When I apply that machine (with its giant pool of pirated knowledge) _to my inputs and context_ I can get results applicable to my modestly novel situation which is not in the training data. Perhaps the output is garbage. Naturally if my situation is way out of distribution I cannot expect very good results.
But I often don't care if the results are garbage some (or even most!) of the time if I have a way to ground-truth whether they are useful to me. This might be via running a compile, a test suite, a theorem prover or mk1 eyeball. Of course the name of the game is to get agents to do this themselves and this is now fairly standard practice.
¹https://chatgpt.com/share/69367c7a-8258-8009-877c-b44b267a35...
It does this all the time, but as often as not then outputs nonsense again, just different nonsense, and if you keep it running long enough it starts repeating previous errors (presumably because some sliding window is exhausted).
I use AI as a means of last resort only now and then mostly as a source of inspiration rather than a direct tool aiming to solve an issue. And like that it has been useful on occasion, but it has at least as often been a tremendous waste of time.