|China’s massive investment in artificial intelligence has an insidious downside|
In a gleaming high-rise here in northern Beijing's Haidian district, two hardware jocks in their 20s are testing new computer chips that might someday make smartphones, robots, and autonomous vehicles truly intelligent. A wiry young man in an untucked plaid flannel shirt watches appraisingly. The onlooker, Chen Yunji, a 34-year-old computer scientist and founding technical adviser of Cambricon Technologies here, explains that traditional processors, designed decades before the recent tsunami of artificial intelligence (AI) research, "are slow and energy inefficient" at processing the reams of data required for AI. "Even if you have a very good algorithm or application," he says, its usefulness in everyday life is limited if you can't run it on your phone, car, or appliance. "Our goal is to change all lives."
In 2012, the seminal Google Brain project required 16,000 microprocessor cores to run algorithms capable of learning to identify a cat. The feat was hailed as a breakthrough in deep learning: crunching vast training data sets to find patterns without guidance from a human programmer. A year later, Yunji and his brother, Chen Tianshi, who is now Cambricon's CEO, teamed up to design a novel chip architecture that could enable portable consumer devices to rival that feat—making them capable of recognizing faces, navigating roads, translating languages, spotting useful information, or identifying "fake news."
Tech companies and computer science departments around the world are now pursuing AI-optimized chips, so central to the future of the technology industry that last October Sundar Pichai, CEO of Google in Mountain View, California, told The Verge that his guiding question today is: "How do we apply AI to rethink our products?" The Chen brothers are by all accounts among the leaders; their Cambricon-1A chip made its commercial debut last fall in a Huawei smartphone billed as the world's first "real AI phone." "The Chen brothers are pioneering in terms of specialized chip architecture," says Qiang Yang, a computer scientist at Hong Kong University of Science and Technology (HKUST) in China.
Just as oil fueled the industrial age, data are fueling advances of the AI age. Many practical AI advances are "more about having a large amount of continually refreshed data and good-enough AI researchers who can make use of that data, rather than some brilliant AI theoretician who doesn't have as much data," says computer scientist Kai-Fu Lee, founder of Sinovation Ventures, a venture capital firm here. And China, as The Economist recently put it, is "the Saudi Arabia of data."