tl;dr: This lecture introduces the foundational concepts of reward modeling for language model alignment, detailing the reinforcement learning framework, the training processes involved, and the critical role of human preference data in shaping models that adhere closely to desired behaviors and ethical standards.

🎓 Lecturer: Gaurav Pandey [  / gaurav-pandey-11321120  ]
🔗 Get the Slides Here: http://lcs2.in/llm2401

Explore the intricate process of aligning language models through reward maximization in this detailed lecture. We delve into how alignment can be modeled as a form of reinforcement learning, focusing on the architecture of the reward model, its training, and the methods for gathering preference data such as RLHF (Reinforcement Learning from Human Feedback) versus RLAIF (Reinforcement Learning with Augmented Inverse Feedback). This session is essential for those interested in the ethical and effective training of AI to ensure its decisions and outputs align with human values.