I started from the view of multiplicative weights over computable predictors, and then when I tried to describe it as an improvement on Solomonoff induction realized it was the same thing. If you write down what the two algorithms actually do, the equivalence to within a constant is clear.
Shane Legg's text Solomonoff Induction has helped me a lot over the last few days. I was trying to iron out the kinks in my understanding of Eliezer's argument in this old thread:
Eliezer's statement is correct (more precisely, a computable human cannot beat Solomonoff in accumulated log scores by more than a constant, even if the universe is uncomputable and loves the human), but understanding his purported proof is tricky. Legg's text doesn't give any direct answer to the question at hand, but all the technical details in there, like the difference between "measures" and "semimeasures", are really damn important if you want to work out the answer for yourself. I know mathematics has many areas where an "intuitive understanding" kinda sorta suffices. This is not one of those areas.