Nov 14, 2017 |
New technology makes artificial intelligence more private and portable
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(Nanowerk News) Technology developed at the University of Waterloo is paving the way for artificial intelligence (AI) to break free of the internet and cloud computing.
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New deep-learning AI software produced with that technology is compact enough to fit on mobile computer chips for use in everything from smartphones to industrial robots.
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That would allow devices to operate independent of the internet while using AI that performs almost as well as tethered neural networks.
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"We feel this has enormous potential," said Alexander Wong, a systems design engineering professor and Waterloo and co-creator of the technology. "This could be an enabler in many fields where people are struggling to get deep-learning AI in an operational form."
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The use of stand-alone deep-learning AI could lead to much lower data processing and transmission costs, greater privacy and use in areas where existing technology is impractical due to expense or other factors.
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Deep-learning AI, which mimics the human brain by processing data through layers and layers of artificial neurons, typically requires considerable computational power, memory and energy to function.
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Researchers took a page from evolutionary forces in nature to make that AI far more efficient by placing it in a virtual environment, then progressively and repeatedly depriving it of resources.
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The deep-learning AI responds by adapting and changing itself to keep functioning each time computational power and memory are taken away.
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"These networks evolve themselves through generations and make themselves smaller to be able to survive in these environments," said Mohammad Javad Shafiee, a systems design engineering research professor at Waterloo and the technology's co-creator.
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In work recently presented during the International Conference on Computer Vision in Venice, Italy, the researchers achieved a 200-fold reduction in the size of deep-learning AI software used for a particular object recognition task.
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When put on a chip and embedded in a smartphone, such compact AI could run its speech-activated virtual assistant and other intelligent features, greatly reducing data usage and operating without internet service.
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Other potential applications range from use in low-cost drones and smart grids, to surveillance cameras and manufacturing plants, where there are significant issues around streaming sensitive or proprietary data to the cloud.
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Wong and Shafiee, who have co-founded a company called DarwinAI to commercialize their efficient AI software, were "amazed" at the results when they first attempted their approach to evolving deep-learning AI about three years ago.
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"We are researchers, so we explore many different things," said Shafiee. "And if it works, we keep going and push harder."
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