Neural networks have revolutionized artificial intelligence. Here’s a look at the advantages, science, architecture behind them.

If you are wondering what is a neural network and how do they work in regards to artificial intelligence. This guide will provide insight ...

Neural networks today do everything from cameras to translations. A professor of computer science provides a basic explanation of how neural networks work.

We’re told neural networks ‘learn’ the way humans do. A neuroscientist explains why that’s not the case — and why AI can't think like us yet.

They can use neural networks to find patterns and associations beyond the subject of chemotherapy. Artificial neural networks, as they currently stand, don't create new answers out of existing data.

Neuroscientists are finding that deep-learning networks, often criticized as “black boxes,” can be good models for the organization of living brains.

Right now, researchers can only assess neural networks based on their final decisions–we don’t really understand how they get to those decisions. That’s a big problem.

How do neural networks work? Neural networks were first developed in the 1950s to test theories about the way that interconnected neurons in the human brain store information and react to input data.

Learn about the most prominent types of modern neural networks such as feedforward, recurrent, convolutional, and transformer networks, and their use cases in modern AI.