Many of the pioneers who began developing artificial neural networks weren’t sure how they actually worked - and we’re no more certain today.

This refers to the fact that — for complex neural networks — researchers don’t entirely understand how the individual neurons combine to create their final output.

By tapping into a decades-old mathematical principle, researchers are hoping that Kolmogorov-Arnold networks will facilitate scientific discovery.

An Alternative to Conventional Neural Networks Could Help Reveal What AI Is Doing behind the Scenes Despite their performance, current AI models have major weaknesses: they require enormous ...

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.