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

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

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

Google’s TurboQuant has the internet joking about Pied Piper from HBO's "Silicon Valley." The compression algorithm promises to shrink AI’s “working memory” by up to 6x, but it’s still just a lab ...

Google’s TurboQuant could cut LLM memory use sixfold, signaling a shift from brute-force scaling to efficiency and broader AI ...

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

With TurboQuant, Google promises 'massive compression for large language models.' ...

Effective compression is about finding patterns to make data smaller without losing information. When an algorithm or model can accurately guess the next piece of data in a sequence, it shows it’s ...

Microsoft is open-sourcing its cloud-compression algorithm and optimized hardware implementation for cloud storage. Microsoft is contributing that algorithm, known as ""=""> plus the associated ...