Exciting Google AI Applications in the Real World

Acquired by Google in 2014, DeepMind is now a critical part of the organization, helping to solidify its leadership in the AI industry. (Image: Screenshot / YouTube)
Acquired by Google in 2014, DeepMind is now a critical part of the organization, helping to solidify its leadership in the AI industry. (Image: Screenshot / YouTube)

Google’s DeepMind first grabbed world attention when one of its AIs beat a human in the game of Go in 2015. Until then, it was said to be an impossible feat. Acquired by Google in 2014, DeepMind is now a critical part of the organization, helping to solidify its leadership in the AI industry.

Data center cooling

An AI developed by DeepMind has been implemented by Google to prevent data centers from overheating. The system has been giving cooling recommendations to the company data center management team since 2016 and is said to have reduced energy usage by about 40 percent.

“Now, we’re taking this system to the next level: Instead of human-implemented recommendations, our AI system is directly controlling data centre cooling, while remaining under the expert supervision of our data centre operators. This first-of-its-kind cloud-based control system is now safely delivering energy savings in multiple Google data centres,” according to the DeepMind blog.

AI checks data from the cooling systems every five minutes and predicts the series of actions that will get the job done while conserving as much energy as possible. While Google operates one of the most energy-efficient data centers in the world, the company hopes that AI will help reduce carbon emissions even further.

data center

AI checks data from the cooling systems every five minutes and predicts the series of actions that will get the job done while conserving as much energy as possible. (Image: Screenshot / YouTube)

Healthcare revolution

DeepMind is also developing an AI that analyzes 3D scans of eyes, identifies common diseases, and recommends an appropriate treatment. The research is being carried out in collaboration with UCL and Moorfields Eye Hospital. Almost 15,000 OCT scans from 7,500 patients were used to train the AI. In a comparison with regular doctor recommendations, it was found that the AI had given the same judgments as doctors 94 percent of the time.

“While the software is not ready for clinical use, it could be deployed in hospitals in a matter of years. Those involved in the research described it as ‘ground-breaking.’ Mustafa Suleyman, head of DeepMind Health, said in a press statement that the project was ‘incredibly exciting’ and could, in time, ‘transform the diagnosis, treatment, and management of patients with sight threatening eye conditions […] around the world,’” according to The Verge.

eye condition

DeepMind is also developing an AI that analyzes 3D scans of eyes, identifies common diseases, and recommends an appropriate treatment. (Image: Screenshot / YouTube)

In collaboration with the Cancer Research UK Centre at Imperial College London, DeepMind is using machine learning to train AI to detect instances of breast cancer. Mammograms of 7,500 women have been fed into the AI. The company is also working with the U.S. Department of Veterans Affairs to predict deterioration in patients.

Energy management

DeepMind is in talks with Britain’s National Grid to implement AI that will manage energy distribution in the UK. “We are in the very early stages of looking at the potential of working with DeepMind and exploring what opportunities they could offer for us… We are always excited to look at how the latest advances in technology can bring improvements in our performance, ensure we are making the best use of renewable energy, and help save money for bill payers,” National Grid said to City AM.

Given that Google reduced the energy required for cooling its data centers by 40 percent and overall energy usage by 15 percent through the use of AI, DeepMind is hopeful that the same technology can be implemented on a larger scale at the National Grid to match supply with demand and drastically reduce electricity wastage.

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