From: <a href="http://spectrum.ieee.org/robotics/artificial-intelligence/machinelearning-maestro-michael-jordan-on-the-delusions-of-big-data-and-other-huge-engineering-efforts" rel="nofollow">http://spectrum.ieee.org/robotics/artificial-intelligence/ma...</a><p>Jordan: Well, humans are able to deal with cluttered scenes. They are able to deal with huge numbers of categories. They can deal with inferences about the scene: “What if I sit down on that?” “What if I put something on top of something?” These are far beyond the capability of today’s machines. Deep learning is good at certain kinds of image classification. “What object is in this scene?”<p>I think Jordan refers here to Bayesian models that incorporate gravity, occlusion, and other such concepts.<p><a href="http://www.cv-foundation.org/openaccess/content_cvpr_2013/html/Jiang_Hallucinated_Humans_as_2013_CVPR_paper.html" rel="nofollow">http://www.cv-foundation.org/openaccess/content_cvpr_2013/ht...</a> e.g. postulates entire humans to improve scene understanding.<p>What I get out of this: Deep learning has to be enriched with progress from other machine learning fields