If we assume that the wise will continuously build subscriptions to data and information services that are frictionless, we can focus next on who is buying to bring context and create applications. For one example, having ready access to overlay, interpret, and apply machine learning models in real-time like to everything from clouds to micro data centers operating as dispersed weather stations allows anyone to stitch together the most accurate extrapolation of weather. The value in such a use case can range from picnic planning to sport stadium dome placement to saving lives.
One challenge is thinking through how one takes vast amounts of data and rationalizes based on location and time – the spatial and temporal view. Rationalization becomes what is essential for these kinds of models.
Setting aside saving lives, at first we won’t be as concerned with it being mission critical or life saving a lot of things. For example, if you listen to the early writings of pundits and venture capitalists, sometimes the next big thing will simply look like a game.