This claim is unsupported:
> The machine, not smart enough to do the actual difficult job of converting these sophisticated image types to each other
Obviously it found an easy way to solve the problem it was given: stenography But could it have solved the problem the researchers intended, if they had framed it correctly? There's no evidence either way for this particular algorithm, but in general this is not hard. This is usually called style transfer and I don't see any reason to believe that standard techniques[1] wouldn't be able to solve the street-map-to-aerial-map problem. And it's pretty well established that adding a bit of noise[2] during training helps GANs avoid these kinds of problems.
[1]: https://medium.com/tensorflow/neural-style-transfer-creating...
[2]: https://www.inference.vc/instance-noise-a-trick-for-stabilis...
