In Asymptotic Mathematics I introduced an example in which mathematical solvers do. Decomposing domains as fine as exact solutions can be obtained and aggregate results.
In reconstruction you might want to use your exact solvers as base for simulations along a wide working-space and produce i/o samples that you can analyze by adequate machine learning methods. Extracting ultrafast Surrogate Models .
In finance, climate, biology, .. we need to model complex behavior knowing that more parameters and complexer models might lack the robustness required (you might get lost in the numerical jungle, stuck in local minima, inverse problems, ..).
Mathematica and mlf enable us to make comprehensive but low-effort experiments with deconstruction and reconstruction in quant finance.
This motivated me to playfully look back at the past from a future perspective.