The "perfect map" paradox: Why scientific models can never be completebigthink.com/13-8/the-perfect-map-paradox-why-scientific-models-can-never-be-complete/
373 sats \ 4 comments \ @south_korea_ln 23 Jul science
The perfect map paradox
The only perfect map is one that reproduces precisely all the details of whatever it is mapping, or the “territory.” Hence the paradox: If the map is as large as the territory, it has no value whatsoever. A perfect map is as useless as it is impossible to create.
The title of Borges’s story, “On Exactitude in Science,” is purposely ironic. Borges is poking fun at scientists who believe, quite naively, that their scientific models and theories are actually producing a perfect map of reality. If science can be understood as a map, a representation of what we see of the world, then nature is the territory.
This kinda reminds me of this field of computation where actual physical systems are being considered to make efficient computations. You kinda replace the real system by a simpler yet other real system, other than a traditional silicon computer...
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90 sats \ 3 replies \ @SimpleStacker 23 Jul
Hmm. This overall topic is too big for my smooth brain, but doesn't this suppose that the complex reality can't be captured by a set of less complex rules?
Like the function f(x) = sin(1/x) may seem very complex when you try to map it, but the entirety of its information can be conveyed in one formula...
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10 sats \ 0 replies \ @Undisciplined 24 Jul
Maybe I'm just similarly smooth-brained, but I had the same thought.
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0 sats \ 0 replies \ @south_korea_ln OP 24 Jul
Well, say you have a smartphone. This smartphone can be represented by a rectangle, which is easy to model with an equation (similar to what you suggest with the sine function). However, if you look closely, your phone probably has some rounded edges. Your model equation for the rectangle has to be modified to account for this. If you look even more closely, you'll see scratches. Your model equation has to be modified again. If you look even more closely, you'll start to notice that at the atomic level, things become even more complicated. You'll need to add quantum effects in your equations to account for everything that is happening there. It all depends on the precision you need, but no model will be able to include all effects at all levels of precision. Reality is too complex. In the end, if you really want to know how reality behaves, best you can do is look at reality. This doesn't mean these imperfect models are useless, you just need to know when and how to use them.
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0 sats \ 0 replies \ @Bell_curve 23 Jul
you need at least 3 dummy variables to hack p values
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