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 ...

According to a new study published this morning in Nature, an algorithm trained via a deep neural network has been able to perform on par with board-certified cardiologists at the annotation of 12 ...

The general definition of quantization states that it is the process of mapping continuous infinite values to a smaller set of discrete finite values. In this blog, we will talk about quantization in ...