Envisioning a Future with Generalized Learning Robots

The robots that have taken on tasks in the real world - which is to say the world where physics apply - are primarily programmed to do a specific job, such as welding a joint in a car or sweeping up cat hair. So what if robots could learn, and take it a step further - what if they could teach themselves, and pass on their knowledge to other robots? Where could that take machines, and the notion of machine intelligence? And how fast could we get there? Those are the questions our guest Sergey Levine, an assistant professor at UC Berkeley's department of Electrical Engineering and Computer Sciences, is finding answers to.