“Compared to how China responded to previous revolutions in information technology, the speed at which China is following the current [AI] trend is the fastest,” says Shouyi Yin, vice director of Tsinghua University’s Institute of Microelectronics and the lead author of the Thinker paper, referring to the effort to design neural-network processors in China.

Even as China has become a manufacturing hub of solar panels and smartphones, the country’s semiconductor industry lags far behind that of the U.S. Between January and September 2017, China spent $182.8 billion importing integrated circuits—a 13.5 percent increase from the previous year, according to the China Semiconductor Industry Association. Major U.S. tech companies, including Google and Intel, as well as a few startups, are developing chips for AI applications (see “The Race to Power AI’s Silicon Brains”).

In a three-year action plan to develop AI, published by China’s Ministry of Industry and Information Technology in December 2017, the government laid out a goal of being able to mass-produce neural-network processing chips by 2020.

A schematic shows different elements of a chip called Thinker, developed at Tsinghua University in Beijing. PROVIDED BY SHOUYI YIN, TSINGHUA UNIVERSITY INSTITUTE OF MICROELECTRONICS

While it is possible to run AI software using existing chips such as the powerful graphics chips or FPGAs (a kind of blank chip that can be reconfigured on the fly), those designs are expensive and do not lend themselves to small devices that use batteries. That’s why Yin’s team at Tsinghua developed Thinker.

Thinker could be embedded in a wide range of devices, such as smartphones, watches, home robots, or equipment stationed in remote areas. Yin’s team plans to launch the first product fitted with Thinker this March.

Similar projects are under way elsewhere in China. In late January, a research team at the Chinese Academy of Sciences’ Institute of Computing Technology (ICT) will have a local semiconductor manufacturer produce a small batch of chips for use in robots. The chip, called Dadu, has two cores—one for running neural networks and another for controlling motion. The neural core runs the algorithms for vision but also allows the motion core to plan the optimal route for reaching a destination or the best motion for grabbing an object.

Yinhe Han, director of the institute’s Cyber Computing Lab and head of the robot chip project, envisions a slew of applications, including robots that deliver coffee and drones controlled with hand gestures. The advantage of developing a system like this in China, he says, is the large user base, which makes updating chip design based on user experience faster.

China has tried, and failed, to shake up the chip industry before. In 2001 the ICT assembled a team to develop desktop CPUs. That team became the kernel of a Chinese chipmaker called Loongson, but the company’s products never became as widely used as the founders would have liked.