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.” [ ...

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

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

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

That much was clear in 2025, when we first saw China's DeepSeek — a slimmer, lighter LLM that required way less data center ...