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

Deep neural networks (DNNs), the machine learning algorithms underpinning the functioning of large language models (LLMs) and ...

Computational neuroscientists are finding that deep-learning neural networks can be good explanatory models for the functional organization of living brains. Photograph: Hiné Mizushima/Quanta ...

Deep neural networks will move past their shortcomings without help from symbolic artificial intelligence, three pioneers of deep learning argue in a paper published in the July issue of the ...

As next-generation mobile networks grow more complex, high-density 5G environments are placing enormous pressure on ...

The 2012 breakthrough—the deep learning revolution—was the discovery that we can get dramatically better performance out of neural networks with not just a few layers but with many.

In most discussions, deep learning means using deep neural networks. There are, however, a few algorithms that implement deep learning using other kinds of hidden layers besides neural networks.

The UCLA team's all-optical deep neural network – which looks like the guts of a solid gold car battery – literally operates at the speed of light, and will find applications in image analysis ...

An artificial neural network (ANN) is a type of machine learning model inspired by neurons in the brain. 1,2 The individual components of the ANN receive information in numerical form, process it, and ...