{"version":"1.0","provider_name":"Technology and Operations Management","provider_url":"https:\/\/d3.harvard.edu\/platform-rctom","author_name":"JHart","author_url":"https:\/\/d3.harvard.edu\/platform-rctom\/author\/jhart\/","title":"GM and Machine Learning Augmented Design - Technology and Operations Management","type":"rich","width":600,"height":338,"html":"<blockquote class=\"wp-embedded-content\" data-secret=\"qoforMyg4R\"><a href=\"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/gm-and-machine-learning-augmented-design\/\">GM and Machine Learning Augmented Design<\/a><\/blockquote><iframe sandbox=\"allow-scripts\" security=\"restricted\" src=\"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/gm-and-machine-learning-augmented-design\/embed\/#?secret=qoforMyg4R\" width=\"600\" height=\"338\" title=\"&#8220;GM and Machine Learning Augmented Design&#8221; &#8212; Technology and Operations Management\" data-secret=\"qoforMyg4R\" frameborder=\"0\" marginwidth=\"0\" marginheight=\"0\" scrolling=\"no\" class=\"wp-embedded-content\"><\/iframe><script type=\"text\/javascript\">\n\/* <![CDATA[ *\/\n\/*! This file is auto-generated *\/\n!function(d,l){\"use strict\";l.querySelector&&d.addEventListener&&\"undefined\"!=typeof URL&&(d.wp=d.wp||{},d.wp.receiveEmbedMessage||(d.wp.receiveEmbedMessage=function(e){var t=e.data;if((t||t.secret||t.message||t.value)&&!\/[^a-zA-Z0-9]\/.test(t.secret)){for(var s,r,n,a=l.querySelectorAll('iframe[data-secret=\"'+t.secret+'\"]'),o=l.querySelectorAll('blockquote[data-secret=\"'+t.secret+'\"]'),c=new RegExp(\"^https?:$\",\"i\"),i=0;i<o.length;i++)o[i].style.display=\"none\";for(i=0;i<a.length;i++)s=a[i],e.source===s.contentWindow&&(s.removeAttribute(\"style\"),\"height\"===t.message?(1e3<(r=parseInt(t.value,10))?r=1e3:~~r<200&&(r=200),s.height=r):\"link\"===t.message&&(r=new URL(s.getAttribute(\"src\")),n=new URL(t.value),c.test(n.protocol))&&n.host===r.host&&l.activeElement===s&&(d.top.location.href=t.value))}},d.addEventListener(\"message\",d.wp.receiveEmbedMessage,!1),l.addEventListener(\"DOMContentLoaded\",function(){for(var e,t,s=l.querySelectorAll(\"iframe.wp-embedded-content\"),r=0;r<s.length;r++)(t=(e=s[r]).getAttribute(\"data-secret\"))||(t=Math.random().toString(36).substring(2,12),e.src+=\"#?secret=\"+t,e.setAttribute(\"data-secret\",t)),e.contentWindow.postMessage({message:\"ready\",secret:t},\"*\")},!1)))}(window,document);\n\/\/# sourceURL=https:\/\/d3.harvard.edu\/platform-rctom\/wp-includes\/js\/wp-embed.min.js\n\/* ]]> *\/\n<\/script>\n","thumbnail_url":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/gm-video-thumb-960x532.jpg","thumbnail_width":960,"thumbnail_height":532,"description":"AI-driven product development may help GM find an edge in an industry that has increasingly trended towards conformity in the face of uncertainty. Can GM use machine learning to transform from a company hedging its risk by dabbling in everything new \u2013 to a company that thrives on compressed, cost effective design cycles with measurable results?"}