Famously, a team of researchers from the University of Massachusetts, Amherst, concluded in 2019 that training a single large AI model could emit five times the carbon as is emitted in the manufacture and use of an average car over its entire lifetime. With the sudden boom in large language models (LLMs) and similar generative AI tools over the past several years, that ominous climate metric is casting an ever-larger shadow. Now, researchers at the University of Michigan have developed a new energy optimization framework for AI training that the developers say can reduce energy use during AI training by up to 75%.
The post University of Michigan’s ‘Zeus’ Framework Downsizes AI’s Massive Carbon Footprint appeared first on HPCwire.
Article From: "Oliver Peckham" Read full article »
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