{"id":136992,"date":"2022-03-17T11:24:02","date_gmt":"2022-03-17T18:24:02","guid":{"rendered":"https:\/\/lifeboat.com\/blog\/2022\/03\/mathematical-paradoxes-demonstrate-the-limits-of-ai"},"modified":"2022-03-17T11:24:02","modified_gmt":"2022-03-17T18:24:02","slug":"mathematical-paradoxes-demonstrate-the-limits-of-ai","status":"publish","type":"post","link":"https:\/\/lifeboat.com\/blog\/2022\/03\/mathematical-paradoxes-demonstrate-the-limits-of-ai","title":{"rendered":"Mathematical paradoxes demonstrate the limits of AI"},"content":{"rendered":"<p><a class=\"aligncenter blog-photo\" href=\"https:\/\/lifeboat.com\/blog.images\/mathematical-paradoxes-demonstrate-the-limits-of-ai2.jpg\"><\/a><\/p>\n<p>Humans are usually pretty good at recognizing when they get things wrong, but artificial intelligence systems are not. According to a new study, AI generally suffers from inherent limitations due to a century-old mathematical paradox.<\/p>\n<p>Like some people, AI systems often have a degree of confidence that far exceeds their actual abilities. And like an overconfident person, many AI systems don\u2019t know when they\u2019re making mistakes. Sometimes it\u2019s even more difficult for an AI system to realize when it\u2019s making a mistake than to produce a correct result.<\/p>\n<p>Researchers from the University of Cambridge and the University of Oslo say that instability is the Achilles\u2019 heel of modern AI and that a mathematical paradox shows AI\u2019s limitations. Neural networks, the state of the art tool in AI, roughly mimic the links between neurons in the brain. The researchers show that there are problems where stable and accurate <a href=\"https:\/\/techxplore.com\/tags\/neural+networks\/\" rel=\"tag\" class=\"\">neural networks<\/a> exist, yet no algorithm can produce such a <a href=\"https:\/\/techxplore.com\/tags\/network\/\" rel=\"tag\" class=\"\">network<\/a>. Only in specific cases can algorithms compute stable and accurate neural networks.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Humans are usually pretty good at recognizing when they get things wrong, but artificial intelligence systems are not. According to a new study, AI generally suffers from inherent limitations due to a century-old mathematical paradox. Like some people, AI systems often have a degree of confidence that far exceeds their actual abilities. And like an [\u2026]<\/p>\n","protected":false},"author":661,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[41,2229,6],"tags":[],"class_list":["post-136992","post","type-post","status-publish","format-standard","hentry","category-information-science","category-mathematics","category-robotics-ai"],"_links":{"self":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts\/136992","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/users\/661"}],"replies":[{"embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/comments?post=136992"}],"version-history":[{"count":0,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts\/136992\/revisions"}],"wp:attachment":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/media?parent=136992"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/categories?post=136992"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/tags?post=136992"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}