Image Processing podcasts

Fatih Porikli examines why scaling image models alone does not guarantee visually correct results. He discusses separating scene planning from rendering, improving controllability and editing, and bringing high-resolution generation to edge devices, including the role of training objectives and reinforcement learning.

Hosted by Sam Charrington

Dustin Podell discusses developments in image generation at Black Forest Labs, from diffusion models to flow matching and FLUX. The conversation considers image editing, local inference and the transition from producing pictures to supporting more capable visual workflows.

Hosted by Chris Benson, Daniel Whitenack

Hung Bui examines efficient diffusion models for image generation and editing on devices. The discussion covers SwiftBrush and SwiftEdit, distillation from iterative teachers into single-step students, and a coach network that aligns denoising behaviour. It also considers personalised agents and reasoning under fixed compute budgets.

Hosted by Sam Charrington