Weaviate Blog

A gentle introduction to Large Language Models (LLMs) - how they work and what they learn.

Using the Weaviate Tile Encoder to compress vectors with Product Quantization.

Implementing HNSW + Product Quantization (PQ) vector compression in Weaviate.

Weaviate 1.18 introduces Faster Filtering through Bitmap Indexing, HNSW-PQ, Cursor API, and more! Learn all about it.

Did you know that Weaviate can summarize information during retrieval? Learn how you can summarize your data to tackle the problem of information overload.

LangChain is one of the most exciting new tools in AI. It helps overcome many limitations of LLMs, such as hallucination and limited input lengths.

Learn about the six pillars outlining how Weaviate will evolve in 2023.

Recent advances in AI are breathing new life into podcasting! The Whisper speech-to-text model is a game-changer!

Machine learning models can create beautiful and novel images. Learn how Diffusion Models work and how you could make use of them.

Get an intuitive understanding of what exactly vector embeddings are, how they're generated, and how they're used in semantic search.

Ever wonder how Weaviate turns objects into vectors, behind-the-scenes? Find out in this post!

Learn about the new hybrid search feature that enables you to combine dense and sparse vectors to deliver the best of both search methods.