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 ...
Tom's Hardware on MSN
Google's TurboQuant reduces AI LLM cache memory capacity requirements by at least six times
The algorithm achieves up to an eight-times performance boost over unquantized keys on Nvidia H100 GPUs.
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 ...
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 ...
Memory stocks fell Wednesday despite broader technology sector strength, with shares dropping after Google unveiled ...
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) ...
Kioxia Corporation today announced the successful demonstration of achieving high-dimensional vector search scaling to 4.8 billion vectors on a single server with its open-source KIOXIA AiSAQ(TM) ...
Nvidia has a structured data enablement strategy. Nvidia provides libaries, software and hardware to index and search data ...
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