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 ...

It’s a counterintuitive result that you might need to add noise to an input signal to get the full benefits from oversampling in analog to digital conversion. [Paul Allen] steps us through a ...

Quantization is a method of reducing the size of AI models so they can be run on more modest computers. The challenge is how to do this while still retaining as much of the model quality as ...