Some medical applications (just for example, you would need quite a robust model):
* Categorize moles on your skin as cancerous or not.
* Categorize cuts on your skin as infected or not.
* Have the user input certain characteristics (images, temperature data, etc) and give some preliminary diagnosis.
Less interesting/helpful:
* Detect photos of certain foods in your app (e.g. Twitter, Instagram, Yelp) and recommend relevant emoji or hashtags.
* For a note-taking or to-do app, classify notes into categories automatically for the user.
* Suggest actions in your app based on what the user types or does.
* Recommend solutions or help articles from the feedback form in your app. Tag the feedback with a certain sentiment to determine how quickly you should follow up on it.
* Detect your products in images/videos and tag them to make them searchable, and recommend relevant things to the user (e.g. in a beer tracking app [2], detect a certain kind of beer, suggest similar types).
If any of this sounds like it's been done before, it probably has, but it's important to note this is done entirely on device (private!) and with custom labels. The current alternative is to use TensorFlow Lite [1], which is a bit more involved. I'm sure as the field develops we will see more creative (and useful/helpful) applications.