Dr. Konrad Körding
"How similar is learning between AI systems and our brain?"
Abstract:
The question about the potential similarity between brains and artificial systems has a long intellectual history. Recent developments in deep learning systems have made this question more salient, after all current large language models appear able to imitate humans really well. This leaves us with the question if Humans may learn in a similar way to artificial neural networks, it invites us to ask if the brain does gradient descent. In my talk I will argue that it probably does, and argue for the usefulness of this stance as well as its teleological justification.
About Konrad:
Konrad Kording runs his lab at the University of Pennsylvania. Konrad is interested in the question of how the brain solves the credit assignment problem and similarly how we should assign credit in the real world (through causality). In extension of this main thrust he is interested in applications of causality in biomedical research. Konrad has trained as student at ETH Zurich with Peter Konig, as postdoc at UCL London with Daniel Wolpert and at MIT with Josh Tenenbaum. After a decade at Northwestern University he is now PIK professor at UPenn.
Category:
Cognitive Science