How machine learning improves energy consumption

At the intersection of machine learning and energy consumption stands an incredibly powerful force with the potential to transform the way we globally produce and consume energy. So powerful in fact, that the concept of merging machine learning and renewable resources has been named the "energy internet" by economic theorist and author Jeremy Rifkin or "digital efficiency" by Intel and GE. Going green with machine learning solutions can drastically improve the way we consume energy, in terms of lower operational costs, more efficient production, better use of natural resources and lower environmental impacts. Last year, Google, with the help of its U.K.-based subsidiary DeepMind, reduced the amount of energy used to cool its data centers by 40%. By introducing machine learning to compensate for the nonlinear interactions between equipment and environment, and using the unique architecture and environment of each data center, this decrease saves Google millions of dollars each year.