This podcast episode explores the active nature of perception, the challenges of deep learning and generative models, the importance of democratizing the development of generative AI, the concept of diffusion models, the challenges of making generative AI models available on consumer hardware, the complexities of visual perception, the role of open source in diffusion models, the debate between open source and proprietary AI models, the role of governments in making compute available for generative AI, strategies for improving the efficiency of AI models, the relationship between intelligence and finite resources, and the limitations of scaling in AI.