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> and the last section assumes that AI will have some kind of normal distribution of IQ just like humans, which doesn't make any sense.

The central limit theorem shows that the normal distribution emerges as the limit of the average of independent and identically distributed random variables of any distribution.

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And there is no particular reason to believe that capabilities are merely the sum of a bunch of random iid variables! If you look at how DL scales with model size or data or FLOPS, it's a powerlaw (or lognormal), and in countless places in the natural world, things are lognormal rather than normal. Similarly, wealth, scientific productivity, lots of things are lognormal rather than normal. Even for human intelligence, the normality is due more to the fact that we all come off the assembly line as Mark 1 human units, practically identical, with the differences coming from environmental randomness & randomness in genetic mutation assortment.

Won't AI designers choose optimal values for those variables that have been identified? If so, I don't think the result looks like a normal curve, or at least the resultant 'optimized' normal curves skew 'smarter' relative to the human normal curve.

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