Just spent a few minutes playing with the Watson Custom Model for vision flow and let's just say I am totally disappointed is an understatement, few things I noticed:
1. You first need to register an account, and to my surprise there is no command line tool or REST APIs, the entire interface is written in HTML. Hmmm, are they expecting me to specify the network structure by pressing buttons
2. Okay next, after choosing the visual model, it leads you directly to a web page with a bunch of widgets where you can add classes and negatives. To a seasoned ML engineers, this whole interface is useless. The classification has to be done at a full image level, no way to define the layers, the loss function, or any knobs to play around with the network. To an amateur, this is also very confusing. What are they expecting us to drag in to the negatives, if it's a logistic classifier, I could understand but for classifying an image, what exactly do you expect us to put?
3. Btw, to upload images, they expect .zip format, and this is where i stopped. Do they seriously think I will now export this so-called "model" to CoreML and load it to my Xcode?
If they came up with this 5 years ago I might play with it a little longer, but don't the IBM engineers keep up with what's going on at GOOGL, FB or AMZN. I can't possibly imagine anyone using this to develop iPhone apps for the purpose of image recognition, even if it's an offline flow.