A New Way for Machines to See, Taking Shape in Toronto

In 2012, Geoffrey Hinton changed the way machines see the world. Along with two graduate students at the University of Toronto, Mr. Hinton, a professor there, built a system that could analyze thousands of photos and teach itself to identify common objects like flowers and cars with an accuracy that didn't seem possible. He and his students soon moved to Google, and the mathematical technique that drove their system -- called a neural network -- spread across the tech world. This is how autonomous cars recognize things like street signs and pedestrians. But as Mr. Hinton himself points out, his idea has had its limits.