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

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 announced a major quantum breakthrough using its Willow chip and the Quantum Echoes algorithm. The new method performed a complex physics task 13,000 times faster than the world’s fastest ...

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 ...

The compression algorithm works by shrinking the data stored by large language models, with Google’s research finding that it can reduce memory usage by at least six times “with zero accuracy loss.” ...

Enabled by the introduction of its Willow quantum chip last year, Google today claims it's conducted breakthrough research that confirms it can create real-world applications for quantum computers.