The following document announces China’s 2023 research priorities in explainable and generalizable artificial intelligence methods. It also provides state funds for projects related to these priorities, and explains how Chinese AI researchers can apply for funding. Applications of AI in medicine, biology, physics, materials science, and mathematics are prominent among the 2023 priorities.
The Chinese source text is available online at:
An archived version of the Chinese source text is available online at: https://perma.cc/9C45-MK52
Notice on the Release of the “Guide to the 2023 Annual Projects for the Major Research Program on Explainable and Generalizable Next-Generation Artificial Intelligence Methods”
National Natural Science Foundation of China 2023 No. 12
The National Natural Science Foundation of China (NSFC) is now releasing the “Guide to the 2023 Annual Projects for the Major Research Program on Explainable and Generalizable Next-Generation Artificial Intelligence Methods.” Applicants and [their] registered host institutions (依托单位)1 are requested to apply in accordance with the requirements and matters of importance as specified in the program guide.2
National Natural Science Foundation of China
March 31, 2023
Guide to the 2023 Annual Projects for the Major Research Program on Explainable and Generalizable Next-Generation Artificial Intelligence Methods
The Major Research Program on Explainable3 and Generalizable (可通用)4 Next-Generation5 Artificial Intelligence Methods is geared towards the national major strategic needs of artificial intelligence (AI) development; developing a system of new AI methods with the basic scientific problems of AI as the core; promoting China’s basic AI research and talent cultivation; and supporting China’s leading position in the new round of international competition in science and technology (S&T).
I. Scientific Objectives
This Major Research Program is geared towards poor robustness, poor explainability, strong dependence on data, and other basic scientific problems in AI methods as represented by deep learning; investigating the basic principles of machine learning; developing explainable and generalizable next-generation AI methods; and promoting the innovation and applications of AI methods in scientific fields.
II. Core Scientific Problems
This Major Research Program is targeted at the basic scientific problems of explainable and generalizable next-generation AI methods, launching research focused on the following three core scientific problems:
(1) The basic principles of deep learning.
Deeply delve into the dependence of deep learning models on hyperparameters; understand the working principles behind deep learning; and establish for deep learning methods approximation theory, generalization error analysis theory, and convergence theory of optimization algorithms.
(2) Explainable and generalizable next-generation AI methods.
Through the means of combining rules and learning, establish new AI methods that are high-precision, explainable, generalizable, and do not rely on large amounts of annotated data. Develop the databases and model training platforms needed for next-generation AI methods; improve infrastructure driven by next-generation AI methods.
(3) Applications of next-generation AI methods geared towards scientific fields.
Develop new physics (物理) models and algorithms; build open-source scientific databases, knowledge bases, and physics model repositories and algorithm repositories; promote exemplary applications of new AI methods in solving complex problems in scientific fields.
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- Translator’s note: In English-language documents NSFC has previously released, they variously translate the Chinese term 依托单位 (literally, “entrusted units”) as “registered host institutions,” “host institutions,” and “supporting institutions.” The term refers to universities, research institutions, and other organizations that conduct research in China and are registered with NSFC. They are responsible for assisting NSFC in recruiting applicants for funding, supervising project implementation, etc. Additional details may be found in the Articles 8 and 9 of the “National Natural Science Foundation Regulations” (available in Chinese and English) and in the “National Natural Science Foundation Registered Host Institutions Funding Work Management Methods” (available in Chinese).
- Translator’s note: Refer to section VI and VI(3) for “requirements” and “matters of importance,” respectively.
- This translation renders the Chinese term 可解释, as it relates to AI, as “explainable.” An alternate translation is “interpretable.”
- Translator’s note: The Chinese word translated as “general” in this document (通用) is the same word that is used in the Chinese expression 通用人工智能, which can be translated as “general purpose artificial intelligence” (general purpose AI) or “artificial general intelligence” (AGI).
- Translator’s note: This document alternately uses the terms “新一代” and “下一代.” For consistency with other translations in the field; we render these as “new generation” and “next-generation,” respectively.