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 ...
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 ...

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 Apple Silicon and llama.cpp.

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

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

How Unsloth Makes Fine-Tuning LLMs a Breeze to Boost AI Performance

Fine-tuning large language models (LLMs) might sound like a task reserved for tech wizards with endless resources, but the reality is far more approachable—and surprisingly exciting. If you’ve ever ...

large language models

Find the latest large language models news from Fast company. See related business and technology articles, photos, ...

PrismML Introduces Ternary Bonsai Model Family

PrismML, a pioneer in high-performance AI models, today announced the Ternary Bonsai model family: three state-of-the-art large language models available in 8B, 4B, and 1.7B parameter sizes, built on ...