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The Unfair Comparison Between Deep Learning and Artificial Intelligence
This approach of trying to make sense of causality and time and space does remind me of earlier efforts to build artificial intelligence, what I suppose we used to call good old fashioned AI. These sorts of approaches were things we were trying in the 60s and 70s and early 80s but they didn't seem to yield lasting results except in some very narrow expert domains. So why would they be appropriate approaches now? Well, I think there's two things to realize there. The techniques actually do have some value. And then the other thing is that it's a totally unfair comparison. Deep learning was terrible in the 1950s. It was useless. It was just papers about it, it took