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Artificial Intelligence

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In short, there is a global demand for clean, cheap, reliable energy – and artificial intelligence (AI) is increasingly being used to help meet this need. 

Researchers poised to deliver key scientific findings in the fast lane

Streaming data, the online process that brings movies, music and videos instantly into homes, is poised to accelerate the worldwide distribution of scientific discoveries in fusion research. Scientists at the U.S. Department of Energy’s (DOE) Princeton Plasma Physics Laboratory (PPPL) and Oak Ridge National Laboratory (ORNL) have demonstrated the streaming and rapid analysis of findings from a fusion reactor in South Korea to Princeton, New Jersey.

Physicist Dan Boyer wins Early Career Award for research in Artificial Intelligence methods to advance fusion energy

Dan Boyer, a physicist and developer of innovative artificial intelligence (AI) machine learning methods to produce real-time adjustments to the plasma that fuels fusion reactions in evices known as spherical tokamaks, has won a highly competitive and prestigious U.S. Department of Energy (DOE) Early Career Award.

Physicist Dan Boyer wins Early Career Award for research in Artificial Intelligence methods to advance fusion energy

Dan Boyer, a physicist and developer of innovative artificial intelligence (AI) machine learning methods to produce real-time adjustments to the plasma that fuels fusion reactions in devices known as spherical tokamaks, has won a highly competitive and prestigious U.S. Department of Energy (DOE) Early Career Award.

Extreme-scale computing and AI help forecast a promising outlook for divertor heat-loads in next-step fusion reactors

Efforts to duplicate on Earth the fusion reactions that power the sun and stars for unlimited energy must contend with extreme heat-load density that can damage the doughnut-shaped fusion facilities called tokamaks, the most widely used laboratory facilities that house fusion reactions, and shut them down.

Extreme-scale computing and AI help forecast a promising outlook for divertor heat-loads in next-step fusion reactors

Efforts to duplicate on Earth the fusion reactions that power the sun and stars for unlimited energy must contend with extreme heat-load density that can damage the doughnut-shaped fusion facilities called tokamaks, the most widely used laboratory facilities that house fusion reactions, and shut them down.

New machine learning theory that can be applied to fusion energy raises questions about the very nature of science

A novel computer algorithm, or set of rules, that accurately predicts the orbits of planets in the solar system could be adapted to better predict and control the behavior of the plasma that fuels fusion facilities designed to harvest on Earth the fusion energy that powers the sun and stars.

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