alt Hacker NewsThere is a distinction between a compressor for a fixed dataset and one for an unknown population from which we have a sample. The optimal compressor for the sample may be the single best guess for the population, but that's not what Solomonoff induction does. It begins with a prior that allows all possible programs, and it never assigns all probability to the single optimal compressor, so it has no problem with the all-zeroes example.
But the Hutter prize (of which I'm a big fan) is for ever-more-optimal compressors, and in fact many of the solutions don't generalise to other input data without stripping out various tricks.
I think it's better to think of the hutter prize as a challenge to see how close people can get to efficiently approximating AIXI without the exponential cost of AIXItl. The fact that winners don't generalize well is just that they're not great approximations, because the behavior is different in the limit.