Qdrant, a leading provider of high-performance, open-source vector search, is offering a private beta of Qdrant Edge, a lightweight, embedded vector search engine designed for AI systems on devices ...

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

Qdrant, the open-source vector search engine built in Rust for production workloads, today announced $50 million in Series B funding led by AVP, with participation from Bosch Ventures, Unusual ...

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

Qdrant, the open-source vector search engine built in Rust for production workloads, announced it has secured $50 million in Series B funding will enable composable vector search as core ...

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 ...

MariaDB has recently released MariaDB Community Server 11.8 as generally available, its yearly long-term support (LTS) release for 2025. The new release introduces integrated vector search ...

Wikidata has built the semantic web backbone supporting knowledge cards in popular engines. Now, it's extending this foundation using a vector database to enhance its existing knowledge graph and ...

Most vector search systems struggle with a basic problem: how to break complex documents into searchable pieces. The typical approach is to split text into fixed size chunks of 200 to 500 tokens, this ...

Information retrieval systems are designed to satisfy a user. To make a user happy with the quality of their recall. It’s important we understand that. Every system and its inputs and outputs are ...