Stop thinking you need a $5,000 rig to run local AI — I finally ran a local AI on my old PC, and everything I believed was ...

RAM prices are enough to make you choke on your toast, so Google Research has turned up with TurboQuant to cram LLMs into less memory. TurboQuant is pitched as a compression trick for the key-value ...

Claude, Gemini, and ChatGPT all have the same flaw — and it’s not privacy or price ...

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 ...

We have seen the future of AI via Large Language Models. And it's smaller than you think. That much was clear in 2025, when ...

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.

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 ...

TL;DR: Google developed three AI compression algorithms-TurboQuant, PolarQuant, and Quantized Johnson-Lindenstrauss-that reduce large language models' KV cache memory by at least six times without ...

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 ...