[jandrewrogers]

I mean actual computational geometry. Reality is significantly non-Euclidean in complicated ways that have to be accounted for if precision matters.

Spatio-temporal analytics or the processing of sensing data frequently requires this. For a simple example, the surface of the Earth is approximately an oblate spheroidal surface, not even a 2-sphere. You can use Euclidean approximations for many cartographic purposes but for analytics this can introduce large errors in the analysis. Understanding how to compute non-Euclidean geometry models is surprisingly useful.