{"id":100195,"date":"2026-07-09T11:17:12","date_gmt":"2026-07-09T11:17:12","guid":{"rendered":"https:\/\/www.europesays.com\/ai\/100195\/"},"modified":"2026-07-09T11:17:12","modified_gmt":"2026-07-09T11:17:12","slug":"strategies-and-design-for-increasing-ai-sustainability","status":"publish","type":"post","link":"https:\/\/www.europesays.com\/ai\/100195\/","title":{"rendered":"Strategies and design for increasing AI sustainability"},"content":{"rendered":"<p class=\"c-article-references__text\" id=\"ref-CR1\">Rolnick, D. et al. Tackling climate change with machine learning. ACM Comput. Surv. 55, 1\u201396 (2022).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 1\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Tackling%20climate%20change%20with%20machine%20learning&amp;journal=ACM%20Comput.%20Surv.&amp;volume=55&amp;pages=1-96&amp;publication_year=2022&amp;author=Rolnick%2CD\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR2\">Villalobos, P. et al. Machine learning model sizes and the parameter gap. Preprint at <a href=\"https:\/\/doi.org\/10.48550\/arXiv.2207.02852\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"10.48550\/arXiv.2207.02852\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/doi.org\/10.48550\/arXiv.2207.02852<\/a> (2022).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR3\">Wu, C.-J., Acun, B., Raghavendra, R. &amp; Hazelwood, K. Beyond efficiency: scaling AI sustainably. IEEE Micro 44, 37\u201346 (2024).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"cas reference\" data-track-action=\"cas reference\" href=\"https:\/\/www.nature.com\/articles\/cas-redirect\/1:CAS:528:DC%2BB2MXitF2ltrvI\" aria-label=\"CAS reference 3\" target=\"_blank\">CAS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 3\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Beyond%20efficiency%3A%20scaling%20AI%20sustainably&amp;journal=IEEE%20Micro&amp;volume=44&amp;pages=37-46&amp;publication_year=2024&amp;author=Wu%2CC-J&amp;author=Acun%2CB&amp;author=Raghavendra%2CR&amp;author=Hazelwood%2CK\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR4\">Powering intelligence: analyzing artificial intelligence and data center energy consumption. White Paper on Technology Innovation Report EPRI <a href=\"https:\/\/www.epri.com\/research\/products\/3002028905\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/www.epri.com\/research\/products\/3002028905\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/www.epri.com\/research\/products\/3002028905<\/a> (2024).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR5\">Davenport, C. et al. AI, data centers and the coming US power demand surge. Equity research report. Goldman Sachs <a href=\"https:\/\/www.goldmansachs.com\/pdfs\/insights\/pages\/generational-growth-ai-data-centers-and-the-coming-us-power-surge\/report.pdf\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/www.goldmansachs.com\/pdfs\/insights\/pages\/generational-growth-ai-data-centers-and-the-coming-us-power-surge\/report.pdf\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/www.goldmansachs.com\/pdfs\/insights\/pages\/generational-growth-ai-data-centers-and-the-coming-us-power-surge\/report.pdf<\/a> (2024).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR6\">O\u2019Donnell, J. &amp; Crownhart, C. We did the math on AI\u2019s energy footprint. Here\u2019s the story you haven\u2019t heard. MIT Technology Review <a href=\"https:\/\/www.technologyreview.com\/2025\/05\/20\/1116327\/ai-energy-usage-climate-footprint-big-tech\/\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/www.technologyreview.com\/2025\/05\/20\/1116327\/ai-energy-usage-climate-footprint-big-tech\/\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/www.technologyreview.com\/2025\/05\/20\/1116327\/ai-energy-usage-climate-footprint-big-tech\/<\/a> (2025).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR7\">Electricity 2024. International Energy Agency <a href=\"https:\/\/www.iea.org\/reports\/electricity-2024\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/www.iea.org\/reports\/electricity-2024\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/www.iea.org\/reports\/electricity-2024<\/a> (2024).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR8\">Shehabi, A. et al. 2024 United States data center energy usage report. LBNL-2001637 Lawrence Berkeley National Laboratory <a href=\"https:\/\/escholarship.org\/uc\/item\/32d6m0d1\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/escholarship.org\/uc\/item\/32d6m0d1\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/escholarship.org\/uc\/item\/32d6m0d1<\/a> (2024).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR9\">2024 environmental report. Google <a href=\"https:\/\/sustainability.google\/reports\/google-2024-environmental-report\/\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/sustainability.google\/reports\/google-2024-environmental-report\/\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/sustainability.google\/reports\/google-2024-environmental-report\/<\/a> (2024).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR10\">Li, P., Yang, J., Islam, M. A. &amp; Ren, S. Making AI less \u201cthirsty\u201d: uncovering and addressing the secret water footprint of AI models. Commun. ACM 68, 54\u201361 (2025).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 10\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Making%20AI%20less%20%E2%80%9Cthirsty%E2%80%9D%3A%20uncovering%20and%20addressing%20the%20secret%20water%20footprint%20of%20AI%20models&amp;journal=Commun.%20ACM&amp;volume=68&amp;pages=54-61&amp;publication_year=2025&amp;author=Li%2CP&amp;author=Yang%2CJ&amp;author=Islam%2CMA&amp;author=Ren%2CS\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR11\">Chien, A. A., Zhang, C. &amp; Lin, L. Beyond PUE: flexible datacenters empowering the cloud to decarbonize. In Workshop on Sustainable Computer Systems 2022 USENIX HotCarbon <a href=\"https:\/\/par.nsf.gov\/biblio\/10400420\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/par.nsf.gov\/biblio\/10400420\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/par.nsf.gov\/biblio\/10400420<\/a> (USENIX, 2022).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR12\">Tomlinson, B., Torrance, A. W. &amp; Ripple, W. J. Scientists\u2019 warning on technology. J. Clean. Prod. 434, 140074 (2024).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 12\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Scientists%E2%80%99%20warning%20on%20technology&amp;journal=J.%20Clean.%20Prod.&amp;volume=434&amp;publication_year=2024&amp;author=Tomlinson%2CB&amp;author=Torrance%2CAW&amp;author=Ripple%2CWJ\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR13\">Wang, J. et al. Designing cloud servers for lower carbon. In Proc. 51st Ann. Int. Symp. Computer Architecture (ISCA \u201824) (ACM\/IEEE, 2024).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR14\">Virginia electricity profile 2024. United States Energy Information Administration <a href=\"https:\/\/sustainability.google\/reports\/google-2024-environmental-report\/\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/sustainability.google\/reports\/google-2024-environmental-report\/\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/www.eia.gov\/electricity\/state\/virginia\/<\/a> (2025).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR15\">Gupta, U. et al. Chasing carbon: the elusive environmental footprint of computing. IEEE Micro 42, 37\u201347 (2022).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 15\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Chasing%20carbon%3A%20the%20elusive%20environmental%20footprint%20of%20computing&amp;journal=IEEE%20Micro&amp;volume=42&amp;pages=37-47&amp;publication_year=2022&amp;author=Gupta%2CU\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR16\">Xiao, T., Nerini, F. F., Matthews, H. D., Tavoni, M. &amp; You, F. Environmental impact and net-zero pathways for sustainable artificial intelligence servers in the USA. Nat. Sustain. 8, 1541\u20131553 (2025).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 16\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Environmental%20impact%20and%20net-zero%20pathways%20for%20sustainable%20artificial%20intelligence%20servers%20in%20the%20USA&amp;journal=Nat.%20Sustain&amp;volume=8&amp;pages=1541-1553&amp;publication_year=2025&amp;author=Xiao%2CT&amp;author=Nerini%2CFF&amp;author=Matthews%2CHD&amp;author=Tavoni%2CM&amp;author=You%2CF\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR17\">Energy and AI. International Energy Agency <a href=\"https:\/\/www.iea.org\/reports\/energy-and-ai\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/www.iea.org\/reports\/energy-and-ai\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/www.iea.org\/reports\/energy-and-ai<\/a> (2025).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR18\">Rivera, M. B., H\u00e5kansson, C., Svenfelt, \u00c5 &amp; Finnveden, G. Including second order effects in environmental assessments of ICT. Environ. Model. Softw. 56, 105\u2013115 (2014). This is a thematic issue on modelling and evaluating the sustainability of smart solutions.<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 18\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Including%20second%20order%20effects%20in%20environmental%20assessments%20of%20ICT&amp;journal=Environ.%20Model.%20Softw.&amp;volume=56&amp;pages=105-115&amp;publication_year=2014&amp;author=Rivera%2CMB&amp;author=H%C3%A5kansson%2CC&amp;author=Svenfelt%2C%C3%85&amp;author=Finnveden%2CG\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR19\">K\u00f6hler, A. &amp; Erdmann, L. Expected environmental impacts of pervasive computing. Hum. Ecol. Risk Assess. 10, 831\u2013852 (2004).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 19\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Expected%20environmental%20impacts%20of%20pervasive%20computing&amp;journal=Hum.%20Ecol.%20Risk%20Assess&amp;volume=10&amp;pages=831-852&amp;publication_year=2004&amp;author=K%C3%B6hler%2CA&amp;author=Erdmann%2CL\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR20\">Zhao, W. X. et al. A survey of large language models. Front. Comput. Sci. 20, 2012627 (2026).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"cas reference\" data-track-action=\"cas reference\" href=\"https:\/\/www.nature.com\/articles\/cas-redirect\/1:CAS:528:DC%2BB28XhtFynsbrF\" aria-label=\"CAS reference 20\" target=\"_blank\">CAS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 20\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=A%20survey%20of%20large%20language%20models&amp;journal=Front.%20Comput.%20Sci.&amp;volume=20&amp;publication_year=2026&amp;author=Zhao%2CWX\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR21\">Gomes, C. et al. Computational sustainability: computing for a better world and a sustainable future. Commun. ACM 62, 56\u201365 (2019).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 21\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Computational%20sustainability%3A%20computing%20for%20a%20better%20world%20and%20a%20sustainable%20future&amp;journal=Commun.%20ACM&amp;volume=62&amp;pages=56-65&amp;publication_year=2019&amp;author=Gomes%2CC\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR22\">Chien, A. A. et al. Reducing the carbon impact of generative AI inference (today and in 2035). ACM SIGENERGY Energy Inform. Rev. 4, 65\u201372 (2024).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 22\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Reducing%20the%20carbon%20impact%20of%20generative%20AI%20inference%20%28today%20and%20in%202035%29&amp;journal=ACM%20SIGENERGY%20Energy%20Inform.%20Rev.&amp;volume=4&amp;pages=65-72&amp;publication_year=2024&amp;author=Chien%2CAA\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR23\">Lechowicz, A. et al. Online conversion with switching costs: robust and learning-augmented algorithms. SIGMETRICS Perform. Eval. Rev. 52, 45\u201346 (2024).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 23\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Online%20conversion%20with%20switching%20costs%3A%20robust%20and%20learning-augmented%20algorithms&amp;journal=SIGMETRICS%20Perform.%20Eval.%20Rev.&amp;volume=52&amp;pages=45-46&amp;publication_year=2024&amp;author=Lechowicz%2CA\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR24\">Brown, T. et al. Language models are few-shot learners. In Advances in Neural Information Processing Systems (NIPS \u201920) (eds Larochelle, H. et al.) Vol. 33, 1877\u20131901 (Curran Associates, 2020).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR25\">Gerke, B. F. et al. The California demand response potential study, phase 4: report on shed and shift resources through 2050. Lawrence Berkeley National Laboratory <a href=\"https:\/\/eta-publications.lbl.gov\/sites\/default\/files\/phase_4_dr_potential_study_final_2024-05-21.pdf\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/eta-publications.lbl.gov\/sites\/default\/files\/phase_4_dr_potential_study_final_2024-05-21.pdf\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/eta-publications.lbl.gov\/sites\/default\/files\/phase_4_dr_potential_study_final_2024-05-21.pdf<\/a> (2024).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR26\">Crafts, N. Artificial intelligence as a general-purpose technology: an historical perspective. Oxford Rev. Econ. Policy 37, 521\u2013536 (2021).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 26\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Artificial%20intelligence%20as%20a%20general-purpose%20technology%3A%20an%20historical%20perspective&amp;journal=Oxford%20Rev.%20Econ.%20Policy&amp;volume=37&amp;pages=521-536&amp;publication_year=2021&amp;author=Crafts%2CN\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR27\">Bahoo, S., Cucculelli, M. &amp; Qamar, D. Artificial intelligence and corporate innovation: a review and research agenda. Technol. Forecast. Social Change 188, 122264 (2023).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 27\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Artificial%20intelligence%20and%20corporate%20innovation%3A%20a%20review%20and%20research%20agenda&amp;journal=Technol.%20Forecast.%20Social%20Change&amp;volume=188&amp;publication_year=2023&amp;author=Bahoo%2CS&amp;author=Cucculelli%2CM&amp;author=Qamar%2CD\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR28\">Intergovernmental Panel on Climate Change (IPCC). Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (Cambridge Univ. Press, 2021).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR29\">Wu, C.-J. et al. Sustainable AI: environmental implications, challenges and opportunities. In Proc. 5th MLSys Conf. <a href=\"https:\/\/proceedings.mlsys.org\/paper_files\/paper\/2022\/file\/462211f67c7d858f663355eff93b745e-Paper.pdf\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/proceedings.mlsys.org\/paper_files\/paper\/2022\/file\/462211f67c7d858f663355eff93b745e-Paper.pdf\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/proceedings.mlsys.org\/paper_files\/paper\/2022\/file\/462211f67c7d858f663355eff93b745e-Paper.pdf<\/a> (2022).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR30\">Patterson, D. et al. The carbon footprint of machine learning training will plateau, then shrink. Computer 55, 18\u201328 (2022).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 30\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=The%20carbon%20footprint%20of%20machine%20learning%20training%20will%20plateau%2C%20then%20shrink&amp;journal=Computer&amp;volume=55&amp;pages=18-28&amp;publication_year=2022&amp;author=Patterson%2CD\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR31\">Gupta, U. et al. ACT: designing sustainable computer systems with an architectural carbon modeling tool. In Proc. 49th Ann. Int. Symp. Computer Architecture (ISCA \u201822) (eds Salapura, V. et al.) 784\u2013799 (ACM\/IEEE, 2022).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR32\">Han, L., Kakadia, J., Lee, B. C. &amp; Gupta, U. Fair-CO2: fair attribution for cloud carbon emissions. In Proc. 52nd Ann. Int. Symp. Computer Architecture (ISCA \u201825) 646\u2013663 (ACM\/IEEE, 2025).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR33\">Lisa Li, Y. et al. Fair, practical, and efficient carbon accounting for LLM serving. SIGMETRICS Perform. Eval. Rev. 53, 99\u2013103 (2025).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 33\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Fair%2C%20practical%2C%20and%20efficient%20carbon%20accounting%20for%20LLM%20serving&amp;journal=SIGMETRICS%20Perform.%20Eval.%20Rev.&amp;volume=53&amp;pages=99-103&amp;publication_year=2025&amp;author=Lisa%20Li%2CY\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR34\">Han, L., Lisa Li, Y. &amp; Gupta, U. Metrics for data center embodied carbon. SIGMETRICS Perform. Eval. Rev. 53, 90\u201392 (2025).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 34\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Metrics%20for%20data%20center%20embodied%20carbon&amp;journal=SIGMETRICS%20Perform.%20Eval.%20Rev.&amp;volume=53&amp;pages=90-92&amp;publication_year=2025&amp;author=Han%2CL&amp;author=Lisa%20Li%2CY&amp;author=Gupta%2CU\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR35\">Lee, B. C. et al. A view of the sustainable computing landscape. Patterns 6, 101296 (2025).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 35\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=A%20view%20of%20the%20sustainable%20computing%20landscape&amp;journal=Patterns&amp;volume=6&amp;publication_year=2025&amp;author=Lee%2CBC\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR36\">Kline, D. et al. GreenChip: a tool for evaluating holistic sustainability of modern computing systems. Sustain. Comput. Inform. Syst. 22, 322\u2013332 (2019).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 36\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=GreenChip%3A%20a%20tool%20for%20evaluating%20holistic%20sustainability%20of%20modern%20computing%20systems&amp;journal=Sustain.%20Comput.%20Inform.%20Syst.&amp;volume=22&amp;pages=322-332&amp;publication_year=2019&amp;author=Kline%2CD\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR37\">Eeckhout, L. Focal: A first-order carbon model to assess processor sustainability. In Proc. 29th ACM Int. Conf. Architectural Support for Programming Languages and Operating Systems (ASPLOS \u201924) (eds Abu-Ghazaleh, N. et al.) Vol. 2, 401\u2013415 (ACM, 2024).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR38\">GreenSKU-Model. GitHub <a href=\"https:\/\/github.com\/Azure\/AzurePublicDataset\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/github.com\/Azure\/AzurePublicDataset\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/github.com\/Azure\/AzurePublicDataset<\/a> (2026).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR39\">Li, S. et al. McPAT: an integrated power, area, and timing modeling framework for multicore and manycore architectures. In Proc. 42nd Ann. Int. Symp. Microarchitecture (MICRO 42) 469\u2013480 (ACM\/IEEE, 2009).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR40\">Binkert, N. et al. The gem5 simulator. SIGARCH Comput. Archit. News 39, 1\u20137 (2011).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 40\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=The%20gem5%20simulator&amp;journal=SIGARCH%20Comput.%20Archit.%20News&amp;volume=39&amp;pages=1-7&amp;publication_year=2011&amp;author=Binkert%2CN\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR41\">Li, S., Chen, K., Ahn, J. H., Brockman, J. B. &amp; Jouppi, N. P. CACTI-P: architecture-level modeling for SRAM-based structures with advanced leakage reduction techniques. In Int. Conf. Computer-Aided Design (ICCAD) 694\u2013701 (ACM\/IEEE, 2011).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR42\">Garcia Bardon, M. et al. DTCO including sustainability: power\u2013performance\u2013area\u2013cost\u2013environmental score (PPACE) analysis for logic technologies. In Proc. Int. Electron Devices Meeting (IEDM) 41.4.1\u201341.4.4 (IEEE, 2020).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR43\">Tannu, S. &amp; Nair, P. J. The dirty secret of SSDs: embodied carbon. SIGENERGY Energy Inform. Rev. 3, 4\u20139 (2022).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 43\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=The%20dirty%20secret%20of%20SSDs%3A%20embodied%20carbon&amp;journal=SIGENERGY%20Energy%20Inform.%20Rev.&amp;volume=3&amp;pages=4-9&amp;publication_year=2022&amp;author=Tannu%2CS&amp;author=Nair%2CPJ\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR44\">Sudarshan, C. C., Matkar, N., Vrudhula, S., Sapatnekar, S. S. &amp; Chhabria, V. A. ECO-CHIP: estimation of carbon footprint of chiplet-based architectures for sustainable VLSI. In Int. Symp. High-Performance Computer Architecture (HPCA) 671\u2013685 (IEEE, 2024).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR45\">Zhao, Y., Zhao, Y. K., Wan, C. &amp; Lin, Y. C. 3D-carbon: an analytical carbon modeling tool for 3D and 2.5D integrated circuits. In Proc. 61st Design Automation Conf. (DAC \u201924) (ACM\/IEEE, 2024).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR46\">Acun, B. et al. Carbon Explorer: a holistic approach for designing carbon aware datacenters. In Proc. 28th Int. Conf. Architectural Support for Programming Languages and Operating Systems 118\u2013132 (ACM, 2023).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR47\">Li, Y. et al. Ecoserve: designing carbon-aware AI inference systems. Preprint at <a href=\"https:\/\/doi.org\/10.48550\/arXiv.2502.05043\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"10.48550\/arXiv.2502.05043\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/doi.org\/10.48550\/arXiv.2502.05043<\/a> (2025).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR48\">IMEC netzero virtual fab. IMEC <a href=\"https:\/\/netzero.imec-int.com\/\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/netzero.imec-int.com\/\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/netzero.imec-int.com\/<\/a> (2024).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR49\">Falk, S. et al. More than carbon: cradle-to-grave environmental impacts of GenAI training on the Nvidia A100 GPU. Environ. Impact Assess. Rev. 121, 108525 (2026).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 49\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=More%20than%20carbon%3A%20cradle-to-grave%20environmental%20impacts%20of%20GenAI%20training%20on%20the%20Nvidia%20A100%20GPU&amp;journal=Environ.%20Impact%20Assess.%20Rev.&amp;volume=121&amp;publication_year=2026&amp;author=Falk%2CS\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR50\">Chen, X., Han, L., Bhagavathula, A. &amp; Gupta, U. CarbonClarity: understanding and addressing uncertainty in embodied carbon for sustainable computing. In Proc. Int. Conf. Computer Aided Design (ICCAD) 1\u20139 (ACM\/IEEE, 2025).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR51\">Bhagavathula, A., Han, L. &amp; Gupta, U. Understanding the implications of uncertainty in embodied carbon models for sustainable computing. HotCarbon <a href=\"https:\/\/hotcarbon.org\/assets\/2024\/pdf\/hotcarbon24-final146.pdf\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/hotcarbon.org\/assets\/2024\/pdf\/hotcarbon24-final146.pdf\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/hotcarbon.org\/assets\/2024\/pdf\/hotcarbon24-final146.pdf<\/a> (2024).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR52\">Ning, A., Tziantzioulis, G. &amp; Wentzlaff, D. Supply chain aware computer architecture. In Proc. 50th Ann. Int. Symp. Computer Architecture (ISCA \u201923) 17 (ACM\/IEEE, 2023).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR53\">Elsworth, C. et al. Measuring the environmental impact of delivering AI at Google scale. Preprint at <a href=\"https:\/\/doi.org\/10.48550\/arXiv.2508.15734\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"10.48550\/arXiv.2508.15734\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/doi.org\/10.48550\/arXiv.2508.15734<\/a> (2025).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR54\">Chung, J.-W. et al. The ML.ENERGY Benchmark: Toward Automated Inference Energy Measurement and Optimization. In Advances in Neural Information Processing Systems 38 (NeurIPS, 2025).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR55\">Schneider, I. et al. An introduction to life-cycle emissions of AI hardware. IEEE Micro 45, 9\u201319 (2025).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 55\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=An%20introduction%20to%20life-cycle%20emissions%20of%20AI%20hardware&amp;journal=IEEE%20Micro&amp;volume=45&amp;pages=9-19&amp;publication_year=2025&amp;author=Schneider%2CI\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR56\">Schneider, I. et al. An Introduction to Life-Cycle Emissions of Artificial Intelligence Hardware. IEEE Micro 45, 10\u201322 (2025).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 56\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=An%20Introduction%20to%20Life-Cycle%20Emissions%20of%20Artificial%20Intelligence%20Hardware&amp;journal=IEEE%20Micro&amp;volume=45&amp;pages=10-22&amp;publication_year=2025&amp;author=Schneider%2CI\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR57\">Luccioni, S., Jernite, Y. &amp; Strubell, E. Power hungry processing: watts driving the cost of AI deployment? In Proc. Conf. Fairness, Accountability, and Transparency 85\u201399 (ACM, 2024).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR58\">Morrison, J. et al. Holistically evaluating the environmental impact of creating language models. Preprint at <a href=\"https:\/\/doi.org\/10.48550\/arXiv.2503.05804\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"10.48550\/arXiv.2503.05804\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/doi.org\/10.48550\/arXiv.2503.05804<\/a> (2025).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR59\">Patterson, D. et al. Recovery-oriented computing (ROC): motivation, definition, techniques, and case studies. Technical Report. ACM Digital Library <a href=\"https:\/\/dl.acm.org\/doi\/10.5555\/894137\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/dl.acm.org\/doi\/10.5555\/894137\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/dl.acm.org\/doi\/10.5555\/894137<\/a> (2002).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR60\">Patterson, D. et al. Carbon emissions and large neural network training. Preprint at <a href=\"https:\/\/doi.org\/10.48550\/arXiv.2104.10350\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"10.48550\/arXiv.2104.10350\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/doi.org\/10.48550\/arXiv.2104.10350<\/a> (2021).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR61\">Wang, J. STAR-Research: GreenSKU-Model: ISCA artifact. Zenodo <a href=\"https:\/\/doi.org\/10.5281\/zenodo.10896255\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"10.5281\/zenodo.10896255\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/doi.org\/10.5281\/zenodo.10896255<\/a> (2024).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR62\">Tomlinson, B., Black, R. W., Patterson, D. J. &amp; Torrance, A. W. The carbon emissions of writing and illustrating are lower for AI than for humans. Sci. Rep. 14, 3732 (2024).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"cas reference\" data-track-action=\"cas reference\" href=\"https:\/\/www.nature.com\/articles\/cas-redirect\/1:CAS:528:DC%2BB2cXksVWlt7c%3D\" aria-label=\"CAS reference 62\" target=\"_blank\">CAS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 62\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=The%20carbon%20emissions%20of%20writing%20and%20illustrating%20are%20lower%20for%20AI%20than%20for%20humans&amp;journal=Sci.%20Rep.&amp;volume=14&amp;publication_year=2024&amp;author=Tomlinson%2CB&amp;author=Black%2CRW&amp;author=Patterson%2CDJ&amp;author=Torrance%2CAW\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR63\">Ren, S., Tomlinson, B., Black, R. W. &amp; Torrance, A. W. Reconciling the contrasting narratives on the environmental impact of large language models. Sci. Rep. 14, 26310 (2024).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"cas reference\" data-track-action=\"cas reference\" href=\"https:\/\/www.nature.com\/articles\/cas-redirect\/1:CAS:528:DC%2BB2cXisVSlu7jI\" aria-label=\"CAS reference 63\" target=\"_blank\">CAS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 63\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Reconciling%20the%20contrasting%20narratives%20on%20the%20environmental%20impact%20of%20large%20language%20models&amp;journal=Sci.%20Rep.&amp;volume=14&amp;publication_year=2024&amp;author=Ren%2CS&amp;author=Tomlinson%2CB&amp;author=Black%2CRW&amp;author=Torrance%2CAW\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR64\">Panteleaki, A. M. et al. Carbon-Efficient 3D DNN Acceleration: Optimizing Performance and Sustainability. In Proc. 2025 IEEE Computer Society Annual Symposium on VLSI 1\u20136 (IEEE, 2025).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR65\">Fayza, F. et al. Photonics for sustainable AI. Commun. Phys. 8, 403 (2025).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 65\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Photonics%20for%20sustainable%20AI&amp;journal=Commun.%20Phys.&amp;volume=8&amp;publication_year=2025&amp;author=Fayza%2CF\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR66\">Elgamal, M. et al. Cordoba: carbon-efficient optimization framework for computing systems. In 31st Int. Symp. High-Performance Computer Architecture (HPCA) 1289\u20131303 (IEEE, 2025).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR67\">Byun, H. J., Gupta, U. &amp; Seo, J.-S. 3D IC architecture evaluation and optimization with digital compute-in-memory designs. In Proc. 29th Int. Symp. Low Power Electronics and Design 1\u20136 (ACM\/IEEE, 2024).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR68\">Byun, H. J., Gupta, U. &amp; Seo, J.-S. Energy-\/carbon-aware evaluation and optimization of 3D IC architecture with digital compute-in-memory designs. IEEE J. Explor. Solid-State Comput. Devices Circuits 10, 98\u2013106 (2024).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 68\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Energy-%2Fcarbon-aware%20evaluation%20and%20optimization%20of%203D%20IC%20architecture%20with%20digital%20compute-in-memory%20designs&amp;journal=IEEE%20J.%20Explor.%20Solid-State%20Comput.%20Devices%20Circuits&amp;volume=10&amp;pages=98-106&amp;publication_year=2024&amp;author=Byun%2CHJ&amp;author=Gupta%2CU&amp;author=Seo%2CJ-S\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR69\">Fayza, F. et al. Epicarbon: a carbon modeling tool for electro-photonic accelerators. In Proc. Int. Conf. Computer-aided Design 1\u20139 (IEEE, 2025).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR70\">Wu, H. et al. COFFEE: a carbon-modeling and optimization framework for HZO-based FeFET eNVMs. Preprint at <a href=\"https:\/\/doi.org\/10.48550\/arXiv.2602.05018\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"10.48550\/arXiv.2602.05018\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/doi.org\/10.48550\/arXiv.2602.05018<\/a> (2026).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR71\">Software carbon intensity (SCI) specification. Green Software Foundation <a href=\"https:\/\/sci.greensoftware.foundation\/\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/sci.greensoftware.foundation\/\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/sci.greensoftware.foundation\/<\/a> (2024).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR72\">Gao, J., Wang, H. &amp; Shen, H. Smartly handling renewable energy instability in supporting a cloud datacenter. In Proc. Int. Parallel and Distributed Processing Symp. 769\u2013778 (IEEE, 2020).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR73\">Chen, G. et al. Energy-aware server provisioning and load dispatching for connection-intensive internet services. In Proc. 5th USENIX Symp. Networked Systems Design and Implementation (NSDI \u201808) 337\u2013350 (USENIX Association, 2008).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR74\">Delimitrou, C. &amp; Kozyrakis, C. Quasar: resource-efficient and QoS-aware cluster management. In Proc. 19th Int. Conf. Architectural Support for Programming Languages and Operating Systems (ASPLOS \u201814) 127\u2013144 (ACM, 2014).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR75\">Wu, Q. et al. Dynamo: Facebook\u2019s data center-wide power management system. ACM SIGARCH Computer Architecture News 44, 469\u2013480 (2016).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 75\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Dynamo%3A%20Facebook%E2%80%99s%20data%20center-wide%20power%20management%20system&amp;journal=ACM%20SIGARCH%20Computer%20Architecture%20News&amp;volume=44&amp;pages=469-480&amp;publication_year=2016&amp;author=Wu%2CQ\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR76\">Urgaonkar, R., Kozat, U. C., Igarashi, K. &amp; Neely, M. J. Dynamic resource allocation and power management in virtualized data centers. In Proc. Network Operations and Management Symp. (NOMS 2010) 479\u2013486 (IEEE, 2010).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR77\">Kumbhare, A. G. et al. Prediction-Based Power Oversubscription in Cloud Platforms. In Proc. 2021 USENIX Annual Technical Conference 473\u2013487 (USENIX Association, 2021).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR78\">Zhang, C. et al. Flex: high-availability datacenters with zero reserved power. In Int. Symp. Computer Architecture (ISCA) 319\u2013332 (ACM\/IEEE, 2021).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR79\">Patel, P. et al. Towards improved power management in cloud GPUs. Comput. Arch. Lett. 22, 141\u2013144 (2023).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 79\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Towards%20improved%20power%20management%20in%20cloud%20GPUs&amp;journal=Comput.%20Arch.%20Lett.&amp;volume=22&amp;pages=141-144&amp;publication_year=2023&amp;author=Patel%2CP\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR80\">Lyu, J. et al. Myths and misconceptions around reducing carbon embedded in cloud platforms. In Proc. 2nd Worksh. Sustainable Computer Systems (HotCarbon \u201823) 7 (ACM, 2023).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR81\">Zhao, J. et al. Galore: memory-efficient LLM training by gradient low-rank projection. In Proc. 41st Int. Conf. Mach. Learn. (ICML\u201924) (eds Salakhutdinov, R. et al.) 2528 (JMLR, 2024).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR82\">Abdin, M. et al. Phi-3 technical report: a highly capable language model locally on your phone. Preprint at <a href=\"https:\/\/doi.org\/10.48550\/arXiv.2404.14219\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"10.48550\/arXiv.2404.14219\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/doi.org\/10.48550\/arXiv.2404.14219<\/a> (2024).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR83\">Mazumder, M. et al. Dataperf: benchmarks for data-centric AI development. In Proc. 37th Int. Conf. Advances in Neural Information Processing Systems (NIPS \u201923) (eds Oh, A. et al.) 235 (Curran Associates, 2023).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR84\">Griggs, T. et al. M\u00e9lange: cost efficient large language model serving by exploiting GPU heterogeneity. Preprint at <a href=\"https:\/\/doi.org\/10.48550\/arXiv.2404.14527\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"10.48550\/arXiv.2404.14527\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/doi.org\/10.48550\/arXiv.2404.14527<\/a> (2024).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR85\">Patel, P. et al. Splitwise: efficient generative LLM inference using phase splitting. In Proc. 51st Ann. Int. Symp. Computer Architecture (ISCA) 118\u2013132 (ACM\/IEEE, 2024).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR86\">Li, Y. L., Graif, O. &amp; Gupta, U. Towards carbon-efficient LLM life cycle. In Proc. 3rd Workshop Sustain. Comput. Syst. (HotCarbon \u201824) (ACM, 2024).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR87\">Naffziger, S. et al. Pioneering chiplet technology and design for the amd epyc\u2122 and ryzen\u2122 processor families: industrial product. In 48th Ann. Int. Symp. Computer Architecture (ISCA) 57\u201370 (ACM\/IEEE, 2021).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR88\">Pentecost, L. et al. Maxnvm: maximizing dnn storage density and inference efficiency with sparse encoding and error mitigation. In Proc. 52nd Ann. Int. Symp. Microarchitecture (MICRO \u201952) 769\u2013781 (ACM\/IEEE, 2019).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR89\">Cortez, E. et al. Resource central: understanding and predicting workloads for improved resource management in large cloud platforms. In Symp. Operating Systems Principles <a href=\"https:\/\/doi.org\/10.1145\/3132747.3132772\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"10.1145\/3132747.3132772\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/doi.org\/10.1145\/3132747.3132772<\/a> (ACM, 2017).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR90\">Connatser, M. AMD adds 128-core Bergamo and 3D V-Cache Genoa CPUs to Zen 4 Epyc lineup. XDA <a href=\"https:\/\/www.xda-developers.com\/amd-128-core-bergame-genoa-epyc-cpu\/\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/www.xda-developers.com\/amd-128-core-bergame-genoa-epyc-cpu\/\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/www.xda-developers.com\/amd-128-core-bergame-genoa-epyc-cpu\/<\/a> (2023).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR91\">Sharma, D. D., Blankenship, R. &amp; Berger, D. S. An Introduction to the Compute Express Link (CXL) interconnect. ACM Comput. Surv. 56, 290 (2024).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 91\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=An%20Introduction%20to%20the%20Compute%20Express%20Link%20%28CXL%29%20interconnect&amp;journal=ACM%20Comput.%20Surv.&amp;volume=56&amp;publication_year=2024&amp;author=Sharma%2CDD&amp;author=Blankenship%2CR&amp;author=Berger%2CDS\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR92\">Larabel, M. AMD EPYC 9754 Benchmarks For The 128-Core Bergamo Review. phoronix <a href=\"https:\/\/www.phoronix.com\/review\/amd-epyc-9754-bergamo\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/www.phoronix.com\/review\/amd-epyc-9754-bergamo\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/www.phoronix.com\/review\/amd-epyc-9754-bergamo<\/a> (2023).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR93\">Long term reliability assessment, january 2026. Tech. Rep. North American Electric Reliability Corporation <a href=\"https:\/\/www.nerc.com\/globalassets\/our-work\/assessments\/nerc_ltra_2025.pdf\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/www.nerc.com\/globalassets\/our-work\/assessments\/nerc_ltra_2025.pdf\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/www.nerc.com\/globalassets\/our-work\/assessments\/nerc_ltra_2025.pdf<\/a> (2026).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR94\">FERC directs nation\u2019s largest grid operator to create new rules to embrace innovation and protect consumers. FERC (2025).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR95\">Mills, D. Board decisional letter on critical issue fast path \u2014 large load additions. PJM <a href=\"https:\/\/www.pjm.com\/-\/media\/DotCom\/about-pjm\/who-we-are\/public-disclosures\/2026\/20260116-pjm-board-letter-re-results-of-the-cifp-process-large-load-additions.pdf\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/www.pjm.com\/-\/media\/DotCom\/about-pjm\/who-we-are\/public-disclosures\/2026\/20260116-pjm-board-letter-re-results-of-the-cifp-process-large-load-additions.pdf\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/www.pjm.com\/-\/media\/DotCom\/about-pjm\/who-we-are\/public-disclosures\/2026\/20260116-pjm-board-letter-re-results-of-the-cifp-process-large-load-additions.pdf<\/a> (2026).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR96\">Ebeed, M., Kamel, S. &amp; Jurado, F. In Classical and Recent Aspects of Power System Optimization (eds Zobaa, A. F., Abdel Aleem, S. H. &amp; Abdelaziz, A. Y.) Ch. 7, 157\u2013183 (Academic, 2018).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR97\">Greatest engineering accomplishments of the 20th century. NAE <a href=\"http:\/\/www.greatachievements.org\/\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"http:\/\/www.greatachievements.org\/\" rel=\"nofollow noopener\" target=\"_blank\">http:\/\/www.greatachievements.org\/<\/a> (2006).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR98\">Monthly outlook for resource adequacy (MORA) reporting month: July 2026. ERCOT <a href=\"https:\/\/www.ercot.com\/files\/docs\/2026\/05\/01\/MORA_July2026.pdf\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/www.ercot.com\/files\/docs\/2026\/05\/01\/MORA_July2026.pdf\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/www.ercot.com\/files\/docs\/2026\/05\/01\/MORA_July2026.pdf<\/a> (2026).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR99\">Miso business process manual manual no. 011 business practices manual resource adequacy. MISO <a href=\"https:\/\/cdn.misoenergy.org\/BPM-011%20Resource%20Adequacy110405.zip?v=20260311160104\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/cdn.misoenergy.org\/BPM-011%20Resource%20Adequacy110405.zip?v=20260311160104\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/cdn.misoenergy.org\/BPM-011%20Resource%20Adequacy110405.zip?v=20260311160104<\/a> (2023).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR100\">CAISO. Monthly renewables performance reports 2026. California ISO <a href=\"https:\/\/www.caiso.com\/library\/monthly-renewables-performance-reports-2026\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/www.caiso.com\/library\/monthly-renewables-performance-reports-2026\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/www.caiso.com\/library\/monthly-renewables-performance-reports-2026<\/a> (2026).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR101\">Wiser, R. H., Mills, A. D., Seel, J., Levin, T. &amp; Botterud, A. Impacts of variable renewable energy on bulk power system assets, pricing, and costs. Tech. Rep. LBNL-2001082 (Lawrence Berkeley National Laboratory, 2017).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR102\">Chien, A. A. Characterizing opportunity power in the California Independent System Operator (CAISO) in years 2015-2017. Energy Earth Sci. 3, 2 (2020).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 102\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Characterizing%20opportunity%20power%20in%20the%20California%20Independent%20System%20Operator%20%28CAISO%29%20in%20years%202015-2017&amp;journal=Energy%20Earth%20Sci.&amp;volume=3&amp;publication_year=2020&amp;author=Chien%2CAA\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR103\">Real time daily market watch, real-time market, march 15, 2026. California ISO <a href=\"https:\/\/www.caiso.com\/documents\/real-time-daily-market-watch-mar-15-2026.html\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/www.caiso.com\/documents\/real-time-daily-market-watch-mar-15-2026.html\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/www.caiso.com\/documents\/real-time-daily-market-watch-mar-15-2026.html<\/a> (2026).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR104\">Millstein, D., O\u2019Shaughnessy, E. &amp; Wiser, R. Exploring wholesale energy price trends the renewables and wholesale electricity prices (REWEP) tool, version 2024. Berkeley Lab <a href=\"https:\/\/emp.lbl.gov\/renewables-and-wholesale-electricity-prices-rewep\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/emp.lbl.gov\/renewables-and-wholesale-electricity-prices-rewep\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/emp.lbl.gov\/renewables-and-wholesale-electricity-prices-rewep<\/a> (2024).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR105\">Chien, A. A. &amp; Lin, L. As grids reach 100% renewable at peak, growing curtailment of 8 gigawatts looms as a challenge to decarbonization. SIGENERGY Energy Inform. Rev. 4, 3\u201310 (2024).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 105\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=As%20grids%20reach%20100%25%20renewable%20at%20peak%2C%20growing%20curtailment%20of%208%20gigawatts%20looms%20as%20a%20challenge%20to%20decarbonization&amp;journal=SIGENERGY%20Energy%20Inform.%20Rev.&amp;volume=4&amp;pages=3-10&amp;publication_year=2024&amp;author=Chien%2CAA&amp;author=Lin%2CL\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR106\">Acun, B. et al. Unlocking the potential of renewable energy through curtailment prediction. In Climate Change AI Workshop at NeurIPS 2023 123 (2023).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR107\">2023 special report on battery storage. CAISO <a href=\"https:\/\/www.caiso.com\/documents\/2023-special-report-on-battery-storage-jul-16-2024.pdf\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/www.caiso.com\/documents\/2023-special-report-on-battery-storage-jul-16-2024.pdf\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/www.caiso.com\/documents\/2023-special-report-on-battery-storage-jul-16-2024.pdf<\/a> (2024).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR108\">Gerke, B. F. et al. The California demand response potential study, phase 3: final report on the shift resource through 2030. Lawrence Berkeley National Laboratory <a href=\"https:\/\/doi.org\/10.20357\/B7MS40\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"10.20357\/B7MS40\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/doi.org\/10.20357\/B7MS40<\/a> (2020).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR109\">Yang, F. &amp; Chien, A. A. ZCCloud: exploring wasted green power for high-performance computing. In Int. Parallel and Distributed Processing Symp. (IPDPS) 1051\u20131060 (IEEE, 2016).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR110\">Yang, F. &amp; Chien, A. A. Large-scale and extreme-scale computing with stranded green power: opportunities and costs. IEEE Trans. Parallel and Distributed Systems 29, 1103\u20131116 (2017).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 110\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Large-scale%20and%20extreme-scale%20computing%20with%20stranded%20green%20power%3A%20opportunities%20and%20costs&amp;journal=IEEE%20Trans.%20Parallel%20and%20Distributed%20Systems&amp;volume=60&amp;pages=1103-1116&amp;publication_year=2017&amp;author=Yang%2CF&amp;author=Chien%2CAA\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR111\">Putnam, M. &amp; Perez, M. Solar potential analysis report. Minnesota Department of Commerce and the Minnesota Solar Pathways Project <a href=\"https:\/\/mn.gov\/commerce-stat\/pdfs\/solar-potential-analysis-report.pdf\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/mn.gov\/commerce-stat\/pdfs\/solar-potential-analysis-report.pdf\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/mn.gov\/commerce-stat\/pdfs\/solar-potential-analysis-report.pdf<\/a> (2018).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR112\">Hoza, M. Wind and solar curtailments on the rise. Factset Insight <a href=\"https:\/\/insight.factset.com\/wind-and-solar-curtailments-on-the-rise\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/insight.factset.com\/wind-and-solar-curtailments-on-the-rise\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/insight.factset.com\/wind-and-solar-curtailments-on-the-rise<\/a> (2023).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR113\">Data center load shape library: Electric Power Research Insitute <a href=\"https:\/\/www.epri.com\/research\/products\/3002033424\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/www.epri.com\/research\/products\/3002033424\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/www.epri.com\/research\/products\/3002033424<\/a> (2025).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR114\">Google to invest $40 billion in new Texas datacenters. Bloomberg News <a href=\"https:\/\/www.bloomberg.com\/news\/articles\/2025-11-14\/google-to-invest-40-billion-in-new-data-centers-in-texas\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/www.bloomberg.com\/news\/articles\/2025-11-14\/google-to-invest-40-billion-in-new-data-centers-in-texas\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/www.bloomberg.com\/news\/articles\/2025-11-14\/google-to-invest-40-billion-in-new-data-centers-in-texas<\/a> (2025).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR115\">Swinhoe, D. &amp; Skidmore, Z. Meta announces 4 million sq ft, 2GW Louisiana data center campus. DCD <a href=\"https:\/\/www.datacenterdynamics.com\/en\/news\/meta-announces-4-million-sq-ft-louisiana-data-center-campus\/\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/www.datacenterdynamics.com\/en\/news\/meta-announces-4-million-sq-ft-louisiana-data-center-campus\/\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/www.datacenterdynamics.com\/en\/news\/meta-announces-4-million-sq-ft-louisiana-data-center-campus\/<\/a> (2024).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR116\">Generational growth: AI, data centers and the coming US power demand surge. Goldman Sachs <a href=\"https:\/\/www.goldmansachs.com\/pdfs\/insights\/pages\/generational-growth-ai-data-centers-and-the-coming-us-power-surge\/report.pdf\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/www.goldmansachs.com\/pdfs\/insights\/pages\/generational-growth-ai-data-centers-and-the-coming-us-power-surge\/report.pdf\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/www.goldmansachs.com\/pdfs\/insights\/pages\/generational-growth-ai-data-centers-and-the-coming-us-power-surge\/report.pdf<\/a> (2024).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR117\">Norris, T., Profeta, T., Patino-Echeverri, D. &amp; Cowie-Haskell, A. Rethinking load growth: assessing the potential for integration of large flexible loads in US power systems. Nicholas Institute for Energy, Environment &amp; Sustainability, Duke University <a href=\"https:\/\/nicholasinstitute.duke.edu\/publications\/rethinking-load-growth\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/nicholasinstitute.duke.edu\/publications\/rethinking-load-growth\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/nicholasinstitute.duke.edu\/publications\/rethinking-load-growth<\/a> (2025).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR118\">Lin, L. et al. Exploding AI power use: an opportunity to rethink grid planning and management. In Proc. 15th ACM Int. Conf. Future and Sustainable Energy Systems (e-Energy \u201924) 434\u2013441 (ACM, 2024).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR119\">Lin, L. &amp; Chien, A. A. Middlebox: unlocking datacenter growth and grid decarbonization. In Proc. Symposium Cloud Computing (SoCC \u201825) 134\u2013148 (ACM, 2025).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR120\">Advantages and challenges of nuclear-powered data centers. United States Department of Energy <a href=\"https:\/\/www.energy.gov\/ne\/articles\/advantages-and-challenges-nuclear-powered-data-centers\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/www.energy.gov\/ne\/articles\/advantages-and-challenges-nuclear-powered-data-centers\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/www.energy.gov\/ne\/articles\/advantages-and-challenges-nuclear-powered-data-centers<\/a> (2025).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR121\">Macknick, J., Newmark, R., Heath, G. &amp; Hallett, K. A review of operational water consumption and withdrawal factors for electricity generating technologies. NREL <a href=\"https:\/\/docs.nlr.gov\/docs\/fy11osti\/50900.pdf\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/docs.nlr.gov\/docs\/fy11osti\/50900.pdf\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/docs.nlr.gov\/docs\/fy11osti\/50900.pdf<\/a> (2011).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR122\">Reig, P. What\u2019s the difference between water use and water consumption? World Resources Institute Commentary <a href=\"https:\/\/www.wri.org\/insights\/whats-difference-between-water-use-and-water-consumption\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/www.wri.org\/insights\/whats-difference-between-water-use-and-water-consumption\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/www.wri.org\/insights\/whats-difference-between-water-use-and-water-consumption<\/a> (2013).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR123\">Environmental sustainability report 2025. Microsoft <a href=\"https:\/\/www.microsoft.com\/en-us\/corporate-responsibility\/sustainability\/report\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/www.microsoft.com\/en-us\/corporate-responsibility\/sustainability\/report\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/www.microsoft.com\/en-us\/corporate-responsibility\/sustainability\/report<\/a> (2024).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR124\">Reig, P., Luo, T., Christensen, E. &amp; Sinistore, J. Guidance for calculating water use embedded in purchased electricity. World Resources Institute <a href=\"https:\/\/www.wri.org\/research\/guidance-calculating-water-use-embedded-purchased-electricity\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/www.wri.org\/research\/guidance-calculating-water-use-embedded-purchased-electricity\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/www.wri.org\/research\/guidance-calculating-water-use-embedded-purchased-electricity<\/a> (2020).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR125\">Siddik, M. A. B., Shehabi, A., Rao, P. &amp; Marston, L. T. Spatially and temporally detailed water and carbon footprints of U.S. electricity generation and use. Water Resour. Res. 60, e2024WR038350 (2024).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 125\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Spatially%20and%20temporally%20detailed%20water%20and%20carbon%20footprints%20of%20U.S.%20electricity%20generation%20and%20use&amp;journal=Water%20Resour.%20Res.&amp;volume=60&amp;publication_year=2024&amp;author=Siddik%2CMAB&amp;author=Shehabi%2CA&amp;author=Rao%2CP&amp;author=Marston%2CLT\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR126\">Siddik, M. A. B., Shehabi, A. &amp; Marston, L. The environmental footprint of data centers in the United States. Environ. Res. Lett. 16, 064017 (2021).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 126\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=The%20environmental%20footprint%20of%20data%20centers%20in%20the%20United%20States&amp;journal=Environ.%20Res.%20Lett.&amp;volume=16&amp;publication_year=2021&amp;author=Siddik%2CMAB&amp;author=Shehabi%2CA&amp;author=Marston%2CL\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR127\">Shehabi, A. et al. United States data center energy usage report. Lawrence Berkeley National Laboratory <a href=\"https:\/\/eta.lbl.gov\/publications\/united-states-data-center-energy\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/eta.lbl.gov\/publications\/united-states-data-center-energy\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/eta.lbl.gov\/publications\/united-states-data-center-energy<\/a> (2016).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR128\">Karimi, L. et al. Water-energy tradeoffs in data centers: a case study in hot-arid climates. Resour. Conserv. Recycl. 181, 106194 (2022).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 128\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Water-energy%20tradeoffs%20in%20data%20centers%3A%20a%20case%20study%20in%20hot-arid%20climates&amp;journal=Resour.%20Conserv.%20Recycl.&amp;volume=181&amp;publication_year=2022&amp;author=Karimi%2CL\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR129\">Frost, K. &amp; Hua, I. Quantifying spatiotemporal impacts of the interaction of water scarcity and water use by the global semiconductor manufacturing industry. Water Resour. Ind. 22, 100115 (2019).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 129\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Quantifying%20spatiotemporal%20impacts%20of%20the%20interaction%20of%20water%20scarcity%20and%20water%20use%20by%20the%20global%20semiconductor%20manufacturing%20industry&amp;journal=Water%20Resour.%20Ind.&amp;volume=22&amp;publication_year=2019&amp;author=Frost%2CK&amp;author=Hua%2CI\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR130\">PUB, Singapore\u2019s National Water Agency. Best Practice Guide in Water Efficiency: Wafer Fabrication and Semiconductor Sector <a href=\"https:\/\/go.nature.com\/4p0UHk1\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/go.nature.com\/4p0UHk1\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/go.nature.com\/4p0UHk1<\/a> (PUB, 2022).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR131\">Han, Y., Li, P., Wierman, A. &amp; Ren, S. Small bottle, big pipe: quantifying and addressing the impact of data centers on public water systems. Preprint at <a href=\"https:\/\/doi.org\/10.48550\/arXiv.2603.02705\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"10.48550\/arXiv.2603.02705\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/doi.org\/10.48550\/arXiv.2603.02705<\/a> (2026).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR132\">Ahmed, S. N., Bencala, K., Nummer, S., Schultz, C. L. &amp; Seck, A. 2025 Washington Metropolitan Area water supply study: demand and resource availability forecast for the year 2050. Interstate Commission on the Potomac River Basin <a href=\"https:\/\/www.potomacriver.org\/publications\/2025-washington-metropolitan-area-water-supply-study-demand-and-resource-availability-forecast-for-the-year-2050\/\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/www.potomacriver.org\/publications\/2025-washington-metropolitan-area-water-supply-study-demand-and-resource-availability-forecast-for-the-year-2050\/\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/www.potomacriver.org\/publications\/2025-washington-metropolitan-area-water-supply-study-demand-and-resource-availability-forecast-for-the-year-2050\/<\/a> (2025).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR133\">Water use by data centers in the Susquehanna River Basin: FAQ. Susquehanna River Basin Commission <a href=\"https:\/\/www.srbc.gov\/about\/news\/docs\/srbc-data-centers-faq.pdf\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/www.srbc.gov\/about\/news\/docs\/srbc-data-centers-faq.pdf\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/www.srbc.gov\/about\/news\/docs\/srbc-data-centers-faq.pdf<\/a> (2025).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR134\">H\u00f6lzle, U. Our commitment to climate-conscious data center cooling. The Keyword <a href=\"https:\/\/blog.google\/outreach-initiatives\/sustainability\/our-commitment-to-climate-conscious-data-center-cooling\/\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/blog.google\/outreach-initiatives\/sustainability\/our-commitment-to-climate-conscious-data-center-cooling\/\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/blog.google\/outreach-initiatives\/sustainability\/our-commitment-to-climate-conscious-data-center-cooling\/<\/a> (2022).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR135\">Google environmental report 2025. Google <a href=\"https:\/\/www.gstatic.com\/gumdrop\/sustainability\/google-2025-environmental-report.pdf\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/www.gstatic.com\/gumdrop\/sustainability\/google-2025-environmental-report.pdf\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/www.gstatic.com\/gumdrop\/sustainability\/google-2025-environmental-report.pdf<\/a> (2025).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR136\"> Principles for sustainable water use by data centers: building more effective public\u2013private collaboration. Water-AI Nexus <a href=\"https:\/\/water-ai-nexus.org\/insight-report\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/water-ai-nexus.org\/insight-report\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/water-ai-nexus.org\/insight-report<\/a> (2025).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR137\">Our contribution to a global environmental standard for AI. Mistral AI <a href=\"https:\/\/mistral.ai\/news\/our-contribution-to-a-global-environmental-standard-for-ai\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/mistral.ai\/news\/our-contribution-to-a-global-environmental-standard-for-ai\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/mistral.ai\/news\/our-contribution-to-a-global-environmental-standard-for-ai<\/a> (2025).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR138\">Firestone, D. et al. Azure accelerated networking: SmartNICs in the public cloud. In Symp. Networked Systems Design and Implementation (USENIX, 2018).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR139\">Li, H. et al. LeapIO: efficient and portable virtual NVMe storage on ARMSoCs. In Proc. 25th Int. Conf. Architectural Support for Programming Languages and Operating Systems (ASPLOS \u201820) (eds Larus, J. et al.) 591\u2013605 (2020).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR140\">Liguori, A. The Nitro Project &#8211; Next-Generation EC2 Infrastructure. aws <a href=\"https:\/\/pages.awscloud.com\/The-Nitro-Project-Next-Generation-EC2-Infrastructure_0119-CMP_OD.html\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/pages.awscloud.com\/The-Nitro-Project-Next-Generation-EC2-Infrastructure_0119-CMP_OD.html\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/pages.awscloud.com\/The-Nitro-Project-Next-Generation-EC2-Infrastructure_0119-CMP_OD.html<\/a> (2018).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR141\">Nguyen, S., Zhou, B., Ding, Y. &amp; Liu, S. Towards sustainable large language model serving. ACM SIGENERGY Energy Inform. Rev. 4, 134\u2013140 (2025).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 141\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Towards%20sustainable%20large%20language%20model%20serving&amp;journal=ACM%20SIGENERGY%20Energy%20Inform.%20Rev.&amp;volume=4&amp;pages=134-140&amp;publication_year=2025&amp;author=Nguyen%2CS&amp;author=Zhou%2CB&amp;author=Ding%2CY&amp;author=Liu%2CS\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR142\">Leviathan, Y., Kalman, M. &amp; Matias, Y. Fast inference from transformers via speculative decoding. In Proc. 40th Int. Conf. Machine Learning (ICML \u201823) (eds Krause, A. et al.) 795 (JMLR, 2023).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR143\">Demand response. PJM <a href=\"https:\/\/www.pjm.com\/markets-and-operations\/demand-response\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/www.pjm.com\/markets-and-operations\/demand-response\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/www.pjm.com\/markets-and-operations\/demand-response<\/a> (2024).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR144\">Zhang, Y., Paschalidis, I. C. &amp; Coskun, A. K. Data center participation in demand response programs with quality-of-service guarantees. In Proc. 10th Int. Conf. Future Energy Systems (e-Energy \u201919) 285\u2013302 (ACM, 2019).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR145\">Sun, Q., Ren, S., Wu, C. &amp; Li, Z. An online incentive mechanism for emergency demand response in geo-distributed colocation data centers. In Proc. 7th Int. Conf. Future Energy Systems (e-Energy \u201916) 3 (ACM, 2016).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR146\">Wierman, A., Liu, Z., Liu, I. &amp; Mohsenian-Rad, H. Opportunities and challenges for data center demand response. In Int. Green Computing Conf. 1\u201310 (IEEE, 2014).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR147\">Large flexible load task force. Electric Reliability Council of Texas <a href=\"https:\/\/www.ercot.com\/committees\/inactive\/lfltf\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/www.ercot.com\/committees\/inactive\/lfltf\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/www.ercot.com\/committees\/inactive\/lfltf<\/a> (2022).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR148\">Barroso, L. A., H\u00f6lzle, U. &amp; Ranganathan, P. The Datacenter as a Computer: Designing Warehouse-scale Machines (Springer Nature, 2026).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR149\">Investigating a higher renewables portfolio standard in California: Executive summary. Energy and Environmental Economics <a href=\"https:\/\/www.ethree.com\/wp-content\/uploads\/2017\/01\/E3_Final_RPS_Report_2014_01_06_ExecutiveSummary-1.pdf\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/www.ethree.com\/wp-content\/uploads\/2017\/01\/E3_Final_RPS_Report_2014_01_06_ExecutiveSummary-1.pdf\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/www.ethree.com\/wp-content\/uploads\/2017\/01\/E3_Final_RPS_Report_2014_01_06_ExecutiveSummary-1.pdf<\/a> (2014).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR150\">Dominion Energy Virginia. RD214 &#8211; Dominion Energy\u00ae Virginia Electric and Power Company\u2019s Report of Its 2023 Integrated Resource Plan \u2013 May 1, 2023 <a href=\"https:\/\/rga.lis.virginia.gov\/Published\/2023\/RD214\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/rga.lis.virginia.gov\/Published\/2023\/RD214\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/rga.lis.virginia.gov\/Published\/2023\/RD214<\/a> (Dominion Energy Virginia, 2023).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR151\">Generation capacity statement 2023\u20132032. Eir Grid and Soni <a href=\"https:\/\/cms.eirgrid.ie\/sites\/default\/files\/publications\/19035-EirGrid-Generation-Capacity-Statement-Combined-2023-V5-Jan-2024.pdf\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/cms.eirgrid.ie\/sites\/default\/files\/publications\/19035-EirGrid-Generation-Capacity-Statement-Combined-2023-V5-Jan-2024.pdf\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/cms.eirgrid.ie\/sites\/default\/files\/publications\/19035-EirGrid-Generation-Capacity-Statement-Combined-2023-V5-Jan-2024.pdf<\/a> (2024).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR152\">PJM load forecast report. PJM Resource Adequacy Planning Department <a href=\"https:\/\/www.pjm.com\/-\/media\/library\/reports-notices\/load-forecast\/2024-load-report.ashx\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/www.pjm.com\/-\/media\/library\/reports-notices\/load-forecast\/2024-load-report.ashx\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/www.pjm.com\/-\/media\/library\/reports-notices\/load-forecast\/2024-load-report.ashx<\/a> (2024).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR153\">Lin, L. &amp; Chien, A. A. Adapting datacenter capacity for greener datacenters and grid. In Proc. 14th ACM Int. Conf. Future Energy Systems (e-Energy \u201923) 200\u2013213 (ACM, 2023).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR154\">Lin, L. &amp; Chien, A. A. Distribution and management of datacenter load decoupling. Preprint at <a href=\"https:\/\/doi.org\/10.48550\/arXiv.2511.08936\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"10.48550\/arXiv.2511.08936\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/doi.org\/10.48550\/arXiv.2511.08936<\/a> (2025).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR155\">Radovanovic, A. et al. Carbon-aware computing for datacenters. IEEE Trans. Power Systems 38, 1270\u20131280 (2021).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 155\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Carbon-aware%20computing%20for%20datacenters&amp;journal=IEEE%20Trans.%20Power%20Systems&amp;volume=38&amp;pages=1270-1280&amp;publication_year=2021&amp;author=Radovanovic%2CA\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR156\">California ISO: today\u2019s outlook. CAISO <a href=\"https:\/\/www.caiso.com\/todays-outlook\/\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/www.caiso.com\/todays-outlook\/\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/www.caiso.com\/todays-outlook\/<\/a> (2026).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR157\">Chien, A. A., Yang, F. &amp; Zhang, C. Characterizing curtailed and uneconomic renewable power in the mid-continent independent system operator. AIMS Energy 6, 376\u2013401 (2018).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 157\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Characterizing%20curtailed%20and%20uneconomic%20renewable%20power%20in%20the%20mid-continent%20independent%20system%20operator&amp;journal=AIMS%20Energy&amp;volume=6&amp;pages=376-401&amp;publication_year=2018&amp;author=Chien%2CAA&amp;author=Yang%2CF&amp;author=Zhang%2CC\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR158\">Kim, K., Yang, F., Zavala, V. &amp; Chien, A. A. Data centers as dispatchable loads to harness stranded power. IEEE Trans. Sustain. Energy 8, 208\u2013218 (2016).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 158\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Data%20centers%20as%20dispatchable%20loads%20to%20harness%20stranded%20power&amp;journal=IEEE%20Trans.%20Sustain.%20Energy&amp;volume=8&amp;pages=208-218&amp;publication_year=2016&amp;author=Kim%2CK&amp;author=Yang%2CF&amp;author=Zavala%2CV&amp;author=Chien%2CAA\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR159\">Wilson, D. C. et al. An end-to-end hpc framework for dynamic power objectives. In Proc. Worksh. Int. Conf. High Performance Computing, Network, Storage, and Analysis (SC-W \u201923) 1801\u20131811 (ACM, 2023).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR160\">Norris, T. H., Profeta, T., Patino-Echeverri, D. &amp; Cowie-Haskell, A. Rethinking load growth: assessing the potential for integration of large flexible loads in US power systems. Nicholas Institute for Energy, Environment &amp; Sustainability, Duke University <a href=\"https:\/\/nicholasinstitute.duke.edu\/sites\/default\/files\/publications\/rethinking-load-growth.pdf\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/nicholasinstitute.duke.edu\/sites\/default\/files\/publications\/rethinking-load-growth.pdf\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/nicholasinstitute.duke.edu\/sites\/default\/files\/publications\/rethinking-load-growth.pdf<\/a> (2025).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR161\">Document 32023l1791: Directive (EU) 2023\/1791 of the European Parliament and of the Council of 13 September 2023 on energy efficiency and amending Regulation (EU) 2023\/955. EurLEX <a href=\"https:\/\/eur-lex.europa.eu\/eli\/dir\/2023\/1791\/oj\/eng\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/eur-lex.europa.eu\/eli\/dir\/2023\/1791\/oj\/eng\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/eur-lex.europa.eu\/eli\/dir\/2023\/1791\/oj\/eng<\/a> (2023).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR162\">I&amp;M, Google filing to support reliability through demand response structure. Indiana Michigan Power <a href=\"https:\/\/www.indianamichiganpower.com\/company\/news\/view?releaseID=10359\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/www.indianamichiganpower.com\/company\/news\/view?releaseID=10359\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/www.indianamichiganpower.com\/company\/news\/view?releaseID=10359<\/a> (2025).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR163\">Zhang, W., Roald, L. A., Chien, A. A., Birge, J. R. &amp; Zavala, V. M. Flexibility from networks of data centers: a market clearing formulation with virtual links. Electric Power Systems Res. 189, 106723 (2020).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 163\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Flexibility%20from%20networks%20of%20data%20centers%3A%20a%20market%20clearing%20formulation%20with%20virtual%20links&amp;journal=Electric%20Power%20Systems%20Res.&amp;volume=189&amp;publication_year=2020&amp;author=Zhang%2CW&amp;author=Roald%2CLA&amp;author=Chien%2CAA&amp;author=Birge%2CJR&amp;author=Zavala%2CVM\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR164\">Lindberg, J., Abdennadher, Y., Chen, J., Lesieutre, B. C. &amp; Roald, L. A guide to reducing carbon emissions through data center geographical load shifting. In Proc. Twelfth ACM Int. Conf. Future Energy Systems (e-Energy \u201921) 430-436 (ACM, 2021).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR165\">Lin, L. P. Decoupling and coordination: the keys to making AI datacenters constructive loads in renewable-dominated grids. PhD thesis, Univ. Chicago <a href=\"http:\/\/zccloud.cs.uchicago.edu\/\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"http:\/\/zccloud.cs.uchicago.edu\/\" rel=\"nofollow noopener\" target=\"_blank\">http:\/\/zccloud.cs.uchicago.edu\/<\/a> (2025).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR166\">Uptime institute global data center survey 2024. Uptime Institute <a href=\"https:\/\/datacenter.uptimeinstitute.com\/rs\/711-RIA-145\/images\/2024.GlobalDataCenterSurvey.Report.pdf\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/datacenter.uptimeinstitute.com\/rs\/711-RIA-145\/images\/2024.GlobalDataCenterSurvey.Report.pdf\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/datacenter.uptimeinstitute.com\/rs\/711-RIA-145\/images\/2024.GlobalDataCenterSurvey.Report.pdf<\/a> (2024).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR167\">Sustainability report. Meta <a href=\"https:\/\/sustainability.atmeta.com\/2024-sustainability-report\/\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/sustainability.atmeta.com\/2024-sustainability-report\/\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/sustainability.atmeta.com\/2024-sustainability-report\/<\/a> (2024).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR168\">Apple\u2019s water strategy. Apple <a href=\"https:\/\/www.apple.com\/environment\/pdf\/Apples_Water_Strategy.pdf\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/www.apple.com\/environment\/pdf\/Apples_Water_Strategy.pdf\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/www.apple.com\/environment\/pdf\/Apples_Water_Strategy.pdf<\/a> (2025).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR169\">Gupta, P. S., Hossen, M. R., Li, P., Ren, S. &amp; Islam, M. A. A dataset for research on water sustainability. In Proc. 15th ACM Int. Conf. Future and Sustainable Energy Systems (e-Energy \u201924) 442\u2013446 (ACM, 2024).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR170\">Wu, Y., Hua, I. &amp; Ding, Y. Not all water consumption is equal: a water stress weighted metric for sustainable computing. SIGENERGY Energy Inform. Rev. 5, 84\u201390 (2025).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 170\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Not%20all%20water%20consumption%20is%20equal%3A%20a%20water%20stress%20weighted%20metric%20for%20sustainable%20computing&amp;journal=SIGENERGY%20Energy%20Inform.%20Rev.&amp;volume=5&amp;pages=84-90&amp;publication_year=2025&amp;author=Wu%2CY&amp;author=Hua%2CI&amp;author=Ding%2CY\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR171\">Van Zetten, J. D., Cholette, M. E. &amp; Bamdad, K. Energy and carbon savings in data centres through liquid-to-chip cooling with differential temperature control. Adv. Appl. Energy 22, 100269 (2026).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 171\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Energy%20and%20carbon%20savings%20in%20data%20centres%20through%20liquid-to-chip%20cooling%20with%20differential%20temperature%20control&amp;journal=Adv.%20Appl.%20Energy&amp;volume=22&amp;publication_year=2026&amp;author=Zetten%2CJD&amp;author=Cholette%2CME&amp;author=Bamdad%2CK\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR172\">Hershberg, K., Burnett, B., Roraff, J., Hopker, P. &amp; Brune, M. The energy and water use impacts of building system design for data centers: design considerations for Oregon and Washington. PAE <a href=\"https:\/\/critfc.org\/wp-content\/uploads\/2025\/03\/data-center-report.pdf\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/critfc.org\/wp-content\/uploads\/2025\/03\/data-center-report.pdf\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/critfc.org\/wp-content\/uploads\/2025\/03\/data-center-report.pdf<\/a> (2025).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR173\">Islam, M. A. et al. Exploiting spatio-temporal diversity for water saving in geo-distributed data centers. IEEE Trans. Cloud Comput. 6, 734\u2013746 (2018).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 173\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Exploiting%20spatio-temporal%20diversity%20for%20water%20saving%20in%20geo-distributed%20data%20centers&amp;journal=IEEE%20Trans.%20Cloud%20Comput.&amp;volume=6&amp;pages=734-746&amp;publication_year=2018&amp;author=Islam%2CMA\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR174\">Islam, M. A., Ren, S., Quan, G., Shakir, M. Z. &amp; Vasilakos, A. V. Water-constrained geographic load balancing in data centers. IEEE Trans. Cloud Comput. <a href=\"https:\/\/doi.org\/10.1109\/TCC.2015.2453982\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"10.1109\/TCC.2015.2453982\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/doi.org\/10.1109\/TCC.2015.2453982<\/a> (2015).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR175\">Jiang, Y., Roy, R. B., Kanakagiri, R. &amp; Tiwari, D. Waterwise: c-optimizing carbon- and water-footprint toward environmentally sustainable cloud computing. In Proc. 30th SIGPLAN Ann. Symp. Principles and Practice of Parallel Programming (PPoPP \u201925) 297\u2013311 (ACM, 2025).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR176\">FAQ: why does AI use water? Amazon <a href=\"https:\/\/sustainability.aboutamazon.com\/stories\/just-back-from-weftec-why-does-ai-use-water\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/sustainability.aboutamazon.com\/stories\/just-back-from-weftec-why-does-ai-use-water\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/sustainability.aboutamazon.com\/stories\/just-back-from-weftec-why-does-ai-use-water<\/a> (2025).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR177\">de Chalendar, J. A., Taggart, J. &amp; Benson, S. M. Tracking emissions in the U.S. electricity system. Proc. Natl Acad. Sci. 116, 25497\u201325502 (2019).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 177\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Tracking%20emissions%20in%20the%20U.S.%20electricity%20system&amp;journal=Proc.%20Natl%20Acad.%20Sci.&amp;volume=116&amp;pages=25497-25502&amp;publication_year=2019&amp;author=Chalendar%2CJA&amp;author=Taggart%2CJ&amp;author=Benson%2CSM\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR178\">Acun, B. et al. Carbon Explorer: a holistic framework for designing carbon aware datacenters. In Proc. 28th Int. Conf. Architectural Support for Programming Languages and Operating Systems (ASPLOS 2023) Vol. 2, 118\u2013132 (ACM, 2023).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR179\">Qureshi, A., Weber, R., Balakrishnan, H., Guttag, J. &amp; Maggs, B. Cutting the electric bill for internet-scale systems. In Proc. Conf. Data Communications (SIGCOMM \u201909) 123\u2013134 (ACM, 2009).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR180\">Gao, P. X., Curtis, A. R., Wong, B. &amp; Keshav, S. It\u2019s not easy being green. Proc. Conf. Applications, Technologies, Architectures and Protocols for Computer Communication (SIGCOMM \u201812) (eds Eggert, L. et al.) 211\u2013222 (ACM, 2012).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR181\">Li, P., Yang, J., Wierman, A. &amp; Ren, S. Towards environmentally equitable AI via geographical load balancing. In Proc. 15th Int. Conf. Future and Sustainable Energy Systems (e-Energy \u201824) 291\u2013307 (ACM, 2024).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR182\">Islam, M. J. &amp; Ren, S. Equity-aware spatial-temporal workload shifting for sustainable AI data centers. In Proc. Worksh. Tackling Climate Change with Machine Learning (NeurIPS \u201824) 33 (USENIX, 2024).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR183\">Pessach, D. &amp; Shmueli, E. A review on fairness in machine learning. ACM Comput. Surv. <a href=\"https:\/\/doi.org\/10.1145\/3494672\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"10.1145\/3494672\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/doi.org\/10.1145\/3494672<\/a> (2022).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR184\">Ahmed, K., Islam, M. A., Ren, S. &amp; Quan, G. Can data center become water self-sufficient? In Proc. 6th Worksh. Power-Aware Computing and Systems (HotPower \u201814) (USENIX, 2014).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR185\">Chen, S., Zhou, Z., Liu, F., Li, Z. &amp; Ren, S. Cloudheat: an efficient online market mechanism for datacenter heat harvesting. ACM Trans. Model. Perform. Eval. Comput. Syst. <a href=\"https:\/\/doi.org\/10.1145\/3199675\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"10.1145\/3199675\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/doi.org\/10.1145\/3199675<\/a> (2018).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR186\">Rockstr\u00f6m, J. et al. A safe operating space for humanity. Nature 461, 472\u2013475 (2009).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 186\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=A%20safe%20operating%20space%20for%20humanity&amp;journal=Nature&amp;volume=461&amp;pages=472-475&amp;publication_year=2009&amp;author=Rockstr%C3%B6m%2CJ\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR187\">Carman, J. et al. Understanding Pro-Climate Voters in the United States. Research Report. Yale Program on Climate Change Communication, Yale University and George Mason University <a href=\"https:\/\/climatecommunication.yale.edu\/publications\/understanding-pro-climate-voters\/\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/climatecommunication.yale.edu\/publications\/understanding-pro-climate-voters\/\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/climatecommunication.yale.edu\/publications\/understanding-pro-climate-voters\/<\/a> (2024).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR188\">Estrin, D. L. &amp; Millett, L. I. Computing Research for Sustainability (National Academies Press, 2012).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR189\">IPCC. Climate change 2021: the physical science basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (eds Masson-Delmotte, V. et al.) (Cambridge University Press, 2021).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR190\">Jaureguiberry, P. et al. The direct drivers of recent global anthropogenic biodiversity loss. Sci. Adv. 8, eabm9982 (2022).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 190\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=The%20direct%20drivers%20of%20recent%20global%20anthropogenic%20biodiversity%20loss&amp;journal=Sci.%20Adv.&amp;volume=8&amp;publication_year=2022&amp;author=Jaureguiberry%2CP\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR191\">Potschin, M., Haines-Young, R., Fish, R. &amp; Turner, R. K. (eds) Routledge Handbook of Ecosystem Services 1st edn (Routledge, 2016).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR192\">UN Environment Global Environmental Outlook (GEO-6): Healthy Planet, Healthy People (Cambridge Univ. Press, 2019).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR193\">Daly, H. E. Steady-state economics. In Thinking About the Environment (eds Cahn, M. A. &amp; O\u2019Brien, R.) 250\u2013255 (Routledge, 2015).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR194\">Kallis, G. In defence of degrowth. Ecol. Econ. 70, 873\u2013880 (2011).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 194\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=In%20defence%20of%20degrowth&amp;journal=Ecol.%20Econ.&amp;volume=70&amp;pages=873-880&amp;publication_year=2011&amp;author=Kallis%2CG\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR195\">K\u00f6stler, L. &amp; Ossewaarde, R. The making of AI society: AI futures frames in German political and media discourses. AI Soc. 37, 249\u2013263 (2022).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 195\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=The%20making%20of%20AI%20society%3A%20AI%20futures%20frames%20in%20German%20political%20and%20media%20discourses&amp;journal=AI%20Soc.&amp;volume=37&amp;pages=249-263&amp;publication_year=2022&amp;author=K%C3%B6stler%2CL&amp;author=Ossewaarde%2CR\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR196\">Monbiot, G. How Do We Get Out of This Mess? The Guardian <a href=\"https:\/\/www.theguardian.com\/books\/2017\/sep\/09\/george-monbiot-how-de-we-get-out-of-this-mess\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/www.theguardian.com\/books\/2017\/sep\/09\/george-monbiot-how-de-we-get-out-of-this-mess\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/www.theguardian.com\/books\/2017\/sep\/09\/george-monbiot-how-de-we-get-out-of-this-mess<\/a> (9 September 2017).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR197\">Artificial intelligence (AI). United Nations <a href=\"https:\/\/www.un.org\/en\/global-issues\/artificial-intelligence\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/www.un.org\/en\/global-issues\/artificial-intelligence\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/www.un.org\/en\/global-issues\/artificial-intelligence<\/a> (2025).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR198\">S\u00e6tra, H. S. Science fiction, sustainability, and scenario use: comprehensive scenarios for improved strategy development and innovation. Technovation 132, 102976 (2024).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 198\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Science%20fiction%2C%20sustainability%2C%20and%20scenario%20use%3A%20comprehensive%20scenarios%20for%20improved%20strategy%20development%20and%20innovation&amp;journal=Technovation&amp;volume=132&amp;publication_year=2024&amp;author=S%C3%A6tra%2CHS\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR199\">Kasneci, E. et al. ChatGPT for good? On opportunities and challenges of large language models for education. Learn. Individ. Differ. 103, 102274 (2023).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 199\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=ChatGPT%20for%20good%3F%20On%20opportunities%20and%20challenges%20of%20large%20language%20models%20for%20education&amp;journal=Learn.%20Individ.%20Differ.&amp;volume=103&amp;publication_year=2023&amp;author=Kasneci%2CE\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR200\">Torrance, A. W. &amp; Tomlinson, B. Governance of the AI, by the AI, and for the AI. Miss. Law J.\u00a093, 107 (2023).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 200\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Governance%20of%20the%20AI%2C%20by%20the%20AI%2C%20and%20for%20the%20AI&amp;journal=Miss.%20Law%20J.&amp;volume=93&amp;publication_year=2023&amp;author=Torrance%2CAW&amp;author=Tomlinson%2CB\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR201\">Filippi, D. S., Tomlinson, B. &amp; Torrance, A. W. The law and AI as an \u201capex collaborator\u201d: legal frameworks for optimized cooperation. FIU Law Rev. 20, 7 (2026).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 201\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=The%20law%20and%20AI%20as%20an%20%E2%80%9Capex%20collaborator%E2%80%9D%3A%20legal%20frameworks%20for%20optimized%20cooperation&amp;journal=FIU%20Law%20Rev.&amp;volume=20&amp;publication_year=2026&amp;author=Filippi%2CDS&amp;author=Tomlinson%2CB&amp;author=Torrance%2CAW\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR202\">Marcuse, H. One-Dimensional Man: Studies in the Ideology of Advanced Industrial Society (Beacon, 1964; reprinted Routledge, 2002).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR203\">Bodnar, C. et al. A foundation model for the Earth system. Nature 641, 1180\u20131187 (2025).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"cas reference\" data-track-action=\"cas reference\" href=\"https:\/\/www.nature.com\/articles\/cas-redirect\/1:CAS:528:DC%2BB2MXht1ehu7%2FM\" aria-label=\"CAS reference 203\" target=\"_blank\">CAS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 203\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=A%20foundation%20model%20for%20the%20Earth%20system&amp;journal=Nature&amp;volume=641&amp;pages=1180-1187&amp;publication_year=2025&amp;author=Bodnar%2CC\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR204\">Recommendations on powering artificial intelligence and data center infrastructure. United States Department of Energy <a href=\"https:\/\/www.energy.gov\/sites\/default\/files\/2024-08\/Powering%20AI%20and%20Data%20Center%20Infrastructure%20Recommendations%20July%202024.pdf\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/www.energy.gov\/sites\/default\/files\/2024-08\/Powering%20AI%20and%20Data%20Center%20Infrastructure%20Recommendations%20July%202024.pdf\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/www.energy.gov\/sites\/default\/files\/2024-08\/Powering%20AI%20and%20Data%20Center%20Infrastructure%20Recommendations%20July%202024.pdf<\/a> (2024).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR205\">Opportunities in a resource-constrained world: how business is rising to the challenge. Carbon Trust <a href=\"https:\/\/www.carbontrust.com\/our-work-and-impact\/guides-reports-and-tools\/opportunities-in-a-resource-constrained-world-how-business-is-rising-to-the-challenge\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/www.carbontrust.com\/our-work-and-impact\/guides-reports-and-tools\/opportunities-in-a-resource-constrained-world-how-business-is-rising-to-the-challenge\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/www.carbontrust.com\/our-work-and-impact\/guides-reports-and-tools\/opportunities-in-a-resource-constrained-world-how-business-is-rising-to-the-challenge<\/a> (2014).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR206\"> Illuminating the unseen power of the cloud. Microsoft Datacenters <a href=\"https:\/\/datacenters.microsoft.com\/\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/datacenters.microsoft.com\/\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/datacenters.microsoft.com\/<\/a> (2024).<\/p>\n","protected":false},"excerpt":{"rendered":"Rolnick, D. et al. Tackling climate change with machine learning. ACM Comput. Surv. 55, 1\u201396 (2022). Google Scholar\u00a0&hellip;\n","protected":false},"author":2,"featured_media":100196,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[2],"tags":[24,25,17277,45251,17278,17276,18344,17273,17275,17274],"class_list":["post-100195","post","type-post","status-publish","format-standard","has-post-thumbnail","category-ai","tag-ai","tag-artificial-intelligence","tag-economics-and-management","tag-electrical-and-electronic-engineering","tag-energy-efficiency","tag-energy-policy","tag-energy-supply-and-demand","tag-environmental-science-and-engineering","tag-renewable-and-green-energy","tag-sustainable-development"],"_links":{"self":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts\/100195","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/comments?post=100195"}],"version-history":[{"count":0,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts\/100195\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/media\/100196"}],"wp:attachment":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/media?parent=100195"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/categories?post=100195"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/tags?post=100195"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}