People calling neural-net classifiers "old-school" AI confused me. For a second I thought they were talking about the really old "expert systems" with everything being a pile of hard-coded rules.
It still feels like there's a place for these rule based systems(Prolog?) to at least place some constraints on the output of non-deterministic, generative AI. If nothing else, have a generative AI generate the ruleset so you have some explicit rules you can audit from time to time.
Yeah, i think one potential way to use blackbox ai in newer systems is having guardrails that are validated as safe (but perhaps non-optimal) and ensuring that the ai takes action within that sample space. Obviously this is hard problem, but might open the doors for policies (in self-driving cars, for example) to be entirely ai driven.
A friend of mine was just telling me how he asked GPT-3 to write a simple program in Prolog and it seemed to get it right. He didn't try compiling it, but he has enough experience w/ Prolog to say that it was more or less correct.
I'm pretty cynical on LLMs(i.e. they're not intelligent and won't take all our jobs soon), but am coming around on their importance and capabilities.
