Nvidia Declines After Suspending Self-Driving Car Testing

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Huang said the crash highlighted why companies are working to develop autonomous vehicles: reducing auto accidents that harm people and damage property.

"I believe as a result of what happened last week, the amount of investment into the seriousness of [autonomous vehicles] is going to go up", he said during a question-and-answer session with journalists at the company's GPU Technology Conference in San Jose, California today.

Arguments that the algorithm driving the Uber self-driving vehicle that struck and killed a pedestrian in Arizona this month may not have been at fault did not matter to Arizona Governor Doug Ducey, when he took away the company's ability to continue testing the technology in the state Monday, calling the incident "an unquestionable failure".

Nvidia is helping autonomous vehicle manufacturers fit in more testing miles, faster. "It's a reminder of how hard SDC technology is and that it needs to be approached with extreme caution and the best safety technologies", a Nvidia spokesperson said in an email.

Nvidia CEO Jensen Huang said today that the autonomous Uber crash in Tempe, Arizona last week would likely lead to more investment in self-driving cars, not less.

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"Ultimately AVs will be far safer than human drivers, so this important work needs to continue". In the meantime, until Nvidia can sign off on the safety of its self-driving auto technology, the company isn't willing to put lives at risk. We are temporarily suspending the testing of our self-driving cars on public roads to learn from the Uber incident.

Nvidia (NASDAQ:NVDA) announces the Drive Constellation system for running self-driving vehicle simulations. "Our global fleet of manually driven data collection vehicles continue to operate".

The simulation server is powered by NVIDIA GPUs, each one generating a stream of simulated sensor data, which then feeds into the DRIVE Pegasus for processing.

The technology is created to allow automakers and others to validate their technology on billions of driving miles and increase the strength of their algorithms by repeatedly testing hard scenarios, which would be impractical in the real world. "See the latest breakthroughs in self-driving cars, smart cities, healthcare, big data, high performance computing, virtual reality and more", writes the firm.

Testing may not involve putting self-driving cars on public streets, with all the safety issues that entails, but virtual environments aren't real ones, no matter how authentic the simulations seem.