On Tuesday, NVIDIA unveiled the world's first artificial intelligence (AI) computer designed to drive fully autonomous vehicles by mid-2018.
The new system, named Pegasus, extends the NVIDIA Drive PX AI computing platform to operate vehicles with Level 5 autonomy—without steering wheels, pedals, or mirrors. Pegasus delivers more than 320 trillion operations per second, or more than 10x the performance of its predecessor, according to NVIDIA.
Some 25 partners are currently developing fully autonomous taxis using the NVIDIA technology, according to a press release. These vehicles could arrive on demand to safely drive passengers to their destinations, bringing mobility to more people and allowing professionals to get work done while commuting. They will also feature interiors that feel more like a living room or office than a traditional car.
Currently, the trunks of these vehicles resemble small data centers, NVIDIA noted in the release, complete with racks of computers with server-class NVIDIA GPUs running deep learning, computer vision, and parallel computing algorithms. Since this is impractical for most vehicles, Pegasus aims to make autonomous driving tech more manageable for production deployment, and fit the needed computational power into the size of a license plate.
SEE: IT leader's guide to the future of autonomous vehicles (Tech Pro Research)
Pegasus will be available to NVIDIA's automotive partners in the second half of 2018, the press release said.
"Creating a fully self-driving car is one of society's most important endeavors — and one of the most challenging to deliver," said Jensen Huang, NVIDIA founder and CEO, in a press release. "The breakthrough AI computing performance and efficiency of Pegasus is crucial for the industry to realize this vision."
If it comes to fruition, the technology could speed the use of autonomous vehicles in the trucking and ridesharing industries, as well as among consumers, potentially disrupting many facets of the auto industry.
"Driverless cars will enable new ride- and car-sharing services. New types of cars will be invented, resembling offices, living rooms or hotel rooms on wheels. Travelers will simply order up the type of vehicle they want based on their destination and activities planned along the way," Huang said in the release. "The future of society will be reshaped."
Nvidia's claim is "credible and realistic," Vivek Wadhwa, a distinguished fellow at Carnegie Mellon University's College of Engineering and author of The Driver in the Driverless Car: How Our Technology Choices Will Create the Future, told TechRepublic.
"I know the folks at Nvidia and that they have been looking to develop the next set of technologies that take AI to the next level," Wadhwa said. "Just as their first GPU enabled the development of neural network-based AI technologies, these new technologies are likely to put it on steroids."
The technology could give them an edge over other players developing self-driving technologies due to the ability to process massive amounts of data in the cars themselves, versus on servers, Wadhwa said.
"Self-driving cars are going to impact many industries," Wadhwa said. "They are closer to reality than most people seem to think."
However, it's important to remember that this is a processing platform, Bryant Walker Smith, an assistant law professor at the University of South Carolina and an expert on the law of driverless vehicles, told TechRepublic. It may have the processing power, speed, and reliability needed for more sophisticated automated driving, but it is not in and of itself an automated driving system, he added.
"The company hasn't claimed to have developed all the software, hardware, and data needed for automated driving; it's merely announced that it plans to market a chip that in theory could support the hardware and software envisioned for such a system," Walker Smith said. "That's a big difference."
Further, Tesla's announcement earlier this year that it had created automated driving-ready hardware was similarly misunderstood, as the company still does not have the software ready, Walker Smith said.
Forrester analyst Laura Koetzle agreed that it will take time for these systems to actually get into production cars. Plus, it must be legal for these vehicles to be used in autonomous mode on public streets, and they will also need to undergo trials.
Koetzle added that the earliest estimate she's seen for level 5 autonomous vehicles operating on the roads is 2025 in the UK.
"So don't expect to see level 5 autonomous vehicles with the new Nvidia technology roaming the streets in the back half of 2018," Koetzle said. "If you live near Singapore one north, the business district where the Grab Taxi/NuTonomy pilot is running, you might, but there'll likely be engineers on board each vehicle monitoring its every move."
The 3 big takeaways for TechRepublic readers
1. On Tuesday, NVIDIA unveiled what it called the world's first AI computer that will power fully autonomous cars.
2. Some 25 auto partners are currently developing fully autonomous taxis using the NVIDIA technology, which will be available in the second half of 2018.
3. If the technology works to its full potential, it could speed the use of autonomous vehicles in the trucking and ridesharing industries, but experts are divided on its potential in the market.
- 81% of Americans believe driverless vehicles will kill jobs for professional drivers (TechRepublic)
- Our autonomous future: How driverless cars will be the first robots we learn to trust (PDF download) (TechRepublic)
- Autonomous driving will spawn $7 trillion 'passenger economy': Intel (ZDNet)
- 'AI as co-pilot': The state of autonomous driving, from the auto world's headquarters in Detroit (TechRepublic)
- Intel, Waymo partner to work on fully autonomous cars (ZDNet)
- Updated: Autonomous driving levels 0 to 5: Understanding the differences (TechRepublic
Alison DeNisco Rayome has nothing to disclose. She does not hold investments in the technology companies she covers.
Alison DeNisco Rayome is a Staff Writer for TechRepublic. She covers CXO, cybersecurity, and the convergence of tech and the workplace.