Enhancing Reasoning in Large Language Models

This chapter explores the advanced capabilities of large language models in reasoning, emphasizing techniques such as chain of thought and mixture of experts. It also examines the challenges and risks associated with using multiple agents in these systems, particularly concerning error amplification and the benefits of iterative reflection.