This episode is about the hidden space where generative models organize meaning. We move from raw data into a compressed representation that captures concepts rather than pixels or tokens, and we explore how models learn to navigate that space to create realistic outputs. Understanding this idea explains both the power of generative AI and why it sometimes fails in surprising ways.