How Chaos Theory Changed the Universe

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It just came out. Jamie, what did you just do? You just sit yourself up for failure.

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with this episode on how chaos theory changed the universe. Welcome to Stuff You Should Know, from How StuffWorks.com. Hey, and welcome to the podcast. I'm Josh Clark with Charles W Chuck Bryant, and there's Jerry over there. So this is Stuff You Should Know, the podcast about chaos theory.

Like, if you've ever seen a vent horizon, I did. Not bad, great movie, or you crazy? I think it was great. Oh, it was so imaginative. I thought it was okay.

It was like a love crafting thing in our space. Yeah, loved it. That's all right. I love craft at it. Yeah, I like that.

“That's what I think of when I think of chaos.”

You know, there's that one part where they kind of give you like a glimpse behind like the dimension that this action is taking place in. Yeah, to see the chaos underneath and you should check that out again. Yeah, I think about Jurassic Park. And Jeff Goldblum is the creep.

Dr. Malcolm explaining chaos in the the little auto driving SUV or whatever that was. All right. Yeah. That's why it was called in the script, the auto driving SUV scene. Yeah, and you know what, he actually rewatched that scene.

And it confirmed two things. One is that he actually did a pretty decent job for a Hollywood movie. Uh, the very rudimentary explanation of chaos. Yeah, um, and you watched it for this. Yeah, okay. Yeah, just that scene.

Yeah. And then it also confirmed of what a creep that character was. Yeah. If you watch that scene, he's like, you know, he was all gross and flirty with her right in front of her x. All right.

But there's this, you know, he's talking to her.

I didn't even notice this at first.

He like, he just like touches her hair out of nowhere for no reason. Really? He's just talking to her and he just like grabs her hair and touches it. Yeah, and I'm like, what a creep. I know, if you look closely, you can see the hormones emerging through his chest hair.

Yeah, it's grody. And I love Jeff Goldblum, it's not a reflection on him. He was basically doing Jeff Goldblum. Well, that's what he, yeah, sure. He's Jeff Goldblum.

“But I don't think that's how in the manner in which he speaks, but I don't think he's a creep.”

Do you? Wow, I've got nothing against Jeff Goldblum. Yeah, okay. I think he's a, uh, I think he's doing Jeff Goldblum. It was also a sign of the times, like if that movie were made today,

Doctor, uh, what was her name in the movie? Elie Sattler, I think? Yeah, Doctor Sattler would be like, uh, it's very inappropriate to stroke my hair. Food. Yeah.

Like, don't touch me. Right. But this was the 90s. Yeah, 90s. Free wheeling.

That was eight. No, it was 90s. It was the early mid 90s, I think. Yeah, 92, 93, 94. The book came out in 1990.

And in the book, uh, Ian Malcolm, who's a, k-attition. Yeah, a creep k-attition. Right. He, um, he, he goes into even more depth about k-ass, not sure.

But that was, I mean, that was the first time I ever heard a k-ass theory was from Jurassic Park.

Yeah, me too probably. And, um, it really, it was really misleading.

as from what I researched in this, this, for this article.

“Well, yeah, I mean, you hear the word k-ass, uh, is a English speaker and you think”

frenetic and crazy. Out of control. Yeah, and that's not what it means in terms of, of science like this. Right. What it means, I guess we can say up front is, is basically the idea that

complex systems do not behave in very neat ways that we can easily grasp, understand or measure, right, and not even, even simple systems don't sometimes.

It doesn't always have to be complex, but um, I want to give a shout out an addition to our own

article, who to, uh, when, you know, when it comes to stuff like this, the brain breaking stuff for me. Man, this is a brain breaker. Uh, you know, how is go to like, blank blank for kids, because it's helps. If there's a dinosaur mascot on the page, it's a sure thing we can understand it. Uh, but the the best explanation for all the stuff that I found on the internet was from a website

called uh, a barram, ABA, RIM publications, which turns out to be, uh, the website about biblical patterns and sandwiched in the middle there is a really great easy to understand series of pages on chaos there. Nice. So I was like, man, I get it now.

“I mean, in a rudimentary way. Right. Roll, yeah. Yeah. Um, I think even a lot of people who deal with”

systems that display chaotic behavior, which I guess is to say basically all systems eventually

under the right conditions. Yeah. Um, don't necessarily understand chaos. Yeah. And they define a complex system as specifically, it doesn't mean just like, oh, it's complex. I mean, it is. Right. But specifically, um, they define it in a way that helped me understand it's a system that has so much motion, so many elements that are in motion, moving parts. Yeah. That it takes like a computer to calculate all the possibilities. Right.

Of like, what that could look like five minutes from now, 10 years from now. Right. Uh, so before computers came around, we before the quantum mechanical revolution, it was, there's a lot more basic. It was like, what comes up must come down. So yeah, let's talk about that. Chuckers, because when you're talking about chaos theory, it helps to understand how it revolutionized the universe by getting a clear picture of how we understood the universe

leading up to the discovery of chaos. Right. Yeah. So prior to the, um, the scientific revolution, everybody was like, oh, well, it's, it's God. The Earth is at the center of the universe and God is spinning everything around like a top. Right. Yeah. It was all a theistic explanation. Then the scientific revolution happens and people start applying things like math and making like mathematical discoveries and and figuring out that there are, there's order. They're finding

order and patterns and predictability to the universe. Yeah. If you can apply mathematics to it. Yeah. Specifically, if you can apply mathematics to the starting point. Right. Right. So if you can, if you can, um, figure out how a system works mathematically speaking, right? Yeah. You can go in and plug in whatever coordinates you want to. Yeah. And watch it go. You can predict what, what the

outcome is going to be. And what this is, it's based on what at the time was a totally revolutionary

“idea. Um, by initially, I think they cart was the first one to kind of say, uh, cause an effect”

is a pretty big part of our universe. Right. Yeah. It was sort of like where, this is 1600s where early science met philosophy. Right. They kind of complemented one another as far as something that's we're, we're talking about determinism. Right. So that was the, the kind of the seeds of determinism was the scientific revolution. And like you said where philosophy and science came together in the form of day cart. Right. Yeah. And then Newton came along and we did a whole episode on him. Yeah. January

of this year. That was a good one. It was really good. Like, I think you said in that episode that there's possibly no science that's changed the world more than Newton has. Maybe he's, he's got legs. People shouted out others in email, but um, I'll just say he's at the near the top for sure with some other people. The cream. Yeah. So Newton came along and Newton said that was his name. Isaac the cream. Newton. Right. I think in any time he'd dunk to be like cream. Yeah. You just got creamed.

Oh, I thought he was a boxer. He's a basketball player. Uh, he was much more well known as a boxer, but he definitely could dunk as a, as a B ball there. Yeah. So um, man, that threw me off a little bit. That's right. The cream. Yeah. The cream comes along and uh, he basically says,

terms. And he comes up with all of these great laws. Yeah. And basically sets the stage, the foundation for science for the next three centuries or so. Yeah. These, these laws that were

so rock solid and powerful that scientists kind of got ahead of themselves a little and said,

we're done. Like done with Newton's laws. We can predict, uh, we can predict everything if we have

“a good enough beginning accurate value to plug into his equations. Yeah. And they weren't, I think”

there was a little hubris and a little just excitement about like, we'll be figured it all out. Right. That that you could take Newton's laws. And if you had accurate enough measurements, you could predict what the outcome would be of that system that you plug those measurements into using this formula. Right. And at the time, a lot of this was like a planetary like, well, we know that these planets are here and they're moving. Right. And they're orbiting. Yeah.

So if we know these things, we can plug it into an equation and we can figure out what it's going to be like in a hundred years. Exactly. And they figured out the basis of determinism is what we just said that if you have accurate measurements, you can take those measurements and use them to predict how a system is going to change over time using differential equations. Right. Yeah. So this is what Newton comes along and figures out that you can describe the universe in these

mathematical terms using differential equations. And like you said, there was a tremendous amount of hubris. And well, I think you said there was some hubris. I think there was a tremendous amount of

hubris where science basically said, we've mastered the universe. We uncovered the blueprint of the

universe. And now we understand everything. It's just a matter now of getting our scientific measurements more and more and more exact. Yeah. Because, again, the hallmark of determinism is that if you have exact measurements, you can predict an outcome accurately. Like the the pool queue example. They're the pool table example. Right. Right. So if you've got a pool table, let's say you're playing some nine ball. Right. So you have that beautiful little diamond.

Yeah. Set up. You got your cue ball. You put that cue ball and you crack it with the cue. And

“if you are super accurate with your initial measurements, you should be able to mathematically”

plot out the angles where the balls will end up. Right. Exactly. Like you can say this is what the table will look like after the break. If you know the force, the angle, all those little variable, temperature, if there's wind in the room, like the felt on the table, like everything, the more specific you are, the more accurate your end result will be. Right. And then one of the other hallmarks of determinism is that if you take those exact same initial conditions and do

them again, the table, the pool table will look exactly the same after the break. Yeah, which is pretty much impossible for like a human to do with their hands. Sure. But the idea at the time of science is that if you could build a perfect machine, sure, that could recreate these conditions, it will happen the same way every time. Right. Yeah. And this, I mean, this led to, they had hubris, but you could understand it when like literally in 1846, two people predicted Neptune would exist.

Yeah, within months. That would exist, but does exist. Right. And this is not by looking up in the sky, like they did it with math. Right. And they were right. Yeah. So imagine an 1846 when that happens, they're like, yeah, we've got the math down, so we're pretty much all knowing. Well, plus also, for the most part, these, that's just with Neptune, they were finding that this stuff really paned out. It held true for everything from, you know, the investigation

into electricity to new chemical reactions and understanding those. Yeah. And it, it laid the scientific revolution, laid the basis for the industrial revolution. Yeah. And just the change that came out of the world like that. It definitely, it is understandable how science kind of was like, we got it all figured out. Well, and like you said, they, um, even Galileo was smart enough to know

“there's uncertainty in these measurements, like the precision is key. So they spent what is”

the article say a lot of the, much of the 19th and 20th century, just trying to build better instrumentation to get more and more smaller and smaller and more precise measurements. Right. That was like basically the goal of it, right? Yeah, which was the right direction. That's like

exactly what they should have been doing. Yeah. The problem is they, like you said, Galileo knew

that there was some sort of, there, there are going to be some flaws in measurement that we just didn't have those great scientific instruments yet, right? Yeah. It's called the uncertainty principle.

you can overcome that. And that the, the more you shrink the, um, air in measuring the initial

conditions, the, the more you're going to shrink the air in the outcome. Yeah. It'd be proportionate. Right. They were correct. The thing is, they were also aware, but ignoring in a lot, in a lot of ways,

“some outstanding problems, specifically something called the end body problem. Yeah. You know what?”

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All right, took her back. So there's some issues, right, with determinism. There's some weird problems out there that are saying, like, hey, pay attention to me because I'm not sure determinism works. Right. And one is the end-body problem. Yeah, how this came about was an 1885 that was King Oscar number two of Sweden and Norway. Yeah, don't want to leave it. Norway, both. He said, you know what? Let's offer a prize to anyone who can prove the stability of the

solar system. Yeah. Something that has been stable for a long time before that. And a lot of the most brilliant minds on planet Earth got together and tried to do this with mathematical proofs and no one could do it. And then a dude named Henri, you got to help me there with that one. Paul Carrey. Oh, say the whole thing. Henri Paul Carrey. Very nice. He was French. Believe it or not. And he was a mathematician and he said, you know what? I'm not going to look at this big picture

of all the planets in the sun and all their orbits. You'd have to be a fool of the planet. Sure, he said, I'm going to shrink this down. Like we talked about, shrinking that initial value. Right,

couple of bodies orbiting one another with a common center of gravity. And I'm going to look at this.

“And this was called the in-body problem. Yeah, which was smart to do because the more variables you”

factor into a nonlinear equation like that, just the harder it's going to be. So he shrunk it down. So the end-body problem has to do with three or more celestial bodies orbiting one another. So Paul Carrey said, oh, I'll just start with three. Yeah. Smart. And what he found from doing is equations for this King Oscar, the sequel prize, was that shrinking the initial conditions, measurement or rate of error. Right? Yeah. Did not really shrink the error in the outcome.

Which flies in the face of determinism. What he found was that just very, very minute differences in the initial conditions fed into a system. Yeah. Produced wildly different outcomes. Yeah. After a fairly short time. Yeah. Like, let me just round off the mass of this planet at like the eighth decimal point. Right. And like, you know, who cares? Who cares? At that point. Yeah. Let me just round that one to a two. Right. And that would throw everything off at a pretty high rate.

“Right. And he was 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 my note to get the equation or whatever, the sum that you want. Right. Well, not only that sum, I guess, but the result. Not only that. And this is what really undermine 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 like the the movement of a celestial body around another. Yeah. It's literally impossible to get infinitely an infinitely precise measurement. Yeah. Which means

that we could never predict out to a certain degree the movement of the celestial bodies. Like

he was saying like, no, you can't get, you can't build a machine there. That gets measurements enough that we can overcome this. 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. Yeah. He discovered dynamical instability or chaos. And they didn't have super computers 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. So there is this dude 70 years later named Edward Lawrence.

Edward 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. He's a scientist who dabbled a meteorology. Right. And he was a mathematician. Yeah. But he was really into meteorology because it 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.

Sure. People were like, "Do you guys know what you're doing?" Yeah. And meteorologists are like, "You have no idea how hard this is." Yeah. Like, yeah, we can predict it a couple of days out, but after that, it's just 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. 1962. There were two notorious storms. I want on the east coast and one on the west.

cost hundreds of millions of dollars in damage. Right. And people were like, "You know, we need to be able to see these things coming a little more." Right. Because it's a problem.

“And meteorologists were like, "Why don't you do it then?" So they thought the key was these big”

super computers. Remember the super computers when they came out, the big rooms full of hardware. Yeah. It was amazing. And they were finally able to do like these incredible calculations

that we could never do before. I know. They were able to like crunch 64 bytes a second.

Yeah. We had the abacus and then the super computer. Right. It was nothing in between. I looked up the computer that Lawrence was working. Was it the wiper? A royal McB. What was the wiper for games? Was it a called the wiper? Yeah. WPR. Right. I can't believe they called it that. I don't know. So the guy just nicknamed it Joshua? No Joshua was the the software. Falcon was the old man who designed all the stuff. And his

son was Joshua. And that was the password to get in. Oh, that was the password. Yeah. I guess I was too young to understand what a password was. Yeah. Okay. You didn't even, there weren't passwords at the time. No, password was just shouted at the computer. And they're like, "Okay, access granted." Yeah. So that movie holds up. Does it really? Oh, totally. Yeah, to check it out. Yeah. Still very, very fun. Young Alley Sheedy boy had a crush on her

“from that movie. She was great. Yeah. What else was she in recently?”

When she in something? Well, I mean, she kind of went away for a while and then had her big comeback with the indie movie High Art. But that was a while ago. Has she been in anything else recently? Sure. I think it's something, something recently and I didn't realize it was her. Oh, really? She looks familiar. I was like, oh, that's Alley Sheedy. I don't know. All right. I could look it up, but I won't.

As the matter. Anyway, I still crush on her. So the Royal McB was not quite the wap or you could actually sit down at it. The Royal McB. That sounds like a hamburger, too. It was by the Royal

Typewriter company and they got into computers for a second. And this was the kind of computer

that Lawrence was working with. And it was a huge deal. Like you were saying, abacus super computer. Yeah. But it was still pretty dumb as far as what we have today as 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 meteorological. I like how you said it. Calculations, which is very basic because they're infinite meteorological calculations, probably. Yeah. Depending they're saying wrong again. No, no, no. Like it sounds like you're about to say it wrong. Then you pull it out at the last second. Maybe. It's really impressive. But so that's very basic. But he wanted to start out, you know, with something attainable. So he narrowed it down to 12 conditions, basically 12

calculations that had, you know, 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 the McWapper. What was it? The Royal McVee. And I'm going to get a print out. So you can visualize what this looks like. Right. So things were going well. And he had this print out. And everyone was amazed because

these these calculations never seemed to repeat themselves. He was making like like word art.

You remember that? That was the first thing anybody did on a computer. Oh, yeah, yeah. It was to make word art like a butterfly. 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 that right kind of brain for that. Right. Or you have to be following a

“guy book. Well, you have to do it. True. Have you ever seen me, you and everyone we know?”

Yeah, 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. Alley, she's not in it. No. It's Miranda July. Right. And she like wrote and directed too. Right. She did a great job. It's one of those rare movies where

like there's just the right amount of whimsy because whimsy so easily overpowers everything else and becomes like, yeah. Yeah. Yeah. Yeah. This is like the most perfectly balanced amount of like whimsy you have ever seen in a movie. Yeah. There's too much whimsy. I just like terrible garden state. I just want to punch it in the face. It's terrible. 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

to a lot of movies today. Oh, yeah. Well, we're stalling. We haven't even talked about butterfly

“effect yet. We're just coming. 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 I'm going 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. So the print out he had went to

three decimal points. Yeah. So he was working from the print out 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. Yeah. But sort of accidentally came upon it.

“It's neat that this guy did this because it changed his career. I think you went from”

emphasis on meteorology to emphasis on chaos math to stud scientists. Basically. So look, 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, like, what was his name, Poencarre? 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 rolling convection current Chuck is where you know how the wind is created where air at the surface is heated and then starts to rise and suddenly cool air from higher above comes into fill that vacuum that's left and that creates a rolling or vertically based convection current. Yeah. Okay. You could I would describe it as oven. oven boiling water? Yeah. 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. Right.

And this is the one he picked out. But had you seen my hands moving listeners? You would be like, oh, yeah, I know it's a timer. He made a little rolly motions. So he's like, okay, I can figure this out. So he comes up with three, 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 this, these three formulae 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 there's three, you graph them out on a three dimensional graph. So X1 and Z. Again, he wanted to just be able to visualize this. Right. Because easier for people to understand. Who's 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 Lorenza's looking at this, he was expecting these three things to equalize and eventually form a line.

“Yeah. Because that's what determinism says. 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 Poincar A 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. Like there was an order to it. But the lines were not on

top of one another. Like let's say draw a figure eight with your pencil. And then you continue drawing that figure eight. It's going to slip outside those curves every time unless you're a robot.

Ever. It had a lot of really surprising properties. And at the time, it just felt completely outside

“the understanding of science, right? Yeah. Luckily this happened to Lawrence, 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 look like butterfly wings a little bit.

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. It's a conference that I'm going to. And I'm going to say something like, you know, the seagull flaps the swings and it starts a small turbulence that can one that can affect weather on the other side of the world. Right. The small little thing will just grow and grow and snowball and affect things. And he had a colleague who was like,

“see, go wings. That's nice. All right. 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. Yeah. Should we take a break? Yes.

All right. We'll be right back. Hey, I'm how to cop the host of the podcast. Joy 101 with Hota Coppy together. We're going to have meaningful conversations with the world's most fascinating people, like when actress Olivia Munn shared how she overcame fierce health challenges. I've gone through breast cancer and then helped my mother through breast cancer. And that was more difficult. There's a

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“the hottest names in the culture, like Swaley. Do you realize how legend there you are?”

I appreciate it. I've seen him and I'm like, man, I still got so much more to do. Like, Prince, he's got like 30 albums. We've got like five right now. That's the rate we've got to be going. Yeah, that's a good attitude. You also hear stories from industry legends and hip-hop pioneers, like Fab-Five Freddy. I directed when Naz is their early video. Which one? One love. Well, I literally filmed in his apartment in Queens Bridge. His mom's been still up in that apartment.

Naz was just beginning to take off. His pop shoes to live near me in Harlem. His dad introduced him to a whole lot of, you know, conscious stuff. And he made a young prodigy. No matter the era, drink champs brings you the biggest names and the most unfiltered conversations. Listen to drink champs from the black effect podcast network on the iHeart Radio app. Apple podcast or wherever you get your podcast. Keith Jumunk of seemed like a mild mannered suburban dad. But secretly,

he became someone else. A master of disguise who went on a crime spree. At the time, did it seem like a crazy idea? It seemed very crazy. But I felt so desperate that I felt it was the quickest, easiest way out. Did you allow yourself to think about how would you go wrong and what that might look like? No. I didn't want to manifest that. I wonder, I was trying to manifest success. Every family has its secrets. But what happens when you discover that your dad

has been living a double life? That is not the look of an innocent. This is going to change my life and my family dynamic forever because everything that had existed prior in my reality is now untrue. Listen to deep cover the family man. I mean, iHeart Radio app, Apple podcasts, or wherever you get your podcasts. All right. So the Lorenz Attractor is that picture that he ended up with. Right. That caught 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'm a, he says, all right, you're a cycle of chaos. He said, uh, actually, I don't know who wrote this. Good woman could have been a small child. Could have been no of undetermined gender. I have no idea.

10,000 people living in it to make that town work. You got to have like a gas station, a grocery store,

“a library, um, whatever you need to sustain that town. Okay. So all these things are built.”

Everyone's happy. You have equilibrium. He said, so that's great. Then let's say you build some someone comes and builds a factory on the outskirts of that town. And there's going to be 10,000 more people living there. 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 happen. Oh, the right. Like, equilibrium. No, no, no. But you just have more people. So there's, uh, 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 3000, those people just up and leave one day. Okay. And the grocery store guys says, well, there's only 7,000 people here. We need 8,000 people living here to to make a profit. So I'm shutting down the 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. Right. They can't sustain. They shut down. Someone else comes

along because of the demand. And it is this search for equilibrium. This dinet. 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. So an attractor is the state which

is system settles on. Stranger attractor is the trajectory on which it never settles down,

but tries to reach the equilibrium with periods of stability. Is that makes sense? That Bible based explanation was dynamite. I understand it better than I did before. And I understood it okay before. That's great. Surely can add. Yeah. Yeah. Now you're going to add to it? No. That's it? No, I mean like it. Yeah. And a attractor is where if you graph something and eventually it reaches equilibrium, it's a regular attractor. If it never reaches equilibrium, it's constantly trying

to and has periods of stability, strange attractor. I can't, I can't top that. All right. grocery store, small town. That was great. So Lorentz's strange attractor was named a Lorentz attractor named after him. Big deal. They weren't using the word chaos yet. No, but he published that paper about butterfly wings, right? Yeah. The butterfly effect. And it coupled with his picture, is the picture of a strange attractor, which is almost the aside from fractals, almost the the

emblem or the logo for chaos theory. The Lorentz attractor is. It got attention off the bat. It wasn't like Poencarre'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 Poencarre had uncovered, is that determinism is possibly based on an illusion, 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, when does this stability that are found in strange

“attractor graphs? Yeah. 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 work concerned, is the actual state of affairs in nature. Yeah. And I think as far as work 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 drive with how the universe actually functions. Yeah. It's just our understanding of it. Yeah. And we're just so anthropocentric that, you know,

we see it as chaos in disorder and something to be feared. 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

was a philosopher, but he was a philosopher, scientists. Sure. His whole jam was like causing effect

“is an illusion 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. Pre-gravity, whenever everyone's just floating around. Yeah. Going this pencil has got me wacky. But the point was that, you know, we are, 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 an effect as an illusion. I love that guy. This definitely supports that idea. For sure. Sorry. I'm excited about chaos there. You can

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 dinner party. Well, thank you 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 just like, "Moo, a different equation." 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. Well, 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. Those are guy named Stephen Smail, fields metal recipient. So, you know, he's good at math. And he described something that we now know as the Smail horseshoe and it goes a little something like this. So, all right, take a piece of dough

like bread dough. Okay. 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." This is going to be so good. So then you just a little rosemary on it? Yeah, maybe so. Well, see 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 Smail horseshoe basically says, you cannot predict where the two points of that horseshoe will end up. 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, I want imitate force comes. Sure. And I can't do that. That's fine. He's not one he's not on 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. Like all of that coincident stuff that... Oh, I love that. Oh, there was something else. So did the smile t-shirt. Like it was just too much. Like he really hammered it too much. I like that.

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. Is it mechus? You know, it was a good Tom Hanks movie that was overlooked a road to perdition. Yeah, that's a good one. Great Sam Mendes. Oh, man, that guy's awesome. Yeah. Oh, what is he going to do? He might do something. He did the James Bar, he did Skyfall. Yeah, yeah, no, he's can also 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?”

Yes, God. It was just like, yeah, you can go on a jump off a bridge. Yeah, it's like every five minutes during that movie. That 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, I'm, yeah, just take a really good, good mood and be like, I'm sick of being in a good mood.

Sit down and watch revolutionary road. Yeah, watch Joe versus the volcano instead. Great movie.

Where was I, smell horseshoe is what that's called. And that was he was the first person to actually use the word chaos. Oh, he was. I think so. I don't know. York was Tom York's dad. Yeah, you're right. He wasn't the first person. You're correct. But it's mail's horseshoe illustrates a really good point, Chuck. Is it Tom York's dad? No, okay. No, but they're both British

which should, which started out right by each other. Yeah, and definitely two totally different places. Yeah. That applies not just to bread dough, but also two things like water molecules. Yeah, that are right next to each other at some point. And then 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. Oh, sure. 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-ified. So we mentioned York where I was going with that was um, there was an Australian named Robert May. And he was a population biologist. Yeah. 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.

“Yeah. And it was working pretty well for a while, but he noticed something really, really weird, right?”

Yeah. He had this formula, um, the logistic difference equation. Yeah.

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 a animal population, yeah. 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 the past three, all of a sudden, the number of the population would diverge. Yeah. If you pushed it equal to three,

actually, or more. 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 animal hope is not, there's not 30, but there's also 45 of them at the same time. Yeah. 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, oh, yeah. Millions of a degree. All of a sudden, it would turn into four. So there'd be four different numbers for that was the animal population. And then we'd 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 four, eight, 16 chaos, two, four, 16, two, four, eight, 16 chaos. Yeah. 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 work together on this. In 1975, they co-authored a paper called period three implies chaos.

And man, finally somebody said the word. Yeah. I kept thinking it was all these other people.

Yeah. And this paper, they first debuted the name chaos. They based it Tom York's dad based it on Edward Lawrence's paper. Yeah. He was like, you know what, I have a feeling this has something to do with the Lawrence attractor. So that that that provided chaos to the world. And it it was the basically the third the third time a scientist had said, we don't understand the universe like we think we do. Yeah. And determinism is based on an illusion

like don't you get it of order in a really chaotic universe. And this established chaos, it took off like a rocket in the 80s and the 90s, you know, as you know, from Jurassic Park. Chaos was everything everybody was like chaos. This is totally awesome. It's the new frontier of science. Yeah. 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. It became a deeper and deeper field, as you'll see.

understanding of the universe. It was saying like, yes, you can still use Newtonian physics.

“Yeah, like don't throw everything out the window. No. 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. Right. Complex systems. Like determinism,

the ultimate goal of determinism is false. It can never be, it can never be done,

because we can't have an infinitely precise measurement for every variable or any variable. Therefore, we can't predict these outcomes, right? So you would expect science to be like, what's the point? Yeah. What's the point of anything? No, not science. Well, some chaos people have said, no, this is, this is, this is great. This is good. We'll take this, 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. Yeah. Say, okay, here is the fish population, here is the ocean temperature, here are all these other variables. Let's feed it into a model and see what happens. Not, this is going to happen. Right. What happens instead? And this is the kind of the understanding of chaos theory now. It's taking raw data.

It's much data as you can possibly get your hands on. It's precise data as you can possibly get your hands on. Yeah. 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, like, when you see things like, you know, 50 years ago, they predicted”

this animal beats extinct and it's not. Well, that's because the variations were too complex. Right. They tried, right. And that's why, if you look at a 10-day forecast, you sure are a fool. Right. It's true. Well, 10 days from now, it says it's going to rain in the afternoon. Come on. But if you take, 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, you could find a time

when it was similar to what it is now. Yeah. And you could conceivably make some assumptions based on that. You can say, well, actually, we can, 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, like, when that animal is not extinct,

like you thought it would be, you go back and look at the original thing and you have a more accurate picture of how the, you know, data could have been off slightly. Yeah. This one value. Right. And then you have more buffalo than you think. Yeah. Sure. 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 mandal, binwa, mandal bread. Yeah,

mandal bread, mandal bread. Yeah. And go listen to that one and hear me clinging to the edge of a

cliff. Yeah. Clifed. Man, we should end this. But first, I want to say, there is a really interesting

article. It's pretty understandable on Quanta Magazine about a guy named George Sugihara. Mm-hmm. And he is a chaos theory dude. There has got a whole lab and is applying it to real life. So it's a really good picture of chaos theory in action. Go check it out. Oof. Okay. If you want a more about chaos theory, hope your brain's not broken. Yeah, go take some LSD. It'll 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 a listener now. I'm going to call this rare shout out. I'll get requests all the time.

“I'm a bad I know each one of this is. Really? Yeah. Do you think it's 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 the state. My first time listening was during my first deployment.

Yeah. Yeah. When I listened to your list on famous and influential films, I was hooked after that. Since I came back states I'd have spent many hours driving to and fro see my girlfriend to my barracks. And I can happily say that they've been made all the more

which was not a pleasant, sorry, which was a pleasant shock to me. She has told me repeatedly that

“she cannot listen to audiobooks because, quote, hearing people talk on the radio gives me a headache”

and quote. Anyway, 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. But 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 greedy mill. I love that one. Glad we don't give you a headache, Rachel. Yeah, for she listens to this

song. She's like up. Oh yeah, everybody's going to get a headache from this one. Like I came to hate

“this on to my own voice from this one. Ah, you'll be right. If you want to get in touch with us,”

you can hang out with us on Twitter at S.Y.S.K. podcast. Same goes for Instagram. You can hang out with us

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join us at our home on the web. Stuff you should know.com for more on this and thousands of other topics visit howstuffworks.com. Joy is essential and it's also elusive, but now there's a new and exciting way to start your journey toward a more joyful existence. Joy 101. It's a new podcast hosted by me, Hota Kopy. If you're craving inspiration to maximize your joy, tune into these candid, uplifting and moving on-air chats.

Open your free-eye heart radio app search. Joy 101. And listen now. Joy 101 with Hota Kopy is presented by CVS. Juni's Black Music Month. And on the drink champs podcast, we're speaking with the hottest names in the culture like Swaley. Do you realize how legendary you are? I appreciate it. I've seen him and I'm like, "Man, I said I like so much more to do, like Prince." He's got like 30 albums.

We've got like five right now, like that's the rate we've got to be going. Yeah, that's a good attitude. No matter the era, drink champs brings you the biggest names and the most unfiltered conversations. Listen to drink champs from the Black Effect podcast network on the iHeart Radio app. Apple podcast or wherever you get your podcast. Get just came out. Jeremy, what did you just do? You just

sit yourself up for failure. I've never heard you tell this story. I've never told this story.

This must have been tucked deep deep in the Jeremy Linfile. My name is MC Jin, excited to tell you about laugh but not least. I'll be chatting with guests from all walks of life about the power of humor when it comes to facing difficult times. These will be conversations that

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