{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/92c9db97467c4a2d851f43a6b8554c90\" frameborder=\"0\" width=\"1280\" height=\"960\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":960,"width":1280,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":960,"thumbnail_width":1280,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/92c9db97467c4a2d851f43a6b8554c90-00001.gif","duration":794,"title":"Machine Learning for Digital Twins to Predict Responsiveness of Cyber-Physical Energy Systems"}