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by agarsev
1594 days ago
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I think this is a very widespread idea, I used to believe in it too, perhaps due to our background. However, if you work on translating science to computers, you soon find it's not so true. There are some many ideas in science which are not mathematically encoded, but rather in human language, it's kind of frustrating. The "low-level" sciences like physics have spoilt us with their very math-like nature. But even in those sciences there are a lot of things which are not well-defined, but rather rely on human intuition and language. If you go "upwards" in the stack, you find things like biology where there is a lot of very formal scientific knowledge which is not maths. And I work in linguistics, so just imagine what it's like at this level ;) |
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I'm finding the deeper I study biology, the more certain I am that complex models with both classical and quantum parameters will eventually be able to predict the overwhelming majority of macromolecular behavior such as protein folding and DNA recombination.
Once you start dealing with concepts bigger than that you get into another mathematical description with Markov chain style models for cellular proliferation, followed by network analysis for tissue growth.
You can take that up further and further, I'm sure you're somewhat familar.
My question is, even if you have some examples, what do you find to be some kind of theoretical limit to the modelling that would actually be accurate?
Not a limit to the accuracy, that must simply always exist, but a limit to what can be successfully modeled at least to "acceptably correct" for use in some application?