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Reducing the carbon footprint of AI: The debate continues

The debate about the energy greediness of large AI models is raging. Recently, an AI ethics researcher at Google was dismissed because she had pinpointed the upward spiral of exploding training data sets. The fact is that the numbers make one’s head swim. In 2018, the BERT model made the headlines by achieving best-in-class NLP performance with a training dataset of 3 billion words. ....

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How to reduce the carbon footprint of AI?


How to reduce the carbon footprint of AI?
Can artificial intelligence be deployed to slow down global warming, or is AI one of the greatest climate sinners ever? That is the interesting debate that finds (not surprisingly) representatives from the AI industry and academia on opposite sides of the issue.
The big players have clearly understood that the public sensibility towards climate change offers a wonderful marketing opportunity. IBM has launched its Green Horizons project to analyze environmental data and predict pollution. Google has announced having cut by 15 percent the amount of energy used in its data centres thanks to machine learning. Forecasting energy consumption, analyzing satellite data to monitor forest conditions in real time are additional examples. The periodical announcement of new applications of AI that might help fight global warming are meant to put green cloths on an industry that, in fact, consumes devastating amounts of energy. This diverts ....

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