[akiselev]

I think that's moot: based on the universal approximation theorem [1], a big enough model is indistinguishable from the human brain, regardless of whether the mechanism of action is fundamentally the same or not. I believe this applies to anything that can somehow be modeled with a continuous function - whether that's possible for the human brain is an open question, though we only need a certain fidelity to be useful.

The more useful question is: can the token prediction model scale to the level of a human intelligence within a reasonable power budget compared to a brain? It's comparing apples to oranges right now but the human brain consumes under 20 watts, a tiny fraction of the TDP of a single A100 GP, and the state of the art isn't even close in performance. We've got a long way to go before we can conclusively answer these questions.

[1] https://en.wikipedia.org/wiki/Universal_approximation_theore...

[checkyoursudo]

This is not the unchallenged, consensus position, though. A competing position within cognitive science is that intelligence requires embodiment, perception, metacognition, curiosity, etc., and that these factors that allow for the emergence of intelligence are indispensable, more or less.

See, e.g., https://plato.stanford.edu/entries/embodied-cognition/

I won't claim to know which is correct, or even if some other alternative is correct; however, this is not settled at all.

I do think it will some day be possible to simulate all of the embodied cognition above, which may truly render this discussion moot, but that LLMs are not doing that at all.

[jasmer]

What is "perception, metacognition, curiosity"

Seriously. How does a bag of random particles have those things?

It cannot, by our own definition.

Hence the metaphysical problem of 'consciousness' as it relates to our variation of scientific materialism.

I suggest the pragmatic approach is along the lines of what the OP said aka 'sufficiently large neural net will be indistinguishable from human' and that's it. We will see things that we can de facto contemplate as 'curiosity' 'perception' 'meta-cognition' if we want to, especially if we start to develop a more meta understanding of these systems, or not, and that's it.

We'll probably be arguing about 'cognition' long, long after we have variation of AI that kind of seem to be AGI. By many measures we are already kind of there Chat GPT will fool humans probably most of the time and that's that.