"This ability [...] to perform abstraction and reasoning, is arguably the defining characteristic of human cognition." He's on the right track. Of course, the

"This ability [...] to perform abstraction and reasoning, is arguably the defining characteristic of human cognition." He's on the right track. Of course, the general thrust goes beyond deep learning. The projection of intelligence onto computers is first and foremost wrong because computers are not able, not even in principle, to engage in abstraction, and claims to the contrary make for notoriously bad, reductionistic philosophy. Ultimately, such claims underestimate what it takes to understand and apprehend reality and overestimate what a desiccated, reductionistic account of mind and the broader world could actually accommodate vis-a-vis the apprehension and intelligibility of the world. Take your apprehension of the concept "horse". The concept is not a concrete thing in the world. We have concrete instances of things int he world that "embody" the concept, but "horse" is not itself concrete. It is abstract and irreducible. Furthermore, because it is a concept, it has meaning. Computers are devoid of semantics. They are, as Searle has said ad nauseam, purely syntactic machines. Indeed, I'd take that further and say that actual, physical computers (as opposed to abstract, formal constructions like Turing machines) aren't even syntactic machines. They do not even truly compute. They simulate computation. That being said, computers are a magnificent invention. The ability to simulate computation over formalisms -- which themselves are products of human beings who first formed abstract concepts on which those formalisms are based -- is fantastic. But it is pure science fiction to project intelligence onto them. If deep learning and AI broadly prove anything, it is that in the narrow applications where AI performs spectacularly, it is possible to substitute what amounts to a mechanical process for human intelligence.