Watson Swift SDK 0.33 at a Glance
IBM has finally released a version of their Watson SDK that supports Cocoapods. All prior versions required the use of Carthage and a somewhat complicated installation process.

Why is this important? Watson has incredible tools for developers. But difficulty getting started has been a show stopper. Matching IBM compilations with Apple development versions was a pain. Cocoapods is the preferred method of installation for developers using Github.
I just upgraded to Xcode 10 and IOS 12. I knew that getting Watson working would be a pain. To my pleasant surprise, version 0.33 with Cocoapods support worked perfectly.
Now, including any of the Watson libraries, like VisualRecognition or SpeechToText, is a snap. Here’s a list of the libraries available for developers to drop into their podfiles.

From your terminal, run the “pod install” command, and open the generated or updated .xcworkspace file. Your Watson Libs are ready for use. To update to newer releases, simply use “pod update”.
When importing the frameworks in your source files, exclude the IBM Watson prefix and the version suffix. For example, after installing WatsonAssistantV1, import into your source files as “Import Assistant”.
Another jazzy improvement is the Watson SDK Documentation. Someone has been busy improving these docs.
If you are a Swift Developer, I strongly recommend checking out the Watson Swift SDK on Github and visit Watson in the Cloud.
I’m building an App for detecting visitors from other worlds and then exposing their true nature with the use of style transfer effects (the science of art). So I’m combining IBM Watson VisualRecognition and Apple CoreML to find and expose Aliens or Alien Hybrids. The App can identify almost anything with trained image recognition models.
You are probably wondering, how can an App use Watson Image Recognition, to find Aliens? Training Watson to see visitors from space will be the subject of another hopefully fascinating article (AI vs ET).
For programmers, using Watson in the cloud to train and then download the trained models on the fly for rapid recognition on a mobile device is very cool. Watson with CoreML makes image recognition within augmented reality possible.

