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 ...

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

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

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

Memory stocks declined Wednesday as investors reacted to Google’s announcement of TurboQuant, a new compression algorithm designed to reduce memory requirements for AI systems, even as the broader ...

Memory stocks fell Wednesday despite broader technology sector strength, with shares dropping after Google unveiled TurboQuant, a new compression algorithm that could reduce memory requirements for AI ...

Google introduced an algorithm that it says improves memory usage in AI models. Whether that will actually eat into business ...

Broadcom is padding post-quantum security with its Emulex SecureHBA adapters now integrated into Everpure’s FlashArray ...

The algorithm achieves up to an eight-times performance boost over unquantized keys on Nvidia H100 GPUs.

Overview AI systems are accelerating targeting, shrinking decision timelines from days to minutes.Autonomous drones and cyber ...

This article outlines the design strategies currently used to address these bottlenecks, ranging from data center systolic ...