The Essential Role of Causality in Foundation World Models for Embodied
  AI
Tarun Gupta Wenbo Gong Chao Ma Nick Pawlowski Agrin Hilmkil Meyer Scetbon Ade Famoti Ashley Juan Llorens Jianfeng Gao Stefan Bauer Danica Kragic Bernhard Schölkopf Cheng Zhang
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 would require the ability to perform new
tasks in many different real-world environments. However, current foundation
models fail to accurately model physical interactions with the real world thus
not sufficient 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
facilitate meaningful physical interactions with the world. Finally, we
demystify misconceptions about causality in this context and present our
outlook for future research.