The difference between ML models and computers since the 1960s is that the ML models weren't programmed with predicates, they "learned" them from analyzing data, and can continue to learn in various ways from further data. That's a meaningful difference, and why the former may qualify as intelligent and the latter cannot.

But I agree in principle that LLMs can be distilled into large IF/THEN/ELSE trees, that's the lesson of BitNet 1-bit LLMs. The predicate tree being learned from data is the important qualifier for intelligence though.

Edit: in case I wasn't clear, I agree that a specific chain of IF/THEN/ELSE statements in a loop can be generally intelligent. How could it not, specific kinds of these chains are Turing complete after all, so unless you think the brain has some kind of magic, it too is reducible to such a program, in principle. We just haven't yet discovered what kind of chain this is, just like we didn't understand what kind of chain could produce distributed consensus before PAXOS.