The Role of Computing Resources in Publishing Foundation Model Research
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arXiv
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| Main Authors: | , , , , , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866908595446087680 |
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| author | Hao, Yuexing Huang, Yue Zhang, Haoran Zhao, Chenyang Liang, Zhenwen Liang, Paul Pu Zhao, Yue Sun, Lichao Kalantari, Saleh Zhang, Xiangliang Ghassemi, Marzyeh |
| author_facet | Hao, Yuexing Huang, Yue Zhang, Haoran Zhao, Chenyang Liang, Zhenwen Liang, Paul Pu Zhao, Yue Sun, Lichao Kalantari, Saleh Zhang, Xiangliang Ghassemi, Marzyeh |
| contents | Cutting-edge research in Artificial Intelligence (AI) requires considerable resources, including Graphics Processing Units (GPUs), data, and human resources. In this paper, we evaluate of the relationship between these resources and the scientific advancement of foundation models (FM). We reviewed 6517 FM papers published between 2022 to 2024, and surveyed 229 first-authors to the impact of computing resources on scientific output. We find that increased computing is correlated with national funding allocations and citations, but our findings don't observe the strong correlations with research environment (academic or industrial), domain, or study methodology. We advise that individuals and institutions focus on creating shared and affordable computing opportunities to lower the entry barrier for under-resourced researchers. These steps can help expand participation in FM research, foster diversity of ideas and contributors, and sustain innovation and progress in AI. The data will be available at: https://mit-calc.csail.mit.edu/ |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_13621 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | The Role of Computing Resources in Publishing Foundation Model Research Hao, Yuexing Huang, Yue Zhang, Haoran Zhao, Chenyang Liang, Zhenwen Liang, Paul Pu Zhao, Yue Sun, Lichao Kalantari, Saleh Zhang, Xiangliang Ghassemi, Marzyeh Computers and Society Artificial Intelligence Cutting-edge research in Artificial Intelligence (AI) requires considerable resources, including Graphics Processing Units (GPUs), data, and human resources. In this paper, we evaluate of the relationship between these resources and the scientific advancement of foundation models (FM). We reviewed 6517 FM papers published between 2022 to 2024, and surveyed 229 first-authors to the impact of computing resources on scientific output. We find that increased computing is correlated with national funding allocations and citations, but our findings don't observe the strong correlations with research environment (academic or industrial), domain, or study methodology. We advise that individuals and institutions focus on creating shared and affordable computing opportunities to lower the entry barrier for under-resourced researchers. These steps can help expand participation in FM research, foster diversity of ideas and contributors, and sustain innovation and progress in AI. The data will be available at: https://mit-calc.csail.mit.edu/ |
| title | The Role of Computing Resources in Publishing Foundation Model Research |
| topic | Computers and Society Artificial Intelligence |
| url | https://arxiv.org/abs/2510.13621 |