The Carbon Footprint of Machine Learning Training Will Plateau, Then Shrink

Understand

Machine Learning (ML) workloads have rapidly grown in importance, but raised concerns about their carbon footprint.

• Four best practices can reduce ML training energy by up to 100x and CO2 emissions up to 1000x.
• By following best practices, overall ML energy use (across research, development, and production) held steady at <15% of Google's total energy use for the past three years.
• If the whole ML field were to adopt best practices, total carbon emissions from training would reduce.