In an exciting development for the future of transportation, Uber and Nvidia have announced their partnership to create a fleet of 100,000 robotaxis. At Nvidia’s inaugural GTC AI conference in Washington D.C., CEO Jensen Huang expressed optimism about this venture, stating, “This is going to be a new computing platform for us, and I’m expecting it to be quite successful.”
This ambitious project is set to launch in 2027, with Nvidia aiming to roll out the entire fleet. While their target is impressive, it’s important to note that competitors like Waymo currently operate around 2,000 robotaxis. Yet, industry leaders like Elon Musk of Tesla have even grander dreams, with plans for “millions of Teslas operating autonomously” by the end of next year.
What Technology Powers These Robotaxis?
The innovative technology behind Uber’s robotaxis leverages Nvidia’s Drive AGX Hyperion 10 in-vehicle computer. This advanced system is designed to facilitate level-4 automation, allowing vehicles to drive themselves without a driver ready to intervene, within specified areas. While this is a significant milestone, achieving true fully autonomous driving without any boundaries remains a challenge not yet conquered by any company.
As Huang aptly put it, “Human robots are still in development, but meanwhile, there’s one robot that is clearly at an inflection point, and it is basically here, and that is a robot on wheels.”
How Will This Fleet Ensure Safety?
Nvidia’s safety protocols are impressive. Ali Kani, the vice president of automotive at Nvidia, emphasized that the entire system is structured to ensure that if any sensor or computer encounters a problem, the vehicle can safely come to a stop. Huang praised the sophisticated sensor suite, which includes surround cameras, radars, and lidar, enabling a comprehensive safety net for passengers.
Who Will Build the Robotaxi Fleet?
Unlike other competitors, Uber will serve exclusively as an autonomous ride-hailing service and will not produce the vehicles. Instead, they will collaborate with automotive partners such as Stellantis, Mercedes-Benz, and Lucid Motors to build the fleet. Huang noted, “We created this architecture so that every car company in the world could create cars. Vehicles could be commercial, could be passenger, dedicated to robotaxi.”
What Other AI Developments Are Happening?
In addition to the robotaxi project, Nvidia is establishing a joint AI data factory based on its Cosmos framework, aimed at training humanoid robots. This move comes in light of increasing competition, with GM recently announcing ambitions for hands-free and “eyes-off” electric vehicles by 2028, generating significant buzz among investors.
Earlier this year, at Nvidia’s GTC in San Jose, Huang revealed that GM would utilize the Drive AGX platform for its forthcoming self-driving vehicle fleet. Following GM’s latest announcements, Elon Musk reassured Tesla investors during an earnings call that the company is experiencing substantial progress in its AI and autonomous driving projects.
How far along is Uber in developing its robotaxi service? While they are aiming for a fleet of 100,000 vehicles, the rollout timeline remains unconfirmed. However, their focus on collaboration and cutting-edge technology indicates a promising future.
What sets Nvidia’s Drive AGX Hyperion apart from competitors? The platform is built for achieving high levels of automation, incorporating extensive safety mechanisms and a robust sensor suite.
Are robotaxis safe for public use? With advanced safety protocols and technology designed to address failures, Uber’s robotaxis prioritize passenger safety as a top concern.
What role do auto manufacturers play in this project? Manufacturers like Stellantis and Mercedes-Benz are responsible for building the actual robotaxis, while Uber focuses on the ride-hailing network.
In conclusion, the partnership between Uber and Nvidia marks a significant step toward the future of transportation. Stay updated on exciting developments in this field and explore more about emerging technologies at Moyens I/O.