Machine learning models called convolutional neural networks (CNNs) power technologies like image recognition and language ...

Modern artificial intelligence systems rely on deep neural networks (DNNs) that demand immense computational resources. Traditional electronic processors often struggle to meet the growing needs of ...

Explaining exactly how artificial neural networks (ANN) work in a mathless way can sometimes feel like a lost cause, though. They’re often likened to neural pathways in the human brain, but that’s not ...

On the hardware side, the next frontier for deep learning innovation will be in getting the performance, efficiency, and accuracy needed for inference at scale. But the newest battleground in software ...

Researchers at the University of Pennsylvania have developed a powerful new optical chip that can process almost 2 billion images per second. The device is made up of a neural network that processes ...

The type of artificial intelligence known as a neural network can be trained to complete tasks once thought to be exclusive to humans, such as driving a car, creating visual art, or composing a heavy ...

In a key step toward making large-scale optical neural networks practical, researchers have demonstrated a first-of-its-kind multilayer all-optical artificial neural network. Researchers detail their ...

ABSTRACT The authors have investigated the possibility of elaborating a new generation of radiative transfer models for climate studies based on the neural network technique. The authors show that ...

In the winter of 2011, Daniel Yamins, a postdoctoral researcher in computational neuroscience at the Massachusetts Institute of Technology, would at times toil past midnight on his machine vision ...