A small error-correction signal keeps compressed vectors accurate, enabling broader, more precise AI retrieval.

Google (GOOG)(GOOGL) revealed a set of new algorithms today designed to reduce the amount of memory needed to run large language models and vector search engines. Shares of major memory and storage ...

BERLIN & NEW YORK--(BUSINESS WIRE)--Qdrant, the leading high-performance open-source vector database, today announced the launch of BM42, a pure vector-based hybrid search approach that delivers more ...

Google thinks it's found the answer, and it doesn't require more or better hardware. Originally detailed in an April 2025 paper, TurboQuant is an advanced compression algorithm that’s going viral over ...

The biggest memory burden for LLMs is the key-value cache, which stores conversational context as users interact with AI chatbots. The cache grows as conversations lengthen, ...

The primary purpose of artificial intelligence is to help people become more creative, productive and ingenious. Targeted at citizen and enterprise developers equally, Vector Search for MongoDB Atlas ...

Learn why Google’s TurboQuant may mark a major shift in search, from indexing speed to AI-driven relevance and content discovery.

Open-source vector database provider Qdrant has launched BM42, a vector-based hybrid search algorithm intended to provide more accurate and efficient retrieval for retrieval-augmented generation (RAG) ...

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More As generative AI usage has grown dramatically in the last several years, ...

Pinecone, the vector database company, has announced the launch of Pinecone Serverless, a cheaper, faster and multi-tenant database that helps in building modern, LLM-based applications. Pinecone was ...