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  1. themarkup.org

    But your research focuses on something receiving less attention: the secret water footprint of AI technology. Tell us about your findings. Ren: Water footprint has been staying under the radar for various reasons, including the big misperception that freshwater is an "infinite" resource and the relatively lower price tag of water. Many AI ...
  2. hackernoon.com

    But your research focuses on something receiving less attention: the secret water footprint of AI technology. Tell us about your findings. Ren: Water footprint has been staying under the radar for various reasons, including the big misperception that freshwater is an "infinite" resource and the relatively lower price tag of water. Many AI ...
  3. footprint. In this paper, we provide a principled methodology to estimate the water footprint of AI models, and also discuss the unique spatial-temporal diversities of AI models' runtime water efficiency. Finally, we highlight the necessity of holistically addressing water footprint along with carbon footprint to enable truly sustainable AI.
  4. The growing carbon footprint of artificial intelligence (AI) models, especially large ones such as GPT-3, has been undergoing public scrutiny. Unfortunately, however, the equally important and enormous water (withdrawal and consumption) footprint of AI models has remained under the radar. For example, training GPT-3 in Microsoft's state-of-the-art U.S. data centers can directly evaporate ...
  5. thelivinglib.org

    Paper by Shaolei Ren, Pengfei Li, Jianyi Yang, and Mohammad A. Islam: "The growing carbon footprint of artificial intelligence (AI) models, especially large ones such as GPT-3 and GPT-4, has been undergoing public scrutiny. Unfortunately, however, the equally important and enormous water footprint of AI models has remained under the radar. For example, training GPT-3 in Microsoft's state ...
  6. semanticscholar.org

    A principled methodology is provided to estimate the water footprint of AI models, and the unique spatial-temporal diversities ofAI models' runtime water efficiency are discussed, highlighting the necessity of holistically addressing water footprint along with carbon footprint to enable truly sustainable AI. The growing carbon footprint of artificial intelligence (AI) models, especially large ...
  7. Secret Water Footprint of AI Models Pengfei Li UC Riverside Jianyi Yang UC Riverside Mohammad A. Islam UT Arlington Shaolei Ren1 UC Riverside Abstract The growing carbon footprint of artificial intelligence (AI) models, especially large ones such as GPT-3 and GPT-4, has been undergoing public scrutiny. Unfortunately, however, the equally ...
  8. bluefieldresearch.com

    Artificial intelligence (AI) is all the rage these days—but when consumers type a question into ChatGPT, they aren't thinking about water. ChatGPT, a generative AI tool with 1.4 billion site visits in August 2023 alone, uses an estimated quarter of a gallon of water for every 40 to 100 queries it receives, according to a study by UC Riverside .
  9. paperswithcode.com

    Unfortunately, however, the equally important and enormous water (withdrawal and consumption) footprint of AI models has remained under the radar. For example, training GPT-3 in Microsoft's state-of-the-art U.S. data centers can directly evaporate 700,000 liters of clean freshwater, but such information has been kept a secret.
  10. sites.psu.edu

    The Secret Water Footprint of AI Technology - The Markup Published by aec67 on June 9, 2023 For inference (i.e., conversation with ChatGPT), our estimate shows that ChatGPT needs a 500-ml bottle of water for a short conversation of roughly 20 to 50 questions and answers, depending on when and where the model is deployed.
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