Towards artificial general intelligence with hybrid Tianjic chip architecture.

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ID: 52733
2019
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Abstract
There are two general approaches to developing artificial general intelligence (AGI): computer-science-oriented and neuroscience-oriented. Because of the fundamental differences in their formulations and coding schemes, these two approaches rely on distinct and incompatible platforms, retarding the development of AGI. A general platform that could support the prevailing computer-science-based artificial neural networks as well as neuroscience-inspired models and algorithms is highly desirable. Here we present the Tianjic chip, which integrates the two approaches to provide a hybrid, synergistic platform. The Tianjic chip adopts a many-core architecture, reconfigurable building blocks and a streamlined dataflow with hybrid coding schemes, and can not only accommodate computer-science-based machine-learning algorithms, but also easily implement brain-inspired circuits and several coding schemes. Using just one chip, we demonstrate the simultaneous processing of versatile algorithms and models in an unmanned bicycle system, realizing real-time object detection, tracking, voice control, obstacle avoidance and balance control. Our study is expected to stimulate AGI development by paving the way to more generalized hardware platforms.
Reference Key
pei2019towardsnature Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Pei, Jing;Deng, Lei;Song, Sen;Zhao, Mingguo;Zhang, Youhui;Wu, Shuang;Wang, Guanrui;Zou, Zhe;Wu, Zhenzhi;He, Wei;Chen, Feng;Deng, Ning;Wu, Si;Wang, Yu;Wu, Yujie;Yang, Zheyu;Ma, Cheng;Li, Guoqi;Han, Wentao;Li, Huanglong;Wu, Huaqiang;Zhao, Rong;Xie, Yuan;Shi, Luping;
Journal Nature
Year 2019
DOI
10.1038/s41586-019-1424-8
URL
Keywords
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