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Navigating AI Fine-Tuning Challenges
This chapter explores the complexities of fine-tuning AI models, including dataset management and debugging issues. The speaker advocates for in-context learning over traditional fine-tuning for companies not centered on foundation models, emphasizing the need for robust evaluation processes. Additionally, it highlights the evolving skill sets necessary for AI product development and the importance of user trust in AI-generated outputs.