RGB colors codes work the same way as vector embeddings 🌈 How? First, think about how we represent colors digitally: • Red might be (255, 0, 0) • An emerald could be (80, 200, 120) Each number represents how much red, green, or blue is in the color.

Don’t do RAG? Apparently Cache-Augmented Generation (CAG) is all you need 👀 (But is it?) The authors of this paper (arxiv.org/pdf/2412.15605) introduce a new question-answer method called CAG that utilizes long-context LLMs to generate a document cache instead of the normal “retrieval” part of RAG

Headed to AWS re:Invent this year? Make sure to stop by booth #1506 to answer these urgent questions: 🕵🏻‍♂️ Can Professor S and his team use the latest AI tech to stop a string of international art heists? Grab a copy of The Vector Vault to find out!

Hack Night Berlin is going to be WILD 🤩 See you there? lu.ma/hacknight-be...

Yes, you don’t need a vector database to do vector search. @victorialslocum.bsky.social shows you how - using just numpy. This article covers: • How does vector search work? • How to do vector search from scratch in Python • and more Learn more: weaviate.io/blog/vector-...

What do Hack Nights with Weaviate look like? Join us in Berlin on December 12 to see for yourself: lu.ma/hacknight-be...

Looking for a comprehensive guide on vector search? I’ve got you covered 💪 Learn about: 🔍 How it's different from keyword search 🐍 How to implement it from scratch 🚀 How it works in vector databases, and why it’s so fast 🗒️ Various types and use cases of vector search weaviate.io/blog/vector-...