肖仰华教授：具身智能距离“涌现”还有多远？

Group 1 - The development of artificial intelligence (AI) has two clear trajectories: one represented by AIGC (Artificial Intelligence Generated Content) and the other by embodied intelligence [3][6] - AIGC is considered a technological revolution due to its foundational nature, its ability to significantly enhance productivity, and its profound impact on societal structures [10][11] - Embodied intelligence aims to replicate human sensory and action capabilities, but its impact on productivity is seen as limited compared to cognitive intelligence [11][13] Group 2 - The current stage of AI development emphasizes the quality of data and training strategies over sheer data volume and computational power [3][15] - The scaling law, which highlights the importance of large datasets and computational resources, is crucial for both AIGC and embodied intelligence [14][15] - The industry faces challenges in gathering sufficient high-quality data for embodied intelligence, which is currently lacking compared to language models [20][21] Group 3 - The future of embodied intelligence relies on its ability to understand and interact with human emotions, making emotional intelligence a core requirement for consumer applications [5][28] - The development of embodied AI is hindered by the complexity of accurately modeling human experiences and environmental interactions [30][32] - There is a need for innovative data acquisition strategies, such as combining real, synthetic, and simulated data, to overcome current limitations in embodied intelligence training [22][23]