Dispatches from the edge of chaos — on nonlinear dynamics, AI, emergence, and the mathematics of complex systems.
Consistency Models are a new family of generative models that enable high-quality single-step image generation by learning to map any point along a diffusion trajectory directly
Flow Matching is a generative modeling framework that learns continuous normalizing flows by regressing onto simple vector fields, providing a simpler and more flexible alternative to
Latent Diffusion Models (LDMs), commercialized as Stable Diffusion, generate high-quality images by performing the diffusion process in a compressed latent space rather than pixel space, dramatically
The Diffusion Transformer (DiT) replaces the traditional U-Net backbone in diffusion models with a Transformer architecture, achieving superior image generation quality with better scalability properties. Architecture