Summary of Key Points
The 2026 Future Science Prize in the category of “Mathematics and Computer Science” was awarded to Professor Yuan Xinyi from Peking University, in recognition of his groundbreaking contributions to the field of arithmetic geometry. In an interview, he shared insightful views on topics such as the rise of Chinese mathematics, the connection between mathematics and industry, the impact of AI on mathematical research, the optimization of the research environment for young scientists, and how young people can utilize AI.
Detailed Analysis
1. Why Do Foreigners Say “China is Taking Over Math”? – The Journey from Training System to International Prestige
Professor Yuan mentioned that the phrase “China is taking over math” often comes from international mathematicians conferences, reflecting a qualitative change in Chinese mathematics over the past two decades. This transformation is not sudden but the result of several generations of effort:
- Preliminary Steps: After the reform and opening up, many Chinese scholars went abroad for further education. Upon returning, they helped establish training systems, design courses, and guide students to study abroad.
- The Benefits of Our Generation: People born in the 1980s (like Professor Yuan) grew up within this system, and even more from the 1990s returned to China full-time.
- Enhanced Resources: With the improvement of the national economy, there are now more resources available for scientific research. China has surpassed Japan and Russia in terms of mathematical data, ranking only behind the United States and Europe. The fact that two out of four Fields Medalists are Chinese is a testament to this success.
2. Mathematics Is Not a “Useless Subject” – A Core Competency Highly Desired by the Industry
Many people think that mathematical conjectures are useless, but Professor Yuan cited the example of Riemann geometry: it was initially so abstract that no one understood it, yet decades later it helped Einstein develop the theory of general relativity. Today, industries such as quantitative finance, AI, and chip manufacturing are in dire need of mathematicians because mathematics provides two crucial skills:
- Logical Rigor: The ability to think through problems thoroughly and avoid basic mistakes.
- Abstract Thinking: The capability to transform complex real-world problems (such as chip design optimization) into mathematical models for easier resolution.
This is also evident from the increasing popularity of mathematics at Peking University. Since 2010, the admission score for its mathematics department has become the highest among all science departments, indicating that students are willing to study mathematics and see its value in their careers.
3. AI Can Assist Mathematicians, but It Cannot Take the Lead – Clear Advantages, Yet a Lack of Originality
AI has made rapid progress in mathematics, but Professor Yuan notes that it has not yet produced truly original results. Its strengths include:
- Broad Knowledge: AI can integrate ideas from various fields.
- Computational Power: It can perform extensive trials and generate examples or counterexamples (for example, in proving the Jacobian conjecture).
However, AI’s limitations are also significant: it cannot determine the importance of problems on its own or propose meaningful questions; all its findings still require human guidance.
4. The Pressure on Young Mathematicians – The “Promotion or Departure” System Is a Major Challenge
Professor Yuan pointed out that the biggest challenge in China’s research environment is the excessive pressure on young researchers. This stems from the adaptation of the American “promotion or departure” system, which has become distorted in China:
- American Model: A single assessment leads to an 80-90% promotion rate, ensuring a lifetime of research.
- Chinese Adaptation: Multiple evaluations are required, resulting in a lower promotion rate. During recruitment, many candidates are chosen based on their paper publications, leading to a high turnover rate after six years.
This creates anxiety among young scholars, preventing them from engaging in long-term, risky research.
5. How Young People Can Use AI: Build Fundamental Skills First, Then Leverage Its Power
Professor Yuan offers practical advice to newcomers:
- Initially, Rely Less on AI: Try to complete your first paper independently to develop your own research skills (such as identifying problems and deriving conclusions).
- Later, Use AI Effectively: Once you have mastered the methods, use AI to search for information and organize your thoughts, which can improve efficiency.
By breaking down complex concepts in simple language, Professor Yuan makes financial and academic content accessible to a wider audience.