This section covers the concept of fine-tuning AI models, which involves altering the model’s underlying patterns to incorporate new knowledge. The speaker discusses the benefits and challenges of fine-tuning, particularly its computational intensity.

Key Takeaways:

• The process and purpose of fine-tuning AI models.
• Differences between fine-tuning and RAG.
• Computational requirements and benefits of fine-tuning.