I agree, but you could always simulate the brain's environment as well. Then you could speed up the environment with the brain. Bridging the gap might be annoying, for the brains, waiting to communicate with the glacial pace of the squishy rubbish real world humans, but I'm sure they'd get over it.
I think this is the most important aspect of this paper. Throwing more computing power at the problem increases performance significantly. It is possible that our algorithms are adequate but our hardware is not.
Isn't effective government a system which can maximise the following function?
G = SUM(Fi(W)) from i to WorldPopulation
Where W is the physical configuration of matter in the world. Fi is the function associated with citizen i that defines his notion of 'goodness'.
Bad government is one which tries to maximise an alternative function:
G = SUM(Fi(W) * Di) from i to WorldPopulation, where Di is some factor for each individual and where some Di are much greater than other Di. i.e. some individuals have much greater say over the configuration of the world which is chosen...
I do not believe that it is irresolvable, I'm looking at biology for my counter example. In biology there exists a rigid framework inside which a "general" search of language/model is taking place, after a few billion years it seems to be doing ok. It is my hunch that there is a big something out there which will pull a lot of these issues together:
How do you build efficient markets?
How do you build an effective AI?
How do you design effective distributed systems?
How do you build effective languages/models with which to compress the world?
Under what circumstances do such 'meta' searches fail and succeed?
It's all beyond me but this is what my nose is saying...