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Well, practical QC seems to be involved with optimization problems. D-Wave recently demonstrated doing something with bus routing for Volkswagen. I could imagine, say, a map service scaling that out by integrating QC into their route-finding for drivers to cooperatively improve traffic flow by finding optimal solutions to problems of a scale that is intractable with classical systems.

The everyday person will use QC like they "use" machine learning today: from a very high level abstract viewpoint, where services they consume have a little bit of intelligence that makes interacting with them more efficient.

Yeah, but what kind of optimization problem where an exact solution is intractable also doesn't have approximate algorithms that are good enough?

D-Wave has never demonstrated quantum speedup. Many doubt that their approach can be useful, even in theory.

Meh, sounds like overly negative propaganda to me. Clearly they're building up a big body of knowledge and have a lot of potential, as long as someone can figure out a practical application for the kinds of optimization problems their machine is good at.

It seems like neural networks should map to it well. Once the degree of connectivity and the number of qubits approaches the millions, there's no way any normal software solver is going to be able to keep up with it.

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