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Show HN: Strange Attractors

blog.shashanktomar.com

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Re: Show HN: Strange Attractors

#36

Post by shashanktomar »

Sreenington wrote: post #35

this is so cool! would be awesome if you can add params to mess with a and b value so we can "find" our own strange attractor patterns. maybe a free mode?

Author here, it already supports that for the best attractors. On phone there is a menubar at bottom, on desktop you can’t miss it.

Re: Show HN: Strange Attractors

#37

Post by cantor_S_drug »

flatline wrote: post #29
cableclasper wrote: post #12

Visualizations like this truly highlight how much there is to be gained from viewing the 3D phase space, but also how much richness we miss in >3D! (I wonder if there are slick ways to visualise the >3D case. Like, we can view 3D cross sections surely. Or maybe could we follow a Lagrangian particle and have it change colour according to the D (or combination of D) it is traversing? And do this for lots of particles?…

The conclusion I’ve come to from works like Flatland, 4D toys, etc., is that we simply don’t have the neural circuitry to grasp anything beyond three dimensions. We can reason about them, we can make inferences about the whole from partial understanding, but we cannot truly grasp more than three, or perhaps only for an instant of forced conceptualization using heuristics like you mentioned. Even three is a stretch, o…

Do you think an AI can learn this intuition by training it in similar environment?

Re: Show HN: Strange Attractors

#38

Post by shashanktomar »

srvmshr wrote: post #28

Coincidentally enough, I dug out my 11th grade CS project on generating fractals from 2002 & modernized it using SFML graphics lib just this week. https://github.com/gradientwolf/fractals_SFML Your post gives me so much joy. These tiny little things take me back to teenage years, simpler times & when interests were different. (I put a little note as "why" in my GH repo readme)

Thanks a lot, it was clearly worth the effort.

Re: Show HN: Strange Attractors

#39

Post by vincnetas »

cantor_S_drug wrote: post #37
flatline wrote: post #29

Earlier quoted context omitted.

The conclusion I’ve come to from works like Flatland, 4D toys, etc., is that we simply don’t have the neural circuitry to grasp anything beyond three dimensions. We can reason about them, we can make inferences about the whole from partial understanding, but we cannot truly grasp more than three, or perhaps only for an instant of forced conceptualization using heuristics like you mentioned. Even three is a stretch, o…

Do you think an AI can learn this intuition by training it in similar environment?

Can we train our neurons? Like the experiment where human vision adapted to upside down image, could our brains somehow adapt to understanding 4D data from VR headset?
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