Proposed framework could reduce energy consumption of federated learning
Modern machine learning systems consume massive amounts of energy. In fact, it’s estimated that training a large model can generate as much carbon dioxide as the total lifetime of five cars. The impact could worsen with the emergence of machine learning in distributed and federated learning settings, where billions of devices are expected to train machine learning models on a regular basis.
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