Nature

Vector Quantization and Learning Algorithms

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

TurboQuant Vector Quantization Cuts LLM Memory Use

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

TurboQuant: Reducing LLM Memory Usage With Vector Quantization

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

Google's new TurboQuant algorithm speeds up AI memory 8x, cutting costs by 50% or more

Within 24 hours of the release, community members began porting the algorithm to popular local AI libraries like MLX for ...
Business Wire

Elastic Announces Faster Filtered Vector Search with ACORN-1 and Default Better Binary Quantization Compression

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 ...
Design-Reuse

Dnotitia and Hanyang University Launch Open-Source Platform Benchmarking AI Quantization

Dnotitia Inc. (Dnotitia), a leading AI and semiconductor company, today announced the release of an open-source platform for evaluating AI quantization techniques. Jointly developed through an ...
Yahoo Finance

Elastic Announces Faster Filtered Vector Search with ACORN-1 and Default Better Binary Quantization Compression

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