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 ...

More information: Lilly May et al, Pre-training artificial neural networks with spontaneous retinal activity improves motion prediction in natural scenes, PLOS Computational Biology (2025). DOI ...

Researchers at TUM trained artificial neural networks using biological data from the early visual system development. These networks completed tasks more quickly and accurately than those without ...

Artificial neural networks leverage the architecture of the human brain to improve numerous technologies and systems, from basic science and medicine to finance and social media.

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, ...

A team has developed a novel approach for comparing neural networks that looks within the 'black box' of artificial intelligence to help researchers understand neural network behavior. Neural ...

What goes on in artificial neural networks work is largely a mystery, even to their creators. But researchers from Anthropic have caught a glimpse. For the past decade, AI researcher Chris Olah ...

Artificial neural networks trained via reinforcement learning developed body-part-centered receptive fields that closely match those of biological peripersonal neurons.

However, these artificial neural networks are essentially just piles of maths inside a computer, and while they are capable of great things, the technology hasn’t yet shown the capability to ...

Researchers have examined a deep neural network—one type of artificial intelligence, a type that’s notoriously enigmatic on the inside—with a well-worn type of mathematical analysis that ...

Nature Biotechnology - Artificial neural networks have been applied to problems ranging from speech recognition to prediction of protein secondary structure, ...