Panelists: Ev Fedorenko, Sydney Levine, Josh Tenenbaum, Phillip Isola, Martin Schrimpf;
Moderator: Tommy Poggio

Abstract: Transformer models have been rapidly gaining popularity as they underlie some of the most advanced deep learning systems to date. Despite their apparent successes, several questions remain unanswered. This discussion panel will focus on comparing transformer networks to human intelligence at multiple levels including the ability for these models to have general cognitive abilities, the similarities in operations to the computations in the human brain and the ability to meet or exceed human performance in different tasks.

About the Panelists:

• Ev Fedorenko, Middleton CD Associate Professor of Neuroscience, MIT BCS
• Sydney Levine, Research Scientist, Allen Institute for AI
• Josh Tenenbaum, Professor, MIT BCS
• Phillip Isola, Class of 1948 Career Development Professor, MIT EECS
• Martin Schrimpf, Research Scientist, MIT Quest / Assistant Professor, EPFL