You take symbol A and derive another symbol from it or combine multiple symbols to form new symbols.
You can approximate this through statistics but sometimes approximations aren't enough.
Maybe it's cheating, but after all, this is the only way humans can do universal computation- we can't hold an infinite tape in our head either, and neither can a CPU, we have to give it sufficient scratch space to act as the tape.
Alternatively, perhaps there's a (very large) neural net that can prove things about Turing machines that aren't too large. It only has finite input and finite output (it's not Turing complete) but it can prove stuff about smallish Turing machines, providing the proofs aren't too long. That seems reasonable, because that's what humans do when we prove stuff about Turing machines! Perhaps neural nets could never actually do this, either they're fundamentally not capable or we never work out how to actually find one that does, but it seems possible?
A method of producing statistical correlations is a product of a reasoning mind and could be thought of as a subset of reasoning (if by "subset" we assume "everything produced by a reasoning mind via an act of reasoning"), but in order to recognise this "subset" another reasoning mind should firstly internalise the notions of statistics that are external phenomena to an act of reasoning itself. And "the act of reasoning" isn't proven to be "just something that produces correlations", it's more than that and nobody knows what exactly it is. Otherwise AI would be solved long time ago.