Comment by michaelchisari
10 hours ago
It reinforces how to "learn AI" is to first master the problem domain.
I can use AI for coding after decades of coding. I can't use it for theoretical physics because I can't evaluate the responses.
10 hours ago
It reinforces how to "learn AI" is to first master the problem domain.
I can use AI for coding after decades of coding. I can't use it for theoretical physics because I can't evaluate the responses.
More and more the skill of being able to ask the right question seems critical to me, and I don't know how one can do that without deeper and deeper domain expertise.
Asking the right questions has almost always been one of if not the most important skills. There are often an almost infinite list of possible approaches, but knowing the domain, you can get close to optimum very quickly. If you just rely on the LLM, it will give you the most common bog standard approach, including the usual bugs and usual quirks.
> I can't use it for theoretical physics because I can't evaluate the responses.
A tool, even if it is a chisel, in the hands of a master sculptor would obviously result in a wildly different outcome.
> I can use AI for coding after decades of coding. I can't use it for theoretical physics because I can't evaluate the responses.
That is what will happen though to future generations: they won't be able to use it for anything because none of them will have the "decades of coding" experience that you have had the privelege to have without AI.
They will have decades of experience with AI and they will be able to guide them by sniffing their hallucinations from single words.
Hopefully in decades hallucinations will be largely solved.
1 reply →