Uploaded December 2024 | Updated September 2026, 2 weeks ago
This media roundtable was held at AGU's 2024 Annual Meeting on 9 December 2024.
Science has widely employed machine learning to tackle analysis of big data, but generative AI opens new possibilities for the design and implementation of experiments. The explosive arrival of ChatGPT has fired up the imagination of the research community to put this new technology to work.
In this press roundtable, panelists discuss how they are exploring the potential for large language models to participate in the process of science, with a focus on climate science applications. Join us to learn about early results, strengths, weaknesses and the future of AI-assisted science.
Panelists:
Ian Foster, University of Chicago and Argonne National Laboratory
Michael Hendrickson, NASA Goddard Institute for Space Studies
Alexander Herron, NASA Goddard Institute for Space Studies
Jennifer A. Sleeman, Johns Hopkins University Applied Physics Laboratory
Matthew J. Widlansky, University of Hawaii at Manoa
This media roundtable was held at AGU's 2024 Annual Meeting on 9 December 2024.
Science has widely employed machine learning to tackle analysis of big data, but generative AI opens new possibilities for the design and implementation of experiments. The explosive arrival of ChatGPT has fired up the imagination of the research community to put this new technology to work.
In this press roundtable, panelists discuss how they are exploring the potential for large language models to participate in the process of science, with a focus on climate science applications. Join us to learn about early results, strengths, weaknesses and the future of AI-assisted science.
Panelists:
Ian Foster, University of Chicago and Argonne National Laboratory
Michael Hendrickson, NASA Goddard Institute for Space Studies
Alexander Herron, NASA Goddard Institute for Space Studies
Jennifer A. Sleeman, Johns Hopkins University Applied Physics Laboratory
Matthew J. Widlansky, University of Hawaii at Manoa
