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what i was interested in is how does something that we would usually identify as complexity arise in nature and i got interested in that question like 50 years ago which is really embarrassingly a long time ago and you know i was you know how does snowflakes get to have complicated forms how do galaxies get to have complicated shapes how does you know how do living systems get produced things like that and the question is what's the sort of underlying scientific basis for those kinds of things and the thing that i was at first very surprised by because i've been doing physics and particle physics and fancy mathematical physics and so on and it's like i know all this fancy stuff i should be able to solve this sort of basic science question and i couldn't this was like early maybe 1980-ish time frame and it's like okay what can one do to understand the sort of basic secret that nature seems to have it seems like nature you look around in the natural world it's full of incredibly complicated forms you look at sort of most engineered kinds of things for instance they tend to be you know we got sort of circles and lines and things like this the question is what secret does nature have that lets it make all this complexity that we in doing engineering for example don't naturally seem to have and so that was the kind of the thing that i got interested in and then the question was you know could i understand that with things like mathematical physics well it didn't work very well so then i got to thinking about okay is there some other way to try to understand this and then the question was if you're going to look at some system in nature how do you make a model for that system for what that system does so you know a model is some abstract representation of the system some formal representation of the system what are what is the raw material that you can make that model out of and so what i realized was well actually programs are really good source of raw material for making models of things and you know in terms of my personal history the to me that seemed really obvious and the reason it seemed really obvious is because i just spent several years building this big piece of software that was sort of a predecessor to mathematica remote language thing called smp (symbolic manipulation program) which was something that had this idea of starting from just these computational primitives and building up everything one had to build up and so kind of the notion of well let's just try and make models by starting from computational primitives and seeing what we can build up that seemed like a totally obvious thing to do in retrospect it might not have been externally quite so obvious but it was obvious to me at the time given the path that i happened to have been on so you know so that got me into this question of let's use programs to model what happens in nature and the question then is well what kind of programs and you know we're used to programs that you write for some particular purpose it's a big long piece of code and it does some specific thing but what i got interested in was okay if you just go out into the sort of computational universe of possible programs you say take the simplest program you can imagine what does it do and so i started studying these things called cellular automata actually i didn't know at first they were called cellular automata but i found that out subsequently but it's just a line of cells you know each one is black or white and it's just some rule that says the colour of the cell is determined by the colour that it had on the previous step and its two neighbors on the previous step and i had initially thought that's you know sufficiently simple setup is not going to do anything interesting it's always going to be simple no complexity simple rules simple behaviour okay but then i actually ran the computer experiment which is pretty easy to do probably took a few hours originally and the and the results were not what i'd expected at all now needless to say in the way that science actually works the results that i got had a lot of unexpected things which i thought were really interesting but the really strongest result which was already right there in the printouts i made i didn't really understand for a couple more years so it was it was not you know the compressed version of the story is you run the experiment and you immediately see what's going on but i wasn't smart enough to do that so to speak but the big, the big thing is even with very simple rules of that type sort of the minimal tiniest program sort of the one line program or something it's possible to get very complicated behaviour my favourite example is this thing called rule 30 which is a particular cellular automaton rule you just started off from one black cell and it makes this really complicated pattern and so that...


Complexity of Life | Stephen Wolfram

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