China’s first national laboratory for brain-like artificial intelligence (AI) technology was inaugurated Saturday to pool the country’s top research talent and boost the technology. China’s rapid rise up the ranks of AI research has the world’s scientific community taking notice. In October, the Obama White House released a “strategic plan” for AI research, which noted that the U.S. no longer leads the world in journal articles on “deep learning,” a particularly hot subset of AI research right now. The country that had overtaken the U.S.? China, of course.
“I have a hard time thinking of an industry we cannot transform with AI,” says Andrew Ng, chief scientist at Baidu. Ng previously cofounded Coursera and Google Brain, the company’s deep learning project. Now he directs Baidu’s AI research out of Sunnyvale, California, right in Silicon Valley.
“China has a fairly deep awareness of what’s happening in the English-speaking world, but the opposite is not true,” says Ng. He points out that Baidu has rolled out neural network-based machine translation and achieved speech recognition accuracy that surpassed humans—but when Google and Microsoft, respectively, did so, the American companies got a lot more publicity. “The velocity of work is much faster in China than in most of Silicon Valley,” says Ng.
Approved by the National Development and Reform Commission in January, the lab, based in China University of Science and Technology (USTC), aims to develop a brain-like computing paradigm and applications.
The university, known for its leading role in developing quantum communication technology, hosts the national lab in collaboration with a number of the country’s top research bodies such as Fudan University, Shenyang Institute of Automation of the Chinese Academy of Sciences as well as Baidu, operator of China’s biggest online search engine.
Wan Lijun, president of USTC and chairman of the national lab, said the ability to mimic the human brain’s ability in sorting out information will help build a complete AI technology development paradigm. The lab will carry out research to guide machine learning such as recognizing messages and using visual neural networks to solve problems. It will also focus on developing new applications with technological achievements.