Noisemaker Bot

I was poking around the internet, looking for good uses of procedural noise. (There are fewer comprehensive catalogs than you’d think.) And I came across Noisemaker Bot, a twitter bot by Alex Ayers that is combining various noise generators and functions to create patterns. Interestingly, it represents images as 32-bit tensors, which is, I think, rare in game applications but more common in scientific fields.

The bot has already generated a wide range of different designs, assembled from its large catalog of operations.

Noise-based patterns like these are more useful than just being pretty things to look at: deterministic, stateless noise pattern generation can be continued indefinitely while smoothly transitioning between any two given points, making it perfect for things like generating terrain. Or adding a bit of jitter to a procedural animation to give it life. Or animating screenshake. Or to pattern a fabric. Or to adjust timing delays on a data visualization to give it a more organic feel.

Any structured, quantitative signal can be used as an input to drive a whole host of different things, which is why I keep talking about unusual inputs. Generation needs structure, but that structure doesn’t necessarily have to be a realistic replication of anything.