A new technical paper titled “Hardware implementation of backpropagation using progressive gradient descent for in situ training of multilayer neural networks” was published by researchers at ...

Understand the Maths behind Backpropagation in Neural Networks. In this video, we will derive the equations for the Back ...

Obtaining the gradient of what's known as the loss function is an essential step to establish the backpropagation algorithm developed by University of Michigan researchers to train a material. The ...

For about a decade, computer engineer Kerem Çamsari employed a novel approach known as probabilistic computing. Based on probabilistic bits (p-bits), it’s used to solve an array of complex ...

Artificial intelligence might now be solving advanced math, performing complex reasoning, and even using personal computers, but today’s algorithms could still learn a thing or two from microscopic ...

The 2024 Nobel Prize in Physics has been awarded to scientists John Hopfield and Geoffrey Hinton “for foundational discoveries and inventions that enable machine learning with artificial neural ...