One approach to redressing the information sabotage of Wikipedia is promised by the Hutter Prize for Lossless Compression of Human Knowledge. Indeed, my original motivation for suggesting that Wikipedia be used as the corpus for the prize was precisely to force the modeling of information sabotage as a by-product of approximating the Kolmogorov Complexity representation of Wikipedia. Now that Deep Mind has been acquired by Google due, in large measure, to Deep Mind co-founder, Shane Legg’s application of Marcus Hutter’s compression-oriented approach to Universal Artificial Intelligence, it seems appropriate that one of the initiatives by Alphabet Corporation should be to scale up the Hutter Prize to include the entire contents of Wikipedia in both corpus (not just the first 100M or even first 1G) and in prize awards offered. I originally wanted to have the corpus be the entire change log of Wikipedia but Matt Mahoney correctly objected that would be too large for the initiation of the prize. However, given the importance of information sabotage to the most critical areas of human knowledge, it may be appropriate for a large scale prize sponsored by Alphabet Corporation to use the entire change log of Wikipedia, rather than just a snapshot of Wikipedia taken at some arbitrary time.