I'd rather say that mathematics at academia aren't real mathematics. It pretty much depends on academia, of course, but what is generally taught to students und

I'd rather say that mathematics at academia aren't real mathematics. It pretty much depends on academia, of course, but what is generally taught to students under the name of "mathematics" (especially on technical programs, like engineering, CS, etc.) has less mathematical value than typical problem at Olympiads. But that wasn't my point, anyway. Yes, that is true that "pure something" is almost always significantly different from "something in the real life". That's pretty obvious, actually. I guess that there's virtually nothing in the "real life" that would consist from only one "core" activity. In fact, it's the opposite: you make some activity "pure" in order to master it, because in the real life there's so much that distracts you from mastering that one essential skill, whatever would it be. Plubmers and painters (and almost everyone else) must to be able to talk to others and to solve totally human-related problems in order to do their job. Person you would call sniper actually does much more running, crawling, waiting and hiding than shooting. Or does it really surprise anyone that policemen do tons of paperwork every day and not so much of that stuff they show in the movies? And somewhat opposite example: it's obvious that cook's work isn't only slicing vegetables, but have you ever seen how any real cook handles his knife? Please do, it's sight to behold. There's nothing "pure" in this world, no surprise here. So if it would be Yan LeCun writing something like this it would be justifiable (although I would be rather surprised to hear that), but in this particular case it's more like saying "Kaggle isn't important, data science is me!", in which case I find that NBA example to be OK. To summarise: "data science is more than building a model" — yes, "Machine learning isn't Kaggle competitions" — no.