Christian Lebiere is a Research Faculty in the Psychology Department at Carnegie Mellon University, having received his Ph.D. from the CMU School of Computer Science. During his graduate career, he studied connectionist models and was the co-developer of the Cascade-Correlation neural network learning algorithm. He has participated in the development of the ACT-R cognitive architecture and most recently has been involved in defining the Common Model of Cognition, an effort to consolidate and formalize the scientific progress from the 50-year research program in cognitive architectures. His main research interests are cognitive architectures and their applications to artificial intelligence, human-computer interaction, intelligent agents, network science, cognitive robotics and human-machine teaming.
Talk
From Large Language Models to Cognitive Architectures | June 11
Sessions in which Christian Lebière participates
Tuesday 11 June, 2024
Large Language Models have displayed an uncanny ability to store information at scale and use it to answer a wide range of queries in robust and general ways. However, they are not truly generative in the sense that they depend on massive amounts of externally generated data for pre-training and lesser but still significant amounts of human feedback for fine-tuning. Conversely, cognitive architectures have been developed to reproduce and explain the structure and mechanisms of human cognition...