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I will present a comprehensive mapping from general theoretical descriptions of the Universe to its large scale structure, over a wide range of physical distance scales. A number of public codes that stitch these theoretical mappings to neural networks put us in a position to greatly constrain most conceivable departures from concordance cosmology using galaxy surveys. In doing so, machine architectures will lend us much needed direction in our search for a more fundamental architecture of Nature. I will describe the key codes, their successes, short-comings and needed extensions. If time and interest permit, I can give a short tutorial on using them to constrain any new physics you may be interested in.