While neural networks (also called “perceptrons”) have been around since the 1940s, it is only in the last several decades where they have become a major part of artificial intelligence.This ...

Artificial Neural Network Architecture. Scientists design ANNs to function like neurons. 6 They write lines of code in an algorithm such that there are nodes that each contain a mathematical function, ...

The brains of humans and other primates are known to execute various sophisticated functions, one of which is the ...

How reliable is artificial intelligence, really? An interdisciplinary research team at TU Wien has developed a method that ...

Deep learning models, such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs) are designed to ...

Let us consider an example problem, for which an artificial neural network is readily applicable. Of two classes of cancer, only one responds to a certain treatment.

In addition to studying network similarity, the paper is a crucial step toward characterizing the behavior of robust neural networks. Neural networks are high performance, but fragile. For example ...

A new machine learning approach tries to better emulate the human brain, in hopes of creating more capable agentic AI.

Using a neural network trained with simulations of supermassive black holes, astronomers have found that the one at the ...

AI models like artificial neural networks and language models help scientists solve a variety of problems, from predicting the 3D structure of proteins to designing novel antibiotics from scratch.

AI has become shorthand for machine learning using artificial neural networks. This technology – developed by Hopfield and Hinton – is based on the structure of the brain.