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

Google says its new TurboQuant method could improve how efficiently AI models run by compressing the key-value cache used in LLM inference and supporting more efficient vector search. In tests on ...

(Nanowerk News) We are in a fascinating era where even low-resource devices, such as Internet of Things (IoT) sensors, can use deep learning algorithms to tackle complex problems such as image ...

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.

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

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

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

Walk through enough industrial AI deployments and a pattern becomes uncomfortable to ignore. The pilot works. The model ...

The next-generation MTIA chip could be expanded to train generative AI models. The next-generation MTIA chip could be expanded to train generative AI models. Meta promises the next generation of its ...