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This article is cited in 49 scientific papers (total in 49 papers)
ADVANCED STUDIES IN ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING
eco2AI: carbon emissions tracking of machine learning models as the first step towards sustainable AI
S. A. Budennyyab, V. D. Lazarevb, N. N. Zakharenkoa, A. N. Korovinb, O. A. Plosskayaa, D. V. Dimitrova, V. S. Akhripkina, I. V. Pavlova, I. V. Oseledetsbc, I. S. Barsolad, I. V. Egorovd, A. A. Kosterinad, L. E. Zhukove a Sber AI Lab, Москва, Россия
b Artificial Intelligence Research Institute, Moscow
c Skolkovo Institute of Science and Technology, Moscow, Russia
d Sber ESG, Moscow, Russia
e HSE University, Moscow
Keywords:
ESG, AI, sustainability, carbon footprint, ecology, CO$_2$ emissions, GHG.
Citation:
S. A. Budennyy, V. D. Lazarev, N. N. Zakharenko, A. N. Korovin, O. A. Plosskaya, D. V. Dimitrov, V. S. Akhripkin, I. V. Pavlov, I. V. Oseledets, I. S. Barsola, I. V. Egorov, A. A. Kosterina, L. E. Zhukov, “eco2AI: carbon emissions tracking of machine learning models as the first step towards sustainable AI”, Dokl. RAN. Math. Inf. Proc. Upr., 508 (2022), 134–145; Dokl. Math., 106:suppl. 1 (2022), S118–S128
Linking options:
https://www.mathnet.ru/eng/danma350 https://www.mathnet.ru/eng/danma/v508/p134
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Abstract page: | 89 | References: | 21 |
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