• Optical illusions can trick computers, too

    Astrid Zeman et al., PLOS ONE

    In the classical four-wing form of this illusion, the top line appears shorter than the bottom line, even though the lines are of equal length. Terminating circles still induce a perceptual effect of line length misjudgment, as will arrows with the line shafts removed.

    By Charles Choi
    LiveScience

    Even computers can get tricked by optical illusions, a new study finds.

    Such research may help shed light on how vision works in the brain, and lead to better computer recognition of images, scientists added.

    Optical illusions, more properly known as visual illusions, take advantage of how the brain perceives what the eyes tell it in a way that plays a variety of tricks on the mind. For instance, these illusions may cause people to see something that is not there, or not see something that is there, or see an unrealistic portrayal of object, or see one thing as two or more completely different things. By investigating how illusions fool the brain, researchers can learn more about the brain's inner workings

    "In most cases, illusions can be really useful," said researcher Astrid Zeman, a cognitive neuroscientist at Macquarie University in Australia. "For example, we watch television and see continuous movement instead of a flickering set of still images."

    One classic visual illusion is the Müller-Lyer illusion, where arrowheads and arrow tails can influence the perceived length of a line. When arrowheads are placed at both ends of a line, they can make it look shorter than a line of equal length; when these are replaced by arrow tails, they can make it look longer. [Eye Tricks: Gallery of Visual Illusions]

    There is ongoing debate as to what causes the Müller-Lyer illusion in the brain. To learn more, scientists experimented with a computer image-recognition model designed to mimic the brain's vision centers to see which might generate specific patterns of errors similar to ones expected from the illusion.

    "Recently, many computer models have tried to imitate how the brain processes visual information because it is so good at it," Zeman said. "We are able to handle all sorts of changes in lighting and background, and we still recognize objects when they have been moved, rotated or deformed. I was curious to see whether copying all of the good aspects of object recognition also has the potential to copy aspects of visual processing that could produce misjudgments."

    The scientists discovered these artificial mimics of the brain could get duped by the illusion.

    "What is exciting about these results is imagining what would happen in the future," Zeman told LiveScience. "If we build robots with artificial brains that are modeled off our brains, the implication is that these robots would also see illusions much like we do. By imitating the amazing accuracy, flexibility and robustness that we have in recognizing objects, we could also be copying potential errors in computation that manifest in visual illusions."

    Tricking a computer
    The researchers first showed pairs of lines to a computer model of human vision. Each pair had one line that was longer than the other. Each line either had both an arrowhead and an arrow tail or an "X" at both ends. The computer model, named HMAX, had to guess which line was longer, and it was told when it was correct and when it was wrong. In this way, the investigators trained the system to correctly identify what long and short lines look like with 90 percent accuracy.

    "We train a biologically plausible model and look at the influence of the images it is exposed to," Zeman said. "If we think of this visual system as something we implant in a robot, this means that we can grow whole bunch of robots up in different environments. Then, once our robots have matured and have learnt to see things, we can then smash their brains open to see what they are thinking. This is something that we can't quite do with humans."

    The scientists then tested the system with pairs of lines. Again, each pair had one line that was longer than the other. However, this time the top line always had two arrow tails and the bottom line always had two arrowheads. In humans, if both lines are actually the same length, the top line will look longer.

    The researchers found the model was indeed mildly vulnerable to the illusion, losing about 0.8 percent to 1.6 percent accuracy. Also, the effect on the model was stronger when the angle of fins of the arrowheads and arrow tails was more acute, just as with humans.

    "I got really excited when we first saw an illusory effect — we hadn't expected that to happen at all," Zeman said.

    How illusions trick the mind
    These findings may eliminate a number of potential explanations for the illusion. For example, in the past, scientists had speculated this illusion was caused by human brains misinterpreting arrowheads and arrow tails as depth cues — in modern-day environments, rooms, buildings and roads present boxy scenes with many edges, and so might lead people to unknowingly make predictions regarding depth whenever they run across angles and corners. However, since this computer model was not trained with 3-D images, these findings may rule out that idea. [The 10 Greatest Mysteries of the Mind]

    Previously, researchers had also conjectured this illusion resulted from human brains focusing more on overall information about shapes instead of on their constituent parts. However, that seems not to be true with the model either.

    All in all, these findings suggest the illusion doesn't necessarily depend on the environment or any rules people learn about the world. Rather, it may result from an inherent property of how the visual system processes information that requires further elucidation.

    Future research could help computers recognize illusions, so they can reject impossibilities and paradoxes. "This can be very important, for example, when judging the distances and sizes of objects in target-tracking systems," Zeman said.

    The researchers now aim to model a range of different visual illusions, especially ones where there is ongoing debate as to what causes them.

    "There are so many visual illusions that exist out there, and new ones are coming out all the time," Zeman said. "These illusions bring to light new questions about how we perceive the world and the assumptions we make about the world. Currently there is no existing formal and comprehensive catalog of illusions, so one direction for future development would be to pool together all of this knowledge."

    The scientists detailed their findings online Feb. 15 in the journal PLOS ONE.

    Follow us @livescience, Facebook and Google+. Original article on LiveScience.com.

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  • A quantum leap is in the works for secure cloud computing

    Equinox Graphics

    Clusters of entangled qubits, shown in this artistic visualization, could allow remote quantum computing to be performed on a server while keeping the contents and results hidden from the remote server.

    By Alan Boyle, Science Editor, NBC News




    If the future is heading toward "cloud computing," where most of your data lives on someone else's server, can you trust the cloud to keep a secret? Researchers say they've found a way to guarantee that your information will be secure in the cloud, using quantum entanglement.

    The technique is called blind quantum computing, and it adds one more piece to a puzzle that could eventually be assembled into an entirely new infrastructure for data processing. Theoretically, quantum computers could outdo classical computers when it comes to making weather predictions, simulating biological processes, analyzing chemical reactions and, not incidentally, deciphering secret codes. Data security could become an even bigger issue than it is today.

    Whom do you trust?
    Today, most of your computing power probably resides on the device you're using, whether it's a desktop or a smartphone. If you send secure data someplace else, those bits are probably encrypted using classical mathematical techniques. They're tough codes to break, but they're not unbreakable. In fact, computer scientists say quantum computers might be well-suited for cracking today's classical codes.

    At the same time, there's a trend toward developing devices that shift more of the computing power onto big servers. You would still use your tablet or smartphone or netbook for input and output, but the information is stored and processed as part of a huge cloud of bits on the server. That's the idea behind the much-debated cloud computing approach.

    How sure can you be that the folks who manage the cloud won't meddle with your data? And could a malicious cloud client meddle with the central server? Such questions are tricky now, and they could get trickier if quantum computing takes hold, according to an international research team led by Stefanie Barz of the Vienna Center for Quantum Science and Technology at the University of Vienna and the Austria-based Institute for Quantum Optics and Quantum Information.

    In this week's issue of the journal Science, Barz and her colleagues note that quantum computers will be so complex that there may be only a few of them in operation at specialized facilities around the world.

    "A key challenge in using such central quantum computers is enabling a quantum computation on a remote server while keeping the client's data hidden from the server," they write.

    Demonstrating blind computing
    The researchers worked out a system to entangle photons of light that were generated by a nonlinear crystal, and then "process" those entangled photons on an experimental setup of beam splitters, filters and couplers. The photons served as quantum bits, or qubits, to be manipulated in two types of quantum calculations (Deutsch's algorithm and Grover's search).

    In this scenario, the person who provided the qubits knows their initial entangled state, and can thus decipher the entangled outcome. But the company that does the data processing wouldn't know how the qubits were entangled — and thus could not even try to decode the qubits without essentially destroying them. As far as it's concerned, all those qubits look like a totally random hodgepodge. What's more, the system has a built-in verification scheme.

    "By inspecting the output, you can know if the company really has a quantum computer, without disclosing your algorithm, the input, or indeed the output," the University of Oxford's Vlatko Vedral said in a Science commentary on the research. "The computation is thus 'doubly' blind."

    Barz and her colleagues say there are still some technical challenges to be overcome. for example, it's theoretically possible for some of the photons emitted while preparing the qubits to reveal information about the "blind" phase of the calculation. Also, it's important to have a high-fidelity, low-signal-loss system for processing the qubits — whether they consist of photons with different polarizations, or electrons with different spins. But however the quantum computing puzzle is put together, the researchers say their experiments will have contributed a key piece.

    "Our demonstration is crucial for unconditionally secure quantum cloud computing," they say, "and might become a key ingredient for real-life applications, especially when considering the challenges of making powerful quantum computers widely available."

    More perspectives on the research:

    More about quantum computing:

    Alan Boyle is msnbc.com's science editor. Connect with the Cosmic Log community by "liking" the log's Facebook page, following @b0yle on Twitter or adding Cosmic Log's Google+ page to your circle. You can also check out "The Case for Pluto," my book about the controversial dwarf planet and the search for other worlds.