You’ll discover that the next decade of AI isn't just about groundbreaking science, but about applying AI to deeply transform everything from digital biology and climate technology to agriculture and robotics. You'll learn about a revolutionary shift in how robots are trained: instead of slow, risky real-world training, they're now learning at lightning speed in sophisticated digital worlds like Omniverse, allowing for endless repetitions and diverse scenarios. You'll understand the crucial concept of giving robots 'common sense' about the physical world, much like how language models work for text, ensuring they grasp fundamental physics like gravity and object permanence through a new 'world model' called Cosmos. Imagine a future where everything that moves is robotic, from your car to your lawnmower, and you might even have your own personal, evolving R2-D2 that accompanies you throughout your life in various forms, from your smart glasses to a physical companion. the next 10 years, we're going to have plenty of science of AI, but the next 10 years is going to be the application science of AI. we might be about to see a huge leap in what all of these robots are capable of because we're changing how we train them. but now we're starting to train robots in digital worlds, which means way more repetitions a day, way more conditions, learning way faster. What is the primary difference in AI development expected in the next 10 years compared to the last 10? According to the speaker, what was a significant limitation of training robots in the real world? How does NVIDIA's Omniverse and Cosmos contribute to the advancement of robotics? What concept is 'Cosmos' designed to provide to robots, analogous to how ChatGPT processes language? What is Jensen's long-term vision for the future of robotics as described in the segment?