AI for Science: In-Depth Analysis of 2024 Nobel Prize Results and Suggestions for Guangdong’s Development

Huan Wang, Xiaohui Fu, Haoyuan Guan () and Huimin Shang
Additional contact information
Huan Wang: Guangdong Institute of Science and Technology Information
Xiaohui Fu: Tsinghua University High School Guangzhou
Haoyuan Guan: Guangdong Institute of Science and Technology Information
Huimin Shang: Guangdong Institute of Science and Technology Information

A chapter in Proceedings of the 2024 6th Management Science Informatization and Economic Innovation Development Conference (MSIEID 2024), 2025, pp 650-659 from Springer

Abstract: Abstract With the theme of “Artificial Intelligence-driven Scientific Research” (AI for Science), this paper focuses on analyzing the results of the 2024 Nobel Prize in Physics and the Nobel Prize in Chemistry, analyzing the innovation path of cross-fertilization of basic sciences such as physics, chemistry and AI, revealing the important role of AI for Science in driving paradigm shifts, enhancing research efficiency, and expanding the horizons of scientific exploration.It analyzes the innovation path of cross-fertilization of physics, chemistry and other basic sciences with AI, reveals the important role of AI for Science in promoting the paradigm change of scientific research, improving the efficiency of scientific research, and broadening the boundaries of scientific research, etc. At the same time, it introduces the practices of various countries in promoting AI for Science as well as China’s strategic deployment in the field of AI for Science, and gives corresponding suggestions for the development of AI for Science in Guangdong.

Keywords: artificial intelligence; scientific research; scientific paradigm; AI for Science (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:advbcp:978-94-6463-676-5_63

Ordering information: This item can be ordered from
http://www.springer.com/9789464636765

DOI: 10.2991/978-94-6463-676-5_63

Access Statistics for this chapter

More chapters in Advances in Economics, Business and Management Research from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().