been enjoying the genre of youtube video where an engineer in some specialty plays a simulation game & applies their skills to it; v interesting to think about why certain IRL techniques transfer over and others dont, which design approaches come in handy
often this comes down to the simulation game simplifying the IRL scenario sufficiently such that not all design considerations are relevant; this causes some IRL approaches to be less effective, as the dimensions they're optimizing along have been removed
dimensional reductions can lead to pretty amusing situations where the simplified physics allow for hacky optimizations which either wouldnt work or would be ridiculous IRL, such as hanging bridge anchors here
rethinking assumptions creates possibilities
i also really enjoy finding the parallels btwn the domains used in these simulations and other domains with comparable dynamics; consider, for ex., how the highways designed here end up looking similar to semiconductor circuits
https://www.youtube.com/watch?v=8L71329wD9c&list=PLC05EA61B84719A29&index=7
studying the abstractions common across real-world problems allows us to develop general theories and classes of solutions, which can then be specialized to different usecases; computer science, specifically combinatorics, gives us the tools to do this
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RT @pee_zombie
30. much more to be said here but combinatorics, specifically graph theory, has already got it covered; which brings me to bemoaning how unknown the graph structure is…
https://twitter.com/pee_zombie/status/1339044568499712000
and in the other direction, we can also find instances where the natural world has developed efficient solutions for these same problems! after all, transporting nutrients is very similar in design constraints to transporting people
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RT @pee_zombie
slime molds are efficient biological 2-space minimum flow cost solvers and thats fuckin dope #slimemoldtwitter https://twitter.com/embryosophy/status/1340367562387832832
https://twitter.com/pee_zombie/status/1342197082598334464
computation is the ultimate paradigm; it has maximum generality, allowing all other problems to be represented in computational terms. to understand the core of any real-world problem one should study computer science, even if they're not a programmer
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RT @pee_zombie
computation is the highest abstraction, and as such, shouldn't those versed in it be well suited for operating in any domain? bit of a self serving view to be sure, and…
https://twitter.com/pee_zombie/status/1441558371870511112
ofc the similarities are superficial, as these network types have radically different purposes & dynamics, w/ the flow units interacting in v different ways
but the emergent similarities of design approaches point at underlying parallels in flow networks
https://brilliant.org/wiki/flow-network/