{"version":"1.0","provider_name":"Technology and Operations Management","provider_url":"https:\/\/aiinstitute.hbs.edu\/platform-rctom","author_name":"Mr. Crimson","author_url":"https:\/\/aiinstitute.hbs.edu\/platform-rctom\/author\/mr-crimson\/","title":"Machine learning in the Energy Sector - Technology and Operations Management","type":"rich","width":600,"height":338,"html":"<blockquote class=\"wp-embedded-content\" data-secret=\"guWTltK3j6\"><a href=\"https:\/\/aiinstitute.hbs.edu\/platform-rctom\/submission\/machine-learning-in-the-energy-sector\/\">Machine learning in the Energy Sector<\/a><\/blockquote><iframe sandbox=\"allow-scripts\" security=\"restricted\" src=\"https:\/\/aiinstitute.hbs.edu\/platform-rctom\/submission\/machine-learning-in-the-energy-sector\/embed\/#?secret=guWTltK3j6\" width=\"600\" height=\"338\" title=\"&#8220;Machine learning in the Energy Sector&#8221; &#8212; Technology and Operations Management\" data-secret=\"guWTltK3j6\" 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:\/\/aiinstitute.hbs.edu\/platform-rctom\/wp-includes\/js\/wp-embed.min.js\n\/* ]]> *\/\n<\/script>\n","thumbnail_url":"https:\/\/aiinstitute.hbs.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/Creating_value-from-M-and-A_1536x1536_400.jpg","thumbnail_width":258,"thumbnail_height":145,"description":"The energy sector although old, is still fertile for innovation, innovative ideas are applied day in and day out in this critical industry. One is the utilization of big data and machine learning to increase efficiency and reduces risk via predicting equipment failures."}