It’s good to be Yann LeCun.
Mark Zuckerberg recently handpicked the longtime NYU professor to run Facebook’s new artificial intelligence lab. The IEEE Computational Society just gave him its prestigious Neural Network Pioneer Award, in honor of his work on deep learning, a form of artificial intelligence meant to more closely mimic the human brain. And, perhaps most of all, deep learning has suddenly spread across the commercial tech world, from Google to Microsoft to Baidu to Twitter, just a few years after most AI researchers openly scoffed at it.
All of these tech companies are now exploring a particular type of deep learning called convolutional neural networks, aiming to build web services that can do things like automatically understand natural language and recognize images. At Google, “convnets” power the voice recognition system available on Android phones. At China’s Baidu, they drive a new visual search engine. This kind of deep learning has many fathers, but its success should resonate with LeCun more than anyone. “Convolutional neural nets for vision—that’s what he pushed more than anybody else,” says Microsoft’s Leon Bottou, one of LeCun’s earliest collaborators.
He pushed it in the face of enormous skepticism. In the ’80s, when LeCun first got behind the idea of convnets—an approximation of the networks of neurons in the brain—the powerful computers and enormous data sets needed to make them work just didn’t exist. The very notion of a neural network had fallen into disrepute after it failed to deliver on the promises of scientists who first dreamed of artificial intelligence at the dawn of the computer age. It was hard to publish anything related to neural nets in the major academic journals, and this would remain the case in the ’90s and on into the aughts.
But LeCun persisted. “He kind of carried the torch through the dark ages,” says Geoffrey Hinton, the central figure in the deep learning movement. And eventually, computer power caught up with the remarkable technology.