Vector quantisation and its associated learning algorithms form an essential framework within modern machine learning, providing interpretable and computationally efficient methods for data ...

Large language models (LLMs) aren’t actually giant computer brains. Instead, they are massive vector spaces in which the ...

TurboQuant vector quantization targets KV cache bloat, aiming to cut LLM memory use by 6x while preserving benchmark accuracy ...

On March 24, 2026, Google Research announced a new suite of compression techniques for large-scale language models and vector search engines: TurboQuant, PolarQuant, and Quantized ...

SAN FRANCISCO--(BUSINESS WIRE)--Elastic (NYSE: ESTC), the Search AI Company, announced new performance and cost-efficiency breakthroughs with two significant enhancements to its vector search. Users ...

Elastic (NYSE: ESTC), the Search AI Company, announced new performance and cost-efficiency breakthroughs with two significant enhancements to its vector search. Users now benefit from ACORN, a smart ...

Now-a-days, data on the web is increasing like water in the ocean. Big data is one of the emerging areas that deal with large velocity of data. “Big data is not defined in single world data sets that ...

AI has a growing memory problem. 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 ...