AI Machine Learning Efforts Encounter A Carbon Footprint Blemish - AI Trends

Recent news about the benefits of Machine Learning (ML) and Deep Learning (DL) has taken a slightly downbeat turn toward pointing out that there is a potential ecological cost associated with these systems. In particular, AI developers and AI researchers need to be mindful of the adverse and damaging carbon footprint that they are generating while crafting ML/DL capabilities. It is a so-called "green" or environmental wake-up call for AI that is worth hearing. Let's first review the nature of carbon footprints (CFPs) that are already quite familiar to all of us, such as the carbon belching transportation industry. A carbon footprint is usually expressed as the amount of carbon dioxide emissions spewed forth, including for example when you fly in a commercial plane from Los Angeles to New York, or when you drive your gasoline-powered car from Silicon Valley to Silicon Beach.