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Progress in machine learning (ML) comes with a cost to the environment, given that training ML models requires significant computational resources, energy and materials.
Life cycle assessment
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A case study and critical assessment in calculating power usage effectiveness for a data centre
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Carbon emissions and large neural network training
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Scaling language models: Methods, analysis & insights from training Gopher
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The atlas of AI: Power, politics, and the planetary costs of artificial intelligence
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Chasing carbon: The elusive environmental footprint of computing
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BigScience Language Open-science Open-access Multilingual (BLOOM) Language Model
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Google · 2022
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Aligning artificial intelligence with climate change mitigation
Kaack, L. H., Donti, P. L., Strubell, E., Kamiya, G., Creutzig, F., and Rolnick, D · 2022
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What language model to train if you have one million gpu hours?
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Nvidia A100 tensor core gpu datasheet
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The carbon footprint of machine learning training will plateau, then shrink, 2022
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OPT: Open pre-trained transformer language models
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