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How do we find the next super material? How do we discover the next breakthrough drug? How do we unlock the mystery of dark matter and the structure of the universe? Scientists develop theories about these questions and test those theories with two powerful tools: laboratory experiments and computational models. But these tests can be costly: Each experiment can use hours or days of person-power on specialized equipment, and simulations can take days or weeks on a supercomputer. Access to these resources is limited; every measurement needs to count. This talk explores how scientists are using artificial intelligence to accelerate discovery, not only to analyze data more effectively, but to actively guide choices about the best next measurements to take to meet scientific goals. Along the way, I will explain what is unique about using AI for scientific research, share examples from my own work, and offer a glimpse of where AI-powered science is headed.
