DWave first showed off its 512 qubit chip in late 2011, but it has taken about one year to prepare it as a commercial product.
“A quantum computer is on a completely different scaling curve, where once it passes traditional computers, they can never catch up,” says Mr. Jurvetson, who sits on D-Wave’s board. “That is just unprecedented in the technology business.”
Investors, including prominent U.S. venture capital firms, have staked $130-million on the Montreal-raised theoretical physicist’s big idea. D-Wave is beginning to attract paying customers, too. In 2010 it sold its first system, to aerospace and defence giant Lockheed Martin. And last month it closed $30-million in equity financing from two big names: Bezos Expeditions, a venture capital shop established by Amazon.com Inc. founder Jeff Bezos; and In-Q-Tel, which sources technology for U.S. intelligence agencies.
The Dwave Adiabatic quantum computer can run machine learning mathematics and could be able to overcome some of the key bottlenecks in machine learning and artificial intelligence.
But D-Wave isn’t building a general-purpose quantum computer, he adds. “It does one very specific class of problems really, really well, and that’s pretty much all it does,” he says. “But luckily that class of problems has wide applicability.”
For example, it could eventually use a person’s genome to determine how they will respond to a particular drug, Dr. Rose says. “Virtually anything that a human does well that conventional computers currently are not good at is something that’s going to be affected by these systems.”
So far, quantum computers are only starting to deliver on that promise. In 2009, for instance, scientists at Google Inc. used a D-Wave system to accurately detect cars in images. Dr. Rose describes such automatic detection as a fundamental problem in AI. “In some ways, understanding how we do that is the key to unlocking intelligence in machines,” he says.
The company gave its researchers funding and access to the rest of the network it was building. In exchange, it got control of the intellectual property they produced and the right to file patents before they published their findings.
Over the next five years, D-Wave’s network expanded to include groups with ties to 10 academic institutions in Canada, Germany, the Netherlands, the Slovak Republic, Sweden, Britain and the Ukraine. As early as 2001, the start-up had access to $440-million worth of equipment.
D-Wave took an entrepreneurial approach to running tests that would otherwise have been very expensive, says Ajay Agrawal, Peter Munk Professor of Entrepreneurship at the University of Toronto’s Rotman School of Management. “If you had all of the equipment in-house, you’d have to be a very large company, like an IBM,” explains Dr. Agrawal, who co-authored a 2004 Harvard Business School case study on D-Wave. “So how does an entrepreneur do it? By leveraging the assets that are out there and in many cases underutilized, and rather than paying the full cost, paying only the marginal cost.”
D-Wave handled what was probably the riskiest stage of its life in a surprisingly careful and efficient way, says Alexei Andreev, executive vice-president and managing director at the Palo Alto, Calif., office of venture capital firm Harris & Harris Group Inc., another investor. “Instead of trying things sequentially, they did it in parallel,” the D-Wave board member says.
Today, D-Wave holds 93 U.S. patents and has 107 patent applications under way globally. Its IP portfolio will make it very difficult for competitors to design a similar machine, at least for 15 years or so, Dr. Rose predicts.
D-Wave Systems Inc. uses the relatively new adiabatic model, also known as quantum annealing. This architecture allows its quantum bits, or qubits, to shift from superposition to a traditional computer state.
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