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RGB->YUV is literally an affine transform, of course it falls to the bitter lesson.



Does it? Because I'm not sure the model has any intrinsic incentive to learn to follow how human perception works.


Right... but I don't see how that means that it doesn't fall to the bitter lesson.

The bitter lesson is not saying that the model will always relearn the same representation as the one that has been useful to humans in the past, merely that the model will learn a better representation for the task at hand than the one hand-coded by humans.

If the model could easily learn the representation useful to humans, then it will fall to the bitter lesson because at minimum the model could easily follow our path (it's just an affine transformation to learn) and more probably will learn very different (& better) representations for itself.




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