Estimating the carbon footprint of deep learning algorithms

The Carbontracker founders estimate that a single training session for the GPT-3 advanced language model – one of the biggest deep learning algorithms – is estimated to use the equivalent of a year's energy consumption of 126 Danish homes. — maciek905/Istock.com/AFP

IT students in Denmark have created a software program that can determine the energy consumption and the amount of CO2 generated by the development of deep learning algorithms. According to their estimates, hardware used to train a deep learning algorithm can use worrying amounts of energy from an environmental standpoint.

Whether browsing movies suggested by Netflix based on your viewing history, asking your voice assistant a question or interacting with a chatbot on an e-commerce website, all of these everyday online processes rely on deep learning algorithms.