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China's Didi Chuxing Teams Up with NVIDIA for Autonomous Driving and Cloud Computing

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【Summary】Chinese transportation giant Didi Chuxing, which is considered the “Uber of China”, is partnering with Nvidia on self-driving technology as well as cloud computing. At Nvidia’s GTC technology conference today in China, DiDi announced it will leverage NVIDIA GPUs and AI technology to develop autonomous driving and cloud computing solutions.

Eric Walz    Dec 17, 2019 8:00 PM PT
 China's Didi Chuxing Teams Up with NVIDIA for Autonomous Driving and Cloud Computing
A fleet of Didi Chuxing's self-driving development vehicles in China.

Chinese transportation giant Didi Chuxing, which is considered the "Uber of China" is partnering with Nvidia on self-driving technology as well as cloud computing. At Nvidia's annual GTC technology conference today in China, DiDi announced it will leverage NVIDIA GPUs and AI technology to develop autonomous driving and cloud computing solutions.

The technology will be used for an autonomous robotaxi service and other mobility technology Didi is currently developing in China. 

In August, DiDi spun out its autonomous driving unit into an independent company and began a wide range of collaborations with industry partners, the latest being Nvidia. Didi is plans to launch an autonomous ride-hailing service in Shanghai with plans to expand outside of China in 2021.

DiDi will use NVIDIA GPUs in the data center for training machine learning algorithms and NVIDIA's DRIVE platform for inference on its Level 4 autonomous driving vehicles. Developing and training deep neural network models quickly is key to delivering highly accurate perception systems so autonomous vehicles can make decisions in real-time, a critical part of navigation.

NVIDIA's inference platform using GPU's delivers the performance and responsiveness for running the next generation of AI-powered devices in the cloud or in the data center.

Some applications of deep-learning for self-driving cars are localization, mapping, sensor fusion and navigation. They can also be used for driver monitoring systems.

To support the massive amounts of AI processing used in DiDi's autonomous vehicles, NVIDIA DRIVE platform supports robust sensors fusion, allowing data to be fused from up to 16 vehicle sensors such as cameras, lidar, radar. The DRIVE platform incorporates numerous deep neural networks (DNNs) to understand the 360-degree environment surrounding the car.

"Developing safe autonomous vehicles requires end-to- end AI, in the cloud and in the car," said

Rishi Dhall, vice president of Autonomous Vehicles at NVIDIA. "NVIDIA AI will enable DiDi to develop safer, more efficient transportation systems and deliver a broad range of cloud services."

To train these DNNs, DiDi will use NVIDIA GPU data center servers to take advantage of their much higher processing capabilities. For cloud computing, DiDi will also build an AI-powered infrastructure and launch virtual GPU (vGPU) cloud servers for computing.

DiDi Cloud will adopt a new virtual GPU license mode to provide users with better experiences and more efficient, flexible GPU cloud computing services. Virtualizing a data center GPU allows it to be shared across multiple virtual machines, greatly improving system performance. 

Currently, DiDi Cloud is collaborating with industry partners including NVIDIA to provide services in transportation, AI, graphics rendering, video games and education. 

Didi Chuxing one of the world's transportation providers. The company completed 10 billion passenger trips last year across Asia, Latin America and Australia and its still growing. 

Didi is working toward the safe, large-scale application of autonomous driving technology, leveraging its own technology capacities, data resources and open collaboration with tech companies like Nvidia and various OEM partners.


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