Nvidia Unveils New AI Models for Robots and Self-Driving Vehicles
Nvidia unveiled a broad set of robotics and autonomous driving developments at CES 2026, outlining how its AI models, simulation software, and hardware are being used to accelerate the deployment of humanoid robots and self-driving vehicles.
During the event, Nvidia said its robotics technologies are already being adopted by a growing number of industrial and technology firms, highlighting the company’s expanding role beyond semiconductors and into physical AI systems that operate in real-world environments. CEO Jensen Huang said these systems could have a major impact on manufacturing and logistics, industries the company estimates to be worth roughly $50 trillion.
Key Takeaways
- Nvidia announced new robotics and autonomous driving technologies at CES 2026.
- Industrial and robotics companies are already using Nvidia’s AI models and simulation tools to develop humanoid and industrial robots.
- Simulation-based training is becoming central to how robots and self-driving systems are developed.
- Nvidia’s new Alpamayo models aim to improve how autonomous vehicles handle rare and complex driving situations.
Robotics adoption expands across industries
Nvidia said companies ranging from Boston Dynamics and Caterpillar to LG Electronics and NEURA Robotics are using its AI models and simulation platforms to develop robots capable of navigating complex environments and performing tasks that require perception, reasoning, and physical interaction.
According to the company, these tools are helping move humanoid and industrial robots closer to commercial deployment by reducing reliance on physical trial-and-error and enabling large-scale virtual training.
Virtual training becomes central to robot development
A major focus of Nvidia’s announcements was simulation-based training. The company introduced new AI models designed to teach robots how to interpret their surroundings and respond to real-world conditions inside virtual environments.
Nvidia said this approach allows developers to expose robots to rare or dangerous scenarios that would be difficult or impractical to recreate in the physical world. By training extensively in simulation, robots can enter real environments better prepared, shortening development timelines and lowering costs.
New AI models target autonomous driving edge cases
In addition to robotics, Nvidia introduced Alpamayo, a new family of AI models aimed at improving self-driving systems. The models use a vision-language-action framework to help autonomous vehicles recognize and reason through uncommon or ambiguous driving situations.
Rather than serving as a complete driving system, Alpamayo is designed as a large-scale teacher model that developers can fine-tune and integrate into their own autonomous stacks. Nvidia said the models can help vehicles respond to scenarios such as malfunctioning traffic signals or unexpected road conditions.
Companies including Lucid, Uber, and Berkeley DeepDrive have expressed interest in using Alpamayo to enhance their autonomous driving technologies.
Why Nvidia is emphasizing simulation
While autonomous vehicles are already operating in limited deployments, led by platforms such as Waymo, the technology continues to struggle with rare and unpredictable situations. Nvidia said simulation offers a scalable way to train AI systems for these edge cases without relying solely on real-world driving data.
Taken together, Nvidia’s announcements point to a broader strategy: positioning the company as a core technology provider for robotics and autonomous systems. By combining AI models, simulation tools, and specialized hardware, Nvidia is aiming to support the next phase of machines that can perceive, reason, and act in physical environments.
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