Baidu and Nvidia collaborate on world’s first map-to-car platform for autonomous vehicles

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A partnership between China’s most widely used internet services company and one of the world leaders in the development of computing systems for self-driving vehicles aims to use artificial intelligence (AI) in the creation of a cloud-to-car autonomous vehicle platform for local Chinese and global car makers.

The CEO of California-based Nvidia, Jen-Hsun Huang (below), together with Baidu’s CEO, Robin Li, announced the partnership at the Baidu World Conference in Beijing. The collaboration combines Baidu’s cloud platform and mapping technology with Nvidia’s self-driving computing platform to develop systems for HD maps, Level 3 autonomous vehicle control, and automated parking.

Baidu is hoping to use the platform created in tandem with Nvidia to roll out self-driving taxis in China. The company has been developing its own autonomous car deployment, and it plans on having a self-driving shuttle ready for public use by the end of 2018, with the new Nvidia partnership likely to accelerate the process. Baidu has previously stated its intention to start the mass production of autonomous cars within five years. Having established a headquarters in Sunnyvale, Baidu recently received approval to test its self-driving technology in California, which will accelerate its progress in the US market.

At Baidu World, Nvidia demonstrated DRIVE PX 2, the world’s first in-car AI supercomputer development platform, along with its DriveWorks software development kit (SDK), which gives developers a foundation to build applications that use computationally intensive algorithms for object detection, map localization, and path planning, which are essential ingredients for an autonomous car. From its origins as a developer of graphical processing units (GPUs) for the computer gaming industry, Nvidia CEO Huang detailed the company’s long history of AI collaboration with Baidu, citing the work done by Baidu’s chief researchers, such as Andrew Ng, who have used its GPUs to achieve some of the key breakthroughs in AI development.

“Baidu and Nvidia continue to share a common goal of using AI for the good of society. We can start applying these capabilities to solve the grand challenges of AI, one of which is intelligent machines,” said Huang. “One of the intelligent machines we would like to build in the future is the self-driving car. We’re going to bring together the technical capabilities and the expertise in AI, and the scale of two world-class AI companies, to build the self-driving car architecture from end-to-end, from top-to-bottom, from the cloud to the car. That means making driving safer, significantly reducing the number of traffic fatalities, while making transportation accessible to all, including the disabled, elderly and children. Developing a fully autonomous car is an end-to-end systems problem, from the in-car supercomputer, to AI algorithms, to an always-updated 3D map in the cloud. Developing a fully autonomous car is an end-to-end systems problem.”

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Tom has edited Traffic Technology International magazine and the Traffic Technology Today website since May 2014. During his time at the title he has interviewed some of the top transportation chiefs in charge of public agencies around the world as well as chairmen and CEOs of multinational transportation technology corporations. Tom's early career saw him working on some the UK's leading consumer magazine titles. He has a law degree from the London School of Economics (LSE).