"name":"Yesha Shastri","author_tags":"Freelance Technical Writer in AI/ML","published_at":"2024-07-29T08:44:59.761Z","created_by":18,"updated_by":18,"created_at":"2024-07-29T08:44:38.291Z","updated_at":"2024-07-29T08:44:59.820Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/yeshashastri/","self_intro":"Yesha Shastri, Freelance Technical Writer in AI/ML","repost_to_medium":null,"repost_state":null,"meta_description":"Yesha Shastri, Freelance Technical Writer","locale":"en"}],"read_time":10,"localizations":[{"id":348,"locale":"ja-JP","published_at":"2024-08-31T12:28:48.393Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/What_is_Computer_Vision_ccfca00fad.png","belong":"learn","authorNames":["Yesha Shastri"]},{"id":"learn-253","title":"What is a Knowledge Graph (KG)? ","image":{"id":4327,"url":"https://assets.zilliz.com/What_is_a_Knowledge_Graph_bb58e9bf7a.png"},"display_time":"Aug 27, 2024","url":"what-is-knowledge-graph","abstract":"A knowledge graph is a data structure representing information as a network of entities and their relationships.","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":118,"name":" Haziqa Sajid","author_tags":"Freelance Technical Writer","published_at":"2024-03-12T10:25:34.265Z","created_by":18,"updated_by":18,"created_at":"2024-03-12T10:25:31.148Z","updated_at":"2024-07-03T07:58:27.010Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/haziqa-sajid-22b53245/","self_intro":"Digital Storytelling for Data, AI, B2B \u0026 SaaS","repost_to_medium":null,"repost_state":null,"meta_description":" Haziqa Sajid, Freelance Technical Writer","locale":"en"}],"read_time":18,"localizations":[{"id":356,"locale":"ja-JP","published_at":"2024-08-31T12:16:32.496Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/What_is_a_Knowledge_Graph_bb58e9bf7a.png","belong":"learn","authorNames":[" Haziqa Sajid"]},{"id":"blog-507","title":"Scaling Search with Milvus: Handling Massive Datasets with Ease","image":{"id":4314,"url":"https://assets.zilliz.com/Scaling_Search_with_Milvus_Handling_Massive_Datasets_with_Ease_2_f16d30b715.png"},"display_time":"Aug 26, 2024","deploy_time":null,"url":"scale-search-with-milvus-handle-massive-datasets-with-ease","abstract":"A tutorial on how to scale your search engine with massive amounts of data using the Milvus vector database. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":115,"name":"Stephen Batifol","author_tags":"Developer Advocate ","published_at":"2024-03-07T03:46:04.655Z","created_by":18,"updated_by":18,"created_at":"2024-03-07T03:46:02.457Z","updated_at":"2024-07-18T15:56:42.529Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/stephen-batifol/","self_intro":"Stephen Batifol is a Developer Advocate at Zilliz. He previously worked as a Machine Learning Engineer at Wolt, where he was working on the ML Platform and as a Data Scientist at Brevo. Stephen studied Computer Science and Artificial Intelligence. He enjoys dancing and surfing. \n","repost_to_medium":null,"repost_state":null,"meta_description":"Stephen Batifol is a Developer Advocate at Zilliz.","locale":"en"}],"read_time":13,"localizations":[{"id":1204,"locale":"ja-JP","published_at":"2024-08-30T12:26:50.884Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Scaling_Search_with_Milvus_Handling_Massive_Datasets_with_Ease_2_f16d30b715.png","belong":"blog","authorNames":["Stephen Batifol"]},{"id":"blog-508","title":"Relational Databases vs Vector Databases","image":{"id":6518,"url":"https://assets.zilliz.com/Aug_25_Relational_vs_Vector_f1ecf04cb0.png"},"display_time":"Aug 25, 2024","deploy_time":"2024-08-25T07:00:00.000Z","url":"relational-databases-vs-vector-databases","abstract":"Choosing the right database is crucial. Relational databases manage structured data well, while vector databases excel in unstructured data and AI tasks. However, before adding a vector database it's important to evaluate whether the benefits outweigh the costs. ","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":36,"name":"Chris Churilo","author_tags":"VP of Marketing","published_at":"2023-04-11T16:51:05.002Z","created_by":18,"updated_by":53,"created_at":"2023-04-11T16:42:46.067Z","updated_at":"2025-01-16T22:35:53.011Z","home_page":"GitHub","home_page_link":"https://github.com/ChrisChurilo","self_intro":"Chris Churilo is the VP of Marketing \u0026 Community at Zilliz where she leads all community, developer relations, and marketing efforts. Prior to Zilliz, Chris was a founding member of the InfluxData’s go to market efforts and helped propel the time series database platform to dominance in the market. In earlier roles she defined and designed a SaaS monitoring solution at Centroid, and prior to that she was the VP of product management at iPass and was the LOB for several cloud services that required her to track the business and operational metrics and analytics to help identify and resolve issues.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":9,"localizations":[{"id":1015,"locale":"ja-JP","published_at":"2024-08-31T23:44:19.978Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Aug_25_Relational_vs_Vector_f1ecf04cb0.png","belong":"blog","authorNames":["Chris Churilo"]},{"id":"learn-251","title":"Top 10 NLP Techniques Every Data Scientist Should Know","image":{"id":4283,"url":"https://assets.zilliz.com/Top_10_NLP_Techniques_Every_Data_Scientist_Should_Know_3bf2001302.png"},"display_time":"Aug 22, 2024","url":"top-10-nlp-techniques-every-data-scientist-should-know","abstract":"In this article, we will explore the top 10 techniques widely used in NLP with clear explanations, applications, and code snippets.\n","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":151,"name":"Fariba Laiq","author_tags":"Freelance Technical Writer","published_at":"2024-04-24T21:23:59.165Z","created_by":18,"updated_by":18,"created_at":"2024-04-24T21:23:57.717Z","updated_at":"2024-07-29T16:21:27.954Z","home_page":null,"home_page_link":null,"self_intro":"Description: Fariba Laiq is a freelance content writer at Zilliz. She has studied Computer Science, been a coding instructor, and published research papers in the domain of AI and cyber-security. She is passionate about learning more about LLMs and vector databases in the ever evolving era of AI. Along with technical skills, she is also a self-taught artist.","repost_to_medium":null,"repost_state":null,"meta_description":"Fariba Laiq, Freelance Technical Writer","locale":"en"}],"read_time":28,"localizations":[{"id":404,"locale":"ja-JP","published_at":"2024-08-24T00:55:10.699Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Top_10_NLP_Techniques_Every_Data_Scientist_Should_Know_3bf2001302.png","belong":"learn","authorNames":["Fariba Laiq"]},{"id":"blog-506","title":"Navigating the Challenges of ML Management: Tools and Insights for Success","image":{"id":4466,"url":"https://assets.zilliz.com/Navigating_the_Challenges_of_ML_Management_Tools_and_Insights_for_Success_ab296c1308.png"},"display_time":"Aug 21, 2024","deploy_time":null,"url":"navigating-challenges-of-ml-management-tools-and-insights","abstract":"Learn how XetHub and vector databases like Milvus address ML model management challenges. \n","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":45,"name":"Fendy Feng","author_tags":"Technical Marketing Writer","published_at":"2023-05-16T01:36:15.102Z","created_by":18,"updated_by":18,"created_at":"2023-05-16T00:04:12.065Z","updated_at":"2024-04-25T08:37:19.712Z","home_page":"GitHub","home_page_link":"https://www.linkedin.com/in/fendy311/","self_intro":"Fendy Feng is the Technical Marketing Writer at Zilliz. She has extensive experience developing and enhancing the impact of open-source projects in various global markets by producing high-quality, tailored content. Before joining Zilliz, Fendy worked as a Content Strategist at PingCAP, a fast-growing E-Series startup renowned for its open-source distributed SQL database.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":6,"localizations":[{"id":1161,"locale":"ja-JP","published_at":"2024-08-24T00:38:32.869Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Navigating_the_Challenges_of_ML_Management_Tools_and_Insights_for_Success_ab296c1308.png","belong":"blog","authorNames":["Fendy Feng"]},{"id":"learn-250","title":"The Evolution of Search: From Traditional Keyword Matching to Vector Search and Generative AI","image":{"id":4280,"url":"https://assets.zilliz.com/The_Evolution_of_Search_From_Traditional_Keyword_Matching_to_Vector_Search_and_Generative_AI_211982e6b3.png"},"display_time":"Aug 20, 2024","url":"evolution-of-search-from-traditional-keyword-matching-to-vector-search-and-genai","abstract":"Explores the evolution of search, the limitations of keyword-matching systems, and how vector search and GenAI are setting new standards for modern search. ","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":170,"name":"Yesha Shastri","author_tags":"Freelance Technical Writer in AI/ML","published_at":"2024-07-29T08:44:59.761Z","created_by":18,"updated_by":18,"created_at":"2024-07-29T08:44:38.291Z","updated_at":"2024-07-29T08:44:59.820Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/yeshashastri/","self_intro":"Yesha Shastri, Freelance Technical Writer in AI/ML","repost_to_medium":null,"repost_state":null,"meta_description":"Yesha Shastri, Freelance Technical Writer","locale":"en"}],"read_time":13,"localizations":[{"id":395,"locale":"ja-JP","published_at":"2024-08-23T16:19:26.628Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/The_Evolution_of_Search_From_Traditional_Keyword_Matching_to_Vector_Search_and_Generative_AI_211982e6b3.png","belong":"learn","authorNames":["Yesha Shastri"]},{"id":"blog-505","title":"How Metadata Lakes Empower Next-Gen AI/ML Applications","image":{"id":4310,"url":"https://assets.zilliz.com/ML_Applications_030e10ad6a.png"},"display_time":"Aug 19, 2024","deploy_time":null,"url":"how-metadata-lakes-empower-next-gen-ai-ml-apps","abstract":"Metadata lakes are centralized repositories that store metadata from various sources, connecting data silos and addressing various challenges in RAG. ","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":147,"name":"ShriVarsheni R","author_tags":"Freelance Technical Writer","published_at":"2024-04-24T21:21:57.571Z","created_by":18,"updated_by":18,"created_at":"2024-04-24T21:21:55.818Z","updated_at":"2024-07-03T07:50:17.617Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"ShriVarsheni, Freelance Technical Writer","locale":"en"},{"id":45,"name":"Fendy Feng","author_tags":"Technical Marketing Writer","published_at":"2023-05-16T01:36:15.102Z","created_by":18,"updated_by":18,"created_at":"2023-05-16T00:04:12.065Z","updated_at":"2024-04-25T08:37:19.712Z","home_page":"GitHub","home_page_link":"https://www.linkedin.com/in/fendy311/","self_intro":"Fendy Feng is the Technical Marketing Writer at Zilliz. She has extensive experience developing and enhancing the impact of open-source projects in various global markets by producing high-quality, tailored content. Before joining Zilliz, Fendy worked as a Content Strategist at PingCAP, a fast-growing E-Series startup renowned for its open-source distributed SQL database.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":7,"localizations":[{"id":1145,"locale":"ja-JP","published_at":"2024-08-23T16:04:35.994Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/ML_Applications_030e10ad6a.png","belong":"blog","authorNames":["ShriVarsheni R","Fendy Feng"]},{"id":"blog-501","title":"RoBERTa: An Optimized Method for Pretraining Self-supervised NLP Systems","image":{"id":4309,"url":"https://assets.zilliz.com/Aug_28_Ro_BER_Ta_An_Optimized_Method_for_Pretraining_Self_supervised_NLP_Systems_11de35c5df.png"},"display_time":"Aug 18, 2024","deploy_time":null,"url":"roberta-optimized-method-for-pretraining-self-supervised-nlp-systems","abstract":"RoBERTa (A Robustly Optimized BERT Pretraining Approach) is an improved version of BERT designed to address its limitations. \n","tags":[{"id":73,"name":"Paper Reading","published_at":"2024-08-10T14:40:10.906Z","created_by":60,"updated_by":60,"created_at":"2024-08-10T14:40:09.192Z","updated_at":"2024-08-10T14:40:10.914Z","locale":"en"}],"authors":[{"id":118,"name":" Haziqa Sajid","author_tags":"Freelance Technical Writer","published_at":"2024-03-12T10:25:34.265Z","created_by":18,"updated_by":18,"created_at":"2024-03-12T10:25:31.148Z","updated_at":"2024-07-03T07:58:27.010Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/haziqa-sajid-22b53245/","self_intro":"Digital Storytelling for Data, AI, B2B \u0026 SaaS","repost_to_medium":null,"repost_state":null,"meta_description":" Haziqa Sajid, Freelance Technical Writer","locale":"en"}],"read_time":16,"localizations":[{"id":977,"locale":"ja-JP","published_at":"2024-08-23T00:39:35.619Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Aug_28_Ro_BER_Ta_An_Optimized_Method_for_Pretraining_Self_supervised_NLP_Systems_11de35c5df.png","belong":"blog","authorNames":[" Haziqa Sajid"]},{"id":"learn-249","title":"Will A GenAI Like ChatGPT Replace Google Search? ","image":{"id":4254,"url":"https://assets.zilliz.com/Will_A_Gen_AI_Like_Chat_GPT_Replace_Google_Search_771b7bc7f5.png"},"display_time":"Aug 17, 2024","url":"will-a-gen-ai-like-chatgpt-replace-google-search","abstract":"In this article, we will explore how GenAI and traditional search engines work, compare their strengths and weaknesses, and discuss the potential for integrating both technologies.\n","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":151,"name":"Fariba Laiq","author_tags":"Freelance Technical Writer","published_at":"2024-04-24T21:23:59.165Z","created_by":18,"updated_by":18,"created_at":"2024-04-24T21:23:57.717Z","updated_at":"2024-07-29T16:21:27.954Z","home_page":null,"home_page_link":null,"self_intro":"Description: Fariba Laiq is a freelance content writer at Zilliz. She has studied Computer Science, been a coding instructor, and published research papers in the domain of AI and cyber-security. She is passionate about learning more about LLMs and vector databases in the ever evolving era of AI. Along with technical skills, she is also a self-taught artist.","repost_to_medium":null,"repost_state":null,"meta_description":"Fariba Laiq, Freelance Technical Writer","locale":"en"}],"read_time":11,"localizations":[{"id":365,"locale":"ja-JP","published_at":"2024-08-22T18:39:18.820Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Will_A_Gen_AI_Like_Chat_GPT_Replace_Google_Search_771b7bc7f5.png","belong":"learn","authorNames":["Fariba Laiq"]},{"id":"learn-248","title":"Understanding Boolean Retrieval Models in Information Retrieval ","image":{"id":4311,"url":"https://assets.zilliz.com/Aug_24_Understanding_Boolean_Retrieval_Models_in_Information_Retrieval_8ffba6fa2e.png"},"display_time":"Aug 16, 2024","url":"understanding-boolean-retrieval-models-in-information-retrieval","abstract":"In this article, we'll discuss a specific information retrieval method known as Boolean Retrieval Models. ","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":125,"name":"Ruben Winastwan","author_tags":"Freelance Technical Writer","published_at":"2024-03-26T09:16:27.310Z","created_by":18,"updated_by":18,"created_at":"2024-03-26T09:16:24.498Z","updated_at":"2024-07-03T07:56:29.256Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Ruben Winastwan, Freelance Technical Writer","locale":"en"}],"read_time":12,"localizations":[{"id":474,"locale":"ja-JP","published_at":"2024-08-21T16:44:56.020Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Aug_24_Understanding_Boolean_Retrieval_Models_in_Information_Retrieval_8ffba6fa2e.png","belong":"learn","authorNames":["Ruben Winastwan"]},{"id":"blog-500","title":"Streamlining the Deployment of Enterprise GenAI Apps with Efficient Management of Unstructured Data ","image":{"id":4198,"url":"https://assets.zilliz.com/Streamlining_the_Deployment_of_Enterprise_Gen_AI_Apps_with_Efficient_Management_of_Unstructured_Data_8e246829a0.png"},"display_time":"Aug 15, 2024","deploy_time":null,"url":"streamlining-deployment-of-enterprise-gen-ai-apps","abstract":"Learn how to leverage the unstructured data platform provided by Aparavi and the Milvus vector database to build and deploy more scalable GenAI apps in production. \n","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":45,"name":"Fendy Feng","author_tags":"Technical Marketing Writer","published_at":"2023-05-16T01:36:15.102Z","created_by":18,"updated_by":18,"created_at":"2023-05-16T00:04:12.065Z","updated_at":"2024-04-25T08:37:19.712Z","home_page":"GitHub","home_page_link":"https://www.linkedin.com/in/fendy311/","self_intro":"Fendy Feng is the Technical Marketing Writer at Zilliz. She has extensive experience developing and enhancing the impact of open-source projects in various global markets by producing high-quality, tailored content. Before joining Zilliz, Fendy worked as a Content Strategist at PingCAP, a fast-growing E-Series startup renowned for its open-source distributed SQL database.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"},{"id":147,"name":"ShriVarsheni R","author_tags":"Freelance Technical Writer","published_at":"2024-04-24T21:21:57.571Z","created_by":18,"updated_by":18,"created_at":"2024-04-24T21:21:55.818Z","updated_at":"2024-07-03T07:50:17.617Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"ShriVarsheni, Freelance Technical Writer","locale":"en"}],"read_time":5,"localizations":[{"id":1096,"locale":"ja-JP","published_at":"2024-08-16T18:12:22.076Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Streamlining_the_Deployment_of_Enterprise_Gen_AI_Apps_with_Efficient_Management_of_Unstructured_Data_8e246829a0.png","belong":"blog","authorNames":["Fendy Feng","ShriVarsheni R"]},{"id":"learn-245","title":"20 Popular Open Datasets for Natural Language Processing","image":{"id":4186,"url":"https://assets.zilliz.com/20_Popular_Open_Datasets_for_Natural_Language_Processing_195801e625.png"},"display_time":"Aug 14, 2024","url":"popular-datasets-for-natural-language-processing","abstract":"Learn the key criteria for selecting the ideal dataset for your NLP projects and explore 20 popular open datasets. \n","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":150,"name":"Tim Mugabi","author_tags":"Freelance Technical Writer","published_at":"2024-04-24T21:23:34.511Z","created_by":18,"updated_by":18,"created_at":"2024-04-24T21:23:32.810Z","updated_at":"2024-07-03T07:49:21.138Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Tim Mugabi, Freelance Technical Writer","locale":"en"}],"read_time":10,"localizations":[{"id":397,"locale":"ja-JP","published_at":"2024-08-14T17:41:51.642Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/20_Popular_Open_Datasets_for_Natural_Language_Processing_195801e625.png","belong":"learn","authorNames":["Tim Mugabi"]},{"id":"learn-246","title":"Constitutional AI: Harmlessness from AI Feedback","image":{"id":4241,"url":"https://assets.zilliz.com/Aug_16_Constitutional_AI_Harmlessness_from_AI_Feedback_bea48cc040.png"},"display_time":"Aug 14, 2024","url":"constitutional-ai-harmlessness-from-ai-feedback","abstract":"In this article, we will discuss a method, Constitutional AI (CAI), presented by the Anthropic team in their paper “Constitutional AI: Harmlessness from AI Feedback\".\n","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":125,"name":"Ruben Winastwan","author_tags":"Freelance Technical Writer","published_at":"2024-03-26T09:16:27.310Z","created_by":18,"updated_by":18,"created_at":"2024-03-26T09:16:24.498Z","updated_at":"2024-07-03T07:56:29.256Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Ruben Winastwan, Freelance Technical Writer","locale":"en"}],"read_time":13,"localizations":[{"id":481,"locale":"ja-JP","published_at":"2024-08-14T18:02:17.777Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Aug_16_Constitutional_AI_Harmlessness_from_AI_Feedback_bea48cc040.png","belong":"learn","authorNames":["Ruben Winastwan"]},{"id":"learn-243","title":"What Are Rerankers and How Do They Enhance Information Retrieval?","image":{"id":4178,"url":"https://assets.zilliz.com/What_Are_Rerankers_and_How_Do_They_Enhance_Information_Retrieval_814d867091.png"},"display_time":"Aug 13, 2024","url":"what-are-rerankers-enhance-information-retrieval","abstract":"This article will explore the concepts behind rerankers and demonstrate how to integrate rerankers with Milvus, a widely adopted open-source vector database, to enhance search and Retrieval Augmented Generation (RAG) applications.\n","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":158,"name":"Denis Kuria","author_tags":"Freelance Technical Writer","published_at":"2024-05-01T00:39:32.350Z","created_by":18,"updated_by":18,"created_at":"2024-05-01T00:39:30.888Z","updated_at":"2024-07-03T06:50:56.660Z","home_page":null,"home_page_link":null,"self_intro":"Denis is a machine learning engineer who enjoys writing guides to help other developers. He has a bachelor's in computer science and loves hiking and exploring the world.\n","repost_to_medium":null,"repost_state":null,"meta_description":"Denis Kuria is a freelance technical writer at Zilliz. ","locale":"en"}],"read_time":19,"localizations":[{"id":354,"locale":"ja-JP","published_at":"2024-08-14T17:04:01.567Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/What_Are_Rerankers_and_How_Do_They_Enhance_Information_Retrieval_814d867091.png","belong":"learn","authorNames":["Denis Kuria"]},{"id":"blog-499","title":"Boosting Work Efficiency with Generative AI Use Cases","image":{"id":4176,"url":"https://assets.zilliz.com/Boosting_Work_Efficiency_with_Generative_AI_Use_Cases_2e7f7d44aa.png"},"display_time":"Aug 12, 2024","deploy_time":null,"url":"boosting-work-efficiency-with-gen-ai-use-cases","abstract":"This blog will explore how Generative AI (GenAI) applications can boost work efficiency.","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":45,"name":"Fendy Feng","author_tags":"Technical Marketing Writer","published_at":"2023-05-16T01:36:15.102Z","created_by":18,"updated_by":18,"created_at":"2023-05-16T00:04:12.065Z","updated_at":"2024-04-25T08:37:19.712Z","home_page":"GitHub","home_page_link":"https://www.linkedin.com/in/fendy311/","self_intro":"Fendy Feng is the Technical Marketing Writer at Zilliz. She has extensive experience developing and enhancing the impact of open-source projects in various global markets by producing high-quality, tailored content. Before joining Zilliz, Fendy worked as a Content Strategist at PingCAP, a fast-growing E-Series startup renowned for its open-source distributed SQL database.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"},{"id":151,"name":"Fariba Laiq","author_tags":"Freelance Technical Writer","published_at":"2024-04-24T21:23:59.165Z","created_by":18,"updated_by":18,"created_at":"2024-04-24T21:23:57.717Z","updated_at":"2024-07-29T16:21:27.954Z","home_page":null,"home_page_link":null,"self_intro":"Description: Fariba Laiq is a freelance content writer at Zilliz. She has studied Computer Science, been a coding instructor, and published research papers in the domain of AI and cyber-security. She is passionate about learning more about LLMs and vector databases in the ever evolving era of AI. Along with technical skills, she is also a self-taught artist.","repost_to_medium":null,"repost_state":null,"meta_description":"Fariba Laiq, Freelance Technical Writer","locale":"en"}],"read_time":5,"localizations":[{"id":973,"locale":"ja-JP","published_at":"2024-08-14T16:41:47.706Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Boosting_Work_Efficiency_with_Generative_AI_Use_Cases_2e7f7d44aa.png","belong":"blog","authorNames":["Fendy Feng","Fariba Laiq"]},{"id":"learn-244","title":"Top 10 Natural Language Processing Tools and Platforms","image":{"id":4184,"url":"https://assets.zilliz.com/Top_10_Natural_Language_Processing_Tools_and_Platforms_d184754d77.png"},"display_time":"Aug 12, 2024","url":"top-10-natural-language-processing-tools-and-platforms","abstract":"An overview of the top ten NLP tools and platforms, highlighting their key features, applications, and advantages to help you select the best options for your needs.\n","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":151,"name":"Fariba Laiq","author_tags":"Freelance Technical Writer","published_at":"2024-04-24T21:23:59.165Z","created_by":18,"updated_by":18,"created_at":"2024-04-24T21:23:57.717Z","updated_at":"2024-07-29T16:21:27.954Z","home_page":null,"home_page_link":null,"self_intro":"Description: Fariba Laiq is a freelance content writer at Zilliz. She has studied Computer Science, been a coding instructor, and published research papers in the domain of AI and cyber-security. She is passionate about learning more about LLMs and vector databases in the ever evolving era of AI. Along with technical skills, she is also a self-taught artist.","repost_to_medium":null,"repost_state":null,"meta_description":"Fariba Laiq, Freelance Technical Writer","locale":"en"}],"read_time":16,"localizations":[{"id":381,"locale":"ja-JP","published_at":"2024-08-14T17:23:24.440Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Top_10_Natural_Language_Processing_Tools_and_Platforms_d184754d77.png","belong":"learn","authorNames":["Fariba Laiq"]},{"id":"learn-247","title":"A Beginner’s Guide to Using OpenAI Text Embedding Models ","image":{"id":4195,"url":"https://assets.zilliz.com/June_04_A_Guide_to_Using_Open_AI_Text_Embeddings_150a299fc3.png"},"display_time":"Aug 11, 2024","url":"guide-to-using-openai-text-embedding-models","abstract":"A comprehensive guide to using OpenAI text embedding models for embedding creation and semantic search. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":45,"name":"Fendy Feng","author_tags":"Technical Marketing Writer","published_at":"2023-05-16T01:36:15.102Z","created_by":18,"updated_by":18,"created_at":"2023-05-16T00:04:12.065Z","updated_at":"2024-04-25T08:37:19.712Z","home_page":"GitHub","home_page_link":"https://www.linkedin.com/in/fendy311/","self_intro":"Fendy Feng is the Technical Marketing Writer at Zilliz. She has extensive experience developing and enhancing the impact of open-source projects in various global markets by producing high-quality, tailored content. Before joining Zilliz, Fendy worked as a Content Strategist at PingCAP, a fast-growing E-Series startup renowned for its open-source distributed SQL database.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":7,"localizations":[{"id":449,"locale":"ja-JP","published_at":"2024-08-14T18:37:52.671Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/June_04_A_Guide_to_Using_Open_AI_Text_Embeddings_150a299fc3.png","belong":"learn","authorNames":["Fendy Feng"]},{"id":"learn-242","title":"Search Still Matters: Enhancing Information Retrieval with Generative AI and Vector Databases","image":{"id":4164,"url":"https://assets.zilliz.com/Search_Still_Matters_Enhancing_Information_Retrieval_with_Generative_AI_and_Vector_Databases_317853f509.png"},"display_time":"Aug 11, 2024","url":"search-still-matters-enhance-information-retrieval-with-genai-and-vector-databases","abstract":"Despite advances in LLMs like ChatGPT, search still matters. Combining GenAI with search and vector databases enhances search accuracy and experience.","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":118,"name":" Haziqa Sajid","author_tags":"Freelance Technical Writer","published_at":"2024-03-12T10:25:34.265Z","created_by":18,"updated_by":18,"created_at":"2024-03-12T10:25:31.148Z","updated_at":"2024-07-03T07:58:27.010Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/haziqa-sajid-22b53245/","self_intro":"Digital Storytelling for Data, AI, B2B \u0026 SaaS","repost_to_medium":null,"repost_state":null,"meta_description":" Haziqa Sajid, Freelance Technical Writer","locale":"en"}],"read_time":11,"localizations":[{"id":472,"locale":"ja-JP","published_at":"2024-08-10T14:27:41.399Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Search_Still_Matters_Enhancing_Information_Retrieval_with_Generative_AI_and_Vector_Databases_317853f509.png","belong":"learn","authorNames":[" Haziqa Sajid"]},{"id":"learn-241","title":"What is Information Retrieval?","image":{"id":4163,"url":"https://assets.zilliz.com/What_is_Information_Retrieval_f4cc552f9b.png"},"display_time":"Aug 10, 2024","url":"what-is-information-retrieval","abstract":"Information retrieval (IR) is the process of efficiently retrieving relevant information from large collections of unstructured or semi-structured data. ","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":118,"name":" Haziqa Sajid","author_tags":"Freelance Technical Writer","published_at":"2024-03-12T10:25:34.265Z","created_by":18,"updated_by":18,"created_at":"2024-03-12T10:25:31.148Z","updated_at":"2024-07-03T07:58:27.010Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/haziqa-sajid-22b53245/","self_intro":"Digital Storytelling for Data, AI, B2B \u0026 SaaS","repost_to_medium":null,"repost_state":null,"meta_description":" Haziqa Sajid, Freelance Technical Writer","locale":"en"}],"read_time":11,"localizations":[{"id":469,"locale":"ja-JP","published_at":"2024-08-10T13:03:04.107Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/What_is_Information_Retrieval_f4cc552f9b.png","belong":"learn","authorNames":[" Haziqa Sajid"]},{"id":"blog-497","title":"How to Choose the Right Milvus Deployment Mode for Your AI Applications ","image":{"id":4136,"url":"https://assets.zilliz.com/How_to_Choose_the_Right_Milvus_Deployment_Mode_for_Your_AI_Applications_9a98377cae.png"},"display_time":"Aug 09, 2024","deploy_time":null,"url":"choose-the-right-milvus-deployment-mode-ai-applications","abstract":"Comparing Milvus Lite, Standalone, and Distributed—deployment modes for different stages, data sizes, and use cases, ensuring seamless project scalability. \n","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":68,"name":"Robert Guo","author_tags":"Director of Product Management","published_at":"2023-06-13T18:34:37.794Z","created_by":18,"updated_by":18,"created_at":"2023-06-08T17:01:36.444Z","updated_at":"2024-04-16T02:44:46.685Z","home_page":"GitHub","home_page_link":"https://github.com/GuoRentong","self_intro":"Robert Guo is a Partner and Director of Product Management at Zilliz and one of the architects behind Milvus, an open-source vector database revolutionizing AI data analysis. With a Ph.D. in Computer Software and Theory from Huazhong University of Science and Technology, he has presented influential work at prestigious conferences and journals, including SIGMOD, VLDB, USENIX ATC, ICS, DATE, and IEEE TPDS. Previously a key developer for Huawei's ModelArts platform, Robert is skilled at crafting efficient and scalable AI data solutions.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":9,"localizations":[{"id":1601,"locale":"it","published_at":"2024-08-09T18:40:15.411Z"},{"id":1036,"locale":"ja-JP","published_at":"2024-08-09T18:40:15.411Z"},{"id":1574,"locale":"ko","published_at":"2024-08-09T18:40:15.411Z"},{"id":1628,"locale":"fr","published_at":"2024-08-09T18:40:15.411Z"},{"id":1520,"locale":"pt","published_at":"2024-08-09T18:40:15.411Z"},{"id":1466,"locale":"de","published_at":"2024-08-09T18:40:15.411Z"},{"id":1547,"locale":"ru","published_at":"2024-08-09T18:40:15.411Z"},{"id":1493,"locale":"es","published_at":"2024-08-09T18:40:15.411Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/How_to_Choose_the_Right_Milvus_Deployment_Mode_for_Your_AI_Applications_9a98377cae.png","belong":"blog","authorNames":["Robert Guo"]},{"id":"blog-498","title":"The Landscape of GenAI Ecosystem: Beyond LLMs and Vector Databases","image":{"id":4148,"url":"https://assets.zilliz.com/The_Landscape_of_Gen_AI_Ecosystem_Beyond_LL_Ms_and_Vector_Databases_d53dc68a16.png"},"display_time":"Aug 09, 2024","deploy_time":null,"url":"landscape-of-gen-ai-ecosystem-beyond-llms-and-vector-databases","abstract":"Initially, Large Language Models (LLMs) and vector databases captured the most attention. However, the GenAI ecosystem is much broader and more complex than just these two components.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":101,"name":"Jiang Chen","author_tags":"Head of Ecosystem and Developer Relations","published_at":"2023-10-16T07:05:20.176Z","created_by":18,"updated_by":82,"created_at":"2023-10-16T07:05:18.702Z","updated_at":"2024-09-10T17:33:55.053Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/jiang-0616/","self_intro":"Jiang is currently Head of Ecosystem and Developer Relations at Zilliz. He has years of experience in data infrastructures and cloud security. Before joining Zilliz, he had previously served as a tech lead and product manager at Google, where he led the development of web-scale semantic understanding and search indexing that powers innovative search products such as short video search. He has extensive industry experience handling massive unstructured data and multimedia content retrieval. He has also worked on cloud authorization systems and research on data privacy technologies. Jiang holds a Master's degree in Computer Science from the University of Michigan.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":10,"localizations":[{"id":1045,"locale":"ja-JP","published_at":"2024-08-10T00:02:20.120Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/The_Landscape_of_Gen_AI_Ecosystem_Beyond_LL_Ms_and_Vector_Databases_d53dc68a16.png","belong":"blog","authorNames":["Jiang Chen"]},{"id":"blog-496","title":"How Vector Databases are Revolutionizing Unstructured Data Search in AI Applications","image":{"id":4129,"url":"https://assets.zilliz.com/Aug_06_How_Vector_Databases_are_Revolutionizing_Unstructured_Data_Search_in_AI_Applications_517c3203b2.png"},"display_time":"Aug 08, 2024","deploy_time":null,"url":"how-vector-dbs-are-revolutionizing-unstructured-data-search-ai-applications","abstract":"Learn how vector databases have emerged as a transformative technology in the field of AI and machine learning, particularly for handling unstructured data. Their applications extend far beyond simple retrieval-augmented generation (RAG) systems, revolutionizing various domains including customer support, recommendation systems, drug discovery, and multimodal search.","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":158,"name":"Denis Kuria","author_tags":"Freelance Technical Writer","published_at":"2024-05-01T00:39:32.350Z","created_by":18,"updated_by":18,"created_at":"2024-05-01T00:39:30.888Z","updated_at":"2024-07-03T06:50:56.660Z","home_page":null,"home_page_link":null,"self_intro":"Denis is a machine learning engineer who enjoys writing guides to help other developers. He has a bachelor's in computer science and loves hiking and exploring the world.\n","repost_to_medium":null,"repost_state":null,"meta_description":"Denis Kuria is a freelance technical writer at Zilliz. ","locale":"en"}],"read_time":12,"localizations":[{"id":1165,"locale":"ja-JP","published_at":"2024-08-09T23:45:15.886Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Aug_06_How_Vector_Databases_are_Revolutionizing_Unstructured_Data_Search_in_AI_Applications_517c3203b2.png","belong":"blog","authorNames":["Denis Kuria"]},{"id":"learn-238","title":"Building a Multimodal RAG with Gemini 1.5, BGE-M3, Milvus Lite, and LangChain ","image":{"id":4102,"url":"https://assets.zilliz.com/Aug_05_Building_a_Multimodal_RAG_with_Gemini_1_5_BGE_M3_Milvus_Lite_and_Lang_Chain_d1dfc0bb0b.png"},"display_time":"Aug 07, 2024","url":"build-multimodal-rag-gemini-bge-m3-milvus-langchain","abstract":"Multimodal RAG extends RAG by accepting data from different modalities as context. Learn how to build one with Gemini 1.5, BGE-M3, Milvus, and LangChain. \n","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":125,"name":"Ruben Winastwan","author_tags":"Freelance Technical Writer","published_at":"2024-03-26T09:16:27.310Z","created_by":18,"updated_by":18,"created_at":"2024-03-26T09:16:24.498Z","updated_at":"2024-07-03T07:56:29.256Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Ruben Winastwan, Freelance Technical Writer","locale":"en"}],"read_time":14,"localizations":[{"id":412,"locale":"ja-JP","published_at":"2024-08-07T16:41:36.638Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Aug_05_Building_a_Multimodal_RAG_with_Gemini_1_5_BGE_M3_Milvus_Lite_and_Lang_Chain_d1dfc0bb0b.png","belong":"learn","authorNames":["Ruben Winastwan"]},{"id":"blog-495","title":"Optimizing Multi-agent Systems with Mistral Large, Mistral Nemo, and Llama-agents","image":{"id":4122,"url":"https://assets.zilliz.com/Optimizing_Multi_agent_Systems_with_Mistral_Large_Mistral_Nemo_and_Llama_agents_b230b29d7e.png"},"display_time":"Aug 06, 2024","deploy_time":null,"url":"optimize-multi-agent-system-with-mistral-large-mistral-nemo-and-llama-agents","abstract":"Agents can handle complex tasks with minimal human intervention. Learn how to build such agents with Mistral Large, Nemo, Llama agents, and Milvus. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":115,"name":"Stephen Batifol","author_tags":"Developer Advocate ","published_at":"2024-03-07T03:46:04.655Z","created_by":18,"updated_by":18,"created_at":"2024-03-07T03:46:02.457Z","updated_at":"2024-07-18T15:56:42.529Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/stephen-batifol/","self_intro":"Stephen Batifol is a Developer Advocate at Zilliz. He previously worked as a Machine Learning Engineer at Wolt, where he was working on the ML Platform and as a Data Scientist at Brevo. Stephen studied Computer Science and Artificial Intelligence. He enjoys dancing and surfing. \n","repost_to_medium":null,"repost_state":null,"meta_description":"Stephen Batifol is a Developer Advocate at Zilliz.","locale":"en"}],"read_time":13,"localizations":[{"id":1137,"locale":"ja-JP","published_at":"2024-08-08T07:45:39.741Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Optimizing_Multi_agent_Systems_with_Mistral_Large_Mistral_Nemo_and_Llama_agents_b230b29d7e.png","belong":"blog","authorNames":["Stephen Batifol"]},{"id":"blog-493","title":"Building a Multilingual RAG with Milvus, LangChain, and OpenAI LLM","image":{"id":4108,"url":"https://assets.zilliz.com/Building_a_Multilingual_RAG_with_Milvus_Lang_Chain_and_Open_AI_LLM_499b6b892b.png"},"display_time":"Aug 05, 2024","deploy_time":null,"url":"building-multilingual-rag-milvus-langchain-openai","abstract":"Multilingual RAG expands the capabilities of traditional RAG to support multiple languages. Learn how to build a multilingual RAG with Milvus, LangChain, and OpenAI. \n","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":150,"name":"Tim Mugabi","author_tags":"Freelance Technical Writer","published_at":"2024-04-24T21:23:34.511Z","created_by":18,"updated_by":18,"created_at":"2024-04-24T21:23:32.810Z","updated_at":"2024-07-03T07:49:21.138Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Tim Mugabi, Freelance Technical Writer","locale":"en"}],"read_time":10,"localizations":[{"id":935,"locale":"ja-JP","published_at":"2024-08-07T17:09:34.100Z"},{"id":1541,"locale":"ru","published_at":"2024-08-07T17:09:34.100Z"},{"id":1595,"locale":"it","published_at":"2024-08-07T17:09:34.100Z"},{"id":1514,"locale":"pt","published_at":"2024-08-07T17:09:34.100Z"},{"id":1622,"locale":"fr","published_at":"2024-08-07T17:09:34.100Z"},{"id":1568,"locale":"ko","published_at":"2024-08-07T17:09:34.100Z"},{"id":1487,"locale":"es","published_at":"2024-08-07T17:09:34.100Z"},{"id":1460,"locale":"de","published_at":"2024-08-07T17:09:34.100Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Building_a_Multilingual_RAG_with_Milvus_Lang_Chain_and_Open_AI_LLM_499b6b892b.png","belong":"blog","authorNames":["Tim Mugabi"]},{"id":"blog-494","title":"Building RAG with Milvus, vLLM, and Llama 3.1","image":{"id":4110,"url":"https://assets.zilliz.com/Aug_05_Building_RAG_with_Milvus_v_LLM_and_Llama_3_1_eed7c57296.png"},"display_time":"Aug 04, 2024","deploy_time":null,"url":"building-rag-milvus-vllm-llama-3-1","abstract":"vLLM is a fast and easy-to-use library for LLM inference and serving. We’ll share how to build a high-performance RAG with vLLM, Milvus, and Llama3.1. \n","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":94,"name":"Christy Bergman","author_tags":"Developer Advocate","published_at":"2023-10-06T00:29:45.486Z","created_by":18,"updated_by":18,"created_at":"2023-10-06T00:29:30.751Z","updated_at":"2024-07-18T16:01:45.942Z","home_page":null,"home_page_link":null,"self_intro":"Christy Bergman is a passionate Developer Advocate at Zilliz. She previously worked in distributed computing at Anyscale and as a Specialist AI/ML Solutions Architect at AWS. Christy studied applied math, is a self-taught coder, and has published papers, including one with ACM Recsys. She enjoys hiking and bird watching.","repost_to_medium":null,"repost_state":null,"meta_description":"Christy Bergman is a passionate Developer Advocate at Zilliz. ","locale":"en"}],"read_time":8,"localizations":[{"id":1504,"locale":"es","published_at":"2024-08-07T18:14:13.945Z"},{"id":1585,"locale":"ko","published_at":"2024-08-07T18:14:13.945Z"},{"id":1639,"locale":"fr","published_at":"2024-08-07T18:14:13.945Z"},{"id":1531,"locale":"pt","published_at":"2024-08-07T18:14:13.945Z"},{"id":1477,"locale":"de","published_at":"2024-08-07T18:14:13.945Z"},{"id":1558,"locale":"ru","published_at":"2024-08-07T18:14:13.945Z"},{"id":1338,"locale":"ja-JP","published_at":"2024-08-07T18:14:13.945Z"},{"id":1612,"locale":"it","published_at":"2024-08-07T18:14:13.945Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Aug_05_Building_RAG_with_Milvus_v_LLM_and_Llama_3_1_eed7c57296.png","belong":"blog","authorNames":["Christy Bergman"]},{"id":"learn-239","title":"Vector Database vs Graph Database","image":{"id":4126,"url":"https://assets.zilliz.com/July_27_Vector_Database_vs_Graph_Database_a4353efd94.png"},"display_time":"Aug 03, 2024","url":"vector-database-vs-graph-database","abstract":"This article will comprehensively compare vector and graph databases, helping you understand their fundamental differences, strengths, and ideal applications","tags":[{"id":39,"name":"VectorDB 101","published_at":"2022-09-30T05:56:34.554Z","created_by":18,"updated_by":18,"created_at":"2022-09-30T05:56:31.633Z","updated_at":"2024-07-10T07:12:04.155Z","locale":"en"}],"authors":[{"id":158,"name":"Denis Kuria","author_tags":"Freelance Technical Writer","published_at":"2024-05-01T00:39:32.350Z","created_by":18,"updated_by":18,"created_at":"2024-05-01T00:39:30.888Z","updated_at":"2024-07-03T06:50:56.660Z","home_page":null,"home_page_link":null,"self_intro":"Denis is a machine learning engineer who enjoys writing guides to help other developers. He has a bachelor's in computer science and loves hiking and exploring the world.\n","repost_to_medium":null,"repost_state":null,"meta_description":"Denis Kuria is a freelance technical writer at Zilliz. ","locale":"en"}],"read_time":12,"localizations":[{"id":455,"locale":"ja-JP","published_at":"2024-08-09T23:41:12.486Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/July_27_Vector_Database_vs_Graph_Database_a4353efd94.png","belong":"learn","authorNames":["Denis Kuria"]},{"id":"blog-492","title":"GraphRAG Explained: Enhancing RAG with Knowledge Graphs","image":{"id":4091,"url":"https://assets.zilliz.com/Graph_RAG_Explained_Enhancing_RAG_with_Knowledge_Graphs_5d49ba839e.png"},"display_time":"Aug 02, 2024","deploy_time":null,"url":"graphrag-explained-enhance-rag-with-knowledge-graphs","abstract":"GraphRAG is a new technique that augments RAG retrieval and generation with knowledge graphs. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":107,"name":"Cheney Zhang","author_tags":"Algorithm Engineer","published_at":"2023-11-08T07:21:13.405Z","created_by":18,"updated_by":18,"created_at":"2023-11-08T07:21:10.513Z","updated_at":"2024-07-18T15:56:58.028Z","home_page":"GitHub","home_page_link":"https://github.com/zc277584121","self_intro":"Cheney Zhang is an accomplished Algorithm Engineer at Zilliz. With a profound passion for and expertise in cutting-edge AI technologies such as LLMs and Retrieval Augmented Generation (RAG), Cheney has actively contributed to many innovative AI projects, including Towhee, Akcio, and OSSChat. Before joining Zilliz, he worked for CMB Network Technology as an Algorithm Engineer. Cheney holds a master's degree from Nanjing University of Aeronautics and Astronautics.","repost_to_medium":null,"repost_state":null,"meta_description":"Cheney Zhang is an accomplished Algorithm Engineer at Zilliz. ","locale":"en"}],"read_time":15,"localizations":[{"id":822,"locale":"ja-JP","published_at":"2024-08-06T06:51:12.316Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Graph_RAG_Explained_Enhancing_RAG_with_Knowledge_Graphs_5d49ba839e.png","belong":"blog","authorNames":["Cheney Zhang"]},{"id":"learn-240","title":"LLM-Eval: A Streamlined Approach to Evaluating LLM Conversations ","image":{"id":4197,"url":"https://assets.zilliz.com/Aug_16_LLM_Eval_A_Streamlined_Approach_to_Evaluating_LLM_Conversations_593619e681.png"},"display_time":"Aug 01, 2024","url":"streamlined-approach-to-evaluating-llm-conversations","abstract":"In this piece, we'll talk about a method called LLM-Eval, which is used to evaluate the response quality of an LLM. ","tags":[{"id":73,"name":"Paper Reading","published_at":"2024-08-10T14:40:10.906Z","created_by":60,"updated_by":60,"created_at":"2024-08-10T14:40:09.192Z","updated_at":"2024-08-10T14:40:10.914Z","locale":"en"}],"authors":[{"id":125,"name":"Ruben Winastwan","author_tags":"Freelance Technical Writer","published_at":"2024-03-26T09:16:27.310Z","created_by":18,"updated_by":18,"created_at":"2024-03-26T09:16:24.498Z","updated_at":"2024-07-03T07:56:29.256Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Ruben Winastwan, Freelance Technical Writer","locale":"en"}],"read_time":13,"localizations":[{"id":439,"locale":"ja-JP","published_at":"2024-08-09T19:02:10.771Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Aug_16_LLM_Eval_A_Streamlined_Approach_to_Evaluating_LLM_Conversations_593619e681.png","belong":"learn","authorNames":["Ruben Winastwan"]},{"id":"blog-491","title":"Function Calling with Ollama, Llama 3.2 and Milvus","image":{"id":4609,"url":"https://assets.zilliz.com/Function_Calling_with_Ollama_Llama_3_2_and_Milvus_6a5ce772ed.png"},"display_time":"Jul 30, 2024","deploy_time":null,"url":"function-calling-ollama-llama-3-milvus","abstract":"A step-by-step guide on how to integrate Llama 3.2 with external tools like Milvus vector database and APIs to build powerful, context-aware applications.\n\n","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":115,"name":"Stephen Batifol","author_tags":"Developer Advocate ","published_at":"2024-03-07T03:46:04.655Z","created_by":18,"updated_by":18,"created_at":"2024-03-07T03:46:02.457Z","updated_at":"2024-07-18T15:56:42.529Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/stephen-batifol/","self_intro":"Stephen Batifol is a Developer Advocate at Zilliz. He previously worked as a Machine Learning Engineer at Wolt, where he was working on the ML Platform and as a Data Scientist at Brevo. Stephen studied Computer Science and Artificial Intelligence. He enjoys dancing and surfing. \n","repost_to_medium":null,"repost_state":null,"meta_description":"Stephen Batifol is a Developer Advocate at Zilliz.","locale":"en"}],"read_time":5,"localizations":[{"id":988,"locale":"ja-JP","published_at":"2024-07-30T16:39:45.059Z"},{"id":1624,"locale":"fr","published_at":"2024-07-30T16:39:45.059Z"},{"id":1516,"locale":"pt","published_at":"2024-07-30T16:39:45.059Z"},{"id":1462,"locale":"de","published_at":"2024-07-30T16:39:45.059Z"},{"id":1543,"locale":"ru","published_at":"2024-07-30T16:39:45.059Z"},{"id":1570,"locale":"ko","published_at":"2024-07-30T16:39:45.059Z"},{"id":1489,"locale":"es","published_at":"2024-07-30T16:39:45.059Z"},{"id":1597,"locale":"it","published_at":"2024-07-30T16:39:45.059Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Function_Calling_with_Ollama_Llama_3_2_and_Milvus_6a5ce772ed.png","belong":"blog","authorNames":["Stephen Batifol"]},{"id":"blog-490","title":"Building a Multimodal Product Recommender Demo Using Milvus and Streamlit","image":{"id":4069,"url":"https://assets.zilliz.com/Building_a_Multimodal_Product_Recommender_Demo_Using_Milvus_and_Streamlit_f1073feb78.png"},"display_time":"Jul 30, 2024","deploy_time":"2024-07-30T04:00:00.000Z","url":"build-multimodal-product-recommender-demo-using-milvus-and-streamlit","abstract":"A step-by-step guide on how to build and run the Multimodal recommendation system with Milvus, Streamlit, MagicLens, and GPT-4o.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":102,"name":"David Wang","author_tags":"Algorithm Engineer at Zilliz","published_at":"2023-10-27T08:41:57.519Z","created_by":18,"updated_by":18,"created_at":"2023-10-27T08:41:55.636Z","updated_at":"2024-04-16T02:43:37.282Z","home_page":"GitHub","home_page_link":"https://github.com/wxywb","self_intro":"David Wang, Algorithm Engineer at Zilliz, brings extensive expertise in computer vision and natural language processing. His contributions to advanced embedding algorithm research, including projects like Towhee and GPTCache, reflect his commitment to advancing AI technologies. Before joining Zilliz, he worked at Alibaba Cloud for large-scale object recognition and classification projects. David holds a Master's degree from Dalian University of Technology.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"},{"id":94,"name":"Christy Bergman","author_tags":"Developer Advocate","published_at":"2023-10-06T00:29:45.486Z","created_by":18,"updated_by":18,"created_at":"2023-10-06T00:29:30.751Z","updated_at":"2024-07-18T16:01:45.942Z","home_page":null,"home_page_link":null,"self_intro":"Christy Bergman is a passionate Developer Advocate at Zilliz. She previously worked in distributed computing at Anyscale and as a Specialist AI/ML Solutions Architect at AWS. Christy studied applied math, is a self-taught coder, and has published papers, including one with ACM Recsys. She enjoys hiking and bird watching.","repost_to_medium":null,"repost_state":null,"meta_description":"Christy Bergman is a passionate Developer Advocate at Zilliz. ","locale":"en"},{"id":171,"name":"Reina Wang","author_tags":"Software Engineer Intern at Zilliz","published_at":"2024-07-30T15:09:21.996Z","created_by":18,"updated_by":18,"created_at":"2024-07-30T15:09:19.946Z","updated_at":"2024-07-30T15:09:22.063Z","home_page":"","home_page_link":"","self_intro":"Reina Wang is a Software Engineer Intern at Zilliz. ","repost_to_medium":null,"repost_state":null,"meta_description":"Reina Wang, Software Engineer Intern at Zilliz","locale":"en"}],"read_time":5,"localizations":[{"id":1345,"locale":"ja-JP","published_at":"2024-07-30T15:07:49.408Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Building_a_Multimodal_Product_Recommender_Demo_Using_Milvus_and_Streamlit_f1073feb78.png","belong":"blog","authorNames":["David Wang","Christy Bergman","Reina Wang"]},{"id":"learn-237","title":"Building RAG with Milvus Lite, Llama3, and LlamaIndex","image":{"id":4066,"url":"https://assets.zilliz.com/Building_RAG_with_Milvus_Lite_Llama3_and_Llama_Index_b59dbcf513.png"},"display_time":"Jul 29, 2024","url":"build-rag-with-milvus-lite-llama3-and-llamaindex","abstract":"Retrieval Augmented Generation (RAG) is a method for mitigating LLM hallucinations. Learn how to build a chatbot RAG with Milvus, Llama3, and LlamaIndex. ","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":125,"name":"Ruben Winastwan","author_tags":"Freelance Technical Writer","published_at":"2024-03-26T09:16:27.310Z","created_by":18,"updated_by":18,"created_at":"2024-03-26T09:16:24.498Z","updated_at":"2024-07-03T07:56:29.256Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Ruben Winastwan, Freelance Technical Writer","locale":"en"}],"read_time":13,"localizations":[{"id":466,"locale":"ja-JP","published_at":"2024-07-30T14:48:17.267Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Building_RAG_with_Milvus_Lite_Llama3_and_Llama_Index_b59dbcf513.png","belong":"learn","authorNames":["Ruben Winastwan"]},{"id":"learn-236","title":"Understanding DETR: End-to-end Object Detection with Transformers","image":{"id":4124,"url":"https://assets.zilliz.com/July_27_Understanding_DETR_End_to_end_Object_Detection_with_Transformers_b6f491a1eb.png"},"display_time":"Jul 27, 2024","url":"detection-transformers-detr-end-to-end-object-detection-with-transformers","abstract":"DETR (DEtection TRansformer) is a deep learning model for end-to-end object detection using transformers. ","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":170,"name":"Yesha Shastri","author_tags":"Freelance Technical Writer in AI/ML","published_at":"2024-07-29T08:44:59.761Z","created_by":18,"updated_by":18,"created_at":"2024-07-29T08:44:38.291Z","updated_at":"2024-07-29T08:44:59.820Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/yeshashastri/","self_intro":"Yesha Shastri, Freelance Technical Writer in AI/ML","repost_to_medium":null,"repost_state":null,"meta_description":"Yesha Shastri, Freelance Technical Writer","locale":"en"}],"read_time":9,"localizations":[{"id":447,"locale":"ja-JP","published_at":"2024-07-29T08:39:11.093Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/July_27_Understanding_DETR_End_to_end_Object_Detection_with_Transformers_b6f491a1eb.png","belong":"learn","authorNames":["Yesha Shastri"]},{"id":"learn-235","title":"A Beginner's Guide to Understanding Vision Transformers (ViT)","image":{"id":4123,"url":"https://assets.zilliz.com/Aug_02_A_Beginner_s_Guide_to_Understanding_Vision_Transformer_Vi_T_8476fa50b4.png"},"display_time":"Jul 26, 2024","url":"understanding-vision-transformers-vit","abstract":"Vision Transformers (ViTs) are neural network models that use transformers to perform computer vision tasks like object detection and image classification. ","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":118,"name":" Haziqa Sajid","author_tags":"Freelance Technical Writer","published_at":"2024-03-12T10:25:34.265Z","created_by":18,"updated_by":18,"created_at":"2024-03-12T10:25:31.148Z","updated_at":"2024-07-03T07:58:27.010Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/haziqa-sajid-22b53245/","self_intro":"Digital Storytelling for Data, AI, B2B \u0026 SaaS","repost_to_medium":null,"repost_state":null,"meta_description":" Haziqa Sajid, Freelance Technical Writer","locale":"en"}],"read_time":11,"localizations":[{"id":419,"locale":"ja-JP","published_at":"2024-07-29T08:22:08.723Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Aug_02_A_Beginner_s_Guide_to_Understanding_Vision_Transformer_Vi_T_8476fa50b4.png","belong":"learn","authorNames":[" Haziqa Sajid"]},{"id":"learn-233","title":"Improving Information Retrieval and RAG with Hypothetical Document Embeddings (HyDE)","image":{"id":4459,"url":"https://assets.zilliz.com/July_31_Improving_Information_Retrieval_and_RAG_with_Hy_DE_8bfa67118f.png"},"display_time":"Jul 25, 2024","url":"improve-rag-and-information-retrieval-with-hyde-hypothetical-document-embeddings","abstract":"HyDE (Hypothetical Document Embeddings) is a retrieval method that uses \"fake\" documents to improve the answers of LLM and RAG. ","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":118,"name":" Haziqa Sajid","author_tags":"Freelance Technical Writer","published_at":"2024-03-12T10:25:34.265Z","created_by":18,"updated_by":18,"created_at":"2024-03-12T10:25:31.148Z","updated_at":"2024-07-03T07:58:27.010Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/haziqa-sajid-22b53245/","self_intro":"Digital Storytelling for Data, AI, B2B \u0026 SaaS","repost_to_medium":null,"repost_state":null,"meta_description":" Haziqa Sajid, Freelance Technical Writer","locale":"en"}],"read_time":9,"localizations":[{"id":300,"locale":"ja-JP","published_at":"2024-07-26T06:40:46.143Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/July_31_Improving_Information_Retrieval_and_RAG_with_Hy_DE_8bfa67118f.png","belong":"learn","authorNames":[" Haziqa Sajid"]},{"id":"blog-489","title":"Techniques and Challenges in Evaluating Your GenAI Applications Using LLM-as-a-judge","image":{"id":4026,"url":"https://assets.zilliz.com/July_19_Techniques_and_Challenges_in_Evaluating_Your_Gen_AI_Applications_Using_LLM_as_a_judge_993cadfb9e.png"},"display_time":"Jul 24, 2024","deploy_time":null,"url":"technique-and-challenges-in-evaluating-your-genai-app-using-llm-as-a-judge","abstract":"LLM-as-a-judge is an approach to systematically assess your LLM outputs' relevance, accuracy, and quality with LLM itself or a separate LLM as the \"judge.\" ","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":151,"name":"Fariba Laiq","author_tags":"Freelance Technical Writer","published_at":"2024-04-24T21:23:59.165Z","created_by":18,"updated_by":18,"created_at":"2024-04-24T21:23:57.717Z","updated_at":"2024-07-29T16:21:27.954Z","home_page":null,"home_page_link":null,"self_intro":"Description: Fariba Laiq is a freelance content writer at Zilliz. She has studied Computer Science, been a coding instructor, and published research papers in the domain of AI and cyber-security. She is passionate about learning more about LLMs and vector databases in the ever evolving era of AI. Along with technical skills, she is also a self-taught artist.","repost_to_medium":null,"repost_state":null,"meta_description":"Fariba Laiq, Freelance Technical Writer","locale":"en"}],"read_time":10,"localizations":[{"id":1153,"locale":"ja-JP","published_at":"2024-07-26T06:01:35.062Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/July_19_Techniques_and_Challenges_in_Evaluating_Your_Gen_AI_Applications_Using_LLM_as_a_judge_993cadfb9e.png","belong":"blog","authorNames":["Fariba Laiq"]},{"id":"blog-488","title":"Enhancing Your RAG with Knowledge Graphs Using KnowHow","image":{"id":4017,"url":"https://assets.zilliz.com/Enhancing_Your_RAG_with_Knowledge_Graphs_1_d2ad1592ce.png"},"display_time":"Jul 23, 2024","deploy_time":null,"url":"enhance-rag-with-knowledge-graphs","abstract":"Knowledge Graphs (KGs) store and link data based on their relationships. KG-enhanced RAG can significantly improve retrieval capabilities and answer quality. ","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":118,"name":" Haziqa Sajid","author_tags":"Freelance Technical Writer","published_at":"2024-03-12T10:25:34.265Z","created_by":18,"updated_by":18,"created_at":"2024-03-12T10:25:31.148Z","updated_at":"2024-07-03T07:58:27.010Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/haziqa-sajid-22b53245/","self_intro":"Digital Storytelling for Data, AI, B2B \u0026 SaaS","repost_to_medium":null,"repost_state":null,"meta_description":" Haziqa Sajid, Freelance Technical Writer","locale":"en"}],"read_time":8,"localizations":[{"id":1478,"locale":"de","published_at":"2024-07-26T05:09:00.619Z"},{"id":1559,"locale":"ru","published_at":"2024-07-26T05:09:00.619Z"},{"id":1586,"locale":"ko","published_at":"2024-07-26T05:09:00.619Z"},{"id":1343,"locale":"ja-JP","published_at":"2024-07-26T05:09:00.619Z"},{"id":1613,"locale":"it","published_at":"2024-07-26T05:09:00.619Z"},{"id":1505,"locale":"es","published_at":"2024-07-26T05:09:00.619Z"},{"id":1640,"locale":"fr","published_at":"2024-07-26T05:09:00.619Z"},{"id":1532,"locale":"pt","published_at":"2024-07-26T05:09:00.619Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Enhancing_Your_RAG_with_Knowledge_Graphs_1_d2ad1592ce.png","belong":"blog","authorNames":[" Haziqa Sajid"]},{"id":"learn-232","title":"Understanding Regularization in Neural Networks ","image":{"id":4013,"url":"https://assets.zilliz.com/Understanding_Regularization_in_Neural_Networks_b60f880a59.png"},"display_time":"Jul 22, 2024","url":"understanding-regularization-in-nueral-networks","abstract":"Regularization prevents a machine-learning model from overfitting during the training process. We'll discuss its concept and key regularization techniques. ","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":125,"name":"Ruben Winastwan","author_tags":"Freelance Technical Writer","published_at":"2024-03-26T09:16:27.310Z","created_by":18,"updated_by":18,"created_at":"2024-03-26T09:16:24.498Z","updated_at":"2024-07-03T07:56:29.256Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Ruben Winastwan, Freelance Technical Writer","locale":"en"}],"read_time":15,"localizations":[{"id":374,"locale":"ja-JP","published_at":"2024-07-23T15:17:05.942Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Understanding_Regularization_in_Neural_Networks_b60f880a59.png","belong":"learn","authorNames":["Ruben Winastwan"]},{"id":"learn-234","title":"Hierarchical Navigable Small Worlds (HNSW) ","image":{"id":1278,"url":"https://assets.zilliz.com/Mar_29_Vector_Database_101_Hierarchical_Navigable_Small_Worlds_HNSW_26ee2ea302.png"},"display_time":"Jul 17, 2024","url":"hierarchical-navigable-small-worlds-HNSW","abstract":"Hierarchical Navigable Small World (HNSW) is a graph-based algorithm that performs approximate nearest neighbor (ANN) searches in vector databases.","tags":[{"id":39,"name":"VectorDB 101","published_at":"2022-09-30T05:56:34.554Z","created_by":18,"updated_by":18,"created_at":"2022-09-30T05:56:31.633Z","updated_at":"2024-07-10T07:12:04.155Z","locale":"en"}],"authors":[{"id":3,"name":"Frank Liu","author_tags":"Director of Operations \u0026 ML Architect at Zilliz","published_at":"2021-12-23T11:08:08.015Z","created_by":18,"updated_by":18,"created_at":"2021-12-23T10:40:59.821Z","updated_at":"2023-04-21T22:30:10.416Z","home_page":"GitHub","home_page_link":"https://github.com/fzliu","self_intro":"Frank Liu is the Director of Operations \u0026 ML Architect at Zilliz, where he serves as a maintainer for the Towhee open-source project. Prior to Zilliz, Frank co-founded Orion Innovations, an ML-powered indoor positioning startup based in Shanghai and worked as an ML engineer at Yahoo in San Francisco. In his free time, Frank enjoys playing chess, swimming, and powerlifting. Frank holds MS and BS degrees in Electrical Engineering from Stanford University. ","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":13,"localizations":[{"id":426,"locale":"ja-JP","published_at":"2024-07-28T17:28:32.243Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Mar_29_Vector_Database_101_Hierarchical_Navigable_Small_Worlds_HNSW_26ee2ea302.png","belong":"learn","authorNames":["Frank Liu"]},{"id":"blog-487","title":"Setting up Milvus on Amazon EKS","image":{"id":3995,"url":"https://assets.zilliz.com/Setting_up_Milvus_on_Amazon_EKS_3a0c8614e8.png"},"display_time":"Jul 16, 2024","deploy_time":null,"url":"set-up-milvus-vector-database-on-amazon-eks","abstract":"This blog provides step-by-step guidance on deploying a Milvus cluster using EKS and other services. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":94,"name":"Christy Bergman","author_tags":"Developer Advocate","published_at":"2023-10-06T00:29:45.486Z","created_by":18,"updated_by":18,"created_at":"2023-10-06T00:29:30.751Z","updated_at":"2024-07-18T16:01:45.942Z","home_page":null,"home_page_link":null,"self_intro":"Christy Bergman is a passionate Developer Advocate at Zilliz. She previously worked in distributed computing at Anyscale and as a Specialist AI/ML Solutions Architect at AWS. Christy studied applied math, is a self-taught coder, and has published papers, including one with ACM Recsys. She enjoys hiking and bird watching.","repost_to_medium":null,"repost_state":null,"meta_description":"Christy Bergman is a passionate Developer Advocate at Zilliz. ","locale":"en"}],"read_time":15,"localizations":[{"id":856,"locale":"ja-JP","published_at":"2024-07-16T12:26:22.561Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Setting_up_Milvus_on_Amazon_EKS_3a0c8614e8.png","belong":"blog","authorNames":["Christy Bergman"]},{"id":"blog-486","title":"Building a Conversational AI Agent with Long-Term Memory Using LangChain and Milvus","image":{"id":3981,"url":"https://assets.zilliz.com/Building_a_Conversational_AI_Agent_with_Long_Term_Memory_Using_Lang_Chain_and_Milvus_b889c18c41.png"},"display_time":"Jul 15, 2024","deploy_time":null,"url":"building-a-conversational-ai-agent-long-term-memory-langchain-milvus","abstract":"Explore LangChain agents, their potential to transform conversational AI, and how Milvus can add long-term memory to your apps. ","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":169,"name":"Rok Benko","author_tags":"Freelance Technical Writer","published_at":"2024-07-15T17:06:44.712Z","created_by":18,"updated_by":18,"created_at":"2024-07-15T17:06:43.335Z","updated_at":"2024-07-18T15:54:15.172Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Rok Benko is a Freelance Technical Writer. ","locale":"en"}],"read_time":8,"localizations":[{"id":1330,"locale":"ja-JP","published_at":"2024-07-15T17:08:26.493Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Building_a_Conversational_AI_Agent_with_Long_Term_Memory_Using_Lang_Chain_and_Milvus_b889c18c41.png","belong":"blog","authorNames":["Rok Benko"]},{"id":"blog-485","title":"Metadata Filtering, Hybrid Search or Agent When Building Your RAG Application","image":{"id":3974,"url":"https://assets.zilliz.com/Metadata_Filtering_Hybrid_Search_or_Agent_When_Building_Your_RAG_Application_463c7c1efb.png"},"display_time":"Jul 12, 2024","deploy_time":null,"url":"metadata-filtering-hybrid-search-or-agent-in-rag-applications","abstract":"Using Metadata Filtering, Hybrid Search, and Agents, all integrated in Milvus, can enhance your RAG application.\n","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":115,"name":"Stephen Batifol","author_tags":"Developer Advocate ","published_at":"2024-03-07T03:46:04.655Z","created_by":18,"updated_by":18,"created_at":"2024-03-07T03:46:02.457Z","updated_at":"2024-07-18T15:56:42.529Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/stephen-batifol/","self_intro":"Stephen Batifol is a Developer Advocate at Zilliz. He previously worked as a Machine Learning Engineer at Wolt, where he was working on the ML Platform and as a Data Scientist at Brevo. Stephen studied Computer Science and Artificial Intelligence. He enjoys dancing and surfing. \n","repost_to_medium":null,"repost_state":null,"meta_description":"Stephen Batifol is a Developer Advocate at Zilliz.","locale":"en"}],"read_time":4,"localizations":[{"id":1344,"locale":"ja-JP","published_at":"2024-07-12T17:15:55.380Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Metadata_Filtering_Hybrid_Search_or_Agent_When_Building_Your_RAG_Application_463c7c1efb.png","belong":"blog","authorNames":["Stephen Batifol"]},{"id":"blog-482","title":"Simplifying Legal Research with RAG, Milvus, and Ollama","image":{"id":3963,"url":"https://assets.zilliz.com/Simplifying_Legal_Research_with_RAG_Milvus_and_Ollama_66918c55d6.png"},"display_time":"Jul 11, 2024","deploy_time":null,"url":"simplifying-legal-research-with-rag-milvus-ollama","abstract":"In this blog post, we will see how we can apply RAG to Legal data. Legal research can be time-consuming. You usually need to review a large number of documents to find the answers you need. Retrieval-Augmented Generation (RAG) can help streamline your research process.\n","tags":[{"id":1,"name":"Case Study","published_at":"2021-01-15T10:34:37.316Z","created_by":18,"updated_by":18,"created_at":"2021-01-15T10:34:34.857Z","updated_at":"2021-01-25T10:31:22.499Z","locale":"en"}],"authors":[{"id":115,"name":"Stephen Batifol","author_tags":"Developer Advocate ","published_at":"2024-03-07T03:46:04.655Z","created_by":18,"updated_by":18,"created_at":"2024-03-07T03:46:02.457Z","updated_at":"2024-07-18T15:56:42.529Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/stephen-batifol/","self_intro":"Stephen Batifol is a Developer Advocate at Zilliz. He previously worked as a Machine Learning Engineer at Wolt, where he was working on the ML Platform and as a Data Scientist at Brevo. Stephen studied Computer Science and Artificial Intelligence. He enjoys dancing and surfing. \n","repost_to_medium":null,"repost_state":null,"meta_description":"Stephen Batifol is a Developer Advocate at Zilliz.","locale":"en"}],"read_time":7,"localizations":[{"id":1298,"locale":"ja-JP","published_at":"2024-07-11T22:37:53.928Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Simplifying_Legal_Research_with_RAG_Milvus_and_Ollama_66918c55d6.png","belong":"blog","authorNames":["Stephen Batifol"]},{"id":"blog-483","title":"Building Production Ready Search Pipelines with Spark and Milvus","image":{"id":3964,"url":"https://assets.zilliz.com/Building_Production_Ready_Search_Pipelines_with_Spark_and_Milvus_3362af6775.png"},"display_time":"Jul 10, 2024","deploy_time":null,"url":"building-production-ready-search-pipelines-spark-milvus","abstract":"A step-by-step process to build an efficient and production-ready vector search pipeline using Databricks Spark and Milvus. ","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":125,"name":"Ruben Winastwan","author_tags":"Freelance Technical Writer","published_at":"2024-03-26T09:16:27.310Z","created_by":18,"updated_by":18,"created_at":"2024-03-26T09:16:24.498Z","updated_at":"2024-07-03T07:56:29.256Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Ruben Winastwan, Freelance Technical Writer","locale":"en"}],"read_time":10,"localizations":[{"id":1312,"locale":"ja-JP","published_at":"2024-07-12T00:05:20.254Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Building_Production_Ready_Search_Pipelines_with_Spark_and_Milvus_3362af6775.png","belong":"blog","authorNames":["Ruben Winastwan"]},{"id":"blog-478","title":"Build Better Multimodal RAG Pipelines with FiftyOne, LlamaIndex, and Milvus","image":{"id":3943,"url":"https://assets.zilliz.com/July_09_Build_Better_Multimodal_RAG_Pipelines_with_Fifty_One_Llama_Index_and_Milvus_7f0138f574.png"},"display_time":"Jul 09, 2024","deploy_time":null,"url":"build-better-multimodal-rag-pipelines-with-fiftyone-llamaindex-and-milvus","abstract":"Enhance the capabilities of multimodal systems by efficiently leveraging text and visual data for improved data retrieval and context-rich responses.","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":158,"name":"Denis Kuria","author_tags":"Freelance Technical Writer","published_at":"2024-05-01T00:39:32.350Z","created_by":18,"updated_by":18,"created_at":"2024-05-01T00:39:30.888Z","updated_at":"2024-07-03T06:50:56.660Z","home_page":null,"home_page_link":null,"self_intro":"Denis is a machine learning engineer who enjoys writing guides to help other developers. He has a bachelor's in computer science and loves hiking and exploring the world.\n","repost_to_medium":null,"repost_state":null,"meta_description":"Denis Kuria is a freelance technical writer at Zilliz. ","locale":"en"}],"read_time":8,"localizations":[{"id":1093,"locale":"ja-JP","published_at":"2024-07-10T07:14:41.837Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/July_09_Build_Better_Multimodal_RAG_Pipelines_with_Fifty_One_Llama_Index_and_Milvus_7f0138f574.png","belong":"blog","authorNames":["Denis Kuria"]},{"id":"blog-477","title":"Safeguarding Data Integrity: On-Prem RAG Deployment with LLMware and Milvus ","image":{"id":4125,"url":"https://assets.zilliz.com/July_10_Safeguarding_Data_Integrity_On_Prem_RAG_Deployment_with_LL_Mware_and_Milvus_1526dbab51.png"},"display_time":"Jul 09, 2024","deploy_time":null,"url":"safeguard-data-integrity-on-prem-rag-deployment-with-llmware-and-milvus","abstract":"Using LLMware and the Milvus vector database, we can combine the power of vector similarity search and LLMs to ask questions on our private documents.","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":118,"name":" Haziqa Sajid","author_tags":"Freelance Technical Writer","published_at":"2024-03-12T10:25:34.265Z","created_by":18,"updated_by":18,"created_at":"2024-03-12T10:25:31.148Z","updated_at":"2024-07-03T07:58:27.010Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/haziqa-sajid-22b53245/","self_intro":"Digital Storytelling for Data, AI, B2B \u0026 SaaS","repost_to_medium":null,"repost_state":null,"meta_description":" Haziqa Sajid, Freelance Technical Writer","locale":"en"}],"read_time":12,"localizations":[{"id":1232,"locale":"ja-JP","published_at":"2024-07-10T12:22:37.344Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/July_10_Safeguarding_Data_Integrity_On_Prem_RAG_Deployment_with_LL_Mware_and_Milvus_1526dbab51.png","belong":"blog","authorNames":[" Haziqa Sajid"]},{"id":"blog-479","title":"Getting Started with LLMOps: Building Better AI Applications","image":{"id":3948,"url":"https://assets.zilliz.com/June_04_Exploring_LLM_Ops_Building_Better_AI_Applications_9baf4ac245.png"},"display_time":"Jul 08, 2024","deploy_time":null,"url":"get-started-with-llmops-build-better-ai-applications","abstract":"LLMOps stands for Large Language Model Operations, which are analogous to MLOps but specifically for large language models (LLMs). ","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":150,"name":"Tim Mugabi","author_tags":"Freelance Technical Writer","published_at":"2024-04-24T21:23:34.511Z","created_by":18,"updated_by":18,"created_at":"2024-04-24T21:23:32.810Z","updated_at":"2024-07-03T07:49:21.138Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Tim Mugabi, Freelance Technical Writer","locale":"en"}],"read_time":12,"localizations":[{"id":913,"locale":"ja-JP","published_at":"2024-07-10T09:47:49.427Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/June_04_Exploring_LLM_Ops_Building_Better_AI_Applications_9baf4ac245.png","belong":"blog","authorNames":["Tim Mugabi"]},{"id":"blog-481","title":"Infrastructure Challenges in Scaling RAG with Custom AI Models","image":{"id":3957,"url":"https://assets.zilliz.com/July_09_Infrastructure_Challenges_in_Scaling_RAG_with_Custom_AI_Models_Read_blog_59e73117ac.png"},"display_time":"Jul 06, 2024","deploy_time":null,"url":"infrastructure-challenges-in-scaling-rag-with-custom-ai-models","abstract":"Retrieval Augmented Generation (RAG) systems have significantly enhanced AI applications by providing more accurate and contextually relevant responses. However, scaling and deploying these systems in production have presented considerable challenges as they become more sophisticated and incorporate custom AI models.","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":154,"name":"Uppu Rajesh Kumar","author_tags":"Freelance Technical Writer","published_at":"2024-04-24T21:25:45.408Z","created_by":18,"updated_by":18,"created_at":"2024-04-24T21:25:43.983Z","updated_at":"2024-07-03T07:48:29.764Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Uppu Rajesh Kumar, Freelance Technical Writer","locale":"en"}],"read_time":17,"localizations":[{"id":1644,"locale":"de","published_at":"2024-07-10T17:32:50.136Z"},{"id":1647,"locale":"es","published_at":"2024-07-10T17:32:50.136Z"},{"id":1662,"locale":"fr","published_at":"2024-07-10T17:32:50.136Z"},{"id":1659,"locale":"it","published_at":"2024-07-10T17:32:50.136Z"},{"id":1650,"locale":"pt","published_at":"2024-07-10T17:32:50.136Z"},{"id":1653,"locale":"ru","published_at":"2024-07-10T17:32:50.136Z"},{"id":1656,"locale":"ko","published_at":"2024-07-10T17:32:50.136Z"},{"id":1070,"locale":"ja-JP","published_at":"2024-07-10T17:32:50.136Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/July_09_Infrastructure_Challenges_in_Scaling_RAG_with_Custom_AI_Models_Read_blog_59e73117ac.png","belong":"blog","authorNames":["Uppu Rajesh Kumar"]},{"id":"blog-480","title":"Building an End-to-End GenAI App with Ruby and Milvus ","image":{"id":3956,"url":"https://assets.zilliz.com/July_09_Building_an_End_to_End_Gen_AI_App_with_Ruby_and_Milvus_29beef6c93.png"},"display_time":"Jul 05, 2024","deploy_time":null,"url":"build-end-to-end-genai-app-with-ruby-and-milvus","abstract":"LangChain.rb eliminates the hassle of full-stack developers switching to another programming language when they want to leverage LLMs in their web applications.","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":125,"name":"Ruben Winastwan","author_tags":"Freelance Technical Writer","published_at":"2024-03-26T09:16:27.310Z","created_by":18,"updated_by":18,"created_at":"2024-03-26T09:16:24.498Z","updated_at":"2024-07-03T07:56:29.256Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Ruben Winastwan, Freelance Technical Writer","locale":"en"}],"read_time":13,"localizations":[{"id":1035,"locale":"ja-JP","published_at":"2024-07-10T12:05:10.557Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/July_09_Building_an_End_to_End_Gen_AI_App_with_Ruby_and_Milvus_29beef6c93.png","belong":"blog","authorNames":["Ruben Winastwan"]},{"id":"blog-484","title":"Metrics-Driven Development of RAGs","image":{"id":3969,"url":"https://assets.zilliz.com/Metrics_Driven_Development_of_RA_Gs_1_2fdfff2810.png"},"display_time":"Jul 04, 2024","deploy_time":null,"url":"metrics-driven-development-of-rags","abstract":"Evaluating and improving Retrieval-Augmented Generation (RAG) systems is a nuanced but essential task in the realm of AI-driven information retrieval. By leveraging a metrics-driven approach, as demonstrated by Jithin James and Shahul Es, you can systematically refine your RAG systems to ensure they deliver accurate, relevant, and trustworthy information.\n","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":158,"name":"Denis Kuria","author_tags":"Freelance Technical Writer","published_at":"2024-05-01T00:39:32.350Z","created_by":18,"updated_by":18,"created_at":"2024-05-01T00:39:30.888Z","updated_at":"2024-07-03T06:50:56.660Z","home_page":null,"home_page_link":null,"self_intro":"Denis is a machine learning engineer who enjoys writing guides to help other developers. He has a bachelor's in computer science and loves hiking and exploring the world.\n","repost_to_medium":null,"repost_state":null,"meta_description":"Denis Kuria is a freelance technical writer at Zilliz. ","locale":"en"}],"read_time":11,"localizations":[{"id":1328,"locale":"ja-JP","published_at":"2024-07-12T00:26:35.205Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Metrics_Driven_Development_of_RA_Gs_1_2fdfff2810.png","belong":"blog","authorNames":["Denis Kuria"]},{"id":"blog-476","title":"Exploring Three Key Strategies for Building Efficient Retrieval Augmented Generation (RAG) ","image":{"id":3973,"url":"https://assets.zilliz.com/July_10_Exploring_Retrieval_Augmented_Generation_RAG_Chunking_LL_Ms_and_Evaluations_9068b59753.png"},"display_time":"Jul 03, 2024","deploy_time":null,"url":"exploring-rag-chunking-llms-and-evaluations","abstract":"Three key strategies to get the most out of RAG: smart text chunking, iterating on different embedding models, and experimenting with different LLMs\n","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":94,"name":"Christy Bergman","author_tags":"Developer Advocate","published_at":"2023-10-06T00:29:45.486Z","created_by":18,"updated_by":18,"created_at":"2023-10-06T00:29:30.751Z","updated_at":"2024-07-18T16:01:45.942Z","home_page":null,"home_page_link":null,"self_intro":"Christy Bergman is a passionate Developer Advocate at Zilliz. She previously worked in distributed computing at Anyscale and as a Specialist AI/ML Solutions Architect at AWS. Christy studied applied math, is a self-taught coder, and has published papers, including one with ACM Recsys. She enjoys hiking and bird watching.","repost_to_medium":null,"repost_state":null,"meta_description":"Christy Bergman is a passionate Developer Advocate at Zilliz. ","locale":"en"}],"read_time":5,"localizations":[{"id":1060,"locale":"ja-JP","published_at":"2024-07-03T20:53:19.511Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/July_10_Exploring_Retrieval_Augmented_Generation_RAG_Chunking_LL_Ms_and_Evaluations_9068b59753.png","belong":"blog","authorNames":["Christy Bergman"]},{"id":"blog-245","title":"Getting Started with Pgvector: A Guide for Developers Exploring Vector Databases","image":{"id":1769,"url":"https://assets.zilliz.com/Getting_Started_Pgvector_Guide_for_Developers_Exploring_Vector_Databases_7927544fd3.png"},"display_time":"Jul 01, 2024","deploy_time":null,"url":"getting-started-pgvector-guide-developers-exploring-vector-databases","abstract":"Equipping you with the knowledge you need to get started with Pgvector and explore other vector databases as an alternative.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":83,"name":"Siddhant Varma","author_tags":"JavaScript developer","published_at":"2023-09-14T14:14:23.644Z","created_by":18,"updated_by":18,"created_at":"2023-09-14T14:14:17.983Z","updated_at":"2023-09-14T14:14:23.664Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/siddhantvarma99/","self_intro":"Siddhant is a full-stack JavaScript developer with expertise in front-end engineering. He’s worked with scaling multiple startups in India and has experience building products in the Ed-Tech and healthcare industries. Siddhant has a passion for teaching and a knack for writing. He's also taught programming to many graduates, helping them become better future developers.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":11,"localizations":[{"id":1534,"locale":"pt","published_at":"2023-09-15T04:21:55.260Z"},{"id":1480,"locale":"de","published_at":"2023-09-15T04:21:55.260Z"},{"id":1615,"locale":"it","published_at":"2023-09-15T04:21:55.260Z"},{"id":1561,"locale":"ru","published_at":"2023-09-15T04:21:55.260Z"},{"id":1642,"locale":"fr","published_at":"2023-09-15T04:21:55.260Z"},{"id":1588,"locale":"ko","published_at":"2023-09-15T04:21:55.260Z"},{"id":1507,"locale":"es","published_at":"2023-09-15T04:21:55.260Z"},{"id":1389,"locale":"ja-JP","published_at":"2023-09-15T04:21:55.260Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Getting_Started_Pgvector_Guide_for_Developers_Exploring_Vector_Databases_7927544fd3.png","belong":"blog","authorNames":["Siddhant Varma"]},{"id":"blog-475","title":"Building RAG with Self-Deployed Milvus Vector Database and Snowpark Container Services","image":{"id":4462,"url":"https://assets.zilliz.com/July_02_Building_RAG_with_Self_Deployed_Milvus_Vector_Database_and_Snowpark_Container_Services_0b3713071e.png"},"display_time":"Jun 28, 2024","deploy_time":null,"url":"build-rag-with-self-deployed-milvus-vector-database-and-snowpark-container-service","abstract":"With Snowflake's Snowpark Container Service (SPCS), users can now run Milvus within the Snowflake ecosystem, allowing them to easily interact with Milvus using data stored in Snowflake.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":125,"name":"Ruben Winastwan","author_tags":"Freelance Technical Writer","published_at":"2024-03-26T09:16:27.310Z","created_by":18,"updated_by":18,"created_at":"2024-03-26T09:16:24.498Z","updated_at":"2024-07-03T07:56:29.256Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Ruben Winastwan, Freelance Technical Writer","locale":"en"}],"read_time":15,"localizations":[{"id":832,"locale":"ja-JP","published_at":"2024-06-28T04:11:29.496Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/July_02_Building_RAG_with_Self_Deployed_Milvus_Vector_Database_and_Snowpark_Container_Services_0b3713071e.png","belong":"blog","authorNames":["Ruben Winastwan"]},{"id":"blog-474","title":"A Review of Hybrid Search in Milvus","image":{"id":3882,"url":"https://assets.zilliz.com/A_Review_of_Hybrid_Search_in_Milvus_e0afd3cfbe.png"},"display_time":"Jun 27, 2024","deploy_time":null,"url":"a-review-of-hybrid-search-in-milvus","abstract":"Hybrid search allows for combining multimodal search, hybrid sparse and dense search, and hybrid dense and full-text search. ","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":157,"name":"Ken Zhang","author_tags":"Senior Product Manager","published_at":"2024-04-29T11:13:18.206Z","created_by":18,"updated_by":18,"created_at":"2024-04-29T03:36:01.335Z","updated_at":"2024-07-03T07:47:25.978Z","home_page":null,"home_page_link":null,"self_intro":"Ken Zhang is a Senior Product Manager at Zilliz, leading the development of the Milvus vector database by setting its strategic direction and key features. Prior to Zilliz, he served as a kernel engineer at SAP HANA and enhanced his product management skills at PingCAP. Ken holds a master's degree from Fudan University and has over eight years of experience specializing in database development and big data infrastructure management.","repost_to_medium":null,"repost_state":null,"meta_description":"Ken Zhang is a Senior Product Manager at Zilliz","locale":"en"}],"read_time":8,"localizations":[{"id":1295,"locale":"ja-JP","published_at":"2024-06-28T03:38:35.092Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/A_Review_of_Hybrid_Search_in_Milvus_e0afd3cfbe.png","belong":"blog","authorNames":["Ken Zhang"]},{"id":"learn-80","title":"Evaluating Your Embedding Model","image":{"id":2646,"url":"https://assets.zilliz.com/Introduction_to_Evaluating_your_Embedding_Models_be01b1e99a.png"},"display_time":"Jun 26, 2024","url":"evaluating-your-embedding-model","abstract":"We'll review some key considerations for selecting a model and a practical example of using Arize Pheonix and RAGAS to evaluate different text embedding models.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":3,"name":"Frank Liu","author_tags":"Director of Operations \u0026 ML Architect at Zilliz","published_at":"2021-12-23T11:08:08.015Z","created_by":18,"updated_by":18,"created_at":"2021-12-23T10:40:59.821Z","updated_at":"2023-04-21T22:30:10.416Z","home_page":"GitHub","home_page_link":"https://github.com/fzliu","self_intro":"Frank Liu is the Director of Operations \u0026 ML Architect at Zilliz, where he serves as a maintainer for the Towhee open-source project. Prior to Zilliz, Frank co-founded Orion Innovations, an ML-powered indoor positioning startup based in Shanghai and worked as an ML engineer at Yahoo in San Francisco. In his free time, Frank enjoys playing chess, swimming, and powerlifting. Frank holds MS and BS degrees in Electrical Engineering from Stanford University. ","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":8,"localizations":[{"id":456,"locale":"ja-JP","published_at":"2024-02-14T19:18:57.616Z"},{"id":513,"locale":"pt","published_at":"2024-02-14T19:18:57.616Z"},{"id":510,"locale":"es","published_at":"2024-02-14T19:18:57.616Z"},{"id":507,"locale":"de","published_at":"2024-02-14T19:18:57.616Z"},{"id":519,"locale":"ko","published_at":"2024-02-14T19:18:57.616Z"},{"id":516,"locale":"ru","published_at":"2024-02-14T19:18:57.616Z"},{"id":522,"locale":"it","published_at":"2024-02-14T19:18:57.616Z"},{"id":525,"locale":"fr","published_at":"2024-02-14T19:18:57.616Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Introduction_to_Evaluating_your_Embedding_Models_be01b1e99a.png","belong":"learn","authorNames":["Frank Liu"]},{"id":"blog-473","title":"Building Intelligent RAG Applications with LangServe, LangGraph, and Milvus","image":{"id":3865,"url":"https://assets.zilliz.com/June_24_Building_Intelligent_RAG_Applications_with_Lang_Serve_Lang_Graph_and_Milvus_29db4a5d23.png"},"display_time":"Jun 25, 2024","deploy_time":null,"url":"build-intelligent-rag-with-langserve-langgraph-and-milvus","abstract":"Build a RAG system using agents with LangServe, LangGraph, Llama 3, and Milvus. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":115,"name":"Stephen Batifol","author_tags":"Developer Advocate ","published_at":"2024-03-07T03:46:04.655Z","created_by":18,"updated_by":18,"created_at":"2024-03-07T03:46:02.457Z","updated_at":"2024-07-18T15:56:42.529Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/stephen-batifol/","self_intro":"Stephen Batifol is a Developer Advocate at Zilliz. He previously worked as a Machine Learning Engineer at Wolt, where he was working on the ML Platform and as a Data Scientist at Brevo. Stephen studied Computer Science and Artificial Intelligence. He enjoys dancing and surfing. \n","repost_to_medium":null,"repost_state":null,"meta_description":"Stephen Batifol is a Developer Advocate at Zilliz.","locale":"en"}],"read_time":4,"localizations":[{"id":1272,"locale":"ja-JP","published_at":"2024-06-28T03:06:21.324Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/June_24_Building_Intelligent_RAG_Applications_with_Lang_Serve_Lang_Graph_and_Milvus_29db4a5d23.png","belong":"blog","authorNames":["Stephen Batifol"]},{"id":"blog-472","title":"Processing streaming data in Kafka with Timeplus Proton","image":{"id":3855,"url":"https://assets.zilliz.com/June_24_Processing_streaming_data_in_Kafka_with_Timeplus_Proton_06e703c683.png"},"display_time":"Jun 24, 2024","deploy_time":null,"url":"processing-streaming-data-in-kafka-with-timeplus-proton","abstract":"Jove Zhong’s talk at the Seattle Unstructured Data Meetup was a masterclass in real-time data processing. From practical demos to deep dives into advanced concepts, Jove provided a comprehensive overview of how Timeplus and Kafka are shaping the future of data analytics. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":151,"name":"Fariba Laiq","author_tags":"Freelance Technical Writer","published_at":"2024-04-24T21:23:59.165Z","created_by":18,"updated_by":18,"created_at":"2024-04-24T21:23:57.717Z","updated_at":"2024-07-29T16:21:27.954Z","home_page":null,"home_page_link":null,"self_intro":"Description: Fariba Laiq is a freelance content writer at Zilliz. She has studied Computer Science, been a coding instructor, and published research papers in the domain of AI and cyber-security. She is passionate about learning more about LLMs and vector databases in the ever evolving era of AI. Along with technical skills, she is also a self-taught artist.","repost_to_medium":null,"repost_state":null,"meta_description":"Fariba Laiq, Freelance Technical Writer","locale":"en"}],"read_time":8,"localizations":[{"id":1320,"locale":"ja-JP","published_at":"2024-06-24T23:17:00.848Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/June_24_Processing_streaming_data_in_Kafka_with_Timeplus_Proton_06e703c683.png","belong":"blog","authorNames":["Fariba Laiq"]},{"id":"blog-470","title":"Generative AI for Creative Applications Using Storia Lab","image":{"id":3862,"url":"https://assets.zilliz.com/June_24_Generative_AI_for_Creative_Applications_using_Storia_Lab_1_53d39cc937.png"},"display_time":"Jun 23, 2024","deploy_time":null,"url":"generative-ai-for-creative-applications-using-storia-lab","abstract":"This post discusses how Storia AI generates and edits images through simple text prompts or clicks and how we can leverage Storia AI and Milvus to build multimodal RAG. ","tags":[{"id":1,"name":"Case Study","published_at":"2021-01-15T10:34:37.316Z","created_by":18,"updated_by":18,"created_at":"2021-01-15T10:34:34.857Z","updated_at":"2021-01-25T10:31:22.499Z","locale":"en"}],"authors":[{"id":158,"name":"Denis Kuria","author_tags":"Freelance Technical Writer","published_at":"2024-05-01T00:39:32.350Z","created_by":18,"updated_by":18,"created_at":"2024-05-01T00:39:30.888Z","updated_at":"2024-07-03T06:50:56.660Z","home_page":null,"home_page_link":null,"self_intro":"Denis is a machine learning engineer who enjoys writing guides to help other developers. He has a bachelor's in computer science and loves hiking and exploring the world.\n","repost_to_medium":null,"repost_state":null,"meta_description":"Denis Kuria is a freelance technical writer at Zilliz. ","locale":"en"}],"read_time":6,"localizations":[{"id":1073,"locale":"ja-JP","published_at":"2024-06-24T10:02:16.986Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/June_24_Generative_AI_for_Creative_Applications_using_Storia_Lab_1_53d39cc937.png","belong":"blog","authorNames":["Denis Kuria"]},{"id":"blog-471","title":"Multilingual Narrative Tracking in the News","image":{"id":3853,"url":"https://assets.zilliz.com/June_14_Multi_lingual_narrative_tracking_in_the_news_real_time_experiments_97247d0270.png"},"display_time":"Jun 22, 2024","deploy_time":null,"url":"multilingual-narrative-tracking-in-the-news","abstract":"Recapping Robert Caulk's meetup talk, discussing the need and ways to track different narratives of news articles, using embedding models, LLMs, and Milvus. ","tags":[{"id":1,"name":"Case Study","published_at":"2021-01-15T10:34:37.316Z","created_by":18,"updated_by":18,"created_at":"2021-01-15T10:34:34.857Z","updated_at":"2021-01-25T10:31:22.499Z","locale":"en"}],"authors":[{"id":147,"name":"ShriVarsheni R","author_tags":"Freelance Technical Writer","published_at":"2024-04-24T21:21:57.571Z","created_by":18,"updated_by":18,"created_at":"2024-04-24T21:21:55.818Z","updated_at":"2024-07-03T07:50:17.617Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"ShriVarsheni, Freelance Technical Writer","locale":"en"}],"read_time":6,"localizations":[{"id":1088,"locale":"ja-JP","published_at":"2024-06-24T12:49:02.653Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/June_14_Multi_lingual_narrative_tracking_in_the_news_real_time_experiments_97247d0270.png","belong":"blog","authorNames":["ShriVarsheni R"]},{"id":"learn-140","title":"Harnessing Product Quantization for Memory Efficiency in Vector Databases","image":{"id":3844,"url":"https://assets.zilliz.com/May_27_Harnessing_Product_Quantization_for_Memory_Efficiency_in_Vector_Databases_e13a0a413c.png"},"display_time":"Jun 22, 2024","url":"harnessing-product-quantization-for-memory-efficiency-in-vector-databases","abstract":"Exploring product quantization's intricacies and practical implementation through hands-on examples.","tags":[{"id":39,"name":"VectorDB 101","published_at":"2022-09-30T05:56:34.554Z","created_by":18,"updated_by":18,"created_at":"2022-09-30T05:56:31.633Z","updated_at":"2024-07-10T07:12:04.155Z","locale":"en"}],"authors":[{"id":147,"name":"ShriVarsheni R","author_tags":"Freelance Technical Writer","published_at":"2024-04-24T21:21:57.571Z","created_by":18,"updated_by":18,"created_at":"2024-04-24T21:21:55.818Z","updated_at":"2024-07-03T07:50:17.617Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"ShriVarsheni, Freelance Technical Writer","locale":"en"}],"read_time":7,"localizations":[{"id":361,"locale":"ja-JP","published_at":"2024-06-24T10:19:01.210Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/May_27_Harnessing_Product_Quantization_for_Memory_Efficiency_in_Vector_Databases_e13a0a413c.png","belong":"learn","authorNames":["ShriVarsheni R"]},{"id":"blog-468","title":"Decoding LLM Hallucinations: A Deep Dive into Language Model Errors","image":{"id":3810,"url":"https://assets.zilliz.com/June_14_Decoding_LLM_Hallucinations_A_Deep_Dive_into_Language_Model_Errors_6c3e600903.png"},"display_time":"Jun 21, 2024","deploy_time":null,"url":"decoding-llm-hallucinations-deep-dive-into-llm-errors","abstract":"This post explores the concept of hallucinations and their potential triggers. Additionally, we introduced four practical methods for detecting hallucinations: self-evaluation, reference-based methods, uncertainty-based methods, and consistency-based detection. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":148,"name":"Abhiram Sharma","author_tags":"Freelance Technical Writer","published_at":"2024-04-24T21:22:31.512Z","created_by":18,"updated_by":18,"created_at":"2024-04-24T21:22:30.072Z","updated_at":"2024-07-03T07:50:07.544Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Abhiram Sharma, Freelance Technical Writer","locale":"en"}],"read_time":8,"localizations":[{"id":1317,"locale":"ja-JP","published_at":"2024-06-21T23:53:11.009Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/June_14_Decoding_LLM_Hallucinations_A_Deep_Dive_into_Language_Model_Errors_6c3e600903.png","belong":"blog","authorNames":["Abhiram Sharma"]},{"id":"blog-469","title":"Introduction to LLM Customization","image":{"id":3822,"url":"https://assets.zilliz.com/June_14_Introduction_to_LLM_Customization_fc05c3d087.png"},"display_time":"Jun 20, 2024","deploy_time":null,"url":"introduction-to-llm-customization","abstract":"This article discusses several options for customizing LLMs to enhance their performance on specific tasks. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":125,"name":"Ruben Winastwan","author_tags":"Freelance Technical Writer","published_at":"2024-03-26T09:16:27.310Z","created_by":18,"updated_by":18,"created_at":"2024-03-26T09:16:24.498Z","updated_at":"2024-07-03T07:56:29.256Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Ruben Winastwan, Freelance Technical Writer","locale":"en"}],"read_time":8,"localizations":[{"id":1049,"locale":"ja-JP","published_at":"2024-06-22T00:06:39.956Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/June_14_Introduction_to_LLM_Customization_fc05c3d087.png","belong":"blog","authorNames":["Ruben Winastwan"]},{"id":"blog-464","title":"Clearing Up Misconceptions about Data Insertion Speed in Milvus ","image":{"id":3766,"url":"https://assets.zilliz.com/June_14_Clearing_Up_Misconceptions_about_Data_Insertion_Speed_in_Milvus_45a5278d5f.png"},"display_time":"Jun 18, 2024","deploy_time":null,"url":"clear-up-misconceptions-about-data-insertion-speed-in-milvus","abstract":"Around 97% of the \"Milvus insert\" time in LangChain or LlamaIndex is spent on embedding generation, while about 3% on the actual database insertion step.\n","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":94,"name":"Christy Bergman","author_tags":"Developer Advocate","published_at":"2023-10-06T00:29:45.486Z","created_by":18,"updated_by":18,"created_at":"2023-10-06T00:29:30.751Z","updated_at":"2024-07-18T16:01:45.942Z","home_page":null,"home_page_link":null,"self_intro":"Christy Bergman is a passionate Developer Advocate at Zilliz. She previously worked in distributed computing at Anyscale and as a Specialist AI/ML Solutions Architect at AWS. Christy studied applied math, is a self-taught coder, and has published papers, including one with ACM Recsys. She enjoys hiking and bird watching.","repost_to_medium":null,"repost_state":null,"meta_description":"Christy Bergman is a passionate Developer Advocate at Zilliz. ","locale":"en"}],"read_time":4,"localizations":[{"id":1090,"locale":"ja-JP","published_at":"2024-06-21T06:43:23.021Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/June_14_Clearing_Up_Misconceptions_about_Data_Insertion_Speed_in_Milvus_45a5278d5f.png","belong":"blog","authorNames":["Christy Bergman"]},{"id":"blog-467","title":"Full RAG: A Modern Architecture for Hyperpersonalization","image":{"id":3784,"url":"https://assets.zilliz.com/Full_RAG_A_Modern_Architecture_for_Hyper_personalization_366eba84f7.png"},"display_time":"Jun 17, 2024","deploy_time":null,"url":"full-rag-modern-architecture-for-hyperpersonalization","abstract":"Mike Del Balso, CEO and Co-founder of Tecton delivered a talk on using the RAG architecture to improve the personalization of AI Recommendation engines at the Unstructured Data Meetup hosted by Zilliz. \n","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":155,"name":"Abdelrahman Elgendy","author_tags":"Freelancer Technical Writer","published_at":"2024-04-24T21:29:55.865Z","created_by":18,"updated_by":18,"created_at":"2024-04-24T21:29:54.451Z","updated_at":"2024-07-03T07:48:12.043Z","home_page":null,"home_page_link":null,"self_intro":"A passionate technical writer who enjoys demystifying AI and machine learning concepts, making them accessible to everyone.\n","repost_to_medium":null,"repost_state":null,"meta_description":"Abdelrahman Elgendy, Freelancer Technical Writer","locale":"en"}],"read_time":7,"localizations":[{"id":1319,"locale":"ja-JP","published_at":"2024-06-20T21:57:27.347Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Full_RAG_A_Modern_Architecture_for_Hyper_personalization_366eba84f7.png","belong":"blog","authorNames":["Abdelrahman Elgendy"]},{"id":"blog-462","title":"🚀 What’s New with Metadata Filtering in Milvus v2.4.3","image":{"id":3765,"url":"https://assets.zilliz.com/Metadata_Filtering_1_4284460ef0.png"},"display_time":"Jun 16, 2024","deploy_time":null,"url":"what-is-new-with-metadata-filtering-in-milvus","abstract":"Milvus introduced powerful string metadata matching! Now, you can match strings using prefix, postfix, infix, and even fuzzy searches. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":94,"name":"Christy Bergman","author_tags":"Developer Advocate","published_at":"2023-10-06T00:29:45.486Z","created_by":18,"updated_by":18,"created_at":"2023-10-06T00:29:30.751Z","updated_at":"2024-07-18T16:01:45.942Z","home_page":null,"home_page_link":null,"self_intro":"Christy Bergman is a passionate Developer Advocate at Zilliz. She previously worked in distributed computing at Anyscale and as a Specialist AI/ML Solutions Architect at AWS. Christy studied applied math, is a self-taught coder, and has published papers, including one with ACM Recsys. She enjoys hiking and bird watching.","repost_to_medium":null,"repost_state":null,"meta_description":"Christy Bergman is a passionate Developer Advocate at Zilliz. ","locale":"en"}],"read_time":3,"localizations":[{"id":1324,"locale":"ja-JP","published_at":"2024-06-17T07:10:02.137Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Metadata_Filtering_1_4284460ef0.png","belong":"blog","authorNames":["Christy Bergman"]},{"id":"blog-466","title":"Copilot Workspace: What It Is, How It Works, Why It Matters","image":{"id":3777,"url":"https://assets.zilliz.com/June_14_Copilot_Workspace_What_It_Is_How_It_Works_Why_It_Matters_7c4941acda.png"},"display_time":"Jun 15, 2024","deploy_time":null,"url":"what-is-copilot-workspace-and-why-it-matters","abstract":"The presentation by Idan Gazit and Cole Bemis illuminates the potential of the GitHub Copilot Workspace. This dev environment represents a significant step in streamlining complicated software development like RAG, enhancing productivity by allowing for task-to-code development workflow using generative AI. \n","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":158,"name":"Denis Kuria","author_tags":"Freelance Technical Writer","published_at":"2024-05-01T00:39:32.350Z","created_by":18,"updated_by":18,"created_at":"2024-05-01T00:39:30.888Z","updated_at":"2024-07-03T06:50:56.660Z","home_page":null,"home_page_link":null,"self_intro":"Denis is a machine learning engineer who enjoys writing guides to help other developers. He has a bachelor's in computer science and loves hiking and exploring the world.\n","repost_to_medium":null,"repost_state":null,"meta_description":"Denis Kuria is a freelance technical writer at Zilliz. ","locale":"en"}],"read_time":6,"localizations":[{"id":1310,"locale":"ja-JP","published_at":"2024-06-20T19:07:00.449Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/June_14_Copilot_Workspace_What_It_Is_How_It_Works_Why_It_Matters_7c4941acda.png","belong":"blog","authorNames":["Denis Kuria"]},{"id":"blog-463","title":"Local Agentic RAG with LangGraph and Llama 3.2","image":{"id":4610,"url":"https://assets.zilliz.com/June_14_Local_Agentic_RAG_with_Lang_Graph_and_Llama3_1_d2551cbdc6.png"},"display_time":"Jun 14, 2024","deploy_time":null,"url":"local-agentic-rag-with-langraph-and-llama3","abstract":"In this blog post, we show you how to build a RAG system using agents with LangChain/ LangGraph, Llama 3.2, and Milvus. \n","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":115,"name":"Stephen Batifol","author_tags":"Developer Advocate ","published_at":"2024-03-07T03:46:04.655Z","created_by":18,"updated_by":18,"created_at":"2024-03-07T03:46:02.457Z","updated_at":"2024-07-18T15:56:42.529Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/stephen-batifol/","self_intro":"Stephen Batifol is a Developer Advocate at Zilliz. He previously worked as a Machine Learning Engineer at Wolt, where he was working on the ML Platform and as a Data Scientist at Brevo. Stephen studied Computer Science and Artificial Intelligence. He enjoys dancing and surfing. \n","repost_to_medium":null,"repost_state":null,"meta_description":"Stephen Batifol is a Developer Advocate at Zilliz.","locale":"en"}],"read_time":9,"localizations":[{"id":824,"locale":"ja-JP","published_at":"2024-06-14T18:35:18.654Z"},{"id":1616,"locale":"fr","published_at":"2024-06-14T18:35:18.654Z"},{"id":1508,"locale":"pt","published_at":"2024-06-14T18:35:18.654Z"},{"id":1454,"locale":"de","published_at":"2024-06-14T18:35:18.654Z"},{"id":1562,"locale":"ko","published_at":"2024-06-14T18:35:18.654Z"},{"id":1535,"locale":"ru","published_at":"2024-06-14T18:35:18.654Z"},{"id":1481,"locale":"es","published_at":"2024-06-14T18:35:18.654Z"},{"id":1589,"locale":"it","published_at":"2024-06-14T18:35:18.654Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/June_14_Local_Agentic_RAG_with_Lang_Graph_and_Llama3_1_d2551cbdc6.png","belong":"blog","authorNames":["Stephen Batifol"]},{"id":"blog-461","title":"Voyage AI Embeddings and Rerankers for Search and RAG ","image":{"id":3750,"url":"https://assets.zilliz.com/Voyage_AI_Embeddings_and_Rerankers_for_Search_and_RAG_9b4987e76f.png"},"display_time":"Jun 14, 2024","deploy_time":null,"url":"voyage-ai-embeddings-and-rerankers-for-search-and-rag","abstract":"This article discussed the popular voyage AI embedding models and rerankers and their integration with Zilliz Cloud. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":118,"name":" Haziqa Sajid","author_tags":"Freelance Technical Writer","published_at":"2024-03-12T10:25:34.265Z","created_by":18,"updated_by":18,"created_at":"2024-03-12T10:25:31.148Z","updated_at":"2024-07-03T07:58:27.010Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/haziqa-sajid-22b53245/","self_intro":"Digital Storytelling for Data, AI, B2B \u0026 SaaS","repost_to_medium":null,"repost_state":null,"meta_description":" Haziqa Sajid, Freelance Technical Writer","locale":"en"}],"read_time":10,"localizations":[{"id":1056,"locale":"ja-JP","published_at":"2024-06-13T14:50:25.910Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Voyage_AI_Embeddings_and_Rerankers_for_Search_and_RAG_9b4987e76f.png","belong":"blog","authorNames":[" Haziqa Sajid"]},{"id":"blog-442","title":"How to Detect and Correct Logical Fallacies from GenAI Models","image":{"id":3703,"url":"https://assets.zilliz.com/How_to_Detect_and_Correct_Logical_Fallacies_from_Gen_AI_Models_0aefb26906.png"},"display_time":"Jun 13, 2024","deploy_time":null,"url":"how-to-detect-and-correct-logical-fallacies-from-genai-models","abstract":"Strategies for detecting and removing logical fallacies from LLMs","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":155,"name":"Abdelrahman Elgendy","author_tags":"Freelancer Technical Writer","published_at":"2024-04-24T21:29:55.865Z","created_by":18,"updated_by":18,"created_at":"2024-04-24T21:29:54.451Z","updated_at":"2024-07-03T07:48:12.043Z","home_page":null,"home_page_link":null,"self_intro":"A passionate technical writer who enjoys demystifying AI and machine learning concepts, making them accessible to everyone.\n","repost_to_medium":null,"repost_state":null,"meta_description":"Abdelrahman Elgendy, Freelancer Technical Writer","locale":"en"}],"read_time":6,"localizations":[{"id":1654,"locale":"ru","published_at":"2024-06-12T08:38:03.904Z"},{"id":1651,"locale":"pt","published_at":"2024-06-12T08:38:03.904Z"},{"id":1308,"locale":"ja-JP","published_at":"2024-06-12T08:38:03.904Z"},{"id":1645,"locale":"de","published_at":"2024-06-12T08:38:03.904Z"},{"id":1660,"locale":"it","published_at":"2024-06-12T08:38:03.904Z"},{"id":1648,"locale":"es","published_at":"2024-06-12T08:38:03.904Z"},{"id":1657,"locale":"ko","published_at":"2024-06-12T08:38:03.904Z"},{"id":1663,"locale":"fr","published_at":"2024-06-12T08:38:03.904Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/How_to_Detect_and_Correct_Logical_Fallacies_from_Gen_AI_Models_0aefb26906.png","belong":"blog","authorNames":["Abdelrahman Elgendy"]},{"id":"learn-208","title":"Image Embeddings for Enhanced Image Search: An In-depth Explainer","image":{"id":3807,"url":"https://assets.zilliz.com/June_06_Image_Embeddings_for_Enhanced_Image_Search_2_cb167b1fd7.png"},"display_time":"Jun 12, 2024","url":"image-embeddings-for-enhanced-image-search","abstract":"Image Embeddings are the core of modern computer vision algorithms. Understand their implementation and use cases and explore different image embedding models.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":118,"name":" Haziqa Sajid","author_tags":"Freelance Technical Writer","published_at":"2024-03-12T10:25:34.265Z","created_by":18,"updated_by":18,"created_at":"2024-03-12T10:25:31.148Z","updated_at":"2024-07-03T07:58:27.010Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/haziqa-sajid-22b53245/","self_intro":"Digital Storytelling for Data, AI, B2B \u0026 SaaS","repost_to_medium":null,"repost_state":null,"meta_description":" Haziqa Sajid, Freelance Technical Writer","locale":"en"}],"read_time":13,"localizations":[{"id":476,"locale":"ja-JP","published_at":"2024-06-12T08:18:50.675Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/June_06_Image_Embeddings_for_Enhanced_Image_Search_2_cb167b1fd7.png","belong":"learn","authorNames":[" Haziqa Sajid"]},{"id":"blog-441","title":"Using Vector Search to Better Understand Computer Vision Data","image":{"id":3704,"url":"https://assets.zilliz.com/June_12_Using_Vector_Search_to_Better_Understand_Computer_Vision_Data_ccd4bcd99d.png"},"display_time":"Jun 11, 2024","deploy_time":null,"url":"use-vector-search-to-better-understand-computer-vision-data","abstract":"How Vector Search improves your understanding of Computer Vision Data","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":143,"name":"Daniella Pontes","author_tags":"Freelance Technical Writer","published_at":"2024-04-19T03:52:05.346Z","created_by":18,"updated_by":18,"created_at":"2024-04-19T03:52:03.759Z","updated_at":"2024-07-03T07:58:01.528Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Daniella Pontes, Freelance Technical Writer","locale":"en"}],"read_time":6,"localizations":[{"id":1316,"locale":"ja-JP","published_at":"2024-06-11T12:29:34.115Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/June_12_Using_Vector_Search_to_Better_Understand_Computer_Vision_Data_ccd4bcd99d.png","belong":"blog","authorNames":["Daniella Pontes"]},{"id":"blog-440","title":"How Delivery Hero Implemented the Safety System for AI-Generated Images","image":{"id":3676,"url":"https://assets.zilliz.com/How_Delivery_Hero_Implemented_the_Safety_System_for_AI_Generated_Images_a183246d9e.png"},"display_time":"Jun 10, 2024","deploy_time":null,"url":"how-delivery-hero-implemented-safety-system-for-ai-generated-images","abstract":"This article discussed how Delivery Hero used AI models to generate high-quality food images to improve user experience and conversion rate. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":125,"name":"Ruben Winastwan","author_tags":"Freelance Technical Writer","published_at":"2024-03-26T09:16:27.310Z","created_by":18,"updated_by":18,"created_at":"2024-03-26T09:16:24.498Z","updated_at":"2024-07-03T07:56:29.256Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Ruben Winastwan, Freelance Technical Writer","locale":"en"}],"read_time":10,"localizations":[{"id":1301,"locale":"ja-JP","published_at":"2024-06-11T12:02:52.567Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/How_Delivery_Hero_Implemented_the_Safety_System_for_AI_Generated_Images_a183246d9e.png","belong":"blog","authorNames":["Ruben Winastwan"]},{"id":"blog-437","title":"Training Text Embeddings with Jina AI ","image":{"id":3656,"url":"https://assets.zilliz.com/June_07_Image_Embeddings_for_Enhanced_Image_Search_83fadfbc4e.png"},"display_time":"Jun 09, 2024","deploy_time":null,"url":"training-text-embeddings-with-jina-ai","abstract":"In a recent talk by Bo Wang, he discussed the creation of Jina text embeddings for modern vector search and RAG systems. He also shared methodologies for training embedding models that effectively encode extensive information, along with guidance o","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":158,"name":"Denis Kuria","author_tags":"Freelance Technical Writer","published_at":"2024-05-01T00:39:32.350Z","created_by":18,"updated_by":18,"created_at":"2024-05-01T00:39:30.888Z","updated_at":"2024-07-03T06:50:56.660Z","home_page":null,"home_page_link":null,"self_intro":"Denis is a machine learning engineer who enjoys writing guides to help other developers. He has a bachelor's in computer science and loves hiking and exploring the world.\n","repost_to_medium":null,"repost_state":null,"meta_description":"Denis Kuria is a freelance technical writer at Zilliz. ","locale":"en"}],"read_time":8,"localizations":[{"id":927,"locale":"ja-JP","published_at":"2024-06-10T21:42:57.899Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/June_07_Image_Embeddings_for_Enhanced_Image_Search_83fadfbc4e.png","belong":"blog","authorNames":["Denis Kuria"]},{"id":"blog-465","title":"Introduction to MemGPT and Its Integration with Milvus","image":{"id":3771,"url":"https://assets.zilliz.com/Introduction_to_Mem_GPT_and_Its_Integration_with_Milvus_fd9f70c984.png"},"display_time":"Jun 08, 2024","deploy_time":null,"url":"introduction-to-memgpt-and-milvus-integration","abstract":"Integrating the Milvus vector database and MemGPT has taken one step further in streamlining the development of AI Agents with connections to external data sources. In this post, we share an example demonstrating how to use this integration to build a chatbot with external memories. \n","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":118,"name":" Haziqa Sajid","author_tags":"Freelance Technical Writer","published_at":"2024-03-12T10:25:34.265Z","created_by":18,"updated_by":18,"created_at":"2024-03-12T10:25:31.148Z","updated_at":"2024-07-03T07:58:27.010Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/haziqa-sajid-22b53245/","self_intro":"Digital Storytelling for Data, AI, B2B \u0026 SaaS","repost_to_medium":null,"repost_state":null,"meta_description":" Haziqa Sajid, Freelance Technical Writer","locale":"en"}],"read_time":7,"localizations":[{"id":1304,"locale":"ja-JP","published_at":"2024-06-20T18:50:26.234Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Introduction_to_Mem_GPT_and_Its_Integration_with_Milvus_fd9f70c984.png","belong":"blog","authorNames":[" Haziqa Sajid"]},{"id":"blog-423","title":"How to Connect to Milvus Lite Using LangChain and LlamaIndex","image":{"id":3635,"url":"https://assets.zilliz.com/June_07_How_to_Connect_to_Milvus_Lite_Using_Lang_Chain_and_Llama_Index_08059bacd7.png"},"display_time":"Jun 07, 2024","deploy_time":null,"url":"how-to-connect-to-milvus-lite-using-langchain-and-llamaindex","abstract":"Milvus Lite is now the default method for third-party connectors like LangChain and LlamaIndex to connect to Milvus, the popular open-source vector database.\n","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":94,"name":"Christy Bergman","author_tags":"Developer Advocate","published_at":"2023-10-06T00:29:45.486Z","created_by":18,"updated_by":18,"created_at":"2023-10-06T00:29:30.751Z","updated_at":"2024-07-18T16:01:45.942Z","home_page":null,"home_page_link":null,"self_intro":"Christy Bergman is a passionate Developer Advocate at Zilliz. She previously worked in distributed computing at Anyscale and as a Specialist AI/ML Solutions Architect at AWS. Christy studied applied math, is a self-taught coder, and has published papers, including one with ACM Recsys. She enjoys hiking and bird watching.","repost_to_medium":null,"repost_state":null,"meta_description":"Christy Bergman is a passionate Developer Advocate at Zilliz. ","locale":"en"}],"read_time":4,"localizations":[{"id":1039,"locale":"ja-JP","published_at":"2024-06-07T23:15:03.754Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/June_07_How_to_Connect_to_Milvus_Lite_Using_Lang_Chain_and_Llama_Index_08059bacd7.png","belong":"blog","authorNames":["Christy Bergman"]},{"id":"blog-421","title":"Text as Data, From Anywhere to Anywhere","image":{"id":3628,"url":"https://assets.zilliz.com/June_06_Text_as_Data_From_Anywhere_to_Anywhere_fe5cad3a6c.png"},"display_time":"Jun 07, 2024","deploy_time":null,"url":"text-as-data-from-anywhere-to-anywhere","abstract":"Whether you prefer a no-code or minimal-code approach, Airbyte and PyAirbyte offer robust solutions for integrating both structured and unstructured data. AJ Steers' painted a good picture of the potential of these tools in revolutionizing data workflows.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":158,"name":"Denis Kuria","author_tags":"Freelance Technical Writer","published_at":"2024-05-01T00:39:32.350Z","created_by":18,"updated_by":18,"created_at":"2024-05-01T00:39:30.888Z","updated_at":"2024-07-03T06:50:56.660Z","home_page":null,"home_page_link":null,"self_intro":"Denis is a machine learning engineer who enjoys writing guides to help other developers. He has a bachelor's in computer science and loves hiking and exploring the world.\n","repost_to_medium":null,"repost_state":null,"meta_description":"Denis Kuria is a freelance technical writer at Zilliz. ","locale":"en"}],"read_time":9,"localizations":[{"id":1280,"locale":"ja-JP","published_at":"2024-06-07T18:44:05.726Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/June_06_Text_as_Data_From_Anywhere_to_Anywhere_fe5cad3a6c.png","belong":"blog","authorNames":["Denis Kuria"]},{"id":"blog-422","title":"Are CPUs Enough? A Review Of Vector Search Running On Novel Hardware","image":{"id":3631,"url":"https://assets.zilliz.com/June_06_Are_CP_Us_Enough_A_Review_Of_Vector_Search_Running_On_Novel_Hardware_f398bde05e.png"},"display_time":"Jun 06, 2024","deploy_time":null,"url":"are-cpus-enough-review-of-vector-search-running-on-novel-hardware","abstract":"The rapid advancements in hardware technology are paving the way for more efficient and powerful vector search capabilities. As illustrated by the NeurIPS BigANN competition and Zilliz's contributions, the intersection of advanced hardware and innovative algorithms is key to the future of data retrieval technologies.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":126,"name":"Antony G.","author_tags":"Freelance Technical Writer","published_at":"2024-03-26T09:18:07.767Z","created_by":18,"updated_by":18,"created_at":"2024-03-26T09:18:00.140Z","updated_at":"2024-07-03T07:56:19.123Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Antony G., Freelance Technical Writer","locale":"en"}],"read_time":5,"localizations":[{"id":842,"locale":"ja-JP","published_at":"2024-06-07T20:06:19.202Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/June_06_Are_CP_Us_Enough_A_Review_Of_Vector_Search_Running_On_Novel_Hardware_f398bde05e.png","belong":"blog","authorNames":["Antony G."]},{"id":"blog-419","title":"Expanding Our Reach: Zilliz Cloud Now Available in 11 Regions across 3 Major Cloud Providers","image":{"id":3627,"url":"https://assets.zilliz.com/June_06_Expanding_Our_Reach_Zilliz_Cloud_Now_Available_in_11_Regions_across_3_Major_Cloud_Providers_d304d69e4b.png"},"display_time":"Jun 05, 2024","deploy_time":null,"url":"zilliz-cloud-available-in-11-regions-across-3-major-cloud-providers","abstract":"This expansion means you can deploy Zilliz Cloud closer to where your users are, reducing latency and improving performance. ","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":76,"name":"Steffi Li","author_tags":"Director of Product Marketing","published_at":"2023-07-13T17:18:42.023Z","created_by":18,"updated_by":18,"created_at":"2023-07-13T17:16:54.449Z","updated_at":"2023-07-13T17:18:42.070Z","home_page":null,"home_page_link":null,"self_intro":"Steffi is the Director of Product Marketing at Zilliz, with prior experience leading the GTM strategies for open-source data technologies such as Apache Kafka and Apache Airflow. Passionate about travel, yoga, and non-fiction reading, she brings a balanced and enriched worldview to her professional pursuits.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":2,"localizations":[{"id":1144,"locale":"ja-JP","published_at":"2024-06-05T14:26:59.848Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/June_06_Expanding_Our_Reach_Zilliz_Cloud_Now_Available_in_11_Regions_across_3_Major_Cloud_Providers_d304d69e4b.png","belong":"blog","authorNames":["Steffi Li"]},{"id":"blog-417","title":"Building Advanced Retrieval Augmented Generation (RAG) Apps with LlamaIndex","image":{"id":3600,"url":"https://assets.zilliz.com/June_04_Advanced_Retrieval_Augmented_Generation_apps_with_Llama_Index_1_b9733e4651.png"},"display_time":"Jun 04, 2024","deploy_time":null,"url":"advanced-rag-apps-with-llamaindex","abstract":"Laurie’s presentation showcases basic and advanced application frameworks for RAG, which we can build with minimal lines of code using LlamaIndex. ","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":148,"name":"Abhiram Sharma","author_tags":"Freelance Technical Writer","published_at":"2024-04-24T21:22:31.512Z","created_by":18,"updated_by":18,"created_at":"2024-04-24T21:22:30.072Z","updated_at":"2024-07-03T07:50:07.544Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Abhiram Sharma, Freelance Technical Writer","locale":"en"}],"read_time":6,"localizations":[{"id":1247,"locale":"ja-JP","published_at":"2024-06-04T21:20:34.881Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/June_04_Advanced_Retrieval_Augmented_Generation_apps_with_Llama_Index_1_b9733e4651.png","belong":"blog","authorNames":["Abhiram Sharma"]},{"id":"blog-416","title":"Elevating User Experience with Image-based Fashion Recommendations ","image":{"id":3598,"url":"https://assets.zilliz.com/June_04_Elevating_User_Experience_with_Image_Based_Fashion_Recommendations_1_33de98719e.png"},"display_time":"Jun 04, 2024","deploy_time":null,"url":"elevating-user-experience-with-image-based-fashion-recommendations","abstract":"This article explores the concepts and architecture, highlighting how AI can transform the fashion industry. We'll begin by explaining visual embeddings, which are crucial for understanding the article. Next, we'll detail how Joan built and stored images in a vector database like Milvus. Finally, we'll outline the step-by-step process of how the model generates recommendations.\n","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":153,"name":"Mostafa Ibrahim","author_tags":"Freelance Technical Writer","published_at":"2024-04-24T21:25:21.361Z","created_by":18,"updated_by":18,"created_at":"2024-04-24T21:25:19.857Z","updated_at":"2024-07-03T06:51:28.798Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":5,"localizations":[{"id":1303,"locale":"ja-JP","published_at":"2024-06-04T18:50:51.485Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/June_04_Elevating_User_Experience_with_Image_Based_Fashion_Recommendations_1_33de98719e.png","belong":"blog","authorNames":["Mostafa Ibrahim"]},{"id":"learn-189","title":"An Introduction to Vector Embeddings: What They Are and How to Use Them ","image":{"id":3419,"url":"https://assets.zilliz.com/Everything_You_Should_Know_about_Vector_Embeddings_1_3d19f86ad2.png"},"display_time":"Jun 03, 2024","url":"everything-you-should-know-about-vector-embeddings","abstract":"In this blog post, we will understand the concept of vector embeddings and explore its applications, best practices, and tools for working with embeddings.\n","tags":[{"id":39,"name":"VectorDB 101","published_at":"2022-09-30T05:56:34.554Z","created_by":18,"updated_by":18,"created_at":"2022-09-30T05:56:31.633Z","updated_at":"2024-07-10T07:12:04.155Z","locale":"en"}],"authors":[{"id":118,"name":" Haziqa Sajid","author_tags":"Freelance Technical Writer","published_at":"2024-03-12T10:25:34.265Z","created_by":18,"updated_by":18,"created_at":"2024-03-12T10:25:31.148Z","updated_at":"2024-07-03T07:58:27.010Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/haziqa-sajid-22b53245/","self_intro":"Digital Storytelling for Data, AI, B2B \u0026 SaaS","repost_to_medium":null,"repost_state":null,"meta_description":" Haziqa Sajid, Freelance Technical Writer","locale":"en"}],"read_time":9,"localizations":[{"id":462,"locale":"ja-JP","published_at":"2024-06-04T21:18:17.494Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Everything_You_Should_Know_about_Vector_Embeddings_1_3d19f86ad2.png","belong":"learn","authorNames":[" Haziqa Sajid"]},{"id":"blog-418","title":"The Path to Production: LLM Application Evaluations and Observability","image":{"id":3612,"url":"https://assets.zilliz.com/June_04_Path_to_Production_LLM_System_Evaluations_and_Observability_995c581a7b.png"},"display_time":"Jun 02, 2024","deploy_time":null,"url":"path-to-production-llm-system-evaluations-and-observability","abstract":"A recap of Hakan Tekgul’s talk about LLM Evaluation and Troubleshooting at the SF Unstructured Data Meetup.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":45,"name":"Fendy Feng","author_tags":"Technical Marketing Writer","published_at":"2023-05-16T01:36:15.102Z","created_by":18,"updated_by":18,"created_at":"2023-05-16T00:04:12.065Z","updated_at":"2024-04-25T08:37:19.712Z","home_page":"GitHub","home_page_link":"https://www.linkedin.com/in/fendy311/","self_intro":"Fendy Feng is the Technical Marketing Writer at Zilliz. She has extensive experience developing and enhancing the impact of open-source projects in various global markets by producing high-quality, tailored content. Before joining Zilliz, Fendy worked as a Content Strategist at PingCAP, a fast-growing E-Series startup renowned for its open-source distributed SQL database.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":7,"localizations":[{"id":1225,"locale":"ja-JP","published_at":"2024-06-04T20:55:52.594Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/June_04_Path_to_Production_LLM_System_Evaluations_and_Observability_995c581a7b.png","belong":"blog","authorNames":["Fendy Feng"]},{"id":"blog-439","title":"Vector Search and RAG - Balancing Accuracy and Context","image":{"id":3705,"url":"https://assets.zilliz.com/June_12_Vector_Search_and_RAG_Balancing_Accuracy_and_Context_2f3cb3a936.png"},"display_time":"Jun 01, 2024","deploy_time":null,"url":"vector-search-and-rag-balancing-accuracy-and-context","abstract":"In this article, we cover AI Hallucinations and how RAG can help solve the issue. Christy demonstrated a great explanation of how building RAG requires careful choices of embedding models, indexes, and semantic search approaches. \n","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":155,"name":"Abdelrahman Elgendy","author_tags":"Freelancer Technical Writer","published_at":"2024-04-24T21:29:55.865Z","created_by":18,"updated_by":18,"created_at":"2024-04-24T21:29:54.451Z","updated_at":"2024-07-03T07:48:12.043Z","home_page":null,"home_page_link":null,"self_intro":"A passionate technical writer who enjoys demystifying AI and machine learning concepts, making them accessible to everyone.\n","repost_to_medium":null,"repost_state":null,"meta_description":"Abdelrahman Elgendy, Freelancer Technical Writer","locale":"en"}],"read_time":10,"localizations":[{"id":1281,"locale":"ja-JP","published_at":"2024-06-10T21:49:56.559Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/June_12_Vector_Search_and_RAG_Balancing_Accuracy_and_Context_2f3cb3a936.png","belong":"blog","authorNames":["Abdelrahman Elgendy"]},{"id":"blog-415","title":"Improving Behavior Science Experiments with LLMs and Milvus ","image":{"id":3591,"url":"https://assets.zilliz.com/May_30_Improving_Behavior_Science_Experiments_with_LL_Ms_and_Milvus_897009ae6e.png"},"display_time":"May 31, 2024","deploy_time":null,"url":"improve-behavior-science-experiments-with-llm-and-milvus","abstract":"this is a meetup recap blog covering how LLMs and Milvus help improve the results of behavior science experiments. ","tags":[{"id":1,"name":"Case Study","published_at":"2021-01-15T10:34:37.316Z","created_by":18,"updated_by":18,"created_at":"2021-01-15T10:34:34.857Z","updated_at":"2021-01-25T10:31:22.499Z","locale":"en"}],"authors":[{"id":143,"name":"Daniella Pontes","author_tags":"Freelance Technical Writer","published_at":"2024-04-19T03:52:05.346Z","created_by":18,"updated_by":18,"created_at":"2024-04-19T03:52:03.759Z","updated_at":"2024-07-03T07:58:01.528Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Daniella Pontes, Freelance Technical Writer","locale":"en"}],"read_time":7,"localizations":[{"id":1221,"locale":"ja-JP","published_at":"2024-05-30T12:35:11.995Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/May_30_Improving_Behavior_Science_Experiments_with_LL_Ms_and_Milvus_897009ae6e.png","belong":"blog","authorNames":["Daniella Pontes"]},{"id":"learn-206","title":"What Are Binary Embeddings? ","image":{"id":3581,"url":"https://assets.zilliz.com/May_29_What_are_binary_embeddings_da94bea180.png"},"display_time":"May 30, 2024","url":"what-are-binary-vector-embedding","abstract":"In this blog, we will introduce the concept of binary embeddings, delineating their defining characteristics, advantages, and comparative merits against other embedding types.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":158,"name":"Denis Kuria","author_tags":"Freelance Technical Writer","published_at":"2024-05-01T00:39:32.350Z","created_by":18,"updated_by":18,"created_at":"2024-05-01T00:39:30.888Z","updated_at":"2024-07-03T06:50:56.660Z","home_page":null,"home_page_link":null,"self_intro":"Denis is a machine learning engineer who enjoys writing guides to help other developers. He has a bachelor's in computer science and loves hiking and exploring the world.\n","repost_to_medium":null,"repost_state":null,"meta_description":"Denis Kuria is a freelance technical writer at Zilliz. ","locale":"en"}],"read_time":13,"localizations":[{"id":380,"locale":"ja-JP","published_at":"2024-05-30T11:55:51.577Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/May_29_What_are_binary_embeddings_da94bea180.png","belong":"learn","authorNames":["Denis Kuria"]},{"id":"blog-414","title":"Tim Spann: Why I Joined Zilliz","image":{"id":3572,"url":"https://assets.zilliz.com/Why_I_joined_Zilliz_Tim_3d5417bae5.png"},"display_time":"May 29, 2024","deploy_time":null,"url":"why-i-joined-zilliz-tim-spann","abstract":"Why Tim Spann Joined Zilliz","tags":[{"id":4,"name":"Company","published_at":"2021-01-21T02:28:23.551Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:20.676Z","updated_at":"2021-01-21T02:28:23.824Z","locale":"en"}],"authors":[{"id":164,"name":"Tim Spann","author_tags":"Principal Developer Advocate","published_at":"2024-05-29T06:54:05.034Z","created_by":18,"updated_by":18,"created_at":"2024-05-29T06:54:02.718Z","updated_at":"2024-07-18T15:55:19.267Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/timothyspann/","self_intro":"Tim Spann is a Principal Developer Advocate at Zilliz. ","repost_to_medium":null,"repost_state":null,"meta_description":"Tim Spann is the Principal Developer Advocate at Zilliz. ","locale":"en"}],"read_time":3,"localizations":[{"id":1130,"locale":"ja-JP","published_at":"2024-05-29T07:09:45.050Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Why_I_joined_Zilliz_Tim_3d5417bae5.png","belong":"blog","authorNames":["Tim Spann"]},{"id":"learn-207","title":"A Beginner's Guide to Website Chunking and Embedding for Your RAG Applications","image":{"id":3589,"url":"https://assets.zilliz.com/May_30_A_Beginner_s_Guide_to_Website_Chunking_and_Embedding_for_Your_RAG_Applications_d1ab794e02.png"},"display_time":"May 29, 2024","url":"beginner-guide-to-website-chunking-and-embedding-for-your-genai-applications","abstract":"In this post, we'll explain how to extract content from a website and use it as context for LLMs in a RAG application. However, before doing so, we need to understand website fundamentals.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":125,"name":"Ruben Winastwan","author_tags":"Freelance Technical Writer","published_at":"2024-03-26T09:16:27.310Z","created_by":18,"updated_by":18,"created_at":"2024-03-26T09:16:24.498Z","updated_at":"2024-07-03T07:56:29.256Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Ruben Winastwan, Freelance Technical Writer","locale":"en"}],"read_time":15,"localizations":[{"id":458,"locale":"ja-JP","published_at":"2024-05-30T12:22:45.976Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/May_30_A_Beginner_s_Guide_to_Website_Chunking_and_Embedding_for_Your_RAG_Applications_d1ab794e02.png","belong":"learn","authorNames":["Ruben Winastwan"]},{"id":"learn-205","title":"An Ultimate Guide to Vectorizing and Querying Structured Data","image":{"id":3573,"url":"https://assets.zilliz.com/May_27_Guide_to_Vectorizing_Structured_Data_b4977fcc8c.png"},"display_time":"May 28, 2024","url":"an-ultimate-guide-to-vectorizing-structured-data","abstract":"This guide explains why and when you should vectorize your structured data and walks you through vectorizing and querying structured data with Milvus from start to finish. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":154,"name":"Uppu Rajesh Kumar","author_tags":"Freelance Technical Writer","published_at":"2024-04-24T21:25:45.408Z","created_by":18,"updated_by":18,"created_at":"2024-04-24T21:25:43.983Z","updated_at":"2024-07-03T07:48:29.764Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Uppu Rajesh Kumar, Freelance Technical Writer","locale":"en"}],"read_time":21,"localizations":[{"id":368,"locale":"ja-JP","published_at":"2024-05-29T08:48:00.808Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/May_27_Guide_to_Vectorizing_Structured_Data_b4977fcc8c.png","belong":"learn","authorNames":["Uppu Rajesh Kumar"]},{"id":"learn-204","title":"Vectorizing and Querying EPUB Content with the Unstructured and Milvus","image":{"id":3570,"url":"https://assets.zilliz.com/May_27_Vectorizing_and_Querying_EPUB_Content_with_Milvus_10808ddb86.png"},"display_time":"May 27, 2024","url":"vectorize-and-query-epub-content-with-unstructured-and-milvus","abstract":"In this post, we explore the vectorization and retrieval of EPUB data using Milvus and the Unstructured framework, offering developers actionable insights for enhancing LLM performance.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":153,"name":"Mostafa Ibrahim","author_tags":"Freelance Technical Writer","published_at":"2024-04-24T21:25:21.361Z","created_by":18,"updated_by":18,"created_at":"2024-04-24T21:25:19.857Z","updated_at":"2024-07-03T06:51:28.798Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":10,"localizations":[{"id":459,"locale":"ja-JP","published_at":"2024-05-28T07:21:28.287Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/May_27_Vectorizing_and_Querying_EPUB_Content_with_Milvus_10808ddb86.png","belong":"learn","authorNames":["Mostafa Ibrahim"]},{"id":"blog-413","title":"How to Build a LangChain RAG Agent with Reporting","image":{"id":3564,"url":"https://assets.zilliz.com/Mar_09_How_to_Build_a_Lang_Chain_RAG_Agent_with_Reporting_d12abae24c.png"},"display_time":"May 24, 2024","deploy_time":null,"url":"how-to-build-a-langchain-rag-agent-with-reporting","abstract":"This tutorial discussed building an AI Agent that does RAG using LangChain. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":41,"name":"Yujian Tang","author_tags":"Developer Advocate at Zilliz","published_at":"2023-04-20T21:52:47.479Z","created_by":18,"updated_by":18,"created_at":"2023-04-20T21:52:45.859Z","updated_at":"2024-07-18T16:02:07.497Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/yujiantang/","self_intro":"Yujian Tang is a Developer Advocate at Zilliz. He has a background as a software engineer working on AutoML at Amazon. Yujian studied Computer Science, Statistics, and Neuroscience with research papers published to conferences including IEEE Big Data. He enjoys drinking bubble tea, spending time with family, and being near water.","repost_to_medium":null,"repost_state":null,"meta_description":"Yujian Tang, Developer Advocate at Zilliz. ","locale":"en"}],"read_time":7,"localizations":[{"id":1152,"locale":"ja-JP","published_at":"2024-05-24T00:50:46.125Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Mar_09_How_to_Build_a_Lang_Chain_RAG_Agent_with_Reporting_d12abae24c.png","belong":"blog","authorNames":["Yujian Tang"]},{"id":"learn-203","title":"Embedding and Querying Multilingual Languages with Milvus","image":{"id":3806,"url":"https://assets.zilliz.com/May_27_Embedding_and_Querying_Multilingual_Languages_with_Milvus_be285965b2.png"},"display_time":"May 23, 2024","url":"embedding-and-querying-multilingual-languages-with-milvus","abstract":"This guide will explore the challenges, strategies, and approaches to embedding multilingual languages into vector spaces using Milvus and the BGE-M3 multilingual embedding model. \n","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":158,"name":"Denis Kuria","author_tags":"Freelance Technical Writer","published_at":"2024-05-01T00:39:32.350Z","created_by":18,"updated_by":18,"created_at":"2024-05-01T00:39:30.888Z","updated_at":"2024-07-03T06:50:56.660Z","home_page":null,"home_page_link":null,"self_intro":"Denis is a machine learning engineer who enjoys writing guides to help other developers. He has a bachelor's in computer science and loves hiking and exploring the world.\n","repost_to_medium":null,"repost_state":null,"meta_description":"Denis Kuria is a freelance technical writer at Zilliz. ","locale":"en"}],"read_time":12,"localizations":[{"id":470,"locale":"ja-JP","published_at":"2024-05-23T21:17:32.616Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/May_27_Embedding_and_Querying_Multilingual_Languages_with_Milvus_be285965b2.png","belong":"learn","authorNames":["Denis Kuria"]},{"id":"blog-412","title":"Choosing the Right Embedding Model for Your Data","image":{"id":6524,"url":"https://assets.zilliz.com/May_21_Choosing_the_Right_Embedding_Model_for_Your_Data_e7b1251ae4.png"},"display_time":"May 22, 2024","deploy_time":null,"url":"choosing-the-right-embedding-model-for-your-data","abstract":"This blog touched on some popular embedding models used in RAG applications.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":94,"name":"Christy Bergman","author_tags":"Developer Advocate","published_at":"2023-10-06T00:29:45.486Z","created_by":18,"updated_by":18,"created_at":"2023-10-06T00:29:30.751Z","updated_at":"2024-07-18T16:01:45.942Z","home_page":null,"home_page_link":null,"self_intro":"Christy Bergman is a passionate Developer Advocate at Zilliz. She previously worked in distributed computing at Anyscale and as a Specialist AI/ML Solutions Architect at AWS. Christy studied applied math, is a self-taught coder, and has published papers, including one with ACM Recsys. She enjoys hiking and bird watching.","repost_to_medium":null,"repost_state":null,"meta_description":"Christy Bergman is a passionate Developer Advocate at Zilliz. ","locale":"en"}],"read_time":6,"localizations":[{"id":1540,"locale":"ru","published_at":"2024-05-24T00:10:35.815Z"},{"id":1621,"locale":"fr","published_at":"2024-05-24T00:10:35.815Z"},{"id":1567,"locale":"ko","published_at":"2024-05-24T00:10:35.815Z"},{"id":1459,"locale":"de","published_at":"2024-05-24T00:10:35.815Z"},{"id":925,"locale":"ja-JP","published_at":"2024-05-24T00:10:35.815Z"},{"id":1594,"locale":"it","published_at":"2024-05-24T00:10:35.815Z"},{"id":1513,"locale":"pt","published_at":"2024-05-24T00:10:35.815Z"},{"id":1486,"locale":"es","published_at":"2024-05-24T00:10:35.815Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/May_21_Choosing_the_Right_Embedding_Model_for_Your_Data_e7b1251ae4.png","belong":"blog","authorNames":["Christy Bergman"]},{"id":"learn-202","title":"Vectorizing JSON Data with Milvus for Similarity Search ","image":{"id":3552,"url":"https://assets.zilliz.com/Milvus_Reference_Architectures_f86ee6ff4e.png"},"display_time":"May 21, 2024","url":"vectorize-JSON-data-with-milvus-for-similarity-search","abstract":"This article explores how Milvus streamlines JSON data vectorization, ingestion, and similarity retrieval. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":132,"name":"Rahul ","author_tags":"Freelance Technical Writer","published_at":"2024-03-30T21:57:22.495Z","created_by":18,"updated_by":18,"created_at":"2024-03-30T21:57:19.140Z","updated_at":"2024-07-03T07:53:30.991Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Rahul, Freelance Technical Writer","locale":"en"},{"id":102,"name":"David Wang","author_tags":"Algorithm Engineer at Zilliz","published_at":"2023-10-27T08:41:57.519Z","created_by":18,"updated_by":18,"created_at":"2023-10-27T08:41:55.636Z","updated_at":"2024-04-16T02:43:37.282Z","home_page":"GitHub","home_page_link":"https://github.com/wxywb","self_intro":"David Wang, Algorithm Engineer at Zilliz, brings extensive expertise in computer vision and natural language processing. His contributions to advanced embedding algorithm research, including projects like Towhee and GPTCache, reflect his commitment to advancing AI technologies. Before joining Zilliz, he worked at Alibaba Cloud for large-scale object recognition and classification projects. David holds a Master's degree from Dalian University of Technology.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":8,"localizations":[{"id":421,"locale":"ja-JP","published_at":"2024-05-22T05:38:02.258Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Milvus_Reference_Architectures_f86ee6ff4e.png","belong":"learn","authorNames":["Rahul ","David Wang"]},{"id":"blog-411","title":"Approximate Nearest Neighbor Search in Recommender Systems","image":{"id":3541,"url":"https://assets.zilliz.com/Approximate_Nearest_Neighbor_Search_in_Recommender_Systems_55ea789dfc.png"},"display_time":"May 20, 2024","deploy_time":null,"url":"approximate-nearest-neighbor-search-in-recommender-systems","abstract":"ANN search is already integrated into the production stacks of the world’s most popular tools. Yury helps us understand the key concepts and background that have driven ANN’s adoption in large-scale recommender systems. \n","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":137,"name":"Tyler Falcon","author_tags":"Digital Marketing Manager at Zilliz. ","published_at":"2024-04-01T19:01:39.023Z","created_by":18,"updated_by":18,"created_at":"2024-04-01T19:01:37.126Z","updated_at":"2024-07-03T06:55:28.378Z","home_page":null,"home_page_link":null,"self_intro":"Tyler Falconis the Digital Marketing Manager at Zilliz. ","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":9,"localizations":[{"id":1114,"locale":"ja-JP","published_at":"2024-05-20T19:00:45.244Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Approximate_Nearest_Neighbor_Search_in_Recommender_Systems_55ea789dfc.png","belong":"blog","authorNames":["Tyler Falcon"]},{"id":"learn-201","title":"Scaling Vector Databases to Meet Enterprise Demands","image":{"id":3567,"url":"https://assets.zilliz.com/May_21_Scaling_Vector_Databases_for_Enterprise_Demands_4bc33c5aa6.png"},"display_time":"May 19, 2024","url":"scaling-vector-databases-to-meet-enterprise-demands","abstract":"In this blog, we will explore the concept of database scalability and unravel Milvus's scaling capability. We will also introduce its scalability techniques and explore how they pave the way for unparalleled performance and innovation in unstructured data management.\n","tags":[{"id":39,"name":"VectorDB 101","published_at":"2022-09-30T05:56:34.554Z","created_by":18,"updated_by":18,"created_at":"2022-09-30T05:56:31.633Z","updated_at":"2024-07-10T07:12:04.155Z","locale":"en"}],"authors":[{"id":162,"name":"Ted Xu","author_tags":"Principal Engineer","published_at":"2024-05-20T12:43:41.099Z","created_by":18,"updated_by":18,"created_at":"2024-05-20T12:43:38.960Z","updated_at":"2024-07-18T15:58:52.645Z","home_page":null,"home_page_link":null,"self_intro":"Ted Xu is a Principal Engineer at Zilliz. ","repost_to_medium":null,"repost_state":null,"meta_description":"Ted Xu is a Principal Engineer at Zilliz. ","locale":"en"}],"read_time":5,"localizations":[{"id":463,"locale":"ja-JP","published_at":"2024-05-17T20:17:08.283Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/May_21_Scaling_Vector_Databases_for_Enterprise_Demands_4bc33c5aa6.png","belong":"learn","authorNames":["Ted Xu"]},{"id":"learn-200","title":"Model Providers: Open Source vs. Closed-Source","image":{"id":3513,"url":"https://assets.zilliz.com/Model_Providers_Open_Source_vs_Closed_Source_080aca8d02.png"},"display_time":"May 19, 2024","url":"model-providers-open-source-vs-closed-source","abstract":"In this article, we will examine the different providers, their pros and cons, and the implications of each. By the end, you will have the knowledge and understanding to make an informed choice between open-source and closed-source model providers.\n","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":154,"name":"Uppu Rajesh Kumar","author_tags":"Freelance Technical Writer","published_at":"2024-04-24T21:25:45.408Z","created_by":18,"updated_by":18,"created_at":"2024-04-24T21:25:43.983Z","updated_at":"2024-07-03T07:48:29.764Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Uppu Rajesh Kumar, Freelance Technical Writer","locale":"en"}],"read_time":10,"localizations":[{"id":457,"locale":"ja-JP","published_at":"2024-05-17T20:07:21.561Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Model_Providers_Open_Source_vs_Closed_Source_080aca8d02.png","belong":"learn","authorNames":["Uppu Rajesh Kumar"]},{"id":"blog-410","title":"Multimodal RAG locally with CLIP and Llama3 ","image":{"id":3536,"url":"https://assets.zilliz.com/May_09_Multimodal_RAG_locally_using_CLIP_and_Llama3_0a5751d3a3.png"},"display_time":"May 17, 2024","deploy_time":null,"url":"multimodal-RAG-with-CLIP-Llama3-and-milvus","abstract":"A tutorial walks you through how to build a multimodal RAG with CLIP, Llama3, and Milvus. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":115,"name":"Stephen Batifol","author_tags":"Developer Advocate ","published_at":"2024-03-07T03:46:04.655Z","created_by":18,"updated_by":18,"created_at":"2024-03-07T03:46:02.457Z","updated_at":"2024-07-18T15:56:42.529Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/stephen-batifol/","self_intro":"Stephen Batifol is a Developer Advocate at Zilliz. He previously worked as a Machine Learning Engineer at Wolt, where he was working on the ML Platform and as a Data Scientist at Brevo. Stephen studied Computer Science and Artificial Intelligence. He enjoys dancing and surfing. \n","repost_to_medium":null,"repost_state":null,"meta_description":"Stephen Batifol is a Developer Advocate at Zilliz.","locale":"en"}],"read_time":3,"localizations":[{"id":1313,"locale":"ja-JP","published_at":"2024-05-20T06:40:21.954Z"},{"id":1637,"locale":"fr","published_at":"2024-05-20T06:40:21.954Z"},{"id":1475,"locale":"de","published_at":"2024-05-20T06:40:21.954Z"},{"id":1502,"locale":"es","published_at":"2024-05-20T06:40:21.954Z"},{"id":1529,"locale":"pt","published_at":"2024-05-20T06:40:21.954Z"},{"id":1610,"locale":"it","published_at":"2024-05-20T06:40:21.954Z"},{"id":1556,"locale":"ru","published_at":"2024-05-20T06:40:21.954Z"},{"id":1583,"locale":"ko","published_at":"2024-05-20T06:40:21.954Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/May_09_Multimodal_RAG_locally_using_CLIP_and_Llama3_0a5751d3a3.png","belong":"blog","authorNames":["Stephen Batifol"]},{"id":"blog-408","title":"Milvus: The Key to RAG Development - Improve Efficiency, Reduce Costs, and Enhance Performance","image":{"id":3509,"url":"https://assets.zilliz.com/Why_Milvus_Makes_Building_RAG_Easier_Faster_and_More_Cost_Efficient_c79d603b20.png"},"display_time":"May 17, 2024","deploy_time":null,"url":"why-milvus-makes-building-rag-easier-faster-cost-efficient","abstract":"This post will jump into Milvus's latest features, highlight its functionalities, and illustrate why it is the premier choice for developing successful RAG applications. \n","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":157,"name":"Ken Zhang","author_tags":"Senior Product Manager","published_at":"2024-04-29T11:13:18.206Z","created_by":18,"updated_by":18,"created_at":"2024-04-29T03:36:01.335Z","updated_at":"2024-07-03T07:47:25.978Z","home_page":null,"home_page_link":null,"self_intro":"Ken Zhang is a Senior Product Manager at Zilliz, leading the development of the Milvus vector database by setting its strategic direction and key features. Prior to Zilliz, he served as a kernel engineer at SAP HANA and enhanced his product management skills at PingCAP. Ken holds a master's degree from Fudan University and has over eight years of experience specializing in database development and big data infrastructure management.","repost_to_medium":null,"repost_state":null,"meta_description":"Ken Zhang is a Senior Product Manager at Zilliz","locale":"en"}],"read_time":6,"localizations":[{"id":1266,"locale":"ja-JP","published_at":"2024-05-17T18:29:44.184Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Why_Milvus_Makes_Building_RAG_Easier_Faster_and_More_Cost_Efficient_c79d603b20.png","belong":"blog","authorNames":["Ken Zhang"]},{"id":"blog-407","title":" Zilliz Achieves AWS Generative AI Competency Partner Designation, Driving Innovation in AI Solutions","image":{"id":3506,"url":"https://assets.zilliz.com/Mar_16_Zilliz_Achieves_AWS_Generative_AI_Competency_Partner_Designation_Driving_Innovation_in_AI_Solutions_eba89eeae0.png"},"display_time":"May 16, 2024","deploy_time":null,"url":"zilliz-achieves-aws-genai-competency-partner-designation","abstract":"Zilliz has achieved the AWS Generative AI Competency status, marking a significant milestone in our commitment to advancing generative AI technologies.","tags":[{"id":4,"name":"Company","published_at":"2021-01-21T02:28:23.551Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:20.676Z","updated_at":"2021-01-21T02:28:23.824Z","locale":"en"}],"authors":[{"id":161,"name":"Sachi Tolani","author_tags":"Marketing Coordinator, Zilliz","published_at":"2024-05-15T20:11:42.999Z","created_by":18,"updated_by":18,"created_at":"2024-05-15T20:11:41.186Z","updated_at":"2024-05-16T16:42:51.441Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/sachi-tolani/","self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":1,"localizations":[{"id":1340,"locale":"ja-JP","published_at":"2024-05-16T16:26:45.480Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Mar_16_Zilliz_Achieves_AWS_Generative_AI_Competency_Partner_Designation_Driving_Innovation_in_AI_Solutions_eba89eeae0.png","belong":"blog","authorNames":["Sachi Tolani"]},{"id":"blog-409","title":"Running Llama 3, Mixtral, and GPT-4o","image":{"id":3530,"url":"https://assets.zilliz.com/Running_Llama_3_Mixtral_and_GPT_4o_f3f3636266.png"},"display_time":"May 15, 2024","deploy_time":null,"url":"running-llama-3-mixtral-gpt-4o","abstract":"This article will show a few ways to run some of the hottest contenders in the space: Llama 3 from Meta, Mixtral from Mistral, and the recently announced GPT-4o from OpenAI.\n","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":94,"name":"Christy Bergman","author_tags":"Developer Advocate","published_at":"2023-10-06T00:29:45.486Z","created_by":18,"updated_by":18,"created_at":"2023-10-06T00:29:30.751Z","updated_at":"2024-07-18T16:01:45.942Z","home_page":null,"home_page_link":null,"self_intro":"Christy Bergman is a passionate Developer Advocate at Zilliz. She previously worked in distributed computing at Anyscale and as a Specialist AI/ML Solutions Architect at AWS. Christy studied applied math, is a self-taught coder, and has published papers, including one with ACM Recsys. She enjoys hiking and bird watching.","repost_to_medium":null,"repost_state":null,"meta_description":"Christy Bergman is a passionate Developer Advocate at Zilliz. ","locale":"en"}],"read_time":8,"localizations":[{"id":1306,"locale":"ja-JP","published_at":"2024-05-17T21:24:34.338Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Running_Llama_3_Mixtral_and_GPT_4o_f3f3636266.png","belong":"blog","authorNames":["Christy Bergman"]},{"id":"learn-198","title":"Top LLMs of 2024: Only the Worthy","image":{"id":3801,"url":"https://assets.zilliz.com/May_19_Top_LL_Ms_of_2024_Only_the_Worthy_64454f7a1d.png"},"display_time":"May 15, 2024","url":"top-llms-2024","abstract":"This blog introduces the six most influential large language models in 2024. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":155,"name":"Abdelrahman Elgendy","author_tags":"Freelancer Technical Writer","published_at":"2024-04-24T21:29:55.865Z","created_by":18,"updated_by":18,"created_at":"2024-04-24T21:29:54.451Z","updated_at":"2024-07-03T07:48:12.043Z","home_page":null,"home_page_link":null,"self_intro":"A passionate technical writer who enjoys demystifying AI and machine learning concepts, making them accessible to everyone.\n","repost_to_medium":null,"repost_state":null,"meta_description":"Abdelrahman Elgendy, Freelancer Technical Writer","locale":"en"}],"read_time":9,"localizations":[{"id":334,"locale":"ja-JP","published_at":"2024-05-15T06:19:22.815Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/May_19_Top_LL_Ms_of_2024_Only_the_Worthy_64454f7a1d.png","belong":"learn","authorNames":["Abdelrahman Elgendy"]},{"id":"learn-192","title":"A Guide to Chunking Strategies for Retrieval Augmented Generation (RAG)","image":{"id":3805,"url":"https://assets.zilliz.com/May_19_A_Guide_to_Chunking_Strategies_for_Retrieval_Augmented_Generation_RAG_1079ea179b.png"},"display_time":"May 15, 2024","url":"guide-to-chunking-strategies-for-rag","abstract":"We explored various facets of chunking strategies within Retrieval-Augmented Generation (RAG) systems in this guide. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":132,"name":"Rahul ","author_tags":"Freelance Technical Writer","published_at":"2024-03-30T21:57:22.495Z","created_by":18,"updated_by":18,"created_at":"2024-03-30T21:57:19.140Z","updated_at":"2024-07-03T07:53:30.991Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Rahul, Freelance Technical Writer","locale":"en"}],"read_time":16,"localizations":[{"id":478,"locale":"ja-JP","published_at":"2024-05-15T07:13:43.841Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/May_19_A_Guide_to_Chunking_Strategies_for_Retrieval_Augmented_Generation_RAG_1079ea179b.png","belong":"learn","authorNames":["Rahul "]},{"id":"learn-199","title":"Building RAG with Snowflake Arctic and Transformers on Milvus","image":{"id":3498,"url":"https://assets.zilliz.com/Building_RAG_with_Snowflake_Arctic_and_Transformers_on_Milvus_c8f7f93dea.png"},"display_time":"May 14, 2024","url":"build-rag-with-snowflake-arctic-and-transformer-on-milvus","abstract":"This article explored the integration of Snowflake Arctic with Milvus.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":126,"name":"Antony G.","author_tags":"Freelance Technical Writer","published_at":"2024-03-26T09:18:07.767Z","created_by":18,"updated_by":18,"created_at":"2024-03-26T09:18:00.140Z","updated_at":"2024-07-03T07:56:19.123Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Antony G., Freelance Technical Writer","locale":"en"}],"read_time":5,"localizations":[{"id":360,"locale":"ja-JP","published_at":"2024-05-15T06:55:45.254Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Building_RAG_with_Snowflake_Arctic_and_Transformers_on_Milvus_c8f7f93dea.png","belong":"learn","authorNames":["Antony G."]},{"id":"learn-190","title":"How to Pick a Vector Index in Your Milvus Instance: A Visual Guide","image":{"id":3420,"url":"https://assets.zilliz.com/How_to_Pick_a_Vector_Index_in_Your_Milvus_Instance_A_Visual_Guide_cded62346b.png"},"display_time":"May 14, 2024","url":"how-to-pick-a-vector-index-in-milvus-visual-guide","abstract":"In this post, we'll explore several vector indexing strategies that can be used to efficiently perform similarity search, even in scenarios where we have large amounts of data and multiple constraints to consider.\n","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":125,"name":"Ruben Winastwan","author_tags":"Freelance Technical Writer","published_at":"2024-03-26T09:16:27.310Z","created_by":18,"updated_by":18,"created_at":"2024-03-26T09:16:24.498Z","updated_at":"2024-07-03T07:56:29.256Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Ruben Winastwan, Freelance Technical Writer","locale":"en"}],"read_time":9,"localizations":[{"id":451,"locale":"ja-JP","published_at":"2024-05-15T00:52:05.944Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/How_to_Pick_a_Vector_Index_in_Your_Milvus_Instance_A_Visual_Guide_cded62346b.png","belong":"learn","authorNames":["Ruben Winastwan"]},{"id":"learn-196","title":"Exploring ColBERT: A Token-Level Embedding and Ranking Model for Efficient Similarity Search ","image":{"id":3460,"url":"https://assets.zilliz.com/May_13_Exploring_Col_BERT_A_Token_Level_Embedding_and_Ranking_Model_for_Efficient_Similarity_Search_819a042117.png"},"display_time":"May 13, 2024","url":"explore-colbert-token-level-embedding-and-ranking-model-for-similarity-search","abstract":"Our review of ColBERT has unveiled a novel approach to token-level embeddings and ranking, specifically engineered to optimize efficiency in similarity search tasks.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":102,"name":"David Wang","author_tags":"Algorithm Engineer at Zilliz","published_at":"2023-10-27T08:41:57.519Z","created_by":18,"updated_by":18,"created_at":"2023-10-27T08:41:55.636Z","updated_at":"2024-04-16T02:43:37.282Z","home_page":"GitHub","home_page_link":"https://github.com/wxywb","self_intro":"David Wang, Algorithm Engineer at Zilliz, brings extensive expertise in computer vision and natural language processing. His contributions to advanced embedding algorithm research, including projects like Towhee and GPTCache, reflect his commitment to advancing AI technologies. Before joining Zilliz, he worked at Alibaba Cloud for large-scale object recognition and classification projects. David holds a Master's degree from Dalian University of Technology.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":9,"localizations":[{"id":357,"locale":"ja-JP","published_at":"2024-05-13T06:11:23.198Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/May_13_Exploring_Col_BERT_A_Token_Level_Embedding_and_Ranking_Model_for_Efficient_Similarity_Search_819a042117.png","belong":"learn","authorNames":["David Wang"]},{"id":"learn-197","title":"Efficiently Deploying Milvus on GCP Kubernetes: A Guide to Open Source Database Management","image":{"id":3461,"url":"https://assets.zilliz.com/Efficiently_Deploying_Milvus_on_GCP_Kubernetes_A_Guide_to_Open_Source_Database_Management_5ad7deb9ce.png"},"display_time":"May 13, 2024","url":"efficiently-deploying-milvus-on-gcp-kubernetes","abstract":"Self-hosting Milvus on Kubernetes (K8s), especially in the Google Cloud Platform (GCP) environment, offers numerous benefits. Read about the benefits and how to set up the Kubernetes cluster on GCP in the blog.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":160,"name":"Roy Lam","author_tags":"Freelance Technical Writer","published_at":"2024-05-06T22:44:01.212Z","created_by":18,"updated_by":18,"created_at":"2024-05-06T22:43:59.769Z","updated_at":"2024-07-03T07:46:48.095Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Roy Lam is a Freelance Technical Writer. ","locale":"en"}],"read_time":13,"localizations":[{"id":453,"locale":"ja-JP","published_at":"2024-05-14T17:02:41.599Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Efficiently_Deploying_Milvus_on_GCP_Kubernetes_A_Guide_to_Open_Source_Database_Management_5ad7deb9ce.png","belong":"learn","authorNames":["Roy Lam"]},{"id":"learn-128","title":"Enhancing Customer Experience with Vector Databases: A Strategic Approach","image":{"id":3802,"url":"https://assets.zilliz.com/May_21_Enhancing_Customer_Experience_with_Vector_Databases_ec959f18ec.png"},"display_time":"May 13, 2024","url":"enhancing-customer-experience-with-vector-databases","abstract":"Understand how vector databases process data to enhance customer experience and drive business growth. ","tags":[{"id":39,"name":"VectorDB 101","published_at":"2022-09-30T05:56:34.554Z","created_by":18,"updated_by":18,"created_at":"2022-09-30T05:56:31.633Z","updated_at":"2024-07-10T07:12:04.155Z","locale":"en"}],"authors":[{"id":118,"name":" Haziqa Sajid","author_tags":"Freelance Technical Writer","published_at":"2024-03-12T10:25:34.265Z","created_by":18,"updated_by":18,"created_at":"2024-03-12T10:25:31.148Z","updated_at":"2024-07-03T07:58:27.010Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/haziqa-sajid-22b53245/","self_intro":"Digital Storytelling for Data, AI, B2B \u0026 SaaS","repost_to_medium":null,"repost_state":null,"meta_description":" Haziqa Sajid, Freelance Technical Writer","locale":"en"}],"read_time":4,"localizations":[{"id":460,"locale":"ja-JP","published_at":"2024-05-15T07:00:28.008Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/May_21_Enhancing_Customer_Experience_with_Vector_Databases_ec959f18ec.png","belong":"learn","authorNames":[" Haziqa Sajid"]},{"id":"blog-406","title":"Harnessing Generative Feedback Loops in AI Systems with Milvus","image":{"id":3804,"url":"https://assets.zilliz.com/May_16_Generative_Feedback_Loops_with_LL_Ms_for_Vector_Databases_0b64ce3096.png"},"display_time":"May 10, 2024","deploy_time":null,"url":"harnessing-generative-feedback-loops-in-ai-systems-with-milvus","abstract":"A generative feedback loop is a cyclical process in which the output generated by an AI model is fed back into the system as training data. This allows the model to learn and improve its capabilities continuously over time. This cycle repeats, allowing the AI to optimize its results progressively. Integrating Milvus with LLMs in a generative feedback loop allows us to create a dynamic system that continually learns and improves. \n\n","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":154,"name":"Uppu Rajesh Kumar","author_tags":"Freelance Technical Writer","published_at":"2024-04-24T21:25:45.408Z","created_by":18,"updated_by":18,"created_at":"2024-04-24T21:25:43.983Z","updated_at":"2024-07-03T07:48:29.764Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Uppu Rajesh Kumar, Freelance Technical Writer","locale":"en"}],"read_time":13,"localizations":[{"id":1246,"locale":"ja-JP","published_at":"2024-05-10T18:26:52.580Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/May_16_Generative_Feedback_Loops_with_LL_Ms_for_Vector_Databases_0b64ce3096.png","belong":"blog","authorNames":["Uppu Rajesh Kumar"]},{"id":"blog-404","title":"Exploring DSPy and Its Integration with Milvus for Crafting Highly Efficient RAG Pipelines","image":{"id":3445,"url":"https://assets.zilliz.com/Exploring_DS_Py_and_Its_Integration_with_Milvus_for_Crafting_Highly_Efficient_RAG_Pipelines_4757b811ac.png"},"display_time":"May 09, 2024","deploy_time":null,"url":"exploring-dspy-and-its-integration-with-milvus-vector-database-for-RAG","abstract":"This blog explores DSPy and its operational mechanics and provides a practical example demonstrating how to construct and optimize RAG apps with DSPy and Milvus. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":102,"name":"David Wang","author_tags":"Algorithm Engineer at Zilliz","published_at":"2023-10-27T08:41:57.519Z","created_by":18,"updated_by":18,"created_at":"2023-10-27T08:41:55.636Z","updated_at":"2024-04-16T02:43:37.282Z","home_page":"GitHub","home_page_link":"https://github.com/wxywb","self_intro":"David Wang, Algorithm Engineer at Zilliz, brings extensive expertise in computer vision and natural language processing. His contributions to advanced embedding algorithm research, including projects like Towhee and GPTCache, reflect his commitment to advancing AI technologies. Before joining Zilliz, he worked at Alibaba Cloud for large-scale object recognition and classification projects. David holds a Master's degree from Dalian University of Technology.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":10,"localizations":[{"id":1064,"locale":"ja-JP","published_at":"2024-05-08T16:36:45.782Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Exploring_DS_Py_and_Its_Integration_with_Milvus_for_Crafting_Highly_Efficient_RAG_Pipelines_4757b811ac.png","belong":"blog","authorNames":["David Wang"]},{"id":"blog-405","title":"Milvus Reference Architectures ","image":{"id":3450,"url":"https://assets.zilliz.com/Milvus_Reference_Architectures_284a835298.png"},"display_time":"May 09, 2024","deploy_time":null,"url":"milvus-reference-architectures","abstract":"This blog addresses some commonly asked questions regarding Milvus resource allocation based on specific use cases.","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":94,"name":"Christy Bergman","author_tags":"Developer Advocate","published_at":"2023-10-06T00:29:45.486Z","created_by":18,"updated_by":18,"created_at":"2023-10-06T00:29:30.751Z","updated_at":"2024-07-18T16:01:45.942Z","home_page":null,"home_page_link":null,"self_intro":"Christy Bergman is a passionate Developer Advocate at Zilliz. She previously worked in distributed computing at Anyscale and as a Specialist AI/ML Solutions Architect at AWS. Christy studied applied math, is a self-taught coder, and has published papers, including one with ACM Recsys. She enjoys hiking and bird watching.","repost_to_medium":null,"repost_state":null,"meta_description":"Christy Bergman is a passionate Developer Advocate at Zilliz. ","locale":"en"}],"read_time":5,"localizations":[{"id":1299,"locale":"ja-JP","published_at":"2024-05-09T17:14:53.321Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Milvus_Reference_Architectures_284a835298.png","belong":"blog","authorNames":["Christy Bergman"]},{"id":"learn-194","title":"Comparing SPLADE Sparse Vectors with BM25","image":{"id":3428,"url":"https://assets.zilliz.com/Comparing_SPLADE_Sparse_Vectors_with_BM_25_b2d1c02a32.png"},"display_time":"May 07, 2024","url":"comparing-splade-sparse-vectors-with-bm25","abstract":"In general, there are two types of vectors: dense vectors and sparse vectors. While they can be utilized for similar tasks, each has advantages and disadvantages. In this post, we will delve into two popular variants of sparse embedding: BM25 and SPLADE. \n","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":125,"name":"Ruben Winastwan","author_tags":"Freelance Technical Writer","published_at":"2024-03-26T09:16:27.310Z","created_by":18,"updated_by":18,"created_at":"2024-03-26T09:16:24.498Z","updated_at":"2024-07-03T07:56:29.256Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Ruben Winastwan, Freelance Technical Writer","locale":"en"}],"read_time":12,"localizations":[{"id":443,"locale":"ja-JP","published_at":"2024-05-07T17:57:47.659Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Comparing_SPLADE_Sparse_Vectors_with_BM_25_b2d1c02a32.png","belong":"learn","authorNames":["Ruben Winastwan"]},{"id":"learn-195","title":"Exploring the Langchain Community API: Seamless Vector Database Integration with Milvus and Zilliz","image":{"id":3439,"url":"https://assets.zilliz.com/Exploring_the_Langchain_Community_API_Seamless_Vector_Database_Integration_with_Milvus_and_Zilliz_1_03627f6c1f.png"},"display_time":"May 07, 2024","url":"exploring-langchain-community-api-vector-database-integration-milvus-zilliz","abstract":" This article will explore the LangChain Community API and how it simplifies the process of integrating Milvus and Zilliz for efficient vector database interaction.\n","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":158,"name":"Denis Kuria","author_tags":"Freelance Technical Writer","published_at":"2024-05-01T00:39:32.350Z","created_by":18,"updated_by":18,"created_at":"2024-05-01T00:39:30.888Z","updated_at":"2024-07-03T06:50:56.660Z","home_page":null,"home_page_link":null,"self_intro":"Denis is a machine learning engineer who enjoys writing guides to help other developers. He has a bachelor's in computer science and loves hiking and exploring the world.\n","repost_to_medium":null,"repost_state":null,"meta_description":"Denis Kuria is a freelance technical writer at Zilliz. ","locale":"en"}],"read_time":12,"localizations":[{"id":450,"locale":"ja-JP","published_at":"2024-05-07T20:20:33.357Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Exploring_the_Langchain_Community_API_Seamless_Vector_Database_Integration_with_Milvus_and_Zilliz_1_03627f6c1f.png","belong":"learn","authorNames":["Denis Kuria"]},{"id":"learn-193","title":"Semantic Search with Milvus and OpenAI","image":{"id":3426,"url":"https://assets.zilliz.com/Semantic_Search_with_Milvus_and_Open_AI_4b5bf4e0c4.png"},"display_time":"May 06, 2024","url":"semantic-search-with-milvus-and-openai","abstract":"In this guide, we’ll explore semantic search capabilities through the integration of Milvus and OpenAI’s Embedding API, using a book title search as an example use case. \n","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":150,"name":"Tim Mugabi","author_tags":"Freelance Technical Writer","published_at":"2024-04-24T21:23:34.511Z","created_by":18,"updated_by":18,"created_at":"2024-04-24T21:23:32.810Z","updated_at":"2024-07-03T07:49:21.138Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Tim Mugabi, Freelance Technical Writer","locale":"en"}],"read_time":7,"localizations":[{"id":441,"locale":"ja-JP","published_at":"2024-05-07T17:25:59.418Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Semantic_Search_with_Milvus_and_Open_AI_4b5bf4e0c4.png","belong":"learn","authorNames":["Tim Mugabi"]},{"id":"learn-185","title":"Building a RAG Pipeline with Milvus and Haystack 2.0 ","image":{"id":3413,"url":"https://assets.zilliz.com/Utilizing_Milvus_and_Haystack_2_0_for_Efficient_Document_Evaluation_4d25100fed.png"},"display_time":"May 05, 2024","url":"using-milvus-and-haystack-for-building-efficient-rag-pinepipes","abstract":"This guide will demonstrate the integration of Milvus and Haystack 2.0 to build a powerful question-answering application. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":146,"name":"Scott Swain","author_tags":"Freelance Technical Writer","published_at":"2024-04-24T21:20:19.581Z","created_by":18,"updated_by":18,"created_at":"2024-04-24T21:20:17.877Z","updated_at":"2024-07-03T07:50:28.549Z","home_page":null,"home_page_link":null,"self_intro":"29 years full stack dev, Machine Learning, Web Design, Web/Database Development, WordPress, writing (technical, philosophical, instructional, and sci-fi) and lead experience. Tech and people lover. Author of A Practical EmPath: Rewire Your Mind book.","repost_to_medium":null,"repost_state":null,"meta_description":"Scott Swain, Freelance Technical Writer","locale":"en"}],"read_time":10,"localizations":[{"id":400,"locale":"ja-JP","published_at":"2024-05-13T14:49:52.823Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Utilizing_Milvus_and_Haystack_2_0_for_Efficient_Document_Evaluation_4d25100fed.png","belong":"learn","authorNames":["Scott Swain"]},{"id":"learn-171","title":"TF-IDF - Understanding Term Frequency-Inverse Document Frequency in NLP","image":{"id":3275,"url":"https://assets.zilliz.com/TF_IDF_Understanding_Term_Frequency_Inverse_Document_Frequency_in_NLP_04d3c51de7.png"},"display_time":"May 04, 2024","url":"tf-idf-understanding-term-frequency-inverse-document-frequency-in-nlp","abstract":"We explore the significance of Term Frequency-Inverse Document Frequency (TF-IDF) and its applications, particularly in enhancing the capabilities of vector databases like Milvus.\n","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":132,"name":"Rahul ","author_tags":"Freelance Technical Writer","published_at":"2024-03-30T21:57:22.495Z","created_by":18,"updated_by":18,"created_at":"2024-03-30T21:57:19.140Z","updated_at":"2024-07-03T07:53:30.991Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Rahul, Freelance Technical Writer","locale":"en"}],"read_time":13,"localizations":[{"id":465,"locale":"ja-JP","published_at":"2024-05-17T11:01:01.071Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/TF_IDF_Understanding_Term_Frequency_Inverse_Document_Frequency_in_NLP_04d3c51de7.png","belong":"learn","authorNames":["Rahul "]},{"id":"learn-184","title":"Building RAG with Zilliz Cloud and AWS Bedrock: A Narrative Guide","image":{"id":3410,"url":"https://assets.zilliz.com/Building_RAG_with_Zilliz_Cloud_and_AWS_Bedrock_A_Narrative_Guide_c3fa7e6b7b.png"},"display_time":"May 03, 2024","url":"build-RAG-with-zilliz-cloud-and-aws-bedrock","abstract":"A comprehensive guide on how to use Zilliz Cloud and AWS Bedrock to build RAG applications","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":126,"name":"Antony G.","author_tags":"Freelance Technical Writer","published_at":"2024-03-26T09:18:07.767Z","created_by":18,"updated_by":18,"created_at":"2024-03-26T09:18:00.140Z","updated_at":"2024-07-03T07:56:19.123Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Antony G., Freelance Technical Writer","locale":"en"}],"read_time":8,"localizations":[{"id":325,"locale":"ja-JP","published_at":"2024-05-06T14:03:07.884Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Building_RAG_with_Zilliz_Cloud_and_AWS_Bedrock_A_Narrative_Guide_c3fa7e6b7b.png","belong":"learn","authorNames":["Antony G."]},{"id":"blog-399","title":"Revolutionizing Search with Zilliz and Azure OpenAI","image":{"id":3408,"url":"https://assets.zilliz.com/Revolutionizing_Search_with_Zilliz_and_Azure_Open_AI_650d199239.png"},"display_time":"May 02, 2024","deploy_time":null,"url":"revolutionizing-search-with-zilliz-and-azure-openai","abstract":"In AI development, a new integration emerged between Zilliz and Azure OpenAI. Together, they redefine the landscape of similarity and semantic search, infusing them with remarkable speed, intelligence, and safeguards. Let's explore this fusion of cutting-edge technologies.\n","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":143,"name":"Daniella Pontes","author_tags":"Freelance Technical Writer","published_at":"2024-04-19T03:52:05.346Z","created_by":18,"updated_by":18,"created_at":"2024-04-19T03:52:03.759Z","updated_at":"2024-07-03T07:58:01.528Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Daniella Pontes, Freelance Technical Writer","locale":"en"}],"read_time":9,"localizations":[{"id":1120,"locale":"ja-JP","published_at":"2024-05-02T21:19:27.098Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Revolutionizing_Search_with_Zilliz_and_Azure_Open_AI_650d199239.png","belong":"blog","authorNames":["Daniella Pontes"]},{"id":"learn-133","title":"Transforming PDFs into Insights: Vectorizing and Ingesting with Zilliz Cloud Pipelines","image":{"id":3396,"url":"https://assets.zilliz.com/Transforming_PD_Fs_into_Insights_Vectorizing_and_Ingesting_with_Zilliz_Cloud_Pipelines_022480dbf7.png"},"display_time":"May 01, 2024","url":"transforming-pdfs-into-insights-vectorizing-and-ingesting-with-zilliz-cloud-pipelines","abstract":"You will learn how Zilliz Cloud Pipeline transforms PDF data into a format ready for LLMs to use in semantic search tasks. Finally, we will conduct data retrieval using vector search.\n","tags":[{"id":39,"name":"VectorDB 101","published_at":"2022-09-30T05:56:34.554Z","created_by":18,"updated_by":18,"created_at":"2022-09-30T05:56:31.633Z","updated_at":"2024-07-10T07:12:04.155Z","locale":"en"}],"authors":[{"id":125,"name":"Ruben Winastwan","author_tags":"Freelance Technical Writer","published_at":"2024-03-26T09:16:27.310Z","created_by":18,"updated_by":18,"created_at":"2024-03-26T09:16:24.498Z","updated_at":"2024-07-03T07:56:29.256Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Ruben Winastwan, Freelance Technical Writer","locale":"en"}],"read_time":14,"localizations":[{"id":377,"locale":"ja-JP","published_at":"2024-05-01T18:05:48.186Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Transforming_PD_Fs_into_Insights_Vectorizing_and_Ingesting_with_Zilliz_Cloud_Pipelines_022480dbf7.png","belong":"learn","authorNames":["Ruben Winastwan"]},{"id":"blog-398","title":"Getting Started with Milvus Hybrid Search","image":{"id":3382,"url":"https://assets.zilliz.com/Hybrid_Search_with_Milvus_0fedf0098e.png"},"display_time":"Apr 30, 2024","deploy_time":null,"url":"hybrid-search-with-milvus","abstract":"In this tutorial, you will learn how to enhance your search by using Milvus 2.4's hybrid search capabilities. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":115,"name":"Stephen Batifol","author_tags":"Developer Advocate ","published_at":"2024-03-07T03:46:04.655Z","created_by":18,"updated_by":18,"created_at":"2024-03-07T03:46:02.457Z","updated_at":"2024-07-18T15:56:42.529Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/stephen-batifol/","self_intro":"Stephen Batifol is a Developer Advocate at Zilliz. He previously worked as a Machine Learning Engineer at Wolt, where he was working on the ML Platform and as a Data Scientist at Brevo. Stephen studied Computer Science and Artificial Intelligence. He enjoys dancing and surfing. \n","repost_to_medium":null,"repost_state":null,"meta_description":"Stephen Batifol is a Developer Advocate at Zilliz.","locale":"en"}],"read_time":10,"localizations":[{"id":1473,"locale":"de","published_at":"2024-04-30T08:08:51.886Z"},{"id":1527,"locale":"pt","published_at":"2024-04-30T08:08:51.886Z"},{"id":1292,"locale":"ja-JP","published_at":"2024-04-30T08:08:51.886Z"},{"id":1608,"locale":"it","published_at":"2024-04-30T08:08:51.886Z"},{"id":1554,"locale":"ru","published_at":"2024-04-30T08:08:51.886Z"},{"id":1635,"locale":"fr","published_at":"2024-04-30T08:08:51.886Z"},{"id":1500,"locale":"es","published_at":"2024-04-30T08:08:51.886Z"},{"id":1581,"locale":"ko","published_at":"2024-04-30T08:08:51.886Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Hybrid_Search_with_Milvus_0fedf0098e.png","belong":"blog","authorNames":["Stephen Batifol"]},{"id":"learn-183","title":"Enhancing Efficiency in Vector Searches with Binary Quantization and Milvus","image":{"id":3389,"url":"https://assets.zilliz.com/Enhancing_Efficiency_in_Vector_Searches_with_Binary_Quantization_and_Milvus_f4e5284f69.png"},"display_time":"Apr 30, 2024","url":"enhancing-efficiency-in-vector-searches-with-binary-quantization-and-milvus","abstract":"Binary quantization represents a transformative approach to managing and searching vector data within Milvus, offering significant enhancements in both performance and efficiency. By simplifying vector representations into binary codes, this method leverages the speed of bitwise operations, substantially accelerating search operations and reducing computational overhead. \n","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":153,"name":"Mostafa Ibrahim","author_tags":"Freelance Technical Writer","published_at":"2024-04-24T21:25:21.361Z","created_by":18,"updated_by":18,"created_at":"2024-04-24T21:25:19.857Z","updated_at":"2024-07-03T06:51:28.798Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":10,"localizations":[{"id":464,"locale":"ja-JP","published_at":"2024-05-01T16:28:25.069Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Enhancing_Efficiency_in_Vector_Searches_with_Binary_Quantization_and_Milvus_f4e5284f69.png","belong":"learn","authorNames":["Mostafa Ibrahim"]},{"id":"learn-182","title":"Effortless AI Workflows: A Beginner's Guide to Hugging Face and PyMilvus","image":{"id":3384,"url":"https://assets.zilliz.com/Effortless_AI_Workflows_A_Beginner_s_Guide_to_Hugging_Face_and_Py_Milvus_57c54455a3.png"},"display_time":"Apr 30, 2024","url":"effortless-ai-workflows-a-beginners-guide-to-hugging-face-and-pymilvus","abstract":"In this comprehensive guide, you will learn how to utilize PyMilvus and Hugging Face datasets to supercharge your machine-learning projects.\n","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":158,"name":"Denis Kuria","author_tags":"Freelance Technical Writer","published_at":"2024-05-01T00:39:32.350Z","created_by":18,"updated_by":18,"created_at":"2024-05-01T00:39:30.888Z","updated_at":"2024-07-03T06:50:56.660Z","home_page":null,"home_page_link":null,"self_intro":"Denis is a machine learning engineer who enjoys writing guides to help other developers. He has a bachelor's in computer science and loves hiking and exploring the world.\n","repost_to_medium":null,"repost_state":null,"meta_description":"Denis Kuria is a freelance technical writer at Zilliz. ","locale":"en"}],"read_time":11,"localizations":[{"id":434,"locale":"ja-JP","published_at":"2024-05-01T00:54:18.055Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Effortless_AI_Workflows_A_Beginner_s_Guide_to_Hugging_Face_and_Py_Milvus_57c54455a3.png","belong":"learn","authorNames":["Denis Kuria"]},{"id":"learn-135","title":"Nemo Guardrails: Elevating AI Safety and Reliability","image":{"id":3026,"url":"https://assets.zilliz.com/Mar_26_AI_and_Machine_Learning_4_fe87668ab1.png"},"display_time":"Apr 29, 2024","url":"nemo-guardrails-elevating-safety-and-reliability","abstract":"In this article, we will provide an in-depth explanation of what Nemo Guardrails are, its practical applications, along with its integration. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":155,"name":"Abdelrahman Elgendy","author_tags":"Freelancer Technical Writer","published_at":"2024-04-24T21:29:55.865Z","created_by":18,"updated_by":18,"created_at":"2024-04-24T21:29:54.451Z","updated_at":"2024-07-03T07:48:12.043Z","home_page":null,"home_page_link":null,"self_intro":"A passionate technical writer who enjoys demystifying AI and machine learning concepts, making them accessible to everyone.\n","repost_to_medium":null,"repost_state":null,"meta_description":"Abdelrahman Elgendy, Freelancer Technical Writer","locale":"en"}],"read_time":8,"localizations":[{"id":317,"locale":"ja-JP","published_at":"2024-04-29T11:43:13.207Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Mar_26_AI_and_Machine_Learning_4_fe87668ab1.png","belong":"learn","authorNames":["Abdelrahman Elgendy"]},{"id":"learn-131","title":"Popular Machine-learning Algorithms Behind Vector Searches","image":{"id":3023,"url":"https://assets.zilliz.com/Mar_26_Accelerated_Vector_Search_05ee0a20a2.png"},"display_time":"Apr 29, 2024","url":"popular-machine-learning-algorithms-behind-vector-search","abstract":"In this post, we’ll explore the essence of vector searches and some popular machine learning algorithms that power efficient vector search, such as K-Nearest Neighbors (ANN) and Approximate Nearest Neighbors (ANN). ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":45,"name":"Fendy Feng","author_tags":"Technical Marketing Writer","published_at":"2023-05-16T01:36:15.102Z","created_by":18,"updated_by":18,"created_at":"2023-05-16T00:04:12.065Z","updated_at":"2024-04-25T08:37:19.712Z","home_page":"GitHub","home_page_link":"https://www.linkedin.com/in/fendy311/","self_intro":"Fendy Feng is the Technical Marketing Writer at Zilliz. She has extensive experience developing and enhancing the impact of open-source projects in various global markets by producing high-quality, tailored content. Before joining Zilliz, Fendy worked as a Content Strategist at PingCAP, a fast-growing E-Series startup renowned for its open-source distributed SQL database.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"},{"id":131,"name":"Samin Chandeepa","author_tags":"Freelance Technical Writer","published_at":"2024-03-29T07:49:43.838Z","created_by":18,"updated_by":18,"created_at":"2024-03-29T07:49:42.003Z","updated_at":"2024-07-03T07:53:42.149Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Samin Chandeepa, Freelance Technical Writer","locale":"en"}],"read_time":8,"localizations":[{"id":431,"locale":"ja-JP","published_at":"2024-04-30T11:02:36.164Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Mar_26_Accelerated_Vector_Search_05ee0a20a2.png","belong":"learn","authorNames":["Fendy Feng","Samin Chandeepa"]},{"id":"blog-397","title":"Vector Databases Are the Base of RAG Retrieval","image":{"id":3350,"url":"https://assets.zilliz.com/Vector_Databases_Are_the_Base_of_RAG_Retrieval_35aa9f0317.png"},"display_time":"Apr 28, 2024","deploy_time":null,"url":"vector-database-are-the-base-of-RAG-retrieval","abstract":"This blog discusses the significance of vector databases in building your RAG applications. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":157,"name":"Ken Zhang","author_tags":"Senior Product Manager","published_at":"2024-04-29T11:13:18.206Z","created_by":18,"updated_by":18,"created_at":"2024-04-29T03:36:01.335Z","updated_at":"2024-07-03T07:47:25.978Z","home_page":null,"home_page_link":null,"self_intro":"Ken Zhang is a Senior Product Manager at Zilliz, leading the development of the Milvus vector database by setting its strategic direction and key features. Prior to Zilliz, he served as a kernel engineer at SAP HANA and enhanced his product management skills at PingCAP. Ken holds a master's degree from Fudan University and has over eight years of experience specializing in database development and big data infrastructure management.","repost_to_medium":null,"repost_state":null,"meta_description":"Ken Zhang is a Senior Product Manager at Zilliz","locale":"en"}],"read_time":7,"localizations":[{"id":1042,"locale":"ja-JP","published_at":"2024-04-28T15:03:11.792Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Vector_Databases_Are_the_Base_of_RAG_Retrieval_35aa9f0317.png","belong":"blog","authorNames":["Ken Zhang"]},{"id":"blog-394","title":"The Landscape of Open Source Licensing in AI: A Primer on LLMs and Vector Databases","image":{"id":3329,"url":"https://assets.zilliz.com/The_Landscape_of_Open_Source_Licensing_in_AI_A_Primer_on_LL_Ms_and_Vector_Databases_24589c43cd.png"},"display_time":"Apr 28, 2024","deploy_time":null,"url":"open-source-licensing-in--AI-a-primer-on-llms-and-vector-databases","abstract":"Deciphering Open Source Licenses in AI: An Essential Guide","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":37,"name":"Emily Kurze","author_tags":"Director of Marketing Operations","published_at":"2023-04-11T16:55:11.838Z","created_by":18,"updated_by":18,"created_at":"2023-04-11T16:55:07.625Z","updated_at":"2024-04-29T03:28:13.160Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/emilykurze/","self_intro":"Emily Kurze is the Director of Marketing at Zilliz. ","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":7,"localizations":[{"id":1240,"locale":"ja-JP","published_at":"2024-04-28T11:47:38.346Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/The_Landscape_of_Open_Source_Licensing_in_AI_A_Primer_on_LL_Ms_and_Vector_Databases_24589c43cd.png","belong":"blog","authorNames":["Emily Kurze"]},{"id":"learn-179","title":"Exploring BGE-M3 and Splade: Two Machine Learning Models for Generating Sparse Embeddings ","image":{"id":3313,"url":"https://assets.zilliz.com/Exploring_BGE_M3_and_Splade_Two_Machine_Learning_Models_for_Generating_Sparse_Embeddings_a3065f09cd.png"},"display_time":"Apr 28, 2024","url":"bge-m3-and-splade-two-machine-learning-models-for-generating-sparse-embeddings","abstract":"In this blog, we’ve journeyed through the intricate world of vector embeddings and explored how BGE-M3 and Splade generate learned sparse embeddings.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":141,"name":"Buqian Zheng ","author_tags":"Senior Software Engineer","published_at":"2024-04-11T22:45:30.022Z","created_by":18,"updated_by":18,"created_at":"2024-04-11T22:45:27.515Z","updated_at":"2024-07-18T15:57:36.555Z","home_page":null,"home_page_link":null,"self_intro":"Buqian Zheng is a Senior Software Engineer at Zilliz, specializing in developing the core vector index engine of Milvus. Before joining Zilliz, he was a Software Engineer at Google, where he contributed to projects such as Google Cloud Dataflow and managed Google-scale data analytic services. With a wealth of industry experience in managing massive data and infrastructures, Buqian brings invaluable expertise to his role. He holds a Master’s degree from Carnegie Mellon University.","repost_to_medium":null,"repost_state":null,"meta_description":"Buqian Zheng, Senior Software Engineer at Zilliz","locale":"en"}],"read_time":8,"localizations":[{"id":454,"locale":"ja-JP","published_at":"2024-04-28T11:08:45.293Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Exploring_BGE_M3_and_Splade_Two_Machine_Learning_Models_for_Generating_Sparse_Embeddings_a3065f09cd.png","belong":"learn","authorNames":["Buqian Zheng "]},{"id":"blog-396","title":"Ensuring Data Privacy in AI Search with Langchain and Zilliz Cloud","image":{"id":3347,"url":"https://assets.zilliz.com/Ensuring_Data_Privacy_in_AI_Search_with_Langchain_and_Zilliz_Cloud_7bee05682e.png"},"display_time":"Apr 27, 2024","deploy_time":null,"url":"ensure-data-privacy-in-AI-search-with-langchain-and-zilliz-cloud","abstract":"This blog showed how to use Zilliz Cloud with LangChain to implement a question-answer bot. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":135,"name":"Antony G.","author_tags":"Freelance Technical Writer","published_at":"2024-03-31T20:39:48.027Z","created_by":18,"updated_by":18,"created_at":"2024-03-31T20:39:30.202Z","updated_at":"2024-07-03T07:52:52.095Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Antony G., Freelance Technical Writer","locale":"en"}],"read_time":6,"localizations":[{"id":1048,"locale":"ja-JP","published_at":"2024-04-29T03:36:31.920Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Ensuring_Data_Privacy_in_AI_Search_with_Langchain_and_Zilliz_Cloud_7bee05682e.png","belong":"blog","authorNames":["Antony G."]},{"id":"blog-393","title":"Practical Tips and Tricks for Developers Building RAG Applications","image":{"id":3034,"url":"https://assets.zilliz.com/Practical_Tips_and_Tricks_for_Developers_Using_Vector_Databases_a923000a3c.png"},"display_time":"Apr 27, 2024","deploy_time":null,"url":"praticial-tips-and-tricks-for-developers-building-rag-applications","abstract":"This guide will explore the multifaceted world of vector databases and the practical approaches required to maximize the efficiency and scalability of your RAG apps. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":34,"name":"James Luan","author_tags":"VP of Engineering at Zilliz","published_at":"2022-05-18T03:15:15.255Z","created_by":18,"updated_by":18,"created_at":"2022-05-18T03:14:35.112Z","updated_at":"2024-01-12T21:01:29.192Z","home_page":"GitHub","home_page_link":"https://github.com/xiaofan-luan","self_intro":"James Luan is the VP of Engineering at Zilliz. With a master's degree in computer engineering from Cornell University, he has extensive experience as a Database Engineer at Oracle, Hedvig, and Alibaba Cloud. James played a crucial role in developing HBase, Alibaba Cloud's open-source database, and Lindorm, a self-developed NoSQL database. He is also a respected member of the Technical Advisory Committee of LF AI \u0026 Data Foundation, contributing his expertise to shaping the future of AI and data technologies.\n","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":13,"localizations":[{"id":1254,"locale":"ja-JP","published_at":"2024-04-28T09:47:52.907Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Practical_Tips_and_Tricks_for_Developers_Using_Vector_Databases_a923000a3c.png","belong":"blog","authorNames":["James Luan"]},{"id":"learn-132","title":"Unlocking the Secrets of GPT-4.0 and Large Language Models","image":{"id":3024,"url":"https://assets.zilliz.com/Mar_26_LLM_3_08101538b3.png"},"display_time":"Apr 26, 2024","url":"what-are-llms-unlock-secrets-of-gpt-4-and-llms","abstract":"Unlocking the Secrets of GPT-4.0 and Large Language Models","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":149,"name":"Ankush Chander","author_tags":"Freelance Technical Writer","published_at":"2024-04-24T21:23:04.834Z","created_by":18,"updated_by":18,"created_at":"2024-04-24T21:23:03.409Z","updated_at":"2024-07-03T07:49:31.787Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Ankush Chander, Freelance Technical Writer","locale":"en"}],"read_time":12,"localizations":[{"id":399,"locale":"ja-JP","published_at":"2024-04-28T14:13:13.502Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Mar_26_LLM_3_08101538b3.png","belong":"learn","authorNames":["Ankush Chander"]},{"id":"learn-176","title":"A Beginner's Guide to Connecting Zilliz Cloud with Google Cloud Platform","image":{"id":3295,"url":"https://assets.zilliz.com/Beginner_s_Guide_to_Connecting_Zilliz_Cloud_with_Google_Cloud_Platform_f3b36c5aa2.png"},"display_time":"Apr 26, 2024","url":"beginners-guide-to-connecting-zilliz-cloud-with-gcp","abstract":"A Beginner's Guide to Connecting Zilliz Cloud with Google Cloud Platform","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":146,"name":"Scott Swain","author_tags":"Freelance Technical Writer","published_at":"2024-04-24T21:20:19.581Z","created_by":18,"updated_by":18,"created_at":"2024-04-24T21:20:17.877Z","updated_at":"2024-07-03T07:50:28.549Z","home_page":null,"home_page_link":null,"self_intro":"29 years full stack dev, Machine Learning, Web Design, Web/Database Development, WordPress, writing (technical, philosophical, instructional, and sci-fi) and lead experience. Tech and people lover. Author of A Practical EmPath: Rewire Your Mind book.","repost_to_medium":null,"repost_state":null,"meta_description":"Scott Swain, Freelance Technical Writer","locale":"en"}],"read_time":7,"localizations":[{"id":425,"locale":"ja-JP","published_at":"2024-04-28T11:14:50.433Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Beginner_s_Guide_to_Connecting_Zilliz_Cloud_with_Google_Cloud_Platform_f3b36c5aa2.png","belong":"learn","authorNames":["Scott Swain"]},{"id":"learn-180","title":"Navigating the Nuances of Lexical and Semantic Search with Zilliz","image":{"id":3343,"url":"https://assets.zilliz.com/Navigating_the_Nuances_of_Lexical_and_Semantic_Search_with_Zilliz_142c13b4d8.png"},"display_time":"Apr 25, 2024","url":"navigate-nuances-of-lexical-and-semantic-search-with-zilliz","abstract":"Learn the mechanics, applications, and benefits of lexical and semantic search and how to perform it in Zilliz.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":118,"name":" Haziqa Sajid","author_tags":"Freelance Technical Writer","published_at":"2024-03-12T10:25:34.265Z","created_by":18,"updated_by":18,"created_at":"2024-03-12T10:25:31.148Z","updated_at":"2024-07-03T07:58:27.010Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/haziqa-sajid-22b53245/","self_intro":"Digital Storytelling for Data, AI, B2B \u0026 SaaS","repost_to_medium":null,"repost_state":null,"meta_description":" Haziqa Sajid, Freelance Technical Writer","locale":"en"}],"read_time":13,"localizations":[{"id":387,"locale":"ja-JP","published_at":"2024-04-28T14:24:12.829Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Navigating_the_Nuances_of_Lexical_and_Semantic_Search_with_Zilliz_142c13b4d8.png","belong":"learn","authorNames":[" Haziqa Sajid"]},{"id":"learn-175","title":"Pandas DataFrame: Chunking and Vectorizing with Milvus","image":{"id":3464,"url":"https://assets.zilliz.com/May10_Pandas_Data_Frame_Chunking_and_Vectorizing_with_Milvus_e449b7a822.png"},"display_time":"Apr 25, 2024","url":"pandas-dataframe-chunking-anf-vectorizing-with-milvus","abstract":"If we store all of the data, including the chunk text and the embedding, inside of Pandas DataFrame, we can easily integrate and import them into the Milvus vector database.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":125,"name":"Ruben Winastwan","author_tags":"Freelance Technical Writer","published_at":"2024-03-26T09:16:27.310Z","created_by":18,"updated_by":18,"created_at":"2024-03-26T09:16:24.498Z","updated_at":"2024-07-03T07:56:29.256Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Ruben Winastwan, Freelance Technical Writer","locale":"en"}],"read_time":16,"localizations":[{"id":461,"locale":"ja-JP","published_at":"2024-04-25T18:51:46.978Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/May10_Pandas_Data_Frame_Chunking_and_Vectorizing_with_Milvus_e449b7a822.png","belong":"learn","authorNames":["Ruben Winastwan"]},{"id":"blog-390","title":"An Overview of Milvus Storage System and Techniques to Evaluate and Optimize Its Performance ","image":{"id":3279,"url":"https://assets.zilliz.com/How_to_Evaluate_and_Optimize_the_Performance_of_Milvus_Storage_1f165b2c63.png"},"display_time":"Apr 24, 2024","deploy_time":null,"url":"how-to-evaluate-and-optimize-performance-of-milvus-storage","abstract":"This guide will delve into Milvus' architecture, break down its key storage components, and explore effective techniques to evaluate their performance. \n\nAn Overview of Milvus Storage System and Techniques to Evaluate and Optimize Its Performance ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":45,"name":"Fendy Feng","author_tags":"Technical Marketing Writer","published_at":"2023-05-16T01:36:15.102Z","created_by":18,"updated_by":18,"created_at":"2023-05-16T00:04:12.065Z","updated_at":"2024-04-25T08:37:19.712Z","home_page":"GitHub","home_page_link":"https://www.linkedin.com/in/fendy311/","self_intro":"Fendy Feng is the Technical Marketing Writer at Zilliz. She has extensive experience developing and enhancing the impact of open-source projects in various global markets by producing high-quality, tailored content. Before joining Zilliz, Fendy worked as a Content Strategist at PingCAP, a fast-growing E-Series startup renowned for its open-source distributed SQL database.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"},{"id":145,"name":"Jay Zhu ","author_tags":"Senior Software Engineer at Zilliz","published_at":"2024-04-23T13:30:47.813Z","created_by":18,"updated_by":18,"created_at":"2024-04-23T13:30:45.814Z","updated_at":"2024-07-03T07:50:40.257Z","home_page":null,"home_page_link":null,"self_intro":"Jay Zhu is the Senior Software Engineer and tech leader of the DevOps \u0026 Infrastructure team at Zilliz. He specializes in DevOps, cloud-native technologies, and Kubernetes projects. Additionally, Jay is actively involved in developing and maintaining various open-source projects, including Milvus, Milvus-helm, and Milvus-operator.","repost_to_medium":null,"repost_state":null,"meta_description":"Jay Zhu, Senior Software Engineer at Zilliz","locale":"en"}],"read_time":7,"localizations":[{"id":924,"locale":"ja-JP","published_at":"2024-04-25T05:46:16.378Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/How_to_Evaluate_and_Optimize_the_Performance_of_Milvus_Storage_1f165b2c63.png","belong":"blog","authorNames":["Fendy Feng","Jay Zhu "]},{"id":"learn-178","title":"A Beginner’s Guide to Zilliz Cloud on the AWS Marketplace","image":{"id":3297,"url":"https://assets.zilliz.com/Beginner_s_Guide_to_Connecting_Zilliz_Cloud_with_AWS_Marketplace_733fdbfbd5.png"},"display_time":"Apr 24, 2024","url":"beginners-guide-to-connecting-zilliz-cloud-to-aws-marketplace","abstract":"In this article, we’ll discover how to connect Zilliz Cloud—the world’s leading vector database—with the AWS marketplace.","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":156,"name":"Jack L","author_tags":"Freelance Technical Writer","published_at":"2024-04-26T23:28:48.997Z","created_by":18,"updated_by":18,"created_at":"2024-04-26T23:28:47.560Z","updated_at":"2024-07-03T07:47:57.897Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Jack is a Freelance Technical Writer. ","locale":"en"}],"read_time":6,"localizations":[{"id":393,"locale":"ja-JP","published_at":"2024-04-28T14:06:57.060Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Beginner_s_Guide_to_Connecting_Zilliz_Cloud_with_AWS_Marketplace_733fdbfbd5.png","belong":"learn","authorNames":["Jack L"]},{"id":"blog-389","title":"RAG Without OpenAI: BentoML, OctoAI and Milvus","image":{"id":3274,"url":"https://assets.zilliz.com/RAG_Without_Open_AI_Bento_ML_Octo_AI_and_Milvus_2_febb5b5c24.png"},"display_time":"Apr 23, 2024","deploy_time":null,"url":"rag-without-open-ai-bentoml-octoai-milvus","abstract":"In this tutorial we will use BentoML to serve embeddings, OctoAI to get the LLM and Milvus as our vector database. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":41,"name":"Yujian Tang","author_tags":"Developer Advocate at Zilliz","published_at":"2023-04-20T21:52:47.479Z","created_by":18,"updated_by":18,"created_at":"2023-04-20T21:52:45.859Z","updated_at":"2024-07-18T16:02:07.497Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/yujiantang/","self_intro":"Yujian Tang is a Developer Advocate at Zilliz. He has a background as a software engineer working on AutoML at Amazon. Yujian studied Computer Science, Statistics, and Neuroscience with research papers published to conferences including IEEE Big Data. He enjoys drinking bubble tea, spending time with family, and being near water.","repost_to_medium":null,"repost_state":null,"meta_description":"Yujian Tang, Developer Advocate at Zilliz. ","locale":"en"}],"read_time":12,"localizations":[{"id":1234,"locale":"ja-JP","published_at":"2024-04-23T19:56:33.594Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/RAG_Without_Open_AI_Bento_ML_Octo_AI_and_Milvus_2_febb5b5c24.png","belong":"blog","authorNames":["Yujian Tang"]},{"id":"blog-395","title":"Spring AI and Milvus: Using Milvus as a Spring AI Vector Store","image":{"id":3332,"url":"https://assets.zilliz.com/Spring_AI_and_Milvus_Using_Milvus_as_a_Spring_AI_Vector_Store_297bf1d1d7.png"},"display_time":"Apr 22, 2024","deploy_time":null,"url":"spring-ai-and-milvus-using-milvus-as-spring-ai-vector-store","abstract":"A comprehensive guide on how to use Milvus as a Spring AI vector store ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":148,"name":"Abhiram Sharma","author_tags":"Freelance Technical Writer","published_at":"2024-04-24T21:22:31.512Z","created_by":18,"updated_by":18,"created_at":"2024-04-24T21:22:30.072Z","updated_at":"2024-07-03T07:50:07.544Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Abhiram Sharma, Freelance Technical Writer","locale":"en"}],"read_time":6,"localizations":[{"id":1265,"locale":"ja-JP","published_at":"2024-04-28T12:16:58.921Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Spring_AI_and_Milvus_Using_Milvus_as_a_Spring_AI_Vector_Store_297bf1d1d7.png","belong":"blog","authorNames":["Abhiram Sharma"]},{"id":"learn-177","title":"How to build a Retrieval-Augmented Generation (RAG) system using Llama3, Ollama, DSPy, and Milvus","image":{"id":3296,"url":"https://assets.zilliz.com/How_to_build_a_Retrieval_Augmented_Generation_RAG_system_using_Llama3_Ollama_DS_Py_and_Milvus_c5dfaea776.png"},"display_time":"Apr 22, 2024","url":"how-to-build-rag-system-using-llama3-ollama-dspy-milvus","abstract":"In this article, we aim to guide readers through constructing an RAG system using four key technologies: Llama3, Ollama, DSPy, and Milvus. First, let’s understand what they are. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":136,"name":"Shanika W.","author_tags":"Freelance Technical Writer","published_at":"2024-04-01T00:56:28.466Z","created_by":18,"updated_by":18,"created_at":"2024-04-01T00:55:44.268Z","updated_at":"2024-07-03T07:52:40.773Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Shanika W, Freelance Technical Writer","locale":"en"}],"read_time":5,"localizations":[{"id":413,"locale":"ja-JP","published_at":"2024-04-28T11:37:21.337Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/How_to_build_a_Retrieval_Augmented_Generation_RAG_system_using_Llama3_Ollama_DS_Py_and_Milvus_c5dfaea776.png","belong":"learn","authorNames":["Shanika W."]},{"id":"learn-138","title":"Integrating Vector Databases with Existing IT Infrastructure","image":{"id":3466,"url":"https://assets.zilliz.com/May9_Integrating_Vector_Databases_with_Existing_IT_Infrastructure_efa017f70c.png"},"display_time":"Apr 21, 2024","url":"integrating-vector-databases-with-existing-it-infrastructure","abstract":"As businesses navigate this dynamic AI landscape, integrating vector databases emerges as a crucial strategy for unlocking the full potential of AI-driven initiatives.","tags":[{"id":39,"name":"VectorDB 101","published_at":"2022-09-30T05:56:34.554Z","created_by":18,"updated_by":18,"created_at":"2022-09-30T05:56:31.633Z","updated_at":"2024-07-10T07:12:04.155Z","locale":"en"}],"authors":[{"id":122,"name":"Nuri Tas","author_tags":"Freelance Technical Writer","published_at":"2024-03-22T07:48:31.809Z","created_by":18,"updated_by":18,"created_at":"2024-03-22T07:48:29.574Z","updated_at":"2024-07-03T07:56:51.751Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Nuri Tas, Freelance Technical Writer","locale":"en"}],"read_time":8,"localizations":[{"id":388,"locale":"ja-JP","published_at":"2024-04-21T22:43:55.066Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/May9_Integrating_Vector_Databases_with_Existing_IT_Infrastructure_efa017f70c.png","belong":"learn","authorNames":["Nuri Tas"]},{"id":"learn-159","title":"Unlocking Content Discovery Potential with Vector Databases","image":{"id":3505,"url":"https://assets.zilliz.com/May9_Unlocking_Content_Discovery_Potential_with_Vector_Databases_2_05aa6c1124.png"},"display_time":"Apr 20, 2024","url":"unlocking-content-discovery-potential-with-vector-databases","abstract":"Semantic similarity search powered by machine learning models and vector databases, has emerged as a powerful solution, promising to transform how we navigate and unlock the full potential of our digital content.\n","tags":[{"id":39,"name":"VectorDB 101","published_at":"2022-09-30T05:56:34.554Z","created_by":18,"updated_by":18,"created_at":"2022-09-30T05:56:31.633Z","updated_at":"2024-07-10T07:12:04.155Z","locale":"en"}],"authors":[{"id":131,"name":"Samin Chandeepa","author_tags":"Freelance Technical Writer","published_at":"2024-03-29T07:49:43.838Z","created_by":18,"updated_by":18,"created_at":"2024-03-29T07:49:42.003Z","updated_at":"2024-07-03T07:53:42.149Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Samin Chandeepa, Freelance Technical Writer","locale":"en"}],"read_time":7,"localizations":[{"id":323,"locale":"ja-JP","published_at":"2024-04-21T18:07:31.721Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/May9_Unlocking_Content_Discovery_Potential_with_Vector_Databases_2_05aa6c1124.png","belong":"learn","authorNames":["Samin Chandeepa"]},{"id":"blog-387","title":"Kickstart Your Local RAG Setup: A Beginner's Guide to Using Llama 3 LangChain with Ollama and Milvus","image":{"id":3245,"url":"https://assets.zilliz.com/Apr_19_Kickstart_Your_Local_RAG_Setup_A_Beginner_s_Guide_to_Using_Llama_3_with_Ollama_Milvus_and_Langchain_418afcfd84.png"},"display_time":"Apr 19, 2024","deploy_time":null,"url":"a-beginners-guide-to-using-llama-3-with-ollama-milvus-langchain","abstract":"Hands on guide to build a Ollama, Llama 3, and Milvus RAG","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":115,"name":"Stephen Batifol","author_tags":"Developer Advocate ","published_at":"2024-03-07T03:46:04.655Z","created_by":18,"updated_by":18,"created_at":"2024-03-07T03:46:02.457Z","updated_at":"2024-07-18T15:56:42.529Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/stephen-batifol/","self_intro":"Stephen Batifol is a Developer Advocate at Zilliz. He previously worked as a Machine Learning Engineer at Wolt, where he was working on the ML Platform and as a Data Scientist at Brevo. Stephen studied Computer Science and Artificial Intelligence. He enjoys dancing and surfing. \n","repost_to_medium":null,"repost_state":null,"meta_description":"Stephen Batifol is a Developer Advocate at Zilliz.","locale":"en"}],"read_time":6,"localizations":[{"id":1463,"locale":"de","published_at":"2024-04-19T17:31:02.499Z"},{"id":1010,"locale":"ja-JP","published_at":"2024-04-19T17:31:02.499Z"},{"id":1490,"locale":"es","published_at":"2024-04-19T17:31:02.499Z"},{"id":1571,"locale":"ko","published_at":"2024-04-19T17:31:02.499Z"},{"id":1625,"locale":"fr","published_at":"2024-04-19T17:31:02.499Z"},{"id":1517,"locale":"pt","published_at":"2024-04-19T17:31:02.499Z"},{"id":1544,"locale":"ru","published_at":"2024-04-19T17:31:02.499Z"},{"id":1598,"locale":"it","published_at":"2024-04-19T17:31:02.499Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Apr_19_Kickstart_Your_Local_RAG_Setup_A_Beginner_s_Guide_to_Using_Llama_3_with_Ollama_Milvus_and_Langchain_418afcfd84.png","belong":"blog","authorNames":["Stephen Batifol"]},{"id":"learn-167","title":"Leveraging Vector Databases for Next-Level E-Commerce Personalization","image":{"id":3467,"url":"https://assets.zilliz.com/May9_Leveraging_Vector_Databases_for_Next_Level_E_Commerce_Personalization_89de8a4197.png"},"display_time":"Apr 19, 2024","url":"leveraging-vector-databases-for-next-level-ecommerce-personalization","abstract":"Explore the concepts of vector embeddings and vector databases and their role in improving the user experience in e-commerce. \n","tags":[{"id":1,"name":"Case Study","published_at":"2021-01-15T10:34:37.316Z","created_by":18,"updated_by":18,"created_at":"2021-01-15T10:34:34.857Z","updated_at":"2021-01-25T10:31:22.499Z","locale":"en"}],"authors":[{"id":125,"name":"Ruben Winastwan","author_tags":"Freelance Technical Writer","published_at":"2024-03-26T09:16:27.310Z","created_by":18,"updated_by":18,"created_at":"2024-03-26T09:16:24.498Z","updated_at":"2024-07-03T07:56:29.256Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Ruben Winastwan, Freelance Technical Writer","locale":"en"}],"read_time":10,"localizations":[{"id":429,"locale":"ja-JP","published_at":"2024-04-19T17:12:34.462Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/May9_Leveraging_Vector_Databases_for_Next_Level_E_Commerce_Personalization_89de8a4197.png","belong":"learn","authorNames":["Ruben Winastwan"]},{"id":"learn-147","title":"Ensuring High Availability of Vector Databases","image":{"id":3038,"url":"https://assets.zilliz.com/Ensuring_High_Availability_of_Vector_Databases_4a20b55435.png"},"display_time":"Apr 18, 2024","url":"ensuring-high-availability-of-vector-databases","abstract":"Ensuring high availability is crucial for the operation of vector databases, especially in applications where downtime translates directly into lost productivity and revenue. \n","tags":[{"id":39,"name":"VectorDB 101","published_at":"2022-09-30T05:56:34.554Z","created_by":18,"updated_by":18,"created_at":"2022-09-30T05:56:31.633Z","updated_at":"2024-07-10T07:12:04.155Z","locale":"en"}],"authors":[{"id":45,"name":"Fendy Feng","author_tags":"Technical Marketing Writer","published_at":"2023-05-16T01:36:15.102Z","created_by":18,"updated_by":18,"created_at":"2023-05-16T00:04:12.065Z","updated_at":"2024-04-25T08:37:19.712Z","home_page":"GitHub","home_page_link":"https://www.linkedin.com/in/fendy311/","self_intro":"Fendy Feng is the Technical Marketing Writer at Zilliz. She has extensive experience developing and enhancing the impact of open-source projects in various global markets by producing high-quality, tailored content. Before joining Zilliz, Fendy worked as a Content Strategist at PingCAP, a fast-growing E-Series startup renowned for its open-source distributed SQL database.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"},{"id":144,"name":"Yanliang Qiao","author_tags":"Senior Quality Assurance Engineer at Zilliz","published_at":"2024-04-19T14:40:52.987Z","created_by":18,"updated_by":18,"created_at":"2024-04-19T14:40:46.052Z","updated_at":"2024-07-03T07:50:52.089Z","home_page":null,"home_page_link":null,"self_intro":"Yanliang Qiao is a Senior Quality Assurance Engineer at Zilliz. ","repost_to_medium":null,"repost_state":null,"meta_description":"Yanliang Qiao, Senior Quality Assurance Engineer at Zilliz","locale":"en"}],"read_time":6,"localizations":[{"id":378,"locale":"ja-JP","published_at":"2024-04-20T20:05:22.833Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Ensuring_High_Availability_of_Vector_Databases_4a20b55435.png","belong":"learn","authorNames":["Fendy Feng","Yanliang Qiao"]},{"id":"learn-166","title":"Ranking Models: What Are They and When to Use Them? ","image":{"id":3241,"url":"https://assets.zilliz.com/Ranking_Models_What_are_they_and_when_to_use_them_5dcf60750f.png"},"display_time":"Apr 18, 2024","url":"ranking-models-what-are-they-and-when-to-use-them","abstract":"Explore different ranking algorithms, their usage, and best practices. Uncover the real-world success stories of ranking algorithms and their evolution over time.\n","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":118,"name":" Haziqa Sajid","author_tags":"Freelance Technical Writer","published_at":"2024-03-12T10:25:34.265Z","created_by":18,"updated_by":18,"created_at":"2024-03-12T10:25:31.148Z","updated_at":"2024-07-03T07:58:27.010Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/haziqa-sajid-22b53245/","self_intro":"Digital Storytelling for Data, AI, B2B \u0026 SaaS","repost_to_medium":null,"repost_state":null,"meta_description":" Haziqa Sajid, Freelance Technical Writer","locale":"en"}],"read_time":14,"localizations":[{"id":418,"locale":"ja-JP","published_at":"2024-04-19T05:15:53.737Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Ranking_Models_What_are_they_and_when_to_use_them_5dcf60750f.png","belong":"learn","authorNames":[" Haziqa Sajid"]},{"id":"blog-385","title":"Milvus Server Docker Installation and Packaging Dependencies","image":{"id":3239,"url":"https://assets.zilliz.com/Milvus_Server_Docker_Installation_and_Packaging_Dependencies_6e58219622.png"},"display_time":"Apr 17, 2024","deploy_time":null,"url":"Milvus-server-docker-installation-and-packaging-dependencies","abstract":"This post introduces key dependencies and release update frequency for deploying the Milvus server on standalone Docker. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":94,"name":"Christy Bergman","author_tags":"Developer Advocate","published_at":"2023-10-06T00:29:45.486Z","created_by":18,"updated_by":18,"created_at":"2023-10-06T00:29:30.751Z","updated_at":"2024-07-18T16:01:45.942Z","home_page":null,"home_page_link":null,"self_intro":"Christy Bergman is a passionate Developer Advocate at Zilliz. She previously worked in distributed computing at Anyscale and as a Specialist AI/ML Solutions Architect at AWS. Christy studied applied math, is a self-taught coder, and has published papers, including one with ACM Recsys. She enjoys hiking and bird watching.","repost_to_medium":null,"repost_state":null,"meta_description":"Christy Bergman is a passionate Developer Advocate at Zilliz. ","locale":"en"}],"read_time":3,"localizations":[{"id":863,"locale":"ja-JP","published_at":"2024-04-19T03:45:05.851Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Milvus_Server_Docker_Installation_and_Packaging_Dependencies_6e58219622.png","belong":"blog","authorNames":["Christy Bergman"]},{"id":"learn-136","title":"Safeguarding Data: Security and Privacy in Vector Database Systems","image":{"id":3808,"url":"https://assets.zilliz.com/Apr_28_Safeguarding_Data_Security_and_Privacy_in_Vector_Database_Systems_b33ab569b1.png"},"display_time":"Apr 17, 2024","url":"safeguarding-data-security-and-privacy-in-vector-database-systems","abstract":"As our world becomes increasingly digital and shaped by ML and AI services, the role of vector databases like Milvus and managed services like Zilliz Cloud becomes ever more crucial. With data providing so much power, it is paramount to prioritize robust data security and privacy measures. \n","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":143,"name":"Daniella Pontes","author_tags":"Freelance Technical Writer","published_at":"2024-04-19T03:52:05.346Z","created_by":18,"updated_by":18,"created_at":"2024-04-19T03:52:03.759Z","updated_at":"2024-07-03T07:58:01.528Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Daniella Pontes, Freelance Technical Writer","locale":"en"}],"read_time":6,"localizations":[{"id":424,"locale":"ja-JP","published_at":"2024-04-19T03:53:52.859Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Apr_28_Safeguarding_Data_Security_and_Privacy_in_Vector_Database_Systems_b33ab569b1.png","belong":"learn","authorNames":["Daniella Pontes"]},{"id":"blog-384","title":"Emerging Trends in Vector Database Research and Development","image":{"id":3237,"url":"https://assets.zilliz.com/Emerging_Trends_in_Vector_Database_Research_and_Development_479ae818c8.png"},"display_time":"Apr 16, 2024","deploy_time":null,"url":"emerging-trends-in-vector-database-research-and-development","abstract":"This post discusses the development and anticipated future of vector databases from both technical and practical perspectives, focusing on cost-efficiency and business requirements.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":70,"name":"Li Liu","author_tags":"Principal Engineer","published_at":"2023-06-15T05:16:42.032Z","created_by":18,"updated_by":18,"created_at":"2023-06-15T05:15:15.087Z","updated_at":"2024-07-18T15:59:40.729Z","home_page":"GitHub","home_page_link":"https://github.com/liliu-z","self_intro":"Li Liu is the Principal Engineer at Zilliz, leading the vector searching research and development. Before joining Zilliz, he was a Senior Engineer at Meta, designing and shaping numerous advertising stream data frameworks. With a Master's degree from Carnegie Mellon University, he boasts extensive experience in databases and big data. Li Liu's expertise in technology and innovation continues to drive advancements in vector searching, leaving a lasting impact on the field.\n","repost_to_medium":null,"repost_state":null,"meta_description":"Li Liu is the Principal Engineer at Zilliz, leading the vector searching research and development.","locale":"en"}],"read_time":9,"localizations":[{"id":974,"locale":"ja-JP","published_at":"2024-04-18T07:02:29.519Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Emerging_Trends_in_Vector_Database_Research_and_Development_479ae818c8.png","belong":"blog","authorNames":["Li Liu"]},{"id":"blog-388","title":"Streamlining Data Processing with Zilliz Cloud Pipelines: A Deep Dive into Document Chunking","image":{"id":3265,"url":"https://assets.zilliz.com/Streamlining_Data_Processing_with_Zilliz_Cloud_Pipelines_A_Deep_Dive_into_Document_Chunking_ccf3e61191.png"},"display_time":"Apr 16, 2024","deploy_time":null,"url":"streamling-data-processing-with-zilliz-cloud-pipelines-a-deep-dive-into-document-chunking","abstract":"Zilliz Cloud Pipelines play a role in simplifying the document chunking process and enhancing search-ability for RAG applications.","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":133,"name":"Ehsanullah Baig","author_tags":"Freelance Technical Writer","published_at":"2024-03-31T17:41:49.656Z","created_by":18,"updated_by":18,"created_at":"2024-03-31T17:28:32.019Z","updated_at":"2024-07-03T07:53:19.713Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Ehsanullah Baig, Freelance Technical Writer","locale":"en"}],"read_time":13,"localizations":[{"id":1339,"locale":"ja-JP","published_at":"2024-04-23T06:30:53.993Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Streamlining_Data_Processing_with_Zilliz_Cloud_Pipelines_A_Deep_Dive_into_Document_Chunking_ccf3e61191.png","belong":"blog","authorNames":["Ehsanullah Baig"]},{"id":"blog-383","title":"The Evolution and Future of AI and Its Influence on Vector Databases: Insights from Charles, CEO of Zilliz ","image":{"id":3163,"url":"https://assets.zilliz.com/The_Evolution_and_Future_of_AI_3d435bb1b9.png"},"display_time":"Apr 15, 2024","deploy_time":"2024-04-15T17:00:00.000Z","url":"the-evolution-and-future-of-ai-and-its-influence-on-vector-databases-zilliz-ceo-charles-xie","abstract":"The Future of AI: The Rise of Affordable General Intelligence within Five Years","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":114,"name":"Charles Xie","author_tags":"Founder \u0026 CEO of Zilliz","published_at":"2024-02-07T19:12:09.772Z","created_by":18,"updated_by":18,"created_at":"2024-02-07T19:11:20.296Z","updated_at":"2024-02-07T19:12:09.793Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/chaoxie/","self_intro":"Charles Xie is the founder and CEO of Zilliz, focusing on building next-generation databases and search technologies for AI and LLMs applications. At Zilliz, he also invented Milvus, the world's most popular open-source vector database for production-ready AI. He is currently a board member of LF AI \u0026 Data Foundation and served as the board's chairperson in 2020 and 2021. Charles previously worked at Oracle as a founding engineer of the Oracle 12c cloud database project. Charles holds a master’s degree in computer science from the University of Wisconsin-Madison.\n","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":7,"localizations":[{"id":1055,"locale":"ja-JP","published_at":"2024-04-15T16:56:31.963Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/The_Evolution_and_Future_of_AI_3d435bb1b9.png","belong":"blog","authorNames":["Charles Xie"]},{"id":"learn-168","title":"Exploring BGE-M3: The Future of Information Retrieval with Milvus","image":{"id":3246,"url":"https://assets.zilliz.com/Exploring_BGE_M3_The_Future_of_Information_Retrieval_with_Milvus_b626ec4df3.png"},"display_time":"Apr 15, 2024","url":"Exploring-BGE-M3-the-future-of-information-retrieval-with-milvus","abstract":"The potential of BGE-M3 and Milvus is limitless, offering vast opportunities for innovation in virtually any field that relies on information retrieval.","tags":[],"authors":[{"id":132,"name":"Rahul ","author_tags":"Freelance Technical Writer","published_at":"2024-03-30T21:57:22.495Z","created_by":18,"updated_by":18,"created_at":"2024-03-30T21:57:19.140Z","updated_at":"2024-07-03T07:53:30.991Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Rahul, Freelance Technical Writer","locale":"en"}],"read_time":11,"localizations":[{"id":407,"locale":"ja-JP","published_at":"2024-04-20T21:20:50.389Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Exploring_BGE_M3_The_Future_of_Information_Retrieval_with_Milvus_b626ec4df3.png","belong":"learn","authorNames":["Rahul "]},{"id":"learn-154","title":"Vector Library vs Vector Database: Which One is Right for You?","image":{"id":3049,"url":"https://assets.zilliz.com/Vector_Library_versus_Vector_Database_1_b5324c8198.png"},"display_time":"Apr 14, 2024","url":"vector-library-versus-vector-database","abstract":"Dive into the differences between these two technologies, their strengths, and their practical applications, providing developers with a comprehensive guide to choosing the right tool for their AI projects.\n","tags":[{"id":39,"name":"VectorDB 101","published_at":"2022-09-30T05:56:34.554Z","created_by":18,"updated_by":18,"created_at":"2022-09-30T05:56:31.633Z","updated_at":"2024-07-10T07:12:04.155Z","locale":"en"}],"authors":[{"id":136,"name":"Shanika W.","author_tags":"Freelance Technical Writer","published_at":"2024-04-01T00:56:28.466Z","created_by":18,"updated_by":18,"created_at":"2024-04-01T00:55:44.268Z","updated_at":"2024-07-03T07:52:40.773Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Shanika W, Freelance Technical Writer","locale":"en"}],"read_time":10,"localizations":[{"id":341,"locale":"ja-JP","published_at":"2024-04-14T23:01:07.312Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Vector_Library_versus_Vector_Database_1_b5324c8198.png","belong":"learn","authorNames":["Shanika W."]},{"id":"learn-165","title":"How to Enhance the Performance of Your RAG Pipeline","image":{"id":3181,"url":"https://assets.zilliz.com/How_to_Enhance_the_Performance_of_Your_RAG_Pipeline_be0465d785.png"},"display_time":"Apr 14, 2024","url":"how-to-enhance-the-performance-of-your-rag-pipeline","abstract":"This article summarizes various popular approaches to enhancing the performance of your RAG applications. We also provided clear illustrations to help you quickly understand these concepts and techniques and expedite their implementation and optimization. \n","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":107,"name":"Cheney Zhang","author_tags":"Algorithm Engineer","published_at":"2023-11-08T07:21:13.405Z","created_by":18,"updated_by":18,"created_at":"2023-11-08T07:21:10.513Z","updated_at":"2024-07-18T15:56:58.028Z","home_page":"GitHub","home_page_link":"https://github.com/zc277584121","self_intro":"Cheney Zhang is an accomplished Algorithm Engineer at Zilliz. With a profound passion for and expertise in cutting-edge AI technologies such as LLMs and Retrieval Augmented Generation (RAG), Cheney has actively contributed to many innovative AI projects, including Towhee, Akcio, and OSSChat. Before joining Zilliz, he worked for CMB Network Technology as an Algorithm Engineer. Cheney holds a master's degree from Nanjing University of Aeronautics and Astronautics.","repost_to_medium":null,"repost_state":null,"meta_description":"Cheney Zhang is an accomplished Algorithm Engineer at Zilliz. ","locale":"en"}],"read_time":8,"localizations":[{"id":420,"locale":"ja-JP","published_at":"2024-04-15T17:27:35.563Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/How_to_Enhance_the_Performance_of_Your_RAG_Pipeline_be0465d785.png","belong":"learn","authorNames":["Cheney Zhang"]},{"id":"learn-151","title":"The Role of Vector Databases in Predictive Analytics","image":{"id":3045,"url":"https://assets.zilliz.com/Leveraging_Vector_Databases_in_Predictive_Analytics_2dcfffd404.png"},"display_time":"Apr 13, 2024","url":"leveraging-vector-databases-in-predictive-analytics","abstract":"Explore how vector databases enhance Predictive Models and their applications. ","tags":[{"id":1,"name":"Case Study","published_at":"2021-01-15T10:34:37.316Z","created_by":18,"updated_by":18,"created_at":"2021-01-15T10:34:34.857Z","updated_at":"2021-01-25T10:31:22.499Z","locale":"en"}],"authors":[{"id":36,"name":"Chris Churilo","author_tags":"VP of Marketing","published_at":"2023-04-11T16:51:05.002Z","created_by":18,"updated_by":53,"created_at":"2023-04-11T16:42:46.067Z","updated_at":"2025-01-16T22:35:53.011Z","home_page":"GitHub","home_page_link":"https://github.com/ChrisChurilo","self_intro":"Chris Churilo is the VP of Marketing \u0026 Community at Zilliz where she leads all community, developer relations, and marketing efforts. Prior to Zilliz, Chris was a founding member of the InfluxData’s go to market efforts and helped propel the time series database platform to dominance in the market. In earlier roles she defined and designed a SaaS monitoring solution at Centroid, and prior to that she was the VP of product management at iPass and was the LOB for several cloud services that required her to track the business and operational metrics and analytics to help identify and resolve issues.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":7,"localizations":[{"id":416,"locale":"ja-JP","published_at":"2024-04-29T11:58:55.653Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Leveraging_Vector_Databases_in_Predictive_Analytics_2dcfffd404.png","belong":"learn","authorNames":["Chris Churilo"]},{"id":"learn-149","title":"Creating Personalized User Experiences through Vector Databases","image":{"id":3043,"url":"https://assets.zilliz.com/Creating_Personalized_User_Experiences_through_Vector_Databases_eabd3aec9b.png"},"display_time":"Apr 13, 2024","url":"creating-personalized-user-experiences-through-vector-databases","abstract":"Explore how vector databases enhance personalized user experiences ","tags":[{"id":1,"name":"Case Study","published_at":"2021-01-15T10:34:37.316Z","created_by":18,"updated_by":18,"created_at":"2021-01-15T10:34:34.857Z","updated_at":"2021-01-25T10:31:22.499Z","locale":"en"}],"authors":[{"id":36,"name":"Chris Churilo","author_tags":"VP of Marketing","published_at":"2023-04-11T16:51:05.002Z","created_by":18,"updated_by":53,"created_at":"2023-04-11T16:42:46.067Z","updated_at":"2025-01-16T22:35:53.011Z","home_page":"GitHub","home_page_link":"https://github.com/ChrisChurilo","self_intro":"Chris Churilo is the VP of Marketing \u0026 Community at Zilliz where she leads all community, developer relations, and marketing efforts. Prior to Zilliz, Chris was a founding member of the InfluxData’s go to market efforts and helped propel the time series database platform to dominance in the market. In earlier roles she defined and designed a SaaS monitoring solution at Centroid, and prior to that she was the VP of product management at iPass and was the LOB for several cloud services that required her to track the business and operational metrics and analytics to help identify and resolve issues.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":8,"localizations":[{"id":408,"locale":"ja-JP","published_at":"2024-04-29T11:51:47.656Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Creating_Personalized_User_Experiences_through_Vector_Databases_eabd3aec9b.png","belong":"learn","authorNames":["Chris Churilo"]},{"id":"blog-382","title":"Embedding Inference at Scale for RAG Applications with Ray Data and Milvus","image":{"id":3158,"url":"https://assets.zilliz.com/Apr_10_Embedding_Inference_at_Scale_for_RAG_Apps_with_Ray_Data_and_Milvus_9837b89112.png"},"display_time":"Apr 12, 2024","deploy_time":null,"url":"embedding-inference-at-scale-for-RAG-app-with-ray-data-and-milvus","abstract":"This blog showed how to use Ray Data and Milvus Bulk Import features to significantly speed up the vector generation and efficiently batch load them into a vector database. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":142,"name":"Cheng Su","author_tags":"Manager of the Data team at Anyscale. ","published_at":"2024-04-12T16:36:00.791Z","created_by":18,"updated_by":18,"created_at":"2024-04-12T16:35:58.433Z","updated_at":"2024-07-03T06:53:49.844Z","home_page":null,"home_page_link":null,"self_intro":"Cheng Su is the manager of the Data team at Anyscale, a committer of the Ray open source project (https://github.com/ray-project/ray), and the code owner of the Ray Data module. Previously, Cheng Su worked in the Data Infrastructure teams at Meta, Spark, and Hadoop. ","repost_to_medium":null,"repost_state":null,"meta_description":"Cheng Su is the manager of the Data team at Anyscale. ","locale":"en"},{"id":94,"name":"Christy Bergman","author_tags":"Developer Advocate","published_at":"2023-10-06T00:29:45.486Z","created_by":18,"updated_by":18,"created_at":"2023-10-06T00:29:30.751Z","updated_at":"2024-07-18T16:01:45.942Z","home_page":null,"home_page_link":null,"self_intro":"Christy Bergman is a passionate Developer Advocate at Zilliz. She previously worked in distributed computing at Anyscale and as a Specialist AI/ML Solutions Architect at AWS. Christy studied applied math, is a self-taught coder, and has published papers, including one with ACM Recsys. She enjoys hiking and bird watching.","repost_to_medium":null,"repost_state":null,"meta_description":"Christy Bergman is a passionate Developer Advocate at Zilliz. ","locale":"en"}],"read_time":8,"localizations":[{"id":1040,"locale":"ja-JP","published_at":"2024-04-12T16:36:26.171Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Apr_10_Embedding_Inference_at_Scale_for_RAG_Apps_with_Ray_Data_and_Milvus_9837b89112.png","belong":"blog","authorNames":["Cheng Su","Christy Bergman"]},{"id":"learn-158","title":"Deploying Vector Databases in Multi-Cloud Environments","image":{"id":3468,"url":"https://assets.zilliz.com/May_8_Deploying_Vector_Databases_in_Multi_Cloud_Environments_8d2d6ae2b0.png"},"display_time":"Apr 12, 2024","url":"Deploying-Vector-Databases-in-Multi-Cloud-Environments","abstract":"Multi-cloud deployment has become increasingly popular for services looking for as much uptime as possible, with organizations leveraging multiple cloud providers to optimize performance, reliability, and cost-efficiency.","tags":[{"id":39,"name":"VectorDB 101","published_at":"2022-09-30T05:56:34.554Z","created_by":18,"updated_by":18,"created_at":"2022-09-30T05:56:31.633Z","updated_at":"2024-07-10T07:12:04.155Z","locale":"en"}],"authors":[{"id":3,"name":"Frank Liu","author_tags":"Director of Operations \u0026 ML Architect at Zilliz","published_at":"2021-12-23T11:08:08.015Z","created_by":18,"updated_by":18,"created_at":"2021-12-23T10:40:59.821Z","updated_at":"2023-04-21T22:30:10.416Z","home_page":"GitHub","home_page_link":"https://github.com/fzliu","self_intro":"Frank Liu is the Director of Operations \u0026 ML Architect at Zilliz, where he serves as a maintainer for the Towhee open-source project. Prior to Zilliz, Frank co-founded Orion Innovations, an ML-powered indoor positioning startup based in Shanghai and worked as an ML engineer at Yahoo in San Francisco. In his free time, Frank enjoys playing chess, swimming, and powerlifting. Frank holds MS and BS degrees in Electrical Engineering from Stanford University. ","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":5,"localizations":[{"id":444,"locale":"ja-JP","published_at":"2024-04-14T16:12:40.900Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/May_8_Deploying_Vector_Databases_in_Multi_Cloud_Environments_8d2d6ae2b0.png","belong":"learn","authorNames":["Frank Liu"]},{"id":"blog-381","title":"Monitoring Milvus with Grafana and Loki","image":{"id":3116,"url":"https://assets.zilliz.com/Monitoring_Milvus_with_Grafana_and_Loki_1_58f07e3bff.png"},"display_time":"Apr 11, 2024","deploy_time":"2024-04-11T19:00:00.000Z","url":"monitoring-in-milvus-with-grafana-and-loki","abstract":"This post guides you through setting up Grafana and Loki to monitor your Milvus deployments effectively. \n","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":115,"name":"Stephen Batifol","author_tags":"Developer Advocate ","published_at":"2024-03-07T03:46:04.655Z","created_by":18,"updated_by":18,"created_at":"2024-03-07T03:46:02.457Z","updated_at":"2024-07-18T15:56:42.529Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/stephen-batifol/","self_intro":"Stephen Batifol is a Developer Advocate at Zilliz. He previously worked as a Machine Learning Engineer at Wolt, where he was working on the ML Platform and as a Data Scientist at Brevo. Stephen studied Computer Science and Artificial Intelligence. He enjoys dancing and surfing. \n","repost_to_medium":null,"repost_state":null,"meta_description":"Stephen Batifol is a Developer Advocate at Zilliz.","locale":"en"}],"read_time":6,"localizations":[{"id":1325,"locale":"ja-JP","published_at":"2024-04-11T21:35:39.384Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Monitoring_Milvus_with_Grafana_and_Loki_1_58f07e3bff.png","belong":"blog","authorNames":["Stephen Batifol"]},{"id":"learn-160","title":"What are Private LLMs? Running Large Language Models Privately - privateGPT and Beyond","image":{"id":3056,"url":"https://assets.zilliz.com/What_are_Private_LL_Ms_Running_Large_Language_Models_Privately_private_GPT_and_Beyond_a3d0da1958.png"},"display_time":"Apr 11, 2024","url":"what-are-private-llms","abstract":"Private LLMs enhance data control through customization to meet organizational policies and privacy needs, ensuring legal compliance and minimizing risks like data breaches. Operating in a secure environment, they reduce third-party access, protecting sensitive data from unauthorized exposure. Private LLMs can be designed to integrate seamlessly with an organization's existing systems, networks, and databases. Organizations can implement tailored security measures in private LLMs to protect sensitive information.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":132,"name":"Rahul ","author_tags":"Freelance Technical Writer","published_at":"2024-03-30T21:57:22.495Z","created_by":18,"updated_by":18,"created_at":"2024-03-30T21:57:19.140Z","updated_at":"2024-07-03T07:53:30.991Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Rahul, Freelance Technical Writer","locale":"en"}],"read_time":11,"localizations":[{"id":367,"locale":"ja-JP","published_at":"2024-04-11T22:36:50.706Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/What_are_Private_LL_Ms_Running_Large_Language_Models_Privately_private_GPT_and_Beyond_a3d0da1958.png","belong":"learn","authorNames":["Rahul "]},{"id":"learn-73","title":"Understanding Faiss (Facebook AI Similarity Search) ","image":{"id":2285,"url":"https://assets.zilliz.com/Nov_30_Mastering_Efficient_Similarity_Search_with_FAISS_Library_c91bb8c295.png"},"display_time":"Apr 10, 2024","url":"faiss","abstract":"Faiss (Facebook AI similarity search) is an open-source library for efficient similarity search of unstructured data and clustering of dense vectors. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":36,"name":"Chris Churilo","author_tags":"VP of Marketing","published_at":"2023-04-11T16:51:05.002Z","created_by":18,"updated_by":53,"created_at":"2023-04-11T16:42:46.067Z","updated_at":"2025-01-16T22:35:53.011Z","home_page":"GitHub","home_page_link":"https://github.com/ChrisChurilo","self_intro":"Chris Churilo is the VP of Marketing \u0026 Community at Zilliz where she leads all community, developer relations, and marketing efforts. Prior to Zilliz, Chris was a founding member of the InfluxData’s go to market efforts and helped propel the time series database platform to dominance in the market. In earlier roles she defined and designed a SaaS monitoring solution at Centroid, and prior to that she was the VP of product management at iPass and was the LOB for several cloud services that required her to track the business and operational metrics and analytics to help identify and resolve issues.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":9,"localizations":[{"id":390,"locale":"ja-JP","published_at":"2023-11-29T07:59:03.996Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Nov_30_Mastering_Efficient_Similarity_Search_with_FAISS_Library_c91bb8c295.png","belong":"learn","authorNames":["Chris Churilo"]},{"id":"learn-163","title":" Demystifying Color Histograms: A Guide to Image Processing and Analysis","image":{"id":3118,"url":"https://assets.zilliz.com/Demystifying_Color_Histograms_A_Guide_to_Image_Processing_and_Analysis_1_d745a9a0bf.png"},"display_time":"Apr 10, 2024","url":"demystifying-color-histograms","abstract":"Mastering color histograms is indispensable for anyone involved in image processing and analysis. By understanding the nuances of color distributions and leveraging advanced techniques, practitioners can unlock the full potential of color histograms in various imaging projects and research endeavors.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":118,"name":" Haziqa Sajid","author_tags":"Freelance Technical Writer","published_at":"2024-03-12T10:25:34.265Z","created_by":18,"updated_by":18,"created_at":"2024-03-12T10:25:31.148Z","updated_at":"2024-07-03T07:58:27.010Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/haziqa-sajid-22b53245/","self_intro":"Digital Storytelling for Data, AI, B2B \u0026 SaaS","repost_to_medium":null,"repost_state":null,"meta_description":" Haziqa Sajid, Freelance Technical Writer","locale":"en"}],"read_time":7,"localizations":[{"id":401,"locale":"ja-JP","published_at":"2024-04-11T22:07:35.374Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Demystifying_Color_Histograms_A_Guide_to_Image_Processing_and_Analysis_1_d745a9a0bf.png","belong":"learn","authorNames":[" Haziqa Sajid"]},{"id":"learn-145","title":"How to Spot Search Performance Bottleneck in Vector Databases","image":{"id":3036,"url":"https://assets.zilliz.com/How_to_Spot_Search_Performance_Bottleneck_in_Vector_Databases_d2c2bd005d.png"},"display_time":"Apr 10, 2024","url":"how-to-spot-search-performance-bottleneck-in-vector-databases","abstract":"Learn how to monitor search performance, spot bottlenecks, and optimize the performance in a vector database like Milvus.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":89,"name":"Patrick Xu","author_tags":"Senior Software Engineer","published_at":"2023-09-22T16:07:01.562Z","created_by":18,"updated_by":18,"created_at":"2023-09-22T16:06:57.605Z","updated_at":"2023-09-22T16:07:01.586Z","home_page":null,"home_page_link":null,"self_intro":"Senior Software Engineer","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":13,"localizations":[{"id":409,"locale":"ja-JP","published_at":"2024-04-12T00:20:48.575Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/How_to_Spot_Search_Performance_Bottleneck_in_Vector_Databases_d2c2bd005d.png","belong":"learn","authorNames":["Patrick Xu"]},{"id":"learn-146","title":"Exploring OpenAI CLIP: The Future of Multi-Modal AI Learning","image":{"id":3037,"url":"https://assets.zilliz.com/Exploring_Open_AI_CLIP_The_Future_of_Multi_Modal_AI_Learning_a4cabc500a.png"},"display_time":"Apr 10, 2024","url":"exploring-openai-clip-the-future-of-multimodal-ai-learning","abstract":"This article will explore CLIP's inner workings and potential in multimodal learning, with a particular focus on the clip-vit-base-patch32 variant.\n","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":118,"name":" Haziqa Sajid","author_tags":"Freelance Technical Writer","published_at":"2024-03-12T10:25:34.265Z","created_by":18,"updated_by":18,"created_at":"2024-03-12T10:25:31.148Z","updated_at":"2024-07-03T07:58:27.010Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/haziqa-sajid-22b53245/","self_intro":"Digital Storytelling for Data, AI, B2B \u0026 SaaS","repost_to_medium":null,"repost_state":null,"meta_description":" Haziqa Sajid, Freelance Technical Writer","locale":"en"}],"read_time":8,"localizations":[{"id":415,"locale":"ja-JP","published_at":"2024-04-10T23:44:01.378Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Exploring_Open_AI_CLIP_The_Future_of_Multi_Modal_AI_Learning_a4cabc500a.png","belong":"learn","authorNames":[" Haziqa Sajid"]},{"id":"learn-156","title":"Maximizing GPT 4.x's Potential Through Fine-Tuning Techniques","image":{"id":3052,"url":"https://assets.zilliz.com/Maximizing_GPT_4_x_s_Potential_Through_Fine_Tuning_Techniques_b21401944a.png"},"display_time":"Apr 10, 2024","url":"maximizing-gpt-4-potential-through-fine-tuning-techniques","abstract":"This article explores the real potential of GPT 4.x, highlighting its advanced powers and the critical role of fine-tuning in making the model suitable for specific applications. ","tags":[{"id":39,"name":"VectorDB 101","published_at":"2022-09-30T05:56:34.554Z","created_by":18,"updated_by":18,"created_at":"2022-09-30T05:56:31.633Z","updated_at":"2024-07-10T07:12:04.155Z","locale":"en"}],"authors":[{"id":133,"name":"Ehsanullah Baig","author_tags":"Freelance Technical Writer","published_at":"2024-03-31T17:41:49.656Z","created_by":18,"updated_by":18,"created_at":"2024-03-31T17:28:32.019Z","updated_at":"2024-07-03T07:53:19.713Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Ehsanullah Baig, Freelance Technical Writer","locale":"en"}],"read_time":8,"localizations":[{"id":471,"locale":"ja-JP","published_at":"2024-04-11T21:30:56.652Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Maximizing_GPT_4_x_s_Potential_Through_Fine_Tuning_Techniques_b21401944a.png","belong":"learn","authorNames":["Ehsanullah Baig"]},{"id":"learn-164","title":"Enhancing Information Retrieval with Learned Sparse Retrieval","image":{"id":3119,"url":"https://assets.zilliz.com/Enhancing_Information_Retrieval_with_Learned_Sparse_Embeddings_a89ddba8f8.png"},"display_time":"Apr 09, 2024","url":"enhancing-information-retrieval-learned-sparse-embeddings","abstract":"Explore the inner workings, advantages, and practical applications of learned sparse embeddings with the Milvus vector database","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":141,"name":"Buqian Zheng ","author_tags":"Senior Software Engineer","published_at":"2024-04-11T22:45:30.022Z","created_by":18,"updated_by":18,"created_at":"2024-04-11T22:45:27.515Z","updated_at":"2024-07-18T15:57:36.555Z","home_page":null,"home_page_link":null,"self_intro":"Buqian Zheng is a Senior Software Engineer at Zilliz, specializing in developing the core vector index engine of Milvus. Before joining Zilliz, he was a Software Engineer at Google, where he contributed to projects such as Google Cloud Dataflow and managed Google-scale data analytic services. With a wealth of industry experience in managing massive data and infrastructures, Buqian brings invaluable expertise to his role. He holds a Master’s degree from Carnegie Mellon University.","repost_to_medium":null,"repost_state":null,"meta_description":"Buqian Zheng, Senior Software Engineer at Zilliz","locale":"en"}],"read_time":16,"localizations":[{"id":326,"locale":"ja-JP","published_at":"2024-04-11T22:54:33.030Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Enhancing_Information_Retrieval_with_Learned_Sparse_Embeddings_a89ddba8f8.png","belong":"learn","authorNames":["Buqian Zheng "]},{"id":"learn-142","title":"Hybrid Search: Combining Text and Image for Enhanced Search Capabilities","image":{"id":3033,"url":"https://assets.zilliz.com/Hybrid_Search_Combining_Text_and_Image_for_Enhanced_Search_Capabilities_c5065add79.png"},"display_time":"Apr 09, 2024","url":"hybrid-search-combining-text-and-image","abstract":"Milvus enables hybrid sparse and dense vector search and multi-vector search capabilities, simplifying the vectorization and search process.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":3,"name":"Frank Liu","author_tags":"Director of Operations \u0026 ML Architect at Zilliz","published_at":"2021-12-23T11:08:08.015Z","created_by":18,"updated_by":18,"created_at":"2021-12-23T10:40:59.821Z","updated_at":"2023-04-21T22:30:10.416Z","home_page":"GitHub","home_page_link":"https://github.com/fzliu","self_intro":"Frank Liu is the Director of Operations \u0026 ML Architect at Zilliz, where he serves as a maintainer for the Towhee open-source project. Prior to Zilliz, Frank co-founded Orion Innovations, an ML-powered indoor positioning startup based in Shanghai and worked as an ML engineer at Yahoo in San Francisco. In his free time, Frank enjoys playing chess, swimming, and powerlifting. Frank holds MS and BS degrees in Electrical Engineering from Stanford University. ","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":8,"localizations":[{"id":402,"locale":"ja-JP","published_at":"2024-04-10T07:15:54.864Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Hybrid_Search_Combining_Text_and_Image_for_Enhanced_Search_Capabilities_c5065add79.png","belong":"learn","authorNames":["Frank Liu"]},{"id":"learn-161","title":"Time Series Embedding in Data Analysis","image":{"id":3093,"url":"https://assets.zilliz.com/Time_Series_Embedding_in_Data_Analysis_6af5b6513e.png"},"display_time":"Apr 09, 2024","url":"time-series-embedding-data-analysis","abstract":"Learn about time series data including general concepts and preprocessing methods to transform time series data into an embedding suitable for forecasting tasks.","tags":[{"id":39,"name":"VectorDB 101","published_at":"2022-09-30T05:56:34.554Z","created_by":18,"updated_by":18,"created_at":"2022-09-30T05:56:31.633Z","updated_at":"2024-07-10T07:12:04.155Z","locale":"en"}],"authors":[{"id":125,"name":"Ruben Winastwan","author_tags":"Freelance Technical Writer","published_at":"2024-03-26T09:16:27.310Z","created_by":18,"updated_by":18,"created_at":"2024-03-26T09:16:24.498Z","updated_at":"2024-07-03T07:56:29.256Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Ruben Winastwan, Freelance Technical Writer","locale":"en"}],"read_time":14,"localizations":[{"id":405,"locale":"ja-JP","published_at":"2024-04-10T05:08:10.177Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Time_Series_Embedding_in_Data_Analysis_6af5b6513e.png","belong":"learn","authorNames":["Ruben Winastwan"]},{"id":"blog-380","title":"The Cost of Open Source Vector Databases: An Engineer’s Guide to DYI Pricing","image":{"id":3469,"url":"https://assets.zilliz.com/May9_The_Cost_of_Open_Source_Vector_Databases_An_Engineer_s_Guide_to_DYI_Pricing_1_9f559018b4.png"},"display_time":"Apr 08, 2024","deploy_time":null,"url":"cost-of-open-source-vector-databases-an-engineer-guide","abstract":"The blog evaluates the costs of using open-source vector databases like Milvus, noting that initial savings can lead to higher expenses as projects grow. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":76,"name":"Steffi Li","author_tags":"Director of Product Marketing","published_at":"2023-07-13T17:18:42.023Z","created_by":18,"updated_by":18,"created_at":"2023-07-13T17:16:54.449Z","updated_at":"2023-07-13T17:18:42.070Z","home_page":null,"home_page_link":null,"self_intro":"Steffi is the Director of Product Marketing at Zilliz, with prior experience leading the GTM strategies for open-source data technologies such as Apache Kafka and Apache Airflow. Passionate about travel, yoga, and non-fiction reading, she brings a balanced and enriched worldview to her professional pursuits.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":8,"localizations":[{"id":852,"locale":"ja-JP","published_at":"2024-04-08T03:35:31.629Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/May9_The_Cost_of_Open_Source_Vector_Databases_An_Engineer_s_Guide_to_DYI_Pricing_1_9f559018b4.png","belong":"blog","authorNames":["Steffi Li"]},{"id":"learn-134","title":"Enhancing ChatGPT with Milvus: Powering AI with Long-Term Memory","image":{"id":3025,"url":"https://assets.zilliz.com/Enhancing_Chat_GPT_with_Milvus_099d0488f7.png"},"display_time":"Apr 08, 2024","url":"enhancing-chatgpt-with-milvus","abstract":"By integrating GPTCache and Milvus with ChatGPT, businesses can create a more robust and efficient AI-powered support system. This approach leverages the advanced capabilities of generative AI and introduces a form of long-term memory, allowing the AI to recall and reuse information effectively.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":135,"name":"Antony G.","author_tags":"Freelance Technical Writer","published_at":"2024-03-31T20:39:48.027Z","created_by":18,"updated_by":18,"created_at":"2024-03-31T20:39:30.202Z","updated_at":"2024-07-03T07:52:52.095Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Antony G., Freelance Technical Writer","locale":"en"}],"read_time":5,"localizations":[{"id":422,"locale":"ja-JP","published_at":"2024-04-15T17:34:32.668Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Enhancing_Chat_GPT_with_Milvus_099d0488f7.png","belong":"learn","authorNames":["Antony G."]},{"id":"learn-162","title":"Mastering Cohere's Reranker for Enhanced AI Performance","image":{"id":3470,"url":"https://assets.zilliz.com/May_8_Mastering_Cohere_s_Reranker_for_Enhanced_AI_Performance_f65d685a4e.png"},"display_time":"Apr 07, 2024","url":"mastering-coheres-reranker-enhanced-ai-performance","abstract":"Cohere's rerank endpoint offers a simple yet powerful solution to enhance search and recommendation systems. Learn how!","tags":[],"authors":[{"id":129,"name":"Saad Ahmed","author_tags":"Freelance Technical Writer","published_at":"2024-03-27T03:04:13.480Z","created_by":18,"updated_by":18,"created_at":"2024-03-27T03:04:10.954Z","updated_at":"2024-07-03T07:58:14.076Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Saad Ahmed, Freelance Technical Writer","locale":"en"}],"read_time":10,"localizations":[{"id":432,"locale":"ja-JP","published_at":"2024-04-10T05:31:55.671Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/May_8_Mastering_Cohere_s_Reranker_for_Enhanced_AI_Performance_f65d685a4e.png","belong":"learn","authorNames":["Saad Ahmed"]},{"id":"learn-157","title":"Large Language Models and Search ","image":{"id":3053,"url":"https://assets.zilliz.com/Large_Language_Models_and_Search_8da05468ac.png"},"display_time":"Apr 07, 2024","url":"large-language-models-and-search","abstract":"Explore the integration of Large Language Models (LLMs) and search technologies, featuring real-world applications and advancements facilitated by Zilliz and Milvus.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":135,"name":"Antony G.","author_tags":"Freelance Technical Writer","published_at":"2024-03-31T20:39:48.027Z","created_by":18,"updated_by":18,"created_at":"2024-03-31T20:39:30.202Z","updated_at":"2024-07-03T07:52:52.095Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Antony G., Freelance Technical Writer","locale":"en"}],"read_time":7,"localizations":[{"id":403,"locale":"ja-JP","published_at":"2024-04-10T04:17:10.098Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Large_Language_Models_and_Search_8da05468ac.png","belong":"learn","authorNames":["Antony G."]},{"id":"learn-155","title":"All-Mpnet-Base-V2: Enhancing Sentence Embedding with AI","image":{"id":3051,"url":"https://assets.zilliz.com/All_Mpnet_Base_V2_Enhancing_Sentence_Embedding_with_AI_481f0078ae.png"},"display_time":"Apr 06, 2024","url":"all-mpnet-base-v2-enhancing-sentence-embedding-with-ai","abstract":"In this article, we will delve into one of the deep learning models that has played a significant role in the development of sentence embedding: MPNet. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":125,"name":"Ruben Winastwan","author_tags":"Freelance Technical Writer","published_at":"2024-03-26T09:16:27.310Z","created_by":18,"updated_by":18,"created_at":"2024-03-26T09:16:24.498Z","updated_at":"2024-07-03T07:56:29.256Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Ruben Winastwan, Freelance Technical Writer","locale":"en"}],"read_time":15,"localizations":[{"id":417,"locale":"ja-JP","published_at":"2024-04-06T23:19:54.419Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/All_Mpnet_Base_V2_Enhancing_Sentence_Embedding_with_AI_481f0078ae.png","belong":"learn","authorNames":["Ruben Winastwan"]},{"id":"blog-379","title":"Redis tightens its license: How can an OSS company survive in the Cloud Era","image":{"id":3471,"url":"https://assets.zilliz.com/May9_Redis_tightens_its_license_How_can_an_OSS_company_survive_in_the_Cloud_Era_1_3c7b0d7afe.png"},"display_time":"Apr 05, 2024","deploy_time":"0202-04-05T19:52:58.000Z","url":"Redis-tightens-its-license-How-can-an-OSS-company-survive-in-the-Cloud-Era","abstract":"These shifts in open-source licensing have previously triggered \"keep-it-open\" forks, such as OpenSearch and OpenTofu. The battle over the future of open-source licensing continues to rage on.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":34,"name":"James Luan","author_tags":"VP of Engineering at Zilliz","published_at":"2022-05-18T03:15:15.255Z","created_by":18,"updated_by":18,"created_at":"2022-05-18T03:14:35.112Z","updated_at":"2024-01-12T21:01:29.192Z","home_page":"GitHub","home_page_link":"https://github.com/xiaofan-luan","self_intro":"James Luan is the VP of Engineering at Zilliz. With a master's degree in computer engineering from Cornell University, he has extensive experience as a Database Engineer at Oracle, Hedvig, and Alibaba Cloud. James played a crucial role in developing HBase, Alibaba Cloud's open-source database, and Lindorm, a self-developed NoSQL database. He is also a respected member of the Technical Advisory Committee of LF AI \u0026 Data Foundation, contributing his expertise to shaping the future of AI and data technologies.\n","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":5,"localizations":[{"id":918,"locale":"ja-JP","published_at":"2024-04-07T01:02:01.782Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/May9_Redis_tightens_its_license_How_can_an_OSS_company_survive_in_the_Cloud_Era_1_3c7b0d7afe.png","belong":"blog","authorNames":["James Luan"]},{"id":"learn-124","title":"Applying Vector Databases in Finance for Risk and Fraud Analysis","image":{"id":3472,"url":"https://assets.zilliz.com/May_8_Applying_Vector_Databases_in_Finance_for_Risk_and_Fraud_Analysis_1217ee1ab9.png"},"display_time":"Apr 05, 2024","url":"applying-vector-databases-in-finance-for-risk-and-fraud-analysis","abstract":"Vector databases represent a transformative technology for the finance sector, particularly in risk analysis and fraud detection. ","tags":[{"id":39,"name":"VectorDB 101","published_at":"2022-09-30T05:56:34.554Z","created_by":18,"updated_by":18,"created_at":"2022-09-30T05:56:31.633Z","updated_at":"2024-07-10T07:12:04.155Z","locale":"en"}],"authors":[{"id":128,"name":"Ankur Ashtikar","author_tags":"Freelance Technical Writer","published_at":"2024-03-27T03:03:55.532Z","created_by":18,"updated_by":18,"created_at":"2024-03-27T03:03:53.778Z","updated_at":"2024-07-03T07:56:02.455Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Ankur Ashtikar, Freelance Technical Writer","locale":"en"}],"read_time":6,"localizations":[{"id":392,"locale":"ja-JP","published_at":"2024-04-06T21:55:23.061Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/May_8_Applying_Vector_Databases_in_Finance_for_Risk_and_Fraud_Analysis_1217ee1ab9.png","belong":"learn","authorNames":["Ankur Ashtikar"]},{"id":"blog-378","title":"The Evolution and Future of Vector Databases: Insights from Charles, CEO of Zilliz ","image":{"id":3039,"url":"https://assets.zilliz.com/The_Evolution_and_Future_of_Vector_Databases_5ccfd25c1a.png"},"display_time":"Apr 04, 2024","deploy_time":"2024-04-04T22:00:00.000Z","url":"evolution-future-vector-databases-insights-zilliz-ceo-charles-xie","abstract":"Vector Databases focused on providing a single functionality: ANN search. However, the landscape is evolving, \u0026 we will see a broader array of functionalities. ","tags":[{"id":4,"name":"Company","published_at":"2021-01-21T02:28:23.551Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:20.676Z","updated_at":"2021-01-21T02:28:23.824Z","locale":"en"},{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":114,"name":"Charles Xie","author_tags":"Founder \u0026 CEO of Zilliz","published_at":"2024-02-07T19:12:09.772Z","created_by":18,"updated_by":18,"created_at":"2024-02-07T19:11:20.296Z","updated_at":"2024-02-07T19:12:09.793Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/chaoxie/","self_intro":"Charles Xie is the founder and CEO of Zilliz, focusing on building next-generation databases and search technologies for AI and LLMs applications. At Zilliz, he also invented Milvus, the world's most popular open-source vector database for production-ready AI. He is currently a board member of LF AI \u0026 Data Foundation and served as the board's chairperson in 2020 and 2021. Charles previously worked at Oracle as a founding engineer of the Oracle 12c cloud database project. Charles holds a master’s degree in computer science from the University of Wisconsin-Madison.\n","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":8,"localizations":[{"id":1268,"locale":"ja-JP","published_at":"2024-04-04T21:41:32.434Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/The_Evolution_and_Future_of_Vector_Databases_5ccfd25c1a.png","belong":"blog","authorNames":["Charles Xie"]},{"id":"learn-127","title":"Transforming Healthcare: The Role of Vector Databases in Patient Care","image":{"id":3473,"url":"https://assets.zilliz.com/May9_The_Role_of_Vector_Databases_in_Patient_Care_600f1e0f71.png"},"display_time":"Apr 04, 2024","url":"the-role-of-vector-databases-in-patient-care","abstract":"Explore how vector databases can play a critical role in transforming patience care in healthcare settings.","tags":[{"id":39,"name":"VectorDB 101","published_at":"2022-09-30T05:56:34.554Z","created_by":18,"updated_by":18,"created_at":"2022-09-30T05:56:31.633Z","updated_at":"2024-07-10T07:12:04.155Z","locale":"en"}],"authors":[{"id":121,"name":"Cahyo Subroto","author_tags":"Freelance Technical Writer","published_at":"2024-03-21T12:44:06.590Z","created_by":18,"updated_by":18,"created_at":"2024-03-21T12:44:03.831Z","updated_at":"2024-07-03T07:57:06.866Z","home_page":null,"home_page_link":null,"self_intro":"","repost_to_medium":null,"repost_state":null,"meta_description":"Cahyo Subroto, Freelance Technical Writer","locale":"en"}],"read_time":7,"localizations":[{"id":382,"locale":"ja-JP","published_at":"2024-04-04T23:57:26.453Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/May9_The_Role_of_Vector_Databases_in_Patient_Care_600f1e0f71.png","belong":"learn","authorNames":["Cahyo Subroto"]},{"id":"blog-377","title":"Building a Tax Appeal RAG with Milvus, LlamaIndex, and GPT","image":{"id":3474,"url":"https://assets.zilliz.com/May10_Building_a_Tax_Appeal_RAG_with_Milvus_Llama_Index_and_GPT_8c874b72a1.png"},"display_time":"Apr 03, 2024","deploy_time":null,"url":"build-tax-appeal-rag-with-milvus-llamaindex-and-gpt","abstract":"SaveHaven is a RAG app that streamlines the tax appeal process, making it more accessible and manageable for the general public. ","tags":[{"id":1,"name":"Case Study","published_at":"2021-01-15T10:34:37.316Z","created_by":18,"updated_by":18,"created_at":"2021-01-15T10:34:34.857Z","updated_at":"2021-01-25T10:31:22.499Z","locale":"en"}],"authors":[{"id":140,"name":"Ash Naik ","author_tags":"Freelance Technical Writer","published_at":"2024-04-03T01:56:43.169Z","created_by":18,"updated_by":18,"created_at":"2024-04-03T01:56:41.122Z","updated_at":"2024-07-03T07:51:50.134Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Ash Naik, Freelance Technical Writer","locale":"en"}],"read_time":4,"localizations":[{"id":831,"locale":"ja-JP","published_at":"2024-04-03T02:04:16.336Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/May10_Building_a_Tax_Appeal_RAG_with_Milvus_Llama_Index_and_GPT_8c874b72a1.png","belong":"blog","authorNames":["Ash Naik "]},{"id":"learn-129","title":"Streamlining Data: Effective Strategies for Reducing Dimensionality","image":{"id":3475,"url":"https://assets.zilliz.com/May10_Streamlining_Data_Effective_Strategies_for_Reducing_Dimensionality_96c4c22cae.png"},"display_time":"Apr 03, 2024","url":"streamlining-data-strategies-for-reducing-dimensionality","abstract":"In this article, we'll discuss how having too much data can hinder the performance of our machine-learning model and what we can do to address this problem.\n","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":125,"name":"Ruben Winastwan","author_tags":"Freelance Technical Writer","published_at":"2024-03-26T09:16:27.310Z","created_by":18,"updated_by":18,"created_at":"2024-03-26T09:16:24.498Z","updated_at":"2024-07-03T07:56:29.256Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Ruben Winastwan, Freelance Technical Writer","locale":"en"}],"read_time":9,"localizations":[{"id":446,"locale":"ja-JP","published_at":"2024-04-03T20:27:31.051Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/May10_Streamlining_Data_Effective_Strategies_for_Reducing_Dimensionality_96c4c22cae.png","belong":"learn","authorNames":["Ruben Winastwan"]},{"id":"learn-126","title":"Decoding Softmax Activation Function","image":{"id":3009,"url":"https://assets.zilliz.com/Mar_26_Vector_Database_105_f3369df5d7.png"},"display_time":"Apr 03, 2024","url":"decoding-softmax-understanding-functions-and-impact-in-ai","abstract":"This article will discuss the Softmax Activation Function, its applications, challenges, and tips for better performance.\n","tags":[{"id":39,"name":"VectorDB 101","published_at":"2022-09-30T05:56:34.554Z","created_by":18,"updated_by":18,"created_at":"2022-09-30T05:56:31.633Z","updated_at":"2024-07-10T07:12:04.155Z","locale":"en"}],"authors":[{"id":118,"name":" Haziqa Sajid","author_tags":"Freelance Technical Writer","published_at":"2024-03-12T10:25:34.265Z","created_by":18,"updated_by":18,"created_at":"2024-03-12T10:25:31.148Z","updated_at":"2024-07-03T07:58:27.010Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/haziqa-sajid-22b53245/","self_intro":"Digital Storytelling for Data, AI, B2B \u0026 SaaS","repost_to_medium":null,"repost_state":null,"meta_description":" Haziqa Sajid, Freelance Technical Writer","locale":"en"}],"read_time":9,"localizations":[{"id":477,"locale":"ja-JP","published_at":"2024-04-03T21:41:51.210Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Mar_26_Vector_Database_105_f3369df5d7.png","belong":"learn","authorNames":[" Haziqa Sajid"]},{"id":"learn-121","title":"Optimizing RAG with Rerankers: The Role and Trade-offs ","image":{"id":3001,"url":"https://assets.zilliz.com/Optimizing_RAG_with_Rerankers_The_Role_and_Trade_offs_2a9a90f6af.png"},"display_time":"Apr 02, 2024","url":"optimize-rag-with-rerankers-the-role-and-tradeoffs","abstract":"Rerankers can enhance the accuracy and relevance of answers in RAG systems, but these benefits come with increased latency and computational costs.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":101,"name":"Jiang Chen","author_tags":"Head of Ecosystem and Developer Relations","published_at":"2023-10-16T07:05:20.176Z","created_by":18,"updated_by":82,"created_at":"2023-10-16T07:05:18.702Z","updated_at":"2024-09-10T17:33:55.053Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/jiang-0616/","self_intro":"Jiang is currently Head of Ecosystem and Developer Relations at Zilliz. He has years of experience in data infrastructures and cloud security. Before joining Zilliz, he had previously served as a tech lead and product manager at Google, where he led the development of web-scale semantic understanding and search indexing that powers innovative search products such as short video search. He has extensive industry experience handling massive unstructured data and multimedia content retrieval. He has also worked on cloud authorization systems and research on data privacy technologies. Jiang holds a Master's degree in Computer Science from the University of Michigan.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":13,"localizations":[{"id":359,"locale":"ja-JP","published_at":"2024-04-01T18:34:05.783Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Optimizing_RAG_with_Rerankers_The_Role_and_Trade_offs_2a9a90f6af.png","belong":"learn","authorNames":["Jiang Chen"]},{"id":"blog-376","title":"An LLM Powered Text to Image Prompt Generation with Milvus","image":{"id":3016,"url":"https://assets.zilliz.com/An_LLM_Powered_Text_to_Image_Prompt_Generation_with_Milvus_093bffc04a.png"},"display_time":"Apr 01, 2024","deploy_time":"0002-04-02T03:54:17.000Z","url":"llm-powered-text-to-image-prompt-generation-with-milvus","abstract":"An interesting LLM project powered by the Milvus vector database for generating more efficient text-to-image prompts. ","tags":[{"id":1,"name":"Case Study","published_at":"2021-01-15T10:34:37.316Z","created_by":18,"updated_by":18,"created_at":"2021-01-15T10:34:34.857Z","updated_at":"2021-01-25T10:31:22.499Z","locale":"en"}],"authors":[{"id":139,"name":"Werner Oswald","author_tags":"Milvus Community Member","published_at":"2024-04-02T17:20:53.627Z","created_by":18,"updated_by":18,"created_at":"2024-04-02T17:20:51.816Z","updated_at":"2024-07-03T07:52:14.842Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Werner Oswald, Milvus Community Member","locale":"en"}],"read_time":4,"localizations":[{"id":1224,"locale":"ja-JP","published_at":"2024-04-02T17:46:22.809Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/An_LLM_Powered_Text_to_Image_Prompt_Generation_with_Milvus_093bffc04a.png","belong":"blog","authorNames":["Werner Oswald"]},{"id":"learn-123","title":"Optimizing AI: A Guide to Stable Diffusion and Efficient Caching Strategies","image":{"id":3004,"url":"https://assets.zilliz.com/Mar_26_AI_and_Machine_Learning_3_4fbc5e14b1.png"},"display_time":"Apr 01, 2024","url":"optimizing-ai-guide-to-stable-diffusion-and-caching-strategies","abstract":"This blog post will explore various caching strategies for optimizing Stable Diffusion models. \n","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":128,"name":"Ankur Ashtikar","author_tags":"Freelance Technical Writer","published_at":"2024-03-27T03:03:55.532Z","created_by":18,"updated_by":18,"created_at":"2024-03-27T03:03:53.778Z","updated_at":"2024-07-03T07:56:02.455Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Ankur Ashtikar, Freelance Technical Writer","locale":"en"}],"read_time":9,"localizations":[{"id":352,"locale":"ja-JP","published_at":"2024-04-21T02:22:54.678Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Mar_26_AI_and_Machine_Learning_3_4fbc5e14b1.png","belong":"learn","authorNames":["Ankur Ashtikar"]},{"id":"learn-152","title":"Mastering Locality Sensitive Hashing: A Comprehensive Tutorial and Use Cases","image":{"id":3046,"url":"https://assets.zilliz.com/Mastering_Locality_Sensitive_Hashing_A_Comprehensive_Tutorial_and_Use_Cases_64eee2ca32.png"},"display_time":"Apr 01, 2024","url":"mastering-locality-sensitive-hashing-a-comprehensive-tutorial","abstract":"Understand Locality Sensitive Hashing as an effective similarity search technique. Learn practical applications, challenges, and Python implementation of LSH.","tags":[{"id":39,"name":"VectorDB 101","published_at":"2022-09-30T05:56:34.554Z","created_by":18,"updated_by":18,"created_at":"2022-09-30T05:56:31.633Z","updated_at":"2024-07-10T07:12:04.155Z","locale":"en"}],"authors":[{"id":118,"name":" Haziqa Sajid","author_tags":"Freelance Technical Writer","published_at":"2024-03-12T10:25:34.265Z","created_by":18,"updated_by":18,"created_at":"2024-03-12T10:25:31.148Z","updated_at":"2024-07-03T07:58:27.010Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/haziqa-sajid-22b53245/","self_intro":"Digital Storytelling for Data, AI, B2B \u0026 SaaS","repost_to_medium":null,"repost_state":null,"meta_description":" Haziqa Sajid, Freelance Technical Writer","locale":"en"}],"read_time":7,"localizations":[{"id":372,"locale":"ja-JP","published_at":"2024-04-07T00:41:00.743Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Mastering_Locality_Sensitive_Hashing_A_Comprehensive_Tutorial_and_Use_Cases_64eee2ca32.png","belong":"learn","authorNames":[" Haziqa Sajid"]},{"id":"learn-115","title":"Langchain Tools: Revolutionizing AI Development with Advanced Toolsets","image":{"id":2998,"url":"https://assets.zilliz.com/Langchain_Tools_Revolutionizing_AI_Development_with_Advanced_Toolsets_337cf3417b.png"},"display_time":"Mar 31, 2024","url":"Langchain-Tools-Revolutionizing-AI-Development","abstract":"LangChain tools redefine the boundaries of what’s achievable with AI. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":134,"name":"Assad A","author_tags":"Freelance Technical Writer","published_at":"2024-03-31T19:11:54.598Z","created_by":18,"updated_by":18,"created_at":"2024-03-31T19:08:19.834Z","updated_at":"2024-07-03T07:53:07.360Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Assad A, Freelance Technical Writer","locale":"en"}],"read_time":13,"localizations":[{"id":467,"locale":"ja-JP","published_at":"2024-03-31T19:12:41.752Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Langchain_Tools_Revolutionizing_AI_Development_with_Advanced_Toolsets_337cf3417b.png","belong":"learn","authorNames":["Assad A"]},{"id":"learn-120","title":"Local Sensitivity Hashing (L.S.H.): A Comprehensive Guide","image":{"id":3477,"url":"https://assets.zilliz.com/May_11_Locality_Sensitive_Hashing_LSH_A_Comprehensive_Guide_1_e4a6168a3d.png"},"display_time":"Mar 30, 2024","url":"Local-Sensitivity-Hashing-A-Comprehensive-Guide","abstract":"Local Sensitivity Hashing (LSH) is a pivotal technique for tackling the complexities of large, high-dimensional datasets, streamlining the process of similarity search and data retrieval.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":136,"name":"Shanika W.","author_tags":"Freelance Technical Writer","published_at":"2024-04-01T00:56:28.466Z","created_by":18,"updated_by":18,"created_at":"2024-04-01T00:55:44.268Z","updated_at":"2024-07-03T07:52:40.773Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Shanika W, Freelance Technical Writer","locale":"en"}],"read_time":7,"localizations":[{"id":344,"locale":"ja-JP","published_at":"2024-04-01T00:57:10.358Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/May_11_Locality_Sensitive_Hashing_LSH_A_Comprehensive_Guide_1_e4a6168a3d.png","belong":"learn","authorNames":["Shanika W."]},{"id":"learn-116","title":"NLP and Vector Databases: Creating a Synergy for Advanced Processing","image":{"id":2987,"url":"https://assets.zilliz.com/NLP_and_Vector_Databases_Creating_a_Synergy_for_Advanced_Processing_25bdb53eb7.png"},"display_time":"Mar 30, 2024","url":"NLP-and-Vector Databases-Creating-a-Synergy-for-Advanced-Processing","abstract":"Finding photos, recommending products, or enabling facial recognition, the power of vector databases lies in their ability to make sense of the complexity of the world around us. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":126,"name":"Antony G.","author_tags":"Freelance Technical Writer","published_at":"2024-03-26T09:18:07.767Z","created_by":18,"updated_by":18,"created_at":"2024-03-26T09:18:00.140Z","updated_at":"2024-07-03T07:56:19.123Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Antony G., Freelance Technical Writer","locale":"en"}],"read_time":6,"localizations":[{"id":364,"locale":"ja-JP","published_at":"2024-03-31T20:46:58.985Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/NLP_and_Vector_Databases_Creating_a_Synergy_for_Advanced_Processing_25bdb53eb7.png","belong":"learn","authorNames":["Antony G."]},{"id":"learn-107","title":"OpenAI Whisper: Transforming Speech-to-Text with Advanced AI","image":{"id":2964,"url":"https://assets.zilliz.com/Mar_26_LLM_4ff9317a23.png"},"display_time":"Mar 29, 2024","url":"open-ai-whisper-transforming-speech-to-text-with-advanced-ai","abstract":"Understand Open AI Whisper and follow this step-by-step article to implement it in projects that can significantly enhance the efficiency of speech-to-text tasks.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":118,"name":" Haziqa Sajid","author_tags":"Freelance Technical Writer","published_at":"2024-03-12T10:25:34.265Z","created_by":18,"updated_by":18,"created_at":"2024-03-12T10:25:31.148Z","updated_at":"2024-07-03T07:58:27.010Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/haziqa-sajid-22b53245/","self_intro":"Digital Storytelling for Data, AI, B2B \u0026 SaaS","repost_to_medium":null,"repost_state":null,"meta_description":" Haziqa Sajid, Freelance Technical Writer","locale":"en"}],"read_time":6,"localizations":[{"id":369,"locale":"ja-JP","published_at":"2024-03-29T21:56:50.878Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Mar_26_LLM_4ff9317a23.png","belong":"learn","authorNames":[" Haziqa Sajid"]},{"id":"learn-104","title":"Exploring BERTopic: A New Era of Neural Topic Modeling","image":{"id":2953,"url":"https://assets.zilliz.com/BER_Topic_9be83c051d.png"},"display_time":"Mar 28, 2024","url":"explore-bertopic-novel-neural-topic-modeling-technique","abstract":"BERTopic is a novel topic modeling technique that allows for easily interpretable topics while keeping important words in the topic descriptions. ","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":118,"name":" Haziqa Sajid","author_tags":"Freelance Technical Writer","published_at":"2024-03-12T10:25:34.265Z","created_by":18,"updated_by":18,"created_at":"2024-03-12T10:25:31.148Z","updated_at":"2024-07-03T07:58:27.010Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/haziqa-sajid-22b53245/","self_intro":"Digital Storytelling for Data, AI, B2B \u0026 SaaS","repost_to_medium":null,"repost_state":null,"meta_description":" Haziqa Sajid, Freelance Technical Writer","locale":"en"}],"read_time":11,"localizations":[{"id":328,"locale":"ja-JP","published_at":"2024-03-29T06:48:01.360Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/BER_Topic_9be83c051d.png","belong":"learn","authorNames":[" Haziqa Sajid"]},{"id":"learn-112","title":"Transforming Text: The Rise of Sentence Transformers in NLP","image":{"id":2970,"url":"https://assets.zilliz.com/Transforming_Text_The_Rise_of_Sentence_Transformers_in_NLP_a5397d83e1.png"},"display_time":"Mar 27, 2024","url":"transforming-text-the-rise-of-sentence-transformers-in-nlp","abstract":"Everything you need to know about the Transformers model, exploring its architecture, implementation, and limitations. Sentence Transformers model is an important breakthrough in the AI domain, as it enables the generation of sentence-level embeddings, which offer broader applicability compared to token-level embeddings.\n","tags":[],"authors":[{"id":125,"name":"Ruben Winastwan","author_tags":"Freelance Technical Writer","published_at":"2024-03-26T09:16:27.310Z","created_by":18,"updated_by":18,"created_at":"2024-03-26T09:16:24.498Z","updated_at":"2024-07-03T07:56:29.256Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Ruben Winastwan, Freelance Technical Writer","locale":"en"}],"read_time":10,"localizations":[{"id":304,"locale":"ja-JP","published_at":"2024-03-30T20:36:33.519Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Transforming_Text_The_Rise_of_Sentence_Transformers_in_NLP_a5397d83e1.png","belong":"learn","authorNames":["Ruben Winastwan"]},{"id":"learn-106","title":"A Beginner's Guide to Implementing Vector Databases","image":{"id":3476,"url":"https://assets.zilliz.com/May_11_A_Beginner_s_Guide_to_Implementing_Vector_Databases_b1da7c3730.png"},"display_time":"Mar 27, 2024","url":"beginner-guide-to-implementing-vector-databases","abstract":"A Beginner's Guide to Vector Databases, including key considerations and steps to get started with a vector database and implementation best practices. ","tags":[{"id":39,"name":"VectorDB 101","published_at":"2022-09-30T05:56:34.554Z","created_by":18,"updated_by":18,"created_at":"2022-09-30T05:56:31.633Z","updated_at":"2024-07-10T07:12:04.155Z","locale":"en"}],"authors":[{"id":131,"name":"Samin Chandeepa","author_tags":"Freelance Technical Writer","published_at":"2024-03-29T07:49:43.838Z","created_by":18,"updated_by":18,"created_at":"2024-03-29T07:49:42.003Z","updated_at":"2024-07-03T07:53:42.149Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Samin Chandeepa, Freelance Technical Writer","locale":"en"}],"read_time":7,"localizations":[{"id":430,"locale":"ja-JP","published_at":"2024-03-29T07:49:18.435Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/May_11_A_Beginner_s_Guide_to_Implementing_Vector_Databases_b1da7c3730.png","belong":"learn","authorNames":["Samin Chandeepa"]},{"id":"blog-373","title":"Milvus Metadata Filtering: JSON and Metadata Filtering in Milvus","image":{"id":2945,"url":"https://assets.zilliz.com/JSON_and_Metadata_Filtering_in_Milvus_68b087be9e.png"},"display_time":"Mar 26, 2024","deploy_time":null,"url":"json-metadata-filtering-in-milvus","abstract":"A brief review of how to ingest your data with JSON in your Milvus vector database","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":94,"name":"Christy Bergman","author_tags":"Developer Advocate","published_at":"2023-10-06T00:29:45.486Z","created_by":18,"updated_by":18,"created_at":"2023-10-06T00:29:30.751Z","updated_at":"2024-07-18T16:01:45.942Z","home_page":null,"home_page_link":null,"self_intro":"Christy Bergman is a passionate Developer Advocate at Zilliz. She previously worked in distributed computing at Anyscale and as a Specialist AI/ML Solutions Architect at AWS. Christy studied applied math, is a self-taught coder, and has published papers, including one with ACM Recsys. She enjoys hiking and bird watching.","repost_to_medium":null,"repost_state":null,"meta_description":"Christy Bergman is a passionate Developer Advocate at Zilliz. ","locale":"en"}],"read_time":9,"localizations":[{"id":874,"locale":"ja-JP","published_at":"2024-03-27T04:25:25.017Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/JSON_and_Metadata_Filtering_in_Milvus_68b087be9e.png","belong":"blog","authorNames":["Christy Bergman"]},{"id":"blog-374","title":"Community and Open Source Contributions in Vector Databases","image":{"id":3478,"url":"https://assets.zilliz.com/May_11_Community_and_Open_Source_Contributions_in_Vector_Databases_ebdf48373a.png"},"display_time":"Mar 26, 2024","deploy_time":null,"url":"community-and-open-source-contributions-in-vector-databases","abstract":"Open-source vector databases drive innovation in handling complex data through global community collaboration, enhancing scalability and performance. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":115,"name":"Stephen Batifol","author_tags":"Developer Advocate ","published_at":"2024-03-07T03:46:04.655Z","created_by":18,"updated_by":18,"created_at":"2024-03-07T03:46:02.457Z","updated_at":"2024-07-18T15:56:42.529Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/stephen-batifol/","self_intro":"Stephen Batifol is a Developer Advocate at Zilliz. He previously worked as a Machine Learning Engineer at Wolt, where he was working on the ML Platform and as a Data Scientist at Brevo. Stephen studied Computer Science and Artificial Intelligence. He enjoys dancing and surfing. \n","repost_to_medium":null,"repost_state":null,"meta_description":"Stephen Batifol is a Developer Advocate at Zilliz.","locale":"en"}],"read_time":5,"localizations":[{"id":1287,"locale":"ja-JP","published_at":"2024-03-27T06:48:32.129Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/May_11_Community_and_Open_Source_Contributions_in_Vector_Databases_ebdf48373a.png","belong":"blog","authorNames":["Stephen Batifol"]},{"id":"learn-103","title":"The 2024 Playbook: Top Use Cases for Vector Search","image":{"id":3479,"url":"https://assets.zilliz.com/May_10_The_2024_Playbook_Top_Use_Cases_for_Vector_Search_9c5bd46dc2.png"},"display_time":"Mar 26, 2024","url":"top-use-cases-for-vector-search","abstract":"An exploration of vector search technologies and their most popular use cases. ","tags":[{"id":1,"name":"Case Study","published_at":"2021-01-15T10:34:37.316Z","created_by":18,"updated_by":18,"created_at":"2021-01-15T10:34:34.857Z","updated_at":"2021-01-25T10:31:22.499Z","locale":"en"}],"authors":[{"id":129,"name":"Saad Ahmed","author_tags":"Freelance Technical Writer","published_at":"2024-03-27T03:04:13.480Z","created_by":18,"updated_by":18,"created_at":"2024-03-27T03:04:10.954Z","updated_at":"2024-07-03T07:58:14.076Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Saad Ahmed, Freelance Technical Writer","locale":"en"}],"read_time":6,"localizations":[{"id":394,"locale":"ja-JP","published_at":"2024-03-27T06:58:43.504Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/May_10_The_2024_Playbook_Top_Use_Cases_for_Vector_Search_9c5bd46dc2.png","belong":"learn","authorNames":["Saad Ahmed"]},{"id":"learn-99","title":"Class Activation Mapping (CAM): Better Interpretability in Deep Learning Models","image":{"id":3480,"url":"https://assets.zilliz.com/May_10_Class_Activation_Mapping_Unveiling_The_Visual_Story_2c8a300031.png"},"display_time":"Mar 25, 2024","url":"class-activation-mapping-CAM","abstract":"Class Activation Mapping (CAM) is used to visualize and understand the decision-making of convolutional neural networks (CNNs) for computer vision tasks. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":125,"name":"Ruben Winastwan","author_tags":"Freelance Technical Writer","published_at":"2024-03-26T09:16:27.310Z","created_by":18,"updated_by":18,"created_at":"2024-03-26T09:16:24.498Z","updated_at":"2024-07-03T07:56:29.256Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Ruben Winastwan, Freelance Technical Writer","locale":"en"}],"read_time":10,"localizations":[{"id":366,"locale":"ja-JP","published_at":"2024-03-26T09:20:55.401Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/May_10_Class_Activation_Mapping_Unveiling_The_Visual_Story_2c8a300031.png","belong":"learn","authorNames":["Ruben Winastwan"]},{"id":"learn-98","title":"Discover SPLADE: Revolutionizing Sparse Data Processing","image":{"id":2914,"url":"https://assets.zilliz.com/Discover_SPLADE_Revolutionizing_Sparse_Data_Processing_1_32861fff33.png"},"display_time":"Mar 25, 2024","url":"discover-splade-revolutionize-sparse-data-processing","abstract":"SPLADE is a technique that uses pre-trained transformer models to process sparse data. This post explores SPLADE, its benefits, and real-world apps. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":118,"name":" Haziqa Sajid","author_tags":"Freelance Technical Writer","published_at":"2024-03-12T10:25:34.265Z","created_by":18,"updated_by":18,"created_at":"2024-03-12T10:25:31.148Z","updated_at":"2024-07-03T07:58:27.010Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/haziqa-sajid-22b53245/","self_intro":"Digital Storytelling for Data, AI, B2B \u0026 SaaS","repost_to_medium":null,"repost_state":null,"meta_description":" Haziqa Sajid, Freelance Technical Writer","locale":"en"}],"read_time":5,"localizations":[{"id":396,"locale":"ja-JP","published_at":"2024-03-26T08:47:32.936Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Discover_SPLADE_Revolutionizing_Sparse_Data_Processing_1_32861fff33.png","belong":"learn","authorNames":[" Haziqa Sajid"]},{"id":"learn-100","title":"CLIP Object Detection: Merging AI Vision with Language Understanding","image":{"id":3481,"url":"https://assets.zilliz.com/May_13_CLIP_Object_Detection_Merging_AI_Vision_with_Language_Understanding_a2d7c1619c.png"},"display_time":"Mar 24, 2024","url":"CLIP-object-detection-merge-AI-vision-with-language-understanding","abstract":"CLIP Object Detection combines CLIP's text-image understanding with object detection tasks, allowing CLIP to locate and identify objects in images using texts.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":127,"name":"Priyanka Israni","author_tags":"Freelance Technical Writer","published_at":"2024-03-26T09:18:45.337Z","created_by":18,"updated_by":18,"created_at":"2024-03-26T09:18:42.686Z","updated_at":"2024-07-03T07:56:11.446Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Priyanka Israni, Freelance Technical Writer","locale":"en"}],"read_time":9,"localizations":[{"id":336,"locale":"ja-JP","published_at":"2024-03-26T09:20:27.381Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/May_13_CLIP_Object_Detection_Merging_AI_Vision_with_Language_Understanding_a2d7c1619c.png","belong":"learn","authorNames":["Priyanka Israni"]},{"id":"learn-101","title":"NLP Essentials: Understanding Transformers in AI","image":{"id":2935,"url":"https://assets.zilliz.com/Nov_03_A_Beginner_s_Guide_to_NLP_6b823ad3eb.png"},"display_time":"Mar 24, 2024","url":"NLP-essentials-understanding-transformers-in-AI","abstract":"This article will introduce you to the field of Natural Language Processing (NLP) and the breakthrough architecture, the transformer. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":126,"name":"Antony G.","author_tags":"Freelance Technical Writer","published_at":"2024-03-26T09:18:07.767Z","created_by":18,"updated_by":18,"created_at":"2024-03-26T09:18:00.140Z","updated_at":"2024-07-03T07:56:19.123Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Antony G., Freelance Technical Writer","locale":"en"}],"read_time":4,"localizations":[{"id":391,"locale":"ja-JP","published_at":"2024-03-26T09:20:01.728Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Nov_03_A_Beginner_s_Guide_to_NLP_6b823ad3eb.png","belong":"learn","authorNames":["Antony G."]},{"id":"learn-95","title":"Key NLP technologies in Deep Learning","image":{"id":2898,"url":"https://assets.zilliz.com/Key_NLP_Technologies_in_Deep_Learning_e7989aa0a4.png"},"display_time":"Mar 23, 2024","url":"nlp-technologies-in-deep-learning","abstract":"An exploration of the evolution and fundamental principles underlying key Natural Language Processing (NLP) technologies within Deep Learning.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":107,"name":"Cheney Zhang","author_tags":"Algorithm Engineer","published_at":"2023-11-08T07:21:13.405Z","created_by":18,"updated_by":18,"created_at":"2023-11-08T07:21:10.513Z","updated_at":"2024-07-18T15:56:58.028Z","home_page":"GitHub","home_page_link":"https://github.com/zc277584121","self_intro":"Cheney Zhang is an accomplished Algorithm Engineer at Zilliz. With a profound passion for and expertise in cutting-edge AI technologies such as LLMs and Retrieval Augmented Generation (RAG), Cheney has actively contributed to many innovative AI projects, including Towhee, Akcio, and OSSChat. Before joining Zilliz, he worked for CMB Network Technology as an Algorithm Engineer. Cheney holds a master's degree from Nanjing University of Aeronautics and Astronautics.","repost_to_medium":null,"repost_state":null,"meta_description":"Cheney Zhang is an accomplished Algorithm Engineer at Zilliz. ","locale":"en"}],"read_time":11,"localizations":[{"id":386,"locale":"ja-JP","published_at":"2024-03-23T23:56:41.245Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Key_NLP_Technologies_in_Deep_Learning_e7989aa0a4.png","belong":"learn","authorNames":["Cheney Zhang"]},{"id":"learn-97","title":"How to Evaluate RAG Applications","image":{"id":2904,"url":"https://assets.zilliz.com/How_to_evaluate_RAG_517731a365.png"},"display_time":"Mar 23, 2024","url":"How-To-Evaluate-RAG-Applications","abstract":"A comparative analysis of evaluating RAG applications, addressing the challenge of determining their relative effectiveness. It explores quantitative metrics for developers to enhance their RAG application performance.\n\n\n\n\n\n\n","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":107,"name":"Cheney Zhang","author_tags":"Algorithm Engineer","published_at":"2023-11-08T07:21:13.405Z","created_by":18,"updated_by":18,"created_at":"2023-11-08T07:21:10.513Z","updated_at":"2024-07-18T15:56:58.028Z","home_page":"GitHub","home_page_link":"https://github.com/zc277584121","self_intro":"Cheney Zhang is an accomplished Algorithm Engineer at Zilliz. With a profound passion for and expertise in cutting-edge AI technologies such as LLMs and Retrieval Augmented Generation (RAG), Cheney has actively contributed to many innovative AI projects, including Towhee, Akcio, and OSSChat. Before joining Zilliz, he worked for CMB Network Technology as an Algorithm Engineer. Cheney holds a master's degree from Nanjing University of Aeronautics and Astronautics.","repost_to_medium":null,"repost_state":null,"meta_description":"Cheney Zhang is an accomplished Algorithm Engineer at Zilliz. ","locale":"en"}],"read_time":13,"localizations":[{"id":468,"locale":"ja-JP","published_at":"2024-03-24T02:41:17.176Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/How_to_evaluate_RAG_517731a365.png","belong":"learn","authorNames":["Cheney Zhang"]},{"id":"learn-93","title":"Batch vs. Layer Normalization - Unlocking Efficiency in Neural Networks","image":{"id":2889,"url":"https://assets.zilliz.com/Layer_vs_Batch_Normalization_Unlocking_Efficiency_in_Neural_Networks8_index_types_d1a4a87044.png"},"display_time":"Mar 22, 2024","url":"layer-vs-batch-normalization-unlocking-efficiency-in-neural-networks","abstract":"By unraveling the intricacies of layer and batch normalization, we aim to equip neural network beginners with the knowledge to unlock efficiency and enhance model performance.","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":124,"name":"Shivek Santosh Maharaj","author_tags":"Freelance Technical Writer","published_at":"2024-03-23T06:02:23.829Z","created_by":18,"updated_by":18,"created_at":"2024-03-23T06:02:21.922Z","updated_at":"2024-07-03T07:56:37.593Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Shivek Santosh Maharaj, Freelance Technical Writer","locale":"en"}],"read_time":15,"localizations":[{"id":307,"locale":"ja-JP","published_at":"2024-03-23T06:02:41.559Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Layer_vs_Batch_Normalization_Unlocking_Efficiency_in_Neural_Networks8_index_types_d1a4a87044.png","belong":"learn","authorNames":["Shivek Santosh Maharaj"]},{"id":"learn-92","title":"Cross-Entropy Loss: Unraveling its Role in Machine Learning","image":{"id":3482,"url":"https://assets.zilliz.com/May_13_Cross_Entropy_Loss_Unraveling_its_Role_in_Machine_Learning_6914ce50f8.png"},"display_time":"Mar 22, 2024","url":"Cross-Entropy-Loss-Unraveling-its-Role-in-Machine-Learning","abstract":"Cross-entropy loss is used for training classification models. It’s an easy-to-implement loss function requiring labels encoded in numeric values for accurate loss calculation. ","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":118,"name":" Haziqa Sajid","author_tags":"Freelance Technical Writer","published_at":"2024-03-12T10:25:34.265Z","created_by":18,"updated_by":18,"created_at":"2024-03-12T10:25:31.148Z","updated_at":"2024-07-03T07:58:27.010Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/haziqa-sajid-22b53245/","self_intro":"Digital Storytelling for Data, AI, B2B \u0026 SaaS","repost_to_medium":null,"repost_state":null,"meta_description":" Haziqa Sajid, Freelance Technical Writer","locale":"en"}],"read_time":6,"localizations":[{"id":373,"locale":"ja-JP","published_at":"2024-03-23T05:41:52.355Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/May_13_Cross_Entropy_Loss_Unraveling_its_Role_in_Machine_Learning_6914ce50f8.png","belong":"learn","authorNames":[" Haziqa Sajid"]},{"id":"learn-90","title":"Dense Vectors in AI: Maximizing Data Potential in Machine Learning","image":{"id":3483,"url":"https://assets.zilliz.com/May_13_Dense_Vectors_in_AI_Maximizing_Data_Potential_in_Machine_Learning_3292639cb9.png"},"display_time":"Mar 22, 2024","url":"dense-vector-in-ai-maximize-data-potential-in-machine-learning","abstract":"This article zooms in on dense vectors, uncovering their advantages compared to sparse vectors and how they are widely used in ML algorithms across various domains. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":122,"name":"Nuri Tas","author_tags":"Freelance Technical Writer","published_at":"2024-03-22T07:48:31.809Z","created_by":18,"updated_by":18,"created_at":"2024-03-22T07:48:29.574Z","updated_at":"2024-07-03T07:56:51.751Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Nuri Tas, Freelance Technical Writer","locale":"en"}],"read_time":4,"localizations":[{"id":442,"locale":"ja-JP","published_at":"2024-03-22T07:48:51.796Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/May_13_Dense_Vectors_in_AI_Maximizing_Data_Potential_in_Machine_Learning_3292639cb9.png","belong":"learn","authorNames":["Nuri Tas"]},{"id":"learn-91","title":"Integrating Vector Databases with Cloud Computing: A Strategic Solution to Modern Data Challenges ","image":{"id":2885,"url":"https://assets.zilliz.com/Mar_14_Vector_Databases_and_Cloud_Computing_An_Integrated_Approach_1_8696b3c73e.png"},"display_time":"Mar 22, 2024","url":"integrating-vector-databases-with-cloud-computing-solution-to-modern-data-challenges","abstract":"Integrating vector databases and cloud computing creates a powerful infrastructure that significantly enhances the management of large-scale, complex data in AI and machine learning. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":123,"name":"Fahad","author_tags":"Freelance Technical Writer","published_at":"2024-03-23T04:59:20.541Z","created_by":18,"updated_by":18,"created_at":"2024-03-23T04:59:18.601Z","updated_at":"2024-07-03T07:57:20.621Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Fahad, Freelance Technical Writer","locale":"en"}],"read_time":6,"localizations":[{"id":480,"locale":"ja-JP","published_at":"2024-03-23T04:59:48.229Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Mar_14_Vector_Databases_and_Cloud_Computing_An_Integrated_Approach_1_8696b3c73e.png","belong":"learn","authorNames":["Fahad"]},{"id":"learn-94","title":"Mastering LLM Challenges: An Exploration of Retrieval Augmented Generation","image":{"id":2897,"url":"https://assets.zilliz.com/RAG_handbook_f5ad3ae4fc.png"},"display_time":"Mar 22, 2024","url":"RAG-handbook","abstract":"This four-part series handbook looks into RAG, exploring its architecture, advantages, the challenges it can address, and why it stands as the preferred choice for elevating the performance of generative AI applications.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":107,"name":"Cheney Zhang","author_tags":"Algorithm Engineer","published_at":"2023-11-08T07:21:13.405Z","created_by":18,"updated_by":18,"created_at":"2023-11-08T07:21:10.513Z","updated_at":"2024-07-18T15:56:58.028Z","home_page":"GitHub","home_page_link":"https://github.com/zc277584121","self_intro":"Cheney Zhang is an accomplished Algorithm Engineer at Zilliz. With a profound passion for and expertise in cutting-edge AI technologies such as LLMs and Retrieval Augmented Generation (RAG), Cheney has actively contributed to many innovative AI projects, including Towhee, Akcio, and OSSChat. Before joining Zilliz, he worked for CMB Network Technology as an Algorithm Engineer. Cheney holds a master's degree from Nanjing University of Aeronautics and Astronautics.","repost_to_medium":null,"repost_state":null,"meta_description":"Cheney Zhang is an accomplished Algorithm Engineer at Zilliz. ","locale":"en"}],"read_time":6,"localizations":[{"id":379,"locale":"ja-JP","published_at":"2024-03-23T23:44:40.992Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/RAG_handbook_f5ad3ae4fc.png","belong":"learn","authorNames":["Cheney Zhang"]},{"id":"blog-371","title":"Milvus 2.4 Unveils CAGRA: Elevating Vector Search with Next-Gen GPU Indexing","image":{"id":2826,"url":"https://assets.zilliz.com/Milvus_2_4_Unveils_CAGRA_Elevating_Vector_Search_with_Next_Gen_GPU_Indexing_69f4012602.png"},"display_time":"Mar 20, 2024","deploy_time":null,"url":"Milvus-introduces-GPU-index-CAGRA","abstract":"With CAGRA Index support, Milvus 2.4 set a new standard in GPU-accelerated graph indexing, ideal for similarity search applications needing minimal latency. ","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":70,"name":"Li Liu","author_tags":"Principal Engineer","published_at":"2023-06-15T05:16:42.032Z","created_by":18,"updated_by":18,"created_at":"2023-06-15T05:15:15.087Z","updated_at":"2024-07-18T15:59:40.729Z","home_page":"GitHub","home_page_link":"https://github.com/liliu-z","self_intro":"Li Liu is the Principal Engineer at Zilliz, leading the vector searching research and development. Before joining Zilliz, he was a Senior Engineer at Meta, designing and shaping numerous advertising stream data frameworks. With a Master's degree from Carnegie Mellon University, he boasts extensive experience in databases and big data. Li Liu's expertise in technology and innovation continues to drive advancements in vector searching, leaving a lasting impact on the field.\n","repost_to_medium":null,"repost_state":null,"meta_description":"Li Liu is the Principal Engineer at Zilliz, leading the vector searching research and development.","locale":"en"}],"read_time":7,"localizations":[{"id":849,"locale":"ja-JP","published_at":"2024-03-20T08:10:55.329Z"},{"id":1456,"locale":"de","published_at":"2024-03-20T08:10:55.329Z"},{"id":1618,"locale":"fr","published_at":"2024-03-20T08:10:55.329Z"},{"id":1510,"locale":"pt","published_at":"2024-03-20T08:10:55.329Z"},{"id":1537,"locale":"ru","published_at":"2024-03-20T08:10:55.329Z"},{"id":1591,"locale":"it","published_at":"2024-03-20T08:10:55.329Z"},{"id":1483,"locale":"es","published_at":"2024-03-20T08:10:55.329Z"},{"id":1564,"locale":"ko","published_at":"2024-03-20T08:10:55.329Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Milvus_2_4_Unveils_CAGRA_Elevating_Vector_Search_with_Next_Gen_GPU_Indexing_69f4012602.png","belong":"blog","authorNames":["Li Liu"]},{"id":"blog-372","title":"What’s New in Milvus 2.4.0? ","image":{"id":2837,"url":"https://assets.zilliz.com/Mar_18_What_Is_New_in_Milvus_2_4_1_d56c190121.png"},"display_time":"Mar 20, 2024","deploy_time":null,"url":"what-is-new-in-milvus-2-4-0","abstract":"Milvus 2.4 provides support for NVIDIA CAGRA GPU Indexing, Multi-vector Search, Sparse Vectors, and more to optimize the vector search capabilities. ","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":76,"name":"Steffi Li","author_tags":"Director of Product Marketing","published_at":"2023-07-13T17:18:42.023Z","created_by":18,"updated_by":18,"created_at":"2023-07-13T17:16:54.449Z","updated_at":"2023-07-13T17:18:42.070Z","home_page":null,"home_page_link":null,"self_intro":"Steffi is the Director of Product Marketing at Zilliz, with prior experience leading the GTM strategies for open-source data technologies such as Apache Kafka and Apache Airflow. Passionate about travel, yoga, and non-fiction reading, she brings a balanced and enriched worldview to her professional pursuits.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":3,"localizations":[{"id":1212,"locale":"ja-JP","published_at":"2024-03-20T11:36:20.814Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Mar_18_What_Is_New_in_Milvus_2_4_1_d56c190121.png","belong":"blog","authorNames":["Steffi Li"]},{"id":"blog-370","title":"Using Similarity Search - How Not to Lose Meetup Content on the Internet","image":{"id":3484,"url":"https://assets.zilliz.com/May_11_Using_Similarity_Search_How_Not_to_Lose_Meetup_Content_on_the_Internet_d45ad6510b.png"},"display_time":"Mar 19, 2024","deploy_time":null,"url":"semantic-search-how-not-lose-meetup-content","abstract":"This tutorial walks you through using the Milvus vector database and sentence transformers to build a smart semantic search for your Meetup content.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":115,"name":"Stephen Batifol","author_tags":"Developer Advocate ","published_at":"2024-03-07T03:46:04.655Z","created_by":18,"updated_by":18,"created_at":"2024-03-07T03:46:02.457Z","updated_at":"2024-07-18T15:56:42.529Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/stephen-batifol/","self_intro":"Stephen Batifol is a Developer Advocate at Zilliz. He previously worked as a Machine Learning Engineer at Wolt, where he was working on the ML Platform and as a Data Scientist at Brevo. Stephen studied Computer Science and Artificial Intelligence. He enjoys dancing and surfing. \n","repost_to_medium":null,"repost_state":null,"meta_description":"Stephen Batifol is a Developer Advocate at Zilliz.","locale":"en"}],"read_time":5,"localizations":[{"id":1089,"locale":"ja-JP","published_at":"2024-03-19T11:13:10.169Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/May_11_Using_Similarity_Search_How_Not_to_Lose_Meetup_Content_on_the_Internet_d45ad6510b.png","belong":"blog","authorNames":["Stephen Batifol"]},{"id":"blog-365","title":"Build Real-time GenAI Applications with Zilliz Cloud and Confluent Cloud for Apache Flink®","image":{"id":2821,"url":"https://assets.zilliz.com/confluent_cloud_and_zilliz_cloud_a4b44c36a8.png"},"display_time":"Mar 19, 2024","deploy_time":null,"url":"real-time-genai-apps-zilliz-confluent-flink","abstract":"Announcing the partnership with Confluent to unlock semantic search for real-time updates powered by Apache Kafka®, Apache Flink®, and the Milvus vector database. ","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":101,"name":"Jiang Chen","author_tags":"Head of Ecosystem and Developer Relations","published_at":"2023-10-16T07:05:20.176Z","created_by":18,"updated_by":82,"created_at":"2023-10-16T07:05:18.702Z","updated_at":"2024-09-10T17:33:55.053Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/jiang-0616/","self_intro":"Jiang is currently Head of Ecosystem and Developer Relations at Zilliz. He has years of experience in data infrastructures and cloud security. Before joining Zilliz, he had previously served as a tech lead and product manager at Google, where he led the development of web-scale semantic understanding and search indexing that powers innovative search products such as short video search. He has extensive industry experience handling massive unstructured data and multimedia content retrieval. He has also worked on cloud authorization systems and research on data privacy technologies. Jiang holds a Master's degree in Computer Science from the University of Michigan.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":3,"localizations":[{"id":1283,"locale":"ja-JP","published_at":"2024-03-19T07:06:52.489Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/confluent_cloud_and_zilliz_cloud_a4b44c36a8.png","belong":"blog","authorNames":["Jiang Chen"]},{"id":"learn-88","title":"LangChain Memory: Enhancing AI Conversational Capabilities","image":{"id":2876,"url":"https://assets.zilliz.com/Mar_19_Lang_Chain_Memory_Enhancing_AI_Conversational_Capabilities_f5bf7ff4a4.png"},"display_time":"Mar 19, 2024","url":"langchain-memory-enhancing-AI-conversational-capabilities","abstract":"This article explores the memory capabilities of modern LLMs, using LangChain modules to establish memory buffers and build conversational AI applications. ","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":118,"name":" Haziqa Sajid","author_tags":"Freelance Technical Writer","published_at":"2024-03-12T10:25:34.265Z","created_by":18,"updated_by":18,"created_at":"2024-03-12T10:25:31.148Z","updated_at":"2024-07-03T07:58:27.010Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/haziqa-sajid-22b53245/","self_intro":"Digital Storytelling for Data, AI, B2B \u0026 SaaS","repost_to_medium":null,"repost_state":null,"meta_description":" Haziqa Sajid, Freelance Technical Writer","locale":"en"}],"read_time":5,"localizations":[{"id":479,"locale":"ja-JP","published_at":"2024-03-19T07:54:02.534Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Mar_19_Lang_Chain_Memory_Enhancing_AI_Conversational_Capabilities_f5bf7ff4a4.png","belong":"learn","authorNames":[" Haziqa Sajid"]},{"id":"blog-367","title":"RAG Evaluation Using Ragas ","image":{"id":2815,"url":"https://assets.zilliz.com/Mar_18_RAG_Evaluation_using_Ragas_20240318_080304_62e448ec81.png"},"display_time":"Mar 18, 2024","deploy_time":null,"url":"rag-evaluation-using-ragas","abstract":"This blog explored key RAG evaluation metrics and their calculation, along with an implementation using the Milvus vector database and the Ragas package.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":94,"name":"Christy Bergman","author_tags":"Developer Advocate","published_at":"2023-10-06T00:29:45.486Z","created_by":18,"updated_by":18,"created_at":"2023-10-06T00:29:30.751Z","updated_at":"2024-07-18T16:01:45.942Z","home_page":null,"home_page_link":null,"self_intro":"Christy Bergman is a passionate Developer Advocate at Zilliz. She previously worked in distributed computing at Anyscale and as a Specialist AI/ML Solutions Architect at AWS. Christy studied applied math, is a self-taught coder, and has published papers, including one with ACM Recsys. She enjoys hiking and bird watching.","repost_to_medium":null,"repost_state":null,"meta_description":"Christy Bergman is a passionate Developer Advocate at Zilliz. ","locale":"en"}],"read_time":7,"localizations":[{"id":1630,"locale":"fr","published_at":"2024-03-18T05:48:38.580Z"},{"id":1522,"locale":"pt","published_at":"2024-03-18T05:48:38.580Z"},{"id":1549,"locale":"ru","published_at":"2024-03-18T05:48:38.580Z"},{"id":1495,"locale":"es","published_at":"2024-03-18T05:48:38.580Z"},{"id":1603,"locale":"it","published_at":"2024-03-18T05:48:38.580Z"},{"id":1468,"locale":"de","published_at":"2024-03-18T05:48:38.580Z"},{"id":1576,"locale":"ko","published_at":"2024-03-18T05:48:38.580Z"},{"id":1121,"locale":"ja-JP","published_at":"2024-03-18T05:48:38.580Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Mar_18_RAG_Evaluation_using_Ragas_20240318_080304_62e448ec81.png","belong":"blog","authorNames":["Christy Bergman"]},{"id":"learn-87","title":" Introduction to the Falcon 180B Large Language Model (LLM)","image":{"id":2875,"url":"https://assets.zilliz.com/Mar_18_Falcon_180_B_Advancing_Language_Models_in_the_AI_Frontier_0291197bd7.png"},"display_time":"Mar 18, 2024","url":"Falcon-180B-advancing-language-models-in-AI-frontier","abstract":"Falcon 180B is an open-source large language model (LLM) with 180B parameters trained on 3.5 trillion tokens. Learn its architecture and benefits in this blog. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":3,"name":"Frank Liu","author_tags":"Director of Operations \u0026 ML Architect at Zilliz","published_at":"2021-12-23T11:08:08.015Z","created_by":18,"updated_by":18,"created_at":"2021-12-23T10:40:59.821Z","updated_at":"2023-04-21T22:30:10.416Z","home_page":"GitHub","home_page_link":"https://github.com/fzliu","self_intro":"Frank Liu is the Director of Operations \u0026 ML Architect at Zilliz, where he serves as a maintainer for the Towhee open-source project. Prior to Zilliz, Frank co-founded Orion Innovations, an ML-powered indoor positioning startup based in Shanghai and worked as an ML engineer at Yahoo in San Francisco. In his free time, Frank enjoys playing chess, swimming, and powerlifting. Frank holds MS and BS degrees in Electrical Engineering from Stanford University. ","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":8,"localizations":[{"id":375,"locale":"ja-JP","published_at":"2024-03-18T07:42:34.586Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Mar_18_Falcon_180_B_Advancing_Language_Models_in_the_AI_Frontier_0291197bd7.png","belong":"learn","authorNames":["Frank Liu"]},{"id":"learn-86","title":"Everything You Need to Know About Zero Shot Learning","image":{"id":2877,"url":"https://assets.zilliz.com/Mar_18_Everything_You_Need_to_Know_About_Zero_Shot_Learning_1_ce7aa79b2c.png"},"display_time":"Mar 16, 2024","url":"what-is-zero-shot-learning","abstract":"A comprehensive guide to Zero-Shot Learning, covering its methodologies, its relations with similarity search, and popular Zero-Shot Classification Models. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":41,"name":"Yujian Tang","author_tags":"Developer Advocate at Zilliz","published_at":"2023-04-20T21:52:47.479Z","created_by":18,"updated_by":18,"created_at":"2023-04-20T21:52:45.859Z","updated_at":"2024-07-18T16:02:07.497Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/yujiantang/","self_intro":"Yujian Tang is a Developer Advocate at Zilliz. He has a background as a software engineer working on AutoML at Amazon. Yujian studied Computer Science, Statistics, and Neuroscience with research papers published to conferences including IEEE Big Data. He enjoys drinking bubble tea, spending time with family, and being near water.","repost_to_medium":null,"repost_state":null,"meta_description":"Yujian Tang, Developer Advocate at Zilliz. ","locale":"en"}],"read_time":4,"localizations":[{"id":376,"locale":"ja-JP","published_at":"2024-03-16T07:38:54.398Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Mar_18_Everything_You_Need_to_Know_About_Zero_Shot_Learning_1_ce7aa79b2c.png","belong":"learn","authorNames":["Yujian Tang"]},{"id":"learn-85","title":"Benchmarking Vector Database Performance: Techniques and Insights","image":{"id":2816,"url":"https://assets.zilliz.com/Mar_18_Benchmarking_Vector_Database_Performance_Techniques_and_Insights_20240318_080138_249b8fc38b.png"},"display_time":"Mar 15, 2024","url":"benchmark-vector-database-performance-techniques-and-insights","abstract":"This article digs explicitly into the key evaluation metrics and benchmarking tools for vector databases. Additionally, it offers insights to aid in evaluating vector databases for informed decision-making.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":120,"name":"Min Tian","author_tags":"Software Engineer","published_at":"2024-03-16T05:39:39.262Z","created_by":18,"updated_by":18,"created_at":"2024-03-16T05:39:37.087Z","updated_at":"2024-07-18T16:00:37.188Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/min-tian-92b997237/","self_intro":"Software Engineer at Zilliz","repost_to_medium":null,"repost_state":null,"meta_description":"Min Tian, Software Engineer at Zilliz","locale":"en"}],"read_time":6,"localizations":[{"id":406,"locale":"ja-JP","published_at":"2024-03-16T05:39:57.991Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Mar_18_Benchmarking_Vector_Database_Performance_Techniques_and_Insights_20240318_080138_249b8fc38b.png","belong":"learn","authorNames":["Min Tian"]},{"id":"learn-84","title":"Safeguard Data Integrity: Backup and Recovery in Vector Databases","image":{"id":2795,"url":"https://assets.zilliz.com/Mar_01_Milvus_Backup_and_Restore_Best_Practice_44e9ae1cd3.png"},"display_time":"Mar 14, 2024","url":"vector-database-backup-and-recovery-safeguard-data-integrity","abstract":"This blog explores data backup and recovery in vectorDBs, their challenges, various methods, and specialized tools to fortify the security of your data assets.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":45,"name":"Fendy Feng","author_tags":"Technical Marketing Writer","published_at":"2023-05-16T01:36:15.102Z","created_by":18,"updated_by":18,"created_at":"2023-05-16T00:04:12.065Z","updated_at":"2024-04-25T08:37:19.712Z","home_page":"GitHub","home_page_link":"https://www.linkedin.com/in/fendy311/","self_intro":"Fendy Feng is the Technical Marketing Writer at Zilliz. She has extensive experience developing and enhancing the impact of open-source projects in various global markets by producing high-quality, tailored content. Before joining Zilliz, Fendy worked as a Content Strategist at PingCAP, a fast-growing E-Series startup renowned for its open-source distributed SQL database.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":5,"localizations":[{"id":370,"locale":"ja-JP","published_at":"2024-03-15T01:18:18.855Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Mar_01_Milvus_Backup_and_Restore_Best_Practice_44e9ae1cd3.png","belong":"learn","authorNames":["Fendy Feng"]},{"id":"blog-366","title":"Building an AI-driven Car Repair Assistant with Milvus and the OpenAI LLM","image":{"id":2788,"url":"https://assets.zilliz.com/Mar_04_Building_an_AI_Driven_Car_Repair_Assistant_with_Milvus_and_the_Open_AI_LLM_aacc8d07e0.png"},"display_time":"Mar 13, 2024","deploy_time":null,"url":"build-ai-driven-car-repair-assistant-with-milvus-and-chatgpt","abstract":"How we leverage Milvus and ChatGPT to build an AI-driven car repair assistant for interactive and reliable automotive advice and solutions. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":119,"name":"Lin Liu","author_tags":"Data Strategy Lead","published_at":"2024-03-13T12:27:57.520Z","created_by":18,"updated_by":18,"created_at":"2024-03-13T12:27:53.820Z","updated_at":"2024-03-13T12:27:57.541Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/lin-liu-innovation/","self_intro":"Data Strategy Lead","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":2,"localizations":[{"id":1288,"locale":"ja-JP","published_at":"2024-03-13T12:28:22.066Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Mar_04_Building_an_AI_Driven_Car_Repair_Assistant_with_Milvus_and_the_Open_AI_LLM_aacc8d07e0.png","belong":"blog","authorNames":["Lin Liu"]},{"id":"learn-83","title":"Information Retrieval Metrics","image":{"id":2779,"url":"https://assets.zilliz.com/Understand_Information_Retrieval_Metrics_and_learn_how_to_apply_these_metrics_to_evaluate_your_systems_1bb609d8f0.png"},"display_time":"Mar 12, 2024","url":"information-retrieval-metrics","abstract":"Understand Information Retrieval Metrics and learn how to apply these metrics to evaluate your systems. ","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":118,"name":" Haziqa Sajid","author_tags":"Freelance Technical Writer","published_at":"2024-03-12T10:25:34.265Z","created_by":18,"updated_by":18,"created_at":"2024-03-12T10:25:31.148Z","updated_at":"2024-07-03T07:58:27.010Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/haziqa-sajid-22b53245/","self_intro":"Digital Storytelling for Data, AI, B2B \u0026 SaaS","repost_to_medium":null,"repost_state":null,"meta_description":" Haziqa Sajid, Freelance Technical Writer","locale":"en"}],"read_time":5,"localizations":[{"id":371,"locale":"ja-JP","published_at":"2024-03-12T10:26:02.450Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Understand_Information_Retrieval_Metrics_and_learn_how_to_apply_these_metrics_to_evaluate_your_systems_1bb609d8f0.png","belong":"learn","authorNames":[" Haziqa Sajid"]},{"id":"blog-364","title":"Building an AI Agent for RAG with Milvus and LlamaIndex","image":{"id":2802,"url":"https://assets.zilliz.com/Mar_12_Building_an_AI_Agent_for_RAG_with_Milvus_and_Llama_Index_c628e218eb.png"},"display_time":"Mar 11, 2024","deploy_time":null,"url":"build-ai-agent-for-rag-with-milvus-and-llamaindex","abstract":"A tutorial that walks you through building an AI agent for RAG using Milvus and LlamaIndex","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":41,"name":"Yujian Tang","author_tags":"Developer Advocate at Zilliz","published_at":"2023-04-20T21:52:47.479Z","created_by":18,"updated_by":18,"created_at":"2023-04-20T21:52:45.859Z","updated_at":"2024-07-18T16:02:07.497Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/yujiantang/","self_intro":"Yujian Tang is a Developer Advocate at Zilliz. He has a background as a software engineer working on AutoML at Amazon. Yujian studied Computer Science, Statistics, and Neuroscience with research papers published to conferences including IEEE Big Data. He enjoys drinking bubble tea, spending time with family, and being near water.","repost_to_medium":null,"repost_state":null,"meta_description":"Yujian Tang, Developer Advocate at Zilliz. ","locale":"en"}],"read_time":9,"localizations":[{"id":855,"locale":"ja-JP","published_at":"2024-03-11T07:11:40.388Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Mar_12_Building_an_AI_Agent_for_RAG_with_Milvus_and_Llama_Index_c628e218eb.png","belong":"blog","authorNames":["Yujian Tang"]},{"id":"blog-363","title":"Zilliz Cloud Now Available on Azure Marketplace","image":{"id":2778,"url":"https://assets.zilliz.com/Mar_12_Zilliz_Cloud_Now_Available_on_Azure_Marketplace_Learn_More_1_4a3c35f21d.png"},"display_time":"Mar 11, 2024","deploy_time":null,"url":"zilliz-cloud-available-on-azure-marketplace","abstract":"So excited to announce Zilliz Cloud is now available on Azure Marketplace after its successful integration into AWS and GCP marketplaces. ","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":76,"name":"Steffi Li","author_tags":"Director of Product Marketing","published_at":"2023-07-13T17:18:42.023Z","created_by":18,"updated_by":18,"created_at":"2023-07-13T17:16:54.449Z","updated_at":"2023-07-13T17:18:42.070Z","home_page":null,"home_page_link":null,"self_intro":"Steffi is the Director of Product Marketing at Zilliz, with prior experience leading the GTM strategies for open-source data technologies such as Apache Kafka and Apache Airflow. Passionate about travel, yoga, and non-fiction reading, she brings a balanced and enriched worldview to her professional pursuits.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":2,"localizations":[{"id":1321,"locale":"ja-JP","published_at":"2024-03-11T07:51:36.776Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Mar_12_Zilliz_Cloud_Now_Available_on_Azure_Marketplace_Learn_More_1_4a3c35f21d.png","belong":"blog","authorNames":["Steffi Li"]},{"id":"learn-170","title":"Mastering BM25: A Deep Dive into the Algorithm and Its Application in Milvus","image":{"id":3251,"url":"https://assets.zilliz.com/Mastering_BM_25_A_Deep_Dive_into_the_Algorithm_and_Its_Application_in_Milvus_f344382aba.png"},"display_time":"Mar 08, 2024","url":"mastering-bm25-a-deep-dive-into-the-algorithm-and-application-in-milvus","abstract":"We can easily implement the BM25 algorithm to turn a document and a query into a sparse vector with Milvus. Then, these sparse vectors can be used for vector search to find the most relevant documents according to a specific query.\n","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":125,"name":"Ruben Winastwan","author_tags":"Freelance Technical Writer","published_at":"2024-03-26T09:16:27.310Z","created_by":18,"updated_by":18,"created_at":"2024-03-26T09:16:24.498Z","updated_at":"2024-07-03T07:56:29.256Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Ruben Winastwan, Freelance Technical Writer","locale":"en"}],"read_time":16,"localizations":[{"id":340,"locale":"ja-JP","published_at":"2024-04-22T18:39:01.747Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Mastering_BM_25_A_Deep_Dive_into_the_Algorithm_and_Its_Application_in_Milvus_f344382aba.png","belong":"learn","authorNames":["Ruben Winastwan"]},{"id":"learn-181","title":"A Beginner's Guide to Connecting Zilliz Cloud with Azure Marketplace","image":{"id":3377,"url":"https://assets.zilliz.com/A_Beginner_s_Guide_to_Connecting_Zilliz_Cloud_with_Azure_Marketplace_19f5d387c4.png"},"display_time":"Mar 08, 2024","url":"beginnier-guide-to-connecting-zilliz-cloud-with-azure-marketplace","abstract":"A Beginner's Guide to Connecting Zilliz Cloud with Azure Marketplace","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":151,"name":"Fariba Laiq","author_tags":"Freelance Technical Writer","published_at":"2024-04-24T21:23:59.165Z","created_by":18,"updated_by":18,"created_at":"2024-04-24T21:23:57.717Z","updated_at":"2024-07-29T16:21:27.954Z","home_page":null,"home_page_link":null,"self_intro":"Description: Fariba Laiq is a freelance content writer at Zilliz. She has studied Computer Science, been a coding instructor, and published research papers in the domain of AI and cyber-security. She is passionate about learning more about LLMs and vector databases in the ever evolving era of AI. Along with technical skills, she is also a self-taught artist.","repost_to_medium":null,"repost_state":null,"meta_description":"Fariba Laiq, Freelance Technical Writer","locale":"en"}],"read_time":7,"localizations":[{"id":433,"locale":"ja-JP","published_at":"2024-04-29T12:35:28.594Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/A_Beginner_s_Guide_to_Connecting_Zilliz_Cloud_with_Azure_Marketplace_19f5d387c4.png","belong":"learn","authorNames":["Fariba Laiq"]},{"id":"learn-137","title":"Data Modeling Techniques Optimized for Vector Databases","image":{"id":3028,"url":"https://assets.zilliz.com/Data_Modeling_Techniques_c1645539c8.png"},"display_time":"Mar 07, 2024","url":"data-modeling-techniques-optimized-for-vector-databases","abstract":"This post explores various data modeling techniques for optimizing the performance of vector databases. ","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":118,"name":" Haziqa Sajid","author_tags":"Freelance Technical Writer","published_at":"2024-03-12T10:25:34.265Z","created_by":18,"updated_by":18,"created_at":"2024-03-12T10:25:31.148Z","updated_at":"2024-07-03T07:58:27.010Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/haziqa-sajid-22b53245/","self_intro":"Digital Storytelling for Data, AI, B2B \u0026 SaaS","repost_to_medium":null,"repost_state":null,"meta_description":" Haziqa Sajid, Freelance Technical Writer","locale":"en"}],"read_time":3,"localizations":[{"id":306,"locale":"ja-JP","published_at":"2024-04-25T12:50:34.396Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Data_Modeling_Techniques_c1645539c8.png","belong":"learn","authorNames":[" Haziqa Sajid"]},{"id":"learn-169","title":"Mastering Text Similarity Search with Vectors in Zilliz Cloud","image":{"id":3248,"url":"https://assets.zilliz.com/Mastering_Text_Similarity_Search_with_Vectors_in_Zilliz_Cloud_f3b473bff2.png"},"display_time":"Mar 07, 2024","url":"mastering-text-similarity-search-with-vectors-in-zilliz-cloud","abstract":"We explore the fundamentals of vector embeddings and demonstrated their application in a practical book title search using Zilliz Cloud and OpenAI embedding models. We delve into key similarity metrics, such as cosine similarity, and discuss how these metrics play a crucial role in enhancing the relevance and accuracy of search results. Furthermore, we highlight best practices and optimization strategies essential for maximizing the performance of text similarity searches.\n","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":135,"name":"Antony G.","author_tags":"Freelance Technical Writer","published_at":"2024-03-31T20:39:48.027Z","created_by":18,"updated_by":18,"created_at":"2024-03-31T20:39:30.202Z","updated_at":"2024-07-03T07:52:52.095Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Antony G., Freelance Technical Writer","locale":"en"}],"read_time":6,"localizations":[{"id":339,"locale":"ja-JP","published_at":"2024-04-22T17:24:23.147Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Mastering_Text_Similarity_Search_with_Vectors_in_Zilliz_Cloud_f3b473bff2.png","belong":"learn","authorNames":["Antony G."]},{"id":"blog-362","title":"Stephen Batifol - Why I Joined Zilliz ","image":{"id":6533,"url":"https://assets.zilliz.com/Why_I_joined_Zilliz_Stephen_Batifol_36995ca24b.png"},"display_time":"Mar 06, 2024","deploy_time":null,"url":"why-i-joined-zilliz-stephen-batifol","abstract":"Stephen Batifol is the newly joined Developer Advocate at Zilliz. ","tags":[{"id":4,"name":"Company","published_at":"2021-01-21T02:28:23.551Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:20.676Z","updated_at":"2021-01-21T02:28:23.824Z","locale":"en"}],"authors":[{"id":115,"name":"Stephen Batifol","author_tags":"Developer Advocate ","published_at":"2024-03-07T03:46:04.655Z","created_by":18,"updated_by":18,"created_at":"2024-03-07T03:46:02.457Z","updated_at":"2024-07-18T15:56:42.529Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/stephen-batifol/","self_intro":"Stephen Batifol is a Developer Advocate at Zilliz. He previously worked as a Machine Learning Engineer at Wolt, where he was working on the ML Platform and as a Data Scientist at Brevo. Stephen studied Computer Science and Artificial Intelligence. He enjoys dancing and surfing. \n","repost_to_medium":null,"repost_state":null,"meta_description":"Stephen Batifol is a Developer Advocate at Zilliz.","locale":"en"}],"read_time":2,"localizations":[{"id":1027,"locale":"ja-JP","published_at":"2024-03-07T03:49:04.177Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Why_I_joined_Zilliz_Stephen_Batifol_36995ca24b.png","belong":"blog","authorNames":["Stephen Batifol"]},{"id":"blog-361","title":"Will Retrieval Augmented Generation (RAG) Be Killed by Long-Context LLMs? ","image":{"id":2750,"url":"https://assets.zilliz.com/Mar_07_Will_RAG_Be_Killed_By_Long_context_LL_Ms_262ff1e515.png"},"display_time":"Mar 05, 2024","deploy_time":null,"url":"will-retrieval-augmented-generation-RAG-be-killed-by-long-context-LLMs","abstract":"Explore Gemini’s long-context capabilities, limitations, and impact on RAG's evolution, and discuss whether long-context LLMs are killing RAG techniques. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":34,"name":"James Luan","author_tags":"VP of Engineering at Zilliz","published_at":"2022-05-18T03:15:15.255Z","created_by":18,"updated_by":18,"created_at":"2022-05-18T03:14:35.112Z","updated_at":"2024-01-12T21:01:29.192Z","home_page":"GitHub","home_page_link":"https://github.com/xiaofan-luan","self_intro":"James Luan is the VP of Engineering at Zilliz. With a master's degree in computer engineering from Cornell University, he has extensive experience as a Database Engineer at Oracle, Hedvig, and Alibaba Cloud. James played a crucial role in developing HBase, Alibaba Cloud's open-source database, and Lindorm, a self-developed NoSQL database. He is also a respected member of the Technical Advisory Committee of LF AI \u0026 Data Foundation, contributing his expertise to shaping the future of AI and data technologies.\n","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":8,"localizations":[{"id":1178,"locale":"ja-JP","published_at":"2024-03-06T07:21:45.120Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Mar_07_Will_RAG_Be_Killed_By_Long_context_LL_Ms_262ff1e515.png","belong":"blog","authorNames":["James Luan"]},{"id":"blog-360","title":"Using Your Vector Database as a JSON (or Relational) Datastore","image":{"id":2751,"url":"https://assets.zilliz.com/Mar_06_Using_Your_Vector_Database_as_a_JSON_or_Relational_Datastore_1_1_908a2e8149.png"},"display_time":"Mar 04, 2024","deploy_time":null,"url":"using-your-vector-database-as-JSON-or-relational-datastore","abstract":"This simple guide walks you through using your vector database to store and search your structured data.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":1,"name":"Zilliz","author_tags":"Vector database","published_at":"2021-12-14T06:36:41.397Z","created_by":18,"updated_by":18,"created_at":"2021-12-14T06:28:27.154Z","updated_at":"2023-04-11T16:54:05.275Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":6,"localizations":[{"id":946,"locale":"ja-JP","published_at":"2024-03-05T17:33:59.954Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Mar_06_Using_Your_Vector_Database_as_a_JSON_or_Relational_Datastore_1_1_908a2e8149.png","belong":"blog","authorNames":["Zilliz"]},{"id":"blog-359","title":"Zilliz Cloud Introduces BYOC for Greater Data Sovereignty and Compliance","image":{"id":2713,"url":"https://assets.zilliz.com/Feb_26_Zilliz_Cloud_Introduces_BYOC_for_Greater_Data_Sovereignty_and_Compliance_7c3d353056.png"},"display_time":"Feb 29, 2024","deploy_time":null,"url":"Zilliz-Introduces-byoc","abstract":"We're excited to introduce Zilliz Cloud BYOC, which lets you enjoy managed services while maintaining your data within your private network. ","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":76,"name":"Steffi Li","author_tags":"Director of Product Marketing","published_at":"2023-07-13T17:18:42.023Z","created_by":18,"updated_by":18,"created_at":"2023-07-13T17:16:54.449Z","updated_at":"2023-07-13T17:18:42.070Z","home_page":null,"home_page_link":null,"self_intro":"Steffi is the Director of Product Marketing at Zilliz, with prior experience leading the GTM strategies for open-source data technologies such as Apache Kafka and Apache Airflow. Passionate about travel, yoga, and non-fiction reading, she brings a balanced and enriched worldview to her professional pursuits.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":4,"localizations":[{"id":1277,"locale":"ja-JP","published_at":"2024-02-29T06:12:42.648Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Feb_26_Zilliz_Cloud_Introduces_BYOC_for_Greater_Data_Sovereignty_and_Compliance_7c3d353056.png","belong":"blog","authorNames":["Steffi Li"]},{"id":"blog-53","title":"How Sohu Enhances Personalized News Recommendation with Milvus ","image":{"id":2709,"url":"https://assets.zilliz.com/Feb_02_How_Sohu_News_Enhances_Personalized_Recommendations_with_Milvus_c29d27b6c1.png"},"display_time":"Feb 28, 2024","deploy_time":null,"url":"how-sohu-improves-its-news-recommendation-system-with-milvus","abstract":"Exploring how Sohu enhances its news recommender system with Milvus, achieving 10x faster response times and elevated recommending accuracy. ","tags":[{"id":1,"name":"Case Study","published_at":"2021-01-15T10:34:37.316Z","created_by":18,"updated_by":18,"created_at":"2021-01-15T10:34:34.857Z","updated_at":"2021-01-25T10:31:22.499Z","locale":"en"}],"authors":[{"id":45,"name":"Fendy Feng","author_tags":"Technical Marketing Writer","published_at":"2023-05-16T01:36:15.102Z","created_by":18,"updated_by":18,"created_at":"2023-05-16T00:04:12.065Z","updated_at":"2024-04-25T08:37:19.712Z","home_page":"GitHub","home_page_link":"https://www.linkedin.com/in/fendy311/","self_intro":"Fendy Feng is the Technical Marketing Writer at Zilliz. She has extensive experience developing and enhancing the impact of open-source projects in various global markets by producing high-quality, tailored content. Before joining Zilliz, Fendy worked as a Content Strategist at PingCAP, a fast-growing E-Series startup renowned for its open-source distributed SQL database.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":3,"localizations":[{"id":1354,"locale":"ja-JP","published_at":"2021-06-08T01:42:53.489Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Feb_02_How_Sohu_News_Enhances_Personalized_Recommendations_with_Milvus_c29d27b6c1.png","belong":"blog","authorNames":["Fendy Feng"]},{"id":"blog-358","title":"Finding the Right Fit: Embedding Creation for AI Retrieval (RAG) in Zilliz Cloud Pipelines from OSS, VoyageAI, and OpenAI","image":{"id":2708,"url":"https://assets.zilliz.com/Feb_22_New_in_Zilliz_Automatically_Supported_Embeddings_from_Open_Source_Voyage_AI_and_Open_AI_1_6e0ad1c11f.png"},"display_time":"Feb 27, 2024","deploy_time":null,"url":"finding-right-fit-embedding-support-for-RAG-in-zilliz-cloud-pipelines-from-voyageai-openai-and-oss","abstract":"Learn how Zilliz Cloud's support for 6 leading embedding models can improve your development of RAG apps. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":94,"name":"Christy Bergman","author_tags":"Developer Advocate","published_at":"2023-10-06T00:29:45.486Z","created_by":18,"updated_by":18,"created_at":"2023-10-06T00:29:30.751Z","updated_at":"2024-07-18T16:01:45.942Z","home_page":null,"home_page_link":null,"self_intro":"Christy Bergman is a passionate Developer Advocate at Zilliz. She previously worked in distributed computing at Anyscale and as a Specialist AI/ML Solutions Architect at AWS. Christy studied applied math, is a self-taught coder, and has published papers, including one with ACM Recsys. She enjoys hiking and bird watching.","repost_to_medium":null,"repost_state":null,"meta_description":"Christy Bergman is a passionate Developer Advocate at Zilliz. ","locale":"en"}],"read_time":12,"localizations":[{"id":1077,"locale":"ja-JP","published_at":"2024-02-27T09:39:56.971Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Feb_22_New_in_Zilliz_Automatically_Supported_Embeddings_from_Open_Source_Voyage_AI_and_Open_AI_1_6e0ad1c11f.png","belong":"blog","authorNames":["Christy Bergman"]},{"id":"blog-357","title":"Building RAG Apps Without OpenAI - Part Two: Mixtral, Milvus and OctoAI","image":{"id":3463,"url":"https://assets.zilliz.com/Apr_29_Building_RAG_Apps_Without_Open_AI_Part_Two_Mixtral_Milvus_and_Octo_AI_49685c5bce.png"},"display_time":"Feb 26, 2024","deploy_time":null,"url":"building-rag-without-openai-mixtral-milvus-octoai","abstract":"How to build your RAG apps with Mixtral, Milvus, and OctoAI. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":41,"name":"Yujian Tang","author_tags":"Developer Advocate at Zilliz","published_at":"2023-04-20T21:52:47.479Z","created_by":18,"updated_by":18,"created_at":"2023-04-20T21:52:45.859Z","updated_at":"2024-07-18T16:02:07.497Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/yujiantang/","self_intro":"Yujian Tang is a Developer Advocate at Zilliz. He has a background as a software engineer working on AutoML at Amazon. Yujian studied Computer Science, Statistics, and Neuroscience with research papers published to conferences including IEEE Big Data. He enjoys drinking bubble tea, spending time with family, and being near water.","repost_to_medium":null,"repost_state":null,"meta_description":"Yujian Tang, Developer Advocate at Zilliz. ","locale":"en"}],"read_time":9,"localizations":[{"id":1025,"locale":"ja-JP","published_at":"2024-02-26T10:59:16.524Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Apr_29_Building_RAG_Apps_Without_Open_AI_Part_Two_Mixtral_Milvus_and_Octo_AI_49685c5bce.png","belong":"blog","authorNames":["Yujian Tang"]},{"id":"blog-356","title":"Exploring Multimodal Embeddings with FiftyOne and Milvus","image":{"id":2705,"url":"https://assets.zilliz.com/Feb_26_Exploring_Multimodal_Embeddings_with_Fifty_One_and_Milvus_4697f1123d.png"},"display_time":"Feb 23, 2024","deploy_time":null,"url":"exploring-multimodal-embeddings-with-fiftyone-and-milvus","abstract":"Exploring how multimodal embeddings work with Voxel51 and Milvus.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":41,"name":"Yujian Tang","author_tags":"Developer Advocate at Zilliz","published_at":"2023-04-20T21:52:47.479Z","created_by":18,"updated_by":18,"created_at":"2023-04-20T21:52:45.859Z","updated_at":"2024-07-18T16:02:07.497Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/yujiantang/","self_intro":"Yujian Tang is a Developer Advocate at Zilliz. He has a background as a software engineer working on AutoML at Amazon. Yujian studied Computer Science, Statistics, and Neuroscience with research papers published to conferences including IEEE Big Data. He enjoys drinking bubble tea, spending time with family, and being near water.","repost_to_medium":null,"repost_state":null,"meta_description":"Yujian Tang, Developer Advocate at Zilliz. ","locale":"en"}],"read_time":6,"localizations":[{"id":1282,"locale":"ja-JP","published_at":"2024-02-24T10:26:24.079Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Feb_26_Exploring_Multimodal_Embeddings_with_Fifty_One_and_Milvus_4697f1123d.png","belong":"blog","authorNames":["Yujian Tang"]},{"id":"learn-125","title":"Exploring the Frontier of Multimodal Retrieval-Augmented Generation (RAG)","image":{"id":3008,"url":"https://assets.zilliz.com/Exploring_the_Frontier_of_Multimodal_Retrieval_Augmented_Generation_RAG_10a3a1c0ad.png"},"display_time":"Feb 21, 2024","url":"multimodal-RAG","abstract":"Multimodal RAG is an extended RAG framework incorporating multimodal data including various data types such as text, images, audio, videos etc. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":137,"name":"Tyler Falcon","author_tags":"Digital Marketing Manager at Zilliz. ","published_at":"2024-04-01T19:01:39.023Z","created_by":18,"updated_by":18,"created_at":"2024-04-01T19:01:37.126Z","updated_at":"2024-07-03T06:55:28.378Z","home_page":null,"home_page_link":null,"self_intro":"Tyler Falconis the Digital Marketing Manager at Zilliz. ","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":5,"localizations":[{"id":383,"locale":"ja-JP","published_at":"2024-04-01T19:03:53.071Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Exploring_the_Frontier_of_Multimodal_Retrieval_Augmented_Generation_RAG_10a3a1c0ad.png","belong":"learn","authorNames":["Tyler Falcon"]},{"id":"learn-110","title":"Empowering AI and Machine Learning with Vector Databases","image":{"id":2955,"url":"https://assets.zilliz.com/Empowering_AI_and_Machine_Learning_with_Vector_Databases_db96a8e90b.png"},"display_time":"Feb 20, 2024","url":"AI-and-ML-with-Vector-Databases","abstract":"As data exponentially grows, robust data management solutions like AI Databases are crucial for harnessing complex, high-dimensional data. This blog explores AI Databases' significance in enabling efficient storage, indexing, and similarity searches on vector data representations, addressing unique requirements of data-driven AI/ML applications. ","tags":[{"id":1,"name":"Case Study","published_at":"2021-01-15T10:34:37.316Z","created_by":18,"updated_by":18,"created_at":"2021-01-15T10:34:34.857Z","updated_at":"2021-01-25T10:31:22.499Z","locale":"en"}],"authors":[{"id":124,"name":"Shivek Santosh Maharaj","author_tags":"Freelance Technical Writer","published_at":"2024-03-23T06:02:23.829Z","created_by":18,"updated_by":18,"created_at":"2024-03-23T06:02:21.922Z","updated_at":"2024-07-03T07:56:37.593Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Shivek Santosh Maharaj, Freelance Technical Writer","locale":"en"}],"read_time":8,"localizations":[{"id":475,"locale":"ja-JP","published_at":"2024-03-30T17:48:56.211Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Empowering_AI_and_Machine_Learning_with_Vector_Databases_db96a8e90b.png","belong":"learn","authorNames":["Shivek Santosh Maharaj"]},{"id":"learn-81","title":" Introduction to LangChain","image":{"id":2652,"url":"https://assets.zilliz.com/Learn_Lang_Chain_bfa682bb16.png"},"display_time":"Feb 19, 2024","url":"LangChain","abstract":"A guide to LangChain, including its definition, workflow, benefits, use cases, and available resources to get started.","tags":[],"authors":[{"id":36,"name":"Chris Churilo","author_tags":"VP of Marketing","published_at":"2023-04-11T16:51:05.002Z","created_by":18,"updated_by":53,"created_at":"2023-04-11T16:42:46.067Z","updated_at":"2025-01-16T22:35:53.011Z","home_page":"GitHub","home_page_link":"https://github.com/ChrisChurilo","self_intro":"Chris Churilo is the VP of Marketing \u0026 Community at Zilliz where she leads all community, developer relations, and marketing efforts. Prior to Zilliz, Chris was a founding member of the InfluxData’s go to market efforts and helped propel the time series database platform to dominance in the market. In earlier roles she defined and designed a SaaS monitoring solution at Centroid, and prior to that she was the VP of product management at iPass and was the LOB for several cloud services that required her to track the business and operational metrics and analytics to help identify and resolve issues.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":8,"localizations":[{"id":473,"locale":"ja-JP","published_at":"2024-02-19T18:43:29.748Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Learn_Lang_Chain_bfa682bb16.png","belong":"learn","authorNames":["Chris Churilo"]},{"id":"blog-355","title":"Building Zilliz Cloud in 18 Months: Lessons Learned While Creating a Scalable Vector Search Service on the Public Cloud","image":{"id":2678,"url":"https://assets.zilliz.com/Feb_21_Building_Zilliz_Cloud_in_18_months_faf33b3d14.png"},"display_time":"Feb 16, 2024","deploy_time":null,"url":"building-zilliz-cloud-from-open-source-vector-db","abstract":"Discover the insights gained and challenges overcome during the 18-month journey of creating Zilliz Cloud, a scalable cloud service built from open-source.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":34,"name":"James Luan","author_tags":"VP of Engineering at Zilliz","published_at":"2022-05-18T03:15:15.255Z","created_by":18,"updated_by":18,"created_at":"2022-05-18T03:14:35.112Z","updated_at":"2024-01-12T21:01:29.192Z","home_page":"GitHub","home_page_link":"https://github.com/xiaofan-luan","self_intro":"James Luan is the VP of Engineering at Zilliz. With a master's degree in computer engineering from Cornell University, he has extensive experience as a Database Engineer at Oracle, Hedvig, and Alibaba Cloud. James played a crucial role in developing HBase, Alibaba Cloud's open-source database, and Lindorm, a self-developed NoSQL database. He is also a respected member of the Technical Advisory Committee of LF AI \u0026 Data Foundation, contributing his expertise to shaping the future of AI and data technologies.\n","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":13,"localizations":[{"id":1293,"locale":"ja-JP","published_at":"2024-02-16T23:25:38.302Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Feb_21_Building_Zilliz_Cloud_in_18_months_faf33b3d14.png","belong":"blog","authorNames":["James Luan"]},{"id":"learn-119","title":"Enhancing App Functionality: Optimizing Search with Vector Databases","image":{"id":2991,"url":"https://assets.zilliz.com/Enhancing_App_Functionality_Optimizing_Search_with_Vector_Databases_0905ce858b.png"},"display_time":"Feb 16, 2024","url":"Enhancing-App-Functionality-Optimizing-Search-with-Vector-Databases","abstract":"Vector databases revolutionize app development by enhancing search functionalities with their ability to perform fast, accurate, and semantic searches. ","tags":[{"id":1,"name":"Case Study","published_at":"2021-01-15T10:34:37.316Z","created_by":18,"updated_by":18,"created_at":"2021-01-15T10:34:34.857Z","updated_at":"2021-01-25T10:31:22.499Z","locale":"en"}],"authors":[{"id":121,"name":"Cahyo Subroto","author_tags":"Freelance Technical Writer","published_at":"2024-03-21T12:44:06.590Z","created_by":18,"updated_by":18,"created_at":"2024-03-21T12:44:03.831Z","updated_at":"2024-07-03T07:57:06.866Z","home_page":null,"home_page_link":null,"self_intro":"","repost_to_medium":null,"repost_state":null,"meta_description":"Cahyo Subroto, Freelance Technical Writer","locale":"en"}],"read_time":7,"localizations":[{"id":438,"locale":"ja-JP","published_at":"2024-03-31T23:47:08.099Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Enhancing_App_Functionality_Optimizing_Search_with_Vector_Databases_0905ce858b.png","belong":"learn","authorNames":["Cahyo Subroto"]},{"id":"learn-108","title":"Maintaining Data Integrity in Vector Databases","image":{"id":2965,"url":"https://assets.zilliz.com/Mar_26_Vector_Database_103_52a048d510.png"},"display_time":"Feb 13, 2024","url":"maintaining-data-integrity-in-vector-databases","abstract":"Guaranteeing that data is correct, consistent, and dependable throughout its lifecycle is important in data management, and especially in vector databases","tags":[{"id":39,"name":"VectorDB 101","published_at":"2022-09-30T05:56:34.554Z","created_by":18,"updated_by":18,"created_at":"2022-09-30T05:56:31.633Z","updated_at":"2024-07-10T07:12:04.155Z","locale":"en"}],"authors":[{"id":127,"name":"Priyanka Israni","author_tags":"Freelance Technical Writer","published_at":"2024-03-26T09:18:45.337Z","created_by":18,"updated_by":18,"created_at":"2024-03-26T09:18:42.686Z","updated_at":"2024-07-03T07:56:11.446Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Priyanka Israni, Freelance Technical Writer","locale":"en"}],"read_time":4,"localizations":[{"id":385,"locale":"ja-JP","published_at":"2024-03-30T00:44:05.723Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Mar_26_Vector_Database_103_52a048d510.png","belong":"learn","authorNames":["Priyanka Israni"]},{"id":"blog-354","title":"TL;DR Milvus Regression in LangChain v0.1.5","image":{"id":2645,"url":"https://assets.zilliz.com/Oct_26_Milvus_regression_in_Langchain_3d7835ba8f.png"},"display_time":"Feb 12, 2024","deploy_time":null,"url":"milvus-regression-in-langchain","abstract":"If you are encountering a \"KeyError: 'pk'\" error when using Langchain v0.1.5 to connect to Milvus, it is due to a recent Milvus regression not automatically generating \"pk\" field (primary key) values.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":94,"name":"Christy Bergman","author_tags":"Developer Advocate","published_at":"2023-10-06T00:29:45.486Z","created_by":18,"updated_by":18,"created_at":"2023-10-06T00:29:30.751Z","updated_at":"2024-07-18T16:01:45.942Z","home_page":null,"home_page_link":null,"self_intro":"Christy Bergman is a passionate Developer Advocate at Zilliz. She previously worked in distributed computing at Anyscale and as a Specialist AI/ML Solutions Architect at AWS. Christy studied applied math, is a self-taught coder, and has published papers, including one with ACM Recsys. She enjoys hiking and bird watching.","repost_to_medium":null,"repost_state":null,"meta_description":"Christy Bergman is a passionate Developer Advocate at Zilliz. ","locale":"en"}],"read_time":3,"localizations":[{"id":1279,"locale":"ja-JP","published_at":"2024-02-12T18:34:00.304Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Oct_26_Milvus_regression_in_Langchain_3d7835ba8f.png","belong":"blog","authorNames":["Christy Bergman"]},{"id":"learn-89","title":"Advanced Querying Techniques in Vector Databases ","image":{"id":2879,"url":"https://assets.zilliz.com/Advanced_Querying_Techniques_in_Vector_Databases8_index_types_27c5c92094.png"},"display_time":"Feb 12, 2024","url":"advanced-querying-techniques-in-vector-databases","abstract":"Vector databases enhance AI apps with advanced querying techniques like ANN, multivector, and range searches, improving data retrieval speed and accuracy.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":121,"name":"Cahyo Subroto","author_tags":"Freelance Technical Writer","published_at":"2024-03-21T12:44:06.590Z","created_by":18,"updated_by":18,"created_at":"2024-03-21T12:44:03.831Z","updated_at":"2024-07-03T07:57:06.866Z","home_page":null,"home_page_link":null,"self_intro":"","repost_to_medium":null,"repost_state":null,"meta_description":"Cahyo Subroto, Freelance Technical Writer","locale":"en"}],"read_time":8,"localizations":[{"id":445,"locale":"ja-JP","published_at":"2024-03-21T12:29:19.890Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Advanced_Querying_Techniques_in_Vector_Databases8_index_types_27c5c92094.png","belong":"learn","authorNames":["Cahyo Subroto"]},{"id":"learn-96","title":"Developing Custom Applications with Vector Databases ","image":{"id":2913,"url":"https://assets.zilliz.com/Developing_Custom_Applications_with_Vector_Databases_c209454f1d.png"},"display_time":"Feb 11, 2024","url":"custom-app-development","abstract":"How Vector Database play a pivotal role in your custom application development","tags":[{"id":1,"name":"Case Study","published_at":"2021-01-15T10:34:37.316Z","created_by":18,"updated_by":18,"created_at":"2021-01-15T10:34:34.857Z","updated_at":"2021-01-25T10:31:22.499Z","locale":"en"}],"authors":[{"id":121,"name":"Cahyo Subroto","author_tags":"Freelance Technical Writer","published_at":"2024-03-21T12:44:06.590Z","created_by":18,"updated_by":18,"created_at":"2024-03-21T12:44:03.831Z","updated_at":"2024-07-03T07:57:06.866Z","home_page":null,"home_page_link":null,"self_intro":"","repost_to_medium":null,"repost_state":null,"meta_description":"Cahyo Subroto, Freelance Technical Writer","locale":"en"}],"read_time":5,"localizations":[{"id":384,"locale":"ja-JP","published_at":"2024-03-24T01:42:56.944Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Developing_Custom_Applications_with_Vector_Databases_c209454f1d.png","belong":"learn","authorNames":["Cahyo Subroto"]},{"id":"blog-353","title":"Zilliz Cloud Pipelines February Release - 3rd Party Embedding Models and Usability Improvements!","image":{"id":2641,"url":"https://assets.zilliz.com/Feb_Zilliz_Cloud_Pipeline_402d1c087e.png"},"display_time":"Feb 09, 2024","deploy_time":"2024-02-09T16:00:00.000Z","url":"zilliz-cloud-pipelines-feb-release","abstract":"The latest updates to Zilliz Cloud Pipelines in February focuses on new embedding models and ease of use. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":101,"name":"Jiang Chen","author_tags":"Head of Ecosystem and Developer Relations","published_at":"2023-10-16T07:05:20.176Z","created_by":18,"updated_by":82,"created_at":"2023-10-16T07:05:18.702Z","updated_at":"2024-09-10T17:33:55.053Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/jiang-0616/","self_intro":"Jiang is currently Head of Ecosystem and Developer Relations at Zilliz. He has years of experience in data infrastructures and cloud security. Before joining Zilliz, he had previously served as a tech lead and product manager at Google, where he led the development of web-scale semantic understanding and search indexing that powers innovative search products such as short video search. He has extensive industry experience handling massive unstructured data and multimedia content retrieval. He has also worked on cloud authorization systems and research on data privacy technologies. Jiang holds a Master's degree in Computer Science from the University of Michigan.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":4,"localizations":[{"id":888,"locale":"ja-JP","published_at":"2024-02-09T18:29:32.161Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Feb_Zilliz_Cloud_Pipeline_402d1c087e.png","belong":"blog","authorNames":["Jiang Chen"]},{"id":"blog-350","title":"Zilliz Joins the AI Alliance: Advancing Open Innovation in AI for a Better Future","image":{"id":2633,"url":"https://assets.zilliz.com/Feb_05_Zilliz_Joins_the_AI_Alliance_08d4f52184.png"},"display_time":"Feb 08, 2024","deploy_time":"2024-02-08T16:00:00.000Z","url":"zilliz-joins-ai-alliance","abstract":"Zilliz is proud to join the AI Alliance, a consortium that fosters open innovation and responsible AI development.\n","tags":[{"id":4,"name":"Company","published_at":"2021-01-21T02:28:23.551Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:20.676Z","updated_at":"2021-01-21T02:28:23.824Z","locale":"en"}],"authors":[{"id":114,"name":"Charles Xie","author_tags":"Founder \u0026 CEO of Zilliz","published_at":"2024-02-07T19:12:09.772Z","created_by":18,"updated_by":18,"created_at":"2024-02-07T19:11:20.296Z","updated_at":"2024-02-07T19:12:09.793Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/chaoxie/","self_intro":"Charles Xie is the founder and CEO of Zilliz, focusing on building next-generation databases and search technologies for AI and LLMs applications. At Zilliz, he also invented Milvus, the world's most popular open-source vector database for production-ready AI. He is currently a board member of LF AI \u0026 Data Foundation and served as the board's chairperson in 2020 and 2021. Charles previously worked at Oracle as a founding engineer of the Oracle 12c cloud database project. Charles holds a master’s degree in computer science from the University of Wisconsin-Madison.\n","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":2,"localizations":[{"id":967,"locale":"ja-JP","published_at":"2024-02-08T16:04:21.640Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Feb_05_Zilliz_Joins_the_AI_Alliance_08d4f52184.png","belong":"blog","authorNames":["Charles Xie"]},{"id":"blog-351","title":"Introducing the Databricks Connector, a Well-Lit Solution to Streamline Unstructured Data Migration and Transformation","image":{"id":2639,"url":"https://assets.zilliz.com/Jan_24_Announcing_Integration_of_Databricks_Connector_4e5aa5dcbb.png"},"display_time":"Feb 08, 2024","deploy_time":null,"url":"introducing-databricks-connector","abstract":"The latest release of Zilliz Cloud introduces a Databricks Connector, a well-lit solution to streamline this process by integrating Apache Spark/Databricks and Milvus/Zilliz Cloud. \n","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":101,"name":"Jiang Chen","author_tags":"Head of Ecosystem and Developer Relations","published_at":"2023-10-16T07:05:20.176Z","created_by":18,"updated_by":82,"created_at":"2023-10-16T07:05:18.702Z","updated_at":"2024-09-10T17:33:55.053Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/jiang-0616/","self_intro":"Jiang is currently Head of Ecosystem and Developer Relations at Zilliz. He has years of experience in data infrastructures and cloud security. Before joining Zilliz, he had previously served as a tech lead and product manager at Google, where he led the development of web-scale semantic understanding and search indexing that powers innovative search products such as short video search. He has extensive industry experience handling massive unstructured data and multimedia content retrieval. He has also worked on cloud authorization systems and research on data privacy technologies. Jiang holds a Master's degree in Computer Science from the University of Michigan.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":5,"localizations":[{"id":1269,"locale":"ja-JP","published_at":"2024-02-08T16:08:35.526Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Jan_24_Announcing_Integration_of_Databricks_Connector_4e5aa5dcbb.png","belong":"blog","authorNames":["Jiang Chen"]},{"id":"blog-352","title":"Crafting Superior RAG for Code-Intensive Texts with Zilliz Cloud Pipelines and Voyage AI","image":{"id":2673,"url":"https://assets.zilliz.com/voyage_AI_657f6d452a.jpeg"},"display_time":"Feb 07, 2024","deploy_time":"2024-02-07T16:00:00.000Z","url":"craft-superior-rag-for-code-intensive-texts-with-zcp-and-voyage","abstract":"We are thrilled to announce that embedding models from Voyage AI are available in Zilliz Cloud Pipelines.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":101,"name":"Jiang Chen","author_tags":"Head of Ecosystem and Developer Relations","published_at":"2023-10-16T07:05:20.176Z","created_by":18,"updated_by":82,"created_at":"2023-10-16T07:05:18.702Z","updated_at":"2024-09-10T17:33:55.053Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/jiang-0616/","self_intro":"Jiang is currently Head of Ecosystem and Developer Relations at Zilliz. He has years of experience in data infrastructures and cloud security. Before joining Zilliz, he had previously served as a tech lead and product manager at Google, where he led the development of web-scale semantic understanding and search indexing that powers innovative search products such as short video search. He has extensive industry experience handling massive unstructured data and multimedia content retrieval. He has also worked on cloud authorization systems and research on data privacy technologies. Jiang holds a Master's degree in Computer Science from the University of Michigan.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":3,"localizations":[{"id":1210,"locale":"ja-JP","published_at":"2024-02-07T16:07:36.254Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/voyage_AI_657f6d452a.jpeg","belong":"blog","authorNames":["Jiang Chen"]},{"id":"blog-346","title":"The High-performance Vector Database Zilliz Cloud Now Available on Google Cloud Marketplace","image":{"id":2607,"url":"https://assets.zilliz.com/JAN_22_Zilliz_Cloud_Now_Available_on_the_GCP_Marketplace_faf2584966.png"},"display_time":"Feb 07, 2024","deploy_time":"2024-02-07T16:00:00.000Z","url":"zilliz-cloud-now-available-on-gcp-marketplace","abstract":"With Zilliz Cloud available on GCP Marketplace, you can use Google Cloud's infrastructure and resources with simplified payment methods. ","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":76,"name":"Steffi Li","author_tags":"Director of Product Marketing","published_at":"2023-07-13T17:18:42.023Z","created_by":18,"updated_by":18,"created_at":"2023-07-13T17:16:54.449Z","updated_at":"2023-07-13T17:18:42.070Z","home_page":null,"home_page_link":null,"self_intro":"Steffi is the Director of Product Marketing at Zilliz, with prior experience leading the GTM strategies for open-source data technologies such as Apache Kafka and Apache Airflow. Passionate about travel, yoga, and non-fiction reading, she brings a balanced and enriched worldview to her professional pursuits.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":3,"localizations":[{"id":1267,"locale":"ja-JP","published_at":"2024-02-07T16:06:14.968Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/JAN_22_Zilliz_Cloud_Now_Available_on_the_GCP_Marketplace_faf2584966.png","belong":"blog","authorNames":["Steffi Li"]},{"id":"blog-347","title":"Zilliz Cloud Enhances Data Protection with More Granular RBAC ","image":{"id":2618,"url":"https://assets.zilliz.com/JAN_22_RBAC_Best_Practice_5984f9c330.png"},"display_time":"Feb 06, 2024","deploy_time":"2024-02-07T00:30:00.000Z","url":"zilliz-cloud-enhances-data-protection-with-more-granular-RBAC","abstract":"Zilliz Cloud presents more nuanced RBAC capabilities for improved access management, data isolation, and protection.","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":39,"name":"Sarah Tang","author_tags":"Senior Product Manager","published_at":"2023-04-12T03:08:03.943Z","created_by":18,"updated_by":18,"created_at":"2023-04-12T02:56:07.784Z","updated_at":"2023-04-12T03:11:53.050Z","home_page":"linkedin","home_page_link":"https://www.linkedin.com/in/xue-tang-070734169/","self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":5,"localizations":[{"id":921,"locale":"ja-JP","published_at":"2024-02-06T16:13:29.486Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/JAN_22_RBAC_Best_Practice_5984f9c330.png","belong":"blog","authorNames":["Sarah Tang"]},{"id":"blog-349","title":"Choosing a Vector Database: Milvus vs. Chroma DB","image":{"id":2629,"url":"https://assets.zilliz.com/Feb_05_Chroma_vs_Milvus_20240202_024325_1633ccfc67.png"},"display_time":"Feb 05, 2024","deploy_time":"2024-02-05T20:00:00.000Z","url":"milvus-vs-chroma","abstract":"In-depth differences between Milvus and Chroma vector databases","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":45,"name":"Fendy Feng","author_tags":"Technical Marketing Writer","published_at":"2023-05-16T01:36:15.102Z","created_by":18,"updated_by":18,"created_at":"2023-05-16T00:04:12.065Z","updated_at":"2024-04-25T08:37:19.712Z","home_page":"GitHub","home_page_link":"https://www.linkedin.com/in/fendy311/","self_intro":"Fendy Feng is the Technical Marketing Writer at Zilliz. She has extensive experience developing and enhancing the impact of open-source projects in various global markets by producing high-quality, tailored content. Before joining Zilliz, Fendy worked as a Content Strategist at PingCAP, a fast-growing E-Series startup renowned for its open-source distributed SQL database.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":10,"localizations":[{"id":881,"locale":"ja-JP","published_at":"2024-02-05T16:03:10.636Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Feb_05_Chroma_vs_Milvus_20240202_024325_1633ccfc67.png","belong":"blog","authorNames":["Fendy Feng"]},{"id":"learn-109","title":"Leveraging Vector Databases for Enhanced Competitive Intelligence ","image":{"id":2966,"url":"https://assets.zilliz.com/Leveraging_Vector_Databases_for_Enhanced_Competitive_Intelligence_7db5eb6448.png"},"display_time":"Feb 05, 2024","url":"leveraging-vector-databases-enhanced-competitive-intelligence","abstract":"Dig in to learn how vector databases are a powerful infrastructure component for creating highly efficient competitive intelligence (CI) tools.","tags":[{"id":39,"name":"VectorDB 101","published_at":"2022-09-30T05:56:34.554Z","created_by":18,"updated_by":18,"created_at":"2022-09-30T05:56:31.633Z","updated_at":"2024-07-10T07:12:04.155Z","locale":"en"}],"authors":[{"id":121,"name":"Cahyo Subroto","author_tags":"Freelance Technical Writer","published_at":"2024-03-21T12:44:06.590Z","created_by":18,"updated_by":18,"created_at":"2024-03-21T12:44:03.831Z","updated_at":"2024-07-03T07:57:06.866Z","home_page":null,"home_page_link":null,"self_intro":"","repost_to_medium":null,"repost_state":null,"meta_description":"Cahyo Subroto, Freelance Technical Writer","locale":"en"}],"read_time":4,"localizations":[{"id":362,"locale":"ja-JP","published_at":"2024-03-30T03:11:37.856Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Leveraging_Vector_Databases_for_Enhanced_Competitive_Intelligence_7db5eb6448.png","belong":"learn","authorNames":["Cahyo Subroto"]},{"id":"blog-348","title":"An Introduction to Milvus Architecture","image":{"id":2627,"url":"https://assets.zilliz.com/Milvus_Architecture_1_e367a4e0b8.png"},"display_time":"Feb 02, 2024","deploy_time":null,"url":"introduction-to-milvus-architecture","abstract":"Exploring the architecture of Milvus and what makes it so scalable. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":41,"name":"Yujian Tang","author_tags":"Developer Advocate at Zilliz","published_at":"2023-04-20T21:52:47.479Z","created_by":18,"updated_by":18,"created_at":"2023-04-20T21:52:45.859Z","updated_at":"2024-07-18T16:02:07.497Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/yujiantang/","self_intro":"Yujian Tang is a Developer Advocate at Zilliz. He has a background as a software engineer working on AutoML at Amazon. Yujian studied Computer Science, Statistics, and Neuroscience with research papers published to conferences including IEEE Big Data. He enjoys drinking bubble tea, spending time with family, and being near water.","repost_to_medium":null,"repost_state":null,"meta_description":"Yujian Tang, Developer Advocate at Zilliz. ","locale":"en"}],"read_time":6,"localizations":[{"id":1066,"locale":"ja-JP","published_at":"2024-02-02T06:27:54.562Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Milvus_Architecture_1_e367a4e0b8.png","belong":"blog","authorNames":["Yujian Tang"]},{"id":"learn-105","title":"From Rows and Columns to Vectors: The Evolutionary Journey of Database Technologies ","image":{"id":2957,"url":"https://assets.zilliz.com/From_Rows_and_Columns_to_Vectors_The_Evolutionary_Journey_of_Database_Technologies_1ca29a46e1.png"},"display_time":"Feb 02, 2024","url":"from-sql-and-nosql-to-vectors-database-evolution-journey","abstract":"From structured SQL and NoSQL and cutting-edge vector databases, this journey undertakes a significant transformation in data management strategies.\n","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":121,"name":"Cahyo Subroto","author_tags":"Freelance Technical Writer","published_at":"2024-03-21T12:44:06.590Z","created_by":18,"updated_by":18,"created_at":"2024-03-21T12:44:03.831Z","updated_at":"2024-07-03T07:57:06.866Z","home_page":null,"home_page_link":null,"self_intro":"","repost_to_medium":null,"repost_state":null,"meta_description":"Cahyo Subroto, Freelance Technical Writer","locale":"en"}],"read_time":6,"localizations":[{"id":363,"locale":"ja-JP","published_at":"2024-03-30T19:26:56.961Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/From_Rows_and_Columns_to_Vectors_The_Evolutionary_Journey_of_Database_Technologies_1ca29a46e1.png","belong":"learn","authorNames":["Cahyo Subroto"]},{"id":"blog-345","title":"Introducing Cardinal: The Most Performant Engine For Vector Searches","image":{"id":2625,"url":"https://assets.zilliz.com/cardinal_search_engine_a8b2c79285.jpg"},"display_time":"Feb 01, 2024","deploy_time":null,"url":"cardinal-most-performant-vector-search-engine","abstract":"Cardinal has demonstrated a 3x increase in performance compared to the previous version, offering a 10x higher search performance (QPS) than Milvus. \n","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":105,"name":"Alexandr Guzhva","author_tags":"Principal Software Engineer at Zilliz","published_at":"2023-11-02T02:16:35.636Z","created_by":18,"updated_by":18,"created_at":"2023-10-31T23:24:45.365Z","updated_at":"2024-07-18T15:59:06.874Z","home_page":null,"home_page_link":null,"self_intro":"Alexandr Guzhva is the Principal Engineer at Zilliz. Before joining Zilliz, he spent 15 years in the finance industry, working as a Quantitative Developer on designing software for algo-trading, time series prediction and performance optimization for CPU/GPU hardware. He is one of the authors of the FAISS library, which he helped to optimize during his work in Meta. Overall, he has been using methods from the similarity search for 10 years. Alexandr holds PhD in CS and MS in Physics from Lomonosov Moscow State University.","repost_to_medium":null,"repost_state":null,"meta_description":"Alexandr Guzhva is the Principal Engineer at Zilliz. ","locale":"en"}],"read_time":8,"localizations":[{"id":867,"locale":"ja-JP","published_at":"2024-02-01T08:34:23.566Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/cardinal_search_engine_a8b2c79285.jpg","belong":"blog","authorNames":["Alexandr Guzhva"]},{"id":"blog-341","title":"New for Zilliz Cloud: Cardinal Search Engine, GCP Marketplace, Databricks Connector and More","image":{"id":2587,"url":"https://assets.zilliz.com/JAN_24_Announcing_Zilliz_Cloud_23fd6bcec9.png"},"display_time":"Jan 30, 2024","deploy_time":null,"url":"Zilliz-Jan-24-launch-Milvus-2-3-RBAC-Databricks-Connector","abstract":"Cardinal search engine, Databricks Connector, improved RBAC and Milvus 2.3 features, delivering superior performance and user experience.","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":76,"name":"Steffi Li","author_tags":"Director of Product Marketing","published_at":"2023-07-13T17:18:42.023Z","created_by":18,"updated_by":18,"created_at":"2023-07-13T17:16:54.449Z","updated_at":"2023-07-13T17:18:42.070Z","home_page":null,"home_page_link":null,"self_intro":"Steffi is the Director of Product Marketing at Zilliz, with prior experience leading the GTM strategies for open-source data technologies such as Apache Kafka and Apache Airflow. Passionate about travel, yoga, and non-fiction reading, she brings a balanced and enriched worldview to her professional pursuits.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":7,"localizations":[{"id":930,"locale":"ja-JP","published_at":"2024-01-30T09:55:18.169Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/JAN_24_Announcing_Zilliz_Cloud_23fd6bcec9.png","belong":"blog","authorNames":["Steffi Li"]},{"id":"blog-343","title":"Nurturing Innovation: Our Approach to Feature Deployment from Open-Source Milvus to Zilliz Cloud","image":{"id":2592,"url":"https://assets.zilliz.com/JAN_24_Why_we_don_t_have_feature_parity_between_Zilliz_and_Milvus_a92008668c.png"},"display_time":"Jan 30, 2024","deploy_time":null,"url":"nurturing-innovation-approach-to-feature-deployment-from-opensource-milvus-to-zilliz-cloud","abstract":"Why and how do we transition extraordinary features from Milvus to Zilliz Cloud?","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":34,"name":"James Luan","author_tags":"VP of Engineering at Zilliz","published_at":"2022-05-18T03:15:15.255Z","created_by":18,"updated_by":18,"created_at":"2022-05-18T03:14:35.112Z","updated_at":"2024-01-12T21:01:29.192Z","home_page":"GitHub","home_page_link":"https://github.com/xiaofan-luan","self_intro":"James Luan is the VP of Engineering at Zilliz. With a master's degree in computer engineering from Cornell University, he has extensive experience as a Database Engineer at Oracle, Hedvig, and Alibaba Cloud. James played a crucial role in developing HBase, Alibaba Cloud's open-source database, and Lindorm, a self-developed NoSQL database. He is also a respected member of the Technical Advisory Committee of LF AI \u0026 Data Foundation, contributing his expertise to shaping the future of AI and data technologies.\n","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":2,"localizations":[{"id":1074,"locale":"ja-JP","published_at":"2024-01-31T03:36:30.022Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/JAN_24_Why_we_don_t_have_feature_parity_between_Zilliz_and_Milvus_a92008668c.png","belong":"blog","authorNames":["James Luan"]},{"id":"blog-342","title":"The Best Vector Database Just Got Better","image":{"id":2589,"url":"https://assets.zilliz.com/JAN_24_3_use_cases_driving_the_latest_release_1_59c297ae46.png"},"display_time":"Jan 30, 2024","deploy_time":null,"url":"driving-business-impact-vector-database","abstract":"Zilliz Cloud's new features drive huge business impact for real-world use cases like autonomous agents, recommenders, and AI-powered drug discovery. ","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":1,"name":"Zilliz","author_tags":"Vector database","published_at":"2021-12-14T06:36:41.397Z","created_by":18,"updated_by":18,"created_at":"2021-12-14T06:28:27.154Z","updated_at":"2023-04-11T16:54:05.275Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":5,"localizations":[{"id":1238,"locale":"ja-JP","published_at":"2024-01-30T09:57:10.980Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/JAN_24_3_use_cases_driving_the_latest_release_1_59c297ae46.png","belong":"blog","authorNames":["Zilliz"]},{"id":"blog-344","title":"Sharding, Partitioning, and Segments - Getting the Most From Your Database","image":{"id":2604,"url":"https://assets.zilliz.com/Jan_31_Sharding_Partitioning_and_Segments_2212434362.png"},"display_time":"Jan 29, 2024","deploy_time":null,"url":"sharding-partitioning-segments-get-most-from-your-database","abstract":"Delving into key distributed data concepts, particularly sharding, partitions, and segments.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":94,"name":"Christy Bergman","author_tags":"Developer Advocate","published_at":"2023-10-06T00:29:45.486Z","created_by":18,"updated_by":18,"created_at":"2023-10-06T00:29:30.751Z","updated_at":"2024-07-18T16:01:45.942Z","home_page":null,"home_page_link":null,"self_intro":"Christy Bergman is a passionate Developer Advocate at Zilliz. She previously worked in distributed computing at Anyscale and as a Specialist AI/ML Solutions Architect at AWS. Christy studied applied math, is a self-taught coder, and has published papers, including one with ACM Recsys. She enjoys hiking and bird watching.","repost_to_medium":null,"repost_state":null,"meta_description":"Christy Bergman is a passionate Developer Advocate at Zilliz. ","locale":"en"}],"read_time":7,"localizations":[{"id":1526,"locale":"pt","published_at":"2024-01-30T13:17:29.449Z"},{"id":1472,"locale":"de","published_at":"2024-01-30T13:17:29.449Z"},{"id":1553,"locale":"ru","published_at":"2024-01-30T13:17:29.449Z"},{"id":1580,"locale":"ko","published_at":"2024-01-30T13:17:29.449Z"},{"id":1634,"locale":"fr","published_at":"2024-01-30T13:17:29.449Z"},{"id":1607,"locale":"it","published_at":"2024-01-30T13:17:29.449Z"},{"id":1275,"locale":"ja-JP","published_at":"2024-01-30T13:17:29.449Z"},{"id":1499,"locale":"es","published_at":"2024-01-30T13:17:29.449Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Jan_31_Sharding_Partitioning_and_Segments_2212434362.png","belong":"blog","authorNames":["Christy Bergman"]},{"id":"blog-340","title":"Zilliz Vector Search Algorithm Dominates All Four Tracks of BigANN","image":{"id":2575,"url":"https://assets.zilliz.com/JAN_25_Zilliz_algorithm_sets_new_records_for_Big_ANN_3e2f86bb68.png"},"display_time":"Jan 26, 2024","deploy_time":null,"url":"zilliz-vector-search-algorithm-dominates-BigANN","abstract":"Zilliz's vector search algorithm surpasses BigANN submissions across all four tracks, achieving 2.5x performance improvement.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":70,"name":"Li Liu","author_tags":"Principal Engineer","published_at":"2023-06-15T05:16:42.032Z","created_by":18,"updated_by":18,"created_at":"2023-06-15T05:15:15.087Z","updated_at":"2024-07-18T15:59:40.729Z","home_page":"GitHub","home_page_link":"https://github.com/liliu-z","self_intro":"Li Liu is the Principal Engineer at Zilliz, leading the vector searching research and development. Before joining Zilliz, he was a Senior Engineer at Meta, designing and shaping numerous advertising stream data frameworks. With a Master's degree from Carnegie Mellon University, he boasts extensive experience in databases and big data. Li Liu's expertise in technology and innovation continues to drive advancements in vector searching, leaving a lasting impact on the field.\n","repost_to_medium":null,"repost_state":null,"meta_description":"Li Liu is the Principal Engineer at Zilliz, leading the vector searching research and development.","locale":"en"}],"read_time":7,"localizations":[{"id":1222,"locale":"ja-JP","published_at":"2024-01-27T02:04:23.712Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/JAN_25_Zilliz_algorithm_sets_new_records_for_Big_ANN_3e2f86bb68.png","belong":"blog","authorNames":["Li Liu"]},{"id":"blog-66","title":"How VIPSHOP Elevated Its E-commerce Recommender 10x Faster with Milvus","image":{"id":2581,"url":"https://assets.zilliz.com/How_VIPSHOP_Elevated_its_E_commerce_Recommender_10x_Faster_with_Milvus_9fb4eb2fb9.png"},"display_time":"Jan 24, 2024","deploy_time":null,"url":"building-a-personalized-product-recommender-system-with-vipshop-and-milvus","abstract":"Milvus has propelled VIPSHOP's recommender system to 10x faster recommendations, fortified its scalability, and reduced maintenance costs. ","tags":[{"id":1,"name":"Case Study","published_at":"2021-01-15T10:34:37.316Z","created_by":18,"updated_by":18,"created_at":"2021-01-15T10:34:34.857Z","updated_at":"2021-01-25T10:31:22.499Z","locale":"en"}],"authors":[{"id":45,"name":"Fendy Feng","author_tags":"Technical Marketing Writer","published_at":"2023-05-16T01:36:15.102Z","created_by":18,"updated_by":18,"created_at":"2023-05-16T00:04:12.065Z","updated_at":"2024-04-25T08:37:19.712Z","home_page":"GitHub","home_page_link":"https://www.linkedin.com/in/fendy311/","self_intro":"Fendy Feng is the Technical Marketing Writer at Zilliz. She has extensive experience developing and enhancing the impact of open-source projects in various global markets by producing high-quality, tailored content. Before joining Zilliz, Fendy worked as a Content Strategist at PingCAP, a fast-growing E-Series startup renowned for its open-source distributed SQL database.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":4,"localizations":[{"id":1284,"locale":"ja-JP","published_at":"2021-07-29T08:46:39.920Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/How_VIPSHOP_Elevated_its_E_commerce_Recommender_10x_Faster_with_Milvus_9fb4eb2fb9.png","belong":"blog","authorNames":["Fendy Feng"]},{"id":"learn-102","title":"Building Interactive AI Chatbots with Vector Databases","image":{"id":2947,"url":"https://assets.zilliz.com/Aug_18_How_to_build_an_AI_chatbot_with_Milvus_1_7ae742a33e.png"},"display_time":"Jan 19, 2024","url":"build-interactive-AI-chatbots-with-vector-database","abstract":"Vector database-powered AI chatbots deliver personalized, context-aware interactions, optimizing user experience through advanced NLP and tech integration.","tags":[{"id":1,"name":"Case Study","published_at":"2021-01-15T10:34:37.316Z","created_by":18,"updated_by":18,"created_at":"2021-01-15T10:34:34.857Z","updated_at":"2021-01-25T10:31:22.499Z","locale":"en"}],"authors":[{"id":128,"name":"Ankur Ashtikar","author_tags":"Freelance Technical Writer","published_at":"2024-03-27T03:03:55.532Z","created_by":18,"updated_by":18,"created_at":"2024-03-27T03:03:53.778Z","updated_at":"2024-07-03T07:56:02.455Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Ankur Ashtikar, Freelance Technical Writer","locale":"en"}],"read_time":7,"localizations":[{"id":311,"locale":"ja-JP","published_at":"2024-03-27T03:05:25.253Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Aug_18_How_to_build_an_AI_chatbot_with_Milvus_1_7ae742a33e.png","belong":"learn","authorNames":["Ankur Ashtikar"]},{"id":"learn-77","title":"Training Your Own Text Embedding Model","image":{"id":2564,"url":"https://assets.zilliz.com/JAN_19_Training_Your_Own_Text_Embedding_Model_63b2fb6e2d.png"},"display_time":"Jan 18, 2024","url":"training-your-own-text-embedding-model","abstract":"Explore how to train your text embedding model using the `sentence-transformers` library and generate our training data by leveraging a pre-trained LLM.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":3,"name":"Frank Liu","author_tags":"Director of Operations \u0026 ML Architect at Zilliz","published_at":"2021-12-23T11:08:08.015Z","created_by":18,"updated_by":18,"created_at":"2021-12-23T10:40:59.821Z","updated_at":"2023-04-21T22:30:10.416Z","home_page":"GitHub","home_page_link":"https://github.com/fzliu","self_intro":"Frank Liu is the Director of Operations \u0026 ML Architect at Zilliz, where he serves as a maintainer for the Towhee open-source project. Prior to Zilliz, Frank co-founded Orion Innovations, an ML-powered indoor positioning startup based in Shanghai and worked as an ML engineer at Yahoo in San Francisco. In his free time, Frank enjoys playing chess, swimming, and powerlifting. Frank holds MS and BS degrees in Electrical Engineering from Stanford University. ","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":6,"localizations":[{"id":520,"locale":"ko","published_at":"2024-01-21T10:01:10.863Z"},{"id":511,"locale":"es","published_at":"2024-01-21T10:01:10.863Z"},{"id":508,"locale":"de","published_at":"2024-01-21T10:01:10.863Z"},{"id":523,"locale":"it","published_at":"2024-01-21T10:01:10.863Z"},{"id":517,"locale":"ru","published_at":"2024-01-21T10:01:10.863Z"},{"id":514,"locale":"pt","published_at":"2024-01-21T10:01:10.863Z"},{"id":398,"locale":"ja-JP","published_at":"2024-01-21T10:01:10.863Z"},{"id":526,"locale":"fr","published_at":"2024-01-21T10:01:10.863Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/JAN_19_Training_Your_Own_Text_Embedding_Model_63b2fb6e2d.png","belong":"learn","authorNames":["Frank Liu"]},{"id":"learn-118","title":"Vector Databases: Redefining the Future of Search Technology","image":{"id":2989,"url":"https://assets.zilliz.com/Vector_Databases_Redefining_the_Future_of_Search_Technology_93f63e2883.png"},"display_time":"Jan 18, 2024","url":"Vector-Databases-Redefining-the-Future-of-Search-Technology","abstract":"The landscape of search technology is rapidly evolving, driven by the quest for faster, more accurate, and context-aware search capabilities.","tags":[{"id":1,"name":"Case Study","published_at":"2021-01-15T10:34:37.316Z","created_by":18,"updated_by":18,"created_at":"2021-01-15T10:34:34.857Z","updated_at":"2021-01-25T10:31:22.499Z","locale":"en"}],"authors":[{"id":124,"name":"Shivek Santosh Maharaj","author_tags":"Freelance Technical Writer","published_at":"2024-03-23T06:02:23.829Z","created_by":18,"updated_by":18,"created_at":"2024-03-23T06:02:21.922Z","updated_at":"2024-07-03T07:56:37.593Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Shivek Santosh Maharaj, Freelance Technical Writer","locale":"en"}],"read_time":7,"localizations":[{"id":389,"locale":"ja-JP","published_at":"2024-03-31T23:08:11.293Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Vector_Databases_Redefining_the_Future_of_Search_Technology_93f63e2883.png","belong":"learn","authorNames":["Shivek Santosh Maharaj"]},{"id":"blog-338","title":"Building RAG Apps Without OpenAI - Part One","image":{"id":2557,"url":"https://assets.zilliz.com/JAN_18_Building_RAG_Apps_Without_Open_AI_Part_One_18955e193c.png"},"display_time":"Jan 17, 2024","deploy_time":null,"url":"building-rag-apps-without-openai-part-I","abstract":"Learn how to build a RAG app using the Milvus vector database, the Nebula LLM, and the MPNet V2 embedding model. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":41,"name":"Yujian Tang","author_tags":"Developer Advocate at Zilliz","published_at":"2023-04-20T21:52:47.479Z","created_by":18,"updated_by":18,"created_at":"2023-04-20T21:52:45.859Z","updated_at":"2024-07-18T16:02:07.497Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/yujiantang/","self_intro":"Yujian Tang is a Developer Advocate at Zilliz. He has a background as a software engineer working on AutoML at Amazon. Yujian studied Computer Science, Statistics, and Neuroscience with research papers published to conferences including IEEE Big Data. He enjoys drinking bubble tea, spending time with family, and being near water.","repost_to_medium":null,"repost_state":null,"meta_description":"Yujian Tang, Developer Advocate at Zilliz. ","locale":"en"}],"read_time":7,"localizations":[{"id":1187,"locale":"ja-JP","published_at":"2024-01-18T06:23:35.735Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/JAN_18_Building_RAG_Apps_Without_Open_AI_Part_One_18955e193c.png","belong":"blog","authorNames":["Yujian Tang"]},{"id":"blog-57","title":"How Mozat's Stylepedia and Milvus Are Redefining Your Closet","image":{"id":2551,"url":"https://assets.zilliz.com/Mozat_Personalizes_Fashion_Discovery_With_Image_Similarity_Search_Using_Milvus_2e6e2514da.png"},"display_time":"Jan 16, 2024","deploy_time":null,"url":"building-a-wardrobe-and-outfit-planning-app-with-milvus","abstract":"Learn how Mozat uses Milvus to create an AI-powered image search system. ","tags":[{"id":1,"name":"Case Study","published_at":"2021-01-15T10:34:37.316Z","created_by":18,"updated_by":18,"created_at":"2021-01-15T10:34:34.857Z","updated_at":"2021-01-25T10:31:22.499Z","locale":"en"}],"authors":[{"id":45,"name":"Fendy Feng","author_tags":"Technical Marketing Writer","published_at":"2023-05-16T01:36:15.102Z","created_by":18,"updated_by":18,"created_at":"2023-05-16T00:04:12.065Z","updated_at":"2024-04-25T08:37:19.712Z","home_page":"GitHub","home_page_link":"https://www.linkedin.com/in/fendy311/","self_intro":"Fendy Feng is the Technical Marketing Writer at Zilliz. She has extensive experience developing and enhancing the impact of open-source projects in various global markets by producing high-quality, tailored content. Before joining Zilliz, Fendy worked as a Content Strategist at PingCAP, a fast-growing E-Series startup renowned for its open-source distributed SQL database.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":2,"localizations":[{"id":1243,"locale":"ja-JP","published_at":"2021-07-09T06:30:06.439Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Mozat_Personalizes_Fashion_Discovery_With_Image_Similarity_Search_Using_Milvus_2e6e2514da.png","belong":"blog","authorNames":["Fendy Feng"]},{"id":"blog-337","title":"What’s New in Milvus 2.3.4","image":{"id":2545,"url":"https://assets.zilliz.com/Jan_10_What_is_new_in_Milvus_2_3_4_ee14e70e25.png"},"display_time":"Jan 15, 2024","deploy_time":null,"url":"what-is-new-in-milvus-2-3-4","abstract":"Introducing Milvus 2.3.4 with the support for Access Logs, Parquet File imports, expanded collections/partitions, and more! ","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":76,"name":"Steffi Li","author_tags":"Director of Product Marketing","published_at":"2023-07-13T17:18:42.023Z","created_by":18,"updated_by":18,"created_at":"2023-07-13T17:16:54.449Z","updated_at":"2023-07-13T17:18:42.070Z","home_page":null,"home_page_link":null,"self_intro":"Steffi is the Director of Product Marketing at Zilliz, with prior experience leading the GTM strategies for open-source data technologies such as Apache Kafka and Apache Airflow. Passionate about travel, yoga, and non-fiction reading, she brings a balanced and enriched worldview to her professional pursuits.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":2,"localizations":[{"id":1075,"locale":"ja-JP","published_at":"2024-01-15T09:38:54.537Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Jan_10_What_is_new_in_Milvus_2_3_4_ee14e70e25.png","belong":"blog","authorNames":["Steffi Li"]},{"id":"learn-114","title":"Everything You Need to Know About Recommendation Systems and Using Them with Vector Database Technology","image":{"id":2979,"url":"https://assets.zilliz.com/Everything_You_Need_to_Know_About_Recommendation_Systems_and_Using_Them_with_Vector_Database_Technology_e140874715.png"},"display_time":"Jan 15, 2024","url":"Introduction-to-Recommendation-systems","abstract":"How you can build an AI powered Recommendation System with Vector Search","tags":[{"id":1,"name":"Case Study","published_at":"2021-01-15T10:34:37.316Z","created_by":18,"updated_by":18,"created_at":"2021-01-15T10:34:34.857Z","updated_at":"2021-01-25T10:31:22.499Z","locale":"en"}],"authors":[{"id":133,"name":"Ehsanullah Baig","author_tags":"Freelance Technical Writer","published_at":"2024-03-31T17:41:49.656Z","created_by":18,"updated_by":18,"created_at":"2024-03-31T17:28:32.019Z","updated_at":"2024-07-03T07:53:19.713Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Ehsanullah Baig, Freelance Technical Writer","locale":"en"}],"read_time":9,"localizations":[{"id":410,"locale":"ja-JP","published_at":"2024-03-31T17:42:12.692Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Everything_You_Need_to_Know_About_Recommendation_Systems_and_Using_Them_with_Vector_Database_Technology_e140874715.png","belong":"learn","authorNames":["Ehsanullah Baig"]},{"id":"learn-113","title":"Revolutionizing IoT Analytics and Device Data with Vector Databases","image":{"id":2977,"url":"https://assets.zilliz.com/Revolutionizing_Io_T_Analytics_and_Device_Data_with_Vector_Databases_3e4d3273c1.png"},"display_time":"Jan 13, 2024","url":"Revolutionizing-IoT-Analytics-and-Device-Data-with-Vector-Databases","abstract":"Vector databases, tailored to manage the high-dimensional data characteristic of IoT devices, stand at the forefront of addressing the inherent challenges of Volume, Velocity, Variety, and Veracity that frustrate traditional data management systems. This specialized data handling is a technical improvement and a paradigm shift, ushering in a new age of IoT data utilization marked by efficiency, accuracy, and scalability.","tags":[{"id":1,"name":"Case Study","published_at":"2021-01-15T10:34:37.316Z","created_by":18,"updated_by":18,"created_at":"2021-01-15T10:34:34.857Z","updated_at":"2021-01-25T10:31:22.499Z","locale":"en"}],"authors":[{"id":132,"name":"Rahul ","author_tags":"Freelance Technical Writer","published_at":"2024-03-30T21:57:22.495Z","created_by":18,"updated_by":18,"created_at":"2024-03-30T21:57:19.140Z","updated_at":"2024-07-03T07:53:30.991Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Rahul, Freelance Technical Writer","locale":"en"}],"read_time":8,"localizations":[{"id":329,"locale":"ja-JP","published_at":"2024-03-30T21:59:23.149Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Revolutionizing_Io_T_Analytics_and_Device_Data_with_Vector_Databases_3e4d3273c1.png","belong":"learn","authorNames":["Rahul "]},{"id":"blog-336","title":"Understanding Consistency Models for Vector Databases","image":{"id":2538,"url":"https://assets.zilliz.com/Dec_18_Tunable_Consistency_f7d53a49c0.png"},"display_time":"Jan 11, 2024","deploy_time":null,"url":"understand-consistency-models-for-vector-databases","abstract":"Discovering data consistency and the four consistency models Milvus offers. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":41,"name":"Yujian Tang","author_tags":"Developer Advocate at Zilliz","published_at":"2023-04-20T21:52:47.479Z","created_by":18,"updated_by":18,"created_at":"2023-04-20T21:52:45.859Z","updated_at":"2024-07-18T16:02:07.497Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/yujiantang/","self_intro":"Yujian Tang is a Developer Advocate at Zilliz. He has a background as a software engineer working on AutoML at Amazon. Yujian studied Computer Science, Statistics, and Neuroscience with research papers published to conferences including IEEE Big Data. He enjoys drinking bubble tea, spending time with family, and being near water.","repost_to_medium":null,"repost_state":null,"meta_description":"Yujian Tang, Developer Advocate at Zilliz. ","locale":"en"}],"read_time":6,"localizations":[{"id":828,"locale":"ja-JP","published_at":"2024-01-11T09:14:17.880Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Dec_18_Tunable_Consistency_f7d53a49c0.png","belong":"blog","authorNames":["Yujian Tang"]},{"id":"learn-76","title":"Sentence Transformers for Long-Form Text","image":{"id":2524,"url":"https://assets.zilliz.com/Dec_6_Sentence_Transformer_A_Comprehensive_Guide_cd27b87a82.png"},"display_time":"Jan 10, 2024","url":"Sentence-Transformers-for-Long-Form-Text","abstract":"Learn about sentence transformers for long-form text, Sentence-BERT architecture and use the IMDB dataset for evaluating different embedding models.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":3,"name":"Frank Liu","author_tags":"Director of Operations \u0026 ML Architect at Zilliz","published_at":"2021-12-23T11:08:08.015Z","created_by":18,"updated_by":18,"created_at":"2021-12-23T10:40:59.821Z","updated_at":"2023-04-21T22:30:10.416Z","home_page":"GitHub","home_page_link":"https://github.com/fzliu","self_intro":"Frank Liu is the Director of Operations \u0026 ML Architect at Zilliz, where he serves as a maintainer for the Towhee open-source project. Prior to Zilliz, Frank co-founded Orion Innovations, an ML-powered indoor positioning startup based in Shanghai and worked as an ML engineer at Yahoo in San Francisco. In his free time, Frank enjoys playing chess, swimming, and powerlifting. Frank holds MS and BS degrees in Electrical Engineering from Stanford University. ","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":6,"localizations":[{"id":427,"locale":"ja-JP","published_at":"2024-01-09T09:10:02.218Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Dec_6_Sentence_Transformer_A_Comprehensive_Guide_cd27b87a82.png","belong":"learn","authorNames":["Frank Liu"]},{"id":"blog-298","title":"Dissecting OpenAI's Built-in Retrieval: Unveiling Storage Constraints, Performance Gaps, and Cost Concerns","image":{"id":2517,"url":"https://assets.zilliz.com/Nov_15_Reverse_engineering_Open_AI_s_Built_in_Retrieval8_index_types_2b50e825b0.png"},"display_time":"Jan 09, 2024","deploy_time":"2023-12-31T16:00:00.000Z","url":"dissecting-openai-built-in-retrieval-storage-constraints-performance-gaps-cost-concerns","abstract":"Delve into the intricacies of OpenAI Assistants, exploring its pricing, architecture, and potential optimizations for cost-efficiency and enhanced storage capabilities.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":68,"name":"Robert Guo","author_tags":"Director of Product Management","published_at":"2023-06-13T18:34:37.794Z","created_by":18,"updated_by":18,"created_at":"2023-06-08T17:01:36.444Z","updated_at":"2024-04-16T02:44:46.685Z","home_page":"GitHub","home_page_link":"https://github.com/GuoRentong","self_intro":"Robert Guo is a Partner and Director of Product Management at Zilliz and one of the architects behind Milvus, an open-source vector database revolutionizing AI data analysis. With a Ph.D. in Computer Software and Theory from Huazhong University of Science and Technology, he has presented influential work at prestigious conferences and journals, including SIGMOD, VLDB, USENIX ATC, ICS, DATE, and IEEE TPDS. Previously a key developer for Huawei's ModelArts platform, Robert is skilled at crafting efficient and scalable AI data solutions.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":10,"localizations":[{"id":1369,"locale":"ja-JP","published_at":"2024-01-09T07:17:39.414Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Nov_15_Reverse_engineering_Open_AI_s_Built_in_Retrieval8_index_types_2b50e825b0.png","belong":"blog","authorNames":["Robert Guo"]},{"id":"learn-117","title":"Building Scalable AI with Vector Databases: A 2024 Strategy","image":{"id":2988,"url":"https://assets.zilliz.com/Building_Scalable_AI_with_Vector_Databases_A_2024_Strategy_b10c3d8de1.png"},"display_time":"Jan 09, 2024","url":"Building-Scalable-AI-with-Vector-Databases-A-2024-Strategy","abstract":"Vector databases are pivotal for scalable AI applications in today's digital landscape. ","tags":[{"id":1,"name":"Case Study","published_at":"2021-01-15T10:34:37.316Z","created_by":18,"updated_by":18,"created_at":"2021-01-15T10:34:34.857Z","updated_at":"2021-01-25T10:31:22.499Z","locale":"en"}],"authors":[{"id":124,"name":"Shivek Santosh Maharaj","author_tags":"Freelance Technical Writer","published_at":"2024-03-23T06:02:23.829Z","created_by":18,"updated_by":18,"created_at":"2024-03-23T06:02:21.922Z","updated_at":"2024-07-03T07:56:37.593Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Shivek Santosh Maharaj, Freelance Technical Writer","locale":"en"}],"read_time":10,"localizations":[{"id":309,"locale":"ja-JP","published_at":"2024-03-31T22:18:18.115Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Building_Scalable_AI_with_Vector_Databases_A_2024_Strategy_b10c3d8de1.png","belong":"learn","authorNames":["Shivek Santosh Maharaj"]},{"id":"learn-75","title":"Build AI Apps with Retrieval Augmented Generation (RAG)","image":{"id":2508,"url":"https://assets.zilliz.com/Dec_08_Learn_RAG_20231208_095526_2e187faa3b.png"},"display_time":"Jan 08, 2024","url":"Retrieval-Augmented-Generation","abstract":"A comprehensive guide to Retrieval Augmented Generation (RAG), including its definition, workflow, benefits, use cases, and challenges. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":36,"name":"Chris Churilo","author_tags":"VP of Marketing","published_at":"2023-04-11T16:51:05.002Z","created_by":18,"updated_by":53,"created_at":"2023-04-11T16:42:46.067Z","updated_at":"2025-01-16T22:35:53.011Z","home_page":"GitHub","home_page_link":"https://github.com/ChrisChurilo","self_intro":"Chris Churilo is the VP of Marketing \u0026 Community at Zilliz where she leads all community, developer relations, and marketing efforts. Prior to Zilliz, Chris was a founding member of the InfluxData’s go to market efforts and helped propel the time series database platform to dominance in the market. In earlier roles she defined and designed a SaaS monitoring solution at Centroid, and prior to that she was the VP of product management at iPass and was the LOB for several cloud services that required her to track the business and operational metrics and analytics to help identify and resolve issues.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":13,"localizations":[{"id":437,"locale":"ja-JP","published_at":"2024-01-08T03:09:33.960Z"},{"id":521,"locale":"ko","published_at":"2024-01-08T03:09:33.960Z"},{"id":512,"locale":"es","published_at":"2024-01-08T03:09:33.960Z"},{"id":518,"locale":"ru","published_at":"2024-01-08T03:09:33.960Z"},{"id":527,"locale":"fr","published_at":"2024-01-08T03:09:33.960Z"},{"id":509,"locale":"de","published_at":"2024-01-08T03:09:33.960Z"},{"id":515,"locale":"pt","published_at":"2024-01-08T03:09:33.960Z"},{"id":524,"locale":"it","published_at":"2024-01-08T03:09:33.960Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Dec_08_Learn_RAG_20231208_095526_2e187faa3b.png","belong":"learn","authorNames":["Chris Churilo"]},{"id":"blog-324","title":"OpenAI RAG vs. Your Customized RAG: Which One Is Better? ","image":{"id":2495,"url":"https://assets.zilliz.com/Dec_13_Open_AI_s_Chat_GPT_and_the_new_AI_Stack_Chat_GPT_your_Vector_Database_and_Prompt_as_code_c650c551fd.png"},"display_time":"Jan 05, 2024","deploy_time":null,"url":"openai-rag-vs-customized-rag-which-one-is-better","abstract":"Comparing the performance of the OpenAI Assistants-enabled RAG system and the Milvus-powered customized RAG system.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":107,"name":"Cheney Zhang","author_tags":"Algorithm Engineer","published_at":"2023-11-08T07:21:13.405Z","created_by":18,"updated_by":18,"created_at":"2023-11-08T07:21:10.513Z","updated_at":"2024-07-18T15:56:58.028Z","home_page":"GitHub","home_page_link":"https://github.com/zc277584121","self_intro":"Cheney Zhang is an accomplished Algorithm Engineer at Zilliz. With a profound passion for and expertise in cutting-edge AI technologies such as LLMs and Retrieval Augmented Generation (RAG), Cheney has actively contributed to many innovative AI projects, including Towhee, Akcio, and OSSChat. Before joining Zilliz, he worked for CMB Network Technology as an Algorithm Engineer. Cheney holds a master's degree from Nanjing University of Aeronautics and Astronautics.","repost_to_medium":null,"repost_state":null,"meta_description":"Cheney Zhang is an accomplished Algorithm Engineer at Zilliz. ","locale":"en"}],"read_time":10,"localizations":[{"id":1080,"locale":"ja-JP","published_at":"2024-01-05T03:20:41.243Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Dec_13_Open_AI_s_Chat_GPT_and_the_new_AI_Stack_Chat_GPT_your_Vector_Database_and_Prompt_as_code_c650c551fd.png","belong":"blog","authorNames":["Cheney Zhang"]},{"id":"blog-325","title":"Demystify Benchmark Result Divergence: Milvus vs. Qdrant","image":{"id":2516,"url":"https://assets.zilliz.com/Jan_8_Milvus_vs_Qdrant_e35ff7a5ba.png"},"display_time":"Jan 04, 2024","deploy_time":null,"url":"demystify-benchmark-result-divergence-milvus-vs-qdrant","abstract":"In-depth technical analysis of the benchmark differences between Qdrant and Milvus vector databases. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":76,"name":"Steffi Li","author_tags":"Director of Product Marketing","published_at":"2023-07-13T17:18:42.023Z","created_by":18,"updated_by":18,"created_at":"2023-07-13T17:16:54.449Z","updated_at":"2023-07-13T17:18:42.070Z","home_page":null,"home_page_link":null,"self_intro":"Steffi is the Director of Product Marketing at Zilliz, with prior experience leading the GTM strategies for open-source data technologies such as Apache Kafka and Apache Airflow. Passionate about travel, yoga, and non-fiction reading, she brings a balanced and enriched worldview to her professional pursuits.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":4,"localizations":[{"id":1044,"locale":"ja-JP","published_at":"2024-01-05T16:03:28.551Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Jan_8_Milvus_vs_Qdrant_e35ff7a5ba.png","belong":"blog","authorNames":["Steffi Li"]},{"id":"blog-323","title":"RAG Evaluation Tools: How to Evaluate Retrieval Augmented Generation Applications","image":{"id":2484,"url":"https://assets.zilliz.com/Dec_27_How_to_Evaluate_An_RAG_System_1_c62bfb2f56.png"},"display_time":"Dec 29, 2023","deploy_time":null,"url":"how-to-evaluate-retrieval-augmented-generation-rag-applications","abstract":"Methodologies, metrics, and tools used to evaluate RAG applications. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":107,"name":"Cheney Zhang","author_tags":"Algorithm Engineer","published_at":"2023-11-08T07:21:13.405Z","created_by":18,"updated_by":18,"created_at":"2023-11-08T07:21:10.513Z","updated_at":"2024-07-18T15:56:58.028Z","home_page":"GitHub","home_page_link":"https://github.com/zc277584121","self_intro":"Cheney Zhang is an accomplished Algorithm Engineer at Zilliz. With a profound passion for and expertise in cutting-edge AI technologies such as LLMs and Retrieval Augmented Generation (RAG), Cheney has actively contributed to many innovative AI projects, including Towhee, Akcio, and OSSChat. Before joining Zilliz, he worked for CMB Network Technology as an Algorithm Engineer. Cheney holds a master's degree from Nanjing University of Aeronautics and Astronautics.","repost_to_medium":null,"repost_state":null,"meta_description":"Cheney Zhang is an accomplished Algorithm Engineer at Zilliz. ","locale":"en"}],"read_time":10,"localizations":[{"id":850,"locale":"ja-JP","published_at":"2023-12-31T13:52:21.916Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Dec_27_How_to_Evaluate_An_RAG_System_1_c62bfb2f56.png","belong":"blog","authorNames":["Cheney Zhang"]},{"id":"blog-322","title":"Harmony in Pixels: Picdmo's Leap into Seamless Photo Management with Zilliz Cloud","image":{"id":2487,"url":"https://assets.zilliz.com/JAN_02_Picdmo_s_Leap_into_Seamless_Photo_Management_with_Zilliz_Cloud_1_c41b4e7d33.png"},"display_time":"Dec 27, 2023","deploy_time":null,"url":"picdmo-achieved-seamless-photo-management-with-zilliz-cloud","abstract":"Zilliz Cloud vector database helps Picdmo improve its photo search performance, reduce development time and costs, and achieve a better user experience. ","tags":[{"id":1,"name":"Case Study","published_at":"2021-01-15T10:34:37.316Z","created_by":18,"updated_by":18,"created_at":"2021-01-15T10:34:34.857Z","updated_at":"2021-01-25T10:31:22.499Z","locale":"en"}],"authors":[{"id":45,"name":"Fendy Feng","author_tags":"Technical Marketing Writer","published_at":"2023-05-16T01:36:15.102Z","created_by":18,"updated_by":18,"created_at":"2023-05-16T00:04:12.065Z","updated_at":"2024-04-25T08:37:19.712Z","home_page":"GitHub","home_page_link":"https://www.linkedin.com/in/fendy311/","self_intro":"Fendy Feng is the Technical Marketing Writer at Zilliz. She has extensive experience developing and enhancing the impact of open-source projects in various global markets by producing high-quality, tailored content. Before joining Zilliz, Fendy worked as a Content Strategist at PingCAP, a fast-growing E-Series startup renowned for its open-source distributed SQL database.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":3,"localizations":[{"id":1231,"locale":"ja-JP","published_at":"2023-12-28T08:27:26.322Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/JAN_02_Picdmo_s_Leap_into_Seamless_Photo_Management_with_Zilliz_Cloud_1_c41b4e7d33.png","belong":"blog","authorNames":["Fendy Feng"]},{"id":"blog-319","title":"How To Evaluate a Vector Database?","image":{"id":2464,"url":"https://assets.zilliz.com/How_to_Evaluate_a_Vector_Database_0dd412724c.png"},"display_time":"Dec 26, 2023","deploy_time":"2023-12-26T14:00:00.000Z","url":"how-to-evaluate-a-vector-database","abstract":"There is no universal ‘best’ vector database—the choice depends on your needs. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":70,"name":"Li Liu","author_tags":"Principal Engineer","published_at":"2023-06-15T05:16:42.032Z","created_by":18,"updated_by":18,"created_at":"2023-06-15T05:15:15.087Z","updated_at":"2024-07-18T15:59:40.729Z","home_page":"GitHub","home_page_link":"https://github.com/liliu-z","self_intro":"Li Liu is the Principal Engineer at Zilliz, leading the vector searching research and development. Before joining Zilliz, he was a Senior Engineer at Meta, designing and shaping numerous advertising stream data frameworks. With a Master's degree from Carnegie Mellon University, he boasts extensive experience in databases and big data. Li Liu's expertise in technology and innovation continues to drive advancements in vector searching, leaving a lasting impact on the field.\n","repost_to_medium":null,"repost_state":null,"meta_description":"Li Liu is the Principal Engineer at Zilliz, leading the vector searching research and development.","locale":"en"}],"read_time":6,"localizations":[{"id":1115,"locale":"ja-JP","published_at":"2023-12-26T07:00:11.517Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/How_to_Evaluate_a_Vector_Database_0dd412724c.png","belong":"blog","authorNames":["Li Liu"]},{"id":"blog-314","title":"What Is A Dynamic Schema?","image":{"id":2460,"url":"https://assets.zilliz.com/dynamic_schema_d5a4535c29.png"},"display_time":"Dec 25, 2023","deploy_time":null,"url":"what-is-dynamic-schema","abstract":"An introduction to dynamic schemas, their usage, and pros and cons. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":41,"name":"Yujian Tang","author_tags":"Developer Advocate at Zilliz","published_at":"2023-04-20T21:52:47.479Z","created_by":18,"updated_by":18,"created_at":"2023-04-20T21:52:45.859Z","updated_at":"2024-07-18T16:02:07.497Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/yujiantang/","self_intro":"Yujian Tang is a Developer Advocate at Zilliz. He has a background as a software engineer working on AutoML at Amazon. Yujian studied Computer Science, Statistics, and Neuroscience with research papers published to conferences including IEEE Big Data. He enjoys drinking bubble tea, spending time with family, and being near water.","repost_to_medium":null,"repost_state":null,"meta_description":"Yujian Tang, Developer Advocate at Zilliz. ","locale":"en"}],"read_time":7,"localizations":[{"id":1021,"locale":"ja-JP","published_at":"2023-12-25T08:33:27.346Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/dynamic_schema_d5a4535c29.png","belong":"blog","authorNames":["Yujian Tang"]},{"id":"blog-312","title":"Unlocking Next-Level APK Security: Trend Micro's Journey with Milvus","image":{"id":2480,"url":"https://assets.zilliz.com/Dec_22_Unlocking_Next_Level_APK_Security_Trend_Micro_s_Journey_with_Milvus_3185393339.png"},"display_time":"Dec 21, 2023","deploy_time":null,"url":"unlocking-next-level-apk-security-trend-micro-journey-with-milvus","abstract":"This blog uncovers the challenges Trend Micro faced and how Milvus came to the rescue. ","tags":[{"id":1,"name":"Case Study","published_at":"2021-01-15T10:34:37.316Z","created_by":18,"updated_by":18,"created_at":"2021-01-15T10:34:34.857Z","updated_at":"2021-01-25T10:31:22.499Z","locale":"en"}],"authors":[{"id":45,"name":"Fendy Feng","author_tags":"Technical Marketing Writer","published_at":"2023-05-16T01:36:15.102Z","created_by":18,"updated_by":18,"created_at":"2023-05-16T00:04:12.065Z","updated_at":"2024-04-25T08:37:19.712Z","home_page":"GitHub","home_page_link":"https://www.linkedin.com/in/fendy311/","self_intro":"Fendy Feng is the Technical Marketing Writer at Zilliz. She has extensive experience developing and enhancing the impact of open-source projects in various global markets by producing high-quality, tailored content. Before joining Zilliz, Fendy worked as a Content Strategist at PingCAP, a fast-growing E-Series startup renowned for its open-source distributed SQL database.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":4,"localizations":[{"id":1124,"locale":"ja-JP","published_at":"2023-12-21T19:12:17.852Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Dec_22_Unlocking_Next_Level_APK_Security_Trend_Micro_s_Journey_with_Milvus_3185393339.png","belong":"blog","authorNames":["Fendy Feng"]},{"id":"blog-310","title":"Metadata Filtering with Zilliz Cloud Pipelines","image":{"id":2479,"url":"https://assets.zilliz.com/Dec_18_Metadata_Filtering_with_Zilliz_Cloud_Pipelines_20231218_083502_b135c27c23.png"},"display_time":"Dec 17, 2023","deploy_time":null,"url":"metadata-filtering-with-zilliz-cloud-pipelines","abstract":"A step-by-step guide on how to perform metadata filtering in fully managed Milvus using Zilliz Cloud Pipeline","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":94,"name":"Christy Bergman","author_tags":"Developer Advocate","published_at":"2023-10-06T00:29:45.486Z","created_by":18,"updated_by":18,"created_at":"2023-10-06T00:29:30.751Z","updated_at":"2024-07-18T16:01:45.942Z","home_page":null,"home_page_link":null,"self_intro":"Christy Bergman is a passionate Developer Advocate at Zilliz. She previously worked in distributed computing at Anyscale and as a Specialist AI/ML Solutions Architect at AWS. Christy studied applied math, is a self-taught coder, and has published papers, including one with ACM Recsys. She enjoys hiking and bird watching.","repost_to_medium":null,"repost_state":null,"meta_description":"Christy Bergman is a passionate Developer Advocate at Zilliz. ","locale":"en"}],"read_time":5,"localizations":[{"id":1363,"locale":"ja-JP","published_at":"2023-12-21T15:45:54.004Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Dec_18_Metadata_Filtering_with_Zilliz_Cloud_Pipelines_20231218_083502_b135c27c23.png","belong":"blog","authorNames":["Christy Bergman"]},{"id":"blog-311","title":"Optimizing User Experience: BIGO Leverages Milvus for Duplicate Video Removal ","image":{"id":2433,"url":"https://assets.zilliz.com/How_Milvus_Transformed_BIGO_s_Video_Deduplication_System_2f5cea177a.png"},"display_time":"Dec 14, 2023","deploy_time":null,"url":"bigo-leverages-milvus-for-duplicate-video-removal","abstract":"Exploring challenges BIGO faced, why it chose the Milvus vector database to power its video deduplication system, and how Milvus came to the rescue.","tags":[{"id":1,"name":"Case Study","published_at":"2021-01-15T10:34:37.316Z","created_by":18,"updated_by":18,"created_at":"2021-01-15T10:34:34.857Z","updated_at":"2021-01-25T10:31:22.499Z","locale":"en"}],"authors":[{"id":45,"name":"Fendy Feng","author_tags":"Technical Marketing Writer","published_at":"2023-05-16T01:36:15.102Z","created_by":18,"updated_by":18,"created_at":"2023-05-16T00:04:12.065Z","updated_at":"2024-04-25T08:37:19.712Z","home_page":"GitHub","home_page_link":"https://www.linkedin.com/in/fendy311/","self_intro":"Fendy Feng is the Technical Marketing Writer at Zilliz. She has extensive experience developing and enhancing the impact of open-source projects in various global markets by producing high-quality, tailored content. Before joining Zilliz, Fendy worked as a Content Strategist at PingCAP, a fast-growing E-Series startup renowned for its open-source distributed SQL database.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":3,"localizations":[{"id":1377,"locale":"ja-JP","published_at":"2023-12-19T13:52:15.003Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/How_Milvus_Transformed_BIGO_s_Video_Deduplication_System_2f5cea177a.png","belong":"blog","authorNames":["Fendy Feng"]},{"id":"learn-74","title":"Sparse and Dense Embeddings","image":{"id":2318,"url":"https://assets.zilliz.com/Sparse_and_Dense_Embeddings_70bcfea8d0.png"},"display_time":"Dec 13, 2023","url":"sparse-and-dense-embeddings","abstract":"Learn about sparse and dense embeddings, their use cases, and a text classification example using these embeddings. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":3,"name":"Frank Liu","author_tags":"Director of Operations \u0026 ML Architect at Zilliz","published_at":"2021-12-23T11:08:08.015Z","created_by":18,"updated_by":18,"created_at":"2021-12-23T10:40:59.821Z","updated_at":"2023-04-21T22:30:10.416Z","home_page":"GitHub","home_page_link":"https://github.com/fzliu","self_intro":"Frank Liu is the Director of Operations \u0026 ML Architect at Zilliz, where he serves as a maintainer for the Towhee open-source project. Prior to Zilliz, Frank co-founded Orion Innovations, an ML-powered indoor positioning startup based in Shanghai and worked as an ML engineer at Yahoo in San Francisco. In his free time, Frank enjoys playing chess, swimming, and powerlifting. Frank holds MS and BS degrees in Electrical Engineering from Stanford University. ","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":14,"localizations":[{"id":436,"locale":"ja-JP","published_at":"2023-12-13T04:21:50.224Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Sparse_and_Dense_Embeddings_70bcfea8d0.png","belong":"learn","authorNames":["Frank Liu"]},{"id":"blog-306","title":"Improving ChatGPT’s Ability to Understand Ambiguous Prompts","image":{"id":2307,"url":"https://assets.zilliz.com/Do_You_Really_Know_How_to_Write_Prompts_20231031_083836_821b2e5ac6.png"},"display_time":"Dec 12, 2023","deploy_time":"2023-12-12T14:00:00.000Z","url":"improving-chatgpts-ability-to-understand-ambiguous-prompts","abstract":"Prompt engineering technique helps large language models (LLMs) handle pronouns and other complex coreferences in retrieval augmented generation (RAG) systems.\n","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":107,"name":"Cheney Zhang","author_tags":"Algorithm Engineer","published_at":"2023-11-08T07:21:13.405Z","created_by":18,"updated_by":18,"created_at":"2023-11-08T07:21:10.513Z","updated_at":"2024-07-18T15:56:58.028Z","home_page":"GitHub","home_page_link":"https://github.com/zc277584121","self_intro":"Cheney Zhang is an accomplished Algorithm Engineer at Zilliz. With a profound passion for and expertise in cutting-edge AI technologies such as LLMs and Retrieval Augmented Generation (RAG), Cheney has actively contributed to many innovative AI projects, including Towhee, Akcio, and OSSChat. Before joining Zilliz, he worked for CMB Network Technology as an Algorithm Engineer. Cheney holds a master's degree from Nanjing University of Aeronautics and Astronautics.","repost_to_medium":null,"repost_state":null,"meta_description":"Cheney Zhang is an accomplished Algorithm Engineer at Zilliz. ","locale":"en"}],"read_time":7,"localizations":[{"id":1286,"locale":"ja-JP","published_at":"2023-12-12T00:42:55.626Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Do_You_Really_Know_How_to_Write_Prompts_20231031_083836_821b2e5ac6.png","belong":"blog","authorNames":["Cheney Zhang"]},{"id":"blog-307","title":"Shaping Tomorrow: How Milvus Powers Shopee's Multimedia Ambition","image":{"id":2309,"url":"https://assets.zilliz.com/Shopee_Revolutionizes_Its_Multimedia_Business_with_Milvus_9a503f269c.png"},"display_time":"Dec 07, 2023","deploy_time":null,"url":"how-milvus-empowers-shopee-multimedia-ambition","abstract":"Exploring how Milvus helps Shopee revolutionize its multimedia business with enhanced user experience and streamlined operation. ","tags":[{"id":1,"name":"Case Study","published_at":"2021-01-15T10:34:37.316Z","created_by":18,"updated_by":18,"created_at":"2021-01-15T10:34:34.857Z","updated_at":"2021-01-25T10:31:22.499Z","locale":"en"}],"authors":[{"id":45,"name":"Fendy Feng","author_tags":"Technical Marketing Writer","published_at":"2023-05-16T01:36:15.102Z","created_by":18,"updated_by":18,"created_at":"2023-05-16T00:04:12.065Z","updated_at":"2024-04-25T08:37:19.712Z","home_page":"GitHub","home_page_link":"https://www.linkedin.com/in/fendy311/","self_intro":"Fendy Feng is the Technical Marketing Writer at Zilliz. She has extensive experience developing and enhancing the impact of open-source projects in various global markets by producing high-quality, tailored content. Before joining Zilliz, Fendy worked as a Content Strategist at PingCAP, a fast-growing E-Series startup renowned for its open-source distributed SQL database.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":2,"localizations":[{"id":1062,"locale":"ja-JP","published_at":"2023-12-11T02:33:50.113Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Shopee_Revolutionizes_Its_Multimedia_Business_with_Milvus_9a503f269c.png","belong":"blog","authorNames":["Fendy Feng"]},{"id":"learn-13","title":"Unveiling the Power of Natural Language Processing: Top 10 Real-World Applications","image":{"id":2305,"url":"https://assets.zilliz.com/Nov_16_Top_10_Real_World_NLP_Applications_5fc7a892d4.png"},"display_time":"Dec 05, 2023","url":"top-5-nlp-applications","abstract":"NLP makes our lives much easier. Learn about the top 10 most popular NLP applications and how they have an impact on our lives. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":12,"name":"Alex Gao","author_tags":"Principle Engineer","published_at":"2022-03-01T06:07:44.591Z","created_by":18,"updated_by":18,"created_at":"2022-03-01T06:07:43.391Z","updated_at":"2022-03-01T06:07:44.604Z","home_page":"GitHub","home_page_link":"https://github.com/soothing-rain/","self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":6,"localizations":[{"id":338,"locale":"ja-JP","published_at":"2022-03-24T06:21:28.357Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Nov_16_Top_10_Real_World_NLP_Applications_5fc7a892d4.png","belong":"learn","authorNames":["Alex Gao"]},{"id":"blog-303","title":"Create a Movie Recommendation Engine with Milvus and Python","image":{"id":2286,"url":"https://assets.zilliz.com/Create_a_Movie_Recommender_with_Milvus_20231018_110612_2c2ffb6475.png"},"display_time":"Dec 04, 2023","deploy_time":null,"url":"create-a-movie-recommendation-engine-with-milvus-and-python","abstract":"This article explains how to build a movie recommender with Milvus and Python.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":110,"name":"Gourav Bais","author_tags":"Applied Machine Learning Engineer","published_at":"2023-12-05T03:15:41.359Z","created_by":18,"updated_by":18,"created_at":"2023-12-05T03:15:39.434Z","updated_at":"2023-12-05T04:22:08.377Z","home_page":"Analytics Vidhya","home_page_link":"https://www.analyticsvidhya.com/blog/author/gourav29","self_intro":" Gourav is an applied machine learning engineer skilled in computer vision/deep learning pipeline development, creating machine learning models, retraining systems, and transforming data science prototypes into production-grade solutions.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":7,"localizations":[{"id":1341,"locale":"ja-JP","published_at":"2023-12-05T04:23:11.753Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Create_a_Movie_Recommender_with_Milvus_20231018_110612_2c2ffb6475.png","belong":"blog","authorNames":["Gourav Bais"]},{"id":"blog-302","title":"Building an Open Source Chatbot Using LangChain and Milvus in Under 5 Minutes","image":{"id":2276,"url":"https://assets.zilliz.com/Nov_28_Building_an_Open_Source_Chatbot_Using_Lang_Chain_and_Milvus_in_Under_5_Minutes_f023330a04.png"},"display_time":"Nov 29, 2023","deploy_time":"2023-11-30T04:00:00.000Z","url":"building-open-source-chatbot-using-milvus-and-langchain-in-5-minutes","abstract":"A start-to-finish tutorial for RAG retrieval and question-answering chatbot on custom documents using Milvus, LangChain, and an open-source LLM. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":94,"name":"Christy Bergman","author_tags":"Developer Advocate","published_at":"2023-10-06T00:29:45.486Z","created_by":18,"updated_by":18,"created_at":"2023-10-06T00:29:30.751Z","updated_at":"2024-07-18T16:01:45.942Z","home_page":null,"home_page_link":null,"self_intro":"Christy Bergman is a passionate Developer Advocate at Zilliz. She previously worked in distributed computing at Anyscale and as a Specialist AI/ML Solutions Architect at AWS. Christy studied applied math, is a self-taught coder, and has published papers, including one with ACM Recsys. She enjoys hiking and bird watching.","repost_to_medium":null,"repost_state":null,"meta_description":"Christy Bergman is a passionate Developer Advocate at Zilliz. ","locale":"en"}],"read_time":9,"localizations":[{"id":899,"locale":"ja-JP","published_at":"2023-11-30T09:53:32.822Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Nov_28_Building_an_Open_Source_Chatbot_Using_Lang_Chain_and_Milvus_in_Under_5_Minutes_f023330a04.png","belong":"blog","authorNames":["Christy Bergman"]},{"id":"blog-301","title":"Transforming Ad Recommendations: SmartNews's Journey with Milvus","image":{"id":2218,"url":"https://assets.zilliz.com/How_Smart_News_Transforms_Real_Time_Ad_Recommendations_with_Milvus_4c7aa08232.png"},"display_time":"Nov 29, 2023","deploy_time":null,"url":"transforming-ad-recommendations-smartnews-journey-with-milvus","abstract":"Exploring how Milvus makes SmartNews’s ad recommender more scalable, reliable, and up-to-date.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":45,"name":"Fendy Feng","author_tags":"Technical Marketing Writer","published_at":"2023-05-16T01:36:15.102Z","created_by":18,"updated_by":18,"created_at":"2023-05-16T00:04:12.065Z","updated_at":"2024-04-25T08:37:19.712Z","home_page":"GitHub","home_page_link":"https://www.linkedin.com/in/fendy311/","self_intro":"Fendy Feng is the Technical Marketing Writer at Zilliz. She has extensive experience developing and enhancing the impact of open-source projects in various global markets by producing high-quality, tailored content. Before joining Zilliz, Fendy worked as a Content Strategist at PingCAP, a fast-growing E-Series startup renowned for its open-source distributed SQL database.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":2,"localizations":[{"id":1327,"locale":"ja-JP","published_at":"2023-11-29T02:46:46.439Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/How_Smart_News_Transforms_Real_Time_Ad_Recommendations_with_Milvus_4c7aa08232.png","belong":"blog","authorNames":["Fendy Feng"]},{"id":"blog-300","title":"Kicking Off the Open Source Advent","image":{"id":2310,"url":"https://assets.zilliz.com/Open_source_advent_cab220c3f2.jpeg"},"display_time":"Nov 27, 2023","deploy_time":null,"url":"advent-of-code-for-open-source","abstract":"Open Source Advent is a fun and festive way to learn new open-source skills and win swag this December. Learn how to participate by reading this blog. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":41,"name":"Yujian Tang","author_tags":"Developer Advocate at Zilliz","published_at":"2023-04-20T21:52:47.479Z","created_by":18,"updated_by":18,"created_at":"2023-04-20T21:52:45.859Z","updated_at":"2024-07-18T16:02:07.497Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/yujiantang/","self_intro":"Yujian Tang is a Developer Advocate at Zilliz. He has a background as a software engineer working on AutoML at Amazon. Yujian studied Computer Science, Statistics, and Neuroscience with research papers published to conferences including IEEE Big Data. He enjoys drinking bubble tea, spending time with family, and being near water.","repost_to_medium":null,"repost_state":null,"meta_description":"Yujian Tang, Developer Advocate at Zilliz. ","locale":"en"}],"read_time":3,"localizations":[{"id":862,"locale":"ja-JP","published_at":"2023-11-28T15:40:19.339Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Open_source_advent_cab220c3f2.jpeg","belong":"blog","authorNames":["Yujian Tang"]},{"id":"blog-299","title":"Getting Started with a Milvus Connection","image":{"id":2202,"url":"https://assets.zilliz.com/Getting_Started_with_a_Milvus_Connection_362b54b690.png"},"display_time":"Nov 24, 2023","deploy_time":null,"url":"getting-started-with-a-milvus-connection","abstract":"A tutorial that guides you through connecting with Milvus in minutes. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":94,"name":"Christy Bergman","author_tags":"Developer Advocate","published_at":"2023-10-06T00:29:45.486Z","created_by":18,"updated_by":18,"created_at":"2023-10-06T00:29:30.751Z","updated_at":"2024-07-18T16:01:45.942Z","home_page":null,"home_page_link":null,"self_intro":"Christy Bergman is a passionate Developer Advocate at Zilliz. She previously worked in distributed computing at Anyscale and as a Specialist AI/ML Solutions Architect at AWS. Christy studied applied math, is a self-taught coder, and has published papers, including one with ACM Recsys. She enjoys hiking and bird watching.","repost_to_medium":null,"repost_state":null,"meta_description":"Christy Bergman is a passionate Developer Advocate at Zilliz. ","locale":"en"}],"read_time":3,"localizations":[{"id":1217,"locale":"ja-JP","published_at":"2023-11-24T17:14:49.854Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Getting_Started_with_a_Milvus_Connection_362b54b690.png","belong":"blog","authorNames":["Christy Bergman"]},{"id":"blog-297","title":"How Milvus Powers Credal’s Mission for “Useful AI, Made Safe”","image":{"id":2195,"url":"https://assets.zilliz.com/How_Credal_AI_Unlocks_Secure_Governable_Gen_AI_with_Milvus_20231103_030950_904a1d61ad.png"},"display_time":"Nov 22, 2023","deploy_time":null,"url":"how-milvus-powers-credal-mission-for-useful-ai-made-safe","abstract":"Learn why Milvus, an open-source vector database, is pivotal in enabling Credal's vision for \"Useful AI, made safe.\"","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":106,"name":"Anya Sage","author_tags":"Tech Content Copyeditor and Copywriter, The Write Cure","published_at":"2023-11-01T00:33:36.126Z","created_by":18,"updated_by":18,"created_at":"2023-11-01T00:17:51.188Z","updated_at":"2023-11-01T14:33:57.889Z","home_page":null,"home_page_link":"","self_intro":"Anya Sage is a freelance tech marketing copywriter/copyeditor. She has extensive experience writing and editing for the tech industry. Through her company The Write Cure, she helps tech companies build and shape their marketing content for clarity and impact.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":4,"localizations":[{"id":1290,"locale":"ja-JP","published_at":"2023-11-22T15:59:44.149Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/How_Credal_AI_Unlocks_Secure_Governable_Gen_AI_with_Milvus_20231103_030950_904a1d61ad.png","belong":"blog","authorNames":["Anya Sage"]},{"id":"blog-295","title":"Zilliz Cloud Now Available on Microsoft Azure","image":{"id":2193,"url":"https://assets.zilliz.com/Nov_08_Zilliz_Cloud_Is_Now_Available_on_Azure_1_d0e80e0388.png"},"display_time":"Nov 21, 2023","deploy_time":"2023-11-21T13:50:00.814Z","url":"zilliz-cloud-now-available-on-microsoft-azure","abstract":"Zilliz Cloud is now available on Microsoft Azure, making its debut in the azure-east-us region.","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":76,"name":"Steffi Li","author_tags":"Director of Product Marketing","published_at":"2023-07-13T17:18:42.023Z","created_by":18,"updated_by":18,"created_at":"2023-07-13T17:16:54.449Z","updated_at":"2023-07-13T17:18:42.070Z","home_page":null,"home_page_link":null,"self_intro":"Steffi is the Director of Product Marketing at Zilliz, with prior experience leading the GTM strategies for open-source data technologies such as Apache Kafka and Apache Airflow. Passionate about travel, yoga, and non-fiction reading, she brings a balanced and enriched worldview to her professional pursuits.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":1,"localizations":[{"id":1353,"locale":"ja-JP","published_at":"2023-11-21T06:27:37.827Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Nov_08_Zilliz_Cloud_Is_Now_Available_on_Azure_1_d0e80e0388.png","belong":"blog","authorNames":["Steffi Li"]},{"id":"blog-296","title":"Milvus 2.3 Beta and Enterprise Upgrades on Zilliz Cloud","image":{"id":2194,"url":"https://assets.zilliz.com/Milvus_2_3_Beta_and_Enterprise_Upgrades_on_Zilliz_Cloud_0b909c9931.png"},"display_time":"Nov 21, 2023","deploy_time":null,"url":"milvus-2-3-beta-and-enterprise-upgrades-on-zilliz-cloud","abstract":"Zilliz Cloud now offers the beta version of Milvus 2.3, marking a significant update in vector database technology. Learn more in this post. ","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":76,"name":"Steffi Li","author_tags":"Director of Product Marketing","published_at":"2023-07-13T17:18:42.023Z","created_by":18,"updated_by":18,"created_at":"2023-07-13T17:16:54.449Z","updated_at":"2023-07-13T17:18:42.070Z","home_page":null,"home_page_link":null,"self_intro":"Steffi is the Director of Product Marketing at Zilliz, with prior experience leading the GTM strategies for open-source data technologies such as Apache Kafka and Apache Airflow. Passionate about travel, yoga, and non-fiction reading, she brings a balanced and enriched worldview to her professional pursuits.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":2,"localizations":[{"id":934,"locale":"ja-JP","published_at":"2023-11-22T15:48:03.815Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Milvus_2_3_Beta_and_Enterprise_Upgrades_on_Zilliz_Cloud_0b909c9931.png","belong":"blog","authorNames":["Steffi Li"]},{"id":"blog-293","title":"Enhancing Data Flow Efficiency: Zilliz Introduces Upsert, Kafka Connector, and Airbyte Integration","image":{"id":2190,"url":"https://assets.zilliz.com/Data_Ingestion8_index_types_88b963db1a.png"},"display_time":"Nov 20, 2023","deploy_time":null,"url":"zilliz-introduces-upsert-kafka-connector-and-airbyte-integration","abstract":"Explore how our recent data ingestion features and integrations streamline data flows and provide developer-friendly experiences.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":76,"name":"Steffi Li","author_tags":"Director of Product Marketing","published_at":"2023-07-13T17:18:42.023Z","created_by":18,"updated_by":18,"created_at":"2023-07-13T17:16:54.449Z","updated_at":"2023-07-13T17:18:42.070Z","home_page":null,"home_page_link":null,"self_intro":"Steffi is the Director of Product Marketing at Zilliz, with prior experience leading the GTM strategies for open-source data technologies such as Apache Kafka and Apache Airflow. Passionate about travel, yoga, and non-fiction reading, she brings a balanced and enriched worldview to her professional pursuits.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":6,"localizations":[{"id":1387,"locale":"ja-JP","published_at":"2023-11-21T05:38:17.757Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Data_Ingestion8_index_types_88b963db1a.png","belong":"blog","authorNames":["Steffi Li"]},{"id":"blog-294","title":"What’s New in Milvus 2.3.2 \u0026 2.3.3","image":{"id":2189,"url":"https://assets.zilliz.com/Milvus_2_3_2_and_2_3_3_Zilliz_4f646a23d4.png"},"display_time":"Nov 20, 2023","deploy_time":null,"url":"whats-new-in-milvus-2-3-2-and-2-3-3","abstract":"Exploring new features and enhancements of Milvus, such as support for Array data types, complex delete expressions, TiKV integration, and more.","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":76,"name":"Steffi Li","author_tags":"Director of Product Marketing","published_at":"2023-07-13T17:18:42.023Z","created_by":18,"updated_by":18,"created_at":"2023-07-13T17:16:54.449Z","updated_at":"2023-07-13T17:18:42.070Z","home_page":null,"home_page_link":null,"self_intro":"Steffi is the Director of Product Marketing at Zilliz, with prior experience leading the GTM strategies for open-source data technologies such as Apache Kafka and Apache Airflow. Passionate about travel, yoga, and non-fiction reading, she brings a balanced and enriched worldview to her professional pursuits.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":2,"localizations":[{"id":1220,"locale":"ja-JP","published_at":"2023-11-21T05:55:09.545Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Milvus_2_3_2_and_2_3_3_Zilliz_4f646a23d4.png","belong":"blog","authorNames":["Steffi Li"]},{"id":"blog-292","title":"How LangChain Implements Self Querying","image":{"id":2184,"url":"https://assets.zilliz.com/Oct_26_How_Lang_Chain_Implements_Self_Querying_0f38182998.png"},"display_time":"Nov 16, 2023","deploy_time":"2023-11-17T04:00:00.000Z","url":"How-LangChain-Implements-Self-Querying","abstract":"Exploring how LangChain implements self querying, a way to build simple retrieval augmented generation (RAG) applications using an LLM, a vector database, and prompts. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":41,"name":"Yujian Tang","author_tags":"Developer Advocate at Zilliz","published_at":"2023-04-20T21:52:47.479Z","created_by":18,"updated_by":18,"created_at":"2023-04-20T21:52:45.859Z","updated_at":"2024-07-18T16:02:07.497Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/yujiantang/","self_intro":"Yujian Tang is a Developer Advocate at Zilliz. He has a background as a software engineer working on AutoML at Amazon. Yujian studied Computer Science, Statistics, and Neuroscience with research papers published to conferences including IEEE Big Data. He enjoys drinking bubble tea, spending time with family, and being near water.","repost_to_medium":null,"repost_state":null,"meta_description":"Yujian Tang, Developer Advocate at Zilliz. ","locale":"en"}],"read_time":4,"localizations":[{"id":1196,"locale":"ja-JP","published_at":"2023-11-17T03:47:51.793Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Oct_26_How_Lang_Chain_Implements_Self_Querying_0f38182998.png","belong":"blog","authorNames":["Yujian Tang"]},{"id":"blog-290","title":"Grounding Our Chat Towards Data Science Results","image":{"id":2181,"url":"https://assets.zilliz.com/Grounding_Our_Chat_Towards_Data_Science_Results_3b38edcf80.png"},"display_time":"Nov 15, 2023","deploy_time":null,"url":"grounding-our-chat-towards-data-science-results","abstract":"In this post, the third installment in our Chat Towards Data Science series, we’ll cover how to ground our RAG results for Towards Data Science via LlamaIndex.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":41,"name":"Yujian Tang","author_tags":"Developer Advocate at Zilliz","published_at":"2023-04-20T21:52:47.479Z","created_by":18,"updated_by":18,"created_at":"2023-04-20T21:52:45.859Z","updated_at":"2024-07-18T16:02:07.497Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/yujiantang/","self_intro":"Yujian Tang is a Developer Advocate at Zilliz. He has a background as a software engineer working on AutoML at Amazon. Yujian studied Computer Science, Statistics, and Neuroscience with research papers published to conferences including IEEE Big Data. He enjoys drinking bubble tea, spending time with family, and being near water.","repost_to_medium":null,"repost_state":null,"meta_description":"Yujian Tang, Developer Advocate at Zilliz. ","locale":"en"}],"read_time":4,"localizations":[{"id":1291,"locale":"ja-JP","published_at":"2023-11-15T17:43:59.585Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Grounding_Our_Chat_Towards_Data_Science_Results_3b38edcf80.png","belong":"blog","authorNames":["Yujian Tang"]},{"id":"blog-291","title":"Join us at AWS re:Invent 2023","image":{"id":2183,"url":"https://assets.zilliz.com/2023_re_Invent_Sponsor_Static_Social_Templates_1920x1080_002_8e79858bcc.png"},"display_time":"Nov 15, 2023","deploy_time":null,"url":"join-us-at-aws-reinvent-2023","abstract":"Planning to join the 50,000+ attendees at AWS re:Invent this year? Stop by the Milvus booth (#1339) and meet the team from Zilliz.","tags":[{"id":4,"name":"Company","published_at":"2021-01-21T02:28:23.551Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:20.676Z","updated_at":"2021-01-21T02:28:23.824Z","locale":"en"}],"authors":[{"id":37,"name":"Emily Kurze","author_tags":"Director of Marketing Operations","published_at":"2023-04-11T16:55:11.838Z","created_by":18,"updated_by":18,"created_at":"2023-04-11T16:55:07.625Z","updated_at":"2024-04-29T03:28:13.160Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/emilykurze/","self_intro":"Emily Kurze is the Director of Marketing at Zilliz. ","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":2,"localizations":[{"id":1355,"locale":"ja-JP","published_at":"2023-11-15T18:42:46.353Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/2023_re_Invent_Sponsor_Static_Social_Templates_1920x1080_002_8e79858bcc.png","belong":"blog","authorNames":["Emily Kurze"]},{"id":"learn-72","title":"Primer on Neural Networks and Embeddings for Language Models","image":{"id":2174,"url":"https://assets.zilliz.com/Nov_08_An_Introduction_to_Modern_NLP_66375866c7.png"},"display_time":"Nov 14, 2023","url":"Neural-Networks-and-Embeddings-for-Language-Models","abstract":"Exploring neural network language models, specifically recurrent neural networks, and taking a sneak peek at how embeddings are generated. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":3,"name":"Frank Liu","author_tags":"Director of Operations \u0026 ML Architect at Zilliz","published_at":"2021-12-23T11:08:08.015Z","created_by":18,"updated_by":18,"created_at":"2021-12-23T10:40:59.821Z","updated_at":"2023-04-21T22:30:10.416Z","home_page":"GitHub","home_page_link":"https://github.com/fzliu","self_intro":"Frank Liu is the Director of Operations \u0026 ML Architect at Zilliz, where he serves as a maintainer for the Towhee open-source project. Prior to Zilliz, Frank co-founded Orion Innovations, an ML-powered indoor positioning startup based in Shanghai and worked as an ML engineer at Yahoo in San Francisco. In his free time, Frank enjoys playing chess, swimming, and powerlifting. Frank holds MS and BS degrees in Electrical Engineering from Stanford University. ","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":8,"localizations":[{"id":324,"locale":"ja-JP","published_at":"2023-11-14T07:11:03.055Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Nov_08_An_Introduction_to_Modern_NLP_66375866c7.png","belong":"learn","authorNames":["Frank Liu"]},{"id":"blog-289","title":"Do We Still Need Vector Databases for RAG with OpenAI's Releasing of Its Built-In Retrieval?","image":{"id":2175,"url":"https://assets.zilliz.com/Nov_14_Customizing_Open_AI_Built_In_Retrieval_Using_Milvus_Vector_Database_5d7df0fd26.png"},"display_time":"Nov 13, 2023","deploy_time":null,"url":"customizing-openai-built-in-retrieval-using-milvus-vector-database","abstract":"OpenAI released its new retrieval feature, which is powerful in retrieving additional knowledge but has imitations like storage constraints and lack of customization. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":67,"name":"Jael Gu","author_tags":"Algorithm Engineer","published_at":"2023-05-31T02:50:25.394Z","created_by":18,"updated_by":18,"created_at":"2023-05-31T02:39:18.234Z","updated_at":"2024-07-18T15:56:18.435Z","home_page":"GitHub","home_page_link":"https://github.com/jaelgu","self_intro":"Algorithm Engineer at Zilliz ","repost_to_medium":null,"repost_state":null,"meta_description":"Jael Gu is an Algorithm Engineer at Zilliz.","locale":"en"}],"read_time":6,"localizations":[{"id":1378,"locale":"ja-JP","published_at":"2023-11-13T20:54:12.353Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Nov_14_Customizing_Open_AI_Built_In_Retrieval_Using_Milvus_Vector_Database_5d7df0fd26.png","belong":"blog","authorNames":["Jael Gu"]},{"id":"learn-15","title":"Top 20 NLP Models to Empower Your ML Application","image":{"id":2168,"url":"https://assets.zilliz.com/Popular_NLP_Models_to_Empower_Your_ML_Applications_cec2da0d0c.png"},"display_time":"Nov 13, 2023","url":"7-nlp-models","abstract":"Learn about the 10 most popular LLMs taking 2023 by storm and another 10 basic NLP models. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":13,"name":"Angela Ni","author_tags":"Technical Writer at Zilliz","published_at":"2022-03-17T08:59:36.247Z","created_by":18,"updated_by":18,"created_at":"2022-03-17T08:59:33.931Z","updated_at":"2024-07-03T07:58:47.615Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/yiyun-n-2aa713163/","self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Angela Ni, Technical Writer at Zilliz","locale":"en"}],"read_time":6,"localizations":[{"id":331,"locale":"ja-JP","published_at":"2022-03-24T07:12:33.592Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Popular_NLP_Models_to_Empower_Your_ML_Applications_cec2da0d0c.png","belong":"learn","authorNames":["Angela Ni"]},{"id":"blog-276","title":"Unlock Advanced Recommendation Engines with Milvus' New Range Search","image":{"id":2161,"url":"https://assets.zilliz.com/Unlock_Recommendation_Use_Cases_with_Milvus_New_Range_Search_0f8cdc3d3c.png"},"display_time":"Nov 09, 2023","deploy_time":null,"url":"unlock-advanced-recommendation-engines-with-milvus-new-range-search","abstract":"Exploring Milvus’s newly released range search feature, how it differs from the traditional KNN search, and when to use it.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":108,"name":"Leon Cai","author_tags":"Senior Software Engineer at Zilliz","published_at":"2023-11-08T08:22:48.776Z","created_by":18,"updated_by":18,"created_at":"2023-11-08T08:22:46.977Z","updated_at":"2024-07-18T15:57:53.956Z","home_page":"GitHub","home_page_link":"https://github.com/cydrain","self_intro":"Senior Software Engineer at Zilliz","repost_to_medium":null,"repost_state":null,"meta_description":"Leon Cai is a Senior Software Engineer at Zilliz.","locale":"en"}],"read_time":6,"localizations":[{"id":1331,"locale":"ja-JP","published_at":"2023-11-09T23:29:53.986Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Unlock_Recommendation_Use_Cases_with_Milvus_New_Range_Search_0f8cdc3d3c.png","belong":"blog","authorNames":["Leon Cai"]},{"id":"blog-275","title":"Zilliz at HackNC 2023","image":{"id":6531,"url":"https://assets.zilliz.com/NOV_03_Recapping_Hack_NC_253a93635a.png"},"display_time":"Nov 08, 2023","deploy_time":"2023-11-09T04:00:00.000Z","url":"Zilliz-vector-database-HackNC-2023","abstract":"In case you missed it, here's a recap of Zilliz at HackNC 2023.","tags":[{"id":4,"name":"Company","published_at":"2021-01-21T02:28:23.551Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:20.676Z","updated_at":"2021-01-21T02:28:23.824Z","locale":"en"}],"authors":[{"id":41,"name":"Yujian Tang","author_tags":"Developer Advocate at Zilliz","published_at":"2023-04-20T21:52:47.479Z","created_by":18,"updated_by":18,"created_at":"2023-04-20T21:52:45.859Z","updated_at":"2024-07-18T16:02:07.497Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/yujiantang/","self_intro":"Yujian Tang is a Developer Advocate at Zilliz. He has a background as a software engineer working on AutoML at Amazon. Yujian studied Computer Science, Statistics, and Neuroscience with research papers published to conferences including IEEE Big Data. He enjoys drinking bubble tea, spending time with family, and being near water.","repost_to_medium":null,"repost_state":null,"meta_description":"Yujian Tang, Developer Advocate at Zilliz. ","locale":"en"}],"read_time":1,"localizations":[{"id":1136,"locale":"ja-JP","published_at":"2023-11-09T23:32:47.192Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/NOV_03_Recapping_Hack_NC_253a93635a.png","belong":"blog","authorNames":["Yujian Tang"]},{"id":"learn-71","title":"Natural Language Processing Fundamentals: Tokens, N-Grams, and Bag-of-Words Models","image":{"id":2150,"url":"https://assets.zilliz.com/Nov_03_Tokens_N_Grams_and_Bag_of_Words_Models_6d73d71beb.png"},"display_time":"Nov 07, 2023","url":"introduction-to-natural-language-processing-tokens-ngrams-bag-of-words-models","abstract":"This post covers Natural Language Processing fundamentals that are essential to understanding all of today’s language models.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":3,"name":"Frank Liu","author_tags":"Director of Operations \u0026 ML Architect at Zilliz","published_at":"2021-12-23T11:08:08.015Z","created_by":18,"updated_by":18,"created_at":"2021-12-23T10:40:59.821Z","updated_at":"2023-04-21T22:30:10.416Z","home_page":"GitHub","home_page_link":"https://github.com/fzliu","self_intro":"Frank Liu is the Director of Operations \u0026 ML Architect at Zilliz, where he serves as a maintainer for the Towhee open-source project. Prior to Zilliz, Frank co-founded Orion Innovations, an ML-powered indoor positioning startup based in Shanghai and worked as an ML engineer at Yahoo in San Francisco. In his free time, Frank enjoys playing chess, swimming, and powerlifting. Frank holds MS and BS degrees in Electrical Engineering from Stanford University. ","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":7,"localizations":[{"id":411,"locale":"ja-JP","published_at":"2023-11-07T09:14:34.964Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Nov_03_Tokens_N_Grams_and_Bag_of_Words_Models_6d73d71beb.png","belong":"learn","authorNames":["Frank Liu"]},{"id":"learn-70","title":"An Introduction to Natural Language Processing","image":{"id":2141,"url":"https://assets.zilliz.com/Nov_03_A_Beginner_s_Guide_to_NLP_20231103_032516_836dcea6a7.png"},"display_time":"Nov 06, 2023","url":"A-Beginner-Guide-to-Natural-Language-Processing","abstract":"Learn the intricacies of Natural Language Processing and how vector databases, like Zilliz Cloud, transform NLP with efficient embedding storage and retrieval. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":36,"name":"Chris Churilo","author_tags":"VP of Marketing","published_at":"2023-04-11T16:51:05.002Z","created_by":18,"updated_by":53,"created_at":"2023-04-11T16:42:46.067Z","updated_at":"2025-01-16T22:35:53.011Z","home_page":"GitHub","home_page_link":"https://github.com/ChrisChurilo","self_intro":"Chris Churilo is the VP of Marketing \u0026 Community at Zilliz where she leads all community, developer relations, and marketing efforts. Prior to Zilliz, Chris was a founding member of the InfluxData’s go to market efforts and helped propel the time series database platform to dominance in the market. In earlier roles she defined and designed a SaaS monitoring solution at Centroid, and prior to that she was the VP of product management at iPass and was the LOB for several cloud services that required her to track the business and operational metrics and analytics to help identify and resolve issues.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":6,"localizations":[{"id":321,"locale":"ja-JP","published_at":"2023-11-06T02:10:04.234Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Nov_03_A_Beginner_s_Guide_to_NLP_20231103_032516_836dcea6a7.png","belong":"learn","authorNames":["Chris Churilo"]},{"id":"blog-272","title":"Zilliz at CalHacks 2023","image":{"id":6532,"url":"https://assets.zilliz.com/NOV_03_Recapping_Cal_Hacks_7a532d3a12.png"},"display_time":"Nov 03, 2023","deploy_time":null,"url":"zilliz-at-calhacks-2023","abstract":"If you didn't catch CalHack 2023, read this recap complete with attendee and prize stats as well as overviews of winning projects. ","tags":[{"id":4,"name":"Company","published_at":"2021-01-21T02:28:23.551Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:20.676Z","updated_at":"2021-01-21T02:28:23.824Z","locale":"en"}],"authors":[{"id":94,"name":"Christy Bergman","author_tags":"Developer Advocate","published_at":"2023-10-06T00:29:45.486Z","created_by":18,"updated_by":18,"created_at":"2023-10-06T00:29:30.751Z","updated_at":"2024-07-18T16:01:45.942Z","home_page":null,"home_page_link":null,"self_intro":"Christy Bergman is a passionate Developer Advocate at Zilliz. She previously worked in distributed computing at Anyscale and as a Specialist AI/ML Solutions Architect at AWS. Christy studied applied math, is a self-taught coder, and has published papers, including one with ACM Recsys. She enjoys hiking and bird watching.","repost_to_medium":null,"repost_state":null,"meta_description":"Christy Bergman is a passionate Developer Advocate at Zilliz. ","locale":"en"}],"read_time":5,"localizations":[{"id":1002,"locale":"ja-JP","published_at":"2023-11-03T14:24:54.534Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/NOV_03_Recapping_Cal_Hacks_7a532d3a12.png","belong":"blog","authorNames":["Christy Bergman"]},{"id":"blog-273","title":"Announcing Confluent's Kafka Connector for Milvus and Zilliz Cloud: Unlocking the Power of Real-Time AI","image":{"id":2142,"url":"https://assets.zilliz.com/Oct_26_Breaking_Barriers_Zilliz_and_Confluent_Integration_for_Real_Time_AI_Applications_20231026_113527_f74decf1f2.png"},"display_time":"Nov 03, 2023","deploy_time":"2023-11-06T04:00:00.000Z","url":"announce-confluent-kafka-connector-for-Milvus-and-Zilliz-unlock-power-of-real-time-ai","abstract":"The newly released Confluent Kafka Sink Connector enables seamless real-time vector data streaming from Confluent to Milvus or Zilliz. \n","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":45,"name":"Fendy Feng","author_tags":"Technical Marketing Writer","published_at":"2023-05-16T01:36:15.102Z","created_by":18,"updated_by":18,"created_at":"2023-05-16T00:04:12.065Z","updated_at":"2024-04-25T08:37:19.712Z","home_page":"GitHub","home_page_link":"https://www.linkedin.com/in/fendy311/","self_intro":"Fendy Feng is the Technical Marketing Writer at Zilliz. She has extensive experience developing and enhancing the impact of open-source projects in various global markets by producing high-quality, tailored content. Before joining Zilliz, Fendy worked as a Content Strategist at PingCAP, a fast-growing E-Series startup renowned for its open-source distributed SQL database.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":4,"localizations":[{"id":1300,"locale":"ja-JP","published_at":"2023-11-06T03:27:44.652Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Oct_26_Breaking_Barriers_Zilliz_and_Confluent_Integration_for_Real_Time_AI_Applications_20231026_113527_f74decf1f2.png","belong":"blog","authorNames":["Fendy Feng"]},{"id":"blog-269","title":"Alexandr Guzhva: Why I Joined Zilliz","image":{"id":2122,"url":"https://assets.zilliz.com/Alexandr_Guzhva_Why_I_Joined_Zilliz_f36dc09545.png"},"display_time":"Nov 02, 2023","deploy_time":"2023-11-02T12:50:00.000Z","url":"alexander-guzhva-why-i-joined-zilliz","abstract":"Learn why Alexandr Guzhva, one of the authors of the FAISS library, joined Zilliz as Principal Software Engineer.","tags":[{"id":4,"name":"Company","published_at":"2021-01-21T02:28:23.551Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:20.676Z","updated_at":"2021-01-21T02:28:23.824Z","locale":"en"}],"authors":[{"id":105,"name":"Alexandr Guzhva","author_tags":"Principal Software Engineer at Zilliz","published_at":"2023-11-02T02:16:35.636Z","created_by":18,"updated_by":18,"created_at":"2023-10-31T23:24:45.365Z","updated_at":"2024-07-18T15:59:06.874Z","home_page":null,"home_page_link":null,"self_intro":"Alexandr Guzhva is the Principal Engineer at Zilliz. Before joining Zilliz, he spent 15 years in the finance industry, working as a Quantitative Developer on designing software for algo-trading, time series prediction and performance optimization for CPU/GPU hardware. He is one of the authors of the FAISS library, which he helped to optimize during his work in Meta. Overall, he has been using methods from the similarity search for 10 years. Alexandr holds PhD in CS and MS in Physics from Lomonosov Moscow State University.","repost_to_medium":null,"repost_state":null,"meta_description":"Alexandr Guzhva is the Principal Engineer at Zilliz. ","locale":"en"}],"read_time":2,"localizations":[{"id":1318,"locale":"ja-JP","published_at":"2023-11-02T06:51:15.635Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Alexandr_Guzhva_Why_I_Joined_Zilliz_f36dc09545.png","belong":"blog","authorNames":["Alexandr Guzhva"]},{"id":"blog-270","title":"Evaluations for Retrieval Augmented Generation: TruLens + Milvus","image":{"id":2118,"url":"https://assets.zilliz.com/Using_Evals_to_Build_Better_RA_Gs_Tru_Lens_Milvus_9a9bcbf354.png"},"display_time":"Oct 31, 2023","deploy_time":"2023-10-31T12:50:00.000Z","url":"evaluations-for-retrieval-augmented-generation-trulens-milvus","abstract":"Learn how to build a RAG with various configurations and parameters, including index type, embedding model, top k and chunk size.\n","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":92,"name":"Josh Reini","author_tags":"Data Scientist, DevRel Engineer at TruEra ","published_at":"2023-09-29T17:13:48.328Z","created_by":18,"updated_by":18,"created_at":"2023-09-29T17:12:33.921Z","updated_at":"2023-10-31T06:11:29.009Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/josh-reini/","self_intro":"Josh is a core contributor to open-source TruLens and the founding Developer Relations Data Scientist at TruEra where he is responsible for education initiatives and nurturing a thriving community of practitioners excited about AI quality.\n\nJosh has delivered tech talks and workshops to more than a thousand developers at events including the Global AI Conference 2023, NYC Dev Day 2023, LLMs and the Generative AI Revolution 2023, AI developer meetups and the AI Quality Workshop (both in live format and on-demand through Udemy).\n\nPrior to TruEra, Josh delivered end-to-end data and machine learning and solutions to clients including the Department of State and the Walter Reed National Military Medical Center.\n","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":10,"localizations":[{"id":1332,"locale":"ja-JP","published_at":"2023-10-31T06:19:37.038Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Using_Evals_to_Build_Better_RA_Gs_Tru_Lens_Milvus_9a9bcbf354.png","belong":"blog","authorNames":["Josh Reini"]},{"id":"blog-268","title":"Retrieval Augmented Generation on Notion Docs via LangChain","image":{"id":2120,"url":"https://assets.zilliz.com/Retrieval_Augmented_Generation_on_Notion_Docs_via_Lang_Chain_c3a92bdb2e.png"},"display_time":"Oct 30, 2023","deploy_time":null,"url":"retrieval-augmented-generation-on-notion-docs-via-langchain","abstract":"This article explores how to enhance Notion documents with language model interactions using LangChain and Milvus.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":41,"name":"Yujian Tang","author_tags":"Developer Advocate at Zilliz","published_at":"2023-04-20T21:52:47.479Z","created_by":18,"updated_by":18,"created_at":"2023-04-20T21:52:45.859Z","updated_at":"2024-07-18T16:02:07.497Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/yujiantang/","self_intro":"Yujian Tang is a Developer Advocate at Zilliz. He has a background as a software engineer working on AutoML at Amazon. Yujian studied Computer Science, Statistics, and Neuroscience with research papers published to conferences including IEEE Big Data. He enjoys drinking bubble tea, spending time with family, and being near water.","repost_to_medium":null,"repost_state":null,"meta_description":"Yujian Tang, Developer Advocate at Zilliz. ","locale":"en"}],"read_time":5,"localizations":[{"id":1147,"locale":"ja-JP","published_at":"2023-10-30T15:49:04.702Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Retrieval_Augmented_Generation_on_Notion_Docs_via_Lang_Chain_c3a92bdb2e.png","belong":"blog","authorNames":["Yujian Tang"]},{"id":"learn-69","title":"DiskANN and the Vamana Algorithm","image":{"id":2155,"url":"https://assets.zilliz.com/Nov_08_Disk_ANN_and_the_Vamana_Algorithm_a0241e5277.png"},"display_time":"Oct 29, 2023","url":"DiskANN-and-the-Vamana-Algorithm","abstract":"Dive into DiskANN, a graph-based vector index, and Vamana, the core data structure behind DiskANN. ","tags":[{"id":39,"name":"VectorDB 101","published_at":"2022-09-30T05:56:34.554Z","created_by":18,"updated_by":18,"created_at":"2022-09-30T05:56:31.633Z","updated_at":"2024-07-10T07:12:04.155Z","locale":"en"}],"authors":[{"id":3,"name":"Frank Liu","author_tags":"Director of Operations \u0026 ML Architect at Zilliz","published_at":"2021-12-23T11:08:08.015Z","created_by":18,"updated_by":18,"created_at":"2021-12-23T10:40:59.821Z","updated_at":"2023-04-21T22:30:10.416Z","home_page":"GitHub","home_page_link":"https://github.com/fzliu","self_intro":"Frank Liu is the Director of Operations \u0026 ML Architect at Zilliz, where he serves as a maintainer for the Towhee open-source project. Prior to Zilliz, Frank co-founded Orion Innovations, an ML-powered indoor positioning startup based in Shanghai and worked as an ML engineer at Yahoo in San Francisco. In his free time, Frank enjoys playing chess, swimming, and powerlifting. Frank holds MS and BS degrees in Electrical Engineering from Stanford University. ","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":6,"localizations":[{"id":303,"locale":"ja-JP","published_at":"2023-10-30T00:39:49.412Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Nov_08_Disk_ANN_and_the_Vamana_Algorithm_a0241e5277.png","belong":"learn","authorNames":["Frank Liu"]},{"id":"blog-267","title":"Exploring LLM-Driven Agents in the Age of AI","image":{"id":2092,"url":"https://assets.zilliz.com/Intelligent_Agent_Using_LL_Ms_ff7a90bffb.png"},"display_time":"Oct 27, 2023","deploy_time":"2023-10-30T02:30:00.000Z","url":"explore-llm-driven-agents-in-age-of-AI","abstract":"Explore the intricacies of LLM-driven agents, their components, challenges, and future prospects, reshaping the future of artificial intelligence and revolutionizing how we approach complex tasks.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":102,"name":"David Wang","author_tags":"Algorithm Engineer at Zilliz","published_at":"2023-10-27T08:41:57.519Z","created_by":18,"updated_by":18,"created_at":"2023-10-27T08:41:55.636Z","updated_at":"2024-04-16T02:43:37.282Z","home_page":"GitHub","home_page_link":"https://github.com/wxywb","self_intro":"David Wang, Algorithm Engineer at Zilliz, brings extensive expertise in computer vision and natural language processing. His contributions to advanced embedding algorithm research, including projects like Towhee and GPTCache, reflect his commitment to advancing AI technologies. Before joining Zilliz, he worked at Alibaba Cloud for large-scale object recognition and classification projects. David holds a Master's degree from Dalian University of Technology.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":4,"localizations":[{"id":1262,"locale":"ja-JP","published_at":"2023-10-30T02:41:09.276Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Intelligent_Agent_Using_LL_Ms_ff7a90bffb.png","belong":"blog","authorNames":["David Wang"]},{"id":"blog-266","title":"Experimenting with Different Chunking Strategies via LangChain for LLM Apps","image":{"id":2059,"url":"https://assets.zilliz.com/Testing_Chunking_Lang_Chain_2e7f698b3c.png"},"display_time":"Oct 24, 2023","deploy_time":"2023-10-24T12:50:00.000Z","url":"experimenting-with-different-chunking-strategies-via-langchain","abstract":"Explore the complexities of text chunking in retrieval augmented generation applications and learn how different chunking strategies impact the same piece of data. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":41,"name":"Yujian Tang","author_tags":"Developer Advocate at Zilliz","published_at":"2023-04-20T21:52:47.479Z","created_by":18,"updated_by":18,"created_at":"2023-04-20T21:52:45.859Z","updated_at":"2024-07-18T16:02:07.497Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/yujiantang/","self_intro":"Yujian Tang is a Developer Advocate at Zilliz. He has a background as a software engineer working on AutoML at Amazon. Yujian studied Computer Science, Statistics, and Neuroscience with research papers published to conferences including IEEE Big Data. He enjoys drinking bubble tea, spending time with family, and being near water.","repost_to_medium":null,"repost_state":null,"meta_description":"Yujian Tang, Developer Advocate at Zilliz. ","locale":"en"}],"read_time":11,"localizations":[{"id":1033,"locale":"ja-JP","published_at":"2023-10-24T05:06:49.632Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Testing_Chunking_Lang_Chain_2e7f698b3c.png","belong":"blog","authorNames":["Yujian Tang"]},{"id":"learn-68","title":"Understanding Vector Databases: Compare Vector Databases, Vector Search Libraries, and Vector Search Plugins","image":{"id":2117,"url":"https://assets.zilliz.com/Oct_30_Vector_Databases_vs_Vector_Search_Plugins_vs_Vector_Search_Libraries_20231031_083818_78d4aaad3d.png"},"display_time":"Oct 23, 2023","url":"comparing-vector-database-vector-search-library-and-vector-search-plugin","abstract":"Deep diving into better understanding vector databases and comparing them to vector search libraries and vector search plugins.","tags":[{"id":39,"name":"VectorDB 101","published_at":"2022-09-30T05:56:34.554Z","created_by":18,"updated_by":18,"created_at":"2022-09-30T05:56:31.633Z","updated_at":"2024-07-10T07:12:04.155Z","locale":"en"}],"authors":[{"id":3,"name":"Frank Liu","author_tags":"Director of Operations \u0026 ML Architect at Zilliz","published_at":"2021-12-23T11:08:08.015Z","created_by":18,"updated_by":18,"created_at":"2021-12-23T10:40:59.821Z","updated_at":"2023-04-21T22:30:10.416Z","home_page":"GitHub","home_page_link":"https://github.com/fzliu","self_intro":"Frank Liu is the Director of Operations \u0026 ML Architect at Zilliz, where he serves as a maintainer for the Towhee open-source project. Prior to Zilliz, Frank co-founded Orion Innovations, an ML-powered indoor positioning startup based in Shanghai and worked as an ML engineer at Yahoo in San Francisco. In his free time, Frank enjoys playing chess, swimming, and powerlifting. Frank holds MS and BS degrees in Electrical Engineering from Stanford University. ","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":6,"localizations":[{"id":293,"locale":"ja-JP","published_at":"2025-01-22T07:06:14.425Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Oct_30_Vector_Databases_vs_Vector_Search_Plugins_vs_Vector_Search_Libraries_20231031_083818_78d4aaad3d.png","belong":"learn","authorNames":["Frank Liu"]},{"id":"blog-265","title":"Jiang Chen: Why I Joined Zilliz","image":{"id":2020,"url":"https://assets.zilliz.com/Why_I_joined_Zilliz_Chen_Jiang_08848819b5.png"},"display_time":"Oct 16, 2023","deploy_time":null,"url":"jiang-chen-why-i-joined-zilliz","abstract":"I am passionate about democratizing AI-native infrastructures and enjoying working with awesome people here at Zilliz.","tags":[{"id":4,"name":"Company","published_at":"2021-01-21T02:28:23.551Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:20.676Z","updated_at":"2021-01-21T02:28:23.824Z","locale":"en"}],"authors":[{"id":101,"name":"Jiang Chen","author_tags":"Head of Ecosystem and Developer Relations","published_at":"2023-10-16T07:05:20.176Z","created_by":18,"updated_by":82,"created_at":"2023-10-16T07:05:18.702Z","updated_at":"2024-09-10T17:33:55.053Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/jiang-0616/","self_intro":"Jiang is currently Head of Ecosystem and Developer Relations at Zilliz. He has years of experience in data infrastructures and cloud security. Before joining Zilliz, he had previously served as a tech lead and product manager at Google, where he led the development of web-scale semantic understanding and search indexing that powers innovative search products such as short video search. He has extensive industry experience handling massive unstructured data and multimedia content retrieval. He has also worked on cloud authorization systems and research on data privacy technologies. Jiang holds a Master's degree in Computer Science from the University of Michigan.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":4,"localizations":[{"id":986,"locale":"ja-JP","published_at":"2023-10-16T14:05:05.493Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Why_I_joined_Zilliz_Chen_Jiang_08848819b5.png","belong":"blog","authorNames":["Jiang Chen"]},{"id":"blog-261","title":"Milvus Introduced MMap for Redefined Data Management and Increased Storage Capability","image":{"id":1985,"url":"https://assets.zilliz.com/Exploring_M_Map_8d1011f85b.png"},"display_time":"Oct 13, 2023","deploy_time":"2023-10-16T03:30:00.000Z","url":"milvus-introduced-mmap-for-redefined-data-management-increased-storage-capability","abstract":"The Milvus MMap feature empowers users to handle more data within limited memory, striking a delicate balance between performance, cost, and system limits.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":100,"name":"Yang Cen","author_tags":"Senior Software Engineer at Zilliz","published_at":"2023-10-12T13:28:44.905Z","created_by":18,"updated_by":18,"created_at":"2023-10-12T13:28:42.580Z","updated_at":"2024-07-18T15:58:00.280Z","home_page":"GitHub","home_page_link":"https://github.com/yah01","self_intro":"Yang Cen is a Senior Software Engineer at Zilliz","repost_to_medium":null,"repost_state":null,"meta_description":"Yang Cen is a Senior Software Engineer at Zilliz.","locale":"en"}],"read_time":3,"localizations":[{"id":1386,"locale":"ja-JP","published_at":"2023-10-16T03:13:43.619Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Exploring_M_Map_8d1011f85b.png","belong":"blog","authorNames":["Yang Cen"]},{"id":"blog-260","title":"Chat with Towards Data Science Using LlamaIndex","image":{"id":1979,"url":"https://assets.zilliz.com/Chat_with_Towards_Data_Science_Using_Llama_Index_704d5c89ea.png"},"display_time":"Oct 12, 2023","deploy_time":"2023-10-12T12:50:00.000Z","url":"chat-with-towards-data-science-using-llamaindex","abstract":"In this second post of the four-part Chat Towards Data Science blog series, we show why LlamaIndex is the leading open source data retrieval framework. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":41,"name":"Yujian Tang","author_tags":"Developer Advocate at Zilliz","published_at":"2023-04-20T21:52:47.479Z","created_by":18,"updated_by":18,"created_at":"2023-04-20T21:52:45.859Z","updated_at":"2024-07-18T16:02:07.497Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/yujiantang/","self_intro":"Yujian Tang is a Developer Advocate at Zilliz. He has a background as a software engineer working on AutoML at Amazon. Yujian studied Computer Science, Statistics, and Neuroscience with research papers published to conferences including IEEE Big Data. He enjoys drinking bubble tea, spending time with family, and being near water.","repost_to_medium":null,"repost_state":null,"meta_description":"Yujian Tang, Developer Advocate at Zilliz. ","locale":"en"}],"read_time":6,"localizations":[{"id":1362,"locale":"ja-JP","published_at":"2023-10-12T05:11:39.962Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Chat_with_Towards_Data_Science_Using_Llama_Index_704d5c89ea.png","belong":"blog","authorNames":["Yujian Tang"]},{"id":"blog-259","title":"Optimizing Data Communication: Milvus Embraces NATS Messaging","image":{"id":1977,"url":"https://assets.zilliz.com/Enhancing_Data_Communication_Milvus_Embraces_NATS_Messaging_de1c4ab893.png"},"display_time":"Oct 11, 2023","deploy_time":"2023-10-11T12:50:00.000Z","url":"optimizing-data-communication-milvus-embraces-nats-messaging","abstract":"Introducing the integration of NATS and Milvus, exploring its features, setup and migration process, and performance testing results.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":95,"name":"Zhen Ye","author_tags":"Software Engineer at Zilliz","published_at":"2023-10-09T11:56:42.604Z","created_by":18,"updated_by":18,"created_at":"2023-10-09T11:56:37.446Z","updated_at":"2024-07-18T16:00:57.159Z","home_page":"GitHub","home_page_link":"https://github.com/chyezh","self_intro":"Software Engineer at Zilliz","repost_to_medium":null,"repost_state":null,"meta_description":"Zhen Ye, Software Engineer at Zilliz","locale":"en"}],"read_time":5,"localizations":[{"id":1270,"locale":"ja-JP","published_at":"2023-10-11T05:27:49.940Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Enhancing_Data_Communication_Milvus_Embraces_NATS_Messaging_de1c4ab893.png","belong":"blog","authorNames":["Zhen Ye"]},{"id":"blog-258","title":"Use Milvus and Airbyte for Similarity Search on All Your Data","image":{"id":1963,"url":"https://assets.zilliz.com/Use_Milvus_and_Airbyte_for_similarity_search_on_all_your_data_57d6a11c7a.png"},"display_time":"Oct 10, 2023","deploy_time":null,"url":"use-milvus-and-airbyte-for-similarity-search-on-all-your-data","abstract":"By using Airbyte, it's straightforward to transfer data from many different sources into Milvus, calculating vector embeddings of texts along the way.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":96,"name":"Joe Reuter ","author_tags":"Software Engineer at Airbyte","published_at":"2023-10-10T09:32:01.267Z","created_by":18,"updated_by":18,"created_at":"2023-10-10T09:31:59.542Z","updated_at":"2024-07-18T16:01:23.047Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/joe-reuter-72b58052/","self_intro":"Joe is a full stack software engineer at Airbyte, mostly working on machine learning and backend projects, occasionally helping out with frontend matters.","repost_to_medium":null,"repost_state":null,"meta_description":"Joe is a full-stack software engineer at Airbyte. ","locale":"en"}],"read_time":8,"localizations":[{"id":964,"locale":"ja-JP","published_at":"2023-10-10T17:46:22.156Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Use_Milvus_and_Airbyte_for_similarity_search_on_all_your_data_57d6a11c7a.png","belong":"blog","authorNames":["Joe Reuter "]},{"id":"blog-257","title":"Christy Bergman: Why I Joined Zilliz","image":{"id":1930,"url":"https://assets.zilliz.com/Christy_Bergman_Why_I_Joined_Zilliz_b2fb83c8a1.png"},"display_time":"Oct 06, 2023","deploy_time":null,"url":"christy-bergman-why-i-joined-zilliz","abstract":"Learn why Christy Bergman joined Zilliz as Developer Advocate and all the steps that brought her here.","tags":[{"id":4,"name":"Company","published_at":"2021-01-21T02:28:23.551Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:20.676Z","updated_at":"2021-01-21T02:28:23.824Z","locale":"en"}],"authors":[{"id":94,"name":"Christy Bergman","author_tags":"Developer Advocate","published_at":"2023-10-06T00:29:45.486Z","created_by":18,"updated_by":18,"created_at":"2023-10-06T00:29:30.751Z","updated_at":"2024-07-18T16:01:45.942Z","home_page":null,"home_page_link":null,"self_intro":"Christy Bergman is a passionate Developer Advocate at Zilliz. She previously worked in distributed computing at Anyscale and as a Specialist AI/ML Solutions Architect at AWS. Christy studied applied math, is a self-taught coder, and has published papers, including one with ACM Recsys. She enjoys hiking and bird watching.","repost_to_medium":null,"repost_state":null,"meta_description":"Christy Bergman is a passionate Developer Advocate at Zilliz. ","locale":"en"}],"read_time":6,"localizations":[{"id":1148,"locale":"ja-JP","published_at":"2023-10-06T11:52:00.428Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Christy_Bergman_Why_I_Joined_Zilliz_b2fb83c8a1.png","belong":"blog","authorNames":["Christy Bergman"]},{"id":"blog-256","title":"Efficient Vector Similarity Search in Recommender Workflows Using Milvus with NVIDIA Merlin","image":{"id":1916,"url":"https://assets.zilliz.com/Efficient_Vector_Similarity_Search_in_Recommender_Workflows_using_Milvus_with_NVIDIA_Merlin_466cecb80d.png"},"display_time":"Oct 04, 2023","deploy_time":null,"url":"efficient-vector-similarity-search-recommender-workflows-using-milvus-nvidia-merlin","abstract":"An introduction to NVIDIA Merlin and Milvus integration in building recommender systems and benchmarking its performance in various scenarios. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":93,"name":"Burcin Bozkaya","author_tags":"Sr. Developer Relations Manager at NVIDIA","published_at":"2023-10-04T02:46:37.035Z","created_by":18,"updated_by":18,"created_at":"2023-10-04T02:39:08.264Z","updated_at":"2024-04-29T03:31:44.198Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":14,"localizations":[{"id":1384,"locale":"ja-JP","published_at":"2023-10-04T13:08:36.510Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Efficient_Vector_Similarity_Search_in_Recommender_Workflows_using_Milvus_with_NVIDIA_Merlin_466cecb80d.png","belong":"blog","authorNames":["Burcin Bozkaya"]},{"id":"blog-255","title":"How to Get the Right Vector Embeddings","image":{"id":1912,"url":"https://assets.zilliz.com/How_to_Get_the_Right_Vector_Embedding_4b747e7448.png"},"display_time":"Oct 03, 2023","deploy_time":null,"url":"how-to-get-the-right-vector-embeddings","abstract":"A comprehensive introduction to vector embeddings and how to generate them with popular open-source models. \n","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":41,"name":"Yujian Tang","author_tags":"Developer Advocate at Zilliz","published_at":"2023-04-20T21:52:47.479Z","created_by":18,"updated_by":18,"created_at":"2023-04-20T21:52:45.859Z","updated_at":"2024-07-18T16:02:07.497Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/yujiantang/","self_intro":"Yujian Tang is a Developer Advocate at Zilliz. He has a background as a software engineer working on AutoML at Amazon. Yujian studied Computer Science, Statistics, and Neuroscience with research papers published to conferences including IEEE Big Data. He enjoys drinking bubble tea, spending time with family, and being near water.","repost_to_medium":null,"repost_state":null,"meta_description":"Yujian Tang, Developer Advocate at Zilliz. ","locale":"en"}],"read_time":8,"localizations":[{"id":1186,"locale":"ja-JP","published_at":"2023-10-03T13:10:17.516Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/How_to_Get_the_Right_Vector_Embedding_4b747e7448.png","belong":"blog","authorNames":["Yujian Tang"]},{"id":"blog-254","title":"How to Migrate Your Data to Milvus Seamlessly: A Comprehensive Guide","image":{"id":1907,"url":"https://assets.zilliz.com/How_to_Migrate_Your_Data_to_Milvus_with_Ease_b56934244d.png"},"display_time":"Oct 02, 2023","deploy_time":null,"url":"how-to-migrate-data-to-milvus-seamlessly-comprehensive-guide","abstract":"A comprehensive guide on migrating your data from Elasticsearch, FAISS, and older Milvus 1.x to Milvus 2.x versions.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":91,"name":"Wenhui Zhang","author_tags":"Senior Software Engineer at Zilliz ","published_at":"2023-09-29T13:29:38.751Z","created_by":18,"updated_by":18,"created_at":"2023-09-29T13:29:34.133Z","updated_at":"2024-07-18T15:58:12.634Z","home_page":null,"home_page_link":null,"self_intro":"Senior Software Engineer at Zilliz ","repost_to_medium":null,"repost_state":null,"meta_description":"Wenhui Zhang is a Senior Software Engineer at Zilliz.","locale":"en"}],"read_time":8,"localizations":[{"id":1239,"locale":"ja-JP","published_at":"2023-10-02T13:26:58.054Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/How_to_Migrate_Your_Data_to_Milvus_with_Ease_b56934244d.png","belong":"blog","authorNames":["Wenhui Zhang"]},{"id":"blog-252","title":"Getting Started with GPU-Powered Milvus: Unlocking 10x Higher Performance","image":{"id":1899,"url":"https://assets.zilliz.com/How_to_Deploy_Milvus_with_GPU_support_Using_Docker_Compose_070a58ebb7.png"},"display_time":"Sep 29, 2023","deploy_time":null,"url":"getting-started-with-gpu-powered-milvus-unlocking-10x-higher-performance","abstract":"A practical tutorial to assist you in quickly getting started with the GPU version of Milvus and significantly boosting your vector search performance by ten times.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":90,"name":"Jaken Ma","author_tags":"Staff Engineer at Zilliz","published_at":"2023-09-27T12:48:17.638Z","created_by":18,"updated_by":18,"created_at":"2023-09-27T12:48:10.328Z","updated_at":"2023-09-27T12:48:17.650Z","home_page":null,"home_page_link":null,"self_intro":"Staff Engineer at Zilliz","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":4,"localizations":[{"id":1154,"locale":"ja-JP","published_at":"2023-09-29T12:47:04.074Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/How_to_Deploy_Milvus_with_GPU_support_Using_Docker_Compose_070a58ebb7.png","belong":"blog","authorNames":["Jaken Ma"]},{"id":"blog-253","title":"Using SelfQueryRetriever with LangChain to Query a Vector Database","image":{"id":1900,"url":"https://assets.zilliz.com/Using_Lang_Chain_to_Query_a_Vector_Database_abd008b4e4.png"},"display_time":"Sep 28, 2023","deploy_time":null,"url":"using-langchain-to-self-query-vector-database","abstract":"Experiment with LangChain’s self-query feature to build a simple RAG app that combines the LLM and a vector database like Milvus.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":41,"name":"Yujian Tang","author_tags":"Developer Advocate at Zilliz","published_at":"2023-04-20T21:52:47.479Z","created_by":18,"updated_by":18,"created_at":"2023-04-20T21:52:45.859Z","updated_at":"2024-07-18T16:02:07.497Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/yujiantang/","self_intro":"Yujian Tang is a Developer Advocate at Zilliz. He has a background as a software engineer working on AutoML at Amazon. Yujian studied Computer Science, Statistics, and Neuroscience with research papers published to conferences including IEEE Big Data. He enjoys drinking bubble tea, spending time with family, and being near water.","repost_to_medium":null,"repost_state":null,"meta_description":"Yujian Tang, Developer Advocate at Zilliz. ","locale":"en"}],"read_time":8,"localizations":[{"id":865,"locale":"ja-JP","published_at":"2023-09-28T13:30:45.737Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Using_Lang_Chain_to_Query_a_Vector_Database_abd008b4e4.png","belong":"blog","authorNames":["Yujian Tang"]},{"id":"blog-251","title":"Zilliz x Galileo: The Power of Vector Embeddings","image":{"id":1876,"url":"https://assets.zilliz.com/Zilliz_x_Galileo_The_Power_of_Vector_Embeddings_4b64b5727e.png"},"display_time":"Sep 27, 2023","deploy_time":null,"url":"zilliz-x-galileo-power-of-vector-embeddings","abstract":"Using vector embeddings to find data errors, find samples not present in your training data, find hallucinations, and fix errors in retrieval augmented generation.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":41,"name":"Yujian Tang","author_tags":"Developer Advocate at Zilliz","published_at":"2023-04-20T21:52:47.479Z","created_by":18,"updated_by":18,"created_at":"2023-04-20T21:52:45.859Z","updated_at":"2024-07-18T16:02:07.497Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/yujiantang/","self_intro":"Yujian Tang is a Developer Advocate at Zilliz. He has a background as a software engineer working on AutoML at Amazon. Yujian studied Computer Science, Statistics, and Neuroscience with research papers published to conferences including IEEE Big Data. He enjoys drinking bubble tea, spending time with family, and being near water.","repost_to_medium":null,"repost_state":null,"meta_description":"Yujian Tang, Developer Advocate at Zilliz. ","locale":"en"}],"read_time":5,"localizations":[{"id":1294,"locale":"ja-JP","published_at":"2023-09-27T02:54:34.391Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Zilliz_x_Galileo_The_Power_of_Vector_Embeddings_4b64b5727e.png","belong":"blog","authorNames":["Yujian Tang"]},{"id":"blog-246","title":"Zilliz Makes Real-Time AI a Reality with Confluent","image":{"id":1874,"url":"https://assets.zilliz.com/Zilliz_Makes_Real_Time_AI_a_Reality_with_Zilliz_and_Confluent_88a17da97d.png"},"display_time":"Sep 26, 2023","deploy_time":null,"url":"zilliz-makes-real-time-ai-a-reality-with-confluent","abstract":"The Zilliz and Confluent integration opens new avenues for leveraging Generative Artificial Intelligence (GenAI) in real-time scenarios.","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":76,"name":"Steffi Li","author_tags":"Director of Product Marketing","published_at":"2023-07-13T17:18:42.023Z","created_by":18,"updated_by":18,"created_at":"2023-07-13T17:16:54.449Z","updated_at":"2023-07-13T17:18:42.070Z","home_page":null,"home_page_link":null,"self_intro":"Steffi is the Director of Product Marketing at Zilliz, with prior experience leading the GTM strategies for open-source data technologies such as Apache Kafka and Apache Airflow. Passionate about travel, yoga, and non-fiction reading, she brings a balanced and enriched worldview to her professional pursuits.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":4,"localizations":[{"id":1263,"locale":"ja-JP","published_at":"2023-09-26T11:17:20.150Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Zilliz_Makes_Real_Time_AI_a_Reality_with_Zilliz_and_Confluent_88a17da97d.png","belong":"blog","authorNames":["Steffi Li"]},{"id":"blog-249","title":"Exploring the Marvels of Knowhere 2.0","image":{"id":1847,"url":"https://assets.zilliz.com/knowhere_2_0_df64340994.png"},"display_time":"Sep 25, 2023","deploy_time":null,"url":"exploring-marvels-of-Knowhere-2-0","abstract":"Exploring Knowhere 2.0: GPU acceleration, Cosine similarity, ARM support, and more advanced features for supercharging Milvus.","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":89,"name":"Patrick Xu","author_tags":"Senior Software Engineer","published_at":"2023-09-22T16:07:01.562Z","created_by":18,"updated_by":18,"created_at":"2023-09-22T16:06:57.605Z","updated_at":"2023-09-22T16:07:01.586Z","home_page":null,"home_page_link":null,"self_intro":"Senior Software Engineer","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":4,"localizations":[{"id":912,"locale":"ja-JP","published_at":"2023-09-25T22:25:50.765Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/knowhere_2_0_df64340994.png","belong":"blog","authorNames":["Patrick Xu"]},{"id":"blog-247","title":"Chat Towards Data Science: Building a Chatbot with Zilliz Cloud ","image":{"id":1817,"url":"https://assets.zilliz.com/Chat_Towards_Data_Science_Building_a_Chatbot_with_Zilliz_Cloud_1_2ebb043bd8.png"},"display_time":"Sep 20, 2023","deploy_time":"2023-09-21T04:00:00.000Z","url":"chat-towards-data-science-building-chatbot-with-zilliz-cloud","abstract":"Building a chatbot for the Towards Data Science publication using the Zilliz vector database","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":41,"name":"Yujian Tang","author_tags":"Developer Advocate at Zilliz","published_at":"2023-04-20T21:52:47.479Z","created_by":18,"updated_by":18,"created_at":"2023-04-20T21:52:45.859Z","updated_at":"2024-07-18T16:02:07.497Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/yujiantang/","self_intro":"Yujian Tang is a Developer Advocate at Zilliz. He has a background as a software engineer working on AutoML at Amazon. Yujian studied Computer Science, Statistics, and Neuroscience with research papers published to conferences including IEEE Big Data. He enjoys drinking bubble tea, spending time with family, and being near water.","repost_to_medium":null,"repost_state":null,"meta_description":"Yujian Tang, Developer Advocate at Zilliz. ","locale":"en"}],"read_time":11,"localizations":[{"id":898,"locale":"ja-JP","published_at":"2023-09-21T15:49:56.919Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Chat_Towards_Data_Science_Building_a_Chatbot_with_Zilliz_Cloud_1_2ebb043bd8.png","belong":"blog","authorNames":["Yujian Tang"]},{"id":"blog-244","title":"Comparing Llama 2 Chat and ChatGPT: How They Perform in Question Answering","image":{"id":1767,"url":"https://assets.zilliz.com/llama2_and_Chat_GPT_9a54f87726.jpg"},"display_time":"Sep 13, 2023","deploy_time":null,"url":"comparing-meta-ai-Llama2-openai-chatgpt","abstract":"What is Llama 2, and how does it perform in question answering compared to ChatGPT?","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":82,"name":"Towhee team","author_tags":"","published_at":"2023-09-12T13:42:29.667Z","created_by":18,"updated_by":18,"created_at":"2023-09-12T13:42:27.827Z","updated_at":"2023-09-12T13:42:29.680Z","home_page":"Website","home_page_link":"https://towhee.io/","self_intro":"Towhee is an open-source machine learning pipeline\nthat helps you encode your unstructured data into embeddings.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":10,"localizations":[{"id":1276,"locale":"ja-JP","published_at":"2023-09-13T13:08:15.791Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/llama2_and_Chat_GPT_9a54f87726.jpg","belong":"blog","authorNames":["Towhee team"]},{"id":"blog-242","title":"An Engineering Perspective: Why Milvus is a Compelling Option for Your Apps?","image":{"id":1763,"url":"https://assets.zilliz.com/Why_Milvus_2_3_2621ce8be2.png"},"display_time":"Sep 10, 2023","deploy_time":"2023-09-12T04:00:00.000Z","url":"engineering-perspective-why-milvus-compelling-option-for-apps","abstract":"Explore Milvus 2.3 from three crucial angles: database selection, development experience, and system reliability.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":81,"name":"Owen jiao","author_tags":"Principal Engineer at Zilliz ","published_at":"2023-09-11T08:52:36.550Z","created_by":18,"updated_by":18,"created_at":"2023-09-11T08:52:19.395Z","updated_at":"2024-07-18T15:59:30.481Z","home_page":"GitHub","home_page_link":"https://github.com/jiaoew1991","self_intro":"Owen Jiao is the Principal Engineer at Zilliz and the dedicated maintainer of the open-source Milvus project. Currently, he leads the research and development for the Milvus query engine, infusing it with innovation and expertise. Before joining Zilliz, Owen was a senior software engineer at Kyligence, where he led the development of Apache Kylin and MDX for Kylin. With extensive experience spanning databases, OLAP, and big data, Owen holds a master's degree in communication engineering from Shanghai Jiao Tong University.","repost_to_medium":null,"repost_state":null,"meta_description":"Owen Jiao was the Principal Engineer at Zilliz and the dedicated maintainer of the open-source Milvus project.","locale":"en"}],"read_time":3,"localizations":[{"id":1361,"locale":"ja-JP","published_at":"2023-09-12T06:49:33.742Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Why_Milvus_2_3_2621ce8be2.png","belong":"blog","authorNames":["Owen jiao"]},{"id":"blog-241","title":"How to Choose A Vector Database: Elastic Cloud vs. Zilliz Cloud","image":{"id":1760,"url":"https://assets.zilliz.com/Zilliz_Cloud_vs_Elastic_Cloud_20230904_033917_144d3814ef.png"},"display_time":"Sep 05, 2023","deploy_time":"2023-09-06T04:00:00.000Z","url":"elasticsearch-cloud-vs-zilliz","abstract":"Compare Elastic Cloud vs. Zilliz Cloud in this in-depth benchmark, cost and features comparison. ","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":36,"name":"Chris Churilo","author_tags":"VP of Marketing","published_at":"2023-04-11T16:51:05.002Z","created_by":18,"updated_by":53,"created_at":"2023-04-11T16:42:46.067Z","updated_at":"2025-01-16T22:35:53.011Z","home_page":"GitHub","home_page_link":"https://github.com/ChrisChurilo","self_intro":"Chris Churilo is the VP of Marketing \u0026 Community at Zilliz where she leads all community, developer relations, and marketing efforts. Prior to Zilliz, Chris was a founding member of the InfluxData’s go to market efforts and helped propel the time series database platform to dominance in the market. In earlier roles she defined and designed a SaaS monitoring solution at Centroid, and prior to that she was the VP of product management at iPass and was the LOB for several cloud services that required her to track the business and operational metrics and analytics to help identify and resolve issues.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":6,"localizations":[{"id":1104,"locale":"ja-JP","published_at":"2023-09-06T12:26:00.593Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Zilliz_Cloud_vs_Elastic_Cloud_20230904_033917_144d3814ef.png","belong":"blog","authorNames":["Chris Churilo"]},{"id":"blog-240","title":"What’s New in Milvus 2.3","image":{"id":1739,"url":"https://assets.zilliz.com/What_is_new_in_Milvus_2_3_d639803329.png"},"display_time":"Aug 30, 2023","deploy_time":null,"url":"whats-new-in-milvus-2-3","abstract":"The Milvus 2.3.0 release contains many exciting new features and improvements. This blog post will highlight some of the more prominent features. ","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":76,"name":"Steffi Li","author_tags":"Director of Product Marketing","published_at":"2023-07-13T17:18:42.023Z","created_by":18,"updated_by":18,"created_at":"2023-07-13T17:16:54.449Z","updated_at":"2023-07-13T17:18:42.070Z","home_page":null,"home_page_link":null,"self_intro":"Steffi is the Director of Product Marketing at Zilliz, with prior experience leading the GTM strategies for open-source data technologies such as Apache Kafka and Apache Airflow. Passionate about travel, yoga, and non-fiction reading, she brings a balanced and enriched worldview to her professional pursuits.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":2,"localizations":[{"id":1329,"locale":"ja-JP","published_at":"2023-08-30T04:44:46.199Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/What_is_new_in_Milvus_2_3_d639803329.png","belong":"blog","authorNames":["Steffi Li"]},{"id":"blog-239","title":"Building LLM Apps with 100x Faster Responses and Drastic Cost Reduction Using GPTCache","image":{"id":1732,"url":"https://assets.zilliz.com/LL_Ms_on_a_budget_with_GPT_Cache_3b85da79e0.png"},"display_time":"Aug 28, 2023","deploy_time":null,"url":"building-llm-apps-100x-faster-responses-drastic-cost-reduction-using-gptcache","abstract":"Open-source GPTCache addresses slow response and high cost and offers reduced network latency, improved availability, and better scalability.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":45,"name":"Fendy Feng","author_tags":"Technical Marketing Writer","published_at":"2023-05-16T01:36:15.102Z","created_by":18,"updated_by":18,"created_at":"2023-05-16T00:04:12.065Z","updated_at":"2024-04-25T08:37:19.712Z","home_page":"GitHub","home_page_link":"https://www.linkedin.com/in/fendy311/","self_intro":"Fendy Feng is the Technical Marketing Writer at Zilliz. She has extensive experience developing and enhancing the impact of open-source projects in various global markets by producing high-quality, tailored content. Before joining Zilliz, Fendy worked as a Content Strategist at PingCAP, a fast-growing E-Series startup renowned for its open-source distributed SQL database.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":6,"localizations":[{"id":1381,"locale":"ja-JP","published_at":"2023-08-28T06:30:43.602Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/LL_Ms_on_a_budget_with_GPT_Cache_3b85da79e0.png","belong":"blog","authorNames":["Fendy Feng"]},{"id":"blog-234","title":"Comparing Different Vector Embeddings","image":{"id":1711,"url":"https://assets.zilliz.com/Comparing_Different_Vector_Embeddings_e7ca1e4e5d.png"},"display_time":"Aug 21, 2023","deploy_time":null,"url":"comparing-different-vector-embeddings","abstract":"Learn about the difference in vector embeddings between models and how to use multiple collections of vector data in one Jupyter Notebook.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":41,"name":"Yujian Tang","author_tags":"Developer Advocate at Zilliz","published_at":"2023-04-20T21:52:47.479Z","created_by":18,"updated_by":18,"created_at":"2023-04-20T21:52:45.859Z","updated_at":"2024-07-18T16:02:07.497Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/yujiantang/","self_intro":"Yujian Tang is a Developer Advocate at Zilliz. He has a background as a software engineer working on AutoML at Amazon. Yujian studied Computer Science, Statistics, and Neuroscience with research papers published to conferences including IEEE Big Data. He enjoys drinking bubble tea, spending time with family, and being near water.","repost_to_medium":null,"repost_state":null,"meta_description":"Yujian Tang, Developer Advocate at Zilliz. ","locale":"en"}],"read_time":11,"localizations":[{"id":1334,"locale":"ja-JP","published_at":"2023-08-21T01:36:21.468Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Comparing_Different_Vector_Embeddings_e7ca1e4e5d.png","belong":"blog","authorNames":["Yujian Tang"]},{"id":"blog-233","title":"How to Build an AI Chatbot with Milvus and Towhee","image":{"id":1728,"url":"https://assets.zilliz.com/how_to_build_a_chatbot_with_Milvus_and_Towhee_ffec2c1a62.jpeg"},"display_time":"Aug 18, 2023","deploy_time":"2023-08-18T04:00:00.000Z","url":"how-to-build-ai-chatbot-with-Milvus-and-Towhee","abstract":"Learn how to build a simple chatbot with Python using Milvus and Towhee.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":74,"name":"Eric Goebelbecker","author_tags":"Infrastructure Engineer","published_at":"2023-07-07T10:35:40.517Z","created_by":18,"updated_by":18,"created_at":"2023-07-07T10:35:37.360Z","updated_at":"2023-07-07T10:35:40.530Z","home_page":"Website","home_page_link":"https://ericgoebelbecker.com/","self_intro":"Infrastructure Engineer","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":11,"localizations":[{"id":1127,"locale":"ja-JP","published_at":"2023-08-18T08:59:10.029Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/how_to_build_a_chatbot_with_Milvus_and_Towhee_ffec2c1a62.jpeg","belong":"blog","authorNames":["Eric Goebelbecker"]},{"id":"blog-232","title":"Building LLM Augmented Apps with Zilliz Cloud ","image":{"id":1716,"url":"https://assets.zilliz.com/Aug_14_Building_LLM_Augmented_Apps_with_Zilliz_Cloud_60bc7ed947.png"},"display_time":"Aug 17, 2023","deploy_time":"2023-08-21T03:30:00.000Z","url":"Build-LLM-Augmented-Apps-with-Zilliz-Cloud","abstract":"The synergy of Zilliz Cloud and GPTCache creates an environment where AI applications can generate more accurate, timely, cost-efficient, and performant responses, significantly improving the user experience. ","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":76,"name":"Steffi Li","author_tags":"Director of Product Marketing","published_at":"2023-07-13T17:18:42.023Z","created_by":18,"updated_by":18,"created_at":"2023-07-13T17:16:54.449Z","updated_at":"2023-07-13T17:18:42.070Z","home_page":null,"home_page_link":null,"self_intro":"Steffi is the Director of Product Marketing at Zilliz, with prior experience leading the GTM strategies for open-source data technologies such as Apache Kafka and Apache Airflow. Passionate about travel, yoga, and non-fiction reading, she brings a balanced and enriched worldview to her professional pursuits.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":6,"localizations":[{"id":1260,"locale":"ja-JP","published_at":"2023-08-21T03:14:15.372Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Aug_14_Building_LLM_Augmented_Apps_with_Zilliz_Cloud_60bc7ed947.png","belong":"blog","authorNames":["Steffi Li"]},{"id":"blog-231","title":"Using AI to Find Your Celebrity Stylist (Part II)","image":{"id":1702,"url":"https://assets.zilliz.com/Aug_11_Using_AI_to_Find_Your_Celebrity_Stylist_16fd5d3f74.png"},"display_time":"Aug 11, 2023","deploy_time":"2023-08-11T04:00:00.000Z","url":"use-ai-find-your-celebrity-style-two","abstract":"Using Hugging Face models and a powerful vector database like Milvus to perform image similarity searches and find celebrity fashion styles that match your own. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":41,"name":"Yujian Tang","author_tags":"Developer Advocate at Zilliz","published_at":"2023-04-20T21:52:47.479Z","created_by":18,"updated_by":18,"created_at":"2023-04-20T21:52:45.859Z","updated_at":"2024-07-18T16:02:07.497Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/yujiantang/","self_intro":"Yujian Tang is a Developer Advocate at Zilliz. He has a background as a software engineer working on AutoML at Amazon. Yujian studied Computer Science, Statistics, and Neuroscience with research papers published to conferences including IEEE Big Data. He enjoys drinking bubble tea, spending time with family, and being near water.","repost_to_medium":null,"repost_state":null,"meta_description":"Yujian Tang, Developer Advocate at Zilliz. ","locale":"en"}],"read_time":11,"localizations":[{"id":1020,"locale":"ja-JP","published_at":"2023-08-11T12:11:52.229Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Aug_11_Using_AI_to_Find_Your_Celebrity_Stylist_16fd5d3f74.png","belong":"blog","authorNames":["Yujian Tang"]},{"id":"blog-230","title":"Using AI to Find Your Celebrity Stylist (Part I)","image":{"id":1691,"url":"https://assets.zilliz.com/Using_AI_to_Find_Your_Celebrity_Stylist_56561aaf32.png"},"display_time":"Aug 08, 2023","deploy_time":null,"url":"using-ai-to-find-your-celebrity-stylist","abstract":"How to generate image segmentation for fashion items, add your image data to Milvus, and which celebrity your dress is most like. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":41,"name":"Yujian Tang","author_tags":"Developer Advocate at Zilliz","published_at":"2023-04-20T21:52:47.479Z","created_by":18,"updated_by":18,"created_at":"2023-04-20T21:52:45.859Z","updated_at":"2024-07-18T16:02:07.497Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/yujiantang/","self_intro":"Yujian Tang is a Developer Advocate at Zilliz. He has a background as a software engineer working on AutoML at Amazon. Yujian studied Computer Science, Statistics, and Neuroscience with research papers published to conferences including IEEE Big Data. He enjoys drinking bubble tea, spending time with family, and being near water.","repost_to_medium":null,"repost_state":null,"meta_description":"Yujian Tang, Developer Advocate at Zilliz. ","locale":"en"}],"read_time":12,"localizations":[{"id":1184,"locale":"ja-JP","published_at":"2023-08-08T16:36:20.159Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Using_AI_to_Find_Your_Celebrity_Stylist_56561aaf32.png","belong":"blog","authorNames":["Yujian Tang"]},{"id":"blog-229","title":"Zilliz Cloud Expands to AWS and GCP Singapore","image":{"id":1689,"url":"https://assets.zilliz.com/Zilliz_Cloud_Expands_to_AWS_and_GCP_Singapore_d2229fc1b0.png"},"display_time":"Aug 07, 2023","deploy_time":"2023-08-07T14:50:00.000Z","url":"zilliz-cloud-expands-to-aws-and-gcp-singapore","abstract":"The expansion of Zilliz Cloud to AWS and GCP Singapore regions provides our customers greater flexibility to suit their needs and unprecedented access. \n","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":76,"name":"Steffi Li","author_tags":"Director of Product Marketing","published_at":"2023-07-13T17:18:42.023Z","created_by":18,"updated_by":18,"created_at":"2023-07-13T17:16:54.449Z","updated_at":"2023-07-13T17:18:42.070Z","home_page":null,"home_page_link":null,"self_intro":"Steffi is the Director of Product Marketing at Zilliz, with prior experience leading the GTM strategies for open-source data technologies such as Apache Kafka and Apache Airflow. Passionate about travel, yoga, and non-fiction reading, she brings a balanced and enriched worldview to her professional pursuits.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":1,"localizations":[{"id":1307,"locale":"ja-JP","published_at":"2023-08-07T07:14:27.260Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Zilliz_Cloud_Expands_to_AWS_and_GCP_Singapore_d2229fc1b0.png","belong":"blog","authorNames":["Steffi Li"]},{"id":"blog-228","title":"Retrieval Augmented Generation with Citations","image":{"id":1688,"url":"https://assets.zilliz.com/Retrieval_Augmented_Generation_with_Citations_d8f59bb67a.png"},"display_time":"Aug 04, 2023","deploy_time":null,"url":"retrieval-augmented-generation-with-citations","abstract":"A look at why it’s important to include citations and how you can get citations from a high level.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":41,"name":"Yujian Tang","author_tags":"Developer Advocate at Zilliz","published_at":"2023-04-20T21:52:47.479Z","created_by":18,"updated_by":18,"created_at":"2023-04-20T21:52:45.859Z","updated_at":"2024-07-18T16:02:07.497Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/yujiantang/","self_intro":"Yujian Tang is a Developer Advocate at Zilliz. He has a background as a software engineer working on AutoML at Amazon. Yujian studied Computer Science, Statistics, and Neuroscience with research papers published to conferences including IEEE Big Data. He enjoys drinking bubble tea, spending time with family, and being near water.","repost_to_medium":null,"repost_state":null,"meta_description":"Yujian Tang, Developer Advocate at Zilliz. ","locale":"en"}],"read_time":5,"localizations":[{"id":1379,"locale":"ja-JP","published_at":"2023-08-04T13:32:01.553Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Retrieval_Augmented_Generation_with_Citations_d8f59bb67a.png","belong":"blog","authorNames":["Yujian Tang"]},{"id":"blog-227","title":"What Is a Real Vector Database?","image":{"id":1684,"url":"https://assets.zilliz.com/What_is_a_real_vector_database_509f2f55fe.png"},"display_time":"Aug 03, 2023","deploy_time":null,"url":"what-is-a-real-vector-database","abstract":"What sets vector databases apart, and how to select the right one for your project","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":45,"name":"Fendy Feng","author_tags":"Technical Marketing Writer","published_at":"2023-05-16T01:36:15.102Z","created_by":18,"updated_by":18,"created_at":"2023-05-16T00:04:12.065Z","updated_at":"2024-04-25T08:37:19.712Z","home_page":"GitHub","home_page_link":"https://www.linkedin.com/in/fendy311/","self_intro":"Fendy Feng is the Technical Marketing Writer at Zilliz. She has extensive experience developing and enhancing the impact of open-source projects in various global markets by producing high-quality, tailored content. Before joining Zilliz, Fendy worked as a Content Strategist at PingCAP, a fast-growing E-Series startup renowned for its open-source distributed SQL database.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":5,"localizations":[{"id":1169,"locale":"ja-JP","published_at":"2023-08-03T16:39:02.578Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/What_is_a_real_vector_database_509f2f55fe.png","belong":"blog","authorNames":["Fendy Feng"]},{"id":"blog-226","title":"Zilliz Cloud: a Fully-Managed Vector Database That Minimizes Users’ Costs for Building AI Apps","image":{"id":1683,"url":"https://assets.zilliz.com/zillizcloud_fully_managed_vector_database_minimize_usage_costs_dad4f3e1e6.jpeg"},"display_time":"Aug 01, 2023","deploy_time":"2023-08-02T04:00:00.000Z","url":"zilliz-cloud-fully-managed-vector-database-minimizes-user-costs-for-building-ai-apps","abstract":"Zilliz Cloud makes vector search accessible to everyone by minimizing the overall usage costs for building AI apps.","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":34,"name":"James Luan","author_tags":"VP of Engineering at Zilliz","published_at":"2022-05-18T03:15:15.255Z","created_by":18,"updated_by":18,"created_at":"2022-05-18T03:14:35.112Z","updated_at":"2024-01-12T21:01:29.192Z","home_page":"GitHub","home_page_link":"https://github.com/xiaofan-luan","self_intro":"James Luan is the VP of Engineering at Zilliz. With a master's degree in computer engineering from Cornell University, he has extensive experience as a Database Engineer at Oracle, Hedvig, and Alibaba Cloud. James played a crucial role in developing HBase, Alibaba Cloud's open-source database, and Lindorm, a self-developed NoSQL database. He is also a respected member of the Technical Advisory Committee of LF AI \u0026 Data Foundation, contributing his expertise to shaping the future of AI and data technologies.\n","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":4,"localizations":[{"id":1342,"locale":"ja-JP","published_at":"2023-08-02T12:53:55.786Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/zillizcloud_fully_managed_vector_database_minimize_usage_costs_dad4f3e1e6.jpeg","belong":"blog","authorNames":["James Luan"]},{"id":"blog-225","title":"Getting Started With the Milvus JavaScript Client","image":{"id":1674,"url":"https://assets.zilliz.com/Getting_Started_With_the_Milvus_Javascript_Client_a68210694d.png"},"display_time":"Jul 28, 2023","deploy_time":null,"url":"getting-started-with-the-milvus-javascript-client","abstract":"A hands-on tutorial with all you need to add vector search capabilities to your web apps using Milvus JavaScript Client. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":47,"name":"Eric Goebelbecker","author_tags":"DevRel","published_at":"2023-05-18T12:46:35.866Z","created_by":18,"updated_by":18,"created_at":"2023-05-18T12:46:32.321Z","updated_at":"2023-05-18T12:47:07.096Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/ericgoebelbecker/","self_intro":"Eric Goebelbecker has worked in the financial markets in New York City for 25 years, developing infrastructure for market data and financial information exchange (FIX) protocol networks. He loves to talk about what makes teams effective (or not so effective!).","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":8,"localizations":[{"id":1311,"locale":"ja-JP","published_at":"2023-07-28T13:54:04.654Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Getting_Started_With_the_Milvus_Javascript_Client_a68210694d.png","belong":"blog","authorNames":["Eric Goebelbecker"]},{"id":"blog-224","title":"Breaking Barriers: Democratizing Access to Vector Databases for All ","image":{"id":1673,"url":"https://assets.zilliz.com/Why_Should_We_Democratize_Vector_Databases_6cc31060c4.png"},"display_time":"Jul 27, 2023","deploy_time":"2023-07-27T14:50:00.000Z","url":"breaking-barriers-democratizing-access-vector-databases-for-all","abstract":"A look at the benefits of this critical infrastructure for AI, why democratizing them is crucial, and how to make them accessible to everyone.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":45,"name":"Fendy Feng","author_tags":"Technical Marketing Writer","published_at":"2023-05-16T01:36:15.102Z","created_by":18,"updated_by":18,"created_at":"2023-05-16T00:04:12.065Z","updated_at":"2024-04-25T08:37:19.712Z","home_page":"GitHub","home_page_link":"https://www.linkedin.com/in/fendy311/","self_intro":"Fendy Feng is the Technical Marketing Writer at Zilliz. She has extensive experience developing and enhancing the impact of open-source projects in various global markets by producing high-quality, tailored content. Before joining Zilliz, Fendy worked as a Content Strategist at PingCAP, a fast-growing E-Series startup renowned for its open-source distributed SQL database.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":6,"localizations":[{"id":1172,"locale":"ja-JP","published_at":"2023-07-27T06:33:54.478Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Why_Should_We_Democratize_Vector_Databases_6cc31060c4.png","belong":"blog","authorNames":["Fendy Feng"]},{"id":"blog-223","title":"Yujian Tang: Why I Joined Zilliz as Developer Advocate","image":{"id":1672,"url":"https://assets.zilliz.com/Why_I_joined_Zilliz_Yujian_0d92eb74fa.png"},"display_time":"Jul 26, 2023","deploy_time":null,"url":"yujian-tang-why-i-joined-zilliz-as-developer-advocate","abstract":"Choosing to join Zilliz was an easy decision for me. As I went through the interview process, it became clear that Zilliz was my top choice.","tags":[{"id":4,"name":"Company","published_at":"2021-01-21T02:28:23.551Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:20.676Z","updated_at":"2021-01-21T02:28:23.824Z","locale":"en"}],"authors":[{"id":41,"name":"Yujian Tang","author_tags":"Developer Advocate at Zilliz","published_at":"2023-04-20T21:52:47.479Z","created_by":18,"updated_by":18,"created_at":"2023-04-20T21:52:45.859Z","updated_at":"2024-07-18T16:02:07.497Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/yujiantang/","self_intro":"Yujian Tang is a Developer Advocate at Zilliz. He has a background as a software engineer working on AutoML at Amazon. Yujian studied Computer Science, Statistics, and Neuroscience with research papers published to conferences including IEEE Big Data. He enjoys drinking bubble tea, spending time with family, and being near water.","repost_to_medium":null,"repost_state":null,"meta_description":"Yujian Tang, Developer Advocate at Zilliz. ","locale":"en"}],"read_time":3,"localizations":[{"id":997,"locale":"ja-JP","published_at":"2023-07-26T15:00:50.502Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Why_I_joined_Zilliz_Yujian_0d92eb74fa.png","belong":"blog","authorNames":["Yujian Tang"]},{"id":"blog-222","title":"Getting Started with the Zilliz REST API","image":{"id":1562,"url":"https://assets.zilliz.com/L_Lama_Index_ef222f85da.png"},"display_time":"Jul 25, 2023","deploy_time":null,"url":"getting-started-zilliz-rest-api","abstract":"Learn how to create a Milvus cluster using Zilliz Cloud and then query it using the Zilliz REST API.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":47,"name":"Eric Goebelbecker","author_tags":"DevRel","published_at":"2023-05-18T12:46:35.866Z","created_by":18,"updated_by":18,"created_at":"2023-05-18T12:46:32.321Z","updated_at":"2023-05-18T12:47:07.096Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/ericgoebelbecker/","self_intro":"Eric Goebelbecker has worked in the financial markets in New York City for 25 years, developing infrastructure for market data and financial information exchange (FIX) protocol networks. He loves to talk about what makes teams effective (or not so effective!).","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":8,"localizations":[{"id":1385,"locale":"ja-JP","published_at":"2023-07-25T13:48:07.825Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/L_Lama_Index_ef222f85da.png","belong":"blog","authorNames":["Eric Goebelbecker"]},{"id":"blog-221","title":"Zilliz Cloud: Igniting Vector Searching with Rocket-Like Speed","image":{"id":1590,"url":"https://assets.zilliz.com/Rocket_Like_Zilliz_Cloud_a54ca79ac8.png"},"display_time":"Jul 19, 2023","deploy_time":"2023-07-19T04:00:00.000Z","url":"Zilliz-cloud-igniting-vector-search-with-rocket-like-speed","abstract":"Zilliz Cloud easily outperforms other vector databases regarding vector searching speed. ","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":70,"name":"Li Liu","author_tags":"Principal Engineer","published_at":"2023-06-15T05:16:42.032Z","created_by":18,"updated_by":18,"created_at":"2023-06-15T05:15:15.087Z","updated_at":"2024-07-18T15:59:40.729Z","home_page":"GitHub","home_page_link":"https://github.com/liliu-z","self_intro":"Li Liu is the Principal Engineer at Zilliz, leading the vector searching research and development. Before joining Zilliz, he was a Senior Engineer at Meta, designing and shaping numerous advertising stream data frameworks. With a Master's degree from Carnegie Mellon University, he boasts extensive experience in databases and big data. Li Liu's expertise in technology and innovation continues to drive advancements in vector searching, leaving a lasting impact on the field.\n","repost_to_medium":null,"repost_state":null,"meta_description":"Li Liu is the Principal Engineer at Zilliz, leading the vector searching research and development.","locale":"en"}],"read_time":4,"localizations":[{"id":858,"locale":"ja-JP","published_at":"2023-07-19T14:17:39.511Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Rocket_Like_Zilliz_Cloud_a54ca79ac8.png","belong":"blog","authorNames":["Li Liu"]},{"id":"blog-220","title":"Frank Liu: Why I Joined a Vector Database Company","image":{"id":1581,"url":"https://assets.zilliz.com/Why_I_joined_Zilliz_Frank_Liu_53b201cf8c.png"},"display_time":"Jul 18, 2023","deploy_time":null,"url":"frank-liu-why-i-joined-vector-database-company","abstract":"My stories with machine learning, vector searching, and Zilliz","tags":[{"id":4,"name":"Company","published_at":"2021-01-21T02:28:23.551Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:20.676Z","updated_at":"2021-01-21T02:28:23.824Z","locale":"en"}],"authors":[{"id":1,"name":"Zilliz","author_tags":"Vector database","published_at":"2021-12-14T06:36:41.397Z","created_by":18,"updated_by":18,"created_at":"2021-12-14T06:28:27.154Z","updated_at":"2023-04-11T16:54:05.275Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":4,"localizations":[{"id":1296,"locale":"ja-JP","published_at":"2023-07-18T15:04:18.788Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Why_I_joined_Zilliz_Frank_Liu_53b201cf8c.png","belong":"blog","authorNames":["Zilliz"]},{"id":"learn-67","title":"Choosing the Right Vector Index for Your Project","image":{"id":1533,"url":"https://assets.zilliz.com/Choosing_the_Right_Vector_Index_for_Your_Project_27998e8ec6.png"},"display_time":"Jul 17, 2023","url":"choosing-right-vector-index-for-your-project","abstract":"Understanding in-memory vector search algorithms, indexing strategies, and guidelines on choosing the right vector index for your project.","tags":[{"id":39,"name":"VectorDB 101","published_at":"2022-09-30T05:56:34.554Z","created_by":18,"updated_by":18,"created_at":"2022-09-30T05:56:31.633Z","updated_at":"2024-07-10T07:12:04.155Z","locale":"en"}],"authors":[{"id":3,"name":"Frank Liu","author_tags":"Director of Operations \u0026 ML Architect at Zilliz","published_at":"2021-12-23T11:08:08.015Z","created_by":18,"updated_by":18,"created_at":"2021-12-23T10:40:59.821Z","updated_at":"2023-04-21T22:30:10.416Z","home_page":"GitHub","home_page_link":"https://github.com/fzliu","self_intro":"Frank Liu is the Director of Operations \u0026 ML Architect at Zilliz, where he serves as a maintainer for the Towhee open-source project. Prior to Zilliz, Frank co-founded Orion Innovations, an ML-powered indoor positioning startup based in Shanghai and worked as an ML engineer at Yahoo in San Francisco. In his free time, Frank enjoys playing chess, swimming, and powerlifting. Frank holds MS and BS degrees in Electrical Engineering from Stanford University. ","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":6,"localizations":[{"id":351,"locale":"ja-JP","published_at":"2023-07-17T05:43:40.185Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Choosing_the_Right_Vector_Index_for_Your_Project_27998e8ec6.png","belong":"learn","authorNames":["Frank Liu"]},{"id":"blog-219","title":"What's New in Milvus 2.2.10 and 2.2.11","image":{"id":1540,"url":"https://assets.zilliz.com/Milvus_2_2_10_2_2_11_3a0e0f7732.png"},"display_time":"Jul 14, 2023","deploy_time":"2023-07-14T14:50:00.000Z","url":"whats-new-in-milvus-version-2-2-10-and-2-2-11","abstract":"Milvus versions 2.2.10 and 2.2.11 come loaded with numerous enhancements that significantly improve the product’s functionality and user experience. ","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":76,"name":"Steffi Li","author_tags":"Director of Product Marketing","published_at":"2023-07-13T17:18:42.023Z","created_by":18,"updated_by":18,"created_at":"2023-07-13T17:16:54.449Z","updated_at":"2023-07-13T17:18:42.070Z","home_page":null,"home_page_link":null,"self_intro":"Steffi is the Director of Product Marketing at Zilliz, with prior experience leading the GTM strategies for open-source data technologies such as Apache Kafka and Apache Airflow. Passionate about travel, yoga, and non-fiction reading, she brings a balanced and enriched worldview to her professional pursuits.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":1,"localizations":[{"id":1335,"locale":"ja-JP","published_at":"2023-07-13T20:36:41.923Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Milvus_2_2_10_2_2_11_3a0e0f7732.png","belong":"blog","authorNames":["Steffi Li"]},{"id":"blog-218","title":"Democratizing Vector Databases: Empowering Access \u0026 Equality","image":{"id":1539,"url":"https://assets.zilliz.com/Democratizing_Vector_Databases_Empowering_Access_and_Equality_461316708b.png"},"display_time":"Jul 12, 2023","deploy_time":"2023-07-12T14:50:00.000Z","url":"democratizing-vector-databases-empowering-access-equality","abstract":"Uncover the true meaning behind democratizing a vector database and its profound implications to promote accessibility, equality, and inclusivity.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":41,"name":"Yujian Tang","author_tags":"Developer Advocate at Zilliz","published_at":"2023-04-20T21:52:47.479Z","created_by":18,"updated_by":18,"created_at":"2023-04-20T21:52:45.859Z","updated_at":"2024-07-18T16:02:07.497Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/yujiantang/","self_intro":"Yujian Tang is a Developer Advocate at Zilliz. He has a background as a software engineer working on AutoML at Amazon. Yujian studied Computer Science, Statistics, and Neuroscience with research papers published to conferences including IEEE Big Data. He enjoys drinking bubble tea, spending time with family, and being near water.","repost_to_medium":null,"repost_state":null,"meta_description":"Yujian Tang, Developer Advocate at Zilliz. ","locale":"en"}],"read_time":5,"localizations":[{"id":1372,"locale":"ja-JP","published_at":"2023-07-12T05:45:50.000Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Democratizing_Vector_Databases_Empowering_Access_and_Equality_461316708b.png","belong":"blog","authorNames":["Yujian Tang"]},{"id":"blog-216","title":"Filip Haltmayer: Why I Joined Zilliz as Software Engineer","image":{"id":6410,"url":"https://assets.zilliz.com/July_10_Why_I_joined_Zilliz_a93e1381e6.png"},"display_time":"Jul 10, 2023","deploy_time":"2023-07-10T18:30:00.000Z","url":"filip-haltmayer-why-i-joined-zilliz-as-software-engineer","abstract":"My passion and educational background in software engineering and interest in machine learning made joining Zilliz the perfect match for my career aspirations. ","tags":[{"id":4,"name":"Company","published_at":"2021-01-21T02:28:23.551Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:20.676Z","updated_at":"2021-01-21T02:28:23.824Z","locale":"en"}],"authors":[{"id":43,"name":"Filip Haltmayer","author_tags":"Software Engineer, Zilliz","published_at":"2023-04-25T19:40:57.629Z","created_by":18,"updated_by":18,"created_at":"2023-04-25T19:11:31.215Z","updated_at":"2023-04-25T22:54:51.135Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/filiphaltmayer/","self_intro":"Filip Haltmayer is a Software Engineer at Zilliz working in both software and community development. His contributions mainly revolve around the Milvus and Towhee projects, helping develop both applications and helping grow their respective user bases through client interaction, integrations, and technical talks.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":3,"localizations":[{"id":1380,"locale":"ja-JP","published_at":"2023-07-10T23:14:42.480Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/July_10_Why_I_joined_Zilliz_a93e1381e6.png","belong":"blog","authorNames":["Filip Haltmayer"]},{"id":"blog-215","title":"Getting Started with PyMilvus","image":{"id":6409,"url":"https://assets.zilliz.com/July_07_Getting_Started_with_Py_Milvus_470efe33e0.png"},"display_time":"Jul 07, 2023","deploy_time":"2023-07-07T04:00:00.000Z","url":"get-started-with-pymilvus","abstract":"This tutorial will guide you in installing and setting up a development environment for using Milvus and PyMilvus.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":47,"name":"Eric Goebelbecker","author_tags":"DevRel","published_at":"2023-05-18T12:46:35.866Z","created_by":18,"updated_by":18,"created_at":"2023-05-18T12:46:32.321Z","updated_at":"2023-05-18T12:47:07.096Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/ericgoebelbecker/","self_intro":"Eric Goebelbecker has worked in the financial markets in New York City for 25 years, developing infrastructure for market data and financial information exchange (FIX) protocol networks. He loves to talk about what makes teams effective (or not so effective!).","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":8,"localizations":[{"id":1031,"locale":"ja-JP","published_at":"2023-07-07T10:43:30.329Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/July_07_Getting_Started_with_Py_Milvus_470efe33e0.png","belong":"blog","authorNames":["Eric Goebelbecker"]},{"id":"blog-210","title":"Setting Up With Facebook AI Similarity Search (FAISS)","image":{"id":6408,"url":"https://assets.zilliz.com/June_04_Setting_Up_With_Facebook_AI_Similarity_Search_f403608c81.png"},"display_time":"Jul 04, 2023","deploy_time":"2023-07-04T04:00:00.000Z","url":"set-up-with-facebook-ai-similarity-search-faiss","abstract":"Here's your guide to setting up FAISS, getting it up and running, and demonstrating its power through a sample search program.","tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":18,"updated_by":18,"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en"}],"authors":[{"id":73,"name":"Keshav Malik","author_tags":"Information Security Engineer at Hitsubscribe ","published_at":"2023-07-04T07:36:38.815Z","created_by":18,"updated_by":18,"created_at":"2023-07-04T07:34:25.174Z","updated_at":"2023-07-04T07:36:38.831Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/keshav-malik/","self_intro":"Keshav Malik is a highly skilled and enthusiastic security engineer. He has a passion for automation, hacking, and exploring different tools and technologies. With a love for finding innovative solutions to complex problems, Keshav is constantly seeking new opportunities to grow and improve as a professional. He is dedicated to staying ahead of the curve and is always on the lookout for the latest and greatest tools and technologies. ","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":11,"localizations":[{"id":1041,"locale":"ja-JP","published_at":"2023-07-04T07:38:22.109Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/June_04_Setting_Up_With_Facebook_AI_Similarity_Search_f403608c81.png","belong":"blog","authorNames":["Keshav Malik"]},{"id":"blog-214","title":"Webinar Recap: Retrieval Techniques for Accessing the Most Relevant Context for LLM Applications","image":{"id":6407,"url":"https://assets.zilliz.com/Jul_03_Building_Long_Term_Memory_for_LLM_Applications_with_Different_Retrieval_Techniques_e9981b9689.png"},"display_time":"Jul 03, 2023","deploy_time":null,"url":"webinar-recap-retrieval-techniques-accessing-most-relevant-context-llm-applications","abstract":"Explore how we can leverage various retrieval techniques to provide memory to LLM applications.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":45,"name":"Fendy Feng","author_tags":"Technical Marketing Writer","published_at":"2023-05-16T01:36:15.102Z","created_by":18,"updated_by":18,"created_at":"2023-05-16T00:04:12.065Z","updated_at":"2024-04-25T08:37:19.712Z","home_page":"GitHub","home_page_link":"https://www.linkedin.com/in/fendy311/","self_intro":"Fendy Feng is the Technical Marketing Writer at Zilliz. She has extensive experience developing and enhancing the impact of open-source projects in various global markets by producing high-quality, tailored content. Before joining Zilliz, Fendy worked as a Content Strategist at PingCAP, a fast-growing E-Series startup renowned for its open-source distributed SQL database.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":7,"localizations":[{"id":1166,"locale":"ja-JP","published_at":"2023-07-04T12:44:44.970Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Jul_03_Building_Long_Term_Memory_for_LLM_Applications_with_Different_Retrieval_Techniques_e9981b9689.png","belong":"blog","authorNames":["Fendy Feng"]},{"id":"blog-207","title":"Persistent Vector Storage for LlamaIndex","image":{"id":6405,"url":"https://assets.zilliz.com/June_27_Persistent_Vector_Storage_for_Llama_Index_a2fe2f2d05.png"},"display_time":"Jun 27, 2023","deploy_time":"2023-06-27T14:50:00.000Z","url":"persistent-vector-storage-for-llamaIndex","abstract":" Discover the benefits of Persistent Vector Storage and optimize your data storage strategy. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":41,"name":"Yujian Tang","author_tags":"Developer Advocate at Zilliz","published_at":"2023-04-20T21:52:47.479Z","created_by":18,"updated_by":18,"created_at":"2023-04-20T21:52:45.859Z","updated_at":"2024-07-18T16:02:07.497Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/yujiantang/","self_intro":"Yujian Tang is a Developer Advocate at Zilliz. He has a background as a software engineer working on AutoML at Amazon. Yujian studied Computer Science, Statistics, and Neuroscience with research papers published to conferences including IEEE Big Data. He enjoys drinking bubble tea, spending time with family, and being near water.","repost_to_medium":null,"repost_state":null,"meta_description":"Yujian Tang, Developer Advocate at Zilliz. ","locale":"en"}],"read_time":5,"localizations":[{"id":1226,"locale":"ja-JP","published_at":"2023-06-27T05:03:27.603Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/June_27_Persistent_Vector_Storage_for_Llama_Index_a2fe2f2d05.png","belong":"blog","authorNames":["Yujian Tang"]},{"id":"blog-206","title":"Enhancing ChatGPT's Intelligence and Efficiency: The Power of LangChain and Milvus","image":{"id":1508,"url":"https://assets.zilliz.com/Enhancing_Chat_GPT_s_Intelligence_Blog_Cover_cab1e69939.png"},"display_time":"Jun 26, 2023","deploy_time":"2023-06-26T14:50:00.000Z","url":"enhancing-chatgpt-intelligence-efficiency-langchain-milvus","abstract":"Learn how LangChain and Milvus can be used to improve the performance and memory of LLMs.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":72,"name":"Silvia Chen","author_tags":"Software Engineer","published_at":"2023-06-26T06:10:36.495Z","created_by":18,"updated_by":18,"created_at":"2023-06-26T06:10:34.755Z","updated_at":"2024-07-18T16:00:04.960Z","home_page":"GitHub","home_page_link":"https://github.com/shiyu22","self_intro":"Software Engineer","repost_to_medium":null,"repost_state":null,"meta_description":"Silvia Chen, Software Engineer at Zilliz","locale":"en"}],"read_time":10,"localizations":[{"id":1359,"locale":"ja-JP","published_at":"2023-06-26T13:49:15.877Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Enhancing_Chat_GPT_s_Intelligence_Blog_Cover_cab1e69939.png","belong":"blog","authorNames":["Silvia Chen"]},{"id":"blog-202","title":"The Philosophy Behind Zilliz Cloud’s Product Experience Optimization ","image":{"id":6404,"url":"https://assets.zilliz.com/June_20_Highlights_of_Zilliz_Cloud_s_Product_Design_Optimization_aad3ff43f5.png"},"display_time":"Jun 20, 2023","deploy_time":"2023-06-20T04:00:00.000Z","url":"philosophy-behind-zilliz-cloud-product-experience-optimization.md","abstract":"Discover How We Improved the Product Experience of Zilliz Cloud and Our Motivation Behind It","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":69,"name":"Koko Lv","author_tags":"Design Lead","published_at":"2023-06-14T03:27:04.616Z","created_by":18,"updated_by":18,"created_at":"2023-06-14T03:27:03.009Z","updated_at":"2023-06-14T03:27:04.636Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/lvling/","self_intro":"Design Lead at Zilliz","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":4,"localizations":[{"id":1211,"locale":"ja-JP","published_at":"2023-06-20T07:20:04.727Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/June_20_Highlights_of_Zilliz_Cloud_s_Product_Design_Optimization_aad3ff43f5.png","belong":"blog","authorNames":["Koko Lv"]},{"id":"blog-203","title":"Query Multiple Documents Using LlamaIndex, LangChain, and Milvus","image":{"id":6403,"url":"https://assets.zilliz.com/June_19_Combine_and_Query_Multiple_Documents_with_LLM_d4a78c6c5a.png"},"display_time":"Jun 19, 2023","deploy_time":"2023-06-19T14:50:00.000Z","url":"combine-and-query-multiple-documents-with-llm","abstract":"Unlock the power of LLM: Combine and query multiple documents with LlamaIndex, LangChain, and Milvus Vector Database","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":41,"name":"Yujian Tang","author_tags":"Developer Advocate at Zilliz","published_at":"2023-04-20T21:52:47.479Z","created_by":18,"updated_by":18,"created_at":"2023-04-20T21:52:45.859Z","updated_at":"2024-07-18T16:02:07.497Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/yujiantang/","self_intro":"Yujian Tang is a Developer Advocate at Zilliz. He has a background as a software engineer working on AutoML at Amazon. Yujian studied Computer Science, Statistics, and Neuroscience with research papers published to conferences including IEEE Big Data. He enjoys drinking bubble tea, spending time with family, and being near water.","repost_to_medium":null,"repost_state":null,"meta_description":"Yujian Tang, Developer Advocate at Zilliz. ","locale":"en"}],"read_time":9,"localizations":[{"id":1383,"locale":"ja-JP","published_at":"2023-06-19T03:48:21.136Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/June_19_Combine_and_Query_Multiple_Documents_with_LLM_d4a78c6c5a.png","belong":"blog","authorNames":["Yujian Tang"]},{"id":"blog-201","title":"Introducing an Open Source Vector Database Benchmark Tool for Choosing the Ideal Vector Database for Your Project","image":{"id":6401,"url":"https://assets.zilliz.com/June_16_Benchmarking_your_way_2a9b819c5b.png"},"display_time":"Jun 16, 2023","deploy_time":null,"url":"open-source-vector-database-benchmarking-your-way","abstract":"Introducing VectorDBBench, an open-source vector database benchmark tool for choosing the ideal vector database for your project.","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":70,"name":"Li Liu","author_tags":"Principal Engineer","published_at":"2023-06-15T05:16:42.032Z","created_by":18,"updated_by":18,"created_at":"2023-06-15T05:15:15.087Z","updated_at":"2024-07-18T15:59:40.729Z","home_page":"GitHub","home_page_link":"https://github.com/liliu-z","self_intro":"Li Liu is the Principal Engineer at Zilliz, leading the vector searching research and development. Before joining Zilliz, he was a Senior Engineer at Meta, designing and shaping numerous advertising stream data frameworks. With a Master's degree from Carnegie Mellon University, he boasts extensive experience in databases and big data. Li Liu's expertise in technology and innovation continues to drive advancements in vector searching, leaving a lasting impact on the field.\n","repost_to_medium":null,"repost_state":null,"meta_description":"Li Liu is the Principal Engineer at Zilliz, leading the vector searching research and development.","locale":"en"}],"read_time":5,"localizations":[{"id":1233,"locale":"ja-JP","published_at":"2023-06-16T23:07:05.408Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/June_16_Benchmarking_your_way_2a9b819c5b.png","belong":"blog","authorNames":["Li Liu"]},{"id":"blog-204","title":"Improved Team Collaboration with Zilliz Cloud’s New Organizations and Roles Feature","image":{"id":6402,"url":"https://assets.zilliz.com/June_16_Improved_Team_Collaboration_with_Zilliz_Cloud_s_New_Organizations_and_Roles_Feature_46500ef963.png"},"display_time":"Jun 16, 2023","deploy_time":"2023-06-20T04:00:00.000Z","url":"Zilliz-Cloud-Organizations-and-Roles-Feature","abstract":"Enables large organizations to easily manage team access, ensuring streamlined collaboration and optimal security and flexibility.","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":39,"name":"Sarah Tang","author_tags":"Senior Product Manager","published_at":"2023-04-12T03:08:03.943Z","created_by":18,"updated_by":18,"created_at":"2023-04-12T02:56:07.784Z","updated_at":"2023-04-12T03:11:53.050Z","home_page":"linkedin","home_page_link":"https://www.linkedin.com/in/xue-tang-070734169/","self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":4,"localizations":[{"id":978,"locale":"ja-JP","published_at":"2023-06-20T06:54:54.301Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/June_16_Improved_Team_Collaboration_with_Zilliz_Cloud_s_New_Organizations_and_Roles_Feature_46500ef963.png","belong":"blog","authorNames":["Sarah Tang"]},{"id":"blog-199","title":"Zilliz Cloud Latest Update: A Game-Changer Bringing Elite Performance within Reach of All Developers","image":{"id":6400,"url":"https://assets.zilliz.com/June_14_News_Elite_Performance_within_Reach_of_All_Developers_b3f10bf55b.png"},"display_time":"Jun 14, 2023","deploy_time":"2023-06-14T12:45:00.000Z","url":"zilliz-cloud-vector-db-for-all","abstract":"Zilliz Cloud has just released a game-changing update for developers looking to implement generative AI applications. ","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":68,"name":"Robert Guo","author_tags":"Director of Product Management","published_at":"2023-06-13T18:34:37.794Z","created_by":18,"updated_by":18,"created_at":"2023-06-08T17:01:36.444Z","updated_at":"2024-04-16T02:44:46.685Z","home_page":"GitHub","home_page_link":"https://github.com/GuoRentong","self_intro":"Robert Guo is a Partner and Director of Product Management at Zilliz and one of the architects behind Milvus, an open-source vector database revolutionizing AI data analysis. With a Ph.D. in Computer Software and Theory from Huazhong University of Science and Technology, he has presented influential work at prestigious conferences and journals, including SIGMOD, VLDB, USENIX ATC, ICS, DATE, and IEEE TPDS. Previously a key developer for Huawei's ModelArts platform, Robert is skilled at crafting efficient and scalable AI data solutions.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":4,"localizations":[{"id":1388,"locale":"ja-JP","published_at":"2023-06-13T18:34:50.901Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/June_14_News_Elite_Performance_within_Reach_of_All_Developers_b3f10bf55b.png","belong":"blog","authorNames":["Robert Guo"]},{"id":"blog-200","title":"Prompting in LangChain","image":{"id":6399,"url":"https://assets.zilliz.com/June_12_Prompting_in_Lang_Chain_841c67a002.png"},"display_time":"Jun 12, 2023","deploy_time":null,"url":"prompting-langchain","abstract":"Prompting is one of today's most popular and important tasks in AI app building. Learn how to use LangChain for more complex prompts.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":41,"name":"Yujian Tang","author_tags":"Developer Advocate at Zilliz","published_at":"2023-04-20T21:52:47.479Z","created_by":18,"updated_by":18,"created_at":"2023-04-20T21:52:45.859Z","updated_at":"2024-07-18T16:02:07.497Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/yujiantang/","self_intro":"Yujian Tang is a Developer Advocate at Zilliz. He has a background as a software engineer working on AutoML at Amazon. Yujian studied Computer Science, Statistics, and Neuroscience with research papers published to conferences including IEEE Big Data. He enjoys drinking bubble tea, spending time with family, and being near water.","repost_to_medium":null,"repost_state":null,"meta_description":"Yujian Tang, Developer Advocate at Zilliz. ","locale":"en"}],"read_time":7,"localizations":[{"id":1302,"locale":"ja-JP","published_at":"2023-06-12T14:33:16.176Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/June_12_Prompting_in_Lang_Chain_841c67a002.png","belong":"blog","authorNames":["Yujian Tang"]},{"id":"blog-166","title":"Auto GPT Explained: A Comprehensive Auto-GPT Guide For Your Unique Use Case","image":{"id":6398,"url":"https://assets.zilliz.com/Jun_08_How_to_Customize_Auto_GPT_for_Your_Unique_Use_Case_A_Comprehensive_Guide_47a1e5159f.png"},"display_time":"Jun 08, 2023","deploy_time":"2023-06-08T17:36:00.000Z","url":"how-to-customize-auto-gpt-for-unique-use-case","abstract":"In “Auto GPT Explained”, learn how to leverage and set up Auto GPT to supercharge your workflow and automate away mundane mistakes.","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":41,"name":"Yujian Tang","author_tags":"Developer Advocate at Zilliz","published_at":"2023-04-20T21:52:47.479Z","created_by":18,"updated_by":18,"created_at":"2023-04-20T21:52:45.859Z","updated_at":"2024-07-18T16:02:07.497Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/yujiantang/","self_intro":"Yujian Tang is a Developer Advocate at Zilliz. He has a background as a software engineer working on AutoML at Amazon. Yujian studied Computer Science, Statistics, and Neuroscience with research papers published to conferences including IEEE Big Data. He enjoys drinking bubble tea, spending time with family, and being near water.","repost_to_medium":null,"repost_state":null,"meta_description":"Yujian Tang, Developer Advocate at Zilliz. ","locale":"en"}],"read_time":8,"localizations":[{"id":1009,"locale":"ja-JP","published_at":"2023-06-08T17:03:48.440Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Jun_08_How_to_Customize_Auto_GPT_for_Your_Unique_Use_Case_A_Comprehensive_Guide_47a1e5159f.png","belong":"blog","authorNames":["Yujian Tang"]},{"id":"blog-198","title":"What's New in Milvus version 2.2.9","image":{"id":1454,"url":"https://assets.zilliz.com/June_6_What_s_New_in_Milvus_2_2_9_42cffd460f.png"},"display_time":"Jun 06, 2023","deploy_time":null,"url":"new-milvus-2-2-9","abstract":"Look what the team added in the latest Milvus release! Dynamic Schema, JSON support, RBAC, and more!","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":36,"name":"Chris Churilo","author_tags":"VP of Marketing","published_at":"2023-04-11T16:51:05.002Z","created_by":18,"updated_by":53,"created_at":"2023-04-11T16:42:46.067Z","updated_at":"2025-01-16T22:35:53.011Z","home_page":"GitHub","home_page_link":"https://github.com/ChrisChurilo","self_intro":"Chris Churilo is the VP of Marketing \u0026 Community at Zilliz where she leads all community, developer relations, and marketing efforts. Prior to Zilliz, Chris was a founding member of the InfluxData’s go to market efforts and helped propel the time series database platform to dominance in the market. In earlier roles she defined and designed a SaaS monitoring solution at Centroid, and prior to that she was the VP of product management at iPass and was the LOB for several cloud services that required her to track the business and operational metrics and analytics to help identify and resolve issues.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":2,"localizations":[{"id":1322,"locale":"ja-JP","published_at":"2023-06-06T23:09:58.957Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/June_6_What_s_New_in_Milvus_2_2_9_42cffd460f.png","belong":"blog","authorNames":["Chris Churilo"]},{"id":"blog-197","title":"Get Ready for GPT-4 with GPTCache \u0026 Milvus, Save Big on Multimodal AI","image":{"id":1442,"url":"https://assets.zilliz.com/May_31_Get_Ready_for_GPT_4_with_GPT_Cache_and_Milvus_Save_Big_on_Multimodal_AI_20230531_060722_0e93060e99.png"},"display_time":"May 31, 2023","deploy_time":"2023-05-31T03:00:00.000Z","url":"Get-Ready-for-GPT-4-with-GPTCache-and-Milvus","abstract":"How to Save Big on Multimodal AI for a more seamless and powerful user experience in multimodal scenarios.","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":67,"name":"Jael Gu","author_tags":"Algorithm Engineer","published_at":"2023-05-31T02:50:25.394Z","created_by":18,"updated_by":18,"created_at":"2023-05-31T02:39:18.234Z","updated_at":"2024-07-18T15:56:18.435Z","home_page":"GitHub","home_page_link":"https://github.com/jaelgu","self_intro":"Algorithm Engineer at Zilliz ","repost_to_medium":null,"repost_state":null,"meta_description":"Jael Gu is an Algorithm Engineer at Zilliz.","locale":"en"}],"read_time":12,"localizations":[{"id":1278,"locale":"ja-JP","published_at":"2023-05-31T02:50:32.514Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/May_31_Get_Ready_for_GPT_4_with_GPT_Cache_and_Milvus_Save_Big_on_Multimodal_AI_20230531_060722_0e93060e99.png","belong":"blog","authorNames":["Jael Gu"]},{"id":"blog-167","title":"GPTCache, LangChain, Strong Alliance","image":{"id":1382,"url":"https://assets.zilliz.com/May_24_GPT_Cache_and_Lang_Chain_the_Powerful_Alliance_Supercharging_Natural_Language_Processing_4290b5bd9d.png"},"display_time":"May 25, 2023","deploy_time":"2023-05-23T04:00:00.000Z","url":"gptcache-langchain-strong-alliance","abstract":"Discover the power of GPTCache and LangChain and how these cutting-edge technologies join forces to revolutionize app development.","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":46,"name":"Sim Fu","author_tags":"Software Engineer","published_at":"2023-05-16T07:59:02.167Z","created_by":18,"updated_by":18,"created_at":"2023-05-16T07:59:00.534Z","updated_at":"2024-07-19T03:23:36.412Z","home_page":"GitHub","home_page_link":"https://github.com/SimFG","self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Sim Fu, Software Engineer at Zilliz","locale":"en"}],"read_time":3,"localizations":[{"id":1022,"locale":"ja-JP","published_at":"2023-05-25T07:00:30.136Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/May_24_GPT_Cache_and_Lang_Chain_the_Powerful_Alliance_Supercharging_Natural_Language_Processing_4290b5bd9d.png","belong":"blog","authorNames":["Sim Fu"]},{"id":"learn-40","title":"Approximate Nearest Neighbors Oh Yeah (Annoy)","image":{"id":6397,"url":"https://assets.zilliz.com/Mar_25_Vector_Database_101_Hierarchical_Navigable_Small_Worlds_HNSW_fcbdf88a1d.png"},"display_time":"May 25, 2023","url":"approximate-nearest-neighbor-oh-yeah-ANNOY","abstract":"Discover the capabilities of Annoy, an innovative algorithm revolutionizing approximate nearest neighbor searches for enhanced efficiency and precision.","tags":[{"id":39,"name":"VectorDB 101","published_at":"2022-09-30T05:56:34.554Z","created_by":18,"updated_by":18,"created_at":"2022-09-30T05:56:31.633Z","updated_at":"2024-07-10T07:12:04.155Z","locale":"en"}],"authors":[{"id":3,"name":"Frank Liu","author_tags":"Director of Operations \u0026 ML Architect at Zilliz","published_at":"2021-12-23T11:08:08.015Z","created_by":18,"updated_by":18,"created_at":"2021-12-23T10:40:59.821Z","updated_at":"2023-04-21T22:30:10.416Z","home_page":"GitHub","home_page_link":"https://github.com/fzliu","self_intro":"Frank Liu is the Director of Operations \u0026 ML Architect at Zilliz, where he serves as a maintainer for the Towhee open-source project. Prior to Zilliz, Frank co-founded Orion Innovations, an ML-powered indoor positioning startup based in Shanghai and worked as an ML engineer at Yahoo in San Francisco. In his free time, Frank enjoys playing chess, swimming, and powerlifting. Frank holds MS and BS degrees in Electrical Engineering from Stanford University. ","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":11,"localizations":[{"id":343,"locale":"ja-JP","published_at":"2023-05-27T12:09:24.955Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Mar_25_Vector_Database_101_Hierarchical_Navigable_Small_Worlds_HNSW_fcbdf88a1d.png","belong":"learn","authorNames":["Frank Liu"]},{"id":"blog-168","title":"Data Mastery Made Easy: Exploring the Magic of Vector Databases in Jupyter Notebooks","image":{"id":6396,"url":"https://assets.zilliz.com/May_24_How_to_Use_a_Vector_DB_in_Your_Jupyter_Notebook_78ce9d7acb.png"},"display_time":"May 24, 2023","deploy_time":null,"url":"exploring-magic-vector-databases-jupyter-notebooks","abstract":"Learn why vector databases can help solve one of the biggest problems LLMs face - a lack of domain knowledge and up-to-date data. ","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":41,"name":"Yujian Tang","author_tags":"Developer Advocate at Zilliz","published_at":"2023-04-20T21:52:47.479Z","created_by":18,"updated_by":18,"created_at":"2023-04-20T21:52:45.859Z","updated_at":"2024-07-18T16:02:07.497Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/yujiantang/","self_intro":"Yujian Tang is a Developer Advocate at Zilliz. He has a background as a software engineer working on AutoML at Amazon. Yujian studied Computer Science, Statistics, and Neuroscience with research papers published to conferences including IEEE Big Data. He enjoys drinking bubble tea, spending time with family, and being near water.","repost_to_medium":null,"repost_state":null,"meta_description":"Yujian Tang, Developer Advocate at Zilliz. ","locale":"en"}],"read_time":4,"localizations":[{"id":1333,"locale":"ja-JP","published_at":"2023-05-24T17:54:11.711Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/May_24_How_to_Use_a_Vector_DB_in_Your_Jupyter_Notebook_78ce9d7acb.png","belong":"blog","authorNames":["Yujian Tang"]},{"id":"blog-165","title":"Ultimate Guide to Getting Started with LangChain","image":{"id":6395,"url":"https://assets.zilliz.com/May_22_Getting_Started_with_Lang_Chain_2e193922fa.png"},"display_time":"May 22, 2023","deploy_time":null,"url":"langchain-ultimate-guide-getting-started","abstract":"This tutorial covers LangChain, how it works and two use cases. It’s everything you need to know about the tool, querying GPT, and adding functionality to LLMs.\n","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":41,"name":"Yujian Tang","author_tags":"Developer Advocate at Zilliz","published_at":"2023-04-20T21:52:47.479Z","created_by":18,"updated_by":18,"created_at":"2023-04-20T21:52:45.859Z","updated_at":"2024-07-18T16:02:07.497Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/yujiantang/","self_intro":"Yujian Tang is a Developer Advocate at Zilliz. He has a background as a software engineer working on AutoML at Amazon. Yujian studied Computer Science, Statistics, and Neuroscience with research papers published to conferences including IEEE Big Data. He enjoys drinking bubble tea, spending time with family, and being near water.","repost_to_medium":null,"repost_state":null,"meta_description":"Yujian Tang, Developer Advocate at Zilliz. ","locale":"en"}],"read_time":7,"localizations":[{"id":1326,"locale":"ja-JP","published_at":"2023-05-22T17:17:30.278Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/May_22_Getting_Started_with_Lang_Chain_2e193922fa.png","belong":"blog","authorNames":["Yujian Tang"]},{"id":"blog-164","title":"What is Pymilvus?","image":{"id":6394,"url":"https://assets.zilliz.com/May_20_What_is_Pymilvus_a0a5da698a.png"},"display_time":"May 20, 2023","deploy_time":null,"url":"what-is-pymilvus","abstract":"Pymilvus a Python SDK built for the Milvus and Zilliz Cloud vector databases. ","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":43,"name":"Filip Haltmayer","author_tags":"Software Engineer, Zilliz","published_at":"2023-04-25T19:40:57.629Z","created_by":18,"updated_by":18,"created_at":"2023-04-25T19:11:31.215Z","updated_at":"2023-04-25T22:54:51.135Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/filiphaltmayer/","self_intro":"Filip Haltmayer is a Software Engineer at Zilliz working in both software and community development. His contributions mainly revolve around the Milvus and Towhee projects, helping develop both applications and helping grow their respective user bases through client interaction, integrations, and technical talks.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":5,"localizations":[{"id":838,"locale":"ja-JP","published_at":"2023-05-20T00:41:28.565Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/May_20_What_is_Pymilvus_a0a5da698a.png","belong":"blog","authorNames":["Filip Haltmayer"]},{"id":"blog-161","title":"Using a Vector Database to Search White House Speeches","image":{"id":6393,"url":"https://assets.zilliz.com/May_19_Using_a_Vector_Database_to_Search_White_House_Speeches_6af45804ca.png"},"display_time":"May 19, 2023","deploy_time":"2023-05-19T04:00:00.000Z","url":"using-vector-database-search-white-house-speeches","abstract":"Learn how to search for speeches using a general description with a vector database.","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":41,"name":"Yujian Tang","author_tags":"Developer Advocate at Zilliz","published_at":"2023-04-20T21:52:47.479Z","created_by":18,"updated_by":18,"created_at":"2023-04-20T21:52:45.859Z","updated_at":"2024-07-18T16:02:07.497Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/yujiantang/","self_intro":"Yujian Tang is a Developer Advocate at Zilliz. He has a background as a software engineer working on AutoML at Amazon. Yujian studied Computer Science, Statistics, and Neuroscience with research papers published to conferences including IEEE Big Data. He enjoys drinking bubble tea, spending time with family, and being near water.","repost_to_medium":null,"repost_state":null,"meta_description":"Yujian Tang, Developer Advocate at Zilliz. ","locale":"en"}],"read_time":9,"localizations":[{"id":887,"locale":"ja-JP","published_at":"2023-05-19T06:40:11.159Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/May_19_Using_a_Vector_Database_to_Search_White_House_Speeches_6af45804ca.png","belong":"blog","authorNames":["Yujian Tang"]},{"id":"blog-163","title":"Getting Started with LlamaIndex","image":{"id":6392,"url":"https://assets.zilliz.com/May_17_Getting_Started_with_Llama_Index_b7cf3a2b2d.png"},"display_time":"May 17, 2023","deploy_time":"2023-05-18T04:00:00.000Z","url":"getting-started-with-llamaindex","abstract":"Learn about LlamaIndex, a flexible data framework connecting private, customized data sources to your large language models (LLMs).","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":41,"name":"Yujian Tang","author_tags":"Developer Advocate at Zilliz","published_at":"2023-04-20T21:52:47.479Z","created_by":18,"updated_by":18,"created_at":"2023-04-20T21:52:45.859Z","updated_at":"2024-07-18T16:02:07.497Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/yujiantang/","self_intro":"Yujian Tang is a Developer Advocate at Zilliz. He has a background as a software engineer working on AutoML at Amazon. Yujian studied Computer Science, Statistics, and Neuroscience with research papers published to conferences including IEEE Big Data. He enjoys drinking bubble tea, spending time with family, and being near water.","repost_to_medium":null,"repost_state":null,"meta_description":"Yujian Tang, Developer Advocate at Zilliz. ","locale":"en"}],"read_time":9,"localizations":[{"id":1289,"locale":"ja-JP","published_at":"2023-05-18T08:59:21.349Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/May_17_Getting_Started_with_Llama_Index_b7cf3a2b2d.png","belong":"blog","authorNames":["Yujian Tang"]},{"id":"blog-162","title":"Revolutionizing Autonomous AI: Harnessing Vector Databases to Empower Auto-GPT","image":{"id":6391,"url":"https://assets.zilliz.com/May_16_Revolutionizing_Autonomous_AI_Harnessing_Vector_Databases_to_Empower_Auto_GPT_24ab21cf10.png"},"display_time":"May 16, 2023","deploy_time":"2023-05-16T04:00:00.000Z","url":"harnessing-vector-databases-to-empower-autogpt","abstract":"Learn how vector databases can strengthen Auto-GPT's contextual capability","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":46,"name":"Sim Fu","author_tags":"Software Engineer","published_at":"2023-05-16T07:59:02.167Z","created_by":18,"updated_by":18,"created_at":"2023-05-16T07:59:00.534Z","updated_at":"2024-07-19T03:23:36.412Z","home_page":"GitHub","home_page_link":"https://github.com/SimFG","self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Sim Fu, Software Engineer at Zilliz","locale":"en"}],"read_time":5,"localizations":[{"id":919,"locale":"ja-JP","published_at":"2023-05-16T08:26:12.261Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/May_16_Revolutionizing_Autonomous_AI_Harnessing_Vector_Databases_to_Empower_Auto_GPT_24ab21cf10.png","belong":"blog","authorNames":["Sim Fu"]},{"id":"blog-160","title":"Webinar Recap: Boost Your LLM with Private Data Using LlamaIndex","image":{"id":6390,"url":"https://assets.zilliz.com/May_15_Webinar_Recap_1_e47e54ade7.png"},"display_time":"May 15, 2023","deploy_time":null,"url":"boost-your-llm-private-data-llamaindex","abstract":"Get answers to the most common questions about using LlamaIndex with Milvus and Zilliz.","tags":[{"id":4,"name":"Company","published_at":"2021-01-21T02:28:23.551Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:20.676Z","updated_at":"2021-01-21T02:28:23.824Z","locale":"en"}],"authors":[{"id":45,"name":"Fendy Feng","author_tags":"Technical Marketing Writer","published_at":"2023-05-16T01:36:15.102Z","created_by":18,"updated_by":18,"created_at":"2023-05-16T00:04:12.065Z","updated_at":"2024-04-25T08:37:19.712Z","home_page":"GitHub","home_page_link":"https://www.linkedin.com/in/fendy311/","self_intro":"Fendy Feng is the Technical Marketing Writer at Zilliz. She has extensive experience developing and enhancing the impact of open-source projects in various global markets by producing high-quality, tailored content. Before joining Zilliz, Fendy worked as a Content Strategist at PingCAP, a fast-growing E-Series startup renowned for its open-source distributed SQL database.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":6,"localizations":[{"id":900,"locale":"ja-JP","published_at":"2023-05-15T21:39:20.525Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/May_15_Webinar_Recap_1_e47e54ade7.png","belong":"blog","authorNames":["Fendy Feng"]},{"id":"learn-39","title":"OpenAI's ChatGPT","image":{"id":6389,"url":"https://assets.zilliz.com/May_09_Open_AI_s_Chat_GPT_and_the_new_AI_Stack_Chat_GPT_your_Vector_Database_and_Prompt_as_code_c1ba3cc5ef.png"},"display_time":"May 09, 2023","url":"ChatGPT-Vector-Database-Prompt-as-code","abstract":"A guide to the new AI Stack - ChatGPT, your Vector Database, and Prompt as code","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":36,"name":"Chris Churilo","author_tags":"VP of Marketing","published_at":"2023-04-11T16:51:05.002Z","created_by":18,"updated_by":53,"created_at":"2023-04-11T16:42:46.067Z","updated_at":"2025-01-16T22:35:53.011Z","home_page":"GitHub","home_page_link":"https://github.com/ChrisChurilo","self_intro":"Chris Churilo is the VP of Marketing \u0026 Community at Zilliz where she leads all community, developer relations, and marketing efforts. Prior to Zilliz, Chris was a founding member of the InfluxData’s go to market efforts and helped propel the time series database platform to dominance in the market. In earlier roles she defined and designed a SaaS monitoring solution at Centroid, and prior to that she was the VP of product management at iPass and was the LOB for several cloud services that required her to track the business and operational metrics and analytics to help identify and resolve issues.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":9,"localizations":[{"id":355,"locale":"ja-JP","published_at":"2023-05-12T14:38:06.267Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/May_09_Open_AI_s_Chat_GPT_and_the_new_AI_Stack_Chat_GPT_your_Vector_Database_and_Prompt_as_code_c1ba3cc5ef.png","belong":"learn","authorNames":["Chris Churilo"]},{"id":"blog-159","title":"Zilliz Cloud: a New Level of Usability and Performance","image":{"id":6387,"url":"https://assets.zilliz.com/May_04_Zilliz_Cloud_a_New_Level_of_Usability_and_Performance_2311827b60.png"},"display_time":"May 04, 2023","deploy_time":"2023-05-04T04:00:00.000Z","url":"zilliz-cloud-updates-improved-usability-and-performance","abstract":"Learn how the latest release of Zilliz Cloud improves the user experience and performance. ","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":39,"name":"Sarah Tang","author_tags":"Senior Product Manager","published_at":"2023-04-12T03:08:03.943Z","created_by":18,"updated_by":18,"created_at":"2023-04-12T02:56:07.784Z","updated_at":"2023-04-12T03:11:53.050Z","home_page":"linkedin","home_page_link":"https://www.linkedin.com/in/xue-tang-070734169/","self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":2,"localizations":[{"id":993,"locale":"ja-JP","published_at":"2023-05-04T09:35:08.849Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/May_04_Zilliz_Cloud_a_New_Level_of_Usability_and_Performance_2311827b60.png","belong":"blog","authorNames":["Sarah Tang"]},{"id":"blog-158","title":"Milvus 2.2.6: New Features and Updates","image":{"id":1330,"url":"https://assets.zilliz.com/Apr_30_What_s_New_in_Milvus_2_2_6_c6c459c80c.png"},"display_time":"Apr 28, 2023","deploy_time":null,"url":"milvus-2-2-6-new-features-and-updates","abstract":"Milvus 2.2.6 includes a key security update to MinIO and a few other performance enhancements.","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":36,"name":"Chris Churilo","author_tags":"VP of Marketing","published_at":"2023-04-11T16:51:05.002Z","created_by":18,"updated_by":53,"created_at":"2023-04-11T16:42:46.067Z","updated_at":"2025-01-16T22:35:53.011Z","home_page":"GitHub","home_page_link":"https://github.com/ChrisChurilo","self_intro":"Chris Churilo is the VP of Marketing \u0026 Community at Zilliz where she leads all community, developer relations, and marketing efforts. Prior to Zilliz, Chris was a founding member of the InfluxData’s go to market efforts and helped propel the time series database platform to dominance in the market. In earlier roles she defined and designed a SaaS monitoring solution at Centroid, and prior to that she was the VP of product management at iPass and was the LOB for several cloud services that required her to track the business and operational metrics and analytics to help identify and resolve issues.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":0,"localizations":[{"id":1146,"locale":"ja-JP","published_at":"2023-05-01T16:31:35.753Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Apr_30_What_s_New_in_Milvus_2_2_6_c6c459c80c.png","belong":"blog","authorNames":["Chris Churilo"]},{"id":"blog-157","title":"The Fight for AI Supremacy","image":{"id":6386,"url":"https://assets.zilliz.com/Apr_25_Fight_for_AI_Supremacy_076724b9e6.png"},"display_time":"Apr 25, 2023","deploy_time":"2023-04-25T22:30:00.000Z","url":"Fight-for-AI-Supremacy","abstract":"Learn how technologies like LangChain and Milvus can be used together to create domain-specific chatbots and combat hallucinations.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":43,"name":"Filip Haltmayer","author_tags":"Software Engineer, Zilliz","published_at":"2023-04-25T19:40:57.629Z","created_by":18,"updated_by":18,"created_at":"2023-04-25T19:11:31.215Z","updated_at":"2023-04-25T22:54:51.135Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/filiphaltmayer/","self_intro":"Filip Haltmayer is a Software Engineer at Zilliz working in both software and community development. His contributions mainly revolve around the Milvus and Towhee projects, helping develop both applications and helping grow their respective user bases through client interaction, integrations, and technical talks.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":5,"localizations":[{"id":938,"locale":"ja-JP","published_at":"2023-04-25T22:07:57.730Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Apr_25_Fight_for_AI_Supremacy_076724b9e6.png","belong":"blog","authorNames":["Filip Haltmayer"]},{"id":"blog-156","title":"Yet another cache, but for ChatGPT","image":{"id":6385,"url":"https://assets.zilliz.com/Apr_11_GPT_Cache_An_open_source_library_to_cache_responses_from_LLM_queries_8_index_types_aeeefc977b.png"},"display_time":"Apr 11, 2023","deploy_time":null,"url":"Yet-another-cache-but-for-ChatGPT","abstract":"With GPTCache, you can cache your LLM responses with just a few lines of code changes, boosting your LLM applications 100 times faster.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":34,"name":"James Luan","author_tags":"VP of Engineering at Zilliz","published_at":"2022-05-18T03:15:15.255Z","created_by":18,"updated_by":18,"created_at":"2022-05-18T03:14:35.112Z","updated_at":"2024-01-12T21:01:29.192Z","home_page":"GitHub","home_page_link":"https://github.com/xiaofan-luan","self_intro":"James Luan is the VP of Engineering at Zilliz. With a master's degree in computer engineering from Cornell University, he has extensive experience as a Database Engineer at Oracle, Hedvig, and Alibaba Cloud. James played a crucial role in developing HBase, Alibaba Cloud's open-source database, and Lindorm, a self-developed NoSQL database. He is also a respected member of the Technical Advisory Committee of LF AI \u0026 Data Foundation, contributing his expertise to shaping the future of AI and data technologies.\n","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":9,"localizations":[{"id":1065,"locale":"ja-JP","published_at":"2023-04-11T16:41:01.810Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Apr_11_GPT_Cache_An_open_source_library_to_cache_responses_from_LLM_queries_8_index_types_aeeefc977b.png","belong":"blog","authorNames":["James Luan"]},{"id":"blog-155","title":"Caching LLM Queries for performance \u0026 cost improvements","image":{"id":6384,"url":"https://assets.zilliz.com/Apr_10_Introducing_GPT_Cache_45014e0dd2.png"},"display_time":"Apr 10, 2023","deploy_time":null,"url":"Caching-LLM-Queries-for-performance-improvements","abstract":"Caching LLM Queries for performance \u0026 cost improvements with the open-source GPTCache","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":36,"name":"Chris Churilo","author_tags":"VP of Marketing","published_at":"2023-04-11T16:51:05.002Z","created_by":18,"updated_by":53,"created_at":"2023-04-11T16:42:46.067Z","updated_at":"2025-01-16T22:35:53.011Z","home_page":"GitHub","home_page_link":"https://github.com/ChrisChurilo","self_intro":"Chris Churilo is the VP of Marketing \u0026 Community at Zilliz where she leads all community, developer relations, and marketing efforts. Prior to Zilliz, Chris was a founding member of the InfluxData’s go to market efforts and helped propel the time series database platform to dominance in the market. In earlier roles she defined and designed a SaaS monitoring solution at Centroid, and prior to that she was the VP of product management at iPass and was the LOB for several cloud services that required her to track the business and operational metrics and analytics to help identify and resolve issues.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":5,"localizations":[{"id":1094,"locale":"ja-JP","published_at":"2023-04-10T17:19:02.922Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Apr_10_Introducing_GPT_Cache_45014e0dd2.png","belong":"blog","authorNames":["Chris Churilo"]},{"id":"blog-154","title":"New Support for Backup and Restore of Zilliz Cloud Databases","image":{"id":6383,"url":"https://assets.zilliz.com/Apr_07_New_Feature_Spotlight_Backup_and_Restore_1_33fac6b964.png"},"display_time":"Apr 07, 2023","deploy_time":"2023-04-07T15:00:00.000Z","url":"backup-and-restore-Zilliz-Cloud","abstract":"Create a snapshots of your Zilliz Cloud database to use it as a baseline for new databases or just as a data backup.","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":39,"name":"Sarah Tang","author_tags":"Senior Product Manager","published_at":"2023-04-12T03:08:03.943Z","created_by":18,"updated_by":18,"created_at":"2023-04-12T02:56:07.784Z","updated_at":"2023-04-12T03:11:53.050Z","home_page":"linkedin","home_page_link":"https://www.linkedin.com/in/xue-tang-070734169/","self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":2,"localizations":[{"id":1141,"locale":"ja-JP","published_at":"2023-04-04T22:12:55.699Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Apr_07_New_Feature_Spotlight_Backup_and_Restore_1_33fac6b964.png","belong":"blog","authorNames":["Sarah Tang"]},{"id":"blog-153","title":"Accelerate your migration experience from Milvus to Zilliz Cloud","image":{"id":1289,"url":"https://assets.zilliz.com/Zilliz_Cloud_Milvus_Migration_Made_Easy_Blog_1200_628_557fc347d5.png"},"display_time":"Apr 06, 2023","deploy_time":"2023-04-06T15:00:00.000Z","url":"Migrating-from-Milvus-to-Zilliz","abstract":"A new migration tool to make it easy to move your collections from Milvus to Zilliz Cloud","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":39,"name":"Sarah Tang","author_tags":"Senior Product Manager","published_at":"2023-04-12T03:08:03.943Z","created_by":18,"updated_by":18,"created_at":"2023-04-12T02:56:07.784Z","updated_at":"2023-04-12T03:11:53.050Z","home_page":"linkedin","home_page_link":"https://www.linkedin.com/in/xue-tang-070734169/","self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":2,"localizations":[{"id":1274,"locale":"ja-JP","published_at":"2023-04-04T21:47:38.227Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Zilliz_Cloud_Milvus_Migration_Made_Easy_Blog_1200_628_557fc347d5.png","belong":"blog","authorNames":["Sarah Tang"]},{"id":"blog-151","title":"Zilliz Cloud Expands with Multi-Cloud Support","image":{"id":6382,"url":"https://assets.zilliz.com/Apr_06_Zilliz_Cloud_Now_Available_on_the_AWS_Marketplace_f667f0ef23.png"},"display_time":"Apr 05, 2023","deploy_time":"2023-04-05T15:00:00.000Z","url":"zilliz-cloud-expands-multi-cloud","abstract":"Zilliz Cloud is available on multiple Google Cloud and AWS regions. Streamlined billing and procurement through the AWS Marketplace makes getting started easy.","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":37,"name":"Emily Kurze","author_tags":"Director of Marketing Operations","published_at":"2023-04-11T16:55:11.838Z","created_by":18,"updated_by":18,"created_at":"2023-04-11T16:55:07.625Z","updated_at":"2024-04-29T03:28:13.160Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/emilykurze/","self_intro":"Emily Kurze is the Director of Marketing at Zilliz. ","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":2,"localizations":[{"id":1158,"locale":"ja-JP","published_at":"2023-04-04T21:10:43.629Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Apr_06_Zilliz_Cloud_Now_Available_on_the_AWS_Marketplace_f667f0ef23.png","belong":"blog","authorNames":["Emily Kurze"]},{"id":"blog-150","title":"Zilliz Cloud, the new billion-scale offering","image":{"id":6381,"url":"https://assets.zilliz.com/Apr_04_Zilliz_Cloud_overview_7e5edd9e7f.png"},"display_time":"Apr 04, 2023","deploy_time":"2023-04-04T10:00:00.000Z","url":"zilliz-cloud-billion-vector-scale","abstract":"Support for billion-scale, performance updates, GCP, AWS Marketplace, Rolling upgrades, Backup and Restore, Recycler bin, Migration from Milvus, \u0026 more!","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":68,"name":"Robert Guo","author_tags":"Director of Product Management","published_at":"2023-06-13T18:34:37.794Z","created_by":18,"updated_by":18,"created_at":"2023-06-08T17:01:36.444Z","updated_at":"2024-04-16T02:44:46.685Z","home_page":"GitHub","home_page_link":"https://github.com/GuoRentong","self_intro":"Robert Guo is a Partner and Director of Product Management at Zilliz and one of the architects behind Milvus, an open-source vector database revolutionizing AI data analysis. With a Ph.D. in Computer Software and Theory from Huazhong University of Science and Technology, he has presented influential work at prestigious conferences and journals, including SIGMOD, VLDB, USENIX ATC, ICS, DATE, and IEEE TPDS. Previously a key developer for Huawei's ModelArts platform, Robert is skilled at crafting efficient and scalable AI data solutions.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":4,"localizations":[{"id":975,"locale":"ja-JP","published_at":"2023-04-04T04:16:13.365Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Apr_04_Zilliz_Cloud_overview_7e5edd9e7f.png","belong":"blog","authorNames":["Robert Guo"]},{"id":"blog-152","title":"ChatGPT+ Vector database + prompt-as-code - The CVP Stack","image":{"id":1291,"url":"https://assets.zilliz.com/OG_image_2105df2d2e.png"},"display_time":"Apr 04, 2023","deploy_time":"2023-04-04T15:00:00.000Z","url":"ChatGPT-VectorDB-Prompt-as-code","abstract":"Extend the capability of ChatGPT with a Vector database and prompts-as-code","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":34,"name":"James Luan","author_tags":"VP of Engineering at Zilliz","published_at":"2022-05-18T03:15:15.255Z","created_by":18,"updated_by":18,"created_at":"2022-05-18T03:14:35.112Z","updated_at":"2024-01-12T21:01:29.192Z","home_page":"GitHub","home_page_link":"https://github.com/xiaofan-luan","self_intro":"James Luan is the VP of Engineering at Zilliz. With a master's degree in computer engineering from Cornell University, he has extensive experience as a Database Engineer at Oracle, Hedvig, and Alibaba Cloud. James played a crucial role in developing HBase, Alibaba Cloud's open-source database, and Lindorm, a self-developed NoSQL database. He is also a respected member of the Technical Advisory Committee of LF AI \u0026 Data Foundation, contributing his expertise to shaping the future of AI and data technologies.\n","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":5,"localizations":[{"id":944,"locale":"ja-JP","published_at":"2023-04-04T15:07:11.339Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/OG_image_2105df2d2e.png","belong":"blog","authorNames":["James Luan"]},{"id":"blog-149","title":"What's New in Milvus version 2.2.5","image":{"id":1279,"url":"https://assets.zilliz.com/Mar_30_What_s_New_in_Milvus_2_2_5_d9cbc3f15f.png"},"display_time":"Mar 30, 2023","deploy_time":null,"url":"milvus-2-2-5-new-features-and-updates","abstract":"Milvus 2.2.5 includes a key security update to MinIO and a few other performance enhancements.","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":36,"name":"Chris Churilo","author_tags":"VP of Marketing","published_at":"2023-04-11T16:51:05.002Z","created_by":18,"updated_by":53,"created_at":"2023-04-11T16:42:46.067Z","updated_at":"2025-01-16T22:35:53.011Z","home_page":"GitHub","home_page_link":"https://github.com/ChrisChurilo","self_intro":"Chris Churilo is the VP of Marketing \u0026 Community at Zilliz where she leads all community, developer relations, and marketing efforts. Prior to Zilliz, Chris was a founding member of the InfluxData’s go to market efforts and helped propel the time series database platform to dominance in the market. In earlier roles she defined and designed a SaaS monitoring solution at Centroid, and prior to that she was the VP of product management at iPass and was the LOB for several cloud services that required her to track the business and operational metrics and analytics to help identify and resolve issues.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":1,"localizations":[{"id":1190,"locale":"ja-JP","published_at":"2023-03-30T17:34:25.601Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Mar_30_What_s_New_in_Milvus_2_2_5_d9cbc3f15f.png","belong":"blog","authorNames":["Chris Churilo"]},{"id":"blog-132","title":"ChatGPT retrieval plugin with Zilliz and Milvus","image":{"id":1274,"url":"https://assets.zilliz.com/Zillizx_Open_AI_bf6627255a.png"},"display_time":"Mar 23, 2023","deploy_time":null,"url":"chatgpt-retrieval-plugin-zilliz-milvus","abstract":"Milvus and Zilliz are one of the preferred vector databases to store these embeddings that can be accessed with the ChatGPT retrieval plugin.","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":43,"name":"Filip Haltmayer","author_tags":"Software Engineer, Zilliz","published_at":"2023-04-25T19:40:57.629Z","created_by":18,"updated_by":18,"created_at":"2023-04-25T19:11:31.215Z","updated_at":"2023-04-25T22:54:51.135Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/filiphaltmayer/","self_intro":"Filip Haltmayer is a Software Engineer at Zilliz working in both software and community development. His contributions mainly revolve around the Milvus and Towhee projects, helping develop both applications and helping grow their respective user bases through client interaction, integrations, and technical talks.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":4,"localizations":[{"id":892,"locale":"ja-JP","published_at":"2023-03-24T01:01:04.968Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Zillizx_Open_AI_bf6627255a.png","belong":"blog","authorNames":["Filip Haltmayer"]},{"id":"blog-131","title":"Milvus support for multiple Index types","image":{"id":6380,"url":"https://assets.zilliz.com/Mar_23_Milvus_Supports_8_Index_Types_for_Optimal_Performance8_index_types_e01b161fd3.png"},"display_time":"Mar 23, 2023","deploy_time":null,"url":"Milvus-Index-Types-Supported","abstract":"One of the essential features of Milvus is the support for various Index types; Indexes help to optimize data querying and retrieval.","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":36,"name":"Chris Churilo","author_tags":"VP of Marketing","published_at":"2023-04-11T16:51:05.002Z","created_by":18,"updated_by":53,"created_at":"2023-04-11T16:42:46.067Z","updated_at":"2025-01-16T22:35:53.011Z","home_page":"GitHub","home_page_link":"https://github.com/ChrisChurilo","self_intro":"Chris Churilo is the VP of Marketing \u0026 Community at Zilliz where she leads all community, developer relations, and marketing efforts. Prior to Zilliz, Chris was a founding member of the InfluxData’s go to market efforts and helped propel the time series database platform to dominance in the market. In earlier roles she defined and designed a SaaS monitoring solution at Centroid, and prior to that she was the VP of product management at iPass and was the LOB for several cloud services that required her to track the business and operational metrics and analytics to help identify and resolve issues.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":3,"localizations":[{"id":1252,"locale":"ja-JP","published_at":"2023-03-23T18:28:56.749Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Mar_23_Milvus_Supports_8_Index_Types_for_Optimal_Performance8_index_types_e01b161fd3.png","belong":"blog","authorNames":["Chris Churilo"]},{"id":"blog-130","title":"What’s New In Milvus 2.3 Beta - 10X faster with GPUs","image":{"id":6379,"url":"https://assets.zilliz.com/Mar_21_Milvus_2_3_is_here_and_faster_than_ever_7f887d5bcc.png"},"display_time":"Mar 21, 2023","deploy_time":null,"url":"milvus-2-3-beta-new-features-and-updates","abstract":"Milvus 2.3 Beta supports GPU acceleration, range search, mmap, dynamic partitioning, and incremental backups, to improve performance of your AI powered app.","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":36,"name":"Chris Churilo","author_tags":"VP of Marketing","published_at":"2023-04-11T16:51:05.002Z","created_by":18,"updated_by":53,"created_at":"2023-04-11T16:42:46.067Z","updated_at":"2025-01-16T22:35:53.011Z","home_page":"GitHub","home_page_link":"https://github.com/ChrisChurilo","self_intro":"Chris Churilo is the VP of Marketing \u0026 Community at Zilliz where she leads all community, developer relations, and marketing efforts. Prior to Zilliz, Chris was a founding member of the InfluxData’s go to market efforts and helped propel the time series database platform to dominance in the market. In earlier roles she defined and designed a SaaS monitoring solution at Centroid, and prior to that she was the VP of product management at iPass and was the LOB for several cloud services that required her to track the business and operational metrics and analytics to help identify and resolve issues.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":3,"localizations":[{"id":953,"locale":"ja-JP","published_at":"2023-03-21T16:50:15.606Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Mar_21_Milvus_2_3_is_here_and_faster_than_ever_7f887d5bcc.png","belong":"blog","authorNames":["Chris Churilo"]},{"id":"blog-128","title":"Milvus Performance Evaluation 2023","image":{"id":6378,"url":"https://assets.zilliz.com/Mar_17_Milvus_Performance_Evaluation_2023_cf9782d312.png"},"display_time":"Mar 17, 2023","deploy_time":null,"url":"milvus-2.x-performance-benchmark-update","abstract":"Milvus v2.2.3 outperformed Milvus v2.0.0 in tests, reducing search latency by 2.5x, 4.5 increase in throughput, even with a scale-out for a billion-scale collection.","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":36,"name":"Chris Churilo","author_tags":"VP of Marketing","published_at":"2023-04-11T16:51:05.002Z","created_by":18,"updated_by":53,"created_at":"2023-04-11T16:42:46.067Z","updated_at":"2025-01-16T22:35:53.011Z","home_page":"GitHub","home_page_link":"https://github.com/ChrisChurilo","self_intro":"Chris Churilo is the VP of Marketing \u0026 Community at Zilliz where she leads all community, developer relations, and marketing efforts. Prior to Zilliz, Chris was a founding member of the InfluxData’s go to market efforts and helped propel the time series database platform to dominance in the market. In earlier roles she defined and designed a SaaS monitoring solution at Centroid, and prior to that she was the VP of product management at iPass and was the LOB for several cloud services that required her to track the business and operational metrics and analytics to help identify and resolve issues.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":2,"localizations":[{"id":1079,"locale":"ja-JP","published_at":"2023-03-17T16:21:33.596Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Mar_17_Milvus_Performance_Evaluation_2023_cf9782d312.png","belong":"blog","authorNames":["Chris Churilo"]},{"id":"blog-129","title":"What’s New In Milvus 2.2.4","image":{"id":1257,"url":"https://assets.zilliz.com/What_s_New_in_Milvus_2_2_4_aa52cb1723.png"},"display_time":"Mar 17, 2023","deploy_time":null,"url":"milvus-2-2-4-new-features-and-updates","abstract":"Milvus 2.2.4 includes the support of resource grouping for QueryNodes, collection renaming, Google Cloud Storage support, and a new search and query API option.\n\n","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":36,"name":"Chris Churilo","author_tags":"VP of Marketing","published_at":"2023-04-11T16:51:05.002Z","created_by":18,"updated_by":53,"created_at":"2023-04-11T16:42:46.067Z","updated_at":"2025-01-16T22:35:53.011Z","home_page":"GitHub","home_page_link":"https://github.com/ChrisChurilo","self_intro":"Chris Churilo is the VP of Marketing \u0026 Community at Zilliz where she leads all community, developer relations, and marketing efforts. Prior to Zilliz, Chris was a founding member of the InfluxData’s go to market efforts and helped propel the time series database platform to dominance in the market. In earlier roles she defined and designed a SaaS monitoring solution at Centroid, and prior to that she was the VP of product management at iPass and was the LOB for several cloud services that required her to track the business and operational metrics and analytics to help identify and resolve issues.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":1,"localizations":[{"id":1251,"locale":"ja-JP","published_at":"2023-03-17T19:03:47.086Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/What_s_New_in_Milvus_2_2_4_aa52cb1723.png","belong":"blog","authorNames":["Chris Churilo"]},{"id":"blog-127","title":"How Zilliz Cloud Protects Your Data","image":{"id":6377,"url":"https://assets.zilliz.com/Mar_09_How_Zilliz_Cloud_Protects_Your_Data_e888247d00.png"},"display_time":"Mar 09, 2023","deploy_time":null,"url":"how-zilliz-cloud-protects-your-data","abstract":"Here at Zilliz, we take data security very seriously. Learn how Zilliz Cloud protects your data.","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":1,"name":"Zilliz","author_tags":"Vector database","published_at":"2021-12-14T06:36:41.397Z","created_by":18,"updated_by":18,"created_at":"2021-12-14T06:28:27.154Z","updated_at":"2023-04-11T16:54:05.275Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":4,"localizations":[{"id":1081,"locale":"ja-JP","published_at":"2023-03-09T10:52:43.903Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Mar_09_How_Zilliz_Cloud_Protects_Your_Data_e888247d00.png","belong":"blog","authorNames":["Zilliz"]},{"id":"blog-126","title":"What’s New In Milvus 2.2.3","image":{"id":1229,"url":"https://assets.zilliz.com/Zilliz_Blog_23_Feb_2_20230227_023516_54c80fa064.png"},"display_time":"Feb 27, 2023","deploy_time":null,"url":"milvus-2-2-3-new-features-and-updates","abstract":"Milvus 2.2.3 includes the support of rolling upgrades to upgrade Milvus without noticeable service disruption and with minimal downtime.","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":36,"name":"Chris Churilo","author_tags":"VP of Marketing","published_at":"2023-04-11T16:51:05.002Z","created_by":18,"updated_by":53,"created_at":"2023-04-11T16:42:46.067Z","updated_at":"2025-01-16T22:35:53.011Z","home_page":"GitHub","home_page_link":"https://github.com/ChrisChurilo","self_intro":"Chris Churilo is the VP of Marketing \u0026 Community at Zilliz where she leads all community, developer relations, and marketing efforts. Prior to Zilliz, Chris was a founding member of the InfluxData’s go to market efforts and helped propel the time series database platform to dominance in the market. In earlier roles she defined and designed a SaaS monitoring solution at Centroid, and prior to that she was the VP of product management at iPass and was the LOB for several cloud services that required her to track the business and operational metrics and analytics to help identify and resolve issues.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":1,"localizations":[{"id":1199,"locale":"ja-JP","published_at":"2023-02-27T18:25:09.711Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Zilliz_Blog_23_Feb_2_20230227_023516_54c80fa064.png","belong":"blog","authorNames":["Chris Churilo"]},{"id":"blog-125","title":"How to Integrate OpenAI Embedding API with Zilliz Cloud","image":{"id":1172,"url":"https://assets.zilliz.com/20230111_162854_6690ae1508.png"},"display_time":"Jan 11, 2023","deploy_time":null,"url":"how-to-integrate-openai-embedding-api-with-zilliz-cloud","abstract":"We are proud to announce that we'll be providing embedding model integrations - a way to connect your Milvus and/or Zilliz Cloud database to open source or paid embedding models.","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":1,"name":"Zilliz","author_tags":"Vector database","published_at":"2021-12-14T06:36:41.397Z","created_by":18,"updated_by":18,"created_at":"2021-12-14T06:28:27.154Z","updated_at":"2023-04-11T16:54:05.275Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":4,"localizations":[{"id":906,"locale":"ja-JP","published_at":"2023-01-11T08:31:37.306Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/20230111_162854_6690ae1508.png","belong":"blog","authorNames":["Zilliz"]},{"id":"blog-313","title":"The Next Stop for Vector Databases: 8 Predictions for 2023","image":{"id":6413,"url":"https://assets.zilliz.com/large_Apr_11_GPT_Cache_An_open_source_library_to_cache_responses_from_LLM_queries_657b8ccd31_eb20a2c4a0.png"},"display_time":"Dec 09, 2022","deploy_time":null,"url":"the-next-stop-for-vector-databases-8-predictions-for-2023","abstract":"Vector database predictions for 2023","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":34,"name":"James Luan","author_tags":"VP of Engineering at Zilliz","published_at":"2022-05-18T03:15:15.255Z","created_by":18,"updated_by":18,"created_at":"2022-05-18T03:14:35.112Z","updated_at":"2024-01-12T21:01:29.192Z","home_page":"GitHub","home_page_link":"https://github.com/xiaofan-luan","self_intro":"James Luan is the VP of Engineering at Zilliz. With a master's degree in computer engineering from Cornell University, he has extensive experience as a Database Engineer at Oracle, Hedvig, and Alibaba Cloud. James played a crucial role in developing HBase, Alibaba Cloud's open-source database, and Lindorm, a self-developed NoSQL database. He is also a respected member of the Technical Advisory Committee of LF AI \u0026 Data Foundation, contributing his expertise to shaping the future of AI and data technologies.\n","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":7,"localizations":[{"id":1375,"locale":"ja-JP","published_at":"2023-12-21T22:23:06.514Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/large_Apr_11_GPT_Cache_An_open_source_library_to_cache_responses_from_LLM_queries_657b8ccd31_eb20a2c4a0.png","belong":"blog","authorNames":["James Luan"]},{"id":"blog-122","title":"All You Need to Know About ANN Machine Learning","image":{"id":1152,"url":"https://assets.zilliz.com/Zilliz_Blog_7_Nov_5de4088ead.png"},"display_time":"Dec 01, 2022","deploy_time":null,"url":"ANN-machine-learning","abstract":"#Learn what ANN (Artificial Neural Networks) in Machine Learning are used for, how ANNs work and more.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":1,"name":"Zilliz","author_tags":"Vector database","published_at":"2021-12-14T06:36:41.397Z","created_by":18,"updated_by":18,"created_at":"2021-12-14T06:28:27.154Z","updated_at":"2023-04-11T16:54:05.275Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":9,"localizations":[{"id":1305,"locale":"ja-JP","published_at":"2022-12-05T03:10:15.093Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Zilliz_Blog_7_Nov_5de4088ead.png","belong":"blog","authorNames":["Zilliz"]},{"id":"blog-110","title":"Understanding K-means Clustering Algorithm in Machine Learning","image":{"id":1125,"url":"https://assets.zilliz.com/Zilliz_Blog_20_Oct_1_8b7d541aaf.png"},"display_time":"Oct 26, 2022","deploy_time":null,"url":"k-means-clustering","abstract":"K-means clustering, K-means algorithm, K-means clustering algorithm - want to know more about them? This article has everything you should know about clustering.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":1,"name":"Zilliz","author_tags":"Vector database","published_at":"2021-12-14T06:36:41.397Z","created_by":18,"updated_by":18,"created_at":"2021-12-14T06:28:27.154Z","updated_at":"2023-04-11T16:54:05.275Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":10,"localizations":[{"id":959,"locale":"ja-JP","published_at":"2022-11-02T08:42:03.915Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Zilliz_Blog_20_Oct_1_8b7d541aaf.png","belong":"blog","authorNames":["Zilliz"]},{"id":"blog-106","title":"From Text to Image: Fundamentals of CLIP","image":{"id":1106,"url":"https://assets.zilliz.com/zilliz_blog_16_1b8ea213ef.png"},"display_time":"Oct 04, 2022","deploy_time":null,"url":"fundamentals-of-clip","abstract":"Search algorithms rely on semantic similarity to retrieve the most relevant results. With the CLIP model, the semantics of texts and images can be connected in a high-dimensional vector space. Read this simple introduction to see how CLIP can help you build a powerful text-to-image service.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":68,"name":"Robert Guo","author_tags":"Director of Product Management","published_at":"2023-06-13T18:34:37.794Z","created_by":18,"updated_by":18,"created_at":"2023-06-08T17:01:36.444Z","updated_at":"2024-04-16T02:44:46.685Z","home_page":"GitHub","home_page_link":"https://github.com/GuoRentong","self_intro":"Robert Guo is a Partner and Director of Product Management at Zilliz and one of the architects behind Milvus, an open-source vector database revolutionizing AI data analysis. With a Ph.D. in Computer Software and Theory from Huazhong University of Science and Technology, he has presented influential work at prestigious conferences and journals, including SIGMOD, VLDB, USENIX ATC, ICS, DATE, and IEEE TPDS. Previously a key developer for Huawei's ModelArts platform, Robert is skilled at crafting efficient and scalable AI data solutions.","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":7,"localizations":[{"id":894,"locale":"ja-JP","published_at":"2022-10-04T02:52:59.668Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/zilliz_blog_16_1b8ea213ef.png","belong":"blog","authorNames":["Robert Guo"]},{"id":"blog-104","title":"Anatomy of A Cloud Native Vector Database Management System ","image":{"id":1093,"url":"https://assets.zilliz.com/Zilliz_Blog_20_b668afaa35.png"},"display_time":"Sep 15, 2022","deploy_time":null,"url":"anatomy-of-a-cloud-native-vector-database-management-system","abstract":"The next-generation vector databases should be equipped with long-term evolvability, tunable consistency, good elasticity, and high performance. The cloud-native architecture and data processing workflow of Manu makes it perfectly suitable for unstructured data search and analytics.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":35,"name":"Zilliz","author_tags":"Zilliz team","published_at":"2022-06-15T02:33:23.458Z","created_by":18,"updated_by":18,"created_at":"2022-06-15T02:26:19.780Z","updated_at":"2024-07-03T06:58:08.413Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":14,"localizations":[{"id":1314,"locale":"ja-JP","published_at":"2022-09-15T08:55:26.536Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Zilliz_Blog_20_b668afaa35.png","belong":"blog","authorNames":["Zilliz"]},{"id":"blog-103","title":"ArXiv Scientific Papers Vector Similarity Search with Milvus 2.1","image":{"id":1037,"url":"https://assets.zilliz.com/blog_cover_b9e1931c5d.png"},"display_time":"Aug 09, 2022","deploy_time":"2023-03-29T02:55:00.000Z","url":"Arxiv-scientific-papers-vector-similarity-search","abstract":"Run semantic search queries on ~640K papers in \u003c50ms using Dask, SBERT SPECTRE, and Milvus Vector database","tags":[{"id":1,"name":"Case Study","published_at":"2021-01-15T10:34:37.316Z","created_by":18,"updated_by":18,"created_at":"2021-01-15T10:34:34.857Z","updated_at":"2021-01-25T10:31:22.499Z","locale":"en"}],"authors":[{"id":1,"name":"Zilliz","author_tags":"Vector database","published_at":"2021-12-14T06:36:41.397Z","created_by":18,"updated_by":18,"created_at":"2021-12-14T06:28:27.154Z","updated_at":"2023-04-11T16:54:05.275Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":14,"localizations":[{"id":1273,"locale":"ja-JP","published_at":"2022-08-09T06:45:45.121Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/blog_cover_b9e1931c5d.png","belong":"blog","authorNames":["Zilliz"]},{"id":"blog-102","title":"Introducing Zilliz Cloud : Fully-managed Vector Database Cloud Service in Preview","image":{"id":1030,"url":"https://assets.zilliz.com/cloud_222250a269.png"},"display_time":"Aug 03, 2022","deploy_time":null,"url":"introducing-zilliz-cloud-preview","abstract":"Zilliz Cloud is a fully-managed vector database service that unlocks powerful similarity search for enterprise users with easy deployment and high-level security. Apply for early access now.","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"},{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":35,"name":"Zilliz","author_tags":"Zilliz team","published_at":"2022-06-15T02:33:23.458Z","created_by":18,"updated_by":18,"created_at":"2022-06-15T02:26:19.780Z","updated_at":"2024-07-03T06:58:08.413Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":2,"localizations":[{"id":1358,"locale":"ja-JP","published_at":"2022-08-05T09:47:23.626Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/cloud_222250a269.png","belong":"blog","authorNames":["Zilliz"]},{"id":"blog-101","title":"Podcast: Using AI to Supercharge Data-Driven Applications with Zilliz","image":{"id":1006,"url":"https://assets.zilliz.com/Podcast_AI_Supercharge_77eb77d183.png"},"display_time":"Jun 16, 2022","deploy_time":null,"url":"Podcast-Using-AI-to-Supercharge-Data-Driven-Applications-with-Zilliz","abstract":"What are vector databases? How do they differ from traditional databases? How can vector databases help companies from enterprises to startups? Find all that and more in the podcast interview with Frank Liu at Zilliz.","tags":[{"id":4,"name":"Company","published_at":"2021-01-21T02:28:23.551Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:20.676Z","updated_at":"2021-01-21T02:28:23.824Z","locale":"en"}],"authors":[{"id":35,"name":"Zilliz","author_tags":"Zilliz team","published_at":"2022-06-15T02:33:23.458Z","created_by":18,"updated_by":18,"created_at":"2022-06-15T02:26:19.780Z","updated_at":"2024-07-03T06:58:08.413Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":1,"localizations":[{"id":1315,"locale":"ja-JP","published_at":"2022-06-16T04:33:52.040Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Podcast_AI_Supercharge_77eb77d183.png","belong":"blog","authorNames":["Zilliz"]},{"id":"blog-100","title":"Visualize Reverse Image Search with Feder","image":{"id":1008,"url":"https://assets.zilliz.com/Zilliz_Blog_3_92e3824f59.png"},"display_time":"May 25, 2022","deploy_time":null,"url":"Visualize-Reverse-Image-Search-with-Feder","abstract":"Feder allows you to visualize the indexing and search process during a reverse image search. See how it visualizes vector similarity search with an example of searching with IVF_FLAT index.","tags":[{"id":1,"name":"Case Study","published_at":"2021-01-15T10:34:37.316Z","created_by":18,"updated_by":18,"created_at":"2021-01-15T10:34:34.857Z","updated_at":"2021-01-25T10:31:22.499Z","locale":"en"},{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":120,"name":"Min Tian","author_tags":"Software Engineer","published_at":"2024-03-16T05:39:39.262Z","created_by":18,"updated_by":18,"created_at":"2024-03-16T05:39:37.087Z","updated_at":"2024-07-18T16:00:37.188Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/min-tian-92b997237/","self_intro":"Software Engineer at Zilliz","repost_to_medium":null,"repost_state":null,"meta_description":"Min Tian, Software Engineer at Zilliz","locale":"en"}],"read_time":6,"localizations":[{"id":1168,"locale":"ja-JP","published_at":"2022-05-25T13:01:01.010Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Zilliz_Blog_3_92e3824f59.png","belong":"blog","authorNames":["Min Tian"]},{"id":"learn-36","title":"Raft or not? The Best Solution to Data Consistency in Cloud-native Databases","image":{"id":6376,"url":"https://assets.zilliz.com/Apr_11_Raft_or_not_The_Best_Solution_to_Data_Consistency_in_Cloud_native_Databases_Read_blog_Xiaofan_Luan_Director_of_Engineering_Milvus_Maintainer_4576a8cc18.png"},"display_time":"May 16, 2022","url":"raft-or-not","abstract":"Explain why consensus-based algorithms like Paxos and Raft are not the silver bullet and propose a solution to consensus-based replication.\n\n","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":34,"name":"James Luan","author_tags":"VP of Engineering at Zilliz","published_at":"2022-05-18T03:15:15.255Z","created_by":18,"updated_by":18,"created_at":"2022-05-18T03:14:35.112Z","updated_at":"2024-01-12T21:01:29.192Z","home_page":"GitHub","home_page_link":"https://github.com/xiaofan-luan","self_intro":"James Luan is the VP of Engineering at Zilliz. With a master's degree in computer engineering from Cornell University, he has extensive experience as a Database Engineer at Oracle, Hedvig, and Alibaba Cloud. James played a crucial role in developing HBase, Alibaba Cloud's open-source database, and Lindorm, a self-developed NoSQL database. He is also a respected member of the Technical Advisory Committee of LF AI \u0026 Data Foundation, contributing his expertise to shaping the future of AI and data technologies.\n","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":8,"localizations":[{"id":350,"locale":"ja-JP","published_at":"2022-05-18T03:53:16.292Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Apr_11_Raft_or_not_The_Best_Solution_to_Data_Consistency_in_Cloud_native_Databases_Read_blog_Xiaofan_Luan_Director_of_Engineering_Milvus_Maintainer_4576a8cc18.png","belong":"learn","authorNames":["James Luan"]},{"id":"blog-99","title":"Vector Database Visualization: Feder, A Powerful Tool for Similarity Search","image":{"id":1007,"url":"https://assets.zilliz.com/Zilliz_Blog_1_691b446ec9.png"},"display_time":"May 06, 2022","deploy_time":null,"url":"Visualize-Your-Approximate-Nearest-Neighbor-Search-with-Feder","abstract":"We are happy to announce the release of Feder, a powerful visualization tool that can help you see the actual structure of an index and the whole process of a vector similarity search.","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":120,"name":"Min Tian","author_tags":"Software Engineer","published_at":"2024-03-16T05:39:39.262Z","created_by":18,"updated_by":18,"created_at":"2024-03-16T05:39:37.087Z","updated_at":"2024-07-18T16:00:37.188Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/min-tian-92b997237/","self_intro":"Software Engineer at Zilliz","repost_to_medium":null,"repost_state":null,"meta_description":"Min Tian, Software Engineer at Zilliz","locale":"en"}],"read_time":8,"localizations":[{"id":871,"locale":"ja-JP","published_at":"2022-05-06T09:24:14.379Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Zilliz_Blog_1_691b446ec9.png","belong":"blog","authorNames":["Min Tian"]},{"id":"learn-34","title":"Understanding Neural Network Embeddings","image":{"id":6375,"url":"https://assets.zilliz.com/Aug_01_Zilliz_Cloud_a_Fully_Managed_Vector_Database_That_Minimizes_Users_Costs_for_Building_AI_Apps_e155c1f6f1.png"},"display_time":"Apr 30, 2022","url":"understanding-neural-network-embeddings","abstract":"This article is dedicated to going a bit more in-depth into embeddings/embedding vectors, along with how they are used in modern ML algorithms and pipelines.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":3,"name":"Frank Liu","author_tags":"Director of Operations \u0026 ML Architect at Zilliz","published_at":"2021-12-23T11:08:08.015Z","created_by":18,"updated_by":18,"created_at":"2021-12-23T10:40:59.821Z","updated_at":"2023-04-21T22:30:10.416Z","home_page":"GitHub","home_page_link":"https://github.com/fzliu","self_intro":"Frank Liu is the Director of Operations \u0026 ML Architect at Zilliz, where he serves as a maintainer for the Towhee open-source project. Prior to Zilliz, Frank co-founded Orion Innovations, an ML-powered indoor positioning startup based in Shanghai and worked as an ML engineer at Yahoo in San Francisco. In his free time, Frank enjoys playing chess, swimming, and powerlifting. Frank holds MS and BS degrees in Electrical Engineering from Stanford University. ","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":10,"localizations":[{"id":353,"locale":"ja-JP","published_at":"2022-05-09T04:12:42.331Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Aug_01_Zilliz_Cloud_a_Fully_Managed_Vector_Database_That_Minimizes_Users_Costs_for_Building_AI_Apps_e155c1f6f1.png","belong":"learn","authorNames":["Frank Liu"]},{"id":"learn-35","title":"Making Machine Learning More Accessible for Application Developers","image":{"id":6374,"url":"https://assets.zilliz.com/Apr_11_GPT_Cache_An_open_source_library_to_cache_responses_from_LLM_queries_5ff1401aad.png"},"display_time":"Apr 09, 2022","url":"making-machine-learning-more-accessible-for-application-developers","abstract":"Learn how Towhee, an open-source embedding pipeline, supercharges the app development that requires embeddings and other ML tasks.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":3,"name":"Frank Liu","author_tags":"Director of Operations \u0026 ML Architect at Zilliz","published_at":"2021-12-23T11:08:08.015Z","created_by":18,"updated_by":18,"created_at":"2021-12-23T10:40:59.821Z","updated_at":"2023-04-21T22:30:10.416Z","home_page":"GitHub","home_page_link":"https://github.com/fzliu","self_intro":"Frank Liu is the Director of Operations \u0026 ML Architect at Zilliz, where he serves as a maintainer for the Towhee open-source project. Prior to Zilliz, Frank co-founded Orion Innovations, an ML-powered indoor positioning startup based in Shanghai and worked as an ML engineer at Yahoo in San Francisco. In his free time, Frank enjoys playing chess, swimming, and powerlifting. Frank holds MS and BS degrees in Electrical Engineering from Stanford University. ","repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":11,"localizations":[{"id":423,"locale":"ja-JP","published_at":"2022-05-09T08:07:02.755Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Apr_11_GPT_Cache_An_open_source_library_to_cache_responses_from_LLM_queries_5ff1401aad.png","belong":"learn","authorNames":["Frank Liu"]},{"id":"learn-14","title":"Accelerating Similarity Search on Really Big Data with Vector Indexing (Part II)","image":{"id":6373,"url":"https://assets.zilliz.com/Apr_07_New_Feature_Spotlight_Backup_and_Restore_b5cf1a1a33.png"},"display_time":"Mar 17, 2022","url":"index-overview-part-2","abstract":"Discover how indexes dramatically accelerate vector similarity search, different types of indexes, and how to choose the right index for your next AI application.\n","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":13,"name":"Angela Ni","author_tags":"Technical Writer at Zilliz","published_at":"2022-03-17T08:59:36.247Z","created_by":18,"updated_by":18,"created_at":"2022-03-17T08:59:33.931Z","updated_at":"2024-07-03T07:58:47.615Z","home_page":"LinkedIn","home_page_link":"https://www.linkedin.com/in/yiyun-n-2aa713163/","self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Angela Ni, Technical Writer at Zilliz","locale":"en"}],"read_time":9,"localizations":[{"id":414,"locale":"ja-JP","published_at":"2022-03-17T09:22:50.830Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Apr_07_New_Feature_Spotlight_Backup_and_Restore_b5cf1a1a33.png","belong":"learn","authorNames":["Angela Ni"]},{"id":"blog-87","title":"Manage Your Milvus Vector Database with One-click Simplicity","image":{"id":1018,"url":"https://assets.zilliz.com/Zilliz_Blog_8_029944fa70.png"},"display_time":"Mar 10, 2022","deploy_time":null,"url":"manage-your-milvus-vector-database-with-one-click-simplicity","abstract":"Zilliz launched Attu - a GUI tool designed specifically for Milvus 2.0. You can use the intuitive Attu web console to manage your vector database in a simple and straightforward manner.","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":35,"name":"Zilliz","author_tags":"Zilliz team","published_at":"2022-06-15T02:33:23.458Z","created_by":18,"updated_by":18,"created_at":"2022-06-15T02:26:19.780Z","updated_at":"2024-07-03T06:58:08.413Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":4,"localizations":[{"id":1112,"locale":"ja-JP","published_at":"2022-03-10T07:10:53.784Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Zilliz_Blog_8_029944fa70.png","belong":"blog","authorNames":["Zilliz"]},{"id":"learn-12","title":"Supercharged Semantic Similarity Search in Production","image":{"id":6372,"url":"https://assets.zilliz.com/Apr_11_GPT_Cache_An_open_source_library_to_cache_responses_from_LLM_queries_1_c24c4cd252.png"},"display_time":"Feb 28, 2022","url":"supercharged-semantic-similarity-search-in-production","abstract":"Building a Blazing Fast, Highly Scalable Text-to-Image Search with CLIP embeddings and Milvus, the most advanced open-source vector database.","tags":[{"id":1,"name":"Case Study","published_at":"2021-01-15T10:34:37.316Z","created_by":18,"updated_by":18,"created_at":"2021-01-15T10:34:34.857Z","updated_at":"2021-01-25T10:31:22.499Z","locale":"en"}],"authors":[{"id":11,"name":"Marie Stephen Leo","author_tags":"Director of Data Science APAC @Edelman DXI","published_at":"2022-01-24T09:40:38.616Z","created_by":18,"updated_by":18,"created_at":"2022-01-24T08:38:13.463Z","updated_at":"2022-01-25T09:07:33.760Z","home_page":"GitHub","home_page_link":"https://github.com/stephenleo","self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":11,"localizations":[{"id":318,"locale":"ja-JP","published_at":"2022-02-28T09:48:32.142Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Apr_11_GPT_Cache_An_open_source_library_to_cache_responses_from_LLM_queries_1_c24c4cd252.png","belong":"learn","authorNames":["Marie Stephen Leo"]},{"id":"learn-11","title":"Powering Semantic Similarity Search in Computer Vision with State of the Art Embeddings","image":{"id":6371,"url":"https://assets.zilliz.com/May_15_Webinar_Recap_f3aa0233db.png"},"display_time":"Jan 24, 2022","url":"embedding-generation","abstract":"Discover how to extract useful information from unstructured data sources in a scalable manner using embeddings.","tags":[{"id":1,"name":"Case Study","published_at":"2021-01-15T10:34:37.316Z","created_by":18,"updated_by":18,"created_at":"2021-01-15T10:34:34.857Z","updated_at":"2021-01-25T10:31:22.499Z","locale":"en"}],"authors":[{"id":11,"name":"Marie Stephen Leo","author_tags":"Director of Data Science APAC @Edelman DXI","published_at":"2022-01-24T09:40:38.616Z","created_by":18,"updated_by":18,"created_at":"2022-01-24T08:38:13.463Z","updated_at":"2022-01-25T09:07:33.760Z","home_page":"GitHub","home_page_link":"https://github.com/stephenleo","self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":22,"localizations":[{"id":440,"locale":"ja-JP","published_at":"2022-01-24T08:38:39.855Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/May_15_Webinar_Recap_f3aa0233db.png","belong":"learn","authorNames":["Marie Stephen Leo"]},{"id":"blog-83","title":"Zilliz Triumphed in Billion-Scale ANN Search Challenge of NeurIPS 2021","image":{"id":1020,"url":"https://assets.zilliz.com/Zilliz_Blog_13_6e624d39cd.png"},"display_time":"Jan 21, 2022","deploy_time":null,"url":"zilliz-triumphed-Neurips-2021","abstract":"Zilliz team has won the first place in the Disk-based ANN Search track in NeurIPS 2021. ","tags":[{"id":4,"name":"Company","published_at":"2021-01-21T02:28:23.551Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:20.676Z","updated_at":"2021-01-21T02:28:23.824Z","locale":"en"}],"authors":[{"id":35,"name":"Zilliz","author_tags":"Zilliz team","published_at":"2022-06-15T02:33:23.458Z","created_by":18,"updated_by":18,"created_at":"2022-06-15T02:26:19.780Z","updated_at":"2024-07-03T06:58:08.413Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":2,"localizations":[{"id":877,"locale":"ja-JP","published_at":"2022-01-21T10:02:47.184Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Zilliz_Blog_13_6e624d39cd.png","belong":"blog","authorNames":["Zilliz"]},{"id":"learn-10","title":"Building an Intelligent Video Deduplication System Powered by Vector Similarity Search","image":{"id":1727,"url":"https://assets.zilliz.com/Building_Intelligent_Video_Deduplication_661f45772e.png"},"display_time":"Jan 05, 2022","url":"video-deduplication-system","abstract":"Learn how to use the Milvus vector database to build an automated solution for identifying and filtering out duplicate video content from archive storage.","tags":[{"id":1,"name":"Case Study","published_at":"2021-01-15T10:34:37.316Z","created_by":18,"updated_by":18,"created_at":"2021-01-15T10:34:34.857Z","updated_at":"2021-01-25T10:31:22.499Z","locale":"en"}],"authors":[{"id":9,"name":"Zhaoxing Li","author_tags":"Senior Engineer at Opera News","published_at":"2021-12-27T07:26:21.586Z","created_by":18,"updated_by":18,"created_at":"2021-12-27T07:26:20.126Z","updated_at":"2022-01-19T02:33:36.870Z","home_page":"GitHub","home_page_link":"https://github.com/YEXINGZHE54","self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":7,"localizations":[{"id":342,"locale":"ja-JP","published_at":"2022-01-05T03:10:32.139Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Building_Intelligent_Video_Deduplication_661f45772e.png","belong":"learn","authorNames":["Zhaoxing Li"]},{"id":"blog-82","title":"Get started with Milvus_CLI","image":{"id":1021,"url":"https://assets.zilliz.com/Zilliz_Blog_15_6568571249.png"},"display_time":"Dec 31, 2021","deploy_time":null,"url":"get-started-with-milvus-cli","abstract":"This article introduces Milvus_CLI and helps you complete common tasks.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":35,"name":"Zilliz","author_tags":"Zilliz team","published_at":"2022-06-15T02:33:23.458Z","created_by":18,"updated_by":18,"created_at":"2022-06-15T02:26:19.780Z","updated_at":"2024-07-03T06:58:08.413Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":3,"localizations":[{"id":1142,"locale":"ja-JP","published_at":"2021-12-31T08:03:17.676Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Zilliz_Blog_15_6568571249.png","belong":"blog","authorNames":["Zilliz"]},{"id":"learn-9","title":" How to Best Fit Filtering into Vector Similarity Search?","image":{"id":6370,"url":"https://assets.zilliz.com/How_to_Best_Fit_Filtering_into_Vector_Similarity_Search_98058d8ca7.png"},"display_time":"Dec 31, 2021","url":"attribute-filtering","abstract":"Learn about three types of attribute filtering in vector similarity search and explore our optimized solution to improve the efficiency of similarity search.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":10,"name":"Yihua Mo","author_tags":"Senior Software Engineer at Zilliz","published_at":"2021-12-29T03:49:07.331Z","created_by":18,"updated_by":18,"created_at":"2021-12-29T03:49:04.818Z","updated_at":"2024-07-18T15:58:29.775Z","home_page":"GitHub","home_page_link":"https://github.com/yhmo","self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":"Yihua Mo is a Senior Software Engineer at Zilliz.","locale":"en"}],"read_time":8,"localizations":[{"id":296,"locale":"ja-JP","published_at":"2021-12-31T02:51:08.909Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/How_to_Best_Fit_Filtering_into_Vector_Similarity_Search_98058d8ca7.png","belong":"learn","authorNames":["Yihua Mo"]},{"id":"learn-8","title":"An Intelligent Similarity Search System for Graphical Designers","image":{"id":6368,"url":"https://assets.zilliz.com/An_Intelligent_Similarity_Search_System_for_Graphical_Designers_bbe0a63a5f.png"},"display_time":"Dec 24, 2021","url":"vector-similarity-search-graphical-design","abstract":"Learn how to use a vector database to build your own similarity search system for design assets that could help designers ramp up their creative production.\n","tags":[{"id":1,"name":"Case Study","published_at":"2021-01-15T10:34:37.316Z","created_by":18,"updated_by":18,"created_at":"2021-01-15T10:34:34.857Z","updated_at":"2021-01-25T10:31:22.499Z","locale":"en"}],"authors":[{"id":7,"name":"James Zhang","author_tags":"Algorithm Engineer at Meetsocial Group","published_at":"2021-12-27T03:37:17.852Z","created_by":18,"updated_by":18,"created_at":"2021-12-27T03:37:16.774Z","updated_at":"2022-02-14T08:48:53.578Z","home_page":"GitHub","home_page_link":"https://github.com/zhangcong2711","self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":4,"localizations":[{"id":333,"locale":"ja-JP","published_at":"2021-12-24T07:58:43.455Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/An_Intelligent_Similarity_Search_System_for_Graphical_Designers_bbe0a63a5f.png","belong":"learn","authorNames":["James Zhang"]},{"id":"learn-7","title":"How to Make Online Shopping More Intelligent with Image Similarity Search?","image":{"id":6367,"url":"https://assets.zilliz.com/How_to_Make_Online_Shopping_More_Intelligent_with_Image_Similarity_Search_9f29d0dafb.png"},"display_time":"Dec 21, 2021","url":"online-shopping-image-similarity-search","abstract":"Learn how to build an intelligent image similarity search system for online shopping using a vector database.","tags":[{"id":1,"name":"Case Study","published_at":"2021-01-15T10:34:37.316Z","created_by":18,"updated_by":18,"created_at":"2021-01-15T10:34:34.857Z","updated_at":"2021-01-25T10:31:22.499Z","locale":"en"}],"authors":[{"id":6,"name":"Jessi Ji","author_tags":"Java Developer at VOVA","published_at":"2021-12-27T03:36:35.683Z","created_by":18,"updated_by":18,"created_at":"2021-12-27T03:36:34.564Z","updated_at":"2022-02-14T08:51:34.147Z","home_page":"GitHub","home_page_link":"https://github.com/axin3892","self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":4,"localizations":[{"id":315,"locale":"ja-JP","published_at":"2021-12-22T08:49:28.432Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/How_to_Make_Online_Shopping_More_Intelligent_with_Image_Similarity_Search_9f29d0dafb.png","belong":"learn","authorNames":["Jessi Ji"]},{"id":"learn-6","title":"Proximity Graph-based Approximate Nearest Neighbor Search","image":{"id":6366,"url":"https://assets.zilliz.com/Proximity_Graph_based_Approximate_Nearest_Neighbor_Search_732a852522.png"},"display_time":"Dec 20, 2021","url":"pg-based-anns","abstract":"Learn what PG-based ANNS is and how to optimize the algorithm to achieve a trade-off between search accuracy and efficiency.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":2,"name":"Mengzhao Wang","author_tags":"Master of Computer Science at Hangzhou Dianzi University","published_at":"2021-12-17T07:04:25.165Z","created_by":18,"updated_by":18,"created_at":"2021-12-17T07:04:23.939Z","updated_at":"2022-02-14T08:59:37.379Z","home_page":"GitHub","home_page_link":"https://github.com/whenever5225","self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":11,"localizations":[{"id":297,"locale":"ja-JP","published_at":"2021-12-22T08:17:48.800Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Proximity_Graph_based_Approximate_Nearest_Neighbor_Search_732a852522.png","belong":"learn","authorNames":["Mengzhao Wang"]},{"id":"learn-4","title":"How to Make Your Wardrobe Sustainable with Vector Similarity Search","image":{"id":6365,"url":"https://assets.zilliz.com/How_to_Make_Your_Wardrobe_Sustainable_with_Vector_Similarity_Search_1137013732.png"},"display_time":"Dec 17, 2021","url":"vector-similarity-search-and-fashion","abstract":"Learn how to use a vector database to build an intelligent outfit recommendation app that can search for similar garments.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":5,"name":"Yu Fang","author_tags":"AI Scientist at Mozat","published_at":"2021-12-27T03:34:56.713Z","created_by":18,"updated_by":18,"created_at":"2021-12-27T03:34:55.446Z","updated_at":"2022-02-14T08:59:54.035Z","home_page":"GitHub","home_page_link":"https://github.com/fangyu1006","self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":5,"localizations":[{"id":314,"locale":"ja-JP","published_at":"2021-12-17T06:45:48.763Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/How_to_Make_Your_Wardrobe_Sustainable_with_Vector_Similarity_Search_1137013732.png","belong":"learn","authorNames":["Yu Fang"]},{"id":"learn-3","title":"HM-ANN Efficient Billion-Point Nearest Neighbor Search on Heterogeneous Memory","image":{"id":6364,"url":"https://assets.zilliz.com/HM_ANN_Efficient_Billion_Point_Nearest_Neighbor_Search_on_Heterogeneous_Memory_e90c8a7da4.png"},"display_time":"Dec 10, 2021","url":"hm-ann-efficient-billion-point-nearest-neighbor-search-on-heterogeneous-memory","abstract":"An introduction to a novel HM-ANN algorithm for graph-based similarity search, which offers distinct advantages over existing ANN search solutions.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":4,"name":"Jigao Luo","author_tags":"Researcher at Zilliz","published_at":"2021-12-24T08:30:52.304Z","created_by":18,"updated_by":18,"created_at":"2021-12-24T08:30:15.659Z","updated_at":"2022-02-14T08:54:24.128Z","home_page":"GitHub","home_page_link":"https://github.com/cakebytheoceanLuo","self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":8,"localizations":[{"id":358,"locale":"ja-JP","published_at":"2021-12-10T10:31:22.442Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/HM_ANN_Efficient_Billion_Point_Nearest_Neighbor_Search_on_Heterogeneous_Memory_e90c8a7da4.png","belong":"learn","authorNames":["Jigao Luo"]},{"id":"learn-2","title":"Image-based Trademark Similarity Search System: A Smarter Solution to IP Protection","image":{"id":6363,"url":"https://assets.zilliz.com/Image_based_Trademark_Similarity_Search_System_A_Smarter_Solution_to_IP_Protection_397176ecfd.png"},"display_time":"Dec 06, 2021","url":"image-based-trademark-similarity-search-system","abstract":"Learn how to use a vector database to build your own trademark image similarity search system that could save you from intellectual property lawsuits.","tags":[{"id":1,"name":"Case Study","published_at":"2021-01-15T10:34:37.316Z","created_by":18,"updated_by":18,"created_at":"2021-01-15T10:34:34.857Z","updated_at":"2021-01-25T10:31:22.499Z","locale":"en"}],"authors":[{"id":8,"name":"Jie Wang","author_tags":"Data Mining Algorithm Engineer","published_at":"2021-12-27T03:38:04.489Z","created_by":18,"updated_by":18,"created_at":"2021-12-27T03:38:03.324Z","updated_at":"2022-01-28T03:34:34.932Z","home_page":"GitHub","home_page_link":"https://github.com/wangjierookie","self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":5,"localizations":[{"id":313,"locale":"ja-JP","published_at":"2021-12-10T10:31:27.682Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Image_based_Trademark_Similarity_Search_System_A_Smarter_Solution_to_IP_Protection_397176ecfd.png","belong":"learn","authorNames":["Jie Wang"]},{"id":"blog-80","title":"Accelerating Candidate Generation in Recommender Systems Using Milvus paired with PaddlePaddle","image":{"id":487,"url":"https://assets.zilliz.com/1_d2090c29c8.png"},"display_time":"Nov 26, 2021","deploy_time":null,"url":"accelerating-candidate-generation-in-recommender-systems-using-milvus-paired-with-paddlepaddle","abstract":"the minimal workflow of a recommender system","tags":[{"id":1,"name":"Case Study","published_at":"2021-01-15T10:34:37.316Z","created_by":18,"updated_by":18,"created_at":"2021-01-15T10:34:34.857Z","updated_at":"2021-01-25T10:31:22.499Z","locale":"en"}],"authors":[{"id":35,"name":"Zilliz","author_tags":"Zilliz team","published_at":"2022-06-15T02:33:23.458Z","created_by":18,"updated_by":18,"created_at":"2022-06-15T02:26:19.780Z","updated_at":"2024-07-03T06:58:08.413Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":12,"localizations":[{"id":1366,"locale":"ja-JP","published_at":"2021-11-26T07:13:42.706Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/1_d2090c29c8.png","belong":"blog","authorNames":["Zilliz"]},{"id":"blog-78","title":"Frustrated with New Data? Our Vector Database can Help","image":{"id":504,"url":"https://assets.zilliz.com/istockphoto_1286642964_170667a_c2ff2976bd.jpeg"},"display_time":"Nov 08, 2021","deploy_time":null,"url":"frustrated-with-new-data-our-vector-database-can-help","abstract":"In the era of Big Data, what database technologies and applications will come into the limelight? What will be the next game-changer?","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":35,"name":"Zilliz","author_tags":"Zilliz team","published_at":"2022-06-15T02:33:23.458Z","created_by":18,"updated_by":18,"created_at":"2022-06-15T02:26:19.780Z","updated_at":"2024-07-03T06:58:08.413Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":13,"localizations":[{"id":943,"locale":"ja-JP","published_at":"2021-11-08T10:36:44.418Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/istockphoto_1286642964_170667a_c2ff2976bd.jpeg","belong":"blog","authorNames":["Zilliz"]},{"id":"blog-84","title":"Zilliz CEO Shared Start-up Experience in 2021 SYNC","image":{"id":655,"url":"https://assets.zilliz.com/SYNC_2021_16c77d7fb3.png"},"display_time":"Oct 30, 2021","deploy_time":null,"url":"zilliz-ceo-shared-start-up-experience","abstract":"Withdrew from Oracle to zero in on unstructured data processing\n","tags":[{"id":4,"name":"Company","published_at":"2021-01-21T02:28:23.551Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:20.676Z","updated_at":"2021-01-21T02:28:23.824Z","locale":"en"}],"authors":[{"id":35,"name":"Zilliz","author_tags":"Zilliz team","published_at":"2022-06-15T02:33:23.458Z","created_by":18,"updated_by":18,"created_at":"2022-06-15T02:26:19.780Z","updated_at":"2024-07-03T06:58:08.413Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":2,"localizations":[{"id":882,"locale":"ja-JP","published_at":"2022-01-28T08:18:33.349Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/SYNC_2021_16c77d7fb3.png","belong":"blog","authorNames":["Zilliz"]},{"id":"blog-71","title":"Building a Video Analysis System with Milvus Vector Database","image":{"id":1144,"url":"https://assets.zilliz.com/video_analysis_engine_cover_7ad180bc9a.jpg"},"display_time":"Oct 09, 2021","deploy_time":null,"url":"milvus-helps-analyze-videos-intelligently","abstract":"Learn how Milvus powers the AI analysis of video content.","tags":[{"id":1,"name":"Case Study","published_at":"2021-01-15T10:34:37.316Z","created_by":18,"updated_by":18,"created_at":"2021-01-15T10:34:34.857Z","updated_at":"2021-01-25T10:31:22.499Z","locale":"en"}],"authors":[{"id":72,"name":"Silvia Chen","author_tags":"Software Engineer","published_at":"2023-06-26T06:10:36.495Z","created_by":18,"updated_by":18,"created_at":"2023-06-26T06:10:34.755Z","updated_at":"2024-07-18T16:00:04.960Z","home_page":"GitHub","home_page_link":"https://github.com/shiyu22","self_intro":"Software Engineer","repost_to_medium":null,"repost_state":null,"meta_description":"Silvia Chen, Software Engineer at Zilliz","locale":"en"}],"read_time":6,"localizations":[{"id":1067,"locale":"ja-JP","published_at":"2021-10-09T10:35:17.337Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/video_analysis_engine_cover_7ad180bc9a.jpg","belong":"blog","authorNames":["Silvia Chen"]},{"id":"blog-70","title":"Combine AI Models for Image Search using ONNX and Milvus","image":{"id":503,"url":"https://assets.zilliz.com/istockphoto_1224971139_170667a_2ad3e58b46.jpeg"},"display_time":"Sep 26, 2021","deploy_time":null,"url":"combine-ai-models-for-image-search-using-onnx-and-milvus","abstract":"Use ONNX to process multiple models of CV (computer vision), and combine multiple models with Milvus for similar vector retrieval to get similar images.","tags":[{"id":1,"name":"Case Study","published_at":"2021-01-15T10:34:37.316Z","created_by":18,"updated_by":18,"created_at":"2021-01-15T10:34:34.857Z","updated_at":"2021-01-25T10:31:22.499Z","locale":"en"}],"authors":[{"id":1,"name":"Zilliz","author_tags":"Vector database","published_at":"2021-12-14T06:36:41.397Z","created_by":18,"updated_by":18,"created_at":"2021-12-14T06:28:27.154Z","updated_at":"2023-04-11T16:54:05.275Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":4,"localizations":[{"id":1649,"locale":"pt","published_at":"2021-09-26T02:55:18.371Z"},{"id":1646,"locale":"es","published_at":"2021-09-26T02:55:18.371Z"},{"id":1652,"locale":"ru","published_at":"2021-09-26T02:55:18.371Z"},{"id":1661,"locale":"fr","published_at":"2021-09-26T02:55:18.371Z"},{"id":1655,"locale":"ko","published_at":"2021-09-26T02:55:18.371Z"},{"id":876,"locale":"ja-JP","published_at":"2021-09-26T02:55:18.371Z"},{"id":1643,"locale":"de","published_at":"2021-09-26T02:55:18.371Z"},{"id":1658,"locale":"it","published_at":"2021-09-26T02:55:18.371Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/istockphoto_1224971139_170667a_2ad3e58b46.jpeg","belong":"blog","authorNames":["Zilliz"]},{"id":"blog-69","title":"DiskANN: A Disk-based ANNS Solution with High Recall and High QPS on Billion-scale Dataset","image":{"id":402,"url":"https://assets.zilliz.com/1_10cebc1e50.png"},"display_time":"Sep 24, 2021","deploy_time":null,"url":"diskann-a-disk-based-anns-solution-with-high-recall-and-high-qps-on-billion-scale-dataset","abstract":"DiskANN is an advanced method for index building and searching on a billion-scale dataset using a single machine with 64GB of RAM and a large enough SSD. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":35,"name":"Zilliz","author_tags":"Zilliz team","published_at":"2022-06-15T02:33:23.458Z","created_by":18,"updated_by":18,"created_at":"2022-06-15T02:26:19.780Z","updated_at":"2024-07-03T06:58:08.413Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":17,"localizations":[{"id":1349,"locale":"ja-JP","published_at":"2021-09-24T10:55:37.980Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/1_10cebc1e50.png","belong":"blog","authorNames":["Zilliz"]},{"id":"blog-68","title":"DNA Sequence Classification based on Milvus","image":{"id":401,"url":"https://assets.zilliz.com/11111_5d089adf08.png"},"display_time":"Sep 06, 2021","deploy_time":null,"url":"dna-sequence-classification-based-on-milvus","abstract":"Use Milvus, an open-source vector database, to recognize gene families of DNA sequences. Less space but higher accuracy.","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"},{"id":1,"name":"Case Study","published_at":"2021-01-15T10:34:37.316Z","created_by":18,"updated_by":18,"created_at":"2021-01-15T10:34:34.857Z","updated_at":"2021-01-25T10:31:22.499Z","locale":"en"}],"authors":[{"id":35,"name":"Zilliz","author_tags":"Zilliz team","published_at":"2022-06-15T02:33:23.458Z","created_by":18,"updated_by":18,"created_at":"2022-06-15T02:26:19.780Z","updated_at":"2024-07-03T06:58:08.413Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":6,"localizations":[{"id":1132,"locale":"ja-JP","published_at":"2021-09-06T06:02:27.431Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/11111_5d089adf08.png","belong":"blog","authorNames":["Zilliz"]},{"id":"blog-85","title":"Zilliz attended VLDB Workshop 2021","image":{"id":1170,"url":"https://assets.zilliz.com/Zilliz_Blog_43_ef664790d5.png"},"display_time":"Aug 27, 2021","deploy_time":null,"url":"zilliz-attended-vldb-workshop-2021","abstract":"Applied ML \u0026 AI for Database Systems and Application","tags":[{"id":4,"name":"Company","published_at":"2021-01-21T02:28:23.551Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:20.676Z","updated_at":"2021-01-21T02:28:23.824Z","locale":"en"}],"authors":[{"id":35,"name":"Zilliz","author_tags":"Zilliz team","published_at":"2022-06-15T02:33:23.458Z","created_by":18,"updated_by":18,"created_at":"2022-06-15T02:26:19.780Z","updated_at":"2024-07-03T06:58:08.413Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":2,"localizations":[{"id":1003,"locale":"ja-JP","published_at":"2022-01-28T09:10:24.813Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Zilliz_Blog_43_ef664790d5.png","belong":"blog","authorNames":["Zilliz"]},{"id":"blog-67","title":"Paper Reading｜HM-ANN: When ANNS Meets Heterogeneous Memory","image":{"id":190,"url":"https://assets.zilliz.com/blog_cover_4a9807b9e0.png"},"display_time":"Aug 26, 2021","deploy_time":null,"url":"paper-reading-hm-ann-when-anns-meets-heterogeneous-memory","abstract":"The HM-ANN algorithm for graph-based similarity search offers distinct advantages over existing state-of-the-art ANN search solutions.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":1,"name":"Zilliz","author_tags":"Vector database","published_at":"2021-12-14T06:36:41.397Z","created_by":18,"updated_by":18,"created_at":"2021-12-14T06:28:27.154Z","updated_at":"2023-04-11T16:54:05.275Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":8,"localizations":[{"id":1139,"locale":"ja-JP","published_at":"2021-08-26T07:18:47.925Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/blog_cover_4a9807b9e0.png","belong":"blog","authorNames":["Zilliz"]},{"id":"blog-65","title":"Audio Retrieval Based on Milvus","image":{"id":370,"url":"https://assets.zilliz.com/blog_audio_search_56b990cee5.jpg"},"display_time":"Jul 27, 2021","deploy_time":null,"url":"audio-retrieval-based-on-milvus","abstract":"Create an audio retrieval system using Milvus, an open-source vector database. Classify and analyze sound data in real time.","tags":[{"id":1,"name":"Case Study","published_at":"2021-01-15T10:34:37.316Z","created_by":18,"updated_by":18,"created_at":"2021-01-15T10:34:34.857Z","updated_at":"2021-01-25T10:31:22.499Z","locale":"en"}],"authors":[{"id":72,"name":"Silvia Chen","author_tags":"Software Engineer","published_at":"2023-06-26T06:10:36.495Z","created_by":18,"updated_by":18,"created_at":"2023-06-26T06:10:34.755Z","updated_at":"2024-07-18T16:00:04.960Z","home_page":"GitHub","home_page_link":"https://github.com/shiyu22","self_intro":"Software Engineer","repost_to_medium":null,"repost_state":null,"meta_description":"Silvia Chen, Software Engineer at Zilliz","locale":"en"}],"read_time":5,"localizations":[{"id":1350,"locale":"ja-JP","published_at":"2021-07-27T03:05:57.524Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/blog_audio_search_56b990cee5.jpg","belong":"blog","authorNames":["Silvia Chen"]},{"id":"blog-55","title":"Quickly Test and Deploy Vector Search Solutions with the Milvus 2.0 Bootcamp","image":{"id":319,"url":"https://assets.zilliz.com/cover_80db9ee49c.png"},"display_time":"Jul 13, 2021","deploy_time":null,"url":"test-and-deploy-vector-search-solutions-milvus-bootcamp","abstract":"A new and improved Milvus bootcamp offers updated guides and easier to follow code examples. Discover how to create your own similarity search solutions with the world's most advanced vector database.","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":35,"name":"Zilliz","author_tags":"Zilliz team","published_at":"2022-06-15T02:33:23.458Z","created_by":18,"updated_by":18,"created_at":"2022-06-15T02:26:19.780Z","updated_at":"2024-07-03T06:58:08.413Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":5,"localizations":[{"id":1371,"locale":"ja-JP","published_at":"2021-07-15T03:05:45.742Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/cover_80db9ee49c.png","belong":"blog","authorNames":["Zilliz"]},{"id":"blog-54","title":"Building a Milvus Cluster Based on JuiceFS","image":{"id":323,"url":"https://assets.zilliz.com/Juice_FS_blog_cover_851cc9e726.jpg"},"display_time":"Jun 15, 2021","deploy_time":null,"url":"building-a-milvus-cluster-based-on-juicefs","abstract":"Learn how to build a Milvus cluster based on JuiceFS, a shared file system designed for cloud-native environments.","tags":[{"id":1,"name":"Case Study","published_at":"2021-01-15T10:34:37.316Z","created_by":18,"updated_by":18,"created_at":"2021-01-15T10:34:34.857Z","updated_at":"2021-01-25T10:31:22.499Z","locale":"en"}],"authors":[{"id":35,"name":"Zilliz","author_tags":"Zilliz team","published_at":"2022-06-15T02:33:23.458Z","created_by":18,"updated_by":18,"created_at":"2022-06-15T02:26:19.780Z","updated_at":"2024-07-03T06:58:08.413Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":5,"localizations":[{"id":1111,"locale":"ja-JP","published_at":"2021-12-15T07:03:32.626Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Juice_FS_blog_cover_851cc9e726.jpg","belong":"blog","authorNames":["Zilliz"]},{"id":"blog-52","title":"Accelerating Compilation 2.5X with Dependency Decoupling \u0026 Testing Containerization","image":{"id":306,"url":"https://assets.zilliz.com/cover_20e3cddb96.jpeg"},"display_time":"May 28, 2021","deploy_time":null,"url":"accelerating-compilation-with-dependency-decoupling-and-testing-containerization","abstract":"Discover how dependency decoupling \u0026 containerization can be used to accelerate compilation times for large-scale AI and MLOps projects. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"},{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"}],"authors":[{"id":35,"name":"Zilliz","author_tags":"Zilliz team","published_at":"2022-06-15T02:33:23.458Z","created_by":18,"updated_by":18,"created_at":"2022-06-15T02:26:19.780Z","updated_at":"2024-07-03T06:58:08.413Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":7,"localizations":[{"id":1374,"locale":"ja-JP","published_at":"2021-12-10T03:56:19.120Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/cover_20e3cddb96.jpeg","belong":"blog","authorNames":["Zilliz"]},{"id":"blog-50","title":"Accelerating AI in Finance with Milvus, an Open-Source Vector Database","image":{"id":501,"url":"https://assets.zilliz.com/tyler_franta_ius_J25i_Yu1c_unsplash_21b1530578.jpg"},"display_time":"May 19, 2021","deploy_time":null,"url":"ai-in-finance","abstract":"The finance industry has long leveraged open-source software to extract insights from large, unstructured datasets. Discover how Milvus, an open-source vector database, can power AI applications including banking chatbots, recommender systems, and semantic text mining. ","tags":[{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en"},{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":35,"name":"Zilliz","author_tags":"Zilliz team","published_at":"2022-06-15T02:33:23.458Z","created_by":18,"updated_by":18,"created_at":"2022-06-15T02:26:19.780Z","updated_at":"2024-07-03T06:58:08.413Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":3,"localizations":[{"id":866,"locale":"ja-JP","published_at":"2021-05-19T03:41:20.776Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/tyler_franta_ius_J25i_Yu1c_unsplash_21b1530578.jpg","belong":"blog","authorNames":["Zilliz"]},{"id":"blog-49","title":"Building a Search by Image Shopping Experience with VOVA and Milvus","image":{"id":287,"url":"https://assets.zilliz.com/vova_thumbnail_db2d6c0c9c.jpg"},"display_time":"May 13, 2021","deploy_time":null,"url":"building-a-search-by-image-shopping-experience-with-vova-and-milvus","abstract":"VOVA, an emerging e-commerce platform, prioritizes convenient and positive user experiences. Learn how the company used Milvus to build an image search tool to help shoppers find items they encounter in real life.","tags":[{"id":1,"name":"Case Study","published_at":"2021-01-15T10:34:37.316Z","created_by":18,"updated_by":18,"created_at":"2021-01-15T10:34:34.857Z","updated_at":"2021-01-25T10:31:22.499Z","locale":"en"}],"authors":[{"id":35,"name":"Zilliz","author_tags":"Zilliz team","published_at":"2022-06-15T02:33:23.458Z","created_by":18,"updated_by":18,"created_at":"2022-06-15T02:26:19.780Z","updated_at":"2024-07-03T06:58:08.413Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":4,"localizations":[{"id":1047,"locale":"ja-JP","published_at":"2021-05-13T08:44:05.528Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/vova_thumbnail_db2d6c0c9c.jpg","belong":"blog","authorNames":["Zilliz"]},{"id":"blog-47","title":"Making with Milvus: Detecting Android Viruses in Real Time for Trend Micro","image":{"id":325,"url":"https://assets.zilliz.com/blog_Trend_Micro_5c8ba3e2ce.jpg"},"display_time":"Apr 23, 2021","deploy_time":null,"url":"Making-with-Milvus-Detecting-Android-Viruses-in-Real-Time-for-Trend-Micro","abstract":"Learn how Milvus is used to mitigate threats to critical data and strengthen cybersecurity with real-time virus detection.","tags":[{"id":1,"name":"Case Study","published_at":"2021-01-15T10:34:37.316Z","created_by":18,"updated_by":18,"created_at":"2021-01-15T10:34:34.857Z","updated_at":"2021-01-25T10:31:22.499Z","locale":"en"}],"authors":[{"id":35,"name":"Zilliz","author_tags":"Zilliz team","published_at":"2022-06-15T02:33:23.458Z","created_by":18,"updated_by":18,"created_at":"2022-06-15T02:26:19.780Z","updated_at":"2024-07-03T06:58:08.413Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":7,"localizations":[{"id":1368,"locale":"ja-JP","published_at":"2021-04-23T06:46:13.732Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/blog_Trend_Micro_5c8ba3e2ce.jpg","belong":"blog","authorNames":["Zilliz"]},{"id":"blog-44","title":"Build Semantic Search at Speed","image":{"id":259,"url":"https://assets.zilliz.com/lucidworks_4753c98727.png"},"display_time":"Apr 19, 2021","deploy_time":null,"url":"build-semantic-search-at-speed-milvus-lucidworks","abstract":"Learn more about using semantic machine learning methodologies to power more relevant search results across your organization.","tags":[{"id":1,"name":"Case Study","published_at":"2021-01-15T10:34:37.316Z","created_by":18,"updated_by":18,"created_at":"2021-01-15T10:34:34.857Z","updated_at":"2021-01-25T10:31:22.499Z","locale":"en"}],"authors":[{"id":35,"name":"Zilliz","author_tags":"Zilliz team","published_at":"2022-06-15T02:33:23.458Z","created_by":18,"updated_by":18,"created_at":"2022-06-15T02:26:19.780Z","updated_at":"2024-07-03T06:58:08.413Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":5,"localizations":[{"id":1128,"locale":"ja-JP","published_at":"2021-04-19T07:32:50.416Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/lucidworks_4753c98727.png","belong":"blog","authorNames":["Zilliz"]},{"id":"blog-34","title":"How to Make 4 Popular AI Applications with Milvus","image":{"id":190,"url":"https://assets.zilliz.com/blog_cover_4a9807b9e0.png"},"display_time":"Apr 08, 2021","deploy_time":null,"url":"AI-applications-with-Milvus","abstract":"Milvus accelerates machine learning application development and machine learning operations (MLOps). With Milvus, you can rapidly develop a minimum viable product (MVP) while keeping costs at lower limits.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":35,"name":"Zilliz","author_tags":"Zilliz team","published_at":"2022-06-15T02:33:23.458Z","created_by":18,"updated_by":18,"created_at":"2022-06-15T02:26:19.780Z","updated_at":"2024-07-03T06:58:08.413Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":5,"localizations":[{"id":1357,"locale":"ja-JP","published_at":"2021-04-08T04:14:03.700Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/blog_cover_4a9807b9e0.png","belong":"blog","authorNames":["Zilliz"]},{"id":"blog-30","title":"Operationalize AI at Scale with Software 2.0, MLOps, and Milvus","image":{"id":506,"url":"https://assets.zilliz.com/istockphoto_1274437411_170667a_9f8ff4a4bf.jpeg"},"display_time":"Mar 31, 2021","deploy_time":null,"url":"Operationalize-AI-at-Scale-with-Software-MLOps-and-Milvus","abstract":"This article explains the concept of machine learning operations, or MLOps, and how Milvus advances MLOps programs of varying complexity.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":35,"name":"Zilliz","author_tags":"Zilliz team","published_at":"2022-06-15T02:33:23.458Z","created_by":18,"updated_by":18,"created_at":"2022-06-15T02:26:19.780Z","updated_at":"2024-07-03T06:58:08.413Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":6,"localizations":[{"id":1356,"locale":"ja-JP","published_at":"2021-03-31T09:51:38.653Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/istockphoto_1274437411_170667a_9f8ff4a4bf.jpeg","belong":"blog","authorNames":["Zilliz"]},{"id":"blog-25","title":"Making With Milvus: AI-Infused Proptech for Personalized Real Estate Search","image":{"id":326,"url":"https://assets.zilliz.com/blog_realistate_search_da4e8ee01d.jpg"},"display_time":"Mar 18, 2021","deploy_time":null,"url":"Making-With-Milvus-AI-Infused-Proptech-for-Personalized-Real-Estate-Search","abstract":"Beike wanted to create a personalized home search experience. Discover how they leveraged Milvus to build an intelligent real estate search platform capable of providing tailored recommendations in near real-time. ","tags":[{"id":1,"name":"Case Study","published_at":"2021-01-15T10:34:37.316Z","created_by":18,"updated_by":18,"created_at":"2021-01-15T10:34:34.857Z","updated_at":"2021-01-25T10:31:22.499Z","locale":"en"}],"authors":[{"id":35,"name":"Zilliz","author_tags":"Zilliz team","published_at":"2022-06-15T02:33:23.458Z","created_by":18,"updated_by":18,"created_at":"2022-06-15T02:26:19.780Z","updated_at":"2024-07-03T06:58:08.413Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":4,"localizations":[{"id":1373,"locale":"ja-JP","published_at":"2021-03-18T03:53:54.736Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/blog_realistate_search_da4e8ee01d.jpg","belong":"blog","authorNames":["Zilliz"]},{"id":"blog-23","title":"Extracting Event Highlights Using iYUNDONG Sports App","image":{"id":327,"url":"https://assets.zilliz.com/blog_iyundong_6db0f70ef4.jpg"},"display_time":"Mar 15, 2021","deploy_time":null,"url":"Extracting-Events-Highlights-Using-iYUNDONG-Sports-App","abstract":"iYUNDONG continually seeks to support its users with real-time image retrieval services. When it decided to develop its App, it chose Milvus to build its core image search system. Discover how Milvus, an open-source vector database, can help build an intelligent image retrieval system that can extract sport event highlights.","tags":[{"id":1,"name":"Case Study","published_at":"2021-01-15T10:34:37.316Z","created_by":18,"updated_by":18,"created_at":"2021-01-15T10:34:34.857Z","updated_at":"2021-01-25T10:31:22.499Z","locale":"en"}],"authors":[{"id":35,"name":"Zilliz","author_tags":"Zilliz team","published_at":"2022-06-15T02:33:23.458Z","created_by":18,"updated_by":18,"created_at":"2022-06-15T02:26:19.780Z","updated_at":"2024-07-03T06:58:08.413Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":5,"localizations":[{"id":1183,"locale":"ja-JP","published_at":"2021-03-15T03:41:30.983Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/blog_iyundong_6db0f70ef4.jpg","belong":"blog","authorNames":["Zilliz"]},{"id":"blog-21","title":"Making with Milvus: AI-Powered News Recommendation Inside Xiaomi's Mobile Browser","image":{"id":324,"url":"https://assets.zilliz.com/blog_Sohu_News_dec53d0814.jpg"},"display_time":"Mar 09, 2021","deploy_time":null,"url":"Making-with-Milvus-AI-Powered-News-Recommendation-Inside-Xiaomi-Mobile-Browser","abstract":"Discover how Xiaomi leveraged AI and Milvus to build an intelligent news recommendation system capable of finding the most relevant content for users of its mobile web browser. ","tags":[{"id":1,"name":"Case Study","published_at":"2021-01-15T10:34:37.316Z","created_by":18,"updated_by":18,"created_at":"2021-01-15T10:34:34.857Z","updated_at":"2021-01-25T10:31:22.499Z","locale":"en"}],"authors":[{"id":35,"name":"Zilliz","author_tags":"Zilliz team","published_at":"2022-06-15T02:33:23.458Z","created_by":18,"updated_by":18,"created_at":"2022-06-15T02:26:19.780Z","updated_at":"2024-07-03T06:58:08.413Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":6,"localizations":[{"id":1376,"locale":"ja-JP","published_at":"2021-03-17T02:30:34.750Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/blog_Sohu_News_dec53d0814.jpg","belong":"blog","authorNames":["Zilliz"]},{"id":"blog-40","title":"Building Personalized Recommender Systems with Milvus and PaddlePaddle","image":{"id":235,"url":"https://assets.zilliz.com/header_e6c4a8aee6.jpg"},"display_time":"Feb 24, 2021","deploy_time":null,"url":"building-personalized-recommender-systems-milvus-paddlepaddle","abstract":"How to build a deep learning powered recommender system","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":35,"name":"Zilliz","author_tags":"Zilliz team","published_at":"2022-06-15T02:33:23.458Z","created_by":18,"updated_by":18,"created_at":"2022-06-15T02:26:19.780Z","updated_at":"2024-07-03T06:58:08.413Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":5,"localizations":[{"id":1346,"locale":"ja-JP","published_at":"2021-04-09T23:12:34.209Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/header_e6c4a8aee6.jpg","belong":"blog","authorNames":["Zilliz"]},{"id":"blog-19","title":"How we used semantic search to make our search 10x smarter","image":{"id":98,"url":"https://assets.zilliz.com/Blog_How_we_used_semantic_search_to_make_our_search_10x_smarter_1_a7bac91379.jpeg"},"display_time":"Jan 29, 2021","deploy_time":null,"url":"How-we-used-semantic-search-to-make-our-search-10-x-smarter","abstract":"Learn how Tokopedia used semantic search to make their search 10x smarter","tags":[{"id":1,"name":"Case Study","published_at":"2021-01-15T10:34:37.316Z","created_by":18,"updated_by":18,"created_at":"2021-01-15T10:34:34.857Z","updated_at":"2021-01-25T10:31:22.499Z","locale":"en"}],"authors":[{"id":35,"name":"Zilliz","author_tags":"Zilliz team","published_at":"2022-06-15T02:33:23.458Z","created_by":18,"updated_by":18,"created_at":"2022-06-15T02:26:19.780Z","updated_at":"2024-07-03T06:58:08.413Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":5,"localizations":[{"id":837,"locale":"ja-JP","published_at":"2021-02-05T06:27:15.076Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/Blog_How_we_used_semantic_search_to_make_our_search_10x_smarter_1_a7bac91379.jpeg","belong":"blog","authorNames":["Zilliz"]},{"id":"blog-9","title":"Vector Similarity Search Hides in Plain View","image":{"id":78,"url":"https://assets.zilliz.com/plainview_703d8497ca.jpg"},"display_time":"Jan 05, 2021","deploy_time":null,"url":"Vector-Similarity-Search-Hides-in-Plain-View","abstract":"Artificial intelligence influences what we read, the things we buy, who we become friends with, and more everyday human behavior. A huge part of what makes many modern AI applications possible is vector similarity search. Understanding how this underlying technology works can help demystify AI, providing insight into what computer intelligence is really made of. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":35,"name":"Zilliz","author_tags":"Zilliz team","published_at":"2022-06-15T02:33:23.458Z","created_by":18,"updated_by":18,"created_at":"2022-06-15T02:26:19.780Z","updated_at":"2024-07-03T06:58:08.413Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":7,"localizations":[{"id":1370,"locale":"ja-JP","published_at":"2021-05-12T03:40:20.821Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/plainview_703d8497ca.jpg","belong":"blog","authorNames":["Zilliz"]},{"id":"blog-26","title":"Building a Graph-based Recommendation System with Milvus, PinSage, DGL, and MovieLens Datasets","image":{"id":147,"url":"https://assets.zilliz.com/thisisengineering_raeng_z3c_Mj_I6k_P_I_unsplash_2228b9411c.jpg"},"display_time":"Dec 01, 2020","deploy_time":null,"url":"graph-based-recommendation-system-with-milvus","abstract":"Discover how to build a recommender system with open-source tools and data.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":35,"name":"Zilliz","author_tags":"Zilliz team","published_at":"2022-06-15T02:33:23.458Z","created_by":18,"updated_by":18,"created_at":"2022-06-15T02:26:19.780Z","updated_at":"2024-07-03T06:58:08.413Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":6,"localizations":[{"id":1364,"locale":"ja-JP","published_at":"2021-03-30T21:41:08.582Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/thisisengineering_raeng_z3c_Mj_I6k_P_I_unsplash_2228b9411c.jpg","belong":"blog","authorNames":["Zilliz"]},{"id":"blog-15","title":"Making Sense of Unstructured Data with Zilliz Founder and CEO Charles Xie","image":{"id":67,"url":"https://assets.zilliz.com/CHAOGE_25f0d04bb8.jpg"},"display_time":"Nov 19, 2020","deploy_time":null,"url":"Making-Sense-of-Unstructured-Data-with-Zilliz-Founder-and-CEO-Charles-Xie","abstract":"An interview with Charles Xie on unstructured data ","tags":[{"id":4,"name":"Company","published_at":"2021-01-21T02:28:23.551Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:20.676Z","updated_at":"2021-01-21T02:28:23.824Z","locale":"en"}],"authors":[{"id":35,"name":"Zilliz","author_tags":"Zilliz team","published_at":"2022-06-15T02:33:23.458Z","created_by":18,"updated_by":18,"created_at":"2022-06-15T02:26:19.780Z","updated_at":"2024-07-03T06:58:08.413Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":4,"localizations":[{"id":1365,"locale":"ja-JP","published_at":"2021-01-21T09:34:44.214Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/CHAOGE_25f0d04bb8.jpg","belong":"blog","authorNames":["Zilliz"]},{"id":"blog-20","title":"ArtLens AI: Share Your View","image":{"id":463,"url":"https://assets.zilliz.com/blog_artlens_9ddbfc2de5.png"},"display_time":"Sep 11, 2020","deploy_time":null,"url":"ArtLens-AI-Share-Your-View","abstract":"Artificial Intelligence Offers a New Way to Find Your View in the CMA Collection","tags":[{"id":1,"name":"Case Study","published_at":"2021-01-15T10:34:37.316Z","created_by":18,"updated_by":18,"created_at":"2021-01-15T10:34:34.857Z","updated_at":"2021-01-25T10:31:22.499Z","locale":"en"}],"authors":[{"id":35,"name":"Zilliz","author_tags":"Zilliz team","published_at":"2022-06-15T02:33:23.458Z","created_by":18,"updated_by":18,"created_at":"2022-06-15T02:26:19.780Z","updated_at":"2024-07-03T06:58:08.413Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":4,"localizations":[{"id":1201,"locale":"ja-JP","published_at":"2021-02-20T06:55:00.939Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/blog_artlens_9ddbfc2de5.png","belong":"blog","authorNames":["Zilliz"]},{"id":"blog-28","title":"Item-based Collaborative Filtering for Music Recommender System","image":{"id":158,"url":"https://assets.zilliz.com/header_f8cea596d2.png"},"display_time":"Sep 07, 2020","deploy_time":null,"url":"music-recommender-system-item-based-collaborative-filtering-milvus","abstract":"Wanyin App is an AI-based music sharing community with an intention to encourage music sharing and make music composition easier for music enthusiasts.","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"},{"id":1,"name":"Case Study","published_at":"2021-01-15T10:34:37.316Z","created_by":18,"updated_by":18,"created_at":"2021-01-15T10:34:34.857Z","updated_at":"2021-01-25T10:31:22.499Z","locale":"en"}],"authors":[{"id":35,"name":"Zilliz","author_tags":"Zilliz team","published_at":"2022-06-15T02:33:23.458Z","created_by":18,"updated_by":18,"created_at":"2022-06-15T02:26:19.780Z","updated_at":"2024-07-03T06:58:08.413Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":6,"localizations":[{"id":1348,"locale":"ja-JP","published_at":"2021-03-31T00:01:59.064Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/header_f8cea596d2.png","belong":"blog","authorNames":["Zilliz"]},{"id":"blog-75","title":"4 Steps to Building a Video Search System","image":{"id":167,"url":"https://assets.zilliz.com/header_3a822736b3.gif"},"display_time":"Aug 29, 2020","deploy_time":null,"url":"building-video-search-system-with-milvus","abstract":"Searching for videos by image with Milvus","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":35,"name":"Zilliz","author_tags":"Zilliz team","published_at":"2022-06-15T02:33:23.458Z","created_by":18,"updated_by":18,"created_at":"2022-06-15T02:26:19.780Z","updated_at":"2024-07-03T06:58:08.413Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":4,"localizations":[{"id":1160,"locale":"ja-JP","published_at":"2021-10-18T08:35:07.600Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/header_3a822736b3.gif","belong":"blog","authorNames":["Zilliz"]},{"id":"blog-33","title":"The Journey to Optimizing Billion-scale Image Search (2/2)","image":{"id":507,"url":"https://assets.zilliz.com/istockphoto_1140691099_170667a_2ab43aee06.jpeg"},"display_time":"Aug 10, 2020","deploy_time":null,"url":"optimizing-billion-scale-image-search-milvus-part-2","abstract":"A case study with UPYUN, part II","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":35,"name":"Zilliz","author_tags":"Zilliz team","published_at":"2022-06-15T02:33:23.458Z","created_by":18,"updated_by":18,"created_at":"2022-06-15T02:26:19.780Z","updated_at":"2024-07-03T06:58:08.413Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":9,"localizations":[{"id":1351,"locale":"ja-JP","published_at":"2021-04-08T22:20:27.855Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/istockphoto_1140691099_170667a_2ab43aee06.jpeg","belong":"blog","authorNames":["Zilliz"]},{"id":"blog-32","title":"The Journey to Optimizing Billion-scale Image Search (1/2)","image":{"id":507,"url":"https://assets.zilliz.com/istockphoto_1140691099_170667a_2ab43aee06.jpeg"},"display_time":"Aug 04, 2020","deploy_time":null,"url":"optimizing-billion-scale-image-search-milvus-part-1","abstract":"A Case Study with UPYUN","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":35,"name":"Zilliz","author_tags":"Zilliz team","published_at":"2022-06-15T02:33:23.458Z","created_by":18,"updated_by":18,"created_at":"2022-06-15T02:26:19.780Z","updated_at":"2024-07-03T06:58:08.413Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":5,"localizations":[{"id":1264,"locale":"ja-JP","published_at":"2021-03-31T20:39:09.882Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/istockphoto_1140691099_170667a_2ab43aee06.jpeg","belong":"blog","authorNames":["Zilliz"]},{"id":"blog-18","title":"Building an AI-Powered Writing Assistant for WPS Office","image":{"id":91,"url":"https://assets.zilliz.com/wps_thumbnail_6cb7876963.jpg"},"display_time":"Jul 28, 2020","deploy_time":null,"url":"Building-an-AI-Powered-Writing-Assistant-with-WPS-Office","abstract":"Learn how Kingsoft leveraged Milvus, an open-source similarity search engine, to build a recommendation engine for WPS Office’s AI-powered writing assistant.","tags":[{"id":1,"name":"Case Study","published_at":"2021-01-15T10:34:37.316Z","created_by":18,"updated_by":18,"created_at":"2021-01-15T10:34:34.857Z","updated_at":"2021-01-25T10:31:22.499Z","locale":"en"}],"authors":[{"id":35,"name":"Zilliz","author_tags":"Zilliz team","published_at":"2022-06-15T02:33:23.458Z","created_by":18,"updated_by":18,"created_at":"2022-06-15T02:26:19.780Z","updated_at":"2024-07-03T06:58:08.413Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":6,"localizations":[{"id":1068,"locale":"ja-JP","published_at":"2021-01-27T03:35:40.105Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/wps_thumbnail_6cb7876963.jpg","belong":"blog","authorNames":["Zilliz"]},{"id":"blog-35","title":"Building an Intelligent QA System with NLP and Milvus","image":{"id":193,"url":"https://assets.zilliz.com/header_ce3a0e103d.png"},"display_time":"May 12, 2020","deploy_time":null,"url":"building-intelligent-chatbot-with-nlp-and-milvus","abstract":"The Next-Gen QA Bot is here","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":35,"name":"Zilliz","author_tags":"Zilliz team","published_at":"2022-06-15T02:33:23.458Z","created_by":18,"updated_by":18,"created_at":"2022-06-15T02:26:19.780Z","updated_at":"2024-07-03T06:58:08.413Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":4,"localizations":[{"id":1050,"locale":"ja-JP","published_at":"2021-04-08T22:33:34.726Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/header_ce3a0e103d.png","belong":"blog","authorNames":["Zilliz"]},{"id":"blog-38","title":"How Does Milvus Schedule Query Tasks","image":{"id":221,"url":"https://assets.zilliz.com/eric_rothermel_Fo_KO_4_Dp_Xam_Q_unsplash_469fe12aeb.jpg"},"display_time":"Mar 02, 2020","deploy_time":null,"url":"scheduling-query-tasks-milvus","abstract":"The work behind the scene","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":35,"name":"Zilliz","author_tags":"Zilliz team","published_at":"2022-06-15T02:33:23.458Z","created_by":18,"updated_by":18,"created_at":"2022-06-15T02:26:19.780Z","updated_at":"2024-07-03T06:58:08.413Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":6,"localizations":[{"id":1030,"locale":"ja-JP","published_at":"2021-04-09T22:38:17.829Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/eric_rothermel_Fo_KO_4_Dp_Xam_Q_unsplash_469fe12aeb.jpg","belong":"blog","authorNames":["Zilliz"]},{"id":"blog-39","title":"How to Select Index Parameters for IVF Index","image":{"id":505,"url":"https://assets.zilliz.com/istockphoto_1332537659_170667a_b857ae8fb9.jpeg"},"display_time":"Feb 26, 2020","deploy_time":null,"url":"select-index-parameters-ivf-index","abstract":"Best practices for IVF index","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":35,"name":"Zilliz","author_tags":"Zilliz team","published_at":"2022-06-15T02:33:23.458Z","created_by":18,"updated_by":18,"created_at":"2022-06-15T02:26:19.780Z","updated_at":"2024-07-03T06:58:08.413Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":3,"localizations":[{"id":1347,"locale":"ja-JP","published_at":"2021-04-09T22:57:02.071Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/istockphoto_1332537659_170667a_b857ae8fb9.jpeg","belong":"blog","authorNames":["Zilliz"]},{"id":"blog-41","title":"Accelerating New Drug Discovery","image":{"id":238,"url":"https://assets.zilliz.com/header_44d6b6aacd.jpg"},"display_time":"Feb 06, 2020","deploy_time":null,"url":"molecular-structure-similarity-with-milvus","abstract":"How to run molecular structure similarity analysis in Milvus","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":35,"name":"Zilliz","author_tags":"Zilliz team","published_at":"2022-06-15T02:33:23.458Z","created_by":18,"updated_by":18,"created_at":"2022-06-15T02:26:19.780Z","updated_at":"2024-07-03T06:58:08.413Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":3,"localizations":[{"id":1271,"locale":"ja-JP","published_at":"2021-04-12T19:08:18.815Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/header_44d6b6aacd.jpg","belong":"blog","authorNames":["Zilliz"]},{"id":"blog-13","title":"Accelerating Similarity Search on Really Big Data with Vector Indexing","image":{"id":502,"url":"https://assets.zilliz.com/istockphoto_1297151834_170667a_39fb80db71.jpeg"},"display_time":"Dec 05, 2019","deploy_time":null,"url":"Accelerating-Similarity-Search-on-Really-Big-Data-with-Vector-Indexing","abstract":"Discover how indexes dramatically accelerate vector similarity search, different index types, and how to choose the right index for your next ML application. ","tags":[{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":18,"updated_by":18,"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en"}],"authors":[{"id":35,"name":"Zilliz","author_tags":"Zilliz team","published_at":"2022-06-15T02:33:23.458Z","created_by":18,"updated_by":18,"created_at":"2022-06-15T02:26:19.780Z","updated_at":"2024-07-03T06:58:08.413Z","home_page":null,"home_page_link":null,"self_intro":null,"repost_to_medium":null,"repost_state":null,"meta_description":null,"locale":"en"}],"read_time":8,"localizations":[{"id":1360,"locale":"ja-JP","published_at":"2021-01-21T08:33:04.230Z"}],"invisible":false,"backgroundImage":"https://assets.zilliz.com/istockphoto_1297151834_170667a_39fb80db71.jpeg","belong":"blog","authorNames":["Zilliz"]}],"tags":[{"id":72,"name":"Community","published_at":"2024-07-10T06:22:15.647Z","created_by":{"id":18,"firstname":"admin","lastname":"admin","username":null,"email":"admin@zilliz.com","password":"$2a$10$OS8coZJRymO4g1dl88yqU.qIxzaqiEyWxa3j4Ab/HuKyOIV7dhTK6","resetPasswordToken":null,"registrationToken":null,"isActive":true,"blocked":null,"preferedLanguage":null},"updated_by":{"id":18,"firstname":"admin","lastname":"admin","username":null,"email":"admin@zilliz.com","password":"$2a$10$OS8coZJRymO4g1dl88yqU.qIxzaqiEyWxa3j4Ab/HuKyOIV7dhTK6","resetPasswordToken":null,"registrationToken":null,"isActive":true,"blocked":null,"preferedLanguage":null},"created_at":"2024-07-10T06:22:04.204Z","updated_at":"2024-07-10T06:22:15.658Z","locale":"en","localizations":[{"id":86,"locale":"es","published_at":"2024-07-10T06:22:15.647Z"},{"id":82,"locale":"de","published_at":"2024-07-10T06:22:15.647Z"},{"id":106,"locale":"fr","published_at":"2024-07-10T06:22:15.647Z"},{"id":75,"locale":"ja-JP","published_at":"2024-07-10T06:22:15.647Z"},{"id":90,"locale":"pt","published_at":"2024-07-10T06:22:15.647Z"},{"id":102,"locale":"it","published_at":"2024-07-10T06:22:15.647Z"},{"id":98,"locale":"ko","published_at":"2024-07-10T06:22:15.647Z"},{"id":94,"locale":"ru","published_at":"2024-07-10T06:22:15.647Z"}]},{"id":39,"name":"VectorDB 101","published_at":"2022-09-30T05:56:34.554Z","created_by":{"id":18,"firstname":"admin","lastname":"admin","username":null,"email":"admin@zilliz.com","password":"$2a$10$OS8coZJRymO4g1dl88yqU.qIxzaqiEyWxa3j4Ab/HuKyOIV7dhTK6","resetPasswordToken":null,"registrationToken":null,"isActive":true,"blocked":null,"preferedLanguage":null},"updated_by":{"id":18,"firstname":"admin","lastname":"admin","username":null,"email":"admin@zilliz.com","password":"$2a$10$OS8coZJRymO4g1dl88yqU.qIxzaqiEyWxa3j4Ab/HuKyOIV7dhTK6","resetPasswordToken":null,"registrationToken":null,"isActive":true,"blocked":null,"preferedLanguage":null},"created_at":"2022-09-30T05:56:31.633Z","updated_at":"2024-07-10T07:12:04.155Z","locale":"en","localizations":[{"id":78,"locale":"ja-JP","published_at":"2022-09-30T05:56:34.554Z"}]},{"id":5,"name":"Engineering","published_at":"2021-01-21T02:28:39.896Z","created_by":{"id":18,"firstname":"admin","lastname":"admin","username":null,"email":"admin@zilliz.com","password":"$2a$10$OS8coZJRymO4g1dl88yqU.qIxzaqiEyWxa3j4Ab/HuKyOIV7dhTK6","resetPasswordToken":null,"registrationToken":null,"isActive":true,"blocked":null,"preferedLanguage":null},"updated_by":{"id":18,"firstname":"admin","lastname":"admin","username":null,"email":"admin@zilliz.com","password":"$2a$10$OS8coZJRymO4g1dl88yqU.qIxzaqiEyWxa3j4Ab/HuKyOIV7dhTK6","resetPasswordToken":null,"registrationToken":null,"isActive":true,"blocked":null,"preferedLanguage":null},"created_at":"2021-01-21T02:28:37.242Z","updated_at":"2022-11-15T19:16:38.988Z","locale":"en","localizations":[{"id":81,"locale":"de","published_at":"2021-01-21T02:28:39.896Z"},{"id":97,"locale":"ko","published_at":"2021-01-21T02:28:39.896Z"},{"id":93,"locale":"ru","published_at":"2021-01-21T02:28:39.896Z"},{"id":85,"locale":"es","published_at":"2021-01-21T02:28:39.896Z"},{"id":101,"locale":"it","published_at":"2021-01-21T02:28:39.896Z"},{"id":105,"locale":"fr","published_at":"2021-01-21T02:28:39.896Z"},{"id":89,"locale":"pt","published_at":"2021-01-21T02:28:39.896Z"},{"id":77,"locale":"ja-JP","published_at":"2021-01-21T02:28:39.896Z"}]},{"id":4,"name":"Company","published_at":"2021-01-21T02:28:23.551Z","created_by":{"id":18,"firstname":"admin","lastname":"admin","username":null,"email":"admin@zilliz.com","password":"$2a$10$OS8coZJRymO4g1dl88yqU.qIxzaqiEyWxa3j4Ab/HuKyOIV7dhTK6","resetPasswordToken":null,"registrationToken":null,"isActive":true,"blocked":null,"preferedLanguage":null},"updated_by":{"id":18,"firstname":"admin","lastname":"admin","username":null,"email":"admin@zilliz.com","password":"$2a$10$OS8coZJRymO4g1dl88yqU.qIxzaqiEyWxa3j4Ab/HuKyOIV7dhTK6","resetPasswordToken":null,"registrationToken":null,"isActive":true,"blocked":null,"preferedLanguage":null},"created_at":"2021-01-21T02:28:20.676Z","updated_at":"2021-01-21T02:28:23.824Z","locale":"en","localizations":[{"id":80,"locale":"ja-JP","published_at":"2021-01-21T02:28:23.551Z"}]},{"id":2,"name":"Product","published_at":"2021-01-21T02:27:46.323Z","created_by":{"id":18,"firstname":"admin","lastname":"admin","username":null,"email":"admin@zilliz.com","password":"$2a$10$OS8coZJRymO4g1dl88yqU.qIxzaqiEyWxa3j4Ab/HuKyOIV7dhTK6","resetPasswordToken":null,"registrationToken":null,"isActive":true,"blocked":null,"preferedLanguage":null},"updated_by":{"id":18,"firstname":"admin","lastname":"admin","username":null,"email":"admin@zilliz.com","password":"$2a$10$OS8coZJRymO4g1dl88yqU.qIxzaqiEyWxa3j4Ab/HuKyOIV7dhTK6","resetPasswordToken":null,"registrationToken":null,"isActive":true,"blocked":null,"preferedLanguage":null},"created_at":"2021-01-21T02:27:42.153Z","updated_at":"2021-01-21T02:27:46.612Z","locale":"en","localizations":[{"id":79,"locale":"ja-JP","published_at":"2021-01-21T02:27:46.323Z"},{"id":99,"locale":"ko","published_at":"2021-01-21T02:27:46.323Z"},{"id":107,"locale":"fr","published_at":"2021-01-21T02:27:46.323Z"},{"id":95,"locale":"ru","published_at":"2021-01-21T02:27:46.323Z"},{"id":103,"locale":"it","published_at":"2021-01-21T02:27:46.323Z"},{"id":83,"locale":"de","published_at":"2021-01-21T02:27:46.323Z"},{"id":87,"locale":"es","published_at":"2021-01-21T02:27:46.323Z"},{"id":91,"locale":"pt","published_at":"2021-01-21T02:27:46.323Z"}]},{"id":1,"name":"Case Study","published_at":"2021-01-15T10:34:37.316Z","created_by":{"id":18,"firstname":"admin","lastname":"admin","username":null,"email":"admin@zilliz.com","password":"$2a$10$OS8coZJRymO4g1dl88yqU.qIxzaqiEyWxa3j4Ab/HuKyOIV7dhTK6","resetPasswordToken":null,"registrationToken":null,"isActive":true,"blocked":null,"preferedLanguage":null},"updated_by":{"id":18,"firstname":"admin","lastname":"admin","username":null,"email":"admin@zilliz.com","password":"$2a$10$OS8coZJRymO4g1dl88yqU.qIxzaqiEyWxa3j4Ab/HuKyOIV7dhTK6","resetPasswordToken":null,"registrationToken":null,"isActive":true,"blocked":null,"preferedLanguage":null},"created_at":"2021-01-15T10:34:34.857Z","updated_at":"2021-01-25T10:31:22.499Z","locale":"en","localizations":[{"id":100,"locale":"ko","published_at":"2021-01-15T10:34:37.316Z"},{"id":74,"locale":"ja-JP","published_at":"2024-11-19T02:34:13.763Z"},{"id":92,"locale":"pt","published_at":"2021-01-15T10:34:37.316Z"},{"id":108,"locale":"fr","published_at":"2021-01-15T10:34:37.316Z"},{"id":96,"locale":"ru","published_at":"2021-01-15T10:34:37.316Z"},{"id":88,"locale":"es","published_at":"2021-01-15T10:34:37.316Z"},{"id":84,"locale":"de","published_at":"2021-01-15T10:34:37.316Z"},{"id":104,"locale":"it","published_at":"2021-01-15T10:34:37.316Z"}]},{"id":73,"name":"Paper Reading","published_at":"2024-08-10T14:40:10.906Z","created_by":{"id":60,"firstname":"Di","lastname":"Feng","username":null,"email":"fendy.feng@zilliz.com","password":"$2a$10$3n0EPwpsTTiNpylnqJ4MReO3yAuO3glfers.zS0Wo4pmwHzaFMbnm","resetPasswordToken":null,"registrationToken":null,"isActive":true,"blocked":null,"preferedLanguage":null},"updated_by":{"id":60,"firstname":"Di","lastname":"Feng","username":null,"email":"fendy.feng@zilliz.com","password":"$2a$10$3n0EPwpsTTiNpylnqJ4MReO3yAuO3glfers.zS0Wo4pmwHzaFMbnm","resetPasswordToken":null,"registrationToken":null,"isActive":true,"blocked":null,"preferedLanguage":null},"created_at":"2024-08-10T14:40:09.192Z","updated_at":"2024-08-10T14:40:10.914Z","locale":"en","localizations":[{"id":76,"locale":"ja-JP","published_at":"2024-08-10T14:40:10.906Z"}]}]},"__N_SSG":true},"page":"/blog","query":{},"buildId":"jZQUVXSOCcaFSI1MpPnBS","isFallback":false,"gsp":true,"scriptLoader":[]}</script></body></html>