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dc.contributor.authorHilton, Erwin
dc.contributor.authorLiao, Qianli
dc.contributor.authorPoggio, Tomaso
dc.date.accessioned2018-01-01T00:17:40Z
dc.date.available2018-01-01T00:17:40Z
dc.date.issued2017-12-31
dc.identifier.urihttp://hdl.handle.net/1721.1/113004
dc.description.abstractWe introduce SITD (Spatial IQ Test Dataset), a dataset used to evaluate the capabilities of computational models for pattern recognition and visual reasoning. SITD is a generator of images in the style of the Raven Progressive Matrices (RPM), a common IQ (Intelligence Quotient) test used to test analytical intelligence. RPMs are purely visual, and require little prior knowledge. RPM tests the users ability to derive abstract rules and patterns from a set of images. For the last 100 years, humans have evaluated intelligence us- ing standardized intelligence quotient exams. These tests examine different aspects of intelligence, including verbal, quantitative reasoning, and spatial reasoning ability. In the field of AI, there exists few intelligence established metrics beyond the Turing Test (TT) and the Total Turing Test (TTT). Thus, SITD makes for a useful dataset researchers can use to divide and conquer the task of creating ’intelligent’ machines.en_US
dc.description.sponsorshipThis work was supported by the Center for Brains, Minds and Machines (CBMM), funded by NSF STC award CCF - 123 1216.en_US
dc.language.isoen_USen_US
dc.rightsAttribution-NonCommercial-ShareAlike 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/us/*
dc.subjectDataseten_US
dc.subjectIQ Testen_US
dc.subjectAIen_US
dc.subjectTuring Testen_US
dc.titleSpatial IQ Test for AIen_US
dc.typeArticleen_US


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