With an announcement that felt straight out of a sci-fi epic, at  CES 2025 (the most important tech event in the world) Jensen Huang, president and CEO of Nvidia, unveiled Cosmos, a family of “world foundation models” poised to reshape robotics and autonomous systems. These neural networks don’t just calculate or generate, they predict and create physics-aware virtual environments and tools. Yes, the machines are learning not just to think but to move – because why stop at taking over the Internet when you can conquer the physical world?

“The ChatGPT moment for robotics is coming,” Huang declared, setting the stage for what might be the next great leap in AI. Like language models before them, world foundation models (WFMs) like Cosmos promise to be transformative, enabling next-gen robots and autonomous vehicles that won’t just stumble through your living room but will navigate it with uncanny precision.

To ensure this revolution isn’t reserved for the privileged few, Nvidia is open-sourcing Cosmos. It’s a bold move, putting these tools in the hands of developers everywhere. “We created Cosmos to put general robotics in reach of every developer,” Huang explained, imagining a world where robots are not only smarter but more widely accessible.

At its core, Cosmos is about realism. These WFMs combine data, text, images, video, and motion to create virtual environments so accurate you might start mistaking the simulation for reality. But this isn’t just about creating pretty virtual worlds – it’s about teaching machines how to understand and interact with the real one. From physical interactions to environmental navigation, these models represent a foundational shift in what AI can do.

This perspective is undeniably ambitious and speaks to a broader shift in how AI could impact the physical landscape. If large language models revolutionized the way we process and generate information, world foundation models aim to do the same for robotics and autonomous systems. But are robots truly poised to make this substantive leap into real-world applications? There are promising signs that they are:

1. Improved simulation capabilities. The ability to simulate complex physical environments with high accuracy is a game-changer. Platforms like Cosmos signal that we are closing the gap between training in a virtual space and performing in the real world.

2. Advances in multimodal learning. Huang’s emphasis on combining data from text, images, video, and movement is aligned with the AI trend of multimodal models. By integrating diverse types of input, WFMs can develop a nuanced understanding of the world, making them better suited to handle dynamic environments.

3. Open-source democratization. Nvidia’s decision to open-source Cosmos is a sign that physical AI is moving from niche research labs to broader developer communities. This democratization could accelerate innovation, with startups, researchers, and even hobbyists contributing to the evolution of robotics.

4. Emerging applications. Autonomous vehicles, warehouse robots, and drones are already functioning in semi-controlled real-world environments. The tools provided by Cosmos could help extend these capabilities to less structured spaces, such as homes, cities, or disaster zones.

5. Economic and industry pressure. Robotics development is no longer a theoretical exercise. Industries like logistics, healthcare, and agriculture are actively seeking AI-driven solutions to labor shortages, efficiency bottlenecks, and environmental challenges. This demand is driving funding, research, and practical deployment.

That said, big jumps into the real world are rarely smooth. Robots must contend with unpredictable human behavior, complex environments, and the need for safety and reliability. Transfer learning (moving knowledge from a simulated environment to the real world) remains a technical hurdle. Ethical and regulatory frameworks are also playing catch-up with the pace of technological progress.

Still, Huang’s vision of WFMs as the “missing link” in robotics isn’t just marketing – it’s a reflection of a tangible trend toward AI systems that are not only intelligent but also physically capable. While Cosmos might not single-handedly bring about the “ChatGPT moment” for robotics, it represents a meaningful step toward that goal. The leap into the real world will depend on whether these advances can translate into scalable, reliable, and widely adoptable systems. What’s clear, though, is that we’re no longer asking if this leap will happen, but when.