  Recent advancements in large foundation models have remarkably enhanced our
understanding of sensory information in open-world environments. In leveraging
the power of foundation models, it is crucial for AI research to pivot away
from excessive reductionism and toward an emphasis on systems that function as
cohesive wholes. Specifically, we emphasize developing Agent AI -- an embodied
system that integrates large foundation models into agent actions. The emerging
field of Agent AI spans a wide range of existing embodied and agent-based
multimodal interactions, including robotics, gaming, and healthcare systems,
etc. In this paper, we propose a novel large action model to achieve embodied
intelligent behavior, the Agent Foundation Model. On top of this idea, we
discuss how agent AI exhibits remarkable capabilities across a variety of
domains and tasks, challenging our understanding of learning and cognition.
Furthermore, we discuss the potential of Agent AI from an interdisciplinary
perspective, underscoring AI cognition and consciousness within scientific
discourse. We believe that those discussions serve as a basis for future
research directions and encourage broader societal engagement.
