The famous Quantum Artificial Intelligence Lab is getting some powerful new hardware. A joint project between Google, NASA, and the Universities Space Research Association, the Quantum AI Lab today announced a multiyear agreement to install a D-Wave 2X, a state-of-the-art quantum processor released earlier this year. With over 1,000 qubits, the machine is the most powerful computer of its kind, and will be put to work tackling difficult optimization problems for both Google and NASA.
The fragility of the qubits also means the computer's processor can only operate at extremely cold temperatures. The 2X's standard operating temperature is less than 15 millikelvin, a temperature far colder than outer space.
The computer operates at 15 millikelvin
"Working with the D-Wave processors has helped us develop and fine-tune models of quantum annealing," Google's Hartmut Neven, head of the Quantum Artificial Intelligence Lab, said in a statement. "We look forward to the continued advancements coming from each generation of D-Wave systems."
But while the lab moves to test the new machine's capabilities, there are still real questions about whether D-Wave's approach to quantum computing will yield results. Benchmarking tests on D-Wave's previous models have failed to find evidence of the so-called "quantum speedup" — the exponential increase in computing power that makes quantum computing so appealing. D-Wave has proposed alternate benchmarks that show something closer to a speedup, but for most experts, the debate is still unsettled.
At the same time, D-Wave's computers aren't Google's only play in the quantum computing space. The company's biggest rival in the quantum computing space is a team of scientists from UC Santa Barbara team that was hired by Google in 2014. Where D-Wave chains together hundreds of qubits with higher error rates, the UC Santa Barbara group is working with smaller numbers of more reliable qubits, and struggling to maintain low error rates at the scale of the D-Wave machine. It remains to be seen which model has the better shot — but if either one succeeds, Google will have first pick of the results.
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