How Does AI Understand Language Meaning

Recent years have witnessed significant breakthroughs in artificial intelligence language processing technologies. However,the core issue of “understanding language meaning” remains plagued by philosophical and technical dilemmas. This paper argues that human comprehension of language meaning is rooted in the dynamic interplay of bodily experiences,active exploration,and social interaction,characterized by the unity of embodiment,agency,and sociability. In contrast,AI achieves only functional understanding through statistical pattern matching,leaving symbols perpetually “suspended” from real-world experience. The crux of the symbol grounding problem lies in AI's inability to establish experiential associations between symbols and the physical world. To address this,the paper proposes a dual-track solution centered on embodiment and association:Embodiment involves constructing multimodal perception systems,aligning cyber-physical spaces,and developing embodied large-scale datasets to ground symbols in sensorimotor experiences. Association emphasizes dynamically linking agents'embodied experiences with environments,others,cultures,and tasks to form decentralized interactive capabilities. Only by embedding symbolic systems in embodied practices and social relational networks can AI transcend computational simulations and achieve genuine semantic understanding. The future development of superintelligent agents will hinge on paradigm shifts toward meaning-generation frameworks rooted in bodily experience and social association,reshaping the cognitive boundaries of human-AI symbiosis.