Towards a new generation of artificial intelligence in China

被引:125
作者
Wu, Fei [1 ]
Lu, Cewu [2 ]
Zhu, Mingjie [3 ]
Chen, Hao [4 ]
Zhu, Jun [5 ]
Yu, Kai [3 ]
Li, Lei [6 ]
Li, Ming [7 ]
Chen, Qianfeng [8 ]
Li, Xi [1 ]
Cao, Xudong [9 ]
Wang, Zhongyuan [10 ]
Zha, Zhengjun [11 ]
Zhuang, Yueting [1 ]
Pan, Yunhe [1 ,12 ]
机构
[1] Zhejiang Univ, Hangzhou, Peoples R China
[2] Shanghai Jiao Tong Univ, Shanghai, Peoples R China
[3] CraiditX, Shanghai, Peoples R China
[4] Imsight Med Technol, Hong Kong, Peoples R China
[5] Tsinghua Univ, Beijing, Peoples R China
[6] ByteDance, Beijing, Peoples R China
[7] Nanjing Univ, Nanjing, Peoples R China
[8] Hong Kong Univ Sci & Technol, Hong Kong, Peoples R China
[9] Momenta, Beijing, Peoples R China
[10] Meituan, Beijing, Peoples R China
[11] Univ Sci & Technol China, Hefei, Peoples R China
[12] Zhejiang Lab, Hangzhou, Peoples R China
关键词
AI;
D O I
10.1038/s42256-020-0183-4
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Artificial intelligence has become a main driving force for a new round of industrial transformation around the world. Many countries including China are seizing the opportunity of the AI revolution to promote domestic economic and technological development. This Perspective briefly introduces the New Generation Artificial Intelligence Development Plan of China (2015-2030) from the point of view of the authors, a group of AI experts from academia and industry who have been involved in various stages of the plan. China's AI development plan outlines a strategy for science and technology as well as education, tackling a number of challenges such as retaining talent, advancing fundamental research and exploring ethical issues. The New Generation Artificial Intelligence Development Plan is intended to be a blueprint for a complete AI ecosystem for the country. China's New Generation Artificial Intelligence Development Plan was launched in 2017 and lays out an ambitious strategy, which intends to make China one of the world's premier AI innovation centre by 2030. This Perspective presents the view from a group of Chinese AI experts from academia and industry about the origins of the plan, the motivations and main focus for attention from research and industry.
引用
收藏
页码:312 / 316
页数:5
相关论文
共 28 条
  • [1] Uncovering and Mitigating Algorithmic Bias through Learned Latent Structure
    Amini, Alexander
    Soleimany, Ava P.
    Schwarting, Wilko
    Bhatia, Sangeeta N.
    Rus, Daniela
    [J]. AIES '19: PROCEEDINGS OF THE 2019 AAAI/ACM CONFERENCE ON AI, ETHICS, AND SOCIETY, 2019, : 289 - 295
  • [2] [Anonymous], 2019, GROW IOT CHIN
  • [3] [Anonymous], 2019, CHINA BANKING NEWS
  • [4] [Anonymous], 2020, MOBILE EC 2020
  • [5] Diagnostic Assessment of Deep Learning Algorithms for Detection of Lymph Node Metastases in Women With Breast Cancer
    Bejnordi, Babak Ehteshami
    Veta, Mitko
    van Diest, Paul Johannes
    van Ginneken, Bram
    Karssemeijer, Nico
    Litjens, Geert
    van der Laak, Jeroen A. W. M.
    [J]. JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION, 2017, 318 (22): : 2199 - 2210
  • [6] Artificial intelligence in cancer imaging: Clinical challenges and applications
    Bi, Wenya Linda
    Hosny, Ahmed
    Schabath, Matthew B.
    Giger, Maryellen L.
    Birkbak, Nicolai J.
    Mehrtash, Alireza
    Allison, Tavis
    Arnaout, Omar
    Abbosh, Christopher
    Dunn, Ian F.
    Mak, Raymond H.
    Tamimi, Rulla M.
    Tempany, Clare M.
    Swanton, Charles
    Hoffmann, Udo
    Schwartz, Lawrence H.
    Gillies, Robert J.
    Huang, Raymond Y.
    Aerts, Hugo J. W. L.
    [J]. CA-A CANCER JOURNAL FOR CLINICIANS, 2019, 69 (02) : 127 - 157
  • [7] Bonawitz K., 2019, P MACHINE LEARNING S, V1, P374
  • [8] Cancer Statistics in China, 2015
    Chen, Wanqing
    Zheng, Rongshou
    Baade, Peter D.
    Zhang, Siwei
    Zeng, Hongmei
    Bray, Freddie
    Jemal, Ahmedin
    Yu, Xue Qin
    He, Jie
    [J]. CA-A CANCER JOURNAL FOR CLINICIANS, 2016, 66 (02) : 115 - 132
  • [9] China AI, 2018, CHINA AI DEV REPORT
  • [10] Fisk P, 2019, GAMECHANGERS