More researchers are sounding the alarm about the growing costs of deep learning. In 2018, OpenAI published a study showing that the computational resources required to train large models was doubling every three to four months. In June, another study found that developing large-scale natural-language processing models, in particular, could produce a shocking carbon footprint.
The trend is driven by the research community's emphasis on advancing the state of the art — with little regard to costs. At this rate, one expert predicts, AI could account for as much as one-tenth of the world's electricity use by 2025.
In "Green AI," researchers at the Seattle-based Allen Institute for Artificial Intelligence have proposed a new way to mitigate this trend.
From Technology Review
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