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Phys.org — Technology · October 13, 2026 · On the brief until October 27, 2026

Coordinated software tools could cut AI training energy use by up to 50%

Computer ScienceEnvironmental ScienceElectrical Engineering
THE AI ANGLE
Undergoing large-scale model training across distributed GPU networks

University of Michigan researchers developed software tools that cut AI training energy use by up to 50 percent without reducing speed. The team is integrating the tools into NVIDIA's open-source Megatron-LM framework. Engineers and researchers can now train large machine learning models using less electricity by slowing down idle processors and reorganizing core schedules.

Summary written by AI Business Lens with an AI model from the article at techxplore.com. It is not the article, and the publisher has not reviewed it. For publishers.

THE TEACHING ANGLE
Classes can examine how slowing down faster GPU cores to match slower ones reduces energy waste without delaying overall job completion.

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