Fundamental questions in chemistry and physics may never be answered due to
the exponential complexity of the underlying quantum phenomena. A desire to
overcome this challenge has sparked a new industry of quantum technologies with
the promise that engineered quantum systems can address these hard problems. A
key step towards demonstrating such a system will be performing a computation
beyond the capabilities of any classical computer, achieving so-called quantum
supremacy. Here, using 9 superconducting qubits, we demonstrate an immediate
path towards quantum supremacy. By individually tuning the qubit parameters, we
are able to generate thousands of unique Hamiltonian evolutions and probe the
output probabilities. The measured probabilities obey a universal distribution,
consistent with uniformly sampling the full Hilbert-space. As the number of
qubits in the algorithm is varied, the system continues to explore the
exponentially growing number of states. Combining these large datasets with
techniques from machine learning allows us to construct a model which
accurately predicts the measured probabilities. We demonstrate an application
of these algorithms by systematically increasing the disorder and observing a
transition from delocalized states to localized states. By extending these
results to a system of 50 qubits, we hope to address scientific questions that
are beyond the capabilities of any classical computer
