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Explore cutting-edge developments in generative artificial intelligence through this comprehensive seminar series covering five critical areas of current research and application. Delve into generative agents and their autonomous capabilities, master techniques for detecting AI-generated content to address authenticity concerns, and understand retrieval augmented generation (RAG) systems that enhance AI responses with external knowledge. Examine the complexities and opportunities of multilingual large language models for global applications, and investigate reinforcement learning from human feedback (RLHF) methods that align AI systems with human preferences and values. Gain insights into the latest methodologies, challenges, and breakthroughs shaping the future of generative AI technology across these interconnected domains.
Syllabus
Advances in Generative AI Seminar: Generative Agents
Advances in Generative AI Seminar: Detecting AI-Generated Content
Advances in Generative AI Seminar: Retrieval augmented generation (RAG)
Advances in Generative AI Seminar: Multilingual large language models
Advances in Generative AI Seminar: Reinforcement learning from human feedback (RLHF)
Taught by
UofU Data Science