We could train AI models to simplify models in ways that require much less "intelligence" in the given domain.
For instance, we could ask AI to simplify the "essence" of the problems it solves in a similar manner to how Einstein and Feynmann simplified laws of Physics. With train/elevator metaphors or representations like Feynmann diagrams.
Of course, such explanations don't give the depth of understanding required to actually do the tensor calculus needed to USE theories like General Relativity or Quantum Electrodynamics.
But it's enough to give us a fuzzy feeling that we understand at least some of it.
The REAL understanding, ie at a level where we can in principle repeat the predictions, may require intuitions so complex that our human brain wouldn't be able to wrap itself around it.
For instance, we could ask AI to simplify the "essence" of the problems it solves in a similar manner to how Einstein and Feynmann simplified laws of Physics. With train/elevator metaphors or representations like Feynmann diagrams.
Of course, such explanations don't give the depth of understanding required to actually do the tensor calculus needed to USE theories like General Relativity or Quantum Electrodynamics.
But it's enough to give us a fuzzy feeling that we understand at least some of it.
The REAL understanding, ie at a level where we can in principle repeat the predictions, may require intuitions so complex that our human brain wouldn't be able to wrap itself around it.