So, I’m a big fan of Lex Fridman’s deep learning podcast. A big ago I watched one he did with Ian Goodfellow.

At the start of the interview Goodfellow describes how deep learning methods are distinguished by the fact that it involves a bunch of computations done in sequence rather than in parallel. (You can watch the video to get a better idea of what he was talking about).

Does anyone have any other examples of machine learning techniques that you feel fit his description of being deep? Just curious about this.