Autonomous Driving and Transportation
Fully autonomous and driver assistance technologies, powered by deep learning, have become a key focus for every car manufacturer, as well as transportation services and technology companies. The vehicle needs to know exactly where it is, recognize the objects around it, and continuously calculate the optimal path for a safe driving experience. This situational and contextual awareness of the car and its surroundings demands a powerful GPU computing systems that can merge data from cameras and other sensors, plus navigation sources, while also figuring out the safest path — all in real-time.
Data scientists in the transportation industry have been using GPUs for machine learning, such as the NVIDIA® Tesla® V100 GPU Acceletator, to make groundbreaking improvements across a variety of applications including image classification and processing, video analytics, and natural language processing. In particular, Deep Learning — the use of sophisticated, multi-level "deep" neural networks to create systems that can perform feature detection from massive amounts of unlabeled training data — is an area that has been seeing significant investment and research from autonomous driving and transportation applications.