> Thanks for that! It is worth noting that taking advantage of the post-rotation distribution

I again feel this claim is too strong. Rotations have been used in information theory/wireless communications for decades at this point, with appropriate scaling done at channel inputs/outputs to hit channel capacity. The signals then pass through the appropriate codebooks that take advantage of the post-rotated+whitened signal.

Our cellphones today are powered by such technology.

I agree with your claim when restricted to deep learning. But I do not agree with the broad characterization that taking advantage of post-rotation distributions was only first done in your work.