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Geoffrey Hinton (now a Nobel Prize winner!) himself did a summary. I think it is the single best summary on this topic.

  Our labeled datasets were thousands of times too small.
  Our computers were millions of times too slow.
  We initialized the weights in a stupid way.
  We used the wrong type of non-linearity.





That is a pithier formulation of the widely accepted summary of "more data + more compute + algo improvements"

No, it isn't. It emphasizes importance of Glorot initialization and ReLU.



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