New center merges math, AI to push frontiers of science
With artificial intelligence poised to assist in profound scientific discoveries that will change the world, Cornell is leading a new $11.3 million center focused on human-AI collaboration that uses mathematics as a common language.
The Scientific Artificial Intelligence Center, or SciAI Center, is being launched with a grant from the Office of Naval Research and is led by Christopher J. Earls, professor of civil and environmental engineering at Cornell Engineering. Co-investigators include Nikolaos Bouklas, assistant professor of mechanical and aerospace engineering at Cornell Engineering; Anil Damle, assistant professor of computer science in the Cornell Ann S. Bowers College of Computing and Information Science; and Alex Townsend, associate professor of mathematics in the College of Arts and Sciences. All of the investigators are field faculty members of the Center for Applied Mathematics.
With the advance of AI systems—built with tangled webs of algorithms and trained on increasingly large sets of data—researchers fear AI's inner workings will provide little insight into its uncanny ability to recognize patterns in data and make scientific predictions. Earls described it as a situation at odds with true scientific discovery.
"Scientific theories are explanatory stories that offer mechanistic insights into how the universe works," Earls said. "These theories offer reasoning behind what has been observed, but also, they predict that which has yet to be observed. Such extrapolatory power is entirely beyond anything standard AI can achieve. Our new center will pioneer radically new AI approaches for scientific discovery."
The SciAI Center will use mathematics as a common language between humans and machines because, Townsend said, math is how scientists have modeled the world for hundreds of years.
"Instead of getting AI to predict the future using data from a physical system, we will get AI to speak in the language of calculus and derive the underlying differential equations that govern a physical system," Townsend said. "We are trying to develop an AI-human collaboration that can become our science teacher, revealing patterns of the natural world."
The SciAI Center will have four intellectual thrusts—scientific data, operator learning, closure models and complex systems. Its three application areas of focus will be materials, turbulence and autonomy.
"By blending machine learning techniques with physics-informed algorithms, we can accelerate computational methods to aid in the understanding of materials and molecular systems," said Damle, who added that Cornell's fostering of interdisciplinary research makes it a natural home for such a center, enabling researchers from a broad set of areas to contribute.
Aside from its research goals, the center will be committed to helping populations underrepresented in science and engineering gain access to emerging AI tools through a series of student pathway programs that prepare young researchers to work in new industries.
Other institutions participating include the United States Naval Academy; the University of California, Santa Cruz; the California Institute of Technology; the University of Cambridge; Brown University; the University of California, Berkeley; and Integer Technologies.
Provided by Cornell University