Artificial Intelligence Accelerates Efforts to Develop Clean, Virtually Limitless Fusion Energy

April 21, 2019

Depiction of fusion research on a doughnut-shaped tokamak enhanced by artificial intelligence.
Credit: Eliot Feibush/PPPL and Julian Kates-Harbeck/Harvard University

Artificial intelligence (AI), a branch of computer science that is transforming scientific inquiry and industry, could now speed the development of safe, clean and virtually limitless fusion energy for generating electricity. A major step in this direction is under way at the U.S. Department of Energy’s (DOE) Princeton Plasma Physics Laboratory (PPPL) and Princeton University, where a team of scientists working with a Harvard graduate student [Julian Kates-Harbeck, a physics graduate student at Harvard University and a DOE-Office of Science Computational Science Graduate Fellow who was lead author of the Nature paper and chief architect of the code] is for the first time applying deep learning — a powerful new version of the machine learning form of AI — to forecast sudden disruptions that can halt fusion reactions and damage the doughnut-shaped tokamaks that house the reactions...

Continue reading the press release from the Princeton Plasma Physics Laboratory by John Greenwald, "Artificial intelligence accelerates efforts to develop clean, virtually limitless fusion energy," April 18, 2019. https://www.pppl.gov/news/press-releases/2019/04/artificial-intelligence-accelerates-efforts-develop-clean-virtually-0.

Also read "Containing the Sun" by Mary Bergman in The Harvard Gazette, April 22, 2019. https://news.harvard.edu/gazette/story/2019/04/harvard-princeton-scientists-make-ai-breakthrough-for-fusion-energy/.

For the original Letter in Nature, please see: Kates-Harbeck, J., A. Svyatkovskiy & W. Tang, "Predicting disruptive instabilities in controlled fusion plasmas through deep learning," Nature (2019) https://doi.org/10.1038/s41586-019-1116-4.