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Kicking off the D-Wave Board meeting over lunch today at Goldman Sachs… with new news from Google that they demonstrated the use of D-Wave’s quantum computer to deliver photo-driven search (and improve on classical machine learning).

Here is a summary from the Google Reseach blog:

“Many Google services we offer depend on sophisticated artificial intelligence technologies such as machine learning or pattern recognition. If one takes a closer look at such capabilities one realizes that they often require the solution of what mathematicians call hard combinatorial optimization problems. It turns out that solving the hardest of such problems requires server farms so large that they can never be built. A new type of machine, a so-called quantum computer, can help here.

Today, at the Neural Information Processing Systems conference (NIPS 2009), we show the progress we have made. We demonstrate a detector that has learned to spot cars by looking at example pictures. It was trained with adiabatic quantum optimization using a D-Wave C4 Chimera chip. There are still many open questions but in our experiments we observed that this detector performs better than those we had trained using classical solvers running on the computers we have in our data centers today. Besides progress in engineering synthetic intelligence we hope that improved mastery of quantum computing will also increase our appreciation for the structure of reality as described by the laws of quantum physics.”

10 responses to “Quantum Computing for Google Goggles”

  1. Interesting to start to see some real applications of quantum computing emerge.

  2. I played a lot with image search technology over the past year or so. While there is no question that image pattern recognition could help, the larger problem is in developing the databases to search against. Visual overloading, similar to symantic overloading in speech to text recognition requires massive duplication in database redundancy of images in order to determine specificity. My interest was in developing technology sufficient to provide assistance in problem solving by leveraging knowledge on the web through social networks. Unfortunately, the database you need to build to handle the diversity in what you encounter in the world is impossible to put together. Not sure how quantum computing can help there.

  3. Neat, feels empowering.

  4. like a Proustian reverie… of a flickr scent that you might like….

    Stop to Smell

    Much of AI research, from Hawkins to Rhodes to Brooks and CCSL, starts at the sensory interfaces.

    RocketMav – Not sure. They have limited the domain of image search, and have had good results. One of the advances was the use of discrete classifiers (vs. continuous variables), which maps well to the QC, and speeds up machine learning on classical machines too.

    Speaking of limiting the domain – they shut down facial search for privacy reasons. Imagine using your camera phone to Google someone you see at the bar…. I have to imagine someone was thinking of Beer Goggles when naming this app… 😉

    I just noticed an "Easter Egg" allusion in the Google Goggles video. They use Oxford Prof. David Deutsch’s book The Fabric of Reality in the demo. I first became interested in quantum computing when I read that inspiring book. He writes: “Quantum computers have the potential to solve problems that would take a classical computer longer than the age of the universe.”

  5. I was at the original launch of D-Wave at the Computer History Museum in California two years ago (almost three now, actually), and it is great to see that the company made progress, and that its hardware is used in concrete applications by Google, with discernible advantages over traditional approaches.

    Congratulations to all the team!

  6. Fun to watch Rose’s Law of compounding qubits play out….

    P.S. Just saw a cool TED video by David Deutsch explaining explanation… Puts a lot in perspective… =)

  7. (Growing more and more uncomfortable about the security of the public key encryption mechanisms protecting the symmetric session keys protecting his Flickr logon credentials)

    Damn VCs sawing off the IT and financial industries’ security branch they’re sitting on

  8. P(Shor)!

    Hey, you can join the distributed supercomputer that is simulating the QC future. See rose blog.

  9. Dear Mr. Jurvetson

    I’ve read in this recent article by Mauldin that you are currently participating in Singularity University. I bet that you have raised the possibility of an X-prize for quantum computing with Diamandis. Could you comment on Geordie Rose’s blog if the X-prize foundation is considering such a prize?

    I realize D-wave is the horse you are betting the farm on, so why would you be interested in advocating an X-prize that would create possible D-wave competitors? Well, maybe D-wave can win the prize. Even if it didn’t, having multiple instead of one solitary private company involved in quantum computing R&D might paradoxically increase the viability of all the companies involved. The more successful companies might still see some value in the less successful ones and buy them or their staff out.

    I think an X prize for quantum computing would be a natural, because:

    (1)In this CNet article, Diamandis said: "The question is, would an incentive prize bring new capital to the market, would it help them bring in new players, and allow new risk taking?"
    MOST DEFINITELY, YES. Most QC research currently being done is being done by academia, funded by DARPA/IARPA. More involvement by industry and private investment is sorely needed. If a QC industry could be created, this would generate lots of jobs.

    (2) probably not hard to find corporate sponsors for this, as many of them would benefit directly from the technology

    (3)A well defined, doable in 8 years, not too easy, not too hard, goal could be conceived by QC experts without too much trouble

  10. I have not pitched such a prize yet, but Diamandis was curious about this and asked me to talk about it at a SU event this Sunday. I can suggest a prize for a quantum compiler to radically rethink the programming model (like Geordie’s "Black Box" or training a neural network but abstracted further to exploit bidirectional feedback)…

    Meanwhile, finally… a move from Phys. Rev. B to the business lead in the NYT, and the second-most shared story for the day.

    "if it performs as Lockheed and D-Wave expect, the design could be used to supercharge even the most powerful systems, solving some science and business problems millions of times faster than can be done today.

    Ray Johnson, Lockheed’s chief technical officer, said his company would use the quantum computer to create and test complex radar, space and aircraft systems. It could be possible, for example, to tell instantly how the millions of lines of software running a network of satellites would react to a solar burst or a pulse from a nuclear explosion — something that can now take weeks, if ever, to determine.

    “This is a revolution not unlike the early days of computing,” he said. “It is a transformation in the way computers are thought about.” Many others could find applications for D-Wave’s computers. Cancer researchers see a potential to move rapidly through vast amounts of genetic data. The technology could also be used to determine the behavior of proteins in the human genome, a bigger and tougher problem than sequencing the genome. Researchers at Google have worked with D-Wave on using quantum computers to recognize cars and landmarks, a critical step in managing self-driving vehicles.

    Quantum computing has been a goal of researchers for more than three decades, but it has proved remarkably difficult to achieve.

    The D-Wave computer that Lockheed has bought uses a different mathematical approach than competing efforts. In the D-Wave system, a quantum computing processor, made from a lattice of tiny superconducting wires, is chilled close to absolute zero. It is then programmed by loading a set of mathematical equations into the lattice.

    The processor then moves through a near-infinity of possibilities to determine the lowest energy required to form those relationships. That state, seen as the optimal outcome, is the answer.

    The approach, which is known as adiabatic quantum computing, has been shown to have promise in applications like calculating protein folding, and D-Wave’s designers said it could potentially be used to evaluate complicated financial strategies or vast logistics problems."

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