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The remainder of the remark is about things that I didn't have a powerful feeling on, so I will leave it for Zach to reply if he wants.
The 2nd To Info Science article references this paper, which happens to be also the main reference by which Levin's result is pointed out in the very first paper you publish. So I suppose examining these references really should be sufficient to obtain the gist.
Alright, thanks! The very first bullet issue is I feel a summary of my initially two bullet details, but with distinct emphasis. I'll check out the experiments you connected.
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I never would like to assert that every one capabilities with very low Kolmogorov complexity have substantial volumes from the parameter-Area of a sufficiently massive neural community. The truth is, I'm able to level to a number of concrete counterexamples to this claim. To give a person case in point, the identification operate absolutely incorporates a lower Kolmogorov complexity, but it surely's very hard for the (entirely linked feed-forward) neural network to learn this functionality (If your enter and output is represented in binary kind by a tiny bit string). If you are trying to íŒŒì›Œë³¼ë¶„ì„ discover this operate by instruction on only odd numbers then the network will not robustly generalise to even numbers (or vice versa).
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