by JOHN MARKOFF
Humans and machines were given an image of a novel character (represented atop each grid) and then asked to copy it IMAGR/Brenden Lake
Computer researchers reported artificial-intelligence advances on Thursday that surpassed human capabilities for a narrow set of vision-related tasks.
The improvements are noteworthy because so-called machine-vision systems are becoming commonplace in many aspects of life, including car-safety systems that detect pedestrians and bicyclists, as well as in video game controls, Internet search and factory robots.
Researchers at the Massachusetts Institute of Technology, New York University and the University of Toronto reported a new type of “one shot” machine learning on Thursday in the journal Science, in which a computer vision program outperformed a group of humans in identifying handwritten characters based on a single example.
The program is capable of quickly learning the characters in a range of languages and generalizing from what it has learned. The authors suggest this capability is similar to the way humans learn and understand concepts.
The new approach, known as Bayesian Program Learning, or B.P.L., is different from current machine learning technologies known as deep neural networks.
Neural networks can be trained to recognize human speech, detect objects in images or identify kinds of behavior by being exposed to large sets of examples.
Although such networks are modeled after the behavior of biological neurons, they do not yet learn the way humans do — acquiring new concepts quickly. By contrast, the new software program described in the Science article is able to learn to recognize handwritten characters after “seeing” only a few or even a single example.
The researchers compared the capabilities of their Bayesian approach and other programming models using five separate learning tasks that involved a set of characters from a research data set known as Omniglot, which includes 1,623 handwritten character sets from 50 languages. Both images and pen strokes needed to create characters were captured.
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