The AI That Cut Google’s Energy Bill Could Soon Help You

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The AI That Cut Google’s Energy Bill Could Soon Help You

Google uses DeepMind AI to cut data center energy bills

 

 

The amount of energy consumed by big data centers has always been a headache for tech companies. Keeping the servers cool as they crunch numbers is such a challenge that Facebook even built one of its facilities on the edge of the Arctic Circle. Well, Google has a different solution to this problem: putting its DeepMind artificial intelligence unit in charge and using AI to manage power usage in parts of its data centers. The results of this experiment? A 40 percent reduction in the amount of electricity needed for cooling, which Google describes as a “phenomenal step forward.”

 

SAVINGS OF HUNDREDS OF MILLIONS OF DOLLARS

 

After accounting for “electrical losses and other non-cooling inefficiencies,” this 40 percent reduction translated into a 15 percent reduction in overall power saving, says Google. Considering that the company used some 4,402,836 MWh of electricity in 2014(equivalent to the amount of energy consumed by 366,903 US households), this 15 percent will translate into savings of hundreds of millions of dollars over the years. And when you remember that Google reportedly paid $600 million for UK-based DeepMind back in 2014, it seems the company’s bet on AI will pay for itself before too long.

 

DeepMind co-founder Demis Hassabis said that the specially designed neural networks control “about 120 variables in the data centers,” including “the fans and the cooling systems and so on, and windows and other things.” The AI worked out the most efficient methods of cooling by analyzing data from sensors among the server racks, including information on things like temperatures and pump speeds. DeepMind’s engineers say the next step is identify where new data is needed to calculate further efficiencies, and to deploy sensors in those areas.

And the company won’t stop with Google’s data centers. “Because the algorithm is a general-purpose framework to understand complex dynamics, we plan to apply this to other challenges in the data centre environment and beyond in the coming months,” said DeepMind in a blog post. “Possible applications of this technology include improving power plant conversion efficiency […], reducing semiconductor manufacturing energy and water usage, or helping manufacturing facilities increase throughput.” Just don’t tell the conspiracy theorists what we’re putting artificial intelligence in charge of next.

Rahul
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