Exploring the Trade-offs in World Model Training and Inference

This chapter examines the challenges of training world models in machine learning, weighing the benefits of larger models against resource constraints. It highlights the trade-offs in computational costs and the quest for enhanced performance as models increase in complexity and data usage.