What if the future of artificial intelligence wasn’t about building bigger, more complex models, but instead about making them smaller, faster, and more accessible? The buzz around so-called “1-bit ...

Reducing the precision of model weights can make deep neural networks run faster in less GPU memory, while preserving model accuracy. If ever there were a salient example of a counter-intuitive ...

Slim-Llama reduces power needs using binary/ternary quantization Achieves 4.59x efficiency boost, consuming 4.69–82.07mW at scale Supports 3B-parameter models with 489ms latency, enabling efficiency ...