The post lists Auto Differentiation as one of the techniques that can overcome non-differentiable loss functions. Can someone explain how this is even possible? After all automatic differentiation[1] is a way to compute gradients/derivatives in a way which could become costly if otherwise done(symbolic differentiation[2]). The function or the operations defined in the function(in case of source-to-source differentiation[3]) needs to be differentiable.
[1] - https://www.youtube.com/watch?v=z8GyNneq5D4
[2] - https://stackoverflow.com/a/45134000
[3] - https://github.com/google/tangent
EDIT: 1. Added reference. 2. Formatting