Neural networks made from photonic chips can be trained using on-chip backpropagation – the most widely used approach to training neural networks, according to a new study. The findings pave the way ...

A new model of learning centers on bursts of neural activity that act as teaching signals — approximating backpropagation, the algorithm behind learning in AI. Every time a human or machine learns how ...

Five DECADES of research into artificial neural networks have earned Geoffrey Hinton the moniker of the Godfather of artificial intelligence (AI). Work by his group at the University of Toronto laid ...

In the realm of artificial intelligence and machine learning, neural networks have proven to be a powerful tool for solving complex problems. These networks, inspired by the workings of the human ...

A new technical paper titled “The backpropagation algorithm implemented on spiking neuromorphic hardware” was published by University of Zurich, ETH Zurich, Los Alamos National Laboratory, Royal ...

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 ...

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

The learning algorithm that enables the runaway success of deep neural networks doesn’t work in biological brains, but researchers are finding alternatives that could. In 2007, some of the leading ...