Google cuts datacentre energy use thanks to AI
Machine-learning means the datacentres effectively manage their own energy usage
Google has announced it has managed to cut datacentre energy by 15 per cent by using artificial intelligence to determine where it needs to cut energy consumption.
The technology was innovated by DeepMind, a company that Google purchased in 2014. It uses machine learning to work out how much energy is required for things like cooling and air flow regulation. It constantly adjusts air temperature, pressure and humidity to make the environment as energy efficient as possible.
DeepMind explained that although humans are able to work these calculations out, using knowledge learned from real-world scenarios makes the process much faster.
"It's one of those perfect examples of a setting where humans have a really good intuition they've developed over time but the machine learning algorithm has so much more data that describes real-world conditions," Mustafa Suleyman, DeepMind's co-founder said.
"It's much more than any human has ever been able to experience, and it's able to learn from all sorts of niche little edge cases seen in the data that a human wouldn't be able to identify. So it's able to tune the settings much more subtly and much more accurately."
DeepMind began its work to build the algorithms two years ago. At the time, Google opted to test the technology on just one per cent of servers, but now it's working on a double-digit percentage, but it will be running on 100 per cent of the company's worldwide datacentres from next year.
"I really think this is just the beginning. There are lots more opportunities to find efficiencies in data centre infrastructure," said Suleyman. "One of the most exciting things is the kind of algorithms we develop are inherently general...that means the same machine learning system should be able to perform well in a wide variety of environments."
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