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Google uses DeepMind-Powered AI to manage power usage
Last updated on Jul 22, 2016, 12:54 pm
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Internet giant Google started using Artificial Intelligence technology of its subsidiary DeepMind to reduce the energy consumption of its data centers.
DeepMind's Co-Founder, Demis Hassabis, stated Alphabet Inc. put the DeepMind AI system in charge of its data centers to manipulate servers, cooling systems, and other equipments to reduce power consumption.
High energy consumption and cooling systems have been a headache for technology companies.
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In this articleWhat is DeepMind? Google uses DeepMind-Powered AI to manage power usage Most efficient data centers 40% less power required to cool down servers Save hundreds of millions of dollars DeepMind's next step AI can address the biggest challenge - climate change Tackle some of the world's most challenging problems
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Introduction
What is DeepMind?
![What is DeepMind?]( "What is DeepMind?")
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DeepMind is a UK-based artificial intelligence startup that specializes in machine learning, systems neuroscience, and advanced algorithms.
Demis Hassabis, a neuroscientist; Mustafa Suleyman, and Shane Legg founded DeepMind in 2012.
DeepMind aimed to design computers that can think like humans; it develops gaming and e-commerce technologies.
Google acquired the two-year-old AI startup for $650 million in one of the biggest European acquisitions in 2014.
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22 Jul 2016
Google uses DeepMind-Powered AI to manage power usage
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Internet giant Google started using Artificial Intelligence technology of its subsidiary DeepMind to reduce the energy consumption of its data centers.
DeepMind's Co-Founder, Demis Hassabis, stated Alphabet Inc. put the DeepMind AI system in charge of its data centers to manipulate servers, cooling systems, and other equipments to reduce power consumption.
High energy consumption and cooling systems have been a headache for technology companies.
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Most efficient data centers
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Google says, "Specifically, our data centers use only 50% of the energy of most other data centers. In addition to reducing our impact on the environment, our efficient data center designs have saved us over a billion dollars to date."
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AI Experiment
40% less power required to cool down servers
![40% less power required to cool down servers]( "40% less power required to cool down servers")
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The result of Google's AI experiment was a 40% cut in the power requirement to cool down servers.
Google described the result as a "phenomenal step forward"; the 40% reduction resulted in a 15% cut in overall energy consumption.
According to Demis Hassabis, the AI technology used in data centers is similar to DeepMind's software, which taught itself to play Atari games.
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Information
Save hundreds of millions of dollars
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In 2014, Google used 4,402,836 MWh of power; which is equal to the power consumed by at least 366,903 households in the US. Google said the 15% reduction in overall energy consumption would save "hundreds of millions of dollars" in the future.
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Next Step
DeepMind's next step
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Hassabis stated the exclusively made neural networks control nearly 120 variables, including fans, cooling systems, windows, etc. in the data centers.
The AI technology cools systems by analyzing sensors' data, including pump speeds and temperatures in the server racks.
DeepMind's next step would be identifying those places that require new data to calculate efficiencies and install sensors there.
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Beyond Data Centers
AI can address the biggest challenge - climate change
![AI can address the biggest challenge - climate change]( "AI can address the biggest challenge - climate change")
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DeepMind stated it wouldn't stop with just Google's data centers.
The company added the "algorithm is a general-purpose framework" that helps to understand complex dynamics.
They intend to apply it to several other challenges beyond data centre environments in the future.
It said by using Artificial Intelligence to reduce energy consumption; one of the biggest challenges - climate change - can be addressed.
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Tackle some of the world's most challenging problems
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DeepMind wrote in its blogpost: "From smartphone assistants to image recognition and translation, machine learning already helps us in our everyday lives. But it can also help us to tackle some of the world's most challenging physical problems -- such as energy consumption."
