learning was really the ability to have steps of a program that run in sequence and I think that we've actually started to see that what's important with deep learning is more the fact that we have a multi-step program rather than the fact that we've learned a representation if you look at things like res nuts for example they take one particular kind of representation and they update it several times back when deep learning first really took off in the academic world in 2006 when Geoff Hinton showed that you could train deep belief