Wave Function Collapse Algorithm - A new Kind of Procedural Generator

I want to discuss this new approach to procedural generators I have found on Github.
Despite its attention-seeking name it has not much to to with the mathematics of quantum mechanics.
But, I find the results astonishing none the less.



As far as I understand the algorithm it basically works like this:

  1. More like machine learning and unlike peril noise based approaches, it takes a sample input data set.
  2. It decomposes the input into elements (currently using a uniform grid).
  3. It calculates the probability of one type of element neighboring another.
  4. It fills a new output set randomly with elements from the input in a fashion that keeps the neighboring probabilities intact.
  5. You get something similar to the input but it is randomly generated and can be far bigger.

I could image this being an add-on for blender, the question is: Would anybody care?

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if this give a user-friendly way to generate some sets procedurally I think this would be much interesting.
For generating cities , bulding, nature ect…
I don’t know how simple for the user it can get…