Google and NASA are exploring quantum computing with the D-Wave 2X
The idea of trading bits for qubits – which can be a one, zero or both simultaneously – isn’t new. But for the first time, someone’s making the concept work on real-world computing problems. Google and NASA have been studying how quantum systems can advance artificial intelligence and machine learning, and solve difficult optimisation problems, using hardware from quantum firm D-Wave. It’s the latter challenge, called quantum annealing, that’s generating fresh excitement. The researchers are using the D-Wave 2X to solve the problem, which could help bring quantum computing into the mainstream.
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So Google didn’t make the hardware?
“The 2X is ten feet tall and must be kept at a chilling -273 degrees C.”
No, NASA and Google simply have a standing order with the Canadian company to receive its top-end machines. That’s now the 2X, a quantum computer that’s 100 million times faster than a normal computer. But using a D-Wave machine isn’t as simple as plugging it in and typing queries. The 2X is ten feet tall and must be kept at a chilling -273 degrees C. Aside from a supply of liquid helium to reach such depths of temperature, those hoping to use a quantum machine must work out how to write algorithms and programs that work with the system. That’s easier said than done, as NASA notes: “Representing information in qubits allows the information to be processed in ways that have no equivalent in classical computing.” We’ve built the machine, now we need to discover how it works.
We don’t know how it works?
Intriguingly, there’s long been debate over whether the D-Wave design even qualifies as a quantum computer, although Google’s research is being seen as proof that it does use quantum properties to solve problems. One critic, MIT professor Scott Aaronson, has pointed out that the research reported by Google does show a 100-million-times speed jump, but he argues it’s an unfair comparison as it’s against a standard computer running an algorithm designed specifically for quantum machines. He claimed better results can still be achieved via “classical” techniques, namely better algorithms on conventional computers.
What could this be used for?
If Google and NASA’s work bears fruit, this subset of machine learning and AI is ideal for optimisation – simply put, figuring out the best way to do something. For NASA, that could be selecting a flight path to Mars, but it could be applied to anything from drug modelling to cracking encryption, or simply revealing the most efficient train route through Europe for a summer holiday.
When will quantum computers land on our desktops?
Google called the results “intriguing and very encouraging,” but there are many more problems to solve before it becomes a “practical technology”. Even then, it will first find use in labs and industry. We’ll likely access such power via companies such as Google, which will offer quantum services the way IBM sells its Watson AI now. Besides, you haven’t got room in your freezer for a D-Wave 2X.