Well as simulations improve that tends to be less of a problem. Engineering by now is highly reliant on simulations, building actual prototypes is only done as

Well as simulations improve that tends to be less of a problem. Engineering by now is highly reliant on simulations, building actual prototypes is only done as a last validating step as you mentioned (specially for something as expensive and complicated as a fusion reactor). So validation devices are a O(1) step in the innovation chain, I don't see a scaling issue here. You can also simply make arbitrarily many experimentation/testing devices. I think a greater issue is the general misconception of intelligence as something of a magical attribute, and even more so "superintelligence", and even more so "recursive-self-improving superintelligence" (RSIS for short?). There are not only various limits to hardware, some of which discussed in the article (size of atoms, capacity of communication between parts), but also there are limits to software. For example, while it seems that an RSIS could really solve any problem it wanted, Turing's almost century-old Halting Problem solution already proved that no such computer exists. There's no algorithm that takes an arbitrary conjecture, e.g. the Riemann hypothesis, and outputs either {yes,no,malformed_problem}. In fact the general expectation of what AGIs can do (think creatively, solve arbitrary problems, replace mathematicians, replace programmers) are things that we ourselves can't really do. We solve problems using a small set of heuristics and lots of trial and error, with no success guarantee. Another fact is that there are many asymptotically optimal algorithms that are already know, and the trivial fact that almost all tasks performed by this super-intelligence (many of which are ordinary tasks we already do, analogous to maybe sorting, database queries, and search engines) will just improve constants on near-optimal algorithms. A god-like creature those AIs will be not.