{"version":"1.0","provider_name":"BDV Big Data Value Association","provider_url":"https:\/\/bdva.eu","author_name":"daniel.djamo@bdva.eu","author_url":"https:\/\/bdva.eu\/author\/daniel-djamobdva-eu\/","title":"V. Sustainable data and AI: enhancing efficiency and resilience while reducing resource demands - BDV Big Data Value Association","type":"rich","width":600,"height":338,"html":"<blockquote class=\"wp-embedded-content\" data-secret=\"t58KhgsTzc\"><a href=\"https:\/\/bdva.eu\/docs\/bdva-strategic-agenda-2024\/v-4-sustainable-data-and-ai-enhancing-efficiency-and-resilience-while-reducing-resource-demands\/\">V. Sustainable data and AI: enhancing efficiency and resilience while reducing resource demands<\/a><\/blockquote><iframe sandbox=\"allow-scripts\" security=\"restricted\" src=\"https:\/\/bdva.eu\/docs\/bdva-strategic-agenda-2024\/v-4-sustainable-data-and-ai-enhancing-efficiency-and-resilience-while-reducing-resource-demands\/embed\/#?secret=t58KhgsTzc\" width=\"600\" height=\"338\" title=\"&#8220;V. Sustainable data and AI: enhancing efficiency and resilience while reducing resource demands&#8221; &#8212; BDV Big Data Value Association\" data-secret=\"t58KhgsTzc\" 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:\/\/bdva.eu\/wp-includes\/js\/wp-embed.min.js\n\/* ]]> *\/\n<\/script>\n","description":"(V1.0 August 2024) As data analytics and AI models gain higher capabilities and provide new functionalities, their resource requirements (storage, power, energy) increase, making them less energy efficient. Moreover, the widespread accessibility to the tools based on those models leads to their extensive usage and a subsequent rise in their environmental impact. Therefore, it is [&hellip;]","thumbnail_url":"https:\/\/bdva.eu\/wp-content\/uploads\/2025\/03\/BDVA-Logo.png","thumbnail_width":1600,"thumbnail_height":900}