Google posted on their “Google Research Blog” a couple of days ago (“When can Quantum Annealing win?“) that:
During the last two years, the Google Quantum AI team has made progress in understanding the physics governing quantum annealers. We recently applied these new insights to construct proof-of-principle optimization problems and programmed these into the D-Wave 2X quantum annealer that Google operates jointly with NASA. The problems were designed to demonstrate that quantum annealing can offer runtime advantages for hard optimization problems characterized by rugged energy landscapes. . . .
What that means is that for the first time there appears to be evidence that the use of a Quantum Computer has yielded the result to a real world problem faster (much, much faster – as much as 108 times faster) than a conventional computer can solve the problem. The ‘annealing’ mentioned here is an algorithm that picks the best answer from a large set of potential solutions where there may be 100s or even a 1000 variables involved.
What this may mean is that AI capability may be greatly advanced, as well as advanced simulation of space launches (NASA is the other major investor in D-Wave 2X Quantum Annealer). These Quantum Computing systems may also enable improved materials through the complex simulation capabilities they offer.