In this episode, we take a deep dive into the mathematical foundations of generative AI, unraveling the complex theories and equations that power models like VAEs, GANs, normalizing flows, and diffusion models. From linear algebra and probability to optimization and game theory, we explore the intricate math that enables AI to generate realistic images, text, and more. Whether you're an AI researcher, machine learning engineer, or just curious about how machines can dream up new realities, this episode will provide a rigorous yet engaging exploration of the formulas and concepts shaping the future of generative AI.