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Vishal Dhupar, NVIDIA, talks about autonomous cars and more

Vishal Dhupar - NVIDIA
Vishal Dhupar, Managing Director, NVIDIA – South Asia

Vishal Dhupar, Managing Director, NVIDIA – South Asia shares his views about autonomous cars and more.

Vishal Dhupar has served as NVIDIA’s managing director in South Asia since 2010, leading business operations for the company in the region. In this role, Vishal is responsible for the development and execution of NVIDIA’s strategic plans in the subcontinent. He is also keenly focused on fostering key partnerships with the ecosystem to accelerate the growth and adoption of GPU technology.

With more than 25 years in the Information Technology industry, Vishal brings extensive leadership and industry
experience.

An expert in the area of change management, he played an active role in understanding and applying change in accordance with the business requirements during the Symantec-Veritas merger, specific to India

TW: Can you tell us about your self-driving car? Will you be launching your own self-driving vehicle or use the learning to improve your offerings as Tier1 Company?

Vishal Dhupar: Autonomous cars represent a dominant and unstoppable trend in the motor industry. For users, this will make driving safer, more convenient and less stressful than ever before.

But a new generation of super-smart cars requires serious Artificial intelligence. To deal with all the stuff a car sees on the road, you need a new kind of technology called ‘Deep learning’, which is at the core of the autonomous car’s development.  A part of Artificial Intelligence, DL allows computers to perform tasks for which they have not been specifically programmed. Thanks to a processor called the Graphics Processing Unit (GPU), originally developed to power video games, deep learning is accelerated for real-world deployment. Large amounts of training data are fed through sophisticated algorithms to build Deep Neural Networks (DNN), which are complex mathematical models which mimic the human brain.

NVIDIA offers an end-to-end mapping technology for self-driving cars, designed to help automakers, map companies, and startups rapidly create HD maps and keep them updated. This state-of-the-art technology uses an NVIDIA DRIVE PX 2 AI supercomputer in the car, coupled with NVIDIA Tesla GPUs in the data center, to create highly detailed maps. For automotive developers, this same architecture used to create maps and keep them up-to-date ultimately enables self-driving cars to operate safer.

TW: NVIDIA is working with Tier1 and automotive companies like Bosch, VW, Audi, Mercedes, Baidu, Tesla on various projects related to autonomous vehicles. Can you share your views on this? How does NVIDIA maintain the privacy of the companies in terms of technology, while working closely with them?

Vishal Dhupar: NVIDIA has entered into several partnerships with the automotive supply chain to bring fully autonomous cars on the road, as this requires work at various levels, from auto OEMs (original equipment manufacturer) to automakers to cloud-mapping solutions. Some of NVIDIA’s auto partners include Tesla, Audi, Bosch, Mercedes-Benz, ZF, Baidu, Volvo, and PACCAR.

NVIDIA gives automakers, tier-1 suppliers, automotive research institutions, and start-ups the power and flexibility to develop and deploy breakthrough artificial intelligence (AI) systems for self-driving vehicles. NVIDIA’s unified AI computing architecture enables training deep neural networks in the data center on the NVIDIA DGX-1™, and then seamlessly runs them on NVIDIA DRIVE PX 2 inside the vehicle. This end-to-end approach leverages NVIDIA DriveWorks software and allows cars to receive over-the-air updates to add new features and capabilities throughout the life of a vehicle.

While we are working with many Tier 1s and carmakers on self-driving solutions, that doesn’t mean that all their autonomous solutions will be identical. As with any business relationship, we maintain strict confidentiality with our customers. It’s likely that, in the future, cars may even differentiate based on the character of their autonomous driving functionality.

TW: Could you tell us more about AI self-driving car computer being developed jointly with Bosch?

Vishal Dhupar: In an announcement at Bosch Connected World in Berlin, Germany, NVIDIA and Bosch revealed the collaboration on an onboard computer capable of running the AI necessary for self-driving.

Based on NVIDIA’s Drive PX technology—which also powers semi-autonomous Teslas—the Bosch will also use NVIDIA’s forthcoming “Xavier” AI system-on-chip. NVIDIA says that Xavier is capable of 20 trillion operations per second while drawing just 20 watts of power, meaning the Bosch car computer should be smaller and cheaper than NVIDIA’s current Drive PX 2 unit. Using DRIVE PX AI car computer, Bosch will build automotive-grade systems for the mass production of autonomous cars.

These sorts of supplier deals will eventually lead to a large market of cars that promise to drive themselves down the highway.

TW: Some companies are predicting 2021 will be the year when autonomous cars can be launched into the commercial market. What are your views?  

Vishal Dhupar: Data gathering and analysis, artificial intelligence and the speed of innovation are some of the new areas on the OEM’s agenda. Safety must continue to be primary to the carmaker’s approach, but it will also require a robust technology strategy—one that will ultimately lead to self-driving cars. The powerful and versatile nature of our graphics processing unit (GPU) is making autonomous vehicles a reality.

Audi has announced that, by 2020, it will release an ‘AI car’ powered by the NVIDIA DRIVE PX2 in-car supercomputer. This model will achieve Level 4 autonomy, meaning the car is able to drive itself in all but the most extreme environments.

NVIDIA claims PX2 can perform 24 trillion deep learning operations per second—enough to make a Level 4 automated car a reality. Research already indicates that half of those who buy luxury cars would choose self-driving features. It won’t be long before they become mainstream offerings. In as little as two years, self-driving features will become as ubiquitous as airbags or ABS. And, like these now-standard features, we’ll wonder how we ever managed without them.

TW: There have been a lot of M&A (merger and acquisition) activity in the automotive market, (Intel acquires Mobileye, Samsung acquires HARMAN, and NXP acquires Freescale and then Qualcomm acquiring NXP) Do you think we are into the consolidation or are we preparing for disruption?

Vishal Dhupar: The strong growth opportunity in the self-driving car space has attracted semiconductor giants Intel (INTC) and Qualcomm (QCOM). Intel has acquired ADAS (advanced driver assistance systems) leader Mobileye (MBLY) for $15.3 billion, and Qualcomm is acquiring the world’s largest automotive semiconductor supplier, NXP Semiconductors (NXPI), for $47 billion.

Computing companies have an increasingly important role to play in the automotive space as your car becomes your most important piece of consumer technology. We expect to see the relationship between Silicon Valley and car manufacturers continue growing closer in the future.

TW:How will the connected world (IoT/M2M driven) impact automotive sector?

Vishal Dhupar: Connected vehicles will be an important trend but it’s critical that self-driving cars are able to function in situations where connectivity is lost. Losing your cell signal in the middle of your call is annoying, not life critical. An autonomous vehicle that relies on connectivity to drive could have much more serious consequences if the signal fails.

That’s why NVIDIA’s approach focuses on placing the power of a supercomputer inside the vehicle, within a package the size of a license plate that sips power. While the car’s connection to the cloud will be important as software updates begin to dictate functionality within the vehicle, the ability to handle the computational demands of AI without connectivity is vital.

 

About Piyush Rajan

Asst. Business Editor |Telematics Wire | Smart automotive

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