Systems that emulate biological neural networks offer an efficient way of running AI algorithms, but they can’t be trained using the conventional approach. The symmetry of these ‘physical’ networks ...

Neural networks are computing systems designed to mimic both the structure and function of the human brain. Caltech researchers have been developing a neural network made out of strands of DNA instead ...

A landmark has been reached in the field of physics and artificial intelligence with the successful resolution of a ...

John Hopfield and Geoffrey Hinton won the Nobel Prize in Physics for their work on artificial neural networks and machine learning. Jonathan Nackstrand / AFP via Getty Images A pair of scientists—John ...

Deep neural networks (DNNs), the machine learning algorithms underpinning the functioning of large language models (LLMs) and other artificial intelligence (AI) models, learn to make accurate ...

Performing a new task based solely on verbal or written instructions, and then describing it to others so that they can reproduce it, is a cornerstone of human communication that still resists ...

The simplified approach makes it easier to see how neural networks produce the outputs they do. A tweak to the way artificial neurons work in neural networks could make AIs easier to decipher.

For all their brilliance, artificial neural networks remain as inscrutable as ever. As these networks get bigger, their abilities explode, but deciphering their inner workings has always been near ...