Abstract
Soft computing was founded to unify and advance computing methods beyond the limits of binary variables, Boolean logic and Turing machines. David Deutsch invented a way to use massive quantum parallelism to massively improve the power of Turing machines in some applications. Here we give a roadmap to use quantum parallelism to massively improve the power of soft computing, focusing on tasks in optimization ranging from function optimization, finding a needle in a haystack, optimal control, energy technology and reinforcement learning (Quantum artificial general intelligence, AGI) in a path leading up to optimization of physical plants themselves put into quantum superpositions. The path begins with design and test of prototypes built on platforms such as Nuclear Magnetic Resonance, sparse quantum optics, superconductors (sQuID), quantum dots and new high speed electronics.
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