具身智能推动实现通用人工智能

Group 1 - The core idea of embodied intelligence emphasizes that cognition is influenced by the agent's perception and actions, suggesting that intelligence arises from the interaction between the agent's body and the surrounding environment, rather than solely from brain function [1][2] - Embodied intelligence theory has profound implications across various fields such as cognitive science, psychology, anthropology, and art, leading to the emergence of sub-disciplines like embodied cognition and embodied psychology [1][2] - The transition from traditional disembodied intelligence to modern embodied intelligence marks a significant shift in artificial intelligence research, where the latter integrates physical interaction with the environment for learning and decision-making [2][3] Group 2 - The history of artificial intelligence has evolved through three stages: the first generation focused on knowledge-based reasoning models, the second generation introduced data-driven models, and the third generation, marked by the emergence of large language models, represents a new phase of development [3][4] - The introduction of large language models in 2020 has enabled machines to achieve free interaction with humans in open domains, indicating a significant step towards general artificial intelligence [4][5] - Despite advancements in language generation, there are still limitations in achieving domain generality across various tasks, particularly in complex areas like medical diagnosis, highlighting the need for embodied intelligence to bridge these gaps [5][6] Group 3 - The concept of embodied intelligence was first proposed in the field of robotics, emphasizing the importance of the interaction between the body and the environment in intelligent behavior [6][7] - Embodied intelligence has driven advancements in robotics technology, shifting from single-modal perception to multi-modal perception, which is crucial for applications like autonomous vehicles [8][9] - The integration of the agent concept in embodied intelligence allows robots to combine thinking, perception, and action, facilitating tasks in both digital and physical worlds, and enhancing the efficiency of robotic development through simulation [9]