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Doesn't literally every optimisation and ML class teaches it nowadays?

Actually, no! You would think so, but again, it's a boring numerical technique so it is all too often sidelined in favour of the more "flashy" symbolic techniques.

An awful lot of tertiary education has been caught up in the publish-or-perish mentality. Unfortunately for AD, it is not "impressive". Differentiating hideously difficult expressions symbolically is impressive. Publishing a paper packed full of enormous, scary looking expressions is impressive. Merely saying that "we used AD and it worked just fine" is unimpressive.

For decades now we've been incentivizing intellectual wankery over practical utility.

Here's an example from my field: "The derivatives of the finite-build coils are computed -- with almost no additional effort from the authors -- using automatic differentiation." Well, what kind of scientist are you, if you are too lazy to take derivatives? /sarcasm

http://meetings.aps.org/Meeting/DPP20/Session/BP14.32

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