Topic: Image generation

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.

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.