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Isn't there a benefit for the generalization capabilities of a system or skill program to be able to compress information? Reading now I have this intuition that generalization and compression have some kind of interplay but I might completely off...
Compression (with respect to a fixed training dataset) is by definition opposite to generalization. If you find the optimal compression dict to compress English Wikipedia it will obviously not be optimal for Spanish Wikipedia.
Because by definition compression discards all information that isn't relevant to the training goal, and by definition the training goal isn't what you want to generalize to (otherwise there is no generalization happening).
The most compressed model that does X is only capable of doing X. If it could do more then you could compress further.
First of all...how cool is it that I got a response from you...this is like so awesome, thanks a lot. With respect to the argument. Ok, I see your point on the dict to compress English, but wouldn't there be some compressed version of language that comprises both?
There might be, but it will be by definition less optimal when applied to just English. You won't find it by optimizing for English.
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