Turning my old GPU into an LLM-hosting behemoth was the best decision ever ...

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 ...

Cloud AI isn't perfect, but it actually works.

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 ...

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 ...

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, which has been at the forefront of artificial intelligence (AI) innovation, has presented a solution to the ongoing memory semiconductor shortage. As the shortage and bottleneck issues ...

AI has a growing memory problem. 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 ...

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 ...