#vectordatabases — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #vectordatabases, aggregated by home.social.
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If you are running a #RAG pipeline on embeddings alone, you are leaving retrieval quality on the table.
To maximize accuracy, you need to:
➤ Add BM25
➤ Fuse with Reciprocal Rank Fusion (RRF)
➤ Consider a cross-encoder re-ranking stage📰 Read the #InfoQ article by Aaditya Chauhan for more information: https://bit.ly/4o8GnoZ
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The paper studies what happens when embedding based systems replace many memories, vectors, or retrieved passages with only a few representatives. The central claim: the same spectral structure that governs forgetting under retrieval noise also governs consolidation under compression: efficiency is increasingly becoming a question of representation geometry rather than brute force scaling alone.https://github.com/niashwin/geometry-of-consolidation/blob/main/paper/arxiv/main.pdf
#AIInfrastructure #RAG #LLM #ArtificialIntelligence #VectorDatabases -
#DoorDash launched a multimodal #ML system aligning images, text, and user queries in a shared embedding space.
• Trained on 32M query–product pairs
• Uses contrastive learning
• Improves semantic search, ranking, and advertising relevanceMore details here ⇨ https://bit.ly/41fhrl3
#SoftwareArchitecture #AI #Rankings #Search #VectorDatabases #EmbeddedDatabases #InfoQ
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Database Systems and Comparisons in 2025: The Ultimate Guide to Choosing Your Data Home
https://techlife.blog/posts/database-systems-2025/ #databases
#SQL #NoSQL #PostgreSQL #MongoDB #Oracle #MySQL #VectorDatabases #CloudDatabases
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Amazon S3 Vectors is now GA!
AWS introduces a “Storage-First” architecture that decouples compute from storage, cutting TCO by up to 90% for large-scale RAG workloads.
With this GA release, S3 Vectors:
• Boosts per-index capacity 40× to 2 billion vectors
• Delivers sub-100ms query latenciesMore on #InfoQ 👉 https://bit.ly/4ppNAQD
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Swiggy launches Hermes V3 – a GenAI-powered text-to-SQL assistant.
Built to operate within #Slack, it uses vector retrieval, session memory, agentic orchestration & an explanation layer to generate accurate SQL queries.
#AI #LLMs #Chatbots #VectorDatabases #SoftwareArchitecture #InfoQ
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via @dotnet : Generative AI with Large Language Models in C# in 2026
https://ift.tt/ikxf7Ej
#GenerativeAI #LargeLanguageModels #CSharp #AI2026 #OpenAI #Microsoft #Azure #SemanticKernel #MachineLearning #AIExtensions #VectorDatabases #DotNet #AIInnovation #ChatGP… -
Oh, you wanna play newspaper tycoon with your own lil' RAG? 🤓 How quaint! Here's a riveting tale of nerds turning Skald into a privacy utopia because nothing screams fun like vector databases and #LLMs. 🙄 Spoiler alert: proprietary APIs are faster, but who needs speed when you have open-source purity, right? 🚀
https://blog.yakkomajuri.com/blog/local-rag #newspaperTycoon #privacyUtopia #vectorDatabases #openSource #HackerNews #ngated -
Replicate joins Cloudflare in a massive bet on the future of developer friendly AI
https://web.brid.gy/r/https://nerds.xyz/2025/11/replicate-joins-cloudflare/
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Explore how #RetrievalAugmentedGeneration & #SemanticCaching can reduce #FalsePositives in AI-powered apps.
Insights come from a production-grade #CaseStudy testing 1,000 queries across 7 bi-encoder models.
📰 Read now: https://bit.ly/4nTPmso
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🔍 Optimiertes Retrieval = bessere Antworten!
Auf der #BaselOne25 zeigt Ursula Deriu, wie man RAG-Systeme mit hybrider Suche, Reranking, Anfrageerweiterung & Vektor-Datenbanken optimiert 🚀 Erwartet Best Practices, Stolperfallen & praxisnahe Strategien.
📅 16. Okt | Markthalle Basel
🎟️ Tickets: https://eventfrog.ch/BaselOne2025
📌 Programm mit @kevindubois, @ixchelruiz & @aalmiray: https://baselone.org/#programm👉 Sichere Dir Dein Ticket & sei live dabei!
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🚀 NEW on We ❤️ Open Source 🚀
Jessica Garson shares how vector databases go beyond keywords to power semantic search, embeddings & smarter AI workflows. A practical intro to RAG & context-aware apps.
Read the article: https://allthingsopen.org/articles/vector-databases-semantic-search-ai
#WeLoveOpenSource #VectorDatabases #AI #SemanticSearch #MachineLearning #OpenSource
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Amazon S3 #vectors are coming for your precious vector databases, like a bear in a honey warehouse 🐻🍯. But don't worry, #Zilliz is here to reassure you with a deluge of buzzwords and a pricing calculator that even your cat could use 🐱🧮. Grab a coffee, folks, this one's a real nail-biter! ☕️💤
https://zilliz.com/blog/will-amazon-s3-vectors-kill-vector-databases-or-save-them #AmazonS3 #VectorDatabases #TechBuzzwords #CloudComputing #HackerNews #ngated -
Will Amazon S3 Vectors Kill Vector Databases–Or Save Them?
https://zilliz.com/blog/will-amazon-s3-vectors-kill-vector-databases-or-save-them
#HackerNews #AmazonS3 #Vectors #VectorDatabases #CloudComputing #DataStorage #TechNews
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🚀 From $26K to $9K/month.
⚡ 3x faster search.
🔓 100% control over your AI memory.Discover why Qdrant is quietly taking over Pinecone in the biggest shift in AI infra you haven’t heard of... yet.
💡 Engineers, founders, DevOps—this one’s for you.
👉 Read the full story:
https://medium.com/@rogt.x1997/qdrant-vs-pinecone-the-open-source-rebellion-thats-reshaping-ai-infrastructure-3c0f13a98135#Qdrant #VectorDatabases #AIInfrastructure #OpenSource
https://medium.com/@rogt.x1997/qdrant-vs-pinecone-the-open-source-rebellion-thats-reshaping-ai-infrastructure-3c0f13a98135 -
🤔 Ah yes, because what we all desperately needed was another way to complicate our Linux filesystems by transforming them into "vector databases" using ✨magic✨ Python packages. 🤯 Just what we've been missing: a filesystem that doubles as an impenetrable, semantic labyrinth—clearly the future of user-friendly computing! 🧩🔍
https://vectorvfs.readthedocs.io/en/latest/ #LinuxFilesystems #VectorDatabases #PythonMagic #UserFriendlyComputing #SemanticLabyrinth #HackerNews #ngated -
Are you passionate about the latest in #AI? Here's your chance to shine!
✍️ Join the #InfoQ Annual Article Writing Competition!
🏆 Win a #FreeTicket to #QCon or #InfoQDevSummit!
🔗 Submit by March 30, 2025: https://bit.ly/417KPtk
Which AI topic are you most excited to explore?
Explore topics like #LLMs, #SLMs, #vLLMs, #GenAI, #VectorDatabases, #ExplainableAI, #RAG, and more!
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Wasn’t this…obvious? 🤔
“Vector Databases Are The Wrong Abstraction”, Timescale (https://www.timescale.com/blog/vector-databases-are-the-wrong-abstraction/).
Via HN: https://news.ycombinator.com/item?id=41985176
#MachineLearning #Databases #Embeddings #VectorDB #DB #ML #AI #ArtificialIntelligence #VectorDatabases
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🎙️ Listen to the #InfoQ #podcast with Edo Liberty as he explores the importance of #VectorDatabases in the successful adoption of Generative AI and LLM-based applications.
Discover the difference between vector databases and traditional data stores: https://bit.ly/4bI0p2I
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🔥⏲️ Fudge Sunday #newsletter "Mind Mapping and A.I." A look at what's on my mind as a map with A.I.
#knowledgegraphs
#aiagents
#aiassistants
#vectordatabases
#mindmapping
#obsidian
#zettelkasten -
Everyone and their dog 🐶 is using #LLMs, #RAG and #vectordatabases now. What is your favorite vector database?
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🔻 @singlestoredb #llm #ai Did you miss our "Building Applications with Vector Databases" webinar? No problem unlock the potential of vector databases in app development by watching it now on demand: http://bit.ly/4a00P3e
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[ Vector databases: Shiny object syndrome and the case of a missing unicorn | VentureBeat ]
https://venturebeat.com/ai/vector-databases-shiny-object-syndrome-and-the-case-of-a-missing-unicorn/ #VectorDatabases #ShinyObject -
Guest @FranckPachot from #yugabyte joins our very own @noctarius2k in this episode of the weekly, 20 min #CloudCommute #podcast, talking about #distributedsql, #postgresql , #vectordatabases, and more. Tune in!
The 🎙️ is available on Spotify, iTunes, Pandora, Amazon Music, and more.
🎥👉 https://youtu.be/1EAKqwcP2SY
#vectordatabase #vectorsearch #vectordb #database #databases #postgres #postgressql
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#vectordatabases are amazing. Created an Q&A #ai running completely local. And it is shockingly good whilst being shockingly easy to implement...
I just dump a folder of PDFs into #apache #tika. Concat them, split them by /n/n to get paragraphs. Yoink them into #chromadb. Done
Now I can pose a question that will query chroma to return 20 semantically similar documents. Those documents are dumped into a mixtral-instruct in combination with the original question.
The results are nearly perfect! -
"Developers are moving fast to adopt new technologies that make their applications more powerful, their businesses more intelligent and their jobs easier. But AI systems that rely on #vectordatabases are introducing risks faster than the defenders can keep up."