Neural networks are now applied across the spectrum of AI applications while deep learning is reserved for more specialized or advanced AI use cases.

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.

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

Brainchip has introduced a new generation of its unique, bio-inspired Akida line of licensable, configurable neural processing IP.

For decades, scientists have looked to light as a way to speed up computing. Photonic neural networks—systems that use light ...

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 ...

It's a novel idea, using light diffracted through numerous plates instead of electrons. And to some, it might seem a little like replacing a computer with an abacus, but researchers at UCLA have ...

By tapping into a decades-old mathematical principle, researchers are hoping that Kolmogorov-Arnold networks will facilitate scientific discovery.

Neural networks are machine-learning models that use layers of connected nodes, or neurons, to recognize patterns in datasets and perform tasks, like classifying images or recognizing speech.