We are busy compiling some examples of potential use cases for XPL. XPL DreamLab will publish these here for all to see. These will be app ideas, product improvement ideas, and new products. Who knows, maybe someone reading this will take one of these ideas as inspiration and build the next unicorn. Remember the three basic tenants for using DAL (Deep Active Learning) with XPL;


1) Define your problem. 

Ex. “I want to build a product that can visualize pollution as it is being emitted.”



2) Define the boundaries of the problem.

“The product will be an app for iPhones. A user can point the camera at a car’s exhaust, and the screen will show pollution as a certain color of the end user’s choice.”



3) Have an initial hypothesis of outcome.

“Users can scan their environment and avoid areas of noticeably high outputs of pollution. Researchers can hack the app and start to use the data for field research. Municipalities can use the output for urban design initiatives (more green space etc). The app will then be able to predict future pollution levels based upon previous patterns and external triggers.”

With XPL, the only real limitation is your imagination.