Achieving a sustainable future for AI

More compute leads to greater electricity consumption, and consequent carbon emissions. A 2019 study by researchers at the University of Massachusetts Amherst estimated that the electricity consumed during the training of a transformer, a type of deep learning algorithm, can emit more than 626,000 pounds ( 284 metric tons) of carbon dioxide--equal to more than 41 round-trip flights between New York City and Sydney, Australia. We are also facing an explosion of data storage. IDC projects that 180 zettabytes of data--or, 180 billion terabytes--will be created in 2025. The collective energy required for data storage at this scale is enormous and will be challenging to address sustainably.