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While current artificial intelligence (AI) technology holds strategic and transformative potential, it isn’t always environmentally-friendly due to high energy consumption. To the rescue are researchers from Massachusetts Institute of Technology (MIT) , who have devised a solution that not only lowers costs but, more importantly, reduces the AI model training’s carbon footprint. Back in June 2019, the University of Massachusetts at Amherst revealed that the amount of energy utilized in AI model training equaled 626,000 pounds of carbon dioxide. How so? Contemporary AI isn’t just run on a personal laptop or simple server. Rather, deep neural networks are deployed on diverse arrays of specialized hardware platforms. The level of energy consumption required to power such AI technologies is approximately five times the lifetime carbon emissions from an average American car, including its manufacturing. Related: This AI food truck could bring fresh produce directly to you Moreover, both Analytics Insight and Kepler Lounge warned that Google’s AlphaGo Zero — the AI that plays the game of Go against itself to self-learn — generated a massive 96 tons of carbon dioxide over 40 days of research training. That amount of carbon dioxide equals 1,000 hours of air travel as well as […]

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