Hackaday

vector quantization

Large language models (LLMs) aren’t actually giant computer brains. Instead, they are massive vector spaces in which the probabilities of tokens occurring in a specific order is encoded. Billions of ...
SDxCentral

TurboQuant: Is compression all you need to beat the memory crunch?

Vector quantization, stock dips & RAMageddon – the real story behind how a memory compression algorithm went viral ...
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 ...
ZDNet

What Google's TurboQuant can and can't do for AI's spiraling cost

Google's TurboQuant can dramatically reduce AI memory usage. TurboQuant is a response to the spiraling cost of AI. A positive outcome is making AI more accessible by lowering inference costs. With the ...
Design-Reuse

Pyramid Vector Quantization and Bit Level Sparsity in Weights for Efficient Neural Networks Inference

This paper discusses three basic blocks for the inference of convolutional neural networks (CNNs). Pyramid Vector Quantization [1] (PVQ) is discussed as an effective quantizer for CNNs weights ...
SDxCentral

TurboQuant: Did Google just drop a compression algorithm capable of stemming RAMageddon?

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 ...
TMCnet

Intersignal Releases Braid Tendril v0.8.2-Alpha, a Secure Mesh Substrate for Sovereign Edge AI

Intersignal, an independent artificial intelligence research lab and systems engineering initiative, today announced the ...