Navigating AI Fine-Tuning Methods

This chapter examines the distinctions between supervised fine-tuning and reinforcement fine-tuning in AI development, highlighting user experience and the challenges developers face. It discusses the balance between technical demands and innovative UX solutions while addressing the complexities involved in adopting AI tools. Additionally, it emphasizes the evolution of AI agents, the importance of effective labeling, and the competitive landscape of hardware in relation to software integration.