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Comment by antegamisou | Hacker News Reader

For anyone interested to look more in-depth on the subject, there's an entire book dedicated to it called Algorithmic Beauty of Plants. The math is really cool!

http://algorithmicbotany.org/papers/#abop

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Yes that is a great resource and the lab that we came from actually!

IIRC that's University of Calgary, right?

I wonder, though, if these techniques are about to be replaced by something like Stable Diffusion (a 3d version of it).

Sure, but L-systems are neato for how simple they are.

ML systems are more difficult to tweak. E.g. if you want to adjust parameters such as growth speed, branching factor, sunlight attraction, etc., and see how the resulting plant changes.

Sure some NN tool can ape anything however that approach sheds zero intuition on understanding the hidden structure of what it's mimicking... current wave of NN masks asking the important questions like how does a cell grow ... I fear NN mania kicks the can down the road without revealing anything fundamental to understanding

In general we know how cells grow, and even plants. Actual plants are controlled by variables that vary species to species, can't be easily measured, and are too numerous to count.

There are a lot of unanswered questions related to how plants grow. If you look through the recent papers at Algorithmic Botany (linked at the start of the thread), you'll notice that they're partnering with other labs to do fundamental biological research (specifically, on the growth of veins in flowers and leaves). That's because they reached the limit of existing knowledge and needed to learn more to improve the computer models.

That's where I did my master's, though I didn't meet Holly and Steve. I'm told they left for Weta shortly before I joined.

Google published some work on reaction-diffusion systems implemented as a ML system. If you would put that on steroids, you could learn and simulate the growth of complex organisms I think.

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