Toward Computers That Teach Themselves

As powerful as reinforcement learning is, Dr. LeCun says he believes that other forms of machine learning are more critical to general intelligence. "My money is on self-supervised learning," he said, referring to computer systems that ingest huge amounts of unlabeled data and make sense of it all without supervision or reward. He is working on models that learn by observation, accumulating enough background knowledge that some sort of common sense can emerge. "Imagine that you give the machine a piece of input, a video clip, for example, and ask it to predict what happens next," Dr. LeCun said in his office at New York University, decorated with stills from the movie "2001: A Space Odyssey." "For the machine to train itself to do this, it has to develop some representation of the data. It has to understand that there are objects that are animate and others that are inanimate. The inanimate objects have predictable trajectories, the other ones don't."