Neural networks and deep learning are closely related artificial intelligence technologies. While they are often used in tandem, there are key differences between them: Neural networks are a ...

Designed to mimic the brain itself, artificial neural networks use mathematical equations to identify and predict patterns in datasets and images.

A new idea called the “information bottleneck” is helping to explain the puzzling success of today’s artificial-intelligence algorithms—and might also explain how human brains learn.

Deep learning can go so much deeper. Now, the latest ImageNet winner is pointing to what could be another step in the evolution of computer vision---and the wider field of artificial intelligence.

One of the most influential technologies of the past decade is artificial neural networks, the fundamental piece of deep learning algorithms, the bleeding edge of artificial intelligence.

The technique relies on so-called artificial neural networks—a core element of current AI research. Artificial neural networks do not mimic precisely how actual neurons work.

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 ...

Discover the best deep learning software for training and deploying neural networks with powerful features and customizable options.

As the world grapples with climate change and dwindling fossil fuel reserves, biodiesel emerges as a promising renewable ...