Unraveling Language Models: Hallucinations and Human Projections

This chapter examines the common misconceptions about large language models (LLMs), particularly their tendency to make mistakes or 'hallucinate.' The speaker emphasizes the importance of not attributing human-like qualities to these models and critiques the anthropomorphism that often occurs in user interactions. By exploring the complexities of LLMs as tools rather than epistemic agents, the chapter highlights the implications of their design and performance on trust and communication.