/Making-AI-Less-Thirsty

[Preprint] Making AI Less ''Thirsty'': Uncovering and Addressing the Secret Water Footprint of AI

Primary LanguageJupyter NotebookMIT LicenseMIT

Making AI Less ''Thirsty'': Uncovering and Addressing the Secret Water Footprint of AI

MIT licensed arxiv

Pengfei Li, Jianyi Yang, Mohammad A. Islam and Shaolei Ren*

(*corresponding author)

Note

This is the official implementation of the arxiv paper [PDF]

Requirements

  • python>=3.6

Installation

  • Clone this repo:
git clone https://github.com/Ren-Research/Making-AI-Less-Thirsty.git
cd Making-AI-Less-Thirsty
  • Install dependencies:
pip install -r requirements.txt

Results

  • Hourly carbon efficiency and on-site WUE for the first week of August 2022.

snapshot

  • Estimated water and carbon footprints of training LaMDA with different starting months in 2022.

footprint

Citation

@article{ren2023water,
  title={Making AI Less "Thirsty": Uncovering and Addressing the Secret Water Footprint of AI Models},
  author={Li, Pengfei and Yang, Jianyi and Islam, Mohammad A. and Ren, Shaolei},
  journal={arXiv preprint arXiv:2304.03271},
  year={2023}
}

Acknowledgement