Practical AI · Thursday, October 1, 2026
Mingyu Liu explains how world models significantly accelerate the development of AI for applications like self-driving cars. Instead of relying solely on real-world testing, policies can be rapidly iterated and verified within the simulated environment provided by a world model, allowing for faster development cycles.
“But with a world model, instead of having your policy deploy the real car, drive in the real world, you can have your policy interact with the world model.”
“When you're still left, what you're going to see, still right, what you're going to see. And from this simulation, you can verify the accuracy of a checkpoint. It can help you quickly narrow down a couple of hypotheses you have.”
“It helps you to get this iteration faster. And now we know in technology, the most important thing is how far you can do iteration.”