New method for comparing neural networks exposes how artificial intelligence works
The "black box" of artificial intelligence has been examined by a team at Los Alamos National Laboratory to create a novel method for comparing neural networks that will aid researchers in understanding neural network activity. In applications like virtual assistants, facial recognition technology, and self-driving cars, neural networks are used to identify patterns in datasets. Haydn Jones, a researcher in the Advanced Research in Cyber Systems group at Los Alamos, stated that the artificial intelligence research community "doesn't necessarily have a thorough knowledge of what neural networks are doing; they give us good outcomes, but we don't know how or why." "Our new approach performs a better job of comparing neural networks, which is key toward better understanding the mathematics behind AI," says the author. The study "If You've Trained One You've Trained Them All: Inter-Architecture Similarity Increases With Robustness," w...