Perception, Learning, and Memory in Brains and AI models: What Aligns and What Doesn't

This talk examines whether AI foundation models are converging on computational principles used by brains for perception, learning, and memory. It argues for moving beyond task accuracy toward mechanistic comparisons of representations and learning dynamics.

Dr. Zoran Tiganj is an Assistant Professor of Computer Science at Indiana University. His research combines artificial intelligence, cognitive science, and computational neuroscience with the objective of building artificial agents that learn from temporal and spatial regularities in the world.