Starting from a random image it's possible to manipulate and filter it to find literally anything. It doesn't mean there are "animal pictures" in the random data; it means the image has been manipulated to look like it. It's a tautology.
The question is about how often image recognition (either human or algorithmic) picks up a signal in random noise -- that is, how often we see things that aren't there (or if you prefer, are there, but by chance). Of course you can find anything, the question is with what frequency.
If you've ever spent much time looking at random patterns, you'd know that we're prone to seeing things that aren't there in noise. Modeling that phenomenon is interesting (at least to me).
As the "animals" are smoothed groups of random data, (and differ every time) , I'd argue it's still (basically) random.
The question of pattern recognition in random noise is interesting and a legitimate question. Animals (given our propensity to see then) and an interesting subject matter.