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Software developed at the University of Michigan could cut the energy used to train AI models by up to 50%, without slowing training or affecting performance, TechXplore reports.
Why it mattersThe researchers are working with NVIDIA to integrate the approach into Megatron-LM, its open-source AI training platform. If it delivers as described, this could make a major part of AI’s energy bill less painful without requiring faster hardware or a performance trade-off. The practical question is whether the saving holds up in real training runs, not just in the headline claim.
Discuss: Should AI developers prioritise software efficiency as energetically as they pursue bigger chips?
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