That was the way I have been looking at it.<p>It is not just an issue of finding solutions to impossible problems, or breaking scientific laws, but also problems where the solutions are along the lines of what George Soros would call reflexive. Computer security is like this, so is securities trading (no pun.)<p>Secondly, what about problems which require the destruction of the problem solvers along the path to the optimal solution? I&#x27;m not sure about the correct word to describe this, or the best example but it could be seen in large systems. Where humans are right now is a result of this. We would not know many things if those things which came before were not destroyed (cities, 1000 year empires, etc.)<p>Thirdly, is a uniform, singular AI the most optimal agent to solve these sorts of problems? Much the way we don&#x27;t rely or use mainframes for computing today, perhaps there will be many AI agents each which may be really good at solving particular narrowly defined problem sets. This could be described perhaps as a swarm AI.<p>Nick Bostrom&#x27;s Superintelligence is a great book, but I don&#x27;t recall much consideration along these lines. When a lot of AI agents are &quot;live&quot; the paths to solutions where AI compete against each other open up even more complex scenarios.<p>There certainly are physical limitations to AI. Things like the speed of light can slow down processing. Consumption of energy. Physical elements that can be assembled for computational purposes.<p>Between now and &quot;super&quot; AI, even really good AI could struggle to find solutions to the most difficult problems, especially if those are problems other AI are creating. The speed alone may be the largest challenge to humans. How do we measure this difficulty relative to human capabilities, I don&#x27;t know.<p>End of rant -- but the limits of not just AI but problem solving is quite interesting.