How do you know if you are sticking your head in the sand versus being reasonable?
One of the first things I learned in ML is that the model can only learn from the information in X. If X doesn't contain enough information to determine y, no amount of compute can fully recover it.
That's why I'm skeptical of grand claims about AI. Scaling can make models much better, but it can't create information that isn't there. An AI system can be extremely useful without becoming superhuman.
And what do you think about recent developments, for example Navier-Stokes? I always thought the same but now I have doubts, but maybe it is just psyops from openai.
It is speculated that there was context leak from a NYU Professor's chat I think? I contribute to SciPy heavily and I've seen AI shit the bed a few times now. So 13 million lines of lean? Hell no dude!