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.

Google said this week that its research on a new compression method could reduce the amount of memory required to run large language models by six times. SK Hynix, Samsung and Micron shares fell as ...

Alphabet (GOOG) and Micron (MU) — Google’s TurboQuant breakthrough reduces memory usage by 6x and attention computation by 8x without accuracy loss, potentially altering the memory supercycle while ...

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

Micron (NASDAQ:MU) shares continue to be the talk of the town this year, with the memory chip juggernaut continuing to gain, ...

Google published a research blog post on Tuesday about a new compression algorithm for AI models. Within hours, memory stocks were falling. Micron dropped 3 per cent, Western Digital lost 4.7 per cent ...

Google's TurboQuant can dramatically reduce AI memory usage. TurboQuant is a response to the spiraling cost of AI. A positive outcome is making AI more accessible by lowering inference costs. With the ...

Google is packing ample amounts of static random access memory into a dedicated chip for running artificial intelligence models, following Nvidia's plans.

Memory prices are falling, and stock prices of memory companies took a hit, following news from Google Research of a breakthrough that will greatly reduce the amount of memory needed for AI processing ...

Even if you don’t know much about the inner workings of generative AI models, you probably know they need a lot of memory. Hence, it is currently almost impossible to buy a measly stick of RAM without ...