Uses Deep Learning To Teach Self-Driving Cars

Today, introduced its technology and strategy for the first time, opening a new chapter in the era of self-driving transportation. Founded in 2015 with a team of deep learning experts out of Stanford's Artificial Intelligence lab, is using unrivaled AI expertise to build the software necessary to power autonomous vehicles of the future. The company also announced the addition of Steve Girsky, noted for his leadership at General Motors over the past seven years, to its board of directors.'s strategy, revealed today, completely re-imagines existing approaches to self-driving using a full stack deep learning approach. Their integrated software and hardware system will enable vehicles to safely navigate any driving environment -- including urban, suburban, and freeway -- while communicating clearly with users, other drivers, and people outside the vehicle.

"Deep learning is the most effective form of artificial intelligence, and the best one capable of responding intelligently to the infinite situations cars face on the roads," said Sameep Tandon, CEO and co-founder of "Our founding team has been working on deep learning's applications to self-driving vehicles since its early stages. This is truly the enabling technology for the future of autonomous transportation, and we're leveraging it for navigation and interaction both inside and outside vehicles."

Building on this technical foundation, aims to create a robust new language of human-robot interactions -- essential for making people trust and welcome self-driving vehicles.

"Self-driving is not just a new feature on vehicles," said Carol Reiley, co-founder and president of "It's a once in a generation opportunity to reimagine the relationship between people, cars, and the world around them. At, we're focused on building a totally new language for vehicles, enabling them to show intent and interact in complex ways with humans inside and outside the car. Vehicles of the future...

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