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That is not how any of this works. This is not even close to why its hard to make a machine like that (and very much possible to do so, in theory).

The model does not produce statistically indistinguishable from human outputs, but the outputs that satisfy its training rewards system most strongly. Those are very different things. And the rest of the argument is less logically.

How would a machine capable of detecting that difference be usable to train a 'better' model? Only _if_ the goal was to make it indistinguishable from human, which it is not, the goal is to make it succeed at a set of training tasks! Tasks that in fact don't lead to it being all that human like.

And compute, famously, cost energy! Which is why this doesn't break thermodynamics. It also doesn't break information theory, because we already know what human text looks like, and are just extracting out the patterns that make it look like so via computation.

Also, the thing is that, a text or any other thing, that has all the average values of a large diverse population, is very strange! A text that is statistically closest to the overall dataset average of all human text, is not very human look at all!

Humans do not write text that is the exact average. Humans write texts with statistically significant differences. In fact, you can compare texts to find if they have the same author! This is not a new thing either!