{"pk":50434,"title":"What Perceptrons Might Tell Us About Our Own Abilities","subtitle":null,"abstract":"Minsky and Papert's (1969) book *Perceptrons* is often remembered as the book that (counter-productively) ended neural network research for nearly two decades. One of the authors' main results was that perceptrons (under reasonable limitations) cannot detect if a pattern is fully connected. Perhaps less known, to their initial surprise, the authors also showed that if guaranteed there are no holes in an image, perceptrons *can* detect if a pattern is fully connected. Given the simplicity of perceptrons, it seems reasonable to think that they might suggest a lower bound for what humans can visually detect without moving their eyes. If so, the results on connectedness suggest some counter-intuitive findings about human perception, namely that we should be able to learn to solve 2D mazes at a glance and detect how many objects are in an image at a glance (i.e., subitize) even when the number is large.","language":"eng","license":{"name":"","short_name":"","text":null,"url":""},"keywords":[{"word":"Artificial Intelligence; Psychology; Learning; Perception; Neural Networks"}],"section":"Member Abstracts with Poster Presentation","is_remote":true,"remote_url":"https://escholarship.org/uc/item/65t946bw","frozenauthors":[{"first_name":"Shayan","middle_name":"","last_name":"Doroudi","name_suffix":"","institution":"University of California, Irvine","department":""}],"date_submitted":null,"date_accepted":null,"date_published":"2025-01-01T18:00:00Z","render_galley":null,"galleys":[{"label":"PDF","type":"pdf","path":"https://journalpub.escholarship.org/cognitivesciencesociety/article/50434/galley/38396/download/"}]}