Nvidia GTC GTU Tech Conference set (virtually only)

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Danny Shapiro, Senior Director of Automotive at Nvidia Corporation in Santa Clara, is as knowledgeable as anyone in the autonomous automotive segment. It’s a good thing because the industry is accelerating as quickly as a Tesla.

The autonomous driving future is among the more recent challenges for Nvidia, which started in the gaming industry. But the technology company is at the forefront of delivering solutions to automakers for self-driving cars, infotainment, digital instrument clusters, rear-seat entertainment and advanced driver assistance systems.

Dany Shapiro discusses Nvidia and the 2020 GTC Technology Conference.
Dany Shapiro discusses Nvidia and the 2020 GTC Technology Conference in this episode of The Weekly Driver Podcast.

Not much of the ever-changing automotive technology world won’t be examined in Nvidia’s GTC GTU Technology Conference. It’s just that this year, it will be a virtual conference.
Conference organizers, citing the uncertainty of the coronavirus, have changed the conference into a digital presentation rather than a live event. The event was scheduled March 22-26 at the San Jose McEnery Convention Center.

Details are pending, but conference spokesperson Dave Jasmin said the keynote speech, as well as other presentation details, will be posted on the website www.nvidia.com. Refunds will be applicable.

The digital conference will address the same issue. What and where is the future of autonomous driving? How safe is it? How intense is the competition in the Silicon Valley marketplace and China, the industry’s international hub?

“Incredible advancements are going on in the transportation industry, but it’s not just cars,” said Shapiro of the pending gathering of industry experts who’ll discuss all things related to the future of autonomous vehicles.

“It’s trucks, construction vehicles, agriculture, mining and transportation of goods, delivery, etc. It’s the future of these vehicles that could have no pedals.”

Since 2014, Nvidia has diversified its business focusing on four markets: gaming, professional visualization, data centers and auto. Nvidia is also now focused on artificial intelligence.

In addition to manufacturing, Nvidia provides parallel processing capabilities to researchers and scientists that allow them to efficiently run high-performance applications. They are deployed in supercomputing sites around the world.

A more than 25-year veteran of the computer graphics and semiconductor industries, Shapiro has degrees in electrical engineering, computer science and business administration from Princeton and UC Berkeley.

He’s keen on the solutions that will enable faster and better design of automobiles, as well as in-vehicle solutions for infotainment, navigation and driver assistance.

“We are working with a number of companies who are developing what’s being called Robotaxis,” said Shapiro. “Think of it as your Uber or Lyft but there’s nobody behind the wheel. You will summon it with an app and it will show up.

“You will be able to get inside and it will take you where you need to go. These vehicles are going to safer than any human driver vehicle. They are no point to get distracted or drowsy. There’s no driving under the influence.”

While manufacturers — Toyota to Volvo to Mercedes-Benz — have been involved in the future of autonomous driving for years, Shapiro echos what other industry analysts believe. Introducing the concept to the driving public is a more difficult task than first anticipated.

“The industry and the reports in the media really underestimated the complexity of what we are trying to solve,” said Shapiro. “It is a massive computing problem. It’s a massive artificial intelligence challenge. I think the original estimates were a little aggressive. But the development is happening rapidly.”

Ever-changing and advancing software to predict the unpredictable in the real world driving remains the biggest challenge. It will be the focus of the companies, exhibitors, panel leaders and workshops throughout the conference.

“There’s really no end in sight in terms of the complexity of everything you need to detect,” said Shapiro. “So we’re are working on a computer model of how the brain works. Just like a human learns over time, well, a child doesn’t know much, so you teach them, they learn and they remember.”

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