How is Nvidia’s Drive PX different from its peers?



Nvidia Drive PX’s approach is unique

Nvidia’s (NVDA) Drive PX is different from its peers, as it takes a fundamentally different approach to the auto pilot. The technology uses 12 cameras and a “Deep Neural Network” in tandem. Thus, the Drive PX is able to recognize various objects on the road, ranging from pedestrians to cars.

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Nvidia’s neural network sets it apart from its peers

The unique feature about Nvidia’s Drive PX is instead of using lasers, radars, and ultrasound in order to detect obstacles, its neural network forms the base of its technology.

The Drive PX is constantly updated, so if a car doesn’t recognize an object, or if the object turned out to be something different than what the system originally suspected, the Drive PX sends the image date to Nvidia. Nvidia then processes it and adds the link to the next update of the Drive PX system. Thus if one car on the road doesn’t recognize a situation, that knowledge then gets contributed to the brains of every car using the system.

The best part about this deep learning system is it is fully automated. Currently, a car can get sufficient training in about 40 hours. In the past, training required months or even years. With customers like Volkswagen, Honda (HMC), BMW (BMW), and Audi, Nvidia already has a strong presence in the automotive market.


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