Forms of Understanding in Artificial Intelligence : Language, Representation, and the Question of Meaning

Recent developments in large language models (LLMs) have renewed philosophical debate about the nature of understanding. This paper examines the capacities of LLMs through a fourfold framework of understanding: referential (and emergent referential), inferential, pragmatic (intentional), and experiential. While LLMs clearly exhibit inferential and pragmatic capacities, and may develop internal structures supporting a weak form of referential understanding, they lack experiential grounding. The analysis highlights how language mastery alone can give rise to sophisticated forms of competence, challenging traditional assumptions that understanding requires embodiment or consciousness. These findings invite a reconsideration of how different forms of understanding relate and suggest that aspects of human understanding may also emerge from linguistic and inferential structures.