  We describe how one may go about performing quantum computation with
arbitrary "quantum stuff", as long as it has some basic physical properties.
Imagine a long strip of stuff, equipped with regularly spaced wires to provide
input settings and to read off outcomes. After showing how the corresponding
map from settings to outcomes can be construed as a quantum circuit, we provide
a machine learning algorithm to tomographically "learn" which settings
implement the members of a universal gate set. At optimum, arbitrary quantum
gates, and thus arbitrary quantum programs, can be implemented using the stuff.
