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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.
The more general point is that generalization requires you to store seemingly useless information at training time (info that doesn't help your training objective), that will become useful in the future (when generalization actually happens). That's the opposite of compression.
Now, obviously, generalization requires abstraction, which requires erasing irrelevant details, so your high-generalization system will be doing *some* amount of compression. But it will be storing lots of seemingly useless info as well.
Ok yeah that makes total sense. So the point on it having to be optimizable for English is such that you can actually get some learning out of the interaction with the task?
Consider a simple example: I give you a set of questions about a movie, and you watch the movie and try to answer the questions. During the movie you write notes. The shortest possible notes that enable you to answer the questions are just the answers to the questions.
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