These parts raise issues for me: > the underlying reason for such mistakes is that “... all the impressive achievements of deep learning amount to just curve f

These parts raise issues for me: > the underlying reason for such mistakes is that “... all the impressive achievements of deep learning amount to just curve fitting.” The key, as Pearl suggests, is to replace “reasoning by association” with “causal reasoning” —the ability to infer causes from observed phenomena. This seems hypocritical in that for tens of thousands of years and for a large part of the population is still what humans do. Only a subset generally apply true logical reasoning. It's also funny that we're now saying logical circuits can't do logic. > “we need to stop building computer systems that merely get better and better at detecting statistical patterns [...]—and start building computer systems that from the moment of their assembly innately grasp three basic concepts: time, space, and causality. This seems like a mistake assuming something we ourselves haven't determined are fundamental concepts. I would prefer if the data produced the concepts and potential proofs or disproofs.