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NVIDIA's infrastructure for autonomous vehicles encompasses the complete data center hardware, software, and workflows needed to develop safe autonomous vehicles—from neural network development and training to testing and validation in simulation.
Autonomous vehicles generate terabytes of data daily from sensors like cameras, lidar, and radar. This data has to be processed, labeled, and used for training AI models.
Sensor data, system logs, and other records can be replayed to recreate the conditions, enabling problem diagnosis and root cause identification.
AV systems need to improve over time, learning from new data and scenarios to refine their decision-making algorithms.
This system powers high-fidelity autonomous vehicle sensor simulations, helping you test and validate complex scenarios at scale.
Announcements
NVIDIA Cosmos™ is a platform comprising state-of-the-art generative world foundation models, advanced tokenizers, guardrails, and an accelerated video processing pipeline built to accelerate the development of physical AI systems such as autonomous vehicles and robots.
NVIDIA showcased accelerated computing and generative AI breakthroughs for autonomous vehicle development at the Computer Vision and Pattern Recognition conference.
NVIDIA platforms are built with safety at their core, prioritizing robust training, simulation, and real-time decision-making to ensure smarter, safer transportation for everyone.
The NVIDIA DRIVE™ team is constantly innovating, developing end-to-end autonomous driving solutions that are transforming the industry.
Join this webinar to learn how NVIDIA DGX™ Cloud provides high-performance computing at scale, and how NVIDIA AI Enterprise provides access to hundreds of AV frameworks.
Gain insights from NVIDIA's AV training and testing efforts on NVIDIA DGX SuperPOD™, including AI infrastructure at scale, overcoming data management challenges, and MLOps.
Hear how NVIDIA is developing autonomous vehicles and training neural networks to let AVs perceive and react to their environments.
Find out how you can start developing AI-powered autonomous vehicles.