Enlarge / Given the right data, a neural network can infer what radar maps would have looked like, were they available. (credit: NOAA/CIMSS. )
It’s become increasingly clear that quantum computers won’t possess a single moment when they become clearly superior to classical hardware. Instead, we’re likely to see them becoming useful for a narrow set of problems and then gradually expand out from there to an increasing range of computations. The question obviously becomes one of where the utility will be seen first.
The quantum-computing startup Rigetti now has a white paper that identifies, at least theoretically, a case when quantum hardware should offer an advantage. And it is actually useful: replacing a neural network that’s used for analyzing weather data.
How’s the weather?
The problem the people at Rigetti looked at involves taking a partial set of weather data and inferring what the rest looks like. Plenty of areas of the particular planet lack good coverage, and so we only get partial information about local conditions. And, if we have things like commercial aircraft going through said remote areas, we’ll often want a more complete picture of the conditions there.
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