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.

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

Google thinks it's found the answer, and it doesn't require more or better hardware. Originally detailed in an April 2025 paper, TurboQuant is an advanced compression algorithm that’s going viral over ...

At 100 billion lookups/year, a server tied to Elasticache would spend more than 390 days of time in wasted cache time. Cachee reduces that to 48 minutes. Everyone pays for faster internet. For ...

SIEVE is a new approach to web caching that's simpler and more effective than today's state-of-the-art algorithms, its creators claim — and big tech companies are taking notice. When you purchase ...

Part 2 looks at the tradeoffs between program and data cache optimizations, and shows how to choose the best compromise. As we saw in the first two parts of this series, cache optimization is often ...

Google's new TurboQuant algorithm drastically cuts AI model memory needs, impacting memory chip stocks like SK Hynix and ...

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