Google and NASA have demonstrated that quantum computing isn’t just a fancy trick, but almost certainly something actually useful — and they’re already working on commercial applications. What does that mean for existing startups and businesses? Simply put: nothing. But that doesn’t mean you can ignore it forever.
There are three main points that anyone concerned with the possibility of quantum computing affecting their work should understand.1. It’ll be a long time before anything really practical comes out of quantum computing.
Google showed that quantum computers are not only functional, but apparently scalable. But that doesn’t mean they’re scaling right now. And if they were, it doesn’t mean there’s anything useful you can do with them. What makes quantum computing effective is that it’s completely different from classical computing — and that also makes creating the software and algorithms that run on it essentially a completely unexplored space.There are theories, of course, and some elementary work on how to use these things to accomplish practical goals. But we are only just now arriving at the time when such theories can be tested at the most basic levels. The work that needs to happen isn’t so much “bringing to market” as “fundamental understanding.” Although it’s tempting to equate the beginning of quantum computing to the beginning of digital computing, in reality they are very different. Classical computing, with its 1s and 0s and symbolic logic, actually maps readily on to human thought processes and ways of thinking about information — with a little abstraction, of course. Quantum computing, on the other hand, is very different from how humans think about and interact with data. It doesn’t make intuitive sense, and not only because we haven’t developed the language for it. Our minds really just don’t work that way! So although even I can now claim to have operated a quantum computer (technically true), there are remarkably few people in the world who can say they can do so deliberately in pursuit of a specific problem. That means progress will be slow (by tech industry standards) and very limited for years to come as the basics of this science are established and the ideas of code and data that we have held for decades are loosened.