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I think that there is some truth to what you and @4bpp are pointing out: the expensive part with an LLM is the training. With the hardware you require to train your network (in any practical time), you can then run quite a few instances. Not nearly an infinite amount, though.
Still, I would argue that we know from history that taking over the world through intelligence is a hard problem. In the cold war, both sides tried stuff which was a lot more outlandish than pay the smartest people in their country to think of a way to defeat their opponent. If that problem was solvable with one von-Neumann year, history would be different.
Also, in my model, other companies would perhaps be lagging ten IQ points behind, so all the low hanging fruits like "write a software stack which is formally proven correct" would already be picked.
I will concede though that it is hardly clear that the von Neumanns would not be able to take over the world, and just claim that it would not be a forgone conclusion like it would be with an IQ 1000 superintelligence.
Does a pretrained, static LLM really measure up to your "actually von Neumann" model? Real humans are capable of on-line learning, and I haven't seen that done practically for LLM-type systems. Without that, you're stuck with whatever novel information you keep in your context window, which is finite. It seems like something a real human could take advantage of against today's models.
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