Demo note. This note demonstrates what the SciDraft Hugo theme can do for academic and scientific publishing — for research institutions, researchers and students. Its content is demonstration material only: readers should ignore whether the demo content is correct. Step sizes in deep learning are chosen as if the loss were smooth in its parameters, and that is an assumption, not a theorem. It is the smoothness postulate: the gradient does not change arbitrarily fast, so a small step in parameter space produces a predictable change in loss. ...