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

Google unveils TurboQuant, PolarQuant and more to cut LLM/vector search memory use, pressuring MU, WDC, STX & SNDK.

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

Extracting and analyzing relevant medical information from large-scale databases such as biobanks poses considerable challenges. To exploit such "big data," attempts have focused on large sampling ...

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.” [ ...

The Big Arch is a burger for its times, which is not to say it’s the burger for its times. Two months after Health Secretary Robert F. Kennedy Jr. flipped the old food pyramid on its head, encouraging ...

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

It remains to be seen how many NFL stars the 2026 draft will produce, but the Scouting Combine proved at least one thing: this class offers plenty of speed. Arkansas quarterback Taylen Green, Oregon ...

Hopefully that means a little less RAMpocalypse.

Google has published TurboQuant, a KV cache compression algorithm that cuts LLM memory usage by 6x with zero accuracy loss, ...