Sure, GPT has to model H -- that's a way of putting it. However think of how the algorithm producing GPT works (and thereby how GPT models QAWH) -- it produces a set of weights which interpolate between the training data --- even if we give it QAWH as training data, implementing the same QAWH patterns would require more storage capacity than is physically possible.
I think there's a genuine ontological (practical, empirical, also) difference between how a system scales with these "inputs". In otherwords if a machine is a `A = m(Q | World, Hidden)`, and a person is a `A = p(Q | World, Hidden)` then their complexity properties *matter*.
We know that the algorithm which produces `m` does so with exponential complexity; and we know that the algorithm producing `p` doesnt. In otherwords, for a person to answer `A` in the relevant ways, does not require exponential space/time. We know that NNs are already exponential scaling in their parameters in their even fairly radically stupid solutions (ie., ones which are grossly insensitive even to W).
So whilst `m` and `p` are equivalent if all we want is an accurate mapping of `Q`-space to `A`-space, they arent equivalent in their complexity properties. This inequivalence makes `m` physically impossible, but i also think, just not intelligent.
As in, it was intelligent to write the textbook; after its written, the HDD space which stores it isnt "intelligent". Intelligence is that capacity which enables low-complexity systems to do "high-complexity" stuff. In other words, that we can map-out QAWH with physically-possible, indeed, ordinary capacities -- our-doing-that is intelligence.
I think this is a radically empirical question, rather than a merely philosophical one. No algorithm which relies on interpolation of training data will have the right properties; it just wont, as a matter of fact, answer questions correclty.
You cannot encode the whole QAWH-space in parameters. Interpolation, as a strategy, is exponential-scaling; and cannot therefore cover even a tiny fraction of the space.
Ie., if I ask "what did you think of will smith hitting christopher walken?" it is unlikely to reply, "I think you mean Chris Rock" firstly; and then if will does hit walken, to reply, "I think Walken deserved it!".
Interpolation, as a strategy, cannot deal with the infinities that counter-factuals require. We are genuinely able to perform well in an infinite number of worlds. We do that by not modelling QA pairs, at all; nor even the W-infinity.
Rather, we implement "taste, imagination, curiosity" etc. and are able to simulate (and much else) everything we need. We arent an interpolation through relevant hisotry, we are a machine direclty responsible to the local environment in ways that show a genuine deep understanding of the world and abiliyt to similate it.
This ability enables `p` to have a lower complexity than `m`, and thereby be actually intelligent.
As an empirical matter, i think you just can't build a system which actually succeeds in answering the-right-way. It isnt intelligent; but likewise, it also just doesnt work.