The Stuff You Should Know Doin’ Science Playlist: How Chaos Theory Changed the Universe

20:36Yeah, like let me just round off the mass of this planet at like the eighth decimal point.

20:41Chuck Bryant:Right. And like, you know, who cares? Who cares? At that point. Let me just round that one to a two. Right. And that would throw everything off at a pretty high rate. And he said, wait a minute, I think this contest is impossible. Right. He said there is no way to prove the stability of the solar system because he just uncovered the idea that it's impossible for us to predict the rate of change among celestial bodies. Yeah, it's such a complex system. there are far too many variables that it's impossible to start with something so minute to get the equation, whatever, the sum that you want at the end.

21:31Well, not only that. Well, not a sum, I guess, but the result.

21:34Chuck Bryant:Not only that, and this is what really undermined determinism, was that he figured out that you would have to have an infinitely precise measurement. Yeah. Which even if you built a perfect machine that could take the infinitely, or a perfect machine that could take a measurement of the movement of a celestial body around another, it's literally impossible to get an infinitely precise measurement. Which means that we could never predict, out to a certain degree, the movement of these celestial bodies. Like he was saying, no, you can't build a machine that gets measurements enough that we can overcome this.

22:19Chuck Bryant:Like, determinism is wrong. Like, you can't just say we have the understanding to predict everything. There's a lot of stuff out there that we're not able to predict, and he uncovered it trying to figure out this end body problem. Yeah, and King Oscar, the sequel, said, you win! Yeah. Bring me another rack of lamb, and here's your prize. Yeah. And he won by proving that it was impossible, which is pretty interesting. And that utterly and completely changed not just math, but like our understanding of the universe and our understanding of our understanding of the universe, which is even more kind of earth shaking.

22:56Yeah, he discovered dynamical instability or chaos, and they didn't have supercomputers at the time, so it would be a little while, about 70 years at MIT, until we could actually kind of feed these things into machines capable of plotting these things out in a way that we could see. Right. Which was really incredible.

23:19Chuck Bryant:So there was this dude 70 years later named Edward Lawrence. Or Lawrence. Yeah, well, first of all, we should set the stage. The reason this guy, he was a meteorologist and scientist. Not that those are not the same thing. Right. He's a scientist who dabbled in meteorology. Right. He was a mathematician. Yeah. But he was really into meteorology because there was a weird juxtaposition at the time where we were sending people into outer space, but we couldn't predict the weather. Yeah, and it was definitely a blot on the field of meteorology. People were like, do you guys know what you're doing?

24:00Chuck Bryant:Yeah. And meteorologists are like, you have no idea how hard this is. Yeah. Like, yeah, we can predict it a couple days out, but after that, it's totally unpredictable. It drives us mad. And it wasn't just their reputations that were at stake. People were losing their lives because of it, right? Yeah, in 1962, there were two notorious storms, one on the east coast and one on the west. the Ash Wednesday storm in the east, and the big blow on the west that killed a lot of people, cost hundreds of millions of dollars in damage. And people were like, you know, we need to be able to see these things coming a little more, because it's a problem.

24:37Chuck Bryant:And meteorologists were like, why don't you do it then? So they thought the key was these big supercomputers. Remember the supercomputers when they came out? The big rooms full of hardware? It was amazing, and they were finally able to do these incredible calculations that we could never do before. I know, they were able to crunch 64 bytes a second. Yeah, we had the Abacus and then the supercomputer. Right. There was nothing in between. I looked up the computer that Lorenz was working with. Was it the Whopper? A Royal McBee. What was the Whopper? War Games. Was it called the Whopper? Yeah, W-O-P-R.

25:13Chuck Bryant:Right. I can't believe they called it that. I don't know, pretty stupid. So the guy just nicknamed it Joshua? Joshua? No, Joshua was the... Software? Falcon was the old man who designed all this stuff, and his son was Joshua, and that was the password to get into the system. Oh, that was the password. Yeah. I guess I was too young to understand what a password was. Yeah. Okay. There weren't passwords at the time. No. And you just shouted it at the computer, and they were like, okay, access granted. Yeah. That movie holds up. Does it really? Oh, totally. I gotta check it out. Yeah, still very, very fun.

25:50Young Ally Sheedy, boy, I had a crush on her from that movie.

25:53Chuck Bryant:She was great. Yeah. What else was she in recently? Wasn't she in something? Well, I mean, she kind of went away for a while and then had her big comeback with that indie movie High Art, but that was a while ago. Has she been in anything else recently? Sure. I think I saw her in something recently and I didn't realize that was her. Oh, really? She looks familiar. I was like, oh, that's Ally Sheedy. I don't know. All right. I could look it up, but I won't. It doesn't matter. Anyway, I still crush on her. So the Royal McBee was not quite the Whopper. You could actually sit down at it. The Royal McBee?

26:31Chuck Bryant:That's the name of it. That sounds like a hamburger too. It was by the Royal Typewriter Company, and they got into computers for a second. And this is the kind of computer that Lawrence was working with. Yes. And it was a huge deal. like you were saying, Abacus supercomputer. But it was still pretty dumb as far as what we have today is concerned. But it was enough that Lawrence was like, Lawrence and his ilk were like, finally, we can start running models and actually predict the weather. Yeah. He started doing just that. He did. So he started off with a computational model of 12 meteorological calculations, I liked how you said it.

27:13calculations, which is very basic, because they're infinite meteorological calculations, probably. Yeah. Depending, did I say it wrong again? No, no, no.

27:22Chuck Bryant:It sounds like you're about to say it wrong, and then you pull it out at the last second. Maybe. It's really impressive. So that's very basic, but he wanted to start out with something attainable. Right. So he narrowed it down to 12 conditions, basically, 12 calculations that had temperature, wind speed, pressure, stuff like that. Right. Started forecasting weather. And then he said, you know, it'd be great if you could see this. So I'm going to spit it into my wonder machine, the McWhopper. What was it? The Royal McBee. The Royal McBee. And I'm going to get a printout so you can visualize what this looks like.

27:57Chuck Bryant:Right. So things were going well, and he had this printout, and everyone was amazed because these calculations never seemed to repeat themselves. He was making like word art. You remember that? That was the first thing anybody did on a computer. Oh, yeah, yeah. Was to make word art, like a butterfly or something. Right, you would print out. Yeah, I never could do that. I couldn't either. Like you have to be able to visualize things spatially. You have to have that right kind of brain for that. Right, or you have to be following a guidebook that tells you how to do it. True. Have you ever seen Me, You, and Everyone We Know?

28:33Chuck Bryant:Yeah, I love that movie. That's a great movie. Yeah. Those little kids in there, they were doing that. Oh, yeah, yeah. The forever back and forth poop. Well, I haven't seen that since it came out. It's been a while. Oh, you've got to see it again. Yeah. Great movie. Good movie. Ally Sheedy's not in it. No. It's Miranda July. Right. And she wrote and directed too, right? She did a great job. It was her show. It's one of those rare movies where there's just the right amount of whimsy. Because whimsy so easily overpowers everything else and becomes like, bleh. Yeah, yeah. This is like the most perfectly balanced amount of whimsy I've ever seen in a movie.

29:12Yeah, if there's too much whimsy, I just like Garden State. I just want to punch it in the face. Terrible.

29:17Chuck Bryant:Although I like Garden State, but I haven't seen it since it came out. It hasn't aged well. Yeah. It's just, when you look at it now, it's just so cutesy and whimsical. Oh, yeah. It's like, oh, come on. Boy, we're getting to a lot of movies today. Oh, yeah, we're stalling. We haven't even talked about Butterfly Effect yet, which is coming. It is. I'm dreading it. That's why I'm stalling. All right, so where were we? He was running his calculations, printing out his values so people could see it. And then he got a little lazy one day in 1961. This output, he noticed, was interesting. So he said, you know, I'm going to repeat this calculation, see it again, but to save time, I'm just going to kind of pick up in the middle, and I'm not going to input as many numbers, but I'm still using the same values, just I'm not going out to six decimal points.

30:12Chuck Bryant:So the printout he had went to three decimal points. Yeah. So he was working from the printout and didn't take into account that the computer accepted six decimal points. So he was just putting in three. Correct. And expecting that the outcome would be the same, right? Yes, but the outcome was way different. Right. And he went, whoa, whoa. What? Yeah. He's like, what's going on here? It was a big deal. I mean, someone would have come up with this eventually, probably. He sort of accidentally came upon it. It's neat that this guy did this because it changed his career. I think he went from emphasis on meteorology to emphasis on chaos math.

30:48To stud scientists.

30:50Chuck Bryant:Basically. So, I mean, the guy's got an attractor named after him, you know what I mean? Yeah, well, let's get to that. So Lorenz starts looking at this and he's like, wait a minute, this is weird. This is worth investigating. And like, what was his name, Poincaré? Yeah. He said, I need fewer variables. So I'm not going to try to predict weather with these 12 differential equations that you have to take into account. I'm just going to take one aspect of weather called the rolling convection current. And I'm going to see how I can write it down in formula form. So a rolling convection current, Chuck, is where, you know how the wind is created?

31:32Chuck Bryant:where air at the surface is heated and it starts to rise and suddenly cool air from higher above comes in to fill that vacuum that's left. And that creates a rolling or vertically based convection current. Yeah. Okay? I would describe it as oven. Oven, boiling water, cup of coffee. Sure. Wherever there's a temperature differential based on a vertical alignment, you're going to have a rolling convection current, okay? Yeah, it sounds complex, but he just picked out one thing, basically, one condition, and this is the one he picked out. But had you seen my hands moving, listeners, you would be like, oh yeah, I know what you're talking about.

32:17Sure, he made little rolly motions.

32:20Chuck Bryant:So he's like, okay, I can figure this out. So he comes up with three formulae that kind of describe a rolling convection current, and he starts trying to figure out how to describe this rolling convection current, right? Correct. And so like I said, he got these three formula which were basically three variables that he calculated over time and he plugged them in and he found three variables that changed over time and he found that after a certain point when you graph these things out and since they're three, you graph them out on a three-dimensional graph, so X, Y, and Z. Again, he wanted to just be able to visualize this.

32:59Right. Because it's easier for people to understand.

33:01Chuck Bryant:He was a very visual guy. Totally. All of a sudden, it made this crazy graph that where the line, as it progressed forward through time, went all over the place. It went from this axis to another axis to the other axis, and it would spend some time over here, and then it would suddenly loop over to the other one, and it followed no rhyme or reason. It never retraced its path. and it was describing how a convection current changes over time, right? Yeah. And Lorenz is looking at this. He was expecting these three things to equalize and eventually form a line. Yeah. Because that's what determinism says.

33:41Chuck Bryant:Things are going to fall into a certain amount of equilibrium and just even out over time. That is not what he found. No. And what he discovered was what Poincaré discovered, which was that some systems, even relatively simple systems, exhibit very complex, unpredictable behavior, which you could call chaos. Yeah, and when you say things were going all over, like if you look at the graph, it's not just lines going in straight lines, bouncing all over the place randomly. There was an order to it, but the lines were not on top of one another. Let's say you draw a figure eight with your pencil, and then you continue drawing that figure eight, it's gonna slip outside those curves every time unless you're a robot.

34:26Sure. And that's what it ended up looking like.

34:29Chuck Bryant:Yeah, yeah. It never retraced the same path twice, ever. It had a lot of really surprising properties. And at the time, it just fell completely outside the understanding of science, right? Yeah. Luckily, this happened to Lorenz, who was curious enough to be like, what is going on here? And again, he sat down and started to do the math and thinking about this, and especially how it applied to the weather, right? Yeah. And he came up with something very famous. Yes, the butterfly effect. Yes. A, this thing kind of looked like butterfly wings a little bit. Yeah. And B, when he went to present his findings, he basically had the notion, he's like, I'm going to wow these people in the crowd in 1972.

35:16to. It's a conference that I'm going to. And I'm going to say something like, you know, the seagull flaps his wings and it starts a small turbulence that can affect weather on the other side of the world. The small little thing will just grow and grow and snowball and affect things. And he had a colleague who was like, eh, seagull wings, that's nice. And he said, how about this? And this is the title they ended up with. Predictability, colon, does the flap of a Butterfly's wings in Brazil set off a tornado in Texas, and everyone was like, whoa. Whoa. Minds blown.

35:53Chuck Bryant:Yeah. Should we take a break? Yes. All right, we'll be right back.

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37:41Chuck Bryant:Stuff you should know All right, so the Lorenz Attractor is that picture that he ended up with. Right, that graph. It's called the Lorenz Attractor. And this biblical pattern website that I found described attractors and strange attractors in a way that even dumb old me could understand. What you got? So if I may. He says, all right, here's the cycle of chaos. He said, actually, I don't know who wrote this. Could have been a woman, could have been a small child. Could have been Noah. Of undetermined gender, I have no idea. To the gender neutral narrator. They said, he said, all right, think about a town that has like 10 ,000 people living in it.

38:33To make that town work, you gotta have like a gas station, a grocery store, a library, whatever you need to sustain that town. So all these things are built. Everyone's happy. You have equilibrium. He said, so that's great. Then let's say you build, someone comes and builds a factory on the outskirts of that town, and there's going to be 10 ,000 more people living there.

38:57Chuck Bryant:Right, and they don't go to church. Maybe so. Did I say church? They needed a church? No, no. Oh, okay. I was just assuming this is what's going to break the equilibrium. Equilibrium. No, no, no. But you just have more people, so you need another gas station and another grocery store, let's say. So they build all these things, and then you reach equilibrium. Again, it's maintained because you build all these other systems up. I see. That equilibrium is called an attractor. Okay. So then he said, it said, they said. He, capital he. The royal he said, All right, now let's say instead of that factory being built and you have those original 10 ,000, let's say 3 ,000 of those people just up and leave one day.

39:44Okay. And the grocery store guy says, well, there's only 7 ,000 people here. We need 8 ,000 people living here to make a profit. So I'm shutting down this grocery store. Then all of a sudden you have demand for groceries. So things go on for a little while and someone comes in and say, hey, this town needs a grocery store. They build a grocery store. They can't sustain. They shut down. Someone else comes along because of the demand. And it is this search for equilibrium, this dynamic. Well, you reach equilibrium here and there as the store opens. Periods of stability. Periods of stability. And that dynamic equilibrium is called a strange attractor.

40:24So an attractor is the state which a system settles on. and strange attractor is the trajectory on which it never settles down, but tries to reach the equilibrium with periods of stability. Man. Does that make sense?

40:39Chuck Bryant:That Bible-based explanation was dynamite. I understand it better than I did before, and I understood it okay before. That's great. Surely you can add. Yeah? Yeah. No, you're gonna add to it? No. That's it? No, I mean, yeah, Yeah, and attractor is where if you graph something and eventually it reaches equilibrium, it's a regular attractor. If it never reaches equilibrium, it is constantly trying to and has periods of stability, strange attractor. I can't top that. All right, grocery store, small town. That was great. So Lorenz's strange attractor was named a Lorenz attractor, named after him, big deal.

41:19They weren't using the word chaos yet.

41:21Chuck Bryant:No, but he published that paper about butterfly wings, right? Yeah. The butterfly effect. And it coupled with his picture, the picture of a strange attractor, which is almost the, aside from fractals, almost the emblem or the logo for chaos theory, the Lorenz attractor is. It got attention off the bat. It wasn't like Poincaré's findings where he got neglected for 70 years. Almost immediately, everybody was talking about this. Because, again, what Lorentz had uncovered, which is the same thing that Poincaré had uncovered, is that determinism is possibly based on an illusion. Yeah. That the universe isn't stable, that the universe isn't predictable, and that what we are seeing as stable and predictable are these little periods, windows of stability that are found in strange attractor graphs.

42:15Chuck Bryant:That that's what we think the order of the universe is, but that that is actually the abnormal aspect of the universe. And that instability, unpredictability, as far as we're concerned, is the actual state of affairs in nature. And I think as far as we're concerned is a really important point too, Chuck. Because it doesn't mean that nature is unstable, chaotic. It means that our picture of what we understand as order doesn't jibe with how the universe actually functions. It's just our understanding of it. Yeah. And we're just so anthropocentric that we see it as chaos and disorder and something to be feared.

43:00Chuck Bryant:Right. When really it's just complexity that we don't have the capability of predicting. Yeah. After a certain degree. Yeah, I think that makes me feel a little better because when you read stuff like this, you start to feel like, well, the Earth could just throw us all off of its face at any moment because it starts spinning so fast that gravity becomes undone. And I know that's not right, by the way. I've always loved that kind of science that shows we don't know anything. Like Robert Hume, who I understand was a philosopher, but he was a philosopher scientist. Sure. His whole jam was like cause and effect is an illusion.

43:35Chuck Bryant:that like we all, it's just an assumption like that if you drop a pencil, it will always fall down. It's an illusion. And this is pre-gravity, understanding gravity. But he makes a good point. It's pre-gravity when everyone's just floating around. Yeah, going this pencil's got me wacky. But the point was that we base a lot of our assumptions or a lot of stuff that we take as law are actually based on assumptions that are made from observations over time and that we're just making predictions that cause and effect is an illusion. I love that guy. Pretty cool. And this definitely supports that idea.

44:14For sure.

44:16Chuck Bryant:Sorry, I'm excited about chaos theory. Can you believe it? Well, I mean, I like that I'm able to understand it in enough of a rudimentary way that I can talk about it at a dinner party. Well, thank your Bible website. Well, once you take the formulas out Yeah. For people like us, we're like, oh, okay, we can understand chaos. Yeah. Then when somebody says, good, do a differential equation, you're just like, what? A what? A different equation? Right. All right, so earlier I said that chaos had not been used, the word chaos, to describe all this junk. Right. And that didn't happen until later on.

44:53Well, actually, not later on. About 10 years. Yeah, but it was kind of at the same time this other stuff was going on with Lorenz. Yeah. Late 60s, early 70s. There was a guy named Stephen Smale, Fields Medal recipient, so you know he's good at math. And he described something that we now know as the Smale horseshoe, and it goes a little something like this. So, all right, take a piece of dough, like bread dough, and you smash it out into a big flat rectangle. Can do. So you're looking at that thing and you're like, boy, I hope this makes some good bread.

45:33Chuck Bryant:This is going to be so good. Put a little rosemary on it. Yeah, maybe so. A little oil, sea salt. Yeah, and then lick it before you bake it so you know it's yours. No one else can have it. So you have that flat rectangle of dough. You roll it up into a tube and then you smash that down kind of flat. And then you bend that down to where it eventually looks like a horseshoe. Okay. So now you take that horseshoe, you take another rectangle of dough, and you throw that horseshoe onto that, and then you do the same thing. The smale horseshoe basically says you cannot predict where the two points of that horseshoe will end up.

46:14Chuck Bryant:Yeah. You can roll it a million times, and it'll end up in a million different places. Totally random different places, too. Totally random. You never know. It's like a box of chocolates. You never know what you're going to get. You have to say it. And that became known. You have to say it. Oh, what? Imitate Forrest Gump? Sure. No, I can't do that. That's fine. He's not in my repertoire. That's fine. Although I did see that again, part of it recently. Does it hold up? Well, I mean, take out 40 minutes of it, and it would have been a better movie. Yeah. Like all of that coincidence stuff that. Oh, I love that.

46:50I thought that was so charming. And he also did the smile t-shirt. Sure. It was just too much. like he really hammered it too much.

46:57Chuck Bryant:I liked it. That was the basis of the movie. I know, but see it again and I guarantee you like an hour and a half into it you'll be like, I get it. Zemeckis. You know it was a good Tom Hanks movie that was overlooked? Road to Perdition. Yeah, not bad. That was a good one. Great Sam Mendes. Oh man, that guy's awesome. Yeah. Oh, what is he gonna do? He might do something. He did the James Bond, he did Skyfall. Yeah, yeah, no, he's gonna do that. that last one that wasn't so great. He's got a potential project coming up and he would be amazing for it. I don't remember what it was. Did you see Revolutionary Road?

47:33Chuck Bryant:Yes, God. It was just like. Yeah, you wanna jump off a bridge after you see that movie. Like every five minutes during that movie. It was hardcore. It is. He did that one too, huh? Yeah, and don't see that if you're like engaged to be married or thinking about it. Yeah, or if you're blue already. Yeah. Yeah, just take a really good mood and be like, I'm sick of being in a good mood. Sit down and watch Revolutionary Road. Yeah. Watch Joe vs. the Volcano instead. Great movie. Where was I? Smale Horseshoe is what that's called. And he was the first person to actually use the word chaos. Oh, he was.

48:12I think so. No, no, no.

48:14Chuck Bryant:York was. Tom York's dad. Yeah, you're right. He wasn't the first person. You're correct. But Smale's Horseshoe illustrates a really good point, Chuck. Is it Tom York's dad? No. Oh, okay. No, but they're both British. Sure, Yorkies. Actually, one's Australian. No, they're British. All right. So those two points, which started out right by each other and then ended up in two totally different places, that applies not just to bread dough, but also to things like water molecules that are right next to each other at some point, and then a month later, they're in two different oceans. Yeah. Even though you would assume that they would go through all the same motions and everything.

48:55Oh, sure.

48:55Chuck Bryant:But they're not. There's so many different variables with things like ocean currents that two water molecules that were once side by side end up in totally random different places. Yeah. And that's part of chaos. It's basically chaos personified. Yeah. Or chaos molecule-fied. So we mentioned York. Where I was going with that was there was an Australian named Robert May and he was a population biologist So he was using math to model how animal populations would change over time, giving certain starting conditions. So he started using these equations, these differential equations, and he came up with a formula known as the logistic difference equation that basically enabled him to predict these animal populations pretty well.

49:46Chuck Bryant:Yeah, it was working pretty well for a while, but he noticed something really, really weird, right? Yeah. He had this formula, the logistic difference equation is the name of it. Sure. Okay, so he had that formula, and he figured out that if you took R, which in this case was the reproductive rate of an animal population, and you pushed it past three. The number three. So that meant that the average animal in this population of animals had three offspring in its lifetime, or in a season, whatever. Yeah. If you pushed it past three, all of a sudden the number of the population would diverge. Yeah, if you pushed it equal to three, actually, or more.

50:33Chuck Bryant:Right, it would diverge. Yeah. Which is weird because a population of animals can't be two different numbers, you know? Like that herd of antelope is not, there's not 30, but there's also 45 of them at the same time. That's called a superposition, and that has to do with quantum states, not herds of antelopes. Sure. That was kind of weird. And then he found if you pushed it a little further, if you made the reproductive rate like 3.057 or something like that, I think it was a different number. But you just tweaked it a little bit, not even to four. We're talking like millionths of a degree. All of a sudden it would turn into four.

51:16Chuck Bryant:So there'd be four different numbers that was the animal population. And then it would turn into 16. And then all of a sudden, after a certain point, it would turn into chaos. Yes. The number would be everything at once, all over the place, just totally random numbers that it oscillated between. Yeah, but in all that chaos, there would be periods of stability. Right, you push it a little further and all of a sudden it would just go to two again. Yeah. But beyond that, it didn't go back to the original two numbers, it went to another two. So if you looked at it on a graph, it went line, divided into two, divided into 4, 8, 16, chaos, 2, 4, 16, 2, 4, 8, 16, chaos.

51:53Yeah.

51:54Chuck Bryant:All before you even got to the number four of the reproductive rate. Yeah, and he was working with Mr. York because he was a little confounded. So he was a mathematician buddy of his, James York from the University of Maryland. So they worked together on this. And in 1975, they co-authored a paper called Period 3 Implies Chaos. and man, finally, somebody said the word. I kept thinking it was all these other people. Yeah, and this paper where they first debuted the name Chaos, they based it, Tom York's dad based it on Edward Lawrence's paper. He was like, you know what? I have a feeling this has something to do with the Lawrence attractor.

52:39Chuck Bryant:So that provided chaos to the world And it was basically the third time a scientist had said, we don't understand the universe like we think we do. And determinism is based on an illusion of order in a really chaotic universe. And this established chaos. It took off like a rocket in the 80s and the 90s, as you know from Jurassic Park. Chaos was everything. Everybody was like, chaos. This is totally awesome. It's the new frontier of science. And then it just went away. And a lot of people said, well, it was a little overhyped. But I think more than anything, and I think this is kind of the current understanding of chaos, because it didn't actually go away.

53:26Chuck Bryant:It became a deeper and deeper field, as you'll see. People mistook what chaos meant. It wasn't the new type of science. It was a new understanding of the universe. It was saying like, yes, you can still use Newtonian physics. Yeah, like don't throw everything out the window. You can still try and predict weather and still try and build more accurate instruments. Right. And get, you know, decent results. But you can't with absolute perfection 100 % predict complex systems. Like determinism, the ultimate goal of determinism is false. It can never be done. Because we can't have an infinitely precise measurement for every variable or any variable.

54:09Chuck Bryant:Therefore, we can't predict these outcomes, right? So you would expect science to be like, what's the point? What's the point of anything? No, not science. Well, some chaos people have said, no, this is great. This is good. We'll take the universe as it is rather than trying to force it into our pretty little equations and saying like if the ocean temperature is this at this time of year and the fish population is this at that time, then this is how many offspring this fish population is going to have. Say, okay, here is the fish population. Here is the ocean temperature. Here are all these other variables.

54:51Chuck Bryant:Let's feed it into a model and see what happens. Not this is going to happen. What happens instead? And this is kind of the understanding of chaos theory now. It's taking raw data, as much data as you can possibly get your hands on, as precise data as you can possibly get your hands on, and just feeding it into a model and seeing what patterns emerge. Rather than making assumptions, it's saying, what's the outcome? What comes out of this model? Yeah, and that's why when you see things like 50 years ago, they predicted this animal would be extinct, and it's not. Well, it's because the variations were too complex.

55:30Right. They tried to predict, and that's why if you look at a 10-day forecast, you, sir, are a fool. Right. It's true. Well, 10 days from now, it says it's going to rain in the afternoon. Come on.

55:45Chuck Bryant:But if you took enough variables for weather for like a city and fed it into a model of the weather for that city, you could find a time when it was similar to what it is now, and you could conceivably make some assumptions based on that. You can say, well, actually, we can predict a little further out than we think. But it's based on this theory, this understanding of chaos, of unpredictability, of not just not forcing nature into our formulas, but putting data into a model and seeing what comes out of it. Yeah, and then at the end of that you learn when that animal is not extinct like you thought it would be.

56:31You go back and look at the original thing and you have a more accurate picture of how the data could have been off slightly. This one value. And then you have more buffalo than you think. Sure.

56:45Chuck Bryant:You got buffaloed by chaos. And we're not even getting into fractals. It's a whole other thing and we did a whole other podcast in June 2012 about fractals and the Benoit Mandelbrot. Mandelbrot? Mandelbrot. Yeah. And go listen to that one and hear me clinging to the edge of a cliff. Yeah. Clift? Man, we should end this. But first, I want to say there is a really interesting article that's pretty understandable on Quanta Magazine about a guy named George Sugihara. And he is a chaos theory dude who's got a whole lab and is applying it to real life. So it's a really good picture of chaos theory in action.

57:33Chuck Bryant:Go check it out. Oof. Okay. If you want to know more about chaos theory, I hope your brain's not broken. Yeah, go take some LSD. And look at fractals. Don't do that. You can type those words into how stuff works in the search bar. Any of those, fractals, LSD, chaos, it'll bring up some good stuff. And since I said good stuff, it's time for Listener Mail. I'm going to call this Rare Shoutout. We get requests all the time. I'll bet I know which one this is. Really? Yeah. Dude and his girlfriend? Yeah? No? So far, so good. Hey, guys, just wanted to say I think you're doing a wonderful job with the show to this date.

58:15My first time listening was during my first deployment. Yes, the one. Yeah? When I listened to your list on famous and influential films, I was hooked after that. Since I came back stateside, I've spent many hours driving to and fro to see my girlfriend to my barracks. And I can happily say that they've been made all the more enjoyable by listening to you guys. Even my girlfriend Rachel has warmed up to you dudes, which was a pleasant shock to me. She has told me repeatedly that she cannot listen to audiobooks because, quote, quote, hearing people talk on the radio gives me a headache, end quote.

58:53Anyway, I hope you guys continue to make awesome podcasts as I'm headed out on my next deployment. And if you could give a shout-out to Rachel, I'm sure it would make her feel a little better that I got the pleasant people on the podcast to reaffirm how much I love her. That is John. Rachel, hang in there. John, be safe. And thanks for listening. Yeah, man, thank you. That was a great email.

59:15Chuck Bryant:I love that one. Glad we don't give you a headache, Rachel. Yeah, for real. She listens to this song and she's like, oh, boy. Oh, yeah. Everybody's going to get a headache from this one. Like, I came to hate the sound of my own voice from this one. Ah, you'll be all right. If you want to get in touch with us, you can hang out with us on Twitter at SYSK Podcast. Same goes for Instagram. You can hang out with us on Facebook.com slash StuffYouShouldKnow. You can send us an email to StuffPodcast at HowStuffWorks.com. And as always, join us at our home on the web, StuffYouShouldKnow.com.

59:51For more on this and thousands of other topics, visit HowStuffWorks.com.

1:00:02Chuck Bryant:I'm U.S. Transportation Secretary Sean Duffy. We all seem to be in a rush these days, from work to driving our kids around. But when you're behind the wheel, please, do not speed. A few minutes saved by going faster is never worth the risk. So follow the speed limit, enjoy the drive, maybe bring some snacks for the kids, and know that along the way, you're getting quality time with your family. Paid for by NHTSA. Change comes fast. So wouldn't it be nice if one thing stayed the same? Like the price of your Wi-Fi. Thanks to the Xfinity five-year price guarantee, you're guaranteed five years of the most reliable fiber-powered Wi-Fi with no annual contracts and our best equipment.

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