If machines are going to become as smart as Google and NASA want them to be, they may need a whole new type of computing to get them there. Quantum computing, that is.

So today Google said it's opening a lab – complete with a quantum computer – called the Quantum Artificial Intelligence Lab. It's hosted at NASA's Ames Research center, located just down the Highway 101 from Google's Mountain View headquarters and run in conjunction with the Universities Space Research Association, a non-profit group devoted to space science.

The lab will operate a 512-qubit quantum computer called the D-Wave Two, a machine that's also being tested out by Lockheed Martin.

Google has had some success using its vast computing resources to build machine learning into services such as voice and image recognition, but this work is incredibly compute-intensive. Although it's still in the early days of experimentation, quantum computing could herald a new era of number-crunching.

That's because it uses quantum physics to break computer processing out of the binary computing paradigm that has dominated for the past half-century. Instead of binary bits, these computers measure qubits, which can simultaneously represent many more values.

"We believe quantum computing may help solve some of the most challenging computer science problems, particularly in machine learning," wrote Hartmut Neven, a Google director of engineering in a blog post. "Machine learning is all about building better models of the world to make more accurate predictions."

The trick is getting these systems far enough along to solve real-world problems.

The company that's making Google and NASA's computer, D-Wave, has been met some skepticism from the quantum computing community. In part, it's because D-Wave is taking a different approach to quantum computing. But it's also because it hasn't produced the kind of peer reviewed research on its systems that academics require.

But this week, researchers at Simon Fraser University and Amherst College presented a paper studying the D-Wave chip's performance. They found that it worked pretty well on certain computing tasks.

Beyond the practical engineering problems involved in building a quantum computer, it's also difficult to develop algorithms that can take advantage of the unique properties of qubits in such a way as to build applications that are more efficient on a quantum computer than on a classical computer. Google claims to have already made some progress on this. "We’ve already developed some quantum machine learning algorithms. One produces very compact, efficient recognizers – very useful when you’re short on power, as on a mobile device," Neven wrote. "Another can handle highly polluted training data, where a high percentage of the examples are mislabeled, as they often are in the real world." Google will also mix classical and quantum computing.

With the Quantum Artificial Intelligence Lab there will be more research to follow. The Lab's D-Wave computer will be open to "researchers from around the world," Neven says. It will be available to researchers by the end of September, D-Wave said in a press release.