Understanding Large Language Models

This chapter explores the functionality and emergence of large language models, drawing comparisons to the human brain's neural networks. It details how these models process language, generate coherent text, and learn from vast data sets, raising ethical considerations along the way. The conversation addresses the limitations of such models, including their lack of true comprehension and the complexities that render them 'black boxes'.