Alphabet's DeepMind uses machine learning to predict wind power output

Alphabet's DeepMind, an artificial intelligence (AI) firm, has used machine learning to boost the productivity of wind energy. In a blogpost Tuesday, DeepMind's Carl Elkin and Sims Witherspoon, together with Google's Will Fadrhonc, described how in 2018 DeepMind and Google had started to apply "machine learning algorithms to 700 megawatts of wind power capacity in the central United States." The post explained how a neural network was trained on weather forecasts and historical turbine data. The DeepMind system was configured in order to "predict wind power output 36 hours ahead of actual generation." This essentially means that the technology deployed by DeepMind can predict how much energy wind turbines and farms can produce.