Measuring AI Emissions
The discussion explores the complexities of quantifying emissions from machine learning systems, particularly focusing on the challenges of measuring carbon footprints during model deployment. Sasha highlights the creation of a tool called codecarbon, which effectively tracks energy usage and its carbon impact, but notes that the shift towards inference in AI has made it increasingly difficult to obtain accurate emissions data. As more people utilize AI models rather than train them, understanding the associated environmental costs becomes crucial.In this clip
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The Gradient
Sasha Luccioni: Connecting the Dots Between AI's Environmental and Social Impacts
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