Speaker: Dr. Ty Tuff, Environmental Data Science Innovation and Inclusion Lab (ESIIL)

Abstract: Join us for an engaging session in the ESIIL Environmental Data Science Seminar Series, where we dive into the fascinating realm of reinforcement learning and its role in enabling System 2 thinking in large language models (LLMs). This lecture will spotlight DeepSeek R1, the revolutionary AI model that has captured global attention this week for achieving groundbreaking performance with unprecedented efficiency. Developed using older and smaller Nvidia H800 GPUs over just a few months, DeepSeek R1 was trained for 95% less cost than comparable efforts by OpenAI, demonstrating a new paradigm in scaling advanced AI systems. We will explore how DeepSeek R1 leverages reinforcement learning to achieve human-like reasoning processes, its implications for scalability and global AI competitiveness, and the ethical considerations of building AI within the constraints of cultural and political influences. Prepare to explore how reinforcement learning is shaping the next generation of LLMs, making advanced reasoning accessible in ways that were once thought impossible.

Speaker Bio: Dr. Ty Tuff is your friendly neighborhood data scientist, based at the Environmental Data Science Innovation and Inclusion Lab (ESIIL). With deep expertise in processing, analyzing, and modeling data, Ty has led cutting-edge research projects in global institutions and is passionate about advancing the frontiers of AI and environmental data science. Ty's work focuses on turning complex datasets into actionable insights while fostering collaboration across disciplines.