The Role of Computing Resources in Publishing Foundation Model Research
Authors: name: Yuexing Hao, name: Yue Huang, name: Haoran Zhang, name: Chenyang Zhao, name: Zhenwen Liang, name: Paul Pu Liang, name: Yue Zhao, name: Lichao Sun, name: Saleh Kalantari, name: Xiangliang Zhang, name: Marzyeh Ghassemi

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/