Calculus of Variations (in Blender) // Optimization Simulations

[sasodoma]

One thing to note about this iterative optimization is that it doesn't necessarily find the most optimal result, just the one that is better than all of the nearby ones. So for example with the two mountains, you would probably never get the line to cross a mountain and find the best path around, because when it tries to go over a mountain, the middle is still comparatively better.

[Casey-nzxl]

Just in case you are not aware, you can uncheck "Normalize" on the "Noise Texture" to change the range from (0, 1) -> (-1, 1) which would have the same effect as the "Subtract" vector node. (But with a factor of 2)🙂

[omidpakbin]

I don't think I will ever going to use this technique, but I still sat through the whole thing, because this is one of my top favorite channels. Dude wastes no time. So on point. Love it.

[fredrik]

In order to reach optimal target faster you can add "temperature" to the simulation. At start the added noise can be high but as the simulation continues it can cool down i.e. the added noise can become smaller and smaller.

[thxenos]

Damn this is amazing.
I had a flashback to my machine learning class where we optimize a function. This could be an amazing learning aid, if a teacher can actually use blender as well as you.
And you can actually use better optimizing functions instead of random. Though even in this simple form I had a hard time following.

[uriinbar]

to invert the endpoint selection, i think using a boolean 'not' node is simpler and more elegant than subtracting from 1

[juliusfucik]

Definately going to use this. This has so many uses in modeling and visualization. 👍

[steamerk]

Pro-tip: decrease the scale of the exploratory offset you use in each iteration.

Extreme pro-tip: try to identify linear or convex aspects of the particular problem and then exploit that. In the case of the bubbles, try to minimize tension. Instead of moving each vertex in a random direction, weight each vertice's movement towards neighbors which are near longer-than-average edges.

[Ali-s-s-s]

I don't know what this channel is about anymore man but I'm always watching nonetheless, this is magnificent.

[gower]

That last example reminds me of that thing you can do on graph paper, where you draw a line from x1 to y10, then x2 to y9 and so on and it ends up tracing out a curve.

[muniz]

it would be pretty interesting to see that setup used to wrap around a second object in a more interesting way than the ways we do IRL, i bet it can get a ship in a bottle kinda vibe

[MysteryPancake]

can't wait for episode 2 neural network in blender

[skop]

man explained calc of var in like a minute
and my physics professor never could get anyone in class to understand
lol
This is very cool, I've always liked calc of var. it creates some very cool shapes

[MooImABunny]

I really love the thought process here, you learned a very important math/physics tool, and you thought "I wonder if I can do this in Blender?"
can't wait to see what you can do with the spectral theorem or like Cauchy's integral formula, or the prime number theorem XD

[Jebarrda]

also fyi u may want to experiment with decreaseing noise amplitude with frame number to get cleaner convergence to a straight line

[Jebarrda]

ok this is cool. lots of cool stuff. iterative optimization is very cool and swaggy

[harryblends]

"It's always the useless things that end up being the most useful" - my mum

[ec]

Basically a evolution algorithm in blender, nice❤

[gwentarinokripperinolkjdsf]

This is useful, but you can get similar results by applying a smoothing operation instead of random noise, then you don't even need to test that the surface area is going down. much less general though i suppose

[grantmcgregor]

I really apricated this, I tried doing lattices in blender and was stuck with geometry nodes without using Booleans. This helped.