Google Research recently revealed TurboQuant, a compression algorithm that reduces the memory footprint of large language ...
The technique reduces the memory required to run large language models as context windows grow, a key constraint on AI ...
Google's TurboQuant algorithm compresses LLM key-value caches to 3 bits with no accuracy loss. Memory stocks fell within ...
Within 24 hours of the release, community members began porting the algorithm to popular local AI libraries like MLX for ...
Tom's Hardware on MSN
Google's TurboQuant reduces AI LLM cache memory capacity requirements by at least six times
The algorithm achieves up to an eight-times performance boost over unquantized keys on Nvidia H100 GPUs.
The Google Research team developed TurboQuant to tackle bottlenecks in AI systems by using "extreme compression".
Memory stocks fell Wednesday despite broader technology sector strength, with shares dropping after Google unveiled ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results