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OpenSearch Project<p>Scaling retrieval shouldn’t break your budget.</p><p>OpenSearch supports Faiss byte vectors, cutting storage and memory costs while keeping retrieval performance strong.</p><p>Save memory. Reduce costs. Scale faster. <a href="https://opensearch.org/blog/faiss-byte-vector/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">opensearch.org/blog/faiss-byte</span><span class="invisible">-vector/</span></a><br><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/OpenSearch" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>OpenSearch</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/ML" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ML</span></a> <a href="https://fosstodon.org/tags/SearchTechnology" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>SearchTechnology</span></a> <a href="https://fosstodon.org/tags/SmartSearch" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>SmartSearch</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>One week away → Chicago's Search User Group! </p><p>Join for an evening of OpenSearch insights and vector search case study deep dive. </p><p>📆 Tuesday, August 19, 2025 | 6:00 PM to 8:00 PM CDT<br>📍 Chicago</p><p>Register now 👉 <a href="https://www.meetup.com/opensearch-project-chicago/events/310125523/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">meetup.com/opensearch-project-</span><span class="invisible">chicago/events/310125523/</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/usergroup" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>usergroup</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/Chicago" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Chicago</span></a></p>
OpenSearch Project<p>Structured data powers your applications.</p><p>Now it can power your vector search too.</p><p>Learn how to generate embeddings from nested objects — and extend vector retrieval beyond plain text.</p><p>Smarter hybrid search starts here. <a href="https://docs.opensearch.org/docs/latest/tutorials/vector-search/vector-operations/generate-embeddings/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">docs.opensearch.org/docs/lates</span><span class="invisible">t/tutorials/vector-search/vector-operations/generate-embeddings/</span></a><br><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/OpenSearch" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>OpenSearch</span></a> <a href="https://fosstodon.org/tags/SmartSearch" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>SmartSearch</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>Chicago's Search User Group!</p><p>Join for an evening of OpenSearch insights and vector search case study deep dive. </p><p>📆 Tuesday, August 19, 2025 | 6:00 PM to 8:00 PM CDT<br>📍 Chicago</p><p>To learn more and to register 👉 <a href="https://www.meetup.com/opensearch-project-chicago/events/310125523/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">meetup.com/opensearch-project-</span><span class="invisible">chicago/events/310125523/</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/usergroup" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>usergroup</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/Chicago" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Chicago</span></a></p>
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>💬 <span class="h-card" translate="no"><a href="https://fosstodon.org/@krisfreedain" class="u-url mention" rel="nofollow noopener" target="_blank">@<span>krisfreedain</span></a></span> and Nils Bandener had a great conversation at the <a href="https://fosstodon.org/tags/WeAreDevelopers" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>WeAreDevelopers</span></a> conference in Berlin, diving into the OpenSearch community, what it takes to become a maintainer, and the journey to getting there.</p><p>Thanks to the OpenSearch community for keeping the momentum going and pushing boundaries.</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/VectorSearch" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>VectorSearch</span></a> <a href="https://fosstodon.org/tags/maintainer" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>maintainer</span></a> <a href="https://fosstodon.org/tags/OpenSource" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>OpenSource</span></a> <a href="https://fosstodon.org/tags/WeAreDevelopers" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>WeAreDevelopers</span></a> <a href="https://fosstodon.org/tags/Berlin" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Berlin</span></a></p>
Dotan Horovits #CNCFAmbassador<p>What if you need both Lexical and Semantic search? <br>No need for 2 data stores, data duplication and clumsy result set relevance merge. <br>The <a href="https://fosstodon.org/tags/OpenSearch" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>OpenSearch</span></a> Project gives you both in one open source! <br><a href="https://www.linkedin.com/feed/update/urn:li:share:7350414216815591424" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">linkedin.com/feed/update/urn:l</span><span class="invisible">i:share:7350414216815591424</span></a></p><p><a href="https://fosstodon.org/tags/vectordb" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>vectordb</span></a> <a href="https://fosstodon.org/tags/genAI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>genAI</span></a> <a href="https://fosstodon.org/tags/semantic" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>semantic</span></a> <a href="https://fosstodon.org/tags/search" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>search</span></a> <a href="https://fosstodon.org/tags/vectorSearch" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>vectorSearch</span></a> <span class="h-card" translate="no"><a href="https://fosstodon.org/@OpenSearchProject" class="u-url mention" rel="nofollow noopener" target="_blank">@<span>OpenSearchProject</span></a></span></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>
OpenSearch Project<p>At Open Source Summit North America, @theCUBE host Paul Nashawaty caught up with Mukul Karnik from OpenSearch to discuss key highlights from OpenSearch 3.0 and new features in 3.1. Check out their chat covering all things hybrid search, MCP, vector search, observability use cases and agentic AI. </p><p>Watch the full interview: <a href="https://www.thecube.net/events/linux-foundation/open-source-summit-na-2025/content/Videos/01a2abef-d221-486b-9eea-4cfdca4e97a8" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">thecube.net/events/linux-found</span><span class="invisible">ation/open-source-summit-na-2025/content/Videos/01a2abef-d221-486b-9eea-4cfdca4e97a8</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/SearchTech" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>SearchTech</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/Observability" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Observability</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>🚀 OpenSearch made a strong showing at <a href="https://fosstodon.org/tags/WeAreDevelopers" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>WeAreDevelopers</span></a> in Berlin.</p><p>Jochen Kressin, Director at <span class="h-card" translate="no"><a href="https://mastodon.social/@eliatra" class="u-url mention" rel="nofollow noopener" target="_blank">@<span>eliatra</span></a></span> shared how they're using OpenSearch as a vector database, and how 3.0 features like GPU support are driving real impact.</p><p>Huge thanks to the OpenSearch community. The momentum is real and the future is bright.</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/Eliatra" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Eliatra</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/Analytics" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Analytics</span></a> <a href="https://fosstodon.org/tags/OpenSource" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>OpenSource</span></a> <a href="https://fosstodon.org/tags/WeAreDevelopers" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>WeAreDevelopers</span></a> <a href="https://fosstodon.org/tags/Berlin" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Berlin</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>
Dotan Horovits #CNCFAmbassador<p>📢 Thrilled to share that, through a collaborative effort between the <span class="h-card" translate="no"><a href="https://fosstodon.org/@OpenSearchProject" class="u-url mention" rel="nofollow noopener" target="_blank">@<span>OpenSearchProject</span></a></span> and <span class="h-card" translate="no"><a href="https://mas.to/@huggingface" class="u-url mention" rel="nofollow noopener" target="_blank">@<span>huggingface</span></a></span> neural sparse models are now available in the Sentence Transformers library. 🤗</p><p>The Sentence Transformers (a.k.a. SBERT) library, developed by <span class="h-card" translate="no"><a href="https://sigmoid.social/@UKPLab" class="u-url mention" rel="nofollow noopener" target="_blank">@<span>UKPLab</span></a></span> and maintained by <a href="https://fosstodon.org/tags/HuggingFace" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>HuggingFace</span></a>, is a Python framework designed to generate semantically meaningful embeddings for sentences, paragraphs, and images. </p><p><a href="https://opensearch.org/blog/neural-sparse-models-are-now-available-in-hugging-face-sentence-transformers/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">opensearch.org/blog/neural-spa</span><span class="invisible">rse-models-are-now-available-in-hugging-face-sentence-transformers/</span></a></p><p>Congrats to all involved! 👏</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/vectorSearch" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>vectorSearch</span></a> <a href="https://fosstodon.org/tags/NLP" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>NLP</span></a> <a href="https://fosstodon.org/tags/ML" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ML</span></a></p>
OpenSearch Project<p>🚀 OpenSearch 3.1 is here with powerful upgrades to boost search, speed up generative AI, and improve observability.</p><p>Highlights include:<br>✅ GPU-accelerated vector search<br>✅ New Search Relevance Workbench<br>✅ Smarter agent and model management<br>✅ Simplified semantic search<br>✅ Better ML monitoring with OpenTelemetry</p><p>Explore what’s new and get started:<br>🔗 <a href="https://opensearch.org/blog/get-started-with-opensearch-3-1/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">opensearch.org/blog/get-starte</span><span class="invisible">d-with-opensearch-3-1/</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/SearchTech" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>SearchTech</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/Observability" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Observability</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>"We’re really pushing the boundaries of search.” — Pallavi Priyadarshini, OpenSearch Project</p><p>💡 In a packed keynote at <a href="https://fosstodon.org/tags/OpenSearchCon" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>OpenSearchCon</span></a> India, leaders from AWS and Freshworks shared how OpenSearch is powering real-world AI use cases—from semantic and hybrid search to federated agents and chat-based assistants. </p><p>👉 To learn more, read the blog here: <a href="https://opensearch.org/blog/vector-powered-ai-ready-how-opensearch-and-freshworks-are-shaping-the-future-of-search/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">opensearch.org/blog/vector-pow</span><span class="invisible">ered-ai-ready-how-opensearch-and-freshworks-are-shaping-the-future-of-search/</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/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/GenerativeAI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>GenerativeAI</span></a> <a href="https://fosstodon.org/tags/AgenticAI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AgenticAI</span></a> <a href="https://fosstodon.org/tags/Freshworks" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Freshworks</span></a> <a href="https://fosstodon.org/tags/AWS" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AWS</span></a> <a href="https://fosstodon.org/tags/OpenSource" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>OpenSource</span></a> <a href="https://fosstodon.org/tags/OpenSearchConIndia" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>OpenSearchConIndia</span></a> <a href="https://fosstodon.org/tags/Communitydriven" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Communitydriven</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>Vector search, now more efficient. ⚙️</p><p>OpenSearch 3.0’s derived source cuts storage up to 3x and lowers search latency by 90%.<br>No code changes. Just better performance.</p><p>Try it now 👉 <a href="https://opensearch.org/blog/do-more-with-less-save-up-to-3x-on-storage-with-derived-vector-source/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">opensearch.org/blog/do-more-wi</span><span class="invisible">th-less-save-up-to-3x-on-storage-with-derived-vector-source/</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/VectorSearch" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>VectorSearch</span></a> <a href="https://fosstodon.org/tags/CNCF" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>CNCF</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>🚀 Smarter pipelines, better performance.<br>OpenSearch now skips redundant inference calls—saving compute, lowering costs, and speeding up updates.</p><p>🧠 Learn how it works: <a href="https://opensearch.org/blog/optimizing-inference-processors-for-cost-efficiency-and-performance/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">opensearch.org/blog/optimizing</span><span class="invisible">-inference-processors-for-cost-efficiency-and-performance/</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/VectorSearch" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>VectorSearch</span></a> <a href="https://fosstodon.org/tags/Efficiency" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Efficiency</span></a> <a href="https://fosstodon.org/tags/MachineLearning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>MachineLearning</span></a> <a href="https://fosstodon.org/tags/OpenSource" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>OpenSource</span></a></p>
Coroot<p>🔎🔥Summoning all <a href="https://mastodon.social/tags/dataengineers" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>dataengineers</span></a>, <a href="https://mastodon.social/tags/AI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AI</span></a> enthusiasts, and <a href="https://mastodon.social/tags/RAG" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>RAG</span></a> masterminds - join us at <a href="https://mastodon.social/tags/VSCON25" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>VSCON25</span></a> June 6th to expand your knowledge and network with global developers from <a href="https://mastodon.social/tags/Google" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Google</span></a>, <a href="https://mastodon.social/tags/Oracle" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Oracle</span></a>, and <a href="https://mastodon.social/tags/Microsoft" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Microsoft</span></a>! </p><p>Sign up at: <a href="http://vsearchcon.com" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">http://</span><span class="">vsearchcon.com</span><span class="invisible"></span></a> </p><p><a href="https://mastodon.social/tags/tech" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>tech</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/postgresql" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>postgresql</span></a> <a href="https://mastodon.social/tags/pgvector" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>pgvector</span></a> <a href="https://mastodon.social/tags/LLMs" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>LLMs</span></a> <a href="https://mastodon.social/tags/MySQL" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>MySQL</span></a> <a href="https://mastodon.social/tags/Vespa" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Vespa</span></a> <a href="https://mastodon.social/tags/Couchbase" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Couchbase</span></a></p>
OpenSearch Project<p>Keyword matching vs. semantic understanding: The battle between traditional &amp; vector search. Discover why context wins for AI apps: <a href="https://opensearch.org/platform/vector-engine/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">opensearch.org/platform/vector</span><span class="invisible">-engine/</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>
Albert David<p>🎉 Just earned the Oracle AI Vector Search Professional Certification!<br>Here’s a quick look at what it covers:</p><p>✅ Building AI-driven apps with Oracle Database 23ai<br>✅ Working with vector data, embeddings &amp; similarity search<br>✅ Using PL/SQL &amp; Python to build RAG applications<br>✅ Leveraging tools like Exadata AI Storage, GoldenGate &amp; Select AI<br>✅ Designed for DBAs, AI engineers &amp; cloud developers</p><p><a href="https://mastodon.social/tags/Oracle" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Oracle</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/Database23ai" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Database23ai</span></a> <a href="https://mastodon.social/tags/RAG" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>RAG</span></a> <a href="https://mastodon.social/tags/plsql" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>plsql</span></a> <a href="https://mastodon.social/tags/python" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>python</span></a><br><a href="https://catalog-education.oracle.com/ords/certview/sharebadge?id=F995FA27441224ADC1E4E12575FB90325ED2103732A5AAA27CD875F4EF00618D" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">catalog-education.oracle.com/o</span><span class="invisible">rds/certview/sharebadge?id=F995FA27441224ADC1E4E12575FB90325ED2103732A5AAA27CD875F4EF00618D</span></a></p>