Google Continues A.I. Expansion

Google Inc is growing its artificial intelligence area, hiring more than half a dozen leading academics and experts in the field and announcing a partnership with Oxford University to “accelerate” its efforts.

Google will make a “substantial contribution” to establish a research partnership with Oxford’s computer science and engineering departments, the company said on Thursday regarding its work to develop the intelligence of machines and software, often to emulate human-like intelligence.

Google did not provide any financial details about the partnership, saying only in a post on its blog that it will include a program of student internships and a series of joint lectures and workshops “to share knowledge and expertise.”

Google, which is based in Mountain View, California, is building up its artificial intelligence capabilities as it strives to maintain its dominance in the Internet search market and to develop new products such as robotics and self-driving cars. In January Google acquired artificial intelligence company Deep Mind for $400 million according to media reports.

The new hires will be joining Google’s Deep Mind team, including three artificial intelligence experts whose work has focused on improving computer visual recognition systems. Among that team is Oxford Professor Andrew Zisserman, a three-time winner of the Marr Prize for computer vision.

The four founders of Dark Blue Labs will also be joining Google where they will be will be leading efforts to help machines “better understand what users are saying to them.”

Google said that three of the professors will hold joint appointments at Oxford, continuing to work part time at the university.

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Scientist Develop Anti-Faking PC

Scientists have developed a computer system with sophisticated pattern recognition abilities that performed more impressively than humans in differentiating between people experiencing genuine pain and people who were just pretending.

In a study published in the journal Current Biology, human subjects did no better than chance – about 50 percent – in correctly judging if a person was feigning pain after seeing videos in which some people were and some were not.

The computer was right 85 percent of the time. Why? The researchers say its pattern-recognition abilities successfully spotted distinctive aspects of facial expressions, particularly involving mouth movements, that people generally missed.

“We all know that computers are good at logic processes and they’ve long out-performed humans on things like playing chess,” said Marian Bartlett of the Institute for Neural Computation at the University of California-San Diego, one of the researchers.

“But in perceptual processes, computers lag far behind humans and have a lot of trouble with perceptual processes that humans tend to find easy, including speech recognition and visual recognition. Here’s an example of a perceptual process that the computer is able to do better than human observers,” Bartlett said in a telephone interview.

For the experiment, 25 volunteers each recorded two videos.

In the first, each of the volunteers immersed an arm in lukewarm water for a minute and were told to try to fool an expert into thinking they were in pain. In the second, the volunteers immersed an arm in a bucket of frigid ice water for a minute, a genuinely painful experience, and were given no instructions on what to do with their facial expressions.

The researchers asked 170 other volunteers to assess which people were in real discomfort and which were faking it.

After they registered a 50 percent accuracy rate, which is no better than a coin flip, the researchers gave the volunteers training in recognizing when someone was faking pain. Even after this, the volunteers managed an accuracy rate of only 55 percent.

The computer’s vision system included a video camera that took images of a person’s facial expressions and decoded them. The computer had been programmed to recognize that one kind of facial movement combinations suggested true pain and another kind suggested faked pain.

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