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Limits of Language Models
This chapter explores the challenges and limitations of large language models (LLMs) in discerning truth from fiction, highlighting their tendency to produce plausible but inaccurate information, known as hallucinations. It questions LLMs' understanding of belief and theory of mind by contrasting their capabilities with human intelligence, emphasizing their lack of real-world verification. The discussion further critiques traditional evaluation methods in AI, advocating for a deeper understanding of the inner workings of these models beyond standard behavioral tests.