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There are two tricks I know of to generative art, which, as it happens, also apply to manually crafted art.

With all things in pattern recognition this principle holds: if the proportions are like a thing you recognize, it maps to that thing symbolically. That could be physical proportion, range of pitch or rhythm, or otherwise. And that means that deconstructing a reference into a sample set of proportions is a useful way to create organic elements and reduce the "cold" of being strictly mathematical. To accomplish, for example, fantasy creature drawings is primarily a matter of reconstructing familiar creatures with new proportions and body plans - it's an art of remixing a stew of influences to create something new, and the methods can be fairly direct(a "photobash and trace" approach will take you to a mostly complete image, though it might be lacking in anatomical understanding). With {Shan, Shui}* the original sample set has a more direct and obvious source; what is interesting is the method of reconstruction. ML is very popular as a reconstruction tool now, but it's a big and unwieldy cannon. Collecting smaller algorithms together is a more intricate exercise but gives a lot more targeted intent to the result.

The second necessary element is chaotic behavior. Randomness is often applied instead of chaos, but we recognize randomness as noise, while we recognize chaos as "a very complex pattern". Hence we tend to see representations of the Mandelbrot set as more beautiful than Perlin noise, because Perlin noise is too random - while it's a believable texture at small scales, it doesn't suggest overall composition. Chaos creates a high depth of engagement in artwork since it mixes anticipation and surprise. It's the moment when you are reading a page-turner novel and need to know what happens next - you might have a rough idea of the plot but be wrong on the details.




This is fascinating and I'm guessing part of the research to combat "the uncanny valley" that we've read so much about.




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