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 ...

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 ...

A technical paper titled “Training neural networks with end-to-end optical backpropagation” was published by researchers at University of Oxford and Lumai Ltd. “Optics is an exciting route for the ...