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Sarah Lea<p>LLMs don’t know your PDF.<br>They don’t know your company wiki either. Or your research papers.</p><p>What they can do with RAG is look through your documents in the background and answer using what they find.</p><p>But how does that actually work? Here’s the basic idea behind RAG:<br>:blobcoffee: Chunking: The document is split into small, overlapping parts so the LLM can handle them. This keeps structure and context.<br>:blobcoffee: Embeddings &amp; Search: Each part is turned into a vector (a numerical representation of meaning). Your question is also turned into a vector, and the system compares them to find the best matches.<br>:blobcoffee: Retriever + LLM: The top matches are sent to the LLM, which uses them to generate an answer based on that context.</p><p><a href="https://techhub.social/tags/llm" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>llm</span></a> <a href="https://techhub.social/tags/largelanguagemodel" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>largelanguagemodel</span></a> <a href="https://techhub.social/tags/ai" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ai</span></a> <a href="https://techhub.social/tags/ki" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ki</span></a> <a href="https://techhub.social/tags/rag" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>rag</span></a> <a href="https://techhub.social/tags/tech" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>tech</span></a> <a href="https://techhub.social/tags/technology" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>technology</span></a> <a href="https://techhub.social/tags/vector" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>vector</span></a> <a href="https://techhub.social/tags/datascience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>datascience</span></a> <a href="https://techhub.social/tags/vectorsearch" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>vectorsearch</span></a> <a href="https://techhub.social/tags/vector" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>vector</span></a> <a href="https://techhub.social/tags/machinelearning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>machinelearning</span></a></p>
OpenSearch Project<p>🚀 OpenSearch 3.1 delivers massive performance gains for hybrid queries with up to 3.5x higher throughput and 80% lower latency! Our new score collection system optimizes parallel execution for faster, more efficient searches. Check out the technical details here 👇<br><a href="http://bit.ly/46CvLrO" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">http://</span><span class="">bit.ly/46CvLrO</span><span class="invisible"></span></a></p><p><a href="https://fosstodon.org/tags/OpenSearch" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>OpenSearch</span></a> <a href="https://fosstodon.org/tags/Performance" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Performance</span></a> <a href="https://fosstodon.org/tags/VectorSearch" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>VectorSearch</span></a></p>
Pragmatic Bookshelf 📚<p>In Berlin at <a href="https://techhub.social/tags/WWC25" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>WWC25</span></a> ? Catch our ✨ newest✨ Pragprog author - Ben Greenberg <span class="h-card" translate="no"><a href="https://fosstodon.org/@hummusonrails" class="u-url mention" rel="nofollow noopener" target="_blank">@<span>hummusonrails</span></a></span><br>Learn how GenAI and Vector Search can help users find what they are looking for - even when they don't know!<br>Fri 2:20 pm - Stage 7 </p><p>Ben's Book - out in Beta this week!<br><a href="https://pragprog.com/titles/bgvector?utm_source=m" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">pragprog.com/titles/bgvector?u</span><span class="invisible">tm_source=m</span></a><br> <a href="https://techhub.social/tags/AI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AI</span></a> <a href="https://techhub.social/tags/MachineLearning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>MachineLearning</span></a> <a href="https://techhub.social/tags/VectorSearch" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>VectorSearch</span></a> <br>WeAreDevs</p>
Margaret Eldridge<p>Celebrating Vector Search with JavaScript: Build Intelligent Search Systems with AI by Ben Greenberg now in beta!</p><p>🔗 Read more: <a href="https://medium.com/pragmatic-programmers/57eed26bc43d" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">medium.com/pragmatic-programme</span><span class="invisible">rs/57eed26bc43d</span></a></p><p>📘 ebook: <a href="https://pragprog.com/titles/bgvector" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="">pragprog.com/titles/bgvector</span><span class="invisible"></span></a></p><p><a href="https://hachyderm.io/tags/javascript" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>javascript</span></a> <a href="https://hachyderm.io/tags/ai" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ai</span></a> <a href="https://hachyderm.io/tags/vectorsearch" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>vectorsearch</span></a> <a href="https://hachyderm.io/tags/programming" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>programming</span></a> <a href="https://hachyderm.io/tags/pragprog" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>pragprog</span></a> <a href="https://hachyderm.io/tags/books" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>books</span></a></p>
OpenSearch Project<p>Headed to <a href="https://fosstodon.org/tags/OpenSourceSummit" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>OpenSourceSummit</span></a> North America in Denver? Don’t miss these OpenSearch sessions:</p><p>🔹 Keynote: Lucene 10 + OpenSearch 3.0 powering the next wave of AI search</p><p>🔹 Lightning Talk: From Fork to Foundation – the OpenSearch journey to @linuxfoundation </p><p>📲 Full schedule: <a href="https://events.linuxfoundation.org/open-source-summit-north-america/program/schedule/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">events.linuxfoundation.org/ope</span><span class="invisible">n-source-summit-north-america/program/schedule/</span></a></p><p><a href="https://fosstodon.org/tags/OpenSearch" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>OpenSearch</span></a> <a href="https://fosstodon.org/tags/OSSNA" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>OSSNA</span></a> <a href="https://fosstodon.org/tags/AI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AI</span></a> <a href="https://fosstodon.org/tags/VectorSearch" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>VectorSearch</span></a> <a href="https://fosstodon.org/tags/Lucene10" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Lucene10</span></a> <a href="https://fosstodon.org/tags/OpenSource" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>OpenSource</span></a></p>
OpenSearch Project<p>Why does vector search matter in 2025? It powers semantic understanding in AI apps like recommendations &amp; search. Learn how OpenSearch to use OpenSearch as a vector database: <a href="https://youtu.be/oX0HMAztP8E" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="">youtu.be/oX0HMAztP8E</span><span class="invisible"></span></a> <a href="https://fosstodon.org/tags/VectorSearch" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>VectorSearch</span></a> <a href="https://fosstodon.org/tags/AI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AI</span></a> <a href="https://fosstodon.org/tags/OpenSource" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>OpenSource</span></a></p>
Harald Klinke<p>Neo4j treibt mit GraphRAG, Vektor-Indizes &amp; Agentic RAG die <a href="https://det.social/tags/KI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>KI</span></a>-Entwicklung voran. Ob <a href="https://det.social/tags/LangChain" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>LangChain</span></a>, <a href="https://det.social/tags/LlamaIndex" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>LlamaIndex</span></a>, <a href="https://det.social/tags/SpringAI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>SpringAI</span></a> oder <a href="https://det.social/tags/VertexAI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>VertexAI</span></a> – das neue Python-Paket und das Model Context Protocol (MCP) verknüpfen Graphdaten nahtlos mit <a href="https://det.social/tags/LLM" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>LLM</span></a>-Anwendungen.<br><a href="https://det.social/tags/Neo4j" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Neo4j</span></a> <a href="https://det.social/tags/GenAI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>GenAI</span></a> <a href="https://det.social/tags/RAG" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>RAG</span></a> <a href="https://det.social/tags/GraphQL" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>GraphQL</span></a> <a href="https://det.social/tags/Cypher" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Cypher</span></a> <a href="https://det.social/tags/VectorSearch" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>VectorSearch</span></a> <a href="https://det.social/tags/AgenticAI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AgenticAI</span></a><br><a href="https://www.bigdata-insider.de/leistungssprung-bei-graph-datenbanken-mit-ki-integration-cloud-skalierung-und-terabyte-graphen-a-2307ed20cfaf562a1a0094b712b5be95/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">bigdata-insider.de/leistungssp</span><span class="invisible">rung-bei-graph-datenbanken-mit-ki-integration-cloud-skalierung-und-terabyte-graphen-a-2307ed20cfaf562a1a0094b712b5be95/</span></a></p>
The Linux Foundation<p>🚀 Scale vector search without breaking the bank! @OpenSearchProject introduces disk-based vector search, combining efficient quantization with secondary storage to reduce RAM usage while maintaining accuracy.</p><p>Read more: <a href="https://opensearch.org/blog/Reduce-Cost-with-Disk-based-Vector-Search/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">opensearch.org/blog/Reduce-Cos</span><span class="invisible">t-with-Disk-based-Vector-Search/</span></a><br><a href="https://social.lfx.dev/tags/OpenSearch" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>OpenSearch</span></a> <a href="https://social.lfx.dev/tags/VectorSearch" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>VectorSearch</span></a> <a href="https://social.lfx.dev/tags/AI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AI</span></a></p>
Brandon H :csharp: :verified:<p>via <span class="h-card" translate="no"><a href="https://dotnet.social/@dotnet" class="u-url mention" rel="nofollow noopener" target="_blank">@<span>dotnet</span></a></span> : Announcing Chroma DB C# SDK</p><p><a href="https://ift.tt/UXHGRPJ" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="">ift.tt/UXHGRPJ</span><span class="invisible"></span></a><br><a href="https://hachyderm.io/tags/ChromaDB" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ChromaDB</span></a> <a href="https://hachyderm.io/tags/CSharpSDK" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>CSharpSDK</span></a> <a href="https://hachyderm.io/tags/AIApplications" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AIApplications</span></a> <a href="https://hachyderm.io/tags/DotNet" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>DotNet</span></a> <a href="https://hachyderm.io/tags/SemanticSearch" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>SemanticSearch</span></a> <a href="https://hachyderm.io/tags/VectorSearch" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>VectorSearch</span></a> <a href="https://hachyderm.io/tags/OpenSource" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>OpenSource</span></a> <a href="https://hachyderm.io/tags/Database" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Database</span></a> <a href="https://hachyderm.io/tags/RetrievalAugmentedGeneration" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>RetrievalAugmentedGeneration</span></a> <a href="https://hachyderm.io/tags/ChromaClient" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ChromaClient</span></a> <a href="https://hachyderm.io/tags/NuGet" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>NuGet</span></a> <a href="https://hachyderm.io/tags/Docker" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Docker</span></a> <a href="https://hachyderm.io/tags/Azure" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Azure</span></a> <a href="https://hachyderm.io/tags/DataCommunity" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>DataCommunity</span></a> <a href="https://hachyderm.io/tags/Developers" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Developers</span></a> <a href="https://hachyderm.io/tags/TechAn" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>TechAn</span></a>…</p>
Tembo<p>Learn how to build a modern e-commerce platform that leverages <a href="https://mastodon.social/tags/vectorsearch" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>vectorsearch</span></a> capabilities using Tembo's VectorDB Stack, so that users can find products using natural language prompts: <a href="https://tembo.io/blog/vector-search-ecommerce-app" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">tembo.io/blog/vector-search-ec</span><span class="invisible">ommerce-app</span></a> <a href="https://mastodon.social/tags/PostgreSQL" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>PostgreSQL</span></a></p>
Tembo<p>Use our generous Free Trial to build an Image Search Engine 🔎 on top of <a href="https://mastodon.social/tags/PostgreSQL" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>PostgreSQL</span></a>: <a href="https://tembo.io/blog/image-search" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="">tembo.io/blog/image-search</span><span class="invisible"></span></a> <a href="https://mastodon.social/tags/vectorsearch" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>vectorsearch</span></a></p>
Tembo<p>Find out how to build an image search engine 🔎 on <a href="https://mastodon.social/tags/PostgreSQL" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>PostgreSQL</span></a>: <a href="https://tembo.io/blog/image-search" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="">tembo.io/blog/image-search</span><span class="invisible"></span></a> <a href="https://mastodon.social/tags/vectorsearch" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>vectorsearch</span></a></p>
o19s<p>How do you build <a href="https://fosstodon.org/tags/vectorsearch" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>vectorsearch</span></a> at billion-item scale? Join Stephen Batifol at Haystack EU next week to find out about the architectural decisions to consider. *Only a handful of in-person tickets remain* <a href="https://haystackconf.com/eu2024/talk-9/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">haystackconf.com/eu2024/talk-9</span><span class="invisible">/</span></a></p>
ObjectBox<p>Swift developers: build local AI apps with Semantic Index now --&gt; Easily personalize AI experiences with the first on-device vector search for iOS and macOS 🤩- private, fast, offline 💚</p><p><a href="https://objectbox.io/swift-ios-on-device-vector-database-aka-semantic-index/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">objectbox.io/swift-ios-on-devi</span><span class="invisible">ce-vector-database-aka-semantic-index/</span></a></p><p><a href="https://techhub.social/tags/iosdev" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>iosdev</span></a> <a href="https://techhub.social/tags/localAI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>localAI</span></a> <a href="https://techhub.social/tags/offlineAI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>offlineAI</span></a> <a href="https://techhub.social/tags/vectorsearch" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>vectorsearch</span></a> <a href="https://techhub.social/tags/RAG" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>RAG</span></a> <a href="https://techhub.social/tags/vectordatabase" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>vectordatabase</span></a></p>
o19s<p>According to Louis Brandy of Rockset, all <a href="https://fosstodon.org/tags/vectorsearch" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>vectorsearch</span></a> applications benefit from some form of hybrid search - find out why at Haystack US 2024 <a href="https://haystackconf.com/us2024/talk-1/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">haystackconf.com/us2024/talk-1</span><span class="invisible">/</span></a> - only a few early bird tickets left now!</p>
InfoQ<p>🆕 <a href="https://techhub.social/tags/GoogleBigQuery" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>GoogleBigQuery</span></a> supports <a href="https://techhub.social/tags/VectorSearch" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>VectorSearch</span></a>!</p><p>The new functionality enables vector similarity search required by data and AI use cases such as semantic search, similarity detection, and retrieval-augmented generation (<a href="https://techhub.social/tags/RAG" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>RAG</span></a>) with a large language model (<a href="https://techhub.social/tags/LLM" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>LLM</span></a>).</p><p>More on <a href="https://techhub.social/tags/InfoQ" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>InfoQ</span></a>: <a href="https://bit.ly/43wmzSx" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="">bit.ly/43wmzSx</span><span class="invisible"></span></a> </p><p><a href="https://techhub.social/tags/CloudComputing" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>CloudComputing</span></a> <a href="https://techhub.social/tags/GenerativeAI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>GenerativeAI</span></a></p>
simplyblock<p>Guest <span class="h-card" translate="no"><a href="https://mastodon.social/@FranckPachot" class="u-url mention" rel="nofollow noopener" target="_blank">@<span>FranckPachot</span></a></span> from <a href="https://mastodon.social/tags/yugabyte" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>yugabyte</span></a> joins our very own @noctarius2k in this episode of the weekly, 20 min <a href="https://mastodon.social/tags/CloudCommute" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>CloudCommute</span></a> <a href="https://mastodon.social/tags/podcast" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>podcast</span></a>, talking about <a href="https://mastodon.social/tags/distributedsql" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>distributedsql</span></a>, <a href="https://mastodon.social/tags/postgresql" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>postgresql</span></a> , <a href="https://mastodon.social/tags/vectordatabases" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>vectordatabases</span></a>, and more. Tune in!</p><p>The 🎙️ is available on Spotify, iTunes, Pandora, Amazon Music, and more.</p><p>🎥👉 <a href="https://youtu.be/1EAKqwcP2SY" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="">youtu.be/1EAKqwcP2SY</span><span class="invisible"></span></a></p><p><a href="https://mastodon.social/tags/vectordatabase" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>vectordatabase</span></a> <a href="https://mastodon.social/tags/vectorsearch" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>vectorsearch</span></a> <a href="https://mastodon.social/tags/vectordb" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>vectordb</span></a> <a href="https://mastodon.social/tags/database" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>database</span></a> <a href="https://mastodon.social/tags/databases" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>databases</span></a> <a href="https://mastodon.social/tags/postgres" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>postgres</span></a> <a href="https://mastodon.social/tags/postgressql" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>postgressql</span></a></p>
Beth Pariseau<p>"The No. 1 goal I have is just visibility and awareness that … it's no longer your grandpa and grandma's ELK stack." - Abhishek Singh </p><p><a href="https://www.techtarget.com/searchitoperations/news/366566574/Ex-Datadog-AWS-exec-steers-Elastics-observability-strategy" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">techtarget.com/searchitoperati</span><span class="invisible">ons/news/366566574/Ex-Datadog-AWS-exec-steers-Elastics-observability-strategy</span></a></p><p><a href="https://hachyderm.io/tags/elastic" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>elastic</span></a> <a href="https://hachyderm.io/tags/elasticsearch" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>elasticsearch</span></a> <a href="https://hachyderm.io/tags/ELKstack" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ELKstack</span></a> <a href="https://hachyderm.io/tags/elasticstack" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>elasticstack</span></a> <a href="https://hachyderm.io/tags/observabilty" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>observabilty</span></a> <a href="https://hachyderm.io/tags/semanticsearch" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>semanticsearch</span></a> <a href="https://hachyderm.io/tags/vectorsearch" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>vectorsearch</span></a> <a href="https://hachyderm.io/tags/generativeAI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>generativeAI</span></a> <a href="https://hachyderm.io/tags/opentelemetry" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>opentelemetry</span></a> <a href="https://hachyderm.io/tags/Datadog" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Datadog</span></a> <a href="https://hachyderm.io/tags/AWS" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AWS</span></a></p>
Iulia Feroli 👩🏻‍💻<p>Getting busy! We just heard from Jim Ferenczi about the latest breakthroughs <a href="https://mastodon.social/tags/Elastic" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Elastic</span></a> brought to <a href="https://mastodon.social/tags/lucene" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>lucene</span></a> to make vector search faster, more memory efficient, and of course more accurate. Read more about even more cool stuff coming: <a href="https://www.elastic.co/search-labs/blog/articles/scalar-quantization-in-lucene" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">elastic.co/search-labs/blog/ar</span><span class="invisible">ticles/scalar-quantization-in-lucene</span></a> <a href="https://mastodon.social/tags/elasticsearch" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>elasticsearch</span></a> <a href="https://mastodon.social/tags/elasticon" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>elasticon</span></a> <a href="https://mastodon.social/tags/search" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>search</span></a> <a href="https://mastodon.social/tags/vectorsearch" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>vectorsearch</span></a></p>
Matt Aslett<p>New Ventana Research Analyst Perspective: Vector Search and RAG Improve Trust in Generative AI</p><p><a href="https://mastodon.cloud/tags/Vectorsearch" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Vectorsearch</span></a> and <a href="https://mastodon.cloud/tags/RAG" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>RAG</span></a> have taken the data platform market by storm as providers position to benefit from the huge surge of interest in generative AI. </p><p><a href="https://mattaslett.ventanaresearch.com/vector-search-and-rag-improve-trust-in-generative-ai" rel="nofollow noopener" target="_blank"><span class="invisible">https://</span><span class="ellipsis">mattaslett.ventanaresearch.com</span><span class="invisible">/vector-search-and-rag-improve-trust-in-generative-ai</span></a></p>