{"id":3749,"date":"2019-10-08T00:00:00","date_gmt":"2019-10-08T00:00:00","guid":{"rendered":"https:\/\/wpdev.hmc.edu\/physics\/2019\/10\/08\/how-can-we-predict-efficiently\/"},"modified":"2019-10-08T00:00:00","modified_gmt":"2019-10-08T00:00:00","slug":"how-can-we-predict-efficiently","status":"publish","type":"physics_colloquium","link":"https:\/\/www.hmc.edu\/physics\/research\/colloquium\/how-can-we-predict-efficiently\/","title":{"rendered":"How can we predict efficiently?"},"content":{"rendered":"<figure id=\"page-featured-image\" class=\"wp-block-image is-style-alignleft\" data-pic=\"pic-637.jpeg\"><img decoding=\"async\" src=\"https:\/\/www.hmc.edu\/physics\/wp-content\/uploads\/sites\/22\/2023\/01\/pic-637.jpeg\" alt=\"Promotional image for talk: Elements of a successful scientific talk\" data-pic=\"pic-637.jpeg\" \/><\/figure>\n<p><strong>Speaker(s):<\/strong> Sarah Marzen<\/p>\n<p>Organisms have to predict the future to best choose actions.&nbsp; How do they do it, especially given the resource constraints that govern their ability to process information?&nbsp; We evaluate the ability of machine learners, bio-inspired neural networks, neurons, and humans to predict and memorize, with surprising preliminary findings.<\/p>\n","protected":false},"author":1,"featured_media":0,"template":"","class_list":["post-3749","physics_colloquium","type-physics_colloquium","status-publish","hentry"],"acf":[],"_links":{"self":[{"href":"https:\/\/www.hmc.edu\/physics\/wp-json\/wp\/v2\/physics_colloquium\/3749","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.hmc.edu\/physics\/wp-json\/wp\/v2\/physics_colloquium"}],"about":[{"href":"https:\/\/www.hmc.edu\/physics\/wp-json\/wp\/v2\/types\/physics_colloquium"}],"author":[{"embeddable":true,"href":"https:\/\/www.hmc.edu\/physics\/wp-json\/wp\/v2\/users\/1"}],"wp:attachment":[{"href":"https:\/\/www.hmc.edu\/physics\/wp-json\/wp\/v2\/media?parent=3749"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}