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

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.

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

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

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 LLC has unveiled a technology called TurboQuant that can speed up artificial intelligence models and lower their memory requirements. Amir Zandieh and Vahab Mirrokni, two of the researchers who ...

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 ...

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 ...