NVIDIA WEBINAR
Accelerating Autonomous Vehicle Development at Scale with NVIDIA on AWS
Offer
Developing, training and testing AI for autonomous driving requires the ability to manage massive amounts of data at scale. In this session, learn about hardware and software technologies that help accelerate end-to-end AI platform development for autonomous vehicles.
By attending this webinar you’ll learn how:
- New breakthroughs in both software and hardware, including the recently announced NVIDIA A100, are enabling one unified compute platform for data collection, model training and testing via RePlay – while delivering significant performance gains that shorten AV development cycles.
- Further testing in simulation on the NVIDIA DRIVE Constellation and DRIVE Sim platform allows for a comprehensive validation methodology, including planning and control, software-in-the-loop (SIL), and hardware-in-the-loop (HIL) testing.
- To tune your cloud deployments for end-to-end AV development, testing and deployment of smart, safe, self-driving cars.
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DGX Station Whitepaper
Dive deeper into the DGX Station and learn more about the architecture, NVLink, frameworks, tools and more.
Dive deeper into the DGX Station and learn more about the architecture, NVLink, frameworks, tools and more.
DGX Station Whitepaper
Dive deeper into the DGX Station and learn more about the architecture, NVLink, frameworks, tools and more.
Dive deeper into the DGX Station and learn more about the architecture, NVLink, frameworks, tools and more.
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Speakers
Norm Marks
Global Sr. Director, Automotive Enterprise, NVIDIANorm Marks is senior director responsible for driving NVIDIA’s global Automotive industry enterprise go-to-market strategy. Marks is focused on establishing areas of application for how deep learning, data science and artificial intelligence, enabled by a new GPU computing revolution, will transform the Automotive and Transportation industry. He speaks frequently on topics around Autonomous Vehicles ranging from AI / Deep Learning, Data Factory, Validation, Simulation and RePlay, as well as the Connected Vehicle, Smart Mobility and Connected Factory.
Marks earned his Bachelor of Science degree in Business Administration from Bowling Green State University, and continued his studies, completing the rigorous Executive Management Program at Stanford’s Graduate School of Business.
Shyam Kumar
Global BD Lead, HPC & Autonomous Vehicles, AWSShyam is on the High Performance Computing (HPC) specialist organization at Amazon Web Services (AWS) and leads the Business Development activities and Go-To-Market (GTM) strategy for the Autonomous Vehicles (AV) segment. In this role, he helps Automotive OEM's, Tier-1's and Startups leverage the elasticity, scale and technical capabilities of AWS to innovate faster and accelerate their AV development process. Shyam has a Master's degree in Mechanical Systems Engineering, and has held various technical, business development, and sales leadership roles in multiple industries over the course of his career with a focus on engineering simulations and scientific computing.
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