benefits and pitfall in fine-tuning generative AI models

This presentation explores the fine-tuning of generative AI models, emphasizing its relevance in scientific teaching. Topics include customizing models for specific domains, improving performance, and addressing ethical and safety risks. It highlights pitfalls such as malicious fine-tuning attacks and misalignment, while offering best practices like defensive strategies and evaluation metrics for safe, effective applications. The session concludes with key insights, unresolved challenges, and...