CAPTCHA CAPTURE: Vicarious's CAPTCHA-solving approach allows AI software to learn new things from a few examples, much as a human child comes to understand the world by learning to recognize what he sees and figuring out how the images are connected. Image: Courtesy of Vicarious
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Luis von Ahn has heard it all before. As co-inventor of the CAPTCHA, those annoying images composed of wiggly letters and numbers that Web sites use to make sure you’re a human rather than a machine, von Ahn has received as many as 50 claims over the past decade of ways to beat his program.
Make that 51.
The start-up Vicarious, based in Union City, Calif., claims it has come up with artificial intelligence (AI) software that reads images nearly as well as humans and can crack a CAPTCHA 90 percent of the time. If the claims are true, they could signify a breakthrough in building AI that is indistinguishable from human cognition—at least when it comes to helping computers identify and understand images.
Vicarious calls the architecture its AI system is based on a “recursive cortical network,” meaning it is modeled along the line of the human neocortex—the brain’s gray matter that processes information. This approach allows AI software to learn new things from a few examples, much as a human child comes to understand the world by learning to recognize what he sees and figuring out how the images are connected.
Vicarious’s approach differs from AI methods such as "deep learning," in which software trains an artificial neural network by providing thousands of training images for it to connect, according to the company. "The human brain is made up of a simple, replicated circuit—a single repeated element that happens over and over again in the neocortex," Vicarious co-founder D. Scott Phoenix says, adding that his company’s software is likewise built from single, repeated elements.
Solving a CAPTCHA (for Completely Automated Public Turing test to tell Computers and Humans Apart) clears the bar that mathematician Alan Turing set in 1950 to determine whether a machine could be said to possess a humanlike intelligence, although in a limited way. Over the years other computer scientists and hackers have found ways to program computers to pass the CAPTCHA test, forcing Web publishers to employ increasingly more complicated CAPTCHAs that are difficult to decipher in their efforts to repel increasingly sophisticated spamming tactics.
Vicarious's CAPTCHA-solving demonstration is an example of "narrow artificial intelligence," a technology that can match or even exceed human performance on a narrowly defined task. IBM's chess-playing Deep Blue is another such example. But Vicarious insists its computer perception software is the foundation of an AI that will learn the way humans do—by experiencing the world around it, principally via vision, and then identifying patterns. "If an algorithm solves vision in general, it is not narrow AI, it's a general AI system,” says, Dileep George, also a Vicarious co-founder. “We are working on a general algorithm for solving [the] vision problem, and CAPTCHA is a stepping stone to that.”
One reason computers scientists are skeptical about Vicarious’s claim is that the company has kept its technology under wraps. It demonstrated the software on video, which showed its technology solving CAPTCHAs from major Web sites, rather than by publishing its findings in scientific journals. Nils Nilsson, emeritus professor at Stanford University and author of The Quest for Artificial Intelligence: A History of Ideas and Achievements, says Vicarious’s claim is significant but he has reservations. Vicarious, he says, uses "the CAPTCHA thing as just one test case to show how well their technology works. I'd say, okay, that's probably a pretty good advance, but I would need to know more."
George, a former PhD student of Nilsson’s, says that Vicarious has elected not to publish its results because publishing papers can be “very constraining." “You work toward the next paper and think in a one-year time frame whereas we are set up to think on a much longer time frame—and that lets us make bets or look in directions other people might not be looking.” Besides, adds Phoenix, they don't want to give spammers any new ideas.
In 2012 Vicarious received $15 million in funding from Silicon Valley venture capital firms led by Good Ventures, the investment firm of Facebook co-founder Dustin Moskovitz. Vicarious is a "flexible-purpose corporation," (pdf) a type of for-profit California corporation that pursues a goal of benefit to society, even at the expense of profits. This lets the company take a very long view—according to Phoenix, Vicarious doesn't expect to demonstrate full AI before 2028.
Stealth mode isn’t necessary to come up with good AI technology, researchers point out. "If you want impressive, neutrally inspired computer vision results, there are many of them around,” says Yann LeCun, director of New York University’s Center for Data Science. “People have published results and used benchmarks so that you can compare them with other methods."
CAPTCHA inventor von Ahn, an associate professor of computer science at Carnegie Mellon University, doesn’t seem excessively worried. It is hard to determine exactly how much better Vicarious's technology is than other work in the field, he says. The Vicarious approach, which relies on visual perception, is in line with current thinking about AI, according to von Ahn. "Many artificial intelligence researchers spend most of their time dealing with perception,” he says. “It's believed that our own intelligence derives from our visual cortex.”
Even if it proves to be a technological dead end, "the one nice thing about the approach of using computer vision is that at the very least, it has applications," von Ahn notes. For example, technology based on Vicarious’s system might someday give a self-driving car the ability to identify pedestrians straying onto a roadway.