The Decade Ahead: Building Frontier AI Systems for Science and the Path to Zettascale

9:00 AM - 9:50 AM

Rick Stevens Rick Stevens
ANL and UChicago
Abstract: The successful development of transformative applications of AI for science, medicine and energy research will have a profound impact on the world. The rate of development of AI capabilities continues to accelerate, and the scientific community is becoming increasingly agile in using AI, leading to us to anticipate significant changes in how science and engineering goals will be pursued in the future. Frontier AI (the leading edge of AI systems) enables small teams to conduct increasingly complex investigations, accelerating some tasks such as generating hypotheses, writing code, or automating entire scientific campaigns. However, certain challenges remain resistant to AI acceleration such as human-to-human communication, large- scale systems integration, and assessing creative contributions. Taken together these developments signify a shift toward more capital-intensive science, as productivity gains from AI will drive resource allocations to groups that can effectively leverage AI into scientific outputs, while other will lag. In addition, with AI becoming the major driver of innovation in high-performance computing, we also expect major shifts in the computing marketplace over the next decade, we see a growing performance gap between systems designed for traditional scientific computing vs those optimized for large-scale AI such as Large Language Models. In part, as a response to these trends, but also in recognition of the role of government supported research to shape the future research landscape the U. S. Department of Energy has created the FASST (Frontier AI for Science, Security and Technology) initiative. FASST is a decadal research and infrastructure development initiative aimed at accelerating the creation and deployment of frontier AI systems for science, energy research, national security. I will review the goals of FASST and how we imagine it transforming the research at the national laboratories. Along with FASST, I’ll discuss the goals of the recently established Trillion Parameter Consortium (TPC), whose aim is to foster a community wide effort to accelerate the creation of large-scale generative AI for science. Additionally, I'll introduce the AuroraGPT project an international collaboration to build a series of multilingual multimodal foundation models for science, that are pretrained on deep domain knowledge to enable them to play key roles in future scientific enterprises.
Bio. Rick Stevens is the Associate Laboratory Director of the Computing, Environment and Life Sciences Directorate at Argonne National Laboratory, and a Professor of Computer Science at the University of Chicago, with significant responsibility in delivering on the U.S. national initiative for Exascale computing and developing the DOE initiative in Artificial Intelligence (AI) for Science. At Argonne, he is leading the Laboratory’s AI for Science initiative and currently focusing on high-performance computing systems which includes leading a significant collaboration with Intel and Cray to launch Argonne’s first exascale computer, Aurora 21, which will pursue some of the farthest-reaching science and engineering breakthroughs ever achieved with supercomputing, as well as a partnership with Cerebras Systems to bring hardware on site to advance the massive deep learning experiments being pursued at Argonne for basic and applied science and medicine with supercompute-scale AI. Prof. Stevens is a member of the American Association for the Advancement of Science and has received many national honors for his research, including an R&D 100 award.