Superstudent intelligence in thermodynamics
Fuente:
arXiv
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| Autori principali: | , , , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| Soggetti: | |
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| _version_ | 1866912425022849024 |
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| author | Loubet, Rebecca Zittlau, Pascal Hoffmann, Marco Vollmer, Luisa Fellenz, Sophie Leitte, Heike Jirasek, Fabian Lenhard, Johannes Hasse, Hans |
| author_facet | Loubet, Rebecca Zittlau, Pascal Hoffmann, Marco Vollmer, Luisa Fellenz, Sophie Leitte, Heike Jirasek, Fabian Lenhard, Johannes Hasse, Hans |
| contents | In this short note, we report and analyze a striking event: OpenAI's large language model o3 has outwitted all students in a university exam on thermodynamics. The thermodynamics exam is a difficult hurdle for most students, where they must show that they have mastered the fundamentals of this important topic. Consequently, the failure rates are very high, A-grades are rare - and they are considered proof of the students' exceptional intellectual abilities. This is because pattern learning does not help in the exam. The problems can only be solved by knowledgeably and creatively combining principles of thermodynamics. We have given our latest thermodynamics exam not only to the students but also to OpenAI's most powerful reasoning model, o3, and have assessed the answers of o3 exactly the same way as those of the students. In zero-shot mode, the model o3 solved all problems correctly, better than all students who took the exam; its overall score was in the range of the best scores we have seen in more than 10,000 similar exams since 1985. This is a turning point: machines now excel in complex tasks, usually taken as proof of human intellectual capabilities. We discuss the consequences this has for the work of engineers and the education of future engineers. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_09822 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Superstudent intelligence in thermodynamics Loubet, Rebecca Zittlau, Pascal Hoffmann, Marco Vollmer, Luisa Fellenz, Sophie Leitte, Heike Jirasek, Fabian Lenhard, Johannes Hasse, Hans Computational Engineering, Finance, and Science Artificial Intelligence In this short note, we report and analyze a striking event: OpenAI's large language model o3 has outwitted all students in a university exam on thermodynamics. The thermodynamics exam is a difficult hurdle for most students, where they must show that they have mastered the fundamentals of this important topic. Consequently, the failure rates are very high, A-grades are rare - and they are considered proof of the students' exceptional intellectual abilities. This is because pattern learning does not help in the exam. The problems can only be solved by knowledgeably and creatively combining principles of thermodynamics. We have given our latest thermodynamics exam not only to the students but also to OpenAI's most powerful reasoning model, o3, and have assessed the answers of o3 exactly the same way as those of the students. In zero-shot mode, the model o3 solved all problems correctly, better than all students who took the exam; its overall score was in the range of the best scores we have seen in more than 10,000 similar exams since 1985. This is a turning point: machines now excel in complex tasks, usually taken as proof of human intellectual capabilities. We discuss the consequences this has for the work of engineers and the education of future engineers. |
| title | Superstudent intelligence in thermodynamics |
| topic | Computational Engineering, Finance, and Science Artificial Intelligence |
| url | https://arxiv.org/abs/2506.09822 |