But how do AI images and videos actually work? | Guest video by @WelchLabsVideo

The podcast explores how AI systems generate videos from text prompts, focusing on the connection between these models and physics, particularly Brownian motion and diffusion. It explains how diffusion models work by transforming pure noise into realistic images and videos through a step-by-step process, and it also discusses the CLIP model, which creates a shared space between words and pictures. The podcast further explains how diffusion models are trained to remove noise and how this process relates to time-varying vector fields, and it also touches on techniques like classifier-free guidance to steer the generation process towards desired outcomes. It concludes by highlighting the rapid advancements in the field and the potential of language as the primary tool for creating lifelike images and videos.