Exploring Large Language Models: Humanity and Error

This chapter examines the complexities of large language models like Grok, focusing on their neural network architecture and the potential for human-like errors. It underscores the intrinsic differences between LLMs and humans, emphasizing the need for skepticism when interpreting LLM outputs despite their human-mimicking capabilities.