NVIDIA demonstrated how artificial intelligence is influencing the direction of mobility at this year's IAA event. Beyond merely a technological advancement, the transition from cloud to automobile signifies a daring rethinking of safety, effectiveness, and innovation in the automotive sector. Watch the video presentation of this new technology and stay informed!
Pioneering the Road to Autonomous Driving.
NVIDIA is now empowering automakers globally to develop, test, and implement AI-driven cars that reimagine what it means to drive safely by fusing decades of experience in GPU processing, deep learning, and simulation technologies.
From AI Breakthroughs to Physical Intelligence.
Successive waves of AI research have cleared the way for self-driving cars. Robust picture categorization was made possible by convolutional neural networks like AlexNet, which marked the beginning of early developments in computer vision. The area moved from recognition to reasoning and content generation as a result of advances in generative AI and massive language models. The industry is currently entering the physical AI era, in which intelligent systems act in the real environment in addition to processing information.
This goes beyond perception for self-driving cars; it calls for precise action and safe decision-making, where every decision might have life-or-death repercussions.
Cloud-to-Car: A Complete AI Pipeline.
NVIDIA's involvement in the automobile industry goes well beyond the dashboard, despite the fact that many people only think of the company's in-car computers. NVIDIA offers complete development pipeline end-to-end solutions:
- High-performance, AI-driven inference systems that securely handle real-time data are known as in-car computing.
- Cloud training: Using large datasets, scalable infrastructure is used to train and improve AI models.
- Simulation and validation: Developers can safely test an infinite number of driving situations with the use of digital twins and synthetic data production.
- AI for factories and businesses: Resources to improve business efficiency throughout the automotive ecosystem, optimize assembly lines, and design automobiles.
Every model update and software enhancement is tested, verified, and smoothly delivered thanks to a continuous feedback loop that runs from the cloud to the vehicle.
Tackling the Long Tail of Driving Scenarios.
The so-called long tail problem—rare and unpredictable events that real-world data alone cannot capture—is one of the biggest obstacles in autonomous driving. It's impossible to compile enough real-world samples to cover every scenario, from strange automobiles or severe weather to luggage falling on a highway.
The three-pronged data strategy is NVIDIA's solution:
- AI that selectively records infrequent occurrences from moving automobiles.
- Real-world problems are simulated and recreated with more variation.
- Creation of synthetic data to cover gaps with situations that are lifelike and physically precise.
By converting thousands of hours of recorded driving into millions of hours of reliable training data, this method greatly increases the safety and resilience of autonomous systems.
The Cosmos AI Suite.
The so-called long tail problem—rare and unpredictable events that real-world data alone cannot capture—is one of the biggest obstacles in autonomous driving. It's impossible to compile enough real-world samples to cover every scenario, from strange automobiles or severe weather to luggage falling on a highway.
NVIDIA has released the Cosmos foundation models, a set of tools created especially for autonomous driving, to empower developers:
- For cars and other road actors, Cosmos Predict creates safe trajectory outputs.
- Cosmos Transfer: Creates photorealistic simulations using real-world sensor data, with variations for heavy traffic, snow, rain, and night.
- By adding chain-of-thought reasoning, Cosmos Reason improves user trust and safety by allowing cars to not only act but also provide an explanation for their choices.
When combined, these models give automakers a potent toolkit that enables them to develop, test, and improve AI systems at a never-before-seen scale and speed.
Redefining the Computer in the Car.
NVIDIA's Thor platform is a significant advancement in automotive computing at the hardware level. Thor is built to handle vision-language-action models with chain-of-thought reasoning while keeping up with the speed needed for cars traveling at highway speeds. It is powered by the Blackwell architecture and FP4 engines.
The Mercedes GLC, Volvo ES90, and Lucid Gravity are just a few of the next-generation automobiles from top automakers like Mercedes-Benz, Volvo, and Lucid that already use NVIDIA-powered technology.
Safety Above All: NVIDIA Halos.
Safety will always be the guiding concept of autonomous transportation, regardless of how strong AI gets. In order to create its Halos methodology—a comprehensive set of tools, SDKs, and simulation infrastructure intended for automotive-grade safety and security—NVIDIA has dedicated 15,000 man-years of engineering knowledge.
This comprises:
- Redundant sensors, including various camera systems, radar, and lidar.
- Runtime constraints that keep an eye on outputs and inputs to ensure dependability.
- Every function and line of code is checked for robustness using extensive validation pipelines.
NVIDIA celebrated earlier this year the introduction of a functionally safe Level 2+ stack on Mercedes-Benz cars in Germany. This is one of the few systems in the world, along with Tesla, that can drive from any location to any address.
Powering the Global Automotive Ecosystem.
NVIDIA works with almost all of the big names in autonomous driving, from Tesla and Waymo to top Chinese EV producers. NVIDIA guarantees that its partners have the resources they need to implement AI-defined mobility on the road more quickly and safely than ever before by providing a full-stack solution that covers cloud, simulation, and in-car computing.
About the Author.
This presentation was delivered at IAA by a senior NVIDIA executive specializing in autonomous driving and AI-defined mobility. With years of experience leading AI and automotive innovation, they continue to play a pivotal role in shaping the future of safe and intelligent transportation.
Watch the full video presentation below and learn in details The Future Of Safer AI-Defined Mobility:
Founded in 1993, NVIDIA is a global leader in accelerated computing. Best known for pioneering the GPU, the company has evolved into a powerhouse driving innovation in AI, simulation, robotics, and autonomous vehicles. Through its cutting-edge platforms and ecosystem of partners, NVIDIA is redefining industries and powering breakthroughs that move the world forward.
