[mdorazio]

It sort of does, though. Let's say we train an ML implementation so that it can recognize things with wheels and seats as vehicles. Now we show it a hovercraft. What will it do? How about a helicopter? All the human brain needs is a single example of people getting in or on something, and it transporting them from point A to point B in order to infer that the thing is a vehicle of some sort. This is because we are able to infer purpose of an object even if we have never seen it before. ML is just statistics - it implies no meaning or comprehension whatsoever beyond "thing A is statistically most like thing B I have seen before". There's an important difference between recognition and understanding, and current ML techniques are solidly in the former camp.