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“DeepMind AI reduces energy used for cooling Google data centers by 40%,” was announced today in a blog post by Google’s Rich Evans, Research Engineer, DeepMind and Jim Gao, Data Center Engineer: “[W]e are excited to share that by applying DeepMind’s machine learning to our own Google data centers, we’ve managed to reduce the amount of energy we use for cooling by up to 40 percent. In any large scale energy-consuming environment, this would be a huge improvement. Given how sophisticated Google’s data centers are already, it’s a phenomenal step forward.”
— Blog also highlights that this success will also result in other companies running on Google’s cloud to improve their own energy efficiency.
— Plan of further expansion: “Because the algorithm is a general-purpose framework to understand complex dynamics, we plan to apply this to other challenges in the data center environment and beyond in the coming months. Possible applications of this technology include improving power plant conversion efficiency (getting more energy from the same unit of input), reducing semiconductor manufacturing energy and water usage, or helping manufacturing facilities increase throughput.”
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