Universal approximation is like saying that a problem is computable
sure, that gives some relief - but it says nothing in practice unlike f.e. which side of P/NP divide the problem is on
Universal approximation is like saying that a problem is computable
sure, that gives some relief - but it says nothing in practice unlike f.e. which side of P/NP divide the problem is on
> unlike f.e. which side of P/NP divide the problem is on
Actually the P/NP divide is a similar case in my opinion. In practice a quadratic algorithm is sometimes unacceptably slow and an NP problem can be virtually solved. E.g. SAT problems are routinely solved at scale.
An NP problem can contain subproblems that are not worst case problems.
It's similar to the gap between pushdown automata and Turing machines. You can check if pushdown automata will terminate or not. You can't do it for Turing machines, but this doesn't stop you from running a pushdown automata algorithm on the turning machine with decidable termination.