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 ...

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

Google thinks it's found the answer, and it doesn't require more or better hardware. Originally detailed in an April 2025 ...

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

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 ...

High-performance open-source vector database Qdrant today announced the launch of BM42, a new pure vector-based hybrid search approach for modern artificial intelligence and retrieval-augmented ...

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 ...

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, ...