I think comparing to humans is a bit of a distraction, unless what you care about is replicating the way human intelligence works in AI. The mechanisms by which

I think comparing to humans is a bit of a distraction, unless what you care about is replicating the way human intelligence works in AI. The mechanisms by which learning is done (in these cases self-supervised and supervised learning) are not at all the same as humans have, so it's unsurprising the qualitative aspects are different. It may be argued we need more human-like learning mechanisms. Then again, if we need internet-scale data to achieve human-level general intelligence, so what? If it works it works. Of course, the comparison has some value in terms of knowing what can be improved and so on, especially for RL. But I wouldn't call this a 'troubling problem'.