Explore the critical role of high-performance, energy-efficient AI computing in developing autonomous vehicles. Learn how NVIDIA DGX Cloud enables scalable computing that facilitates efficient AI model training and supports real-time decision making. NVIDIA AI Enterprise provides developers with …

Join senior leadership from renowned automotive companies, including Jaguar Land Rover, Waabi, and Wayve as they discuss their experiences in incorporating Generative AI and industrial digitalization across their organizations. This session, moderated by NVIDIA, provides an exploration into the …

Developing AI for an autonomous vehicle software stack is a complex undertaking. Hear how leaders in the AV industry are approaching this challenge to deploy safe self-driving vehicles for transportation and delivery. This panel of experts discusses proven solutions to streamline AV development and …

Software-defined vehicles are transforming business models and the customer experience. To support this fundamental shift, metaverse applications for virtual collaboration and digital twin creation are helping automotive companies redesign the development process from vehicle design and …

Autonomous vehicles are born in the data center, where high-performance supercomputing accelerates deep neural network development, training, and testing. However, this AI infrastructure must be scalable in order to meet fast-paced industry timelines. Learn how the NVIDIA DGX SuperPOD delivers…

A primary challenge in developing autonomous vehicles is the complexity of the infrastructure and testing required to support AI development. This session provides insights and expertise from NVIDIA's AV training and testing efforts on NVIDIA DGX SuperPOD, including AI infrastructure at scale, …

Drive Infrastructure is a complete workflow platform addressing many areas of the AV development lifecycle including data ingestion, curation, labeling, training, validation through simulation, replay, and synthetic data generation. This session will talk about how the DGX SuperPOD will help simplify and …

Developing, training, and testing AI for autonomous driving is an extremely complex and costly effort. NVIDIA DRIVE Infrastructure accelerates end-to-end AI platform development for AVs, encompassing the data center hardware, software and workflows needed to develop and validate self-driving technology…

Developing AVs is a time-intensive and complex process that requires best-in-class AI training infrastructure. Companies developing software-defined vehicles need to accelerate time to market and minimize costs without sacrificing safety.This webinar examines how to best leverage NVIDIA AI-…

Autonomy software is artificial intelligence for the physical world: recreating a human driver using a combination of software and hardware. Powered by AI, our vehicles independently navigate the ever-changing world safely and reliably. Teaching our driverless vehicles to navigate public roads has been…

Simulation is critical for autonomous vehicle development. However, the need for high-fidelity, physically based simulation has created challenges in both accessibility and scalability. CARLA is an open-source simulator widely used by developers, researchers, and engineers across the AV industry.…

Learn how NVIDIA Omniverse brings together the AV ecosystem to address the challenges of achieving scalable, high-fidelity simulation. In this session, we'll cover how Omniverse enables core technologies, such as physically based sensor simulation, realistic physics, and behavior modeling, for developers …