When Hinton gave a lecture at the annual NIPS conference, then held in Vancouver, on his sixtieth birthday, the phrase “deep learning” appeared in the title for the first time. It was a cunning piece of rebranding. Referring to the multiple layers of neural networks, there was nothing new about “deep learning.” But it was an evocative term designed to galvanize research in an area that had once again fallen from favor. He knew the name was a good one when, in the middle of the lecture, he said everyone else was doing “shallow learning,” and his audience let out a laugh. In the long term, it
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