How Far Can 5,500 Hours of Driving Take You? A Scaling Law Analysis of Video Diffusion Models
The episode discusses a paper analyzing scaling laws for video diffusion models trained from scratch on driving data. Hosts discuss how repeating training clips doesn't hurt performance and how model size, training time, and compute power balance out. The discussion concludes that this analysis provides a mathematical framework for optimizing training budgets to build reliable driving AI systems.