Even though traditional databases now support vector types, vector-native databases have the edge for AI development. Here’s how to choose. AI is turning the idea of a database on its head.

Vector embeddings are the backbone of modern enterprise AI, powering everything from retrieval-augmented generation (RAG) to semantic search. But a new study from Google DeepMind reveals a fundamental ...

First solution to combine dense, sparse, and image embeddings with vector search in one managed environment. Reduces latency, cuts network costs, and simplifies hybrid and multimodal search BERLIN & ...

A new open-source framework called PageIndex solves one of the old problems of retrieval-augmented generation (RAG): handling very long documents. The classic RAG workflow (chunk documents, calculate ...