The Role of Computing Resources in Publishing Foundation Model Research
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/
68f0515b36f8b025381e18f5
Yuexing Hao
claimed_verified
2025-10-17T04:14:07.673Z
67b879f192b9b5b81873f44a
https://cdn-avatars.huggingface.co/v1/production/uploads/no-auth/Uc4nGPdhPXmHqlRA58bVB.png
Yuexing Hao
user
YuexingHao
68f0515b36f8b025381e18f6
Yue Huang
68f0515b36f8b025381e18f7
Haoran Zhang
68f0515b36f8b025381e18f8
Chenyang Zhao
68f0515b36f8b025381e18f9
Zhenwen Liang
68f0515b36f8b025381e18fa
Paul Pu Liang
68f0515b36f8b025381e18fb
Yue Zhao
68f0515b36f8b025381e18fc
Lichao Sun
68f0515b36f8b025381e18fd
Saleh Kalantari
68f0515b36f8b025381e18fe
Xiangliang Zhang
68f0515b36f8b025381e18ff
Marzyeh Ghassemi
The Role of Computing Resources in Publishing Foundation Model Research
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/
Increased computing resources are correlated with national funding and citations in foundation model research, but not with research environment, domain, or methodology.
foundation models computing resources national funding citations research environment domain study methodology shared computing affordable computing under-resourced researchers diversity of ideas innovation progress in AI