•  
  •  
 

Bulletin of Chinese Academy of Sciences (Chinese Version)

Keywords

large-scale model development, open-source innovation ecosystem, policy recommendations

Document Type

Policy & Management Research

Abstract

Addressing the current technological development issues that constrain the development of China’s large-scale model industry is needed to promote the continuous prosperity and development of the industry and enhance its international competitiveness. The study analyzes the significance of the open-source innovation ecosystem for the development of large-scale models in China. Based on reviewing the international experience of constructing the open-source innovation ecosystem, it further dissects the problems and challenges faced by the construction of the open-source innovation ecosystem for large-scale models in China and puts forward targeted suggestions. The study finds that the open-source innovation ecosystem for large-scale models in China is faced with problems such as the restriction of ecological formation by technical capabilities, the significant limitation of technological development by data computing power, the disorderly competition among innovation subjects restricting the overall development speed, the low level of construction of the open-source support system, and the lack of the design of the system collaborative policy architecture, which hinder its rapid development and the improvement of competitiveness. There is a need to strengthen the top-level design and coordinated development, to build a shared basic system for large-scale model research and development, to enhance the construction of opensource and open systems throughout the entire industry chain, and to improve the governance of the open-source innovation system for large-scale models.

First page

1313

Last Page

1326

Language

Chinese

Publisher

Bulletin of Chinese Academy of Sciences

References

1 Bommasani R, Hudson D A, Adeli E, et al. On the opportunities and risks of foundation models. arXiv, 2022, doi: 10.48550/arXiv.2108.07258.

2 Bonaccorsi A, Rossi C. Why open source software can succeed. Research Policy, 2003, 32(7): 1243-1258.

3 Xie, X M, Wang H W. How can open innovation ecosystem modes push product innovation forward? An fsQCA analysis. Journal of Business Research, 2020, 108: 29-41.

4 中国信息通信研究院. 开源生态白皮书. 北京: 中国信息通信研究院, 2020. China Academy of Information and Communications Technology. Open Source Ecosystem White Paper. Beijing: China Academy of Information and Communications Technology, 2020. (in Chinese)

5 余江, 丁禹民, 刘嘉琪, 等. 深度数字化背景下开源创新的开放机理、治理机制与启示分析. 创新科技, 2021, 21(11): 13-20. Yu J, Ding Y M, Liu J Q, et al. Analysis of the open mechanism, governance mechanism, and enlightenment of open source innovation under the background of deep digitalization. Innovation Science and Technology, 2021, 21 (11): 13-20. (in Chinese)

6 隆云滔, 王晓明, 顾荣, 等. 国际开源发展经验及其对我国开源创新体系建设的启示. 中国科学院院刊, 2021, 36(12): 1497-1505. Long Y T, Wang X M, Gu R, et al. International open source development experience and its enlightenment to the construction of China’s open source innovation system. Bulletin of Chinese Academy of Sciences, 2021, 36(12): 1497-1505. (in Chinese)

7 Le S T, Fan A, Akiki C, et al. Bloom: A 176b-parameter open-access multilingual language model. arXiv, 2022, doi: 10.48550/arXiv.2211.05100.

8 Feller J, Fitzgerald B, Hissam S A, et al. An analysis of open source business models// Perspectives on Free and Open Source Software. Cambridge: MIT Press, 2007: 279-296.

9 Liang X, Li A Q, Zhu L, et al. SuperCLUE: A comprehensive Chinese large language model benchmark. arXiv, 2023, doi:10.48550/arXiv.2307.15020.

10 黄鹏, 李宏宽. 中国开源软件生态构建的风险及对策. 科技导报, 2021, 39(2): 83-95. Huang P, Li H K. Risks and Countermeasures in the construction of China’s open source software ecosystem. Science & Technology Review, 2021, 39(2): 83-95. (in Chinese)

11 Kaplan J, McCandlish S, Henighan T, et al. Scaling laws for neural language models. arXiv, 2020, doi: 10.48550/ arXiv.2001.08361.

12 Wei J, Tay Y, Bommasani R, et al. Emergent abilities of large language models. arXiv, 2022, doi: 10.48550/ arXiv.2206.07682.

13 中国信息通信研究院. 数据要素白皮书. 北京: 中国信息通信研究院, 2023. China Academy of Information and Communications Technology. Data Element White Paper. Beijing: China Academy of Information and Communications Technology, 2023. (in Chinese)

14 中国信息通信研究院. 中国算力指数发展白皮书. 北京: 中国信息通信研究院, 2023. China Academy of Information and Communications Technology. China Computing Power Index Development White Paper. Beijing: China Academy of Information and Communications Technology, 2023. (in Chinese)

15 北京市科学技术委员会, 中关村科技园区管理委员会. 北京市人工智能行业大模型创新应用白皮书(2023 年). 北京: 北京市科学技术委员会, 2023. Beijing Municipal Science and Technology Commission, Zhongguancun Science and Technology Park Management Committee. Beijing Artificial Intelligence Industry LargeScale Model Innovation Application White Paper (2023). Beijing: Beijing Municipal Science and Technology Commission, 2023. (in Chinese)

16 中国科学技术信息研究所. 中国人工智能大模型地图研究报告. 北京: 中国科学技术信息研究所, 2023. Institute of Scientific and Technical Information of China. Research Report on the Map of China’s Artificial Intelligence Large-Scale Models. Beijing: Institute of Scientific and Technical Information of China, 2023. (in Chinese)

Share

COinS