These aren't just repeating what they've been taught. The "stochastic parrot" thing is an irritating common misconception I think.

One way AIs really really really excel is pulling together a lot of different data sources and reasoning over that data. In the past sure we could collect data and create huge datasets, but the analysis of that data - extracting themes, finding commonality or issues etc - either required extensive human research and analysis at best, or at worst crude regexes or keyword matching.

Now an AI can pour over that data and make its own inferences and decisions and findings that we've simply not been able to do before at this kind of speed or scale just because of time and resources.

And the AI, having done that, can propose new things for e.g. training, i.e. new things that no human has ever done before that the AI is simply repeating. For example it can propose a task that it knows from it's research is hard for it to solve currently, and then we just throw compute and randomness at it to find the "best" solution from many many attempts, then repeat until we hill-climb up to a perfect 1.0 score (... although of course we have to try and avoid cheating/attempts to short-ciruit the eval)

So this could be coding tasks, UI control tasks, protein folding, maths, chemistry etc etc. Anything that is easily and objectively programmatically scored. You can run this in a loop many times, each time you go around the loop the model gets smarter, learns more things from it's research, new areas of loss it can optimise etc etc.

It's harder where there is not a way to objectively score the outcomes (e.g. art, creative writing). Often this uses a fuzzy "judge" model that is trained specifically to give the work a score based on it's appraisal. This works but you can see how we might end up with feedback loops, so often it is paired with humans who provide feedback to provide supervised fine tuning datasets.

Tl:Dr - It's not just "repeating what it's seen". AI is finding new ideas and creating new things millions of times a day, and that is just software engineers asking it to write code or fix bugs, let alone people using it for actual research or whatever.