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 ...

Compression reduces bandwidth and storage requirements by removing redundancy and irrelevancy. Redundancy occurs when data is sent when it’s not needed. Irrelevancy frequently occurs in audio and ...

Google thinks it's found the answer, and it doesn't require more or better hardware. Originally detailed in an April 2025 ...

Bernstein upgraded Western Digital to Outperform from Market Perform, hiking its price target to $340 from $170, arguing that a sharp pullback driven by fears over Google’s new TurboQuant compression ...

Within 24 hours of the release, community members began porting the algorithm to popular local AI libraries like MLX for ...

At least one PC parts vendor that had stockpiled a load of DRAM components as prices skyrocketed is now apparently worried ...

DDR5 RAM prices are finally dropping after months of inflation, according to Wccftech. Consumers and hardware manufacturers ...

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 ...

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

Google's new TurboQuant algorithm drastically cuts AI model memory needs, impacting memory chip stocks like SK Hynix and Kioxia. This innovation targets the AI's 'memory' cache, compressing it ...