Deep learning has rapidly knocked down some longstanding challenges in AI—but it doesn’t immediately seem well suited to many that remain. Problems that involve reasoning or social intelligence, such as weighing up a potential hire in the way a human would, are still out of reach, he said. “All of the models that we have learned how to train are about passing a test or winning a game with a score, [but] so many things that intelligences do aren’t covered by that rubric at all,” he said.
Deep learning works brilliantly at capturing all the edgy patterns in our syntactic gymnastics, but because it lacks a pre-coded base of procedural knowledge it can’t use its language skills to reason or to conceptualize. An intelligent machine needs both kinds of thinking.