Weight decay and weight restriction are two closely related, optional techniques that can be used when training a neural network. This article explains exactly what weight decay and weight restriction ...

Artificial intelligence in its deep learning form is producing neural networks that will have trillions and trillions of neural weights, or parameters, and the increasing scale presents special ...

Special-purpose chip that performs some simple, analog computations in memory reduces the energy consumption of binary-weight neural networks by up to 95 percent while speeding them up as much as ...

The brain processes information through multiple layers of neurons. This deep architecture is representationally powerful, but complicates learning because it is difficult to identify the responsible ...

The growing energy use of AI has gotten a lot of people working on ways to make it less power hungry. One option is to develop processors that are a better match to the sort of computational needs of ...