VNI Distinguished Lecture Series - Science and Intelligence: A Virtuous Cycle
Supporting the below United Nations Sustainable Development Goals:支持以下聯合國可持續發展目標：支持以下联合国可持续发展目标：
Artificial Intelligence (AI) is revolutionizing our world, transforming everything from daily life to the fundamental pursuit of scientific discovery. As AI evolves into a new paradigm for scientific research, a critical question emerges: what is the deeper relationship between intelligence and science itself?
This lecture will explore this fascinating synergy. I will begin by re-examining the core concepts of "intelligence" — as the fundamental capacity for problem-solving that this process requires, and "science" — not just as a body of knowledge, but as a process for uncovering the laws of the universe.
I will argue that this relationship is a virtuous cycle: science is the engine that creates intelligence (both human and artificial), and this enhanced intelligence, in turn, accelerates the process of science. This will be illustrated by examples, including some of our recent progress in scientific discovery enabled by AI and how we design better AI under the guidance of scientific principles. Today, we stand at a pivotal moment, pushing against the limits of carbon-based human intelligence (HI) by creating silicon-based intelligence (AI).
The lecture will conclude by envisioning a future of collaborative discovery, where the combined power of HI and AI continues to propel this virtuous cycle forward, leading us to a deeper understanding of the universe than ever.
An internationally renowned AI expert, Strategic Scientist of the "Hai Ju Project," Council Member of the Chinese Information Processing Society, and Academic Committee Member of Changping Laboratory. He previously served as Assistant Managing Director of Microsoft Research Asia and Distinguished Scientist of Microsoft Research AI for Science. He is a Fellow of the IEEE, ACM, and AAIA.
With a long-standing focus on information retrieval and AI, he has achieved remarkable accomplishments in both academia and industry. His work has significantly contributed to bridging the gap between machine learning and information retrieval, as well as advancing scientific discovery and industrial development through artificial intelligence. Recognized for his groundbreaking contributions, he was named one of the "100 Most Influential AI Scholars Globally Since 1943" by the International Open Benchmarking Council.