Memory prices are plunging and stocks in memory companies are collapsing following news from Google Research of a breakthrough that will greatly reduce the amount of memory needed for AI processing.

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.

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

Processor architectures are evolving faster than ever, but they still lag the pace of AI development. Chip architects must ...

Apple is already planning a MacBook Neo refresh in 2027, but the runaway success of the current model is making it difficult ...

At its core, the TurboQuant algorithm minimizes the space required to store memory while also preserving model accuracy. To ...

Researchers have shown that blending quantum computing with AI can dramatically improve predictions of complex, chaotic ...

How does the brain categorize objects? Scientists reveal that categorization is a predictive process where the brain prepares an action plan before perceiving a stimulus.

Google's new TurboQuant algorithm drastically cuts AI model memory needs, impacting memory chip stocks like SK Hynix and Kioxia. This innovation targets the AI's 'memory' cache, compressing it ...