Hackaday

TurboQuant: Reducing LLM Memory Usage With Vector Quantization

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

Google unveils TurboQuant, a new AI memory compression algorithm — and yes, the internet is calling it ‘Pied Piper’

Google’s TurboQuant has the internet joking about Pied Piper from HBO's "Silicon Valley." The compression algorithm promises ...

IndexCache, a new sparse attention optimizer, delivers 1.82x faster inference on long-context AI models

Researchers at Tsinghua University and Z.ai built IndexCache to eliminate redundant computation in sparse attention models ...

Why Google’s TurboQuant Algorithm is Disrupting the AI Memory Chip Market

Google's TurboQuant combines PolarQuant with Quantized Johnson-Lindenstrauss correction to shrink memory use, raising ...
Semiconductor Engineering

GDDR7: The Ideal Memory Solution In AI Inference

The generative AI market is experiencing rapid growth, driven by the increasing parameter size of Large Language Models (LLMs). This growth is pushing the boundaries of performance requirements for ...
Forbes

The Current And Future Path To AI Inference Data Center Optimization

Expertise from Forbes Councils members, operated under license. Opinions expressed are those of the author. We are still only at the beginning of this AI rollout, where the training of models is still ...

What is Google's new AI algorithm that has sent stocks of biggest memory makers plummeting?

Google's new TurboQuant algorithm drastically cuts AI model memory needs, impacting memory chip stocks like SK Hynix and ...