Google Research recently revealed TurboQuant, a compression algorithm that reduces the memory footprint of large language ...

Google's TurboQuant algorithm compresses LLM key-value caches to 3 bits with no accuracy loss. Memory stocks fell within ...

The compression algorithm works by shrinking the data stored by large language models, with Google’s research finding that it can reduce memory usage by at least six times “with zero accuracy loss.” [ ...

Google has unveiled a new memory-optimization algorithm for AI inferencing that researchers claim could reduce the amount of ...

Google LLC has unveiled a technology called TurboQuant that can speed up artificial intelligence models and lower their ...

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, ...

Micron's shares are down after a new algorithm from Google spurred fears that memory demand could slow.

Some investors panicked over a new Google AI compression algorithm.

A more efficient method for using memory in AI systems could increase overall memory demand, especially in the long term.

South Korean equities took a sharp hit Friday as mounting concerns over reduced artificial intelligence memory demand dragged the KOSPI index to its lowest point in more than two weeks. The benchmark ...

The Google Research team developed TurboQuant to tackle bottlenecks in AI systems by using "extreme compression".

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.