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Exploring Occlusions in World Modeling and AI Training Data Approaches
The chapter delves into the topic of modeling occlusions in the physical world and questions the efficacy of two-dimensional training data approaches for reaching the same level as underlying 3D models. It discusses the limitations and weaknesses of current systems, the importance of self-supervised learning with internet-scale data, and the potential dangers of releasing AI systems like deep fakes. Additionally, it explores the evolving impact of AI on tasks in the economy, the evolution of economic systems with incentives for humans, and the anticipation for future AI advancements like GPT-5.