Would you say that compression ‘includes’ many other problems or that compression and those problems (I assume you mean things like statistics etc.) are isomorphic (or partially anyway)? Why do you recommend focusing on compression and applying compression techniques to other fields instead of vice versa or both at once? Is there a reason you see compression as more fundamental?
I would say that if you understand phenomenon X, you should be able to build a specialized compressor for phenomenon X that will achieve a short codelength. The study of compression algorithms for datasets produced by phenomenon X is effectively identical to the study of phenomenon X. Furthermore compression provides a strong methodological advantage: there can be no hand-waving; it is impossible to “cheat” or self-deceive.
Would you say that compression ‘includes’ many other problems or that compression and those problems (I assume you mean things like statistics etc.) are isomorphic (or partially anyway)? Why do you recommend focusing on compression and applying compression techniques to other fields instead of vice versa or both at once? Is there a reason you see compression as more fundamental?
I would say that if you understand phenomenon X, you should be able to build a specialized compressor for phenomenon X that will achieve a short codelength. The study of compression algorithms for datasets produced by phenomenon X is effectively identical to the study of phenomenon X. Furthermore compression provides a strong methodological advantage: there can be no hand-waving; it is impossible to “cheat” or self-deceive.