LAS VEGAS — Nvidia (NVDA) is touting its latest robotics advancements at CES 2026 as the broader tech industry begins a large-scale effort to bring humanoid robots to life.
During the company’s keynote on Monday, CEO Jensen Huang revealed that firms ranging from Boston Dynamics and Caterpillar (CAT) to LG Electronics and NEURA Robotics are using Nvidia’s robotics technologies to develop and power their various bots.
Nvidia has claimed that physical AI could revolutionize the $50 trillion manufacturing and logistics industries, and the company wants to be at the center of it all.
During CES, Nvidia revealed a variety of new AI models to help train robots to interact with the world around them, as well as the hardware necessary to power their digital brains.
In addition to humanoid bots, Nvidia showed off a new family of models for self-driving cars called Alpamayo. According to the company, Alpamayo uses a chain-of-thought reasoning-based vision language action (VLA) model.
That’s a lot to take in, but essentially the models can recognize unique driving situations that might not otherwise happen during a regular drive and come up with the proper way to move forward.
For instance, the model could see that a traffic light is out when a vehicle is approaching an intersection, recognize the problem, and try to figure out what to do next.
Nvidia said the models are meant to serve as “large-scale teacher models that developers can fine-tune and distill into the backbones of their complete [self-driving] stacks.”
In other words, Alpamayo is meant to help developers improve their self-driving vehicle technologies over time.
Nvidia said companies including Lucid (LCID), Uber (UBER), and Berkeley DeepDrive have shown interest in Alpamayo.
Self-driving vehicles are hitting roads around the world, with Google’s Waymo leading the way, but they’re still not perfect. Some cars have caused traffic jams and have gotten confused in certain situations.
Nvidia sees virtual training as a helpful solution for the continued development of the technology, allowing developers to teach their AI models without having to necessarily put cars on the road at all times.
