Title: The Intelligence Feedback Loop: From Biological Inspiration to Augmented Cognition

Abstract: This talk presents an exploration of the intelligence feedback loop—a two-way street where biological inspiration drives AI development, and advanced AI, in turn, amplifies human cognitive capabilities. We begin with a concise history of AI’s evolution, emphasizing the influence of neuroscience on models ranging from classic symbolic agents to modern multimodal large language models (LLMs) that unite multisensory inputs with symbolic reasoning. For augmented cognition, we will discuss computer-use agents that operate in the complex digital world and automate information search and intent execution for human users. We then focus on new biologically-inspired developments, detailing our work on HippoRAG, a long-term memory framework for LLMs inspired by the hippocampal indexing theory. We will conclude with an overview of exciting future research directions for agents.

Bio: Yu Su is a Distinguished Assistant Professor at the Ohio State University, where he co-directs the NLP group. He has broad interests in artificial intelligence, with a primary interest in the role of language as a vehicle for reasoning and communication. His group is a driving force on the emerging topic of LLM-based language agents, with seminal contributions such as Mind2Web, SeeAct, HippoRAG, LLM-Planner, and MMMU. He is a 2025 Sloan Fellow and has received multiple paper awards from CVPR and ACL.