Running a large language model is expensive, and a surprising amount of that cost comes down to memory, not computation.

A team of Google researchers has published a technique that could let developers squeeze roughly three times more throughput ...

Google AI breakthrough TurboQuant reduces KV cache memory 6x, improving chatbot efficiency, enabling longer context and faster real-time AI inference.

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.

Nvidia researchers have introduced a new technique that dramatically reduces how much memory large language models need to track conversation history — by as much as 20x — without modifying the model ...

Large language models (LLMs) aren’t actually giant computer brains. Instead, they are massive vector spaces in which the probabilities of tokens occurring in a specific order is encoded. Billions of ...

Google's TurboQuant reduces the KV cache of large language models to 3 bits. Accuracy is said to remain, speed to multiply. Google Research has published new technical details about its compression ...

FREMONT, Calif.--(BUSINESS WIRE)--Penguin Solutions, Inc. (Nasdaq: PENG), the AI factory platform company, today announced the industry's first production-ready KV cache server that utilizes CXL ...