Recent advances in foundation models, especially in large multi-modal models and conversational agents, have ignited interest in the potential of generally capable embodied agents. Such agents will require the ability to perform new tasks in many different real-world environments. However, current foundation models fail to accurately model physical interactions and are therefore insufficient for Embodied AI. The study of causality lends itself to the construction of veridical world models, which are crucial for accurately predicting the outcomes of possible interactions. This paper focuses on the prospects of building foundation world models for the upcoming generation of embodied agents and presents a novel viewpoint on the significance of causality within these. We posit that integrating causal considerations is vital to facilitating meaningful physical interactions with the world. Finally, we demystify misconceptions about causality in this context and present our outlook for future research.

翻译：近期基础模型，尤其是大型多模态模型与对话智能体的进展，激发了人们对通用能力具身智能体潜力的兴趣。这类智能体需具备在多种真实世界环境中执行新任务的能力。然而，现有基础模型难以精准建模物理交互，因此不足以支撑具身人工智能。因果关系研究有助于构建真实世界模型，这对准确预测可能交互的结果至关重要。本文聚焦于为下一代具身智能体构建基础世界模型的前景，并提出关于因果关系在其中重要性的新视角。我们认为，将因果考量融入模型是促进与物理世界有意义交互的关键。最后，我们厘清了该背景下对因果关系的常见误解，并展望了未来研究方向。