Presenter
Abstract
The DOE National Laboratories are convening four town hall meetings aimed at collecting community input on the opportunities and challenges facing the scientific community in the era of convergence of high-performance computing (HPC) and artificial intelligence (AI) technologies and the expected integration of large-scale simulation, advanced data analysis, data-driven predictive modeling, theory, and high-throughput experiments. The term we are using to represent the next generation of methods and scientific opportunity is “AI for Science”.
AI for Science is broadly construed to mean the use of AI methods (e.g., machine learning, deep learning, statistical methods, data analytics, automated control, and related areas) to build models from data and to use these models alone or in conjunction with simulation to advance scientific research. These discussions will focus on transformational and large-scale uses of AI that use HPC and data analysis as well as take advantage of data sets and challenges unique to DOE user facilities and broad fundamental and applied science enterprise. The goal of AI for Science is to dramatically accelerate our approaches to scientific discovery, improve scientific competitiveness, and open up new avenues of scientific inquiry. Crosscutting approaches that may fall outside traditional notions of experiment, theory, and simulation are also included.
The town hall meetings will engage the DOE science community in a series of broad and open discussions about opportunities that can be realized by advancing and accelerating the development of AI capabilities specifically for science and science use cases.
The town halls aim to address critical research and facility challenges, including the application of AI in various scientific domains, data analysis and management, automation and control of experiments, algorithms and mathematical foundations, challenges of scale within and across data sets, and emerging computer- and system-level architectures. The facility discussions will address the need for a more tightly integrated national- and global-scale data and computing environment that brings together data assets organized and prepared for discovery and integrated with the variety of computing capabilities (e.g., AI, machine learning, modeling and simulation). This environment will need flexible, high-speed networking to connect devices on the edge with centralized and federated computing and data resources, regionally and across the national leadership facilities.
We expect approximately 200 to 300 researchers and engineers from universities, national laboratories, and industry around the United States to participate at each town hall. With some participant overlap across town halls to relay and convey a continuous stream of scientific knowledge, the total interaction with the scientific community will include input from at least 500 scientists and researchers over the four meetings.
Each town hall will be broken into a series of high-level talks, breakout sessions, and report-out periods. Each breakout session will have two scientific co-leads, a scientific scribe, and a technical writer. The end goal of the town halls is to quickly produce one integrated report from the four meetings that can be used to inform strategic planning.