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Seminar on topics of current interest as announced in the Class Schedule. Course Information: Approved for S/U grading only. May be repeated in the same or separate terms if topics vary. Prerequisite: As specified for each topic offering, see Class Schedule or departmental course description.

Topic: From Biological to Artificial Intelligence Recent breakthroughs in Artificial Intelligence (AI) technologies, notably deep neural networks and reinforcement learning, were largely inspired by our understanding of biological intelligence and how human brain works. At the same time, effective AI models such as large language models may also provide insights useful for understanding biological intelligence. This course will explore a broad range of topics in AI, as well as biological principles of intelligence and their implementation in AI. We will review current state-of-the-art AI models, with particular focus on biological plausibility. Course topics may include but are not limited to: biological and artificial memory systems, generative AI models, reinforcement learning algorithms, and evolution of nervous systems and behavioral complexity. There will be weekly discussions and student presentations of recent papers, aiming to explore the potential advantages, complexities, a