The deepest problem with deep learning – Gary Marcus – Medium

On November 21, I read an interview with Yoshua Bengio in Technology Review that to a suprising degree downplayed recent successes in deep learning, emphasizing instead some other important problems in AI might require important extensions to what deep learning is currently able to do. I agreed with virtually every word and thought it was terrific that Bengio said so publicly. Instead I accidentally launched a Twitterstorm, at times illuminating, at times maddening, with some of the biggest folks in the field, including Bengio's fellow deep learning pioneer Yann LeCun and one of AI's deepest thinkers, Judea Pearl. Here's the tweet, perhaps forgotten in the storm that followed: For the record and for comparison, here's what I had said almost exactly six years earlier, on November 25, 2012, eerily similar, I stand by that -- which as far as I know (and I could be wrong) is the first place where anybody said that deep learning per se wouldn't be a panacea, and would instead need to work in a larger context to solve a certain class of problems. Bengio was pretty much saying the same thing.