MIT EI seminar, Hyung Won Chung from OpenAI. "Don't teach. Incentivize."

This podcast episode features Hyung Won Chung from OpenAI discussing the pivotal role of scalability in AI research, emphasizing how leveraging advancements in compute power can enhance AI models. Chung advocates for reframing our understanding of scaling by moving beyond simply increasing resources and instead addressing underlying modeling assumptions that limit performance. He expounds on the success of large language models (LLMs), particularly through the lens of next token prediction as a method of implicit multitask learning. As he draws distinctions between generalists and specialists in AI, he highlights the importance of incentive structures and emergent abilities, which arise at higher scales. Ultimately, Chung encourages the research community to prioritize general skill development in AI systems, paving the way for innovative applications.