Technology Review – Bezos and In-Q-Tel (CIA Investment arm) are in a group of investors who are betting $30 million on DWave Systems If the bet works out, some of the world’s thorniest computing problems, such as the hunt for new drugs or efforts to build artificial intelligence, would become dramatically less challenging.
D-Wave’s supercooled processor is designed to handle what software engineers call “optimization” problems, the core of conundrums such as figuring out the most efficient delivery route, or how the atoms in a protein will move around when it meets a drug compound. “Virtually everything has to do with optimization, and it’s the bedrock of machine learning, which underlies virtually all the wealth creation on the Internet,” says Geordie Rose, D-Wave’s founder and chief technology officer. In machine learning, a branch of artificial intelligence, software examines information about the world and formulates an appropriate way to act in the future. It underpins technologies such as speech recognition and product recommendations and is a priority for research by companies, such as Google and Amazon, that rely on big data.
“Our intelligence community customers have many complex problems that tax classical computing architecture,” Robert Ames, vice president for information and communication technologies at In-Q-Tel, said in a statement released today. In-Q-Tel’s primary “customer” is the CIA, and the National Security Agency is another. Both are known to be investing heavily in automated intelligence gathering and analysis.
The Technology Review article plays up the criticism that DWave received and says that DWave Systems has been publicly quiet.
Nextbigfuture has had 40 articles on Dwave systems and over 80 articles on Adiabatic Quantum Computing. The criticism was wrong and was made without taking the time to understand what DWave was doing. DWAve has continued to make many important developments and announcements. The later work received less attention than the initial coverage. Although IEEE Spectrum and Technology Review have had articles covering Dwave in the intervening years.
In May 2011, Dwave published in the journal Nature with proof that D-Wave’s chips have some of the quantum properties.
Artificial intelligence researchers at Google regularly log into a D-Wave computer over the Internet to try it out, and 2011 also saw the company sign its first customer. Defense contractor Lockheed Martin paid $10 million for a computer for research into automatically detecting software bugs in complex projects such as the delayed F-35 fighter.
Questions remain about just how its technology works, but D-Wave says more evidence is forthcoming. It is readying an improved processor that Rose calls the company’s first true product rather than a piece of research equipment. D-Wave is expected to announce other major customers in coming months.
Rose says that D-Wave is working on proving evidence of entanglement, and that recent head-to-head tests against classical computers showed it pulling ahead on the kind of computing problem that it is designed to solve. [Nextbigfuture covered the research paper which showed adiabatic times for the simulated processor architecture are about 10 thousand to 1 million times faster than the two classical solvers’ times.]
Whether or not D-Wave can satisfy skeptics doesn’t necessarily matter to investors and technology companies. That’s because in so many areas of business, computing power is crucial to maintaining a competitive advantage, says Steve Jurvetson, a partner at venture capital firm Draper Fisher Jurvetson, who has invested in D-Wave twice and calls it “the most singular swing-for-the-fences technology” he ever funded. “The application space for this,” he says, “is anywhere we’ve had to fall back on an heuristic—a rule of thumb—to solve a problem: day traders, molecular modeling, anyone in e-commerce and the Googles and Microsofts of the world.” Companies such as Lockheed, Amazon, and big pharma companies are most familiar with the limits of conventional computers and will be first in line, says Jurvetson, but designing a new car or a new online store could also benefit.
Bob Lucas, who directs research on supercomputing and quantum computing at the University of Southern California, where Lockheed’s D-Wave computer is installed. “We’re living in the last 10 years of exponential growth of [classical] computing power, and alternatives to that will become more of interest,” Lucas says. He adds that through his experiments on Lockheed’s D-Wave system he has been converted from “highly skeptical to cautiously optimistic” about the technology.
Bezos has also invested in the General Fusion, which is another Canadian company. General Fusion is working to develop magnetized target fusion.
Summary of Nextbigfuture coverage of Dwave
I covered that Dwave got more funding to cover the next two years, so they should reach profitably and be able to reach an IPO in a few years. Now, Technology Review indicates that another $7 to 8 million was raised.
I had an interview with DWave CTO Geordie Rose in Dec, 2011
The amount of speedup from adiabiatic quantum computers depends upon the different quantum algorithms that are being run.
If the (cancer radiation) treatment optimization problem were indicative of the speedup of different algorithms, then one might expect (I am extrapolating the 512/128 qubit example)
512 qubits 1000 times faster than 128 qubits
2048 qubits 1000 times faster than 512 qubits
Dwave sold a system to Lockheed for $10 million back in late 2010
I made a public bet in 2006 that Dwave would get to over 100 qubits for a commercial system.
“There will be a quantum computer with over 100 qubits of processing capability sold either as a hardware system or whose use is made available as a commercial service by Dec 31, 2010”
In Jan 2010, IEEE Spectrum picked Dwave systems as a loser.
In July 2011, IEEE Spectrum recants and admits they were wrong
IEEE spectrum could not predict as well as I did when I made a prediction in 2006 when they were predicting nearly 4 years later.
I have written over 80 articles on Dwave and adiabatic quantum computers.
Adiabatic computers do outperform all classical computers for some problems.
Scott talked about the evidence of Dwave quantumness in Nature in 2011
Scott Aaronson (theoretical quantum computing professor) who blogs at Shetyl Optimized.
D-Wave was finally able to clarify a conceptual point that had been bugging me for years. I [Scott]—and apparently many others!—thought D-Wave was claiming that their qubits decohere almost immediately (so that, in particular, entanglement would almost certainly never be present during the computation), but that the lack of entanglement didn’t matter, for some complicated reason having to do with energy gaps. I was far from alone in regarding such a claim as incredible: as mentioned earlier, there’s no evidence that a quantum computer without entanglement can solve any problem asymptotically faster than a classical computer. However, that isn’t D-Wave’s claim. What they think is that their system decoheres almost immediately in the energy eigenbasis, but that it doesn’t decohere in the computational basis—so that, in particular, there would be entanglement at intermediate stages. If so, that would be perfectly fine from the standpoint of the adiabatic algorithm, which doesn’t need coherence in the energy eigenbasis anyway.
I [Scott] do regret the snowballing nastiness that developed as a combined result of my and other skeptics’ statements, D-Wave’s and its supporters’ statements, and the adversarial nature of the blogosphere. For the first time, I find myself really, genuinely hoping—with all my heart—that D-Wave will succeed in proving that it can do some (not necessarily universal) form of scalable quantum computation.
So Scott was criticizing something that DWave was not claiming.
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Brian Wang is a Futurist Thought Leader and a popular Science blogger with 1 million readers per month. His blog Nextbigfuture.com is ranked #1 Science News Blog. It covers many disruptive technology and trends including Space, Robotics, Artificial Intelligence, Medicine, Anti-aging Biotechnology, and Nanotechnology.
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