Google Deep Mind and Google Labs released their new AI hurricane model to the public. The Google team claims its AI model ...

This important study demonstrates the significance of incorporating biological constraints in training neural networks to develop models that make accurate predictions under novel conditions. By ...

An autonomous drone carrying water to help extinguish a wildfire in the Sierra Nevada might encounter swirling Santa Ana winds that threaten to push it off course. Rapidly adapting to these unknown di ...

This type of neural net is designed to closely approximate the physical structure of the brain. Spiking neural nets often move information according to rules collectively described as the "leaky ...

Activation functions play a critical role in AI inference, helping to ferret out nonlinear behaviors in AI models. This makes them an integral part of any neural network, but nonlinear functions can ...

They recognized that even if the single-value functions generated by the theorem were not smooth, the network could still approximate them with smooth functions. They further understood that most of ...

A tweak to the way artificial neurons work in neural networks could make AIs easier to decipher. Artificial neurons—the fundamental building blocks of deep neural networks—have survived almost ...

A neural network is a series of algorithms that seek to identify relationships in a data set via a process that mimics how the human brain works.

bestdesigns/Getty Images. A neural net -- which is at the heart of most conventional, advanced AIs -- mimics the way our brains work. Just as our brains send and receive electrical impulses that ...

If the network is more transparent, it’s easier to determine where the problems are cropping up. Of course. And if the network is smaller, it’s easier from the point of view of a human.