"Our machine learning system was able to consistently achieve a 40% reduction in the amount of energy used for cooling, which equates to a 15% reduction in overall PUE after accounting for electrical losses and other non-cooling inefficiencies. It also produced the lowest PUE the site had ever seen," Google said.
Google now plans to direct DeepMind's machine learning algorithm at other data center challenges, such as improving power plant conversion efficiency (getting more energy from the same unit of input); reducing semiconductor manufacturing energy and water usage; and helping manufacturing facilities increase throughput.
The company plans to share the results so that other data center and industrial system operators can benefit from what it learns.
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