Publication | Closed Access
The Carbon Footprint of Machine Learning Training Will Plateau, Then Shrink
260
Citations
10
References
2022
Year
Artificial IntelligenceNeural Scaling LawEngineeringMachine LearningData ScienceCarbon Dioxide EmissionsSustainable EnergyComputational Learning TheoryPredictive AnalyticsMachine Learning ModelMachine Learning ToolComputer ScienceBest PracticesEmissionsSupervised Learning
Machine learning (ML) workloads have rapidly grown, raising concerns about their carbon footprint. We show four best practices to reduce ML training energy and carbon dioxide emissions. If the whole ML field adopts best practices, we predict that by 2030, total carbon emissions from training will decline.
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