A recent discussion highlights the limitations of large language models, arguing that AI is inherently constrained because human language is a fundamentally lossy encoding of the human experience. While LLMs excel at low-ambiguity tasks like coding, they lack physical qualia and true contextual understanding. Consequently, the actual significance of their outputs ultimately relies on the human receiver to bridge the semantic gaps.