The Little Book of Generative AI Foundations: An Intuitive Mathematical Primer

Key points

• •It covers a range of models including PCA, probabilistic PCA, VAEs, diffusion models, normalising flows, autoregressive factorisations, GANs, Wasserstein GANs, and energy-based models.
• •Instead of surveying recent architectures or implementation details, it provides a coherent route connecting major families of generative models.
• •The aim is to provide an intuitive understanding of the mathematical foundations of modern generative AI.