I think that the idea that learning is what was missing from the prior generation of AI is the most important insight of this generation. There are many things

I think that the idea that learning is what was missing from the prior generation of AI is the most important insight of this generation. There are many things that we don't know how to implement from first principals but that can be implemented by a system that can learn. The problem now is that the substrates for learning are extremely low level, practically the raw inputs to the retina or pure symbols. In order to go beyond the admittedly impressive parlor tricks you can play with these kinds of inputs we need much higher level representations that can be the substrates for learning. We are still missing that ever illusive 'common sense' knowledge about the world that evolution baked into nervous systems millions of years ago, and it is not at all clear to me whether learning algorithms are going to be the tool that allows machines to build an actionable internal model of the world, evolution didn't do it by learning, it did it by billions of years of trial and error and the search space is unimaginably larger than that of something like go.