AI foundation models for experimental fusion tasks
Artificial Intelligence (AI) foundation models, while successful in various domains of language, speech, and vision, have not been adopted in production for fusion energy experiments. This brief paper presents how AI foundation models can be used for fusion energy diagnostics, enabling, for example,...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2025-02-01
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| Series: | Frontiers in Physics |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fphy.2024.1531334/full |
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| _version_ | 1823861062151176192 |
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| author | R. Michael Churchill |
| author_facet | R. Michael Churchill |
| author_sort | R. Michael Churchill |
| collection | DOAJ |
| description | Artificial Intelligence (AI) foundation models, while successful in various domains of language, speech, and vision, have not been adopted in production for fusion energy experiments. This brief paper presents how AI foundation models can be used for fusion energy diagnostics, enabling, for example, visual automated logbooks to provide greater insights into chains of plasma events in a discharge, in time for between-shot analysis. |
| format | Article |
| id | doaj-art-ce06634fac4f459db503a685443fd614 |
| institution | Kabale University |
| issn | 2296-424X |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Physics |
| spelling | doaj-art-ce06634fac4f459db503a685443fd6142025-02-10T05:16:21ZengFrontiers Media S.A.Frontiers in Physics2296-424X2025-02-011210.3389/fphy.2024.15313341531334AI foundation models for experimental fusion tasksR. Michael ChurchillArtificial Intelligence (AI) foundation models, while successful in various domains of language, speech, and vision, have not been adopted in production for fusion energy experiments. This brief paper presents how AI foundation models can be used for fusion energy diagnostics, enabling, for example, visual automated logbooks to provide greater insights into chains of plasma events in a discharge, in time for between-shot analysis.https://www.frontiersin.org/articles/10.3389/fphy.2024.1531334/fullfusion energyartificial intelligencemachine learningfoundation modelsdiagnostic |
| spellingShingle | R. Michael Churchill AI foundation models for experimental fusion tasks Frontiers in Physics fusion energy artificial intelligence machine learning foundation models diagnostic |
| title | AI foundation models for experimental fusion tasks |
| title_full | AI foundation models for experimental fusion tasks |
| title_fullStr | AI foundation models for experimental fusion tasks |
| title_full_unstemmed | AI foundation models for experimental fusion tasks |
| title_short | AI foundation models for experimental fusion tasks |
| title_sort | ai foundation models for experimental fusion tasks |
| topic | fusion energy artificial intelligence machine learning foundation models diagnostic |
| url | https://www.frontiersin.org/articles/10.3389/fphy.2024.1531334/full |
| work_keys_str_mv | AT rmichaelchurchill aifoundationmodelsforexperimentalfusiontasks |