I think you did a better job than all other commenters here (who seem to be mostly free-associating on the title and abstract), but your comment still doesn't quite capture the contribution of the paper or the reasonable takeaways from it.

The key is section 4.3.3, which draws a distinction between measures and predictors. The Solomonoff lower-semicomputable semimeasure is universal for all lower-semicomputable semimeasures, not just for some narrower class. But if we forget the idea of lower-semicomputable semimeasures and treat Solomonoff as a member of a wider class - limit-computable predictors - it turns out to be not universal for that class. In fact, moving from measures to predictors is so lossy that no predictor can be universal for its own class, by a simple diagonal argument. To me that means Solomonoff's approach with measures is more nuanced and informative than the approach with predictors.