Keegan McCallum

This talk details Luma AI's experience scaling their Dream Machine video generation model to one million users in four days. It covers the immense infrastructure challenges faced during the launch, including the need to rapidly scale GPU resources from an initial 500 H100s to 5,000. The presentation also discusses the evolution of their serving stack from a brittle, coupled system to a more robust, decoupled architecture built on PyTorch, and the strategies implemented for fair job scheduling and efficient model management.