Artificial neural networks, the foundation of modern artificial intelligence, are often seen as black boxes. However, a new architecture called Kolmogorov-Arnold Networks (KANs) changes the game. These networks offer more interpretable and accurate results, while utilizing fewer learned parameters. The KANs are able to represent data in a more flexible manner, allowing for greater performance with fewer parameters compared to traditional systems. Researchers are already combining KANs with other architectures, such as convolutional neural networks and transformers, to achieve impressive results. While KANs take longer to train per parameter, they show great potential in advancing scientific research by unveiling new laws of nature.
https://spectrum.ieee.org/kan-neural-network