The 2025 International Congress of Basic Science (ICBS) in Beijing brought together Nobel laureates, Fields medalists, Turing Award winners and leading scholars to explore the frontiers of basic science.

CGTN Digital had an exclusive interview with Wu Rongling, deputy head of the Beijing Institute of Mathematical Sciences and Applications (BIMSA), where most of the event took place.

Wu's insights into the intersection of mathematics and artificial intelligence (AI) offer a compelling vision for China's role in shaping the future of science.

AI race and the role of math

The drastic geopolitical shift in recent years, especially last year, has made AI a critical battleground, Wu told CGTN.

For China, mastering mathematics is not just an academic pursuit but a strategic imperative. "Only by mastering mathematics ourselves can we develop our own AI frameworks. Applied math is critical in the field of AI – we cannot avoid this issue," he said.

This urgency is underscored by the U.S.'s fluctuating policies on basic research. "The U.S. faces setbacks in basic research due to leadership issues," Wu said, referring to the Trump administration's effort to cut the funding of major research sponsors like the National Science Foundation. "This creates an opportunity for China."

By prioritizing mathematics, China can fill the void left by the U.S.' inconsistent attitude toward basic research, Wu said.

Math-AI synergy

Much of Wu's work focuses on the symbiotic relationship between mathematics and AI. "AI helps solve complex problems. Strong math research pushes AI forward. They are complementary," he told CGTN.

His team is pioneering methods to integrate advanced mathematics into AI's foundational frameworks, moving beyond the simplistic algorithms currently in use.

"AI now uses basic math ... but real-world problems are complex," he explained. " Complex problems need complex tools."

By applying advanced mathematical theories – such as those pioneered by Shing-Tung Yau, a Fields medalist and the head of BIMSA – Wu's team reduces computational demands, enabling AI to tackle challenges like molecular modeling and disease prediction with unprecedented efficiency.

Preparing the next generation

For Wu, the future of science hinges on education. "Teach children AI skills and basics – especially math theory," he urged. "Without this, they'll lack judgment, becoming dependent on AI alone."

He stresses that young researchers must understand "why algorithms work," not just "how to use them." This dual focus – technical proficiency and theoretical depth – will enable them to innovate rather than merely operate tools.

Cameraman: Gong Zhe

Video editor: Gong Zhe