There is a growing list of AIs that can generate data, such as this Microsoft AI that can draw birds from a simple text description.
What’s especially interesting is how the bot can fill in the blanks when specific details aren’t mentioned – basically, it has a little common sense and imagination of its own, thanks to its training data. In the bird example, the bot will usually draw a bird sitting on a tree branch even if that’s not stated in the text, because the images originally fed to it often showed something similar.
What is intriguing from a validation and explainability point of view is that through data generation (creating new images) we are learning insights about the training data (usually shows birds on tree branches). This raises a number of questions such as: will any AI trained with this same data set generalize to handle cases of birds that are not in trees?