New tools emerge for reducing the carbon footprint of AI - Dataconomy

There is an exponential increase in the size of machine learning models and the carbon footprint of AI systems is an important thing to consider in order to create a sustainable world. In order to train them to accurately process images, text, or video, they need more and more energy. Some conferences now request submissions of papers to include information on CO2 emissions as the AI community struggles with its environmental impact. A new study proposes a way for quantifying those emissions that is more precise. It also contrasts the elements that influence them and evaluates two strategies for lowering them.