raises $50 million in Series B funding led by NEA and GGV Capital, a self-driving car startup has raised $50 million in Series B funding. The funding was led by New Enterprise Associates (NEA) and GGV Capital. An existing investor Northern Light Venture Capital also participated in this round. This raised capital will bolster’s technology development, global reach, and scalability. raises  million in Series B funding led by NEA and GGV Capital

“ has an ambitious vision. Our company is out to transform the relationship between people, cars, and the world around them,” said Sameep Tandon, CEO and co-founder of “The self-driving race is a complex mix of technology, business models and policy. This funding from NEA and GGV Capital is massive validation of our vision, and gives us essential fuel for tackling all three components.” was founded in 2015 by young researchers from Stanford University’s Artificial Intelligence Lab, and specializes in deep learning-based driving software, developing for use in business, government and shared vehicle fleets. Soon, the kits will be deployed on existing business fleets, with pilots starting later this year.

The company has added Carmen Chang, chairman and head of Asia of NEA and Andrew Ng, a renowned deep learning expert who led artificial intelligence projects at Baidu and Google to its Board of Directors. In addition, Jenny Lee, managing partner of GGV Capital is joining as a board observer.

“Self-driving transportation is one of the most exciting and important innovations of our time,” said Chang. “To make self-driving a reality requires an understanding of technology, public policy, business and global society as a whole. deeply understands these requirements and has created a clear leadership position in the race to make self-driving a reality for the world. NEA is thrilled to partner with the talented team as they pioneer the self-driving future.”

“The cutting-edge of autonomous driving has shifted squarely to deep learning,” said Ng. “Even traditional autonomous driving teams have ‘sprinkled on’ some deep learning, but is at the forefront of leveraging deep learning to build a truly modern autonomous driving software stack.”