In order to model intelligence explosion, we need to be able to measure intelligence.

Describe a computer's power as <Memory, FLOPS>. What is the relative intelligence of these 3 computers?

1. <M, S>
2. <M, 2S>
3. <2M, S>

Is 2 twice as smart as 1 because it can compute twice as many square roots in the same time? Is it smarter by a constant C, because it can predict the folding of a protein with C more residues, or can predict weather C days farther ahead?

If we want to ask where superintelligence of some predicted computational power will lie along the scale of intelligence we know from biology, we could look at evolution over the past 2 billion years, construct a table estimating how much computation evolution performed in each million years, and see how the capabilities of the organisms constructed scaled with computational power.

This would probably conclude that superintelligence will explode, because, looking only at more and more complex organisms, the computational power of evolution has decreased dramatically owing to larger generation times and smaller population sizes, yet the rate of intelligence increase has probably been increasing. And evolution is fairly brute-force as search algorithms go; smarter algorithms should have lower computational complexity, and should scale better as genome sizes increase.