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Explore the critical intersection of data creation, attribution, and legal considerations in generative AI development through this 42-minute Stanford University lecture. Examine how massive datasets serve as the foundation for large language models and other generative AI systems, while addressing the contentious copyright disputes that have emerged, particularly those involving OpenAI. Delve into the complex challenges surrounding data usage in AI training, including legal and policy implications that shape the field. Discover how researchers are working to ground their investigations in real-world applications across high-impact domains such as law and medicine. The session includes a comprehensive 29-minute lecture followed by a 13-minute Q&A segment, providing insights into ongoing research supported by Stanford's Hoffman-Yee Research Grant program and offering perspectives on navigating the evolving landscape of data rights and AI development.
