Similar to how ChatGPT uses massive language models to understand and respond intelligently, Cosmos provides robots with foundation models that help them navigate, interact, and adapt to real-world environments.
Last year in July we posted an article titled “Nvidia Project GR00T.” In it we talk about Nvidia’s Generalist Robot 00 Technology powered by the Blackwell chip and how it enables robots to mimic humans purely by observation. This new update from Nvidia, however, is next level, and many are even referring to it as a “ChatGPT” moment for robotics.
The NVIDIA Cosmos platform was unveiled at CES 2025 by Jensen Huang during his keynote speech. In it, he described the platform quite simply as a transformative tool for developing physical AI systems. While that doesn’t really sound like a eureka moment, it is. Nvidia Cosmos utilizes what’s known as world foundation models to simulate real-world conditions that allow developers to test AI systems in sandboxes, also referred to as staging, or virtual environments.
Physics-Aware AI Systems
World Foundation Models (WFMs) are advanced neural networks designed to simulate real-world environments. They can also be used to predict outcomes based on various inputs. Now unlike Large Language Models where everything revolves around communication and language, these models are geared towards Physical AI systems like robots and autonomous vehicles.
So when we say Cosmos provides users with virtual testing grounds, what we mean is virtual testing grounds that accurately reflect real-world physics, like a Matrix for Robots. So while traditional AI development relies on extensive real-world data collection and testing, Cosmos’ WFMs relies on what’s being called “physics-aware” synthetic data and that’s what allows them to conduct simulations that successfully mimic real-world conditions.
Now before Cosmos, developing robotic AI was a massive expense requiring gigantic volumes of real-world data, expensive hardware, and years of testing. With Cosmos, however, developers can build and refine AI models without any of the above. Similar to how ChatGPT uses massive language models to understand and respond intelligently, Cosmos provides robots with foundation models that help them navigate, interact, and adapt to real-world environments, most importantly, without needing to be programmed for every specific task.
That’s a game changer since instead of robots having to learn everything through trial and error in a physical space, they can now be trained in hyper-realistic simulations using Omniverse. Sort of like teaching pilots to fly in simulators before putting them in an Airbus full of passengers.
Generalist Robots
If you think about the Chatbots that we had ten or even five years ago, they were all pretty task-specific and you couldn’t get them to reply intelligently about topics they weren’t familiar with. Similarly, the robots we have today are task-specific, they can assemble cars, clean your floors, make coffee or even food but you can’t really ask them to do anything outside of what they’re designed to do.
That could change with Cosmos which allows AI models to analyze, predict, and make real-time decisions in unpredictable and unfamiliar environments. Think Irona the robot maid from the Richie Rich cartoons, or Rosie the robot from The Jetsons. Yes, we’re talking about “generalist robots” that can learn and perform a wide range of tasks.
Now while truly general-purpose robots capable of performing the wide array of tasks that humans can are still considered science fiction, we do have a few that are pushing the boundaries. One example is called Digit ( built by Agility Robotics) which is a humanoid robot standing 5-foot-9 with gripping hands and backward-folding legs. Digit is employed in GXO Logistics’ facilities, handling tasks like moving totes, showcasing its adaptability in warehouse settings.
What’s interesting is that Agility Robotics has expressed interest in NVIDIA’s Cosmos platform, indicating that tools like Cosmos assist in solidifying the path from simulation to robust real-world action. Similarly, Apptronik is developing Apollo, a general-purpose humanoid robot designed to operate in human-centric environments. Apollo integrates with NVIDIA’s Project GR00T.
R2D2 and C3PO
Everyone who’s watched The Star Wars movies, The Mandalorian, or anything from that franchise knows that having a really intelligent friend made out of steel is pretty useful. You could get one to build your house, clean it, plant a garden, water it, do the dishes, wash and iron your clothes, and the list of things we wish we didn’t have to do as humans is endless. Labour is one of the main ingredients in any business and if you take away the need for that, you’re talking about a new world, plain and simple.
Would you go to a restaurant if your robot could cook you a Michelin Star meal at home? Or would you take your car to the service station if your robot could service it for you? What if your robot could build you a car out of scrap metal? Would you even bother to buy one then? That’s a lot of questions and the answer to most of them, for most people, would be “No.”
In case you missed:
- Nvidia Project GROOT for humanoid robots
- What’s Nvidia doing in the restaurant business?
- Introducing Nvidia’s L4 GPU profiles in the cloud
- NVIDIA just dropped “ACE” at CES 2025: Truly intelligent NPCs coming soon!
- Scientists gave a mushroom robotic legs and the results may frighten you
- How AI Is Helping Restore the World’s Coral Reefs
- So AI can get bored, “suffer,” and even commit suicide?
- Omnidirectional VR treadmills, go anywhere without going anywhere!
- Mainstream AI workloads too resource-hungry? Try Hala Point, Intel’s largest Neuromorphic computer
- Samsung’s new Android XR Headset all set to crush Apple’s Vision Pro
