Deep Learning allowed the automated visual analysis of every unique building (65 million) in Japan; identifying roof types, location, orientation, and condition to predict losses in the event of a typhoon with an accuracy of 94%.
An insurer carried out an exercise to determine if any major factor was related to the cancellation of live musical events. An analysis of 20 years of global news reports covering the sector revealed that artist age was the single most relevant factor. Doing this manually would have taken many man years effort.
Deep Learning can be injected into any Robotic Process Automation (RPA) solution your may have deployed. It can significantly enhance the static logic and rules, which are a feature of this supposedly ‘intelligent’ technology by imbuing it with genuine machine intelligence.