Modeled on the human brain, neural networks are one of the most common styles of machine learning. Get started with the basic design and concepts of artificial neural networks.

Neural networks, machine learning? Nobel-winning AI science explained Paris (AFP) – The Nobel Prize in Physics was awarded to two scientists on Tuesday for discoveries that laid the groundwork ...

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 ...

Don't know your machine learning from your evolutionary algorithms? Our handy A.I. buzzword guide is here to help.

New learning algorithms and architectures that are currently being developed for deep neural networks will only accelerate this progress.

A big challenge in neuroscience is understanding how the brain encodes information. Neural networks are turning out to be great code crackers.

To help them explain the shocking success of deep neural networks, researchers are turning to older but better-understood models of machine learning.

Princeton engineers used neural networks and metasurfaces to bend ultrahigh-frequency beams around obstacles, tackling signal collapse in cluttered environments.

Mark van der Wilk, an expert in machine learning at the University of Oxford, told AFP that an artificial neural network is a mathematical construct "loosely inspired" by the human brain.