This year marks the 120th anniversary of the publication of the MIT Technology Review. The 3rd “MIT Technology Review Innovators under 35 in China” was released at the EmTech MIT China Global Emerging Technology Summit on December 14th, 2019. Deng Lei, the first Ph.D from the Center for Brain-Inspired Computing Research at Tsinghua University (now the postdoctoral fellow at UCSB), was named an Innovators under 35 in China (2019).

Without “entrepreneurs” on the list this year, many of the selected still have great potential in the scientific field of industrialization. Moreover, with their efforts, Chinese scientists in top overseas academic institutions have made prestigious advancements. More than half of the innovators on the list dedicated to science and technology have achieved world-class breakthroughs.

In August 2019, the Tianjic Chip developed by Professor Shi Luping and his team from the Center for Brain-Inspired Computing Research (CBICR) at Tsinghua University was published in Nature as the cover article. It was the first hybrid-paradigm brain-inspired chip in the world to support not only Spiking Neural Networks (SNNs) in the brain-inspired computing but also Artificial Neural Networks (ANNs) in AI. Its processing ability was successfully verified in the application scenario of autonomous bicycles. This is the first time that work by a Chinese team in the fields of chips and AI has been published as the cover article of Nature.

A brief introduction of Dr. Deng Lei in the MIT Technology Review is as follows:

Age: 29

Position: Postdoctoral Fellow at the UCSB

Reasons for award: Dr. Deng is the lead designer of the Tianjic Chip, the first hybrid-paradigm brain-inspired chip in the world, which verifies the feasibility of AGI in the application scenario of autonomous bicycles.

As the lead designer, the awardee has completed the development of the Tianjic Chip, the first hybrid-paradigm brain-inspired chip in the world. As distinct from traditional intelligent scenarios, this chip supports not only SNNs but also ANNs, bridging computer-science-oriented machine learning and neuroscience-oriented neuromorphic computing on the same platform.

In an authentic application scenario of an unmanned bicycle, the Tianjic Chip verified its ability in terms of recognition, object detection and tracking, obstacle avoidance, and decision making, which reflects more than 10 times the energy efficiency ratio.

The Tianjic Chip brings a new computing platform for future AI and brain science research. It will become an important part of the infrastructure in scientific research for the next generation of AI and brain science, and provides the possibility for the new implementation of artificial general intelligence.

Contributor: MIT Technology Review