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4 weeks ago
Traffic Prediction With Advanced Graph Neural Networks

 

By partnering with Google, DeepMind is able to bring the benefits of AI to billions of people all over the world.  From reuniting a speech-impaired user with his original voice, to helping users discover personalised apps, we can apply breakthrough research to immediate real-world problems at a Google scale. Today we’re delighted to share the results of our latest partnership, delivering a truly global impact for the more than one billion people that use Google Maps. 

Our collaboration with Google Maps

People rely on Google Maps for accurate traffic predictions and estimated times of arrival (ETAs). These are critical tools that are especially useful when you need to be routed around a traffic jam, if you need to notify friends and family that you’re running late, or if you need to leave in time to attend an important meeting. These features are also useful for businesses such as rideshare companies, which use Google Maps Platform to power their services with information about pickup and dropoff times, along with estimated prices based on trip duration.

Researchers at DeepMind have partnered with the Google Maps team to improve the accuracy of real time ETAs by up to 50% in places like Berlin, Jakarta, São Paulo, Sydney, Tokyo, and Washington D.C. by using advanced machine learning techniques including Graph Neural Networks, as the graphic below shows:

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