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This is beyond my expertise and involves some words that I don’t understand, but my understanding is that quite a few people in ML (eg Michael Jordan) specifically care about things like gradient flows in the space of probability measures, and have research questions involving quite challenging differential geometry. You’d have to browse his papers to get a better understanding as I’m not qualified to expand much on this subject.



it's quite plausible that at the fringe/edge there is research being done that involves differential geometry - hell there's this paper

https://arxiv.org/pdf/1410.3831v1.pdf

that's occupies very rarefied air, but that's not what the person to whom i'm responding to claims (that somewhere someone there's a relationship):

>DG is the foundation of all modern AI/ML/DL

which is just blather spoken in a tone of confidence in order to sound very smart.




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