Position Paper: Agent AI Towards a Holistic Intelligence
Abstract
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.
Cite
@article{arxiv.2403.00833,
title = {Position Paper: Agent AI Towards a Holistic Intelligence},
author = {Qiuyuan Huang and Naoki Wake and Bidipta Sarkar and Zane Durante and Ran Gong and Rohan Taori and Yusuke Noda and Demetri Terzopoulos and Noboru Kuno and Ade Famoti and Ashley Llorens and John Langford and Hoi Vo and Li Fei-Fei and Katsu Ikeuchi and Jianfeng Gao},
journal= {arXiv preprint arXiv:2403.00833},
year = {2024}
}
Comments
22 pages, 4 figures. arXiv admin note: substantial text overlap with arXiv:2401.03568