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

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.

The biggest memory burden for LLMs is the key-value cache, which stores conversational context as users interact with AI chatbots. The cache grows as conversations lengthen, ...

In his Sunday column, Jim Cramer explored key battleground issues for the stock market such as the Iran war and software sell ...

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

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 ...

More than 800 U.S. TikTok users shared their data with The Washington Post. We used it to find out why some people become power users, spending hours per day scrolling. Each circle in the chart ...

The computer system aboard the current Artemis II lunar space mission is from a different world that the one from the Apollo ...

As social media begins to play a bigger role in political campaigns, students should be careful of how they engage with ...

Google's TurboQuant reduces the KV cache of large language models to 3 bits. Accuracy is said to remain, speed to multiply.

Micron (MU) looked infallible just days ago, until Alphabet (GOOGL) broke the news that memory may no longer be in extreme ...