Exploring the incorporation of a world model based on physics in self-driving car systems to enhance safety by controlling acceleration and preventing collisions. Discussing the role of verifiers in assessing AI decision-making against predefined safety metrics, with a focus on rider comfort in train design. Emphasizing the importance of explicit safety specifications and the need for varied representations in world models for ensuring AI systems interact safely and adapt to uncertainties.

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