A conversation between Nassim Nicholas Taleb and Stephen Wolfram at the Wolfram Summer School 2021

i think we're probably ready to get started so well thanks for joining us and um uh so the the main reason that i wanted to have this conversation is because we've been doing this physics project the physics project is a big surprise at how far it's managed to get in physics and not satisfied with having managed to make great progress in physics we're trying to understand how the formalism that we've developed for physics might apply to other things and one of the other things that we think it might apply to is economics and we're not sure if we know what we're talking about and i figure you're a good person to tell us if we know what we're talking about um and we haven't we're not finished with trying to figure this out but i guess i guess one thing i mean i know you and i have talked before about you know economics is not really a scientific kind of thing and and somehow i'm trying to understand you know i i i view there as being some kind of talabian economics because by the time you know by the time it's a big book that they are full of full of uh wonderful formulas and things this is a whole giant technical tower that seems to be based on gas go ahead it's this is not the book the book is the next volume this is like to get fat tails out of the way which is not really the central point okay so my uh if i were to define i mean i said okay my my uh my work was maybe not my work it's you know my application the app my my own versions of work done elsewhere maybe in the real world is the following is you're missing a layer of dimensionality in economics so for example you take the any equation an equation that has a sigma all right volatility okay and you tell yourself what if that parameter is right on average but not uh but it's variable chances inequalities effect so the function of an average is not an average of a function so it all comes from that by saying i'm adding a layer of stochasticity to things so it all started when i was when i started doing and i remember i was i was programming in mathematica the option formula and i figure out the following trick it's a very simple trick okay you take the black trolls you price the option at 10 percent higher volatility which was about the the variation of volatility that we had and you know over time and then you should explain for people that volatility is is the the variance of this time series for exactly the square square the the square root of the variance of that that the expected time series annualized okay and it's a parameter for an option because an option has some convexity that depends on that so it's very simple you price the option at instead of pricing the option that says sigma you price the option at 110 percent of sigma and you price it at 90 percent of sigma and see the effect very simple heuristic and now that heuristic i haven't discovered anything else in my life so wait a minute when you say price it at that there is a black shoals formula which tells you what the exactly should be priced at given a particular volatility and you see what happens let me give you a demonstration using mathematica all right and i'm going to do using mathematica and i'm going to do it using the gaussian distribution and how we can obtain fat tails from gaussian distribution okay okay so do you mind i'm a little slower than you from mathematica would you guys be patient with me right yeah yeah we'll we'll we're uh so let me uh unless i can find an existing program let me do the following uh share screen share screen and then i have mathematica untitled two okay and i i do the what window uh magnification uh hundred fifty percent will it'll probably be okay yeah a hundred fifty hundred fifty percent let's try that okay so let me do it in mathematica and let's do the following all right let's say here i have pdf okay normal distribution normal distribution okay it's mu and sigma let's say mu is zero and sigma let's say is one point one okay ten percent higher x plus pdf normal distribution 0.9 x okay you do that one half okay and actually i can let me let me do this uh let me do this and say plot plot pdf normal distribution x minus uh four four okay okay okay you have a a sort of like a fairy tale gaussian okay so here let me do i can't tell that's fat tailed i mean for me that just came but let me show you how we can tell if it's fat tail one plus a okay and here one one minus a okay and now i don't manipulate okay a uh zero probably to something yeah but but it's easier to do it discrete okay zero point one point two point three point four okay and uh and we do a control with it okay plot i do i do two things i do and i do a control with it as a normal distribution okay pdf normal distribution with x uh at just one okay yep all right now we do manipulate you can see that they coincide okay they don't concern no more right okay you got fat tails uh-huh higher shoulders okay so this is one way to say that there are two ways to to do the thing and and to write let me write using mathematica here okay i have f okay of sigma f of sigma okay i do f of sigma average f of sigma versus f average sigma yep okay and the difference between them gives you a bias okay so everything i've done is variation around these okay but nothing particularly more intelligent than this okay except that you go in higher dimension you start playing with correlation you start playing with other things but there's not much more intelligent than this as as we as you can see okay look here you can get extremely fat tails here uh say 0.9 0.9 uh yeah this is what happened here that's okay just just but the pull down will will should have a point nine in it there you go look how crazy it is and let me do a plot range all here plot range all now this is a rough way to do this uh game you see a very rough way to do this game but you can make a stochastic you'd rather have a second layer of stochasticity but the the problem is when i take for and let me apply this to anything in economics all right let me just explain what you mean by a second layer of stochasticity what you're saying is the first layer of stochasticity is there's a random walkish thing that's bouncing around with a certain hex exactly and the second level of stochasticity is this variance of the variance exactly exactly the variance has a variance here i use the bernoulli for the variance okay two state thing but then you can make it more complicated and more complex so the uh and and the way i traded options is i discovered that because an option instead of taking an option off the average variance you take an average option across a two-state variance now it makes the the out of the money options the options that are remote you know it it increases the price uh considerably so why isn't this thing that you're constructing from these two two options oh it's because of the the the non-computing of averaging and taking the function f function f is your option function exactly so as an option trader i function like that all the time whenever i see a parameter and i told myself you don't need to fix economics all you need is introduce a second layer of uh stochasticity into the game you know for the sake of some of the people who are here maybe we should explain what an option is uh okay no no but i mean maybe it's complicated to go into options because i discovered it with a complicated thing but i can apply it to simpler things i i love the way that you refer to functions in terms of puts and calls where some people you know if you do machine learning it'll be re-lose if you do you know it'll be polynomials for other people but um maybe an easier way to do things is an example i give an anti-fragile okay let's forget this you have a grandmother i mean i'm a lot of the high school people still have grandmothers around okay and if you don't have grandmothers think of grand uncle all right to make it uh gen well distributed gender and uh geographic and everything okay so you have grandmother or grand uncle you pick it's your choice okay now your grandmother or grand uncle is gonna spend um what's the best temperature uh say 70 degrees no in florida 70 degrees fahrenheit uh-huh okay in florida no it's a great time so what is better okay to have the person spend day one and day two at 70 degrees or to have your grand uncle or grandmother spend the first day at zero degrees and the second day at 140 degrees for an average of 70 degrees what do you prefer the first case or the second case okay wait a minute go through the cases again zero degrees and 140 are very bad for humans 70 70 okay okay four zero one forty yeah okay fine is this big enough or you can yeah yeah this is fine okay so you can make it this way so it's the same game i'm playing okay and i discovered uh something called ricardo uh have you heard of ricardo's comparative advantage i've heard of it other people probably have now let me let me explain it very very simply that i i realized there's something wrong in economics because they believe that 70 and 70 or 0 140 are equivalent they only look at the average of the parameter so so i started spotting in central papers in economics or central books something and the error you can see it in ricardo and ricardo came up with the following idea right he said that countries should specialize where they have something called a comparative advantage not absolute advantage so let's say that um you're the best brain surgeon in town but also happen to be the best person in town at uh driving an uber okay you're not gonna do both okay you're gonna do what makes you the most money and let someone drive the uber although you're better at both so and in the example uh ricardo and all the economists use the story of of portugal versus the uk and wine versus cloth by saying okay portugal does wine we do the clothes because of this concept okay and they consider the average price like here the grandmother 70 degrees okay which is the average now i came up with what if there's a fatwa on wine in portugal right now what would ha or what if you something so if the average is let's say the come up with 70 and 70 equivalent okay the price and they give you the calculus of that the calculus falls apart under introducing a very simple layer of stochasticity in other words making these numbers random okay that's very simple so i started doing this and it's explained in the back of antifragile and no economist has to date been able to grasp what i was talking about okay we might have some sample economists here we'll see what they're doing i mean the the i'm saying your model is right okay it okay but you gotta consider what would have you know maybe it's right maybe it's not right but you got to consider some layers of casticity so we can apply this to economic without going into options something very complicated i'm applying it applying it first to your grand uncle okay and and next to uh wine versus claus and ricardo's example which is taught in every like uh book in inter no beginning beginning in economics 101 okay and i applied that to the gaussian distribution which is a very simple 101 okay of what you learned when you learn about probability you learn about gaussian distribution and then we can apply it to other things something very very very very simple other thing so what happens if i make that price all right that is deemed to be fixed i make it stochastic variable now someone may tell me how do you know it's this distribution not that distribution they start arguing and i tell them it's fine now we're talking about details well i mean but but so one question is yeah you know the central people in many fields including i suspect economics believe the central limit theorem tells them everything it says that you know all distributions end up being gaussian and i think you know as soon as you're talking about fat tails you're away from that story that's why we have mathematica here all right so let me explain the central limit to everyone here using mathematica okay so uh let me make a uh have you heard of uh okay r equals all right rhinovariate variate uniform distribution okay don't let me see my screen because it's not shown in my screen okay here's a form distribution okay so i do r and it gives me a number between zero and one okay i can make a discrete uniform doesn't matter okay all right i can make a zero one so let's do here table r then three okay or let's say 10 5 histogram i know i could put upstairs but we're going to see why i need r to be separate okay look what you get you get numbers between 0 and one like that okay now let's do the following if i adapt two numbers obviously i'm gonna get the maximum the most likely probability at one okay because you get one one half one and a half point one one point one but to get here on the left zero or to get two okay you need a lot of work or help from god because only two can give you two and zero continue to no combination can give you that all right so as you see now already you see the distribution is already not flat anymore the sum two distribution two two numbers and you already have this distribution now let's do it this way plus r your or you almost have a gaussian by summing up three numbers okay look all right so this is called the central limit theorem and the our condition under which as you sum up numbers or average numbers same thing however you want to do it okay we can average them okay you get the same so no no sorry okay average now you know so so however you want to do it okay as you sum up numbers you end up with a a gaussian now i picked this one because this is the one that goes there the fastest but you can pick the random walk random ones and zeros okay the you sum them you know you do it so many times then you have a binomial and so on you get a gaussian if you want i could give you this uh as an example but but we can speed up so that's the story in every textbook yep my problem is that this reaches the central limit very very quickly so let me stop here and tell you there are two theorems that work together in economics and in statistics and everywhere one is called the central limit that we just saw means you can use a gaussian if you have a sum that's large enough without going into details okay and the second one is a lot of large numbers which tells you that as you sum up that stuff you get the average okay so for example let's do a distribution of the average of this okay you do the distribution of the average i i do a random variant uh any distribution let's say i take uh i take uniform distribution because all right and then i do a hundred i mean so here if i do table of that discrete plot so if i do many many times or if i can do this table of this forget having a hundred i just do 30 let me do 30 okay okay mean and i do it uh say 10 000 times instagram and and and the reason i mean the reason i'm invited here is because as an amateur you want to play with things and to play with things you gotta do monte carlo and other programs are little uh uh uh i mean mathematica i think in terms of mathematica so i you know i i i i love seeing you actually use ten to the four with a superscript that's that's that's yeah i hate it i hate that i hate the other the the other four i hate the aesthetics of it are not not okay so so look what you're getting here the distribution of the mean is very concentrated okay if i go to 100 and if i take 300 you see look at this if i take 300 it's going to be even more concentrated okay look at this most observations are between 46 and uh and my observation between 48 and 52 okay that's called the the law of large numbers that you're gonna have the distribution of your mean compressing as your sample becomes larger okay and the variance of your mean is going to be small now i realize that when you work in an environment that is called extremistan all that only holds at infinity if it holds let's do a very simple solid experiment with a different have you heard of pareto 80 20 pareto distributions yeah right so anything or any distribution let's say let me take a student t distribution okay fat tails student t is uh has parental tales okay the let me see pedagogically since we have high school people and we have physicists i don't want to board the physicist and i don't want to upset the high school students so let me find the most well-known distribution is the pareto 80 20. okay this maps to pareto distribution one okay it's about one and one point one uh four okay all right and let's see if i do this one yeah sorry show the pdf maybe okay so let me do the the pdf pdf this x minimum value is one one [Music] so now plot sorry pdf x112 is now supposed to do pd operator distribution x sorry okay so this is how it looks like okay this is how the distribution looks like it has most of its values here and it has one excursion in the tail and the reason it's called 80 20 is because 80 percent of it lives in 20 of the of the range exactly so if i do the the the cdf of the you know the the the cumulative without going into detail eighty percent of the people will own twenty percent of the land and twenty percent of people own eighty percent of the land and if you recurse it means that one percent of the people who own 50 of the land uh-huh so so you continue with it so when i when i uh so that's a pareto distribution now let's do a random variate with that distribution we do random variant okay and let's do 30 all right the problem with this you guys left the pdf in there sorry no random variant uh so yeah pdf so so the so you get a lot of numbers and and and and you i do a table and i do take the average of 30. so i got the mean okay as as you can see the mean fluctuate every time i get different numbers and i here at the table the mean and i do 10 to the four okay you want to you want another battery table 10 to the four now yeah i need the bracket here and then i do histogram so no i was looking for diego there at the same time this is why uh so maybe here i can make it cleaner no i think you just want larger number there right yeah i want a lot of number no no i'm so you know what you're sorry that you've got an instagram thing you want to get rid of the thing for the histogram you want to change your 10 to the four right yeah no the range the problem is let me just show you this is not this is a feature not a bug as i say because some some averages are at a thousand and the histogram is showing uh all the range oh i see i see i see you see what i mean so some of them you cannot control from up there right from here you cannot control because you don't know where you're gonna get right and there's a black swan wandering around on the other on the tail there so you get this uh and and even better if you do this okay uh you do this and then you do the max you even you're even going to be more surprised with the max you're going to be getting this max is 19 and you can get 28 12 but sometimes you get 2 000. like here we have a thousand okay so max for an average at a thousand which means that the the the the max was maybe 30 000. 23. and then you got a 30 000. so if you have the patience you play with these so this one will never be follow the the this one will never obey the central limit theorem okay and and we can we can but the conditions of the central limit theorem are that the distribution has bounded variance this doesn't have bounded variance right but there's something even worse it has it obey the condition to obey to get to the uh what's named the the large numbers is have bounded mean no which this one exists the mean here exists if you look at the mean is going to be uh alpha or one over one mass alpha it's going to be around eight okay uh okay so but it has a bounded mean but the problem is that that given that the variance is infinite okay that mean is going to jump around a lot so the idea is to get the same stability you get with the gaussian upstairs with 30 observations how many do you need let's get let's let someone guess all right people how many how many who can venture a number come on we've got lots of people here somebody into the six how much 10 to the six who said 10 to the six why do you exaggerate so much i just pick the extremes and i have to make a choice okay you're not exaggerating you're as a matter of fact underestimating 10 to 13 10 to 13. to compress the variance enough in other words to get the mean and you're the same reliability for the mean for a sample of 30 you need 10 to the 13. okay so economically i mean if you're a trader everybody's dead by that time exactly so you got to work with other techniques to figure out the mean some other characteristics of distribution the whole idea is that maybe you don't need to know the mean you need to know other properties okay but the central in this environment is that economics has been using distribution that are more like this one on one hand they say well either genie is high or concentrated on the other hand using tools designed for the variants thinking that with end of 30 they're happy so let's uh okay so i want to if we could try taking this in a something that goes further towards the fundamental physics story okay because this phenomenon of gaussians all that kind of thing it's a thing one in physics you know those kinds of things show up in statistical mechanics and one of the questions you know when you have a bunch of gas molecules bouncing around in a box the you know the averages end up being these gaussian kinds of things there are occasionally long tail phenomena but mostly in statistical mechanics once concerned with things that end up being sort of uh roughly gaussian and so on so the question you know in what we've now been able to understand in physics is that just like there are discrete gas molecules bouncing around in boxes to make fluids and things so also there are kind of discrete atoms of space that make space time and so on so that may seem irrelevant but the question now is let's try and think about economics and let's ask what are the atoms of economics in other words if we try and break down an economic system into the kind of smallest elements of what's going on what are those smallest elements and do they aggregate up to something which is like statistical mechanics or like what we see in our physics project okay i have i have let me make a side comment before i answer yours um and the if i up if i maximize if i say i'm trying to maximize the entropy of the distribution you know maximize entropy is the the expectation of p log of p okay or in this case continuous case p of x log of p of x okay so if i maximize entropy under no constraint i don't know if you can get a distribution and no constraint i think under no constraint you get uh a pushy or reverse outcome so if you maximize entropy under constraint of variance and mean and variance i think i have the mathematica file here somewhere you get a gaussian so you have to realize that you're you're bounding the equivalent in physics would be by you know you're putting a boundary on energy because it varies is energy or whatever you want to define it okay so the problem with economics is that we don't have anything binding a number like like i remember when when uh feynman was giving his lecture one of years ago thirty years ago i remember saying oh we talk about astronomical number we should be talking about economic numbers what do you mean uh he said you know there was expression very large number astronomic numbers yes he said now that the deficit is reaching billions and billions of billions we're talking about economic numbers okay and and in the blacks one i explained that i said the price can go from one to a billion or like say bitcoin tomorrow people decide to price it for uh a hundred billion dollars each bitcoin you know be my guest that number is meaningless all right because there's no boundaries on on well okay so this is a very interesting point okay so one thing i wanted to come to is sort of the definition of value in economics yes and you know in a sense you're saying you know what i'm trying to understand is you've got it seems an economic system some network of transactions that are happening i mean i don't know how you view sort of at a granular level what is an economic system it's presumably a bunch of people making transactions with each other is that is that the correct picture no the way i view economics is completely different representation let me tell you my the way i view the world and i see it from finance and economics in finance i'd use the what is arbitrage uh-huh and economics i view the world as law of one price okay so the the things converge that you cannot have one good okay priced at one dollar and have an identical good price that's seventy to seventy two dollars that's a lot one price and i've used it for example to explain why there are laws defining the relationship between currencies called you know the purchasing power parity of stuff like that but let me give a very simple example if the swiss franc in switzerland is multiplied by 10 and if you have free exchange between switzerland and france then no person um except for those under substances or stuff like that would buy goods in switzerland they would go buy them in france right so so another and then what happened is that the the vendors in switzerland would not be able to sell and the currency will depreciate and and and the french currency assuming it's its own currency would appreciate and then sure enough then you have the same uh parity between currencies okay so so in other words and i i traded securities as as a trader looking for similarities between island price differently so for example if you have a an option on this item and correlates heavily on that other item i can use one a substitute for the other at a cheaper cost and this is called the replication business so i wrote my entire business into something i called dynamic replication and that was actually my doctoral thesis how to dynamically replicate an item into another dynamically you could probably replicate an option into a stock or stock into an option or something by replicate you mean that the distribution that all these various distributions that you compute for one of these uh instruments agree with the distributions you get for the other instrument exactly or dynamically for example if you own a stock or you okay and sorry if you own an option or you own a stock that you buy and sell continuously you replicate it right except that when when you're under fat tail these don't work dynamically now with my subspecialties breakdown of these theories locally and and where they don't break down so to to to go back i mean re re put it and understand formal clarity uh my first answer that in economics we don't have energy when prices are concerned so so for example a currency like the the the mark the the the mark of the reichsmark i think if i forgot the name of germany during weimar went from one to a dollar to three trillion to a dollar right but you cannot have a random variable okay that can reach that level in the physical world that easily okay so so i don't think i mean i think that the analogy between with value is probably not energy it's probably something more to do with the way that an observer samples the system i think that's something can be much more arbitrary okay i think in modern economics or the way i view i'm not an economist i'm a financial economist and and for us we don't know what value means we have arbitrage replication equivalent well okay but so so for you i mean so by arbitrage i mean one way to think about arbitrage you know the physics point of view is it's like curvature in a space you go you go around a closed path and you you know you're you're taking 90 degree angles going around a rectangle you don't get back to where you started from again i mean that's kind of a a physicist analog of arbitrage in the sense that you go around a loop you know you go around this financial loop you're converting this to that you're converting this to that yes and it doesn't close you you know you make money by doing it by going around that loop or you make little residual money because effectively uh the world is uh not as uh finance is not as inefficient they're called inefficient where you can find that stuff right and let me give you an example in finance where uh where my idea breaks down and why in fact in the long run it tends to hold i don't know if you remember at some point uh i think volkswagen is own sport or one one company owned the other and the company that was owned his market value was higher than a company that owned it i was like that happened with palm right that was the that happened with porsche uh it happens periodically or you have these absurdities and and but you cannot arbitrage it because you have some idiot holding on to shares and doesn't want to sell it to you okay so for example so you have things that make uh markets uh not as you know frictionless and efficient but in general in general in general uh market tend to be not that stupid so in other words you can have stupid pockets of inefficiencies but they don't last for a long time they may last a year two years they don't last decades and the last decade they don't last for a century you see i thought they only lasted minutes in many cases in many cases when you have a focus or you can replicate easily something against the other it's last seconds okay like for example uh when uh you know but they're things that last longer i was doing currency option arbitrage between a currency option using what are called triangle arbitrages if you buy new zealand dollar volatility an option against uh australian dollar do australian dollar against hong kong dollar hong kong dollar against something else and end up with enough money to go pay for your rent you get the idea so so you you you could so you could do these things um for you know and and have you know sip a drink while doing it you see whereas but there's more narrow arbitrages they take nanosecond so and you have statistical arbitrages where you're making a bet on statistical relationship and you think in the long run you're going to do okay thanks to the law of large numbers so but trying to come by and trying to say they are foundational economics uh i think i read enough books on economics that say that but to tell you how unimportant it is that i forgot about it i forgot what they are if they say foundational economics is i'm not sure there are well-defined foundations i mean it's not a it's not like an axiomatic theory i mean one might think there was a version of economics where you start from sort of axioms of human psychological uh behavior or something we have in finance uh axiomatic stuff that's quite robust but uh and effectively linked to what i'm talking about absence of arbitrage from the free launch theorems of arbitrage complete markets uh having a pricing kernel or things like that they are but the problem is they're made under strong assumption in other words they assume that some linearity somewhere so they make assumptions that don't hold in the real world but by linearity you mean i mean do they are they things that depend on things like you know fixed point theorems or are they things that depend on gaussian distributions uh okay by linearity is you know factor a pca or factor analysis yes where you can have a price as a function of these factors right okay so you have you're essentially making a model where you say this variable can be determined as maybe some linear combination of these other things exactly so they try to do that in finance called the factors okay so you have factors and then each variable is function of the factors and and therefore you compress everything with these basic factors and or whatever factor you have an awaining importance uh like in a pca and i've showed in the book uh on the fat tails they don't they may exist but they don't know what the factors are well those are essentially those would be sort of the primes of the financial system they will be the the um you know what the index funds should be attaching themselves to those that's what they do they do models models around that but but my problem is to go back to what the parameter is you see again i mean is it the average factor or is it is you see or or or you might want to stop sharing because then we then we then we'd be bigger on the screen okay so what it's worth i'm sharing sorry no no it's okay so i mean i okay i have and you're asked me a question i never thought about before because i don't think in in terms of these economic uh i mean i came to economics without knowing anything about anything you see and then later on picked up stuff so i so i went backwards so i don't ask myself question coming from stuff and then started linking say oh what's the main difference someone asked me with statistical mechanics i say you have you know you don't have energy in economics right i think that's too narrow a view of statistical mechanics i mean i think that the you know the big question you know the big sort of idea of statistical mechanics as the things that we're finding about uh you know space time and so on is you know there are simple underlying processes going on and it doesn't matter much what those individual processes are but in the aggregate they have certain behavior yeah yeah so we have a mean field problem in in economics okay which is that uh and i can explain it again here in terms of the gaussian okay what is the law of large numbers it's an aggregation yes what is central limit it's an aggregation okay now some things aggregate very well okay so you don't need to know the details because overall it's going to work out very well so it becomes sampling you know when you sample portfolio say you built the portfolio if you live in the gaussian world then there's something called portfolio theory that would work beautifully okay the problem is we don't live in that world so to get to understand the behavior of an ensemble of securities okay you cannot obtain that as easily as if you do you don't have uh so you see at the limit things become deterministic but your your your your portfolio can is not large enough for that to happen well the basic the basic claim is that the tail will always eventually wag the dog that's exactly the thing in in economics and in in a lot of these a lot of variables related to finance and uh the drivers that we have so so so to give you a very simple example uh and i have a mathematica uh page for that is i take something called the principal component analysis right and in fact and say even if a true factor analysis worked it doesn't but let's say it worked and the factors were constant didn't change over time then mutate or anything uh you would all you see the spears factors for the same reason the law of large number is slow yeah so you you would not see the real factors from your sample right so that that's the the okay so that's the first problem the second problem we have in economics is dimensionality that you know when you correlation itself is a random variable that also obeys a lot of large numbers except that when you have a high dimensionality you end up having a lot of securities and not enough data per security so to give you a very simple example let's say i have a thousand securities okay how many coordination do i have i have say a thousand uh one half of a thousand uh it's about one half thousand square and n minus one all right uh so one half thousand square you remove the diagonal and then you count okay so and now i add one security now that additional security you got to look at correlation with the with the other thousand now i add one so so every time i add a security okay i add the spuriousness because people look at the extreme correlation or the high correlations you see i mean to give a very simple example if i have a lot of securities on this planet i would find exactly a one security that correlates 100 with your cholesterol level and fluctuation uh-huh this is so what happened is so when you have a lot of securities to stabilize you must have a lot more data per security so the problem is that our spurious information grows with squares with a number of variables but the contraction to the law of large numbers goes way too slowly okay but let me let me take so one argument you're making is eventually the tail eats you eventually tails you know that's one of the problems that is one of the problems but then i'm going to make another point which is that that you know there's a lot of kind of the normal operation of economics in which you're not being eaten by tails in which people are just buying and selling lettuces or whatever else it is um is there you know you know what presumably there is some level of kind of uh you know there's there's something to describe that isn't the unpredictable undescribable tales yeah i mean then you're dealing with if you are uh if you're operating a grocery store then becomes uh grocery store management and you don't need an economist for that you need a good uh grocery store expert and it becomes a local expertise of how to handle grocery store because the income for a grocery store may not be determined by the tails because of giardia stuff like that uh maybe thin tail but not two centails actually not gaussian then maybe we can talk about it but then the minute you're talking about economic variables that that may interest anyone you're starting a corporation uh wolfram research or maz bahrami and company or whatever company you're you're doing all right the minute you're selling to more than one person on this planet okay and then local you're not confining yourself to a neighborhood then becomes out of control okay okay let's give you a very simple example sorry go ahead no no no i was i was just going to make sure that we covered a few other things because i think people um so i mean one thing one thing i've been curious about is okay and in the current economic system maybe the sort of atomic pieces of the economic system are people doing transactions with each other maybe in the future it's not people doing that it's you know bots doing it and the question is what does it look like in you know in in the current sort of so what one question seems to me maybe this isn't not a you know one non-trivial fact about economics is that uh money exists and is meaningful that is that there is a that there's a it's not self-evident that you can uh whoops um it it does not seem self-evident that there is a kind of scalar quantity that represents the value of things in other words it could be the case that whenever you want to trade two things the things would have all kinds of attributes in order for a trade to happen those things have to you know they they have to match in their fame they have to match in their you know financial whatever they have to make okay that's okay you say there's something we call the numerator and it's it is uh essential in finance and financial economics there's a numerator a unit of account uh-huh okay that you're going to have to have a home currency what we call a home currency and the home currency doesn't can be expressed in beanie in baseball cards you can have your home currency in anything okay but why is it obvious that there has to be a scalar measure of value why is it obvious that transactions can be and then you no longer have you cannot enforce the law of one price if if you don't have one unit you're valuing everything else this is where and also you cannot have arbitrage if you have one unit but let me tell you the complication that two people can be transacting each one having a different currency yep and and the strange thing is the distribution of these two would not be symmetric so to give you an example from dynamic hedging my book let's say your home currency is u.s dollar and my home currency is the british found okay to reverse things okay now the british pound goes to infinity what happens to you to the parity for one one goes to zero for one the other one goes to zero because my units of accounting british pound uses us dollars so by jensen inequality you see by johnson's inequality the other one is contacts with respect to yours so to give you a very simple idea is that let's say the the the bridge problem now is what about let's say 140 okay if the british pound goes to zero with respect to the us dollar the dollar with respect to you the response goes to infinity yeah okay so you have two different dynamics one is skewed left one skewed right and when we price options between two different people okay the same equation doesn't reverse you don't get the same price okay i i don't i don't think in terms of options so it's harder for me to okay okay let's say in terms of probability or a probability that that because you have two log normal distribution each one skewed in a different direction we can be uh using the same distribution and the probability of the british pound going going over you know five dollars for me okay is maybe 10 percent and for you or maybe 90 yeah the two country paradoxes so i don't want to uh people to drown in that notion except that for two two statements the first one you must have a numerator to be coherent and have the law of one price and two your dynamics for your numerator okay i would never be symmetric to dynamics into another numerator you see i think that this point about uh you know numerair as you as you're calling it i suspect that that i mean in you know we have some analogies to this in the physics project about kind of what it means to construct space time and so on there's a long story not to be to be told here um and you know i i think it is not as obvious that um i mean in other words you say economics as we know it with things like arbitrage wouldn't work unless there was this numeria idea but the question is in a let's say that there was an economy where everything was just done by bots and you simply told your bot i have these preferences i you know i want to achieve this and all the bot is going to do is do barter trading with other bots yes so in the end you know you're going to you want to buy a book um and uh you know you're going to buy it from somebody who in the end wants to uh i don't know provide food for their cat or something yeah and there's a chain of bots that eventually go from the you know getting the book to providing food for the cat and but not in nowhere in this whole picture was there any numera there would be an implied numerator okay if uh if for the system to be coherent okay i think this i i this is exactly what i suspect is the case very similar to physics where you have the observer traveling at different speeds and stuff like that but the system stays coherent yeah it's coherent for every observer okay and it's also coherent in transaction intro observers right well i mean so so this is this is why i think there's an analogy between what we're doing in physics yeah that's the newer error one is a is a the the the numerator is an analogy because okay i'm different yes go ahead so so i mean one of my exercises then is a feature of physics is time dilation and relativity okay so our explanation of time dilation in modern times is sort of everything that's going on in the universe is computational you can either use your computation to compute what happens next in time or you can use their computation to move in space to replace yourself in space if you're using some of your computation to move in space that's going at a at some speed then you will have less computation to use to evolve in time so time will effectively run slower for you i mean that that's a that's the intuition i don't think okay you you probably can find an analog in economics but i'm not an expert on that i have a book here that i couldn't go you know i went i think i've read laboriously it took me about 10 years to read the 22 pages on entropy and economics by nicholas uh something rude gun or something so it took me 10 years to read 21 pages i don't think yeah but i think entropy is a confusing concept see entrepreneurs yeah but i mean i'm curious even in the spatialization of economics is there is there a notion of kind of specialized economics presumably in times when that you know when the economics you know the economy was largely agricultural and so on there was a notion to you know you you dig up the carrots in this place and you're going to move them to some other place and so on there's some spatial component to economics i mean in modern times with this i haven't thought about it in these terms just simply because uh it takes me a while to uh you know it doesn't matter for markets for markets you've got fiber optics going all over the world yeah yeah i know but but the the the structure of transaction hasn't changed since the beginning of times okay the difference that we have today is that uh the the tails are more important and let me explain how how that happened okay and this has to do with connectivity which is the most important thing for economics is connectivity so to explain the dynamics and why things are getting more fat-tailed let's say that you're an opera singer in and that's the example i've used okay in naples in the 1800s okay you have a good life because nobody can transport goods from new york namely singing so so you you know so people can sing in milan and they don't no threat to you so therefore you're gonna have the income local income determined locally okay now let's say that someone invented something called the vcr or stuff like that where suddenly now you've been displaced by audiovisual and and and they didn't have planes and now people can fly and go to milan new york other places see other opera singers okay now that creates a winner take all effect or a smaller and probably the let's say perceived to be the best okay we'll take all the money and this applies to practically everything like google today taking all the money for browser worldwide or in the past no farmer could take all the money for farming worldwide all right you're very local so things are being delocalized in many respects they've been localized in literature where you have a clustering to a smaller number of books worldwide and you have stuff like that so these dynamics come from connectivity so the way i look at it that that we have had a statistical transfer a probabilistic distribution okay changing in nature but the transaction will be the same you go you sing you get your money all right but here in one case it is fat tailed in one case it's much less fat tail you see or you do transaction but i never went into uh whether they are constants and these things other than arbitrages and the very simple arbitrage is i'm not going to pay 10 for this if i can pay 791 for for it here you see right and and then you can say you can make the train not pairwise but generalize it to people doing this and then suddenly becomes arbitrage so the way i view the world is just arbitrage you see so uh and and and if you have differences in price it because in between things because they're not arbitragible right or sometimes there's too much risk in doing the arbitrage i think we should before we before we run out of time we've got to talk about cryptocurrencies uh okay great thanks um and actually i think did fred want to make a comment i noticed that um uh uh yeah it was mostly that you know transaction costs it was something that nasim was saying transaction costs are a measure of distance between uh yeah transaction difficulty or transaction cost fair enough okay anyway back to cryptocurrencies so so nasim just sent me this this piece that basically says bitcoin is worthless it was zero exactly that's called worthless if it's worth zero yes exactly right and and as i understand the argument part of what it starts from is this idea i mean you know people always used to say the value of a stock should be the discounted future value of all its dividends and so on yes do people still believe that yes because when you when you buy a stock but the the company stop compensating you in dividends but lots of tech companies have never paid dividends yeah because they put the money in instead of paying you a dividend i don't want the dividend i want the value to stay in a stock yeah okay so so with the whole idea the the the idea the way i see it is the stock of this kind of value what cash flow i'm gonna get whether i'm gonna get dividend i don't need the dividend okay i get a lump sum at the end you see so the way you look at it is at period zero i'm gonna get okay i price the stock as if the dividend i'm gonna get period one plus valuation period uh period one and how do you evaluate period one it's a dividend you get at period two plus valuation period two okay if you change those valuation using something called iterated expectations okay and adapt the stock today is gonna be the cash flow i'm gonna get it on it plus the price at infinity how long do you think you should wait i mean like other examples where people have waited a hundred years no because these things happen i mean when you look at pet.com i mean the reason uh stocks you know uh have you know are ended up having value is because you always find either some idiot to buy the company and pay up a lot okay or the company eventually makes a lot of money yeah you see so the people doubt the discount the dividend discount model not on grounds of um you know no hey nobody cares about cash flow from stock because the difference between a ponzi and that the ponzi is something where that had absolutely no value and we know it has no value okay it's a pyramid scheme and and hopefully we won't stuck with it we're going to sell it to someone even more foolish than we are it's a greater fool okay so so your stocks are priced off of some kind of expected cash flow in the future so go ahead no no so i mean your argument with respect to bitcoin is at the end of the day there's nothing there that's the basic as opposed to a company no there's one thing i said the difference is that gold for example i explained gold i have gold here gold doesn't give you cash flow but during that period okay it is a consumer item all right so i'm paying to to wear the jewelry okay so that because what happened is that if you're discounting p very far down it's worth zero right but so so the question for cryptocurrencies one of the questions is is i are they actually useful for something i mean as opposed to just being thought of as a pure repository of value or place to speculate and so on are they actually useful for anything and i mean they could be useful merely for being able to transfer money between obscure places that you can't usually transfer money they could also otherwise i mean okay so my point about bitcoin the first thing that people weren't getting tell me it's successful why is it successful is anybody using it no the price is going up so that part you see and and uh not because it's useful for transactions because if it's useful for transactions say the web the web doesn't have a market value can you buy the web if you're bullish on the web no you buy company using the web i mean you know look bitcoin is being used for some transactions i mean your iranian oil traders and things they're using okay yeah no no it is you bitcoin or other so so the the point is it's too volatile to be a currency and you should not price the currency the success of a currency is in its uses and then the other problem had two more problems gold if i leave it alone on the ground doesn't degrade doesn't require maintenance what happens with bitcoin you must apply a hazard model to it like i applied to life of a person if a person dies there's a small probability of people dying okay but but if they die they they're done so it's an absorbent barrier so if i apply an absorbent barrier to bitcoin i cannot apply that absorbent barrier to other things well you're saying gold will be forever so to speak like diamonds and that that there's no nothing financially physically it physically cannot degrade doesn't have the absorbing variation or at least not in the next 100 000 years yes but but bitcoin if people lose interest in the technology okay all your assets on it are are vaporware i mean it's just like if people if if a bank if people just decide oh they're lost interest in running the bank it's it's the same type of thing isn't it i mean it's the bank wires the money to you and this etc but with bitcoin okay it's all this value on the label just you know if there's a bank in the wild west and it had a vault in it and everybody just leaves the bank and they just say forget it it's going to turn into a ghost town you lose the money as well no because you can take the money you can say okay we're gonna open the bank and this is your five hundred dollars this is your this is yours tax buy you close but with bitcoin if they do that bitcoin will be worth zero because nobody's gonna maintain that ledger well okay but okay so first question small probability of that happening it's a tiny probability that happening all right maybe it may take 10 years 20 years if i know in the future it will happen then the value got to be this is very simple i know of no other model than discounted cash flow to price anything you see and if there is an absorbent barrier then it must have a use in between which is good problem let's talk about the use let's talk about the use right so bitcoin itself is a not particularly well-engineered cryptocurrency it's the most common it was the first okay it's not particularly well engineered can you give me one second one second one second i see leanne making lots of comments here and lyanna's as perhaps we can i'm not sure how long the scene can stay um but uh i'll put my camera on okay all right sorry yeah um no i mean so so you know bitcoin is you know not particularly well engineered it happened to be the first it's the largest cryptocurrency i mean the you know one thing i mean i know you and i talked about this several years ago the concept of computational contracts and the idea of kind of autonomous things that can happen in a purely computational domain that's an example of something for which cryptocurrencies are presumably useful that is it's um uh you know as a as something where you i mean both the ledger capability of blockchain and the kind of autonomous execution idea of blockchain and even the transaction concept of blockchain is something that is useful if the if if the number of contracts in the world increases by a factor of a thousand and most of them are purely computational contracts between machines between ais and effect then there is something then there's a utility in having uh this sort of purely computational notion of a currency i think yes okay so so but how does that utility enter the valuation well because then there is a thing for which people find i mean if if you know if bitcoin was the swift network or something if bitcoin was a bank network people would say oh we want it we want to use this bank network uh okay i mean we should disentangle the idea that bitcoin trading at 34 000 okay and what use we can have of the network built that way that can and and the fact that that cannot be imitated by other networks or broker like for example the notion of blockchain requires the thing to be public distributed and irreversible you agree yes so so uh and people say oh we're doing blockchain and you tell them is it a reversal say no we can change it so if it's not blockchain anymore is it public is it is it so well there are there are non-public versions i mean the permission blockchains which are a little bit different but in a first approximation it's public okay so what i meant is that there's nice technologies but i don't understand technology i understand markets i said uses and i'd rather wait uh given the history of technology i'd rather wait for something to be used before the the hype rather than than hyped for the use yeah and i don't think i think the things is overhyped but let me start focusing now on the one one essential thing is that i thought that bitcoin would be a currency so we're talking bitcoin now okay and but but then i realized two things i realized that gold couldn't be a currency because to have something priced fixed in the currency floating in in fiat dollars or what they call fiat it's that then you must have let's say i want to buy uh you know i i want to rent an apartment in in uh bitcoin for my rent to be in bitcoin my income gonna be in bitcoin sure so for so if my income is in bitcoin my employer got to have liabilities you know matching assets sure so bitcoin all the way down it has to be more and more all the way down but given the government owned so much of gdp and government contract it's impossible to displace the government well until a government decides to use bitcoin as their legal tender exactly but the problem is if a government of where the the thing is we're so everything's so interactive like remember my example of switzerland and and so globalized that we are we are currently the volatility between currencies is very low when you have commerce what called frictional volatility is about five to seven percent from experience this is the minimum volatile you can have okay so and and and some some sometimes it's close to zero like hong kong dollar by construction the government compresses but the five up to five percent doesn't matter it's transaction uh volatility you see but so what i meant is so bitcoin must have exactly the volatility all right of zero or close to frictional okay with respect to the us dollar and stuff like that for it to be adopted and if anything's volatility have been increasing over time well i mean volatility is measured with respect to dollars i mean in other words at some level you could say if if everybody was using bitcoin you would say oh gosh dollars are so volatile okay the numerator that is the most the least volatile the way i expressed it is i take a basket of goods and services constantly revise and see what numerator would make that bask at least non-volatile so why do people not use things like cpi as a as a as a medium i mean as you cannot buy a cell cpi you see and it's not uh it requires dynamic hedging and effectively the cpi is pretty much historically the closest thing to the cpi is is is a dollar but there's inflation with respect i mean the i know so inflation compensated by interest rates you had to net out inflation by interest rates so people over time have have settled for fiat when they're compensated with uh with interest income but so so you're saying in a perfect world the the currency would track the consumer price index let's say but that's or or after interest and this pretty much has what what the federal reserve and everybody have have done historically maybe not now okay is try to do that because when you think about it um and i keep saying that the problem of the cpi is is that if you look at the way indices are built the the the map quantity changes and price changes so if you may have a new good that enters it so for example i give the example of the thing that was the most stable in italy was a jitoni the telephoned token was you know that basket of goods they say the the different regions were was less volatile in jet tony than it was in the italian lira okay and the problem is think about it now you have it says the cost cut the cost of a phone call and then price of communication collapsed right but that's a that's a technology change in changing the goods people want now i mean you're making a statement because the currency is never going to be technologically obsolete okay so no no one one comment i'm making about tracking the cpi they are things called inflation index bonds but the problem is they will not track the cpi they will track the the expectations by the market of the cpi so for example you buy them today for a cpi of three percent per annum and then cpi turns out to be two percent okay you're going to lose a lot of money it's president for over this duration what the cpi is going to be you see so it's difference between expectation so the the the goods and services trade off of expectations what i'm saying is i spent i'm obsessed with trying to get to minimize the effect of inflation on my assets portfolio and everything and so far i think the best thing is by constructing portfolios that have some short bonds and stuff like that cocktails or portfolios i can probably get close okay but if i have to close my ass by one item in spite of all these hypes about inflation take the us dollar and let me tell you why let's say a three percent inflation a year okay that's what the last hour bitcoin chain moved you see probably yeah right so so let me let me show you it's one definitely what the the the lot less than that bitcoin moved today you see so yeah so so so so since we were speaking it moved two percent maybe so so you realize that the the the uh to have the the government has such an edge over us now in controlling prices because they dictate the currencies and they control salaries as well well in in what way i mean companies and companies do what i'm saying that when you have a large bulk employer paying you in this currency you see it determines the currency so to switch out of the us dollar into something else it's non-trivial it's much more complicated and i don't see why the bitcoin should be it but not something else but so i mean there's a practical matter one here's you know that there's the whole story of you know the iranian oil traders who can't uh sell oil for dollars so they're selling it for bitcoin instead so and things like that illegal activities so so my argument uh uh i i said if someone you know gave him criticism from my peace and economist he said you know illegal activity i said yes but it's a currency it's just there for illegal activities okay so in other words the currency for fraudsters ransomware and pariah okay cannot be a currency it needs to have a bunch of suckers around them trading their currency for it to to to to to have a value because you can't i mean if if the bitcoin is something for uh for hackers and ransomware people and stuff like that so who will take it off your hand you see so to give you fiat or something else against it well so so your argument is for a currency to work it has to be a currency for almost everything that people want now for the bulk of what people what happened is they think what what in the past you could have double currencies like bi-mentalism has prevailed i looked in history the problem is when economies become developed they become practically impossible so this is your argument sorry this is your argument about a single numeraire numerator and let me give a very simple example very simple example uh let's say that you know you could buy goods at a at a store and return it okay and some people are pricing goods and silver other pricing but then gold all right and i use gold as a newer air all right so i go on days where gold is down sure okay i i return the merchandise all right and silver so so you start arming people like when i say tesla i wanted to price its cars and and bitcoins this is great i buy a car from tesla in bitcoin and i have 30 days to return it if bitcoin collapses you say i i i return it so don't i keep it and if bitcoin rises a lot i go return and give my bitcoin back you see so you get arbitrage like hell you see so you got so you said no we're pricing it in dollars but you can pay in bitcoin so i'm saying okay you can pay i can pay swiss franc doesn't make a difference or can pay an apple stock or that so the thing cannot be denominated in bitcoin so the argument for currency not being there then you're left with other arguments that evaluation you know what it's digital goal i said well it's not digital i mean you have to settle on what you want it for you see gold didn't become digital gold like because by fiat but i say oh this is great let's have this store of value it inches its way into the habits of people progressively over centuries till it became a store of value yeah so that's the idea so the best way to view it is to look at what technology is used and go with that because 99 of technology separately 99 technologies fail yeah and and and so far in 12 years we haven't done much with this maybe there's some resistance maybe people love to have a custodian well i think the the look the the technology side of bitcoin is my impression is this you know what i had imagined would happen is that computational contracts would start becoming big and that most transactions will be between bots basically that most of the you know contracts that are being executed are between machines most of the transactions are between bots at that point it's a little weird for bots to be trading in dollars okay i i i let me let me go go back to the states so the trading probably done in in bots but the price kernel in the market invariant to who's trading what you see because if bots are not coherent they get arbitraged i understand so your basic argument i mean by the way this sort of comes back to a physics type story yes yes of you know this is a i mean this resonates with a bunch of things about the way reference frames are made in in relativity and things like this that essentially there is your notion of a numerator that is somehow uh you know flat this idea that there's no arbitrage is i think a notion of of saying we're going to define prices to somehow be flat across all these different kinds of places because if they're not flat if there's curvature you can do this kind of loop around and that's that's your arbitrage i think and i think that the um i mean i think there's a probably a somewhat deep analogy between um kind of what we see in physics and the way that we pick reference frames in physics and so on and your statement that economies work only if there's a single numerator no no not if there's a single numerator you can have multiple numerair but you cannot have volatility between enumerators or arbitrage models we call that arbitrage balance well so you mean if there are multiple currencies but they're pegged together they're sort of like the volatility between them should not be beyond uh regular transaction cost it's not enough because if i go to the grocery store and buy two spaced okay and come back and then the currency of the grocery store moved by two percent i'm not going to do the arbitrage that works i'm just i i have to say for physicists who are here this reminds me a lot of coordinate charts um and uh the correspondence between coordinate charts that was that was engaged theory to like normalize things so that globally it's sort of invariant to the local decisions yes excellent excellent uh i'm sorry because i had there was a misha you know the with the time zone i know you you probably have to go yeah i'm gonna be yelled at them in a few minutes but uh okay well that no this is very interesting and i i i can continue i can continue if you want if you want because i want to talk about uh about things that i think think are quite uh because you hear you're making me talk about things that i'm not my specialty i never thought in terms of economics but i'd like to talk in terms of uh of your uh your uh uh what you call it the the computational irreducibility yes that's a whole that that's a completely different conversation which we should have maybe we should schedule this for a different time if you're whenever i'm around i would like to talk about this and link it to the fat tales and and also to dimensionality problems yeah that would be interesting and finance and finance as well right i think um uh yeah okay so people are saying we should do it part two and i agree we should do a part two yeah part two where we're at least and now now i know because you're putting me on the spot making me talk about economics in 37 years on the market not once did i think in terms of economics that's amusing okay so we have to i think we have several actual economists here not only that but i've read books on economics it goes here goes out there absolutely zero all right do we want to let's just let just for one second i notice we have leanne here does leanne want to make a few a few comments in defense of economics yeah oh i can't defend economics because economics has so many different schools of thought that are all um arguing against each other but i i just wanted to push back a little bit to say that gold also could be considered a fetish and not have a fundamental value if we ignore the fact that there is a few things it's useful for but overall it's just some desire no no i mean gold gold to me maybe a fetish it's not a big deal but it will still i'll still pay something for a fetish but i would not pay for a fetish that may expire okay so what do you think about nfts nothing because those are we we're we're thinking about doing a whole bunch of stuff with nfts because they're fun you know we could for example we could make an nft from this conversation i i let me tell you one thing i i maybe maybe i have no idea i have no idea i mean i i don't collect i have stuff i have collectible stuff that i don't collect books but i used to collect roman heads upstairs and uh and i'll tell you one thing i don't understand the the thing but there is you can see a pattern in how much people pay to collect they use it with their a few money so when there's a lot of liquidity they use a lot of a few money into collectibles and like now now there's a lot of liquidity people are going to put nfts and stuff like that but the minute there's tightness you see bit the rise in bitcoin is a product of the injection of liquidity last march i mean people bought any assets and now of course they're bored than nft and and tomorrow they'll have sft whatever it is they're going to figure out you see so that's fine i mean this has some value maybe for if you enjoy it and you have satisfaction from it it has some value finished goods have value they're not zero there's an either like consumer item stochastic stopping time but i'm paying for it like i'm paying i would pay a cent a year for my gold chain so it has something but there are things but if i know it would disappear you see and i don't wear it that's the problem okay then that is another matter well so i mean you're i mean you know the contention about cryptocurrencies in part is they have no ultimate real world utility they are merely at an attempt to make a store of value that's one that's that's that's a necessary claim i'm not sure that claim is correct i mean i think that the whole story of computational contracts and so on uh is an argument against that claim although i have to admit that that world has not really taken off yet and maybe it won't we'll see but there's one thing that i always the one thing i've learned from my years in finance to always look for a soccer problem and a soccer problem is when people have a nice story that's coherent well tight like they did in the in in the 1990 late 1990s early 2000s with nasdaq and they've come up with a story oh the web is going to be wonderful that's thereforepet.com and now they tell you inflation money supply therefore bitcoin okay okay but i mean any fundamentals story about a stock is eventually something like that i mean you say you should buy you know company x amazon or something because uh you know they're going to take over from bricks and mortar stores or whatever or they're going to have bricks and mortar yeah yeah there's always some kind of expectation of the story for use but amazon is saying eventually they're going to bring cash some cash flow and we're going to be able to use that cash flow uh you know to accumulate stuff or will gain a value from the inside but okay so so the argument has to be that you don't find the story of why bitcoin you know the the non-government connector no no because bitcoin is zero-sum you see in an economy these things are zero-sum in the sense that it's like baseball cards because they are zero-sum whereas the the the the amazon you can say that it brings it it creates an economic activity that enhances economic activity well i could make the argument that cryptocurrencies make it simpler to do certain kinds of computational contract transactions that's fine but why buy bitcoin for that i can you can start your own crypto that does it or your own well just as you can start your own facebook i mean there's a certain network effect that's hard to overcome uh okay so yes but then i would i would go for other uh other cryptos should be worth more like ethereum yeah okay i as i said bitcoin is the first and not the best technology exactly so eventually it's like saying that there's a network effect and people should be using uh whether you remember the osborne the first portable computer yeah i had one of those yeah okay there you go they they're typically the first the first people get robust and and then uh they have an error they have everything going for them even apple almost went bust right no it is surprising that bitcoin as the first has also been the largest that is a surprising thing it is a surprise so so i'm sorry because of this uh time thing but i'd love to reschedule and and to be continued okay part two computational irreducibility and risk management and tail risk okay sounds good great great thanks thanks okay great see you next time thanks thanks bye now bye thank you part two of our discussion with uh nasim talab and i think i wanted to talk about um kind of the relationship between some of the things that nasim thinks about about risk in the world and how things happen in the world and some of the things i think about in computational irreducibility and science and so on and i guess one way that maybe one could think about this is the sort of traditional view of science has been in knowing what will happen in a sort of riskless fashion if this is the input science tells us this is what's going to happen and in a sense computational irreducibility is the story of the extent to which that is not possible that is you might have thought once you have a scientific theory of you know how the pandemic is going to develop or how you know the climate is going to change or whatever it is once you have a scientific theory you're done you can you know you can figure out everything you can base your your behavior on what's what's being um uh uh on on that sort of scientific knowledge but one of the things that's come out of science i've done is that that's just not true that science in a sense sort of eats itself from the inside because even when you know the scientific rules by which something should operate knowing what's actually going to happen is something that's kind of computationally irreducible where you can't sort of jump ahead and figure out what's going to happen by any mechanism that's that's uh much more efficient than just running each step and seeing what happens so i'm kind of curious in a you know when you think about sort of risk of things how does does does this kind of you can't know what happens as a as an internal feature of science how does that relate to kinds of thinking about about um uh about risk i mean i kind of tend to feel that that often when you talk about risk there's a there's a notion of probabilities involved and in my view of science i i like to think if science is complete there is nothing left to chance you are describing everything and this but computational irreducibility says even when you have the rules to describe everything you haven't solved the complete problem uh so so today i i posted an aphorism a tweet in which i explained that risk survival supersedes science and let me explain why risk management and science are two different professions so to speak and why one supersedes the other because there's a conditioning on you need to survive to do science you see so when people think of science they have this notion that it is a hardwired solution an answer to problems and that science is definitive see where science itself is a mechanism it's a process not an answer it's a process by which you have the closest thing we know to the truth that's pretty much the most coherent and the most and the story that has uh the least amount of holes in it for the time being you mean as a definition of science as it's a methodology science is a methodology right i mean definition of science if you go literally it means to know which is not not quite how it's done it's done and and the preparing view of science which philosophers like and now no longer like all right is that science is fundamentally incomplete and you're adding something and it must have holes in it so we know where it doesn't work and update progressively based on that so that's my understanding of science is that we know just as we know more today than we did 10 years ago or definitely i don't know uh 20 years ago and we'll know a lot more in 20 years so therefore it's not complete nothing is closed it's not settled i i would i would slightly take issue without a personal logical point of view i think that science has traditionally been along the lines of we'll make this model for how the world works our model is not complete therefore you know over time we'll learn more that will allow us to add more stuff to the model however there is one exception if we have a fundamental model for physics we can potentially have a model which just nails it it's like this is how the universe works you know there is a model and it is the universe now that's the good news the bad news is we end up with this computational irreducibility phenomenon so even when we have this this complete model we can't necessarily know what will happen but i think it isn't correct to say that science is fundamentally incomplete there is a form of science that is okay so i see so you're telling me that there exists a science that has captured everything in this field and it is settled and definitive i'm saying that there is i think there's this one case i mean that you know it's the one little footnote to the usual story of science the one footnote is except in the case of the fundamental theory of physics because that's the case where it is conceivable and we think we've actually managed to get a framework for doing it that we can actually know that uh you know we're we're sort of we're done we know the foundation now it's not relevant to everyday life it's completely irrelevant to everyday life but in terms of the the kind of conceptual epistemology of science okay so so let's assume it's an exception or that will converge to that we have conversion one domain either it's the inception or maybe the rule because we'll conversion anything to that but we don't but not yet as as you can say all right so that's that's the idea so and and but still uh i thought there'd be this caveat uh that even when you think you have a theory of everything right you should always be open to some revision because you have no idea whether that framework is the so you say the right one i mean that's the theory of miracles alone probability sorry that's the theory of miracles i mean that is is the universe governed by definite laws or are there occasionally miracles that go outside of those laws i mean i think that this is you know the level of description okay so this whole question about whether it's possible to have a theory of everything at the level of fundamental physics i think is irrelevant to everyday discussions of risk and how people lead their lives i think from the point of view of the fundamental epistemology of science it can be important but i think it's irrelevant to the sort of the everyday theories about i don't know you know trading stocks or or you know or figuring out about pandemics or anything like that so i think we can we can put it aside we we can we can discuss it it's an interesting topic so i don't know it'd be very interesting to to wonder whether it is you can state that this is complete but within the system but that's another uh you know that's another problem so i'm saying so the the to go back to this representation of science as a methodology that supposed to get you somewhere and and and we let's assume that it's incomplete and most domains with some exceptions maybe your exceptions okay that uh the problem of risk management is is that you have you don't need to understand the process okay before you know to take action because you know understanding may come too late so therefore i have the the sort of like the guiding principle of the inserto is that if i have uncertainty it's easier to make a decision okay under uncertainty than uncertainty this water for example i'm uncertain about uh let's assume that i give you a glass of water i tell you i'm concerned about the purity of the water what would you do i don't know smell the water see what it smells disgusting the the first thing you'd say no okay you say i want this other uh glass of water no it's a choice yeah okay so so the the the the idea is there's uncertainty about the water i won't drink from it okay i'll drink from something else okay uh i have uncertainty in the example i keep giving is i have uncertainty about the skills of the pilot someone tells me we're not sure about the pilot skills i get off the plane you see i take another plane or i drive or i swim or do whatever okay so so the idea that the uncertainty behind the certain is how to make decisions under uncertainty and it's actually very easy to make decision under uncertainty okay so now now comes if all doors lead to uncertainty so there's doors a b and c they're all uncertain yes then what do you do if i'm uncertain about the the the then you're randomized if you have no other option but but but it depends if it's uh to have fun i'd go for the most uncertain you see if it's to have uh to protect my life because there's i could be poisoned or or i could you know have a problem that terminates so so this is where i put a rank risk management okay i have layers okay whereas the first thing is you want to survive because yeah there are mistakes you don't recover from uh-huh so so whatever strategy you do it needs to ensure not just your survival but the survival of your species okay so you want to avoid that worst case scenario and when i ask people what is your worst case scenario if it's trained in economics the first answer is my death okay and then i answered no that's not your death they got to be a layer above you do you own pets so what's worse you die or you die plus your loved ones your pets your loved one your your uh your neighbor everybody and humanity died so they are layers that are worse than your death okay so we need to protect hence they have precautionary measures to protect important layers that don't have expiration time from disappearing okay or don't have a a reasonable expiration time like for example humanity is not supposed to have an expiration time i have an expiration time so it depends who you are right i mean you know they're people who say you know humanity is destroying the planet the planet is important to preserve i would i would okay there's a balance here because if we destroy the planet then we won't survive as well so there's here's the sometimes you have full discussions attending them so i'm trying to say that make the difference between risk management and science we've survived thanks to paranoia for uh hundreds of millions a year however you define our species okay and we didn't have science and our intention is to survive and we have the right instinct to survive and and if you look at how the cat behaves it has the right instinct to survive so i say that risk management surviving supersede science or as warren buffett uh says it in order to make money you must first survive it's not like you play russian roulette okay you you die and then later on you're gonna have a good run okay you're you're absorbed there's an absorbent barrier you want to avoid so that absorbing barrier is central for for for us and it has layers of absorbent barriers me my species humanity you know stuff like the universe for example the universe whatever it is i don't want to destroy the planet okay so because it's not supposed to have an expiration time so anyway so this is risk management and why it's more important than uh knowledge okay because our knowledge is fundamentally incomplete except in cases like yours that are either inapplicable or rare okay or both in this case uh the the you have uh you know it's incomplete so we assume that it's incomplete and we agree on that without anything uh further philosophical uh disagreement you know for philosophical uh back and forth that we agree that if it's incomplete science isn't complete i must survive and i'm not gonna wait for science to be completed before making a decision okay so so uh the the the mechanism for risk management become very different from scientific mechanism i mean okay that's science but but you know i think i think we'll let's come back to the question of the definition of science and what science really is and what science claims to be able to do i mean let me say that that in the world as the world is using science it is overusing and abusing science okay this i i i agree because i've used this argument before by saying you're doing scientism not science okay but but but to make my argument stronger i say even if we do science properly it's not making claims about these things about what so it's not making claim about completeness okay for example we don't understand uh uh everything about viruses and they're everywhere for example when the virus hits okay we know that uh but there's things we know from science okay that it's a fat tail process but we think we know things from science i mean that's one of the issues is whether or not we know what we know okay so they they there is a judge okay telling you how you trust your uh trustee and someone trusted trustee the custodian of the custodian if you if you if you wish we have that in ranking statistical distributions but we don't have that in science i mean in science knowing but science is is if you notice that there's empirical science and empirical science outside physics where the variance of results is so small as to be deemed deterministic you say we have most other what we call science like medicine is entirely statistical it's a strange kind of science okay so it is so it is statistical where you have these p-values you have these notions that depend on understanding probability distributions and and can't probably distribution and in the previous uh session for those who are not here we showed how the law of large numbers ber and the central limit theorem are the backbone of all these methodologies and why they don't hold in some domain or they don't hold that in some domain in ways that you think they hold and medicine is particularly bad offender in that regard i mean medicine is psychological economics right but i mean medicine it is implicitly assumed everything is assumed to be a gaussian and it's not true and it's a big mess okay but but in medicine there's something worse even that the the misunderstanding of the mechanism of science you know we're digressing into it but to explain the following that when you do evidence-based science you're making claims about an aggregate you're not making claims about individuals yep and a lot of people don't get that the claims made about an aggregate hold for an aggregate not for individuals so even medicine is largely gaussian actually the problem is not there with medicine the problem is p values wait a second there are several different points i mean so first of all the question is you know it's a it's a good thing to like look in wolfram alpha at the distributions of results from blood tests okay so some of them are nice and gaussian human heights are roughly gaussian distributed human weights are not they're log normal um the you know human technically isn't like normal anything that's bounded at zero would be sort of like like normal but there's a lot of lower barriers low various right okay fair enough but it's it's a it's a pretty good approximation to a gas yes but but there are plenty of you know blood test results that have nothing to do with gaussian distributions they're really very different yeah but the the the the i mean we're digressing into us but but i mean but let me make a point about that and i'm not worried about that because in medicine very often you're looking at decisions that are gaussianized and to give you an example if you would not you know to give you a very simple example the patient is going to die or not die okay we're not dealing with an unknown number of patients who may die when you look at that it becomes tail risk and this is where pandemics enter the game and pandemics are patently not gaussian it has an effect whereas in medicine if blood tests results are not gaussian okay the the if the impact will be gaussian be or will be bounded to one person therefore you re-enter a sentence distribution somehow and and that was in in a paper and actually in the black swan i said that individuals all right whatever you do for an individual or is confined to an individual can be approximated with a gaussian for decision okay but once you have collective okay then becomes a uh non-gaussian for in a medical field like you're you're uh go ahead no i mean you know one of the issues with medicine is we're all different and we're all you know and and medicine and medical tests and medical statistics are based on this idea that somehow there is it is like physics where you can do that quantum experiment and you know the electron will always be the same electron but humans are all different and that means that my point that's exactly the point i'm trying i was uh you know uh exactly my point where the problem of uh a lot of things in in iq test and a lot of nothing where people start mixing groups and individuals okay so for example if i uh want to know okay something about attributes of individuals okay uh i may be inspired by results from a collective but they may not necessarily apply to give you an idea if we start because a collective is is more abstract than individual to give you a very simple example if i take the average human then the average human must have one breast right and uh and uh and one testicle on average or maybe a little less because of uh okay so so so see so we cannot generalize and and that's problem in the discuss there's some discussion about it in the black swan it's trying to get norms it's flowing from the general to the particular rather than going from particular to the general you see but i think this this idea that okay you take there are certain situations in which taking statistical averages makes sense taking an average as in a mean for example taking the numbers 2 1 0 whatever makes sense there are others where it doesn't make sense at all even in physics there are places where that doesn't make sense and i think that that's a that's a particularly simplistic way of combining things is just saying we've got these numbers let's add them together let's take the average i mean it's um you know there are plenty of places where you know in physics for example you know that lots of things are quantized you could say well you know on average the um uh you know we've got this laser or something that's got some uh you know we could say the average energy is this but nothing is that that energy it's it's because there's there's these two different quantized levels i mean it's the same kind of thing as you you're describing for for humans i mean there's there's exactly so so we can use averages for some uh properties okay but the problem is a lot of people have the feeling that it's more scientific it's more scientific to ignore clinical uh experience and clinical results as they apply to an individual it's not because when i look at they don't even understand their own statistics the statistics only are making claims on aggregates for sure so if i treat the aggregates as one patient this is what we got to give them six uh like i had this experience when i had covet i had covered and they ran a clinical trial in the uk that's very formal and discovered that uh they had uh that you must give steroids and and six milligrams dosage okay so so i i read the thing and i started calling out doctors they said well that's a little time we know that works i say okay i weigh 220 pounds okay you have 145 uh you know uh people in the samples sample 45 okay so there's got to be some variation that's the first one and two gonna be something interesting age and stuff like that that you can increase the dosage and i realized that for example why my situation was different from the aggregate okay i was uh in lebanon on the third floor of my house with no contact with anyone everything foods count via an elevator all right so so therefore i had absolutely not the same risk class as others and the reason they lower the dosage is because of hospital viruses you see so when you start going into particulars okay you can use general results and fix them to particulars you see the the and and also i'm going to tell you about when i when i talk about racism for example racism is the same problem all right let's assume let's talk about that but let's let's finish our medicine for a second because there are interesting points to make i mean so so one question is current the current practice of medicine is all about statistics you know it's all about we've done this trial this happens that happens what's the alternative view of medicine alternative view of medicine is to have a theory but medicine is extremely allergic to theories that is you could say you know if you know you should take steroids because we have this model that shows how steroids are absorbed in the lungs and it produces this and it does that medicine has been a field unlike physics for example which has had a great time with theories medicine has had has decided that theories are doomed that is because the alternative to saying let's just follow what the statistical averages say would be to say we have a model for naseem's lungs or something and we're going to say based on that model we're going to work out that he should have two milligrams of steroids and um or you know eight milligrams of steroids or whatever it is but that's the thing that is even more you know that's the thing for whatever reason and i think it's a sort of society of of science type reason is is very people people you know people have gotten the idea that there is no theory for biology there's no theory for medicine and there can't be a theory and people say for example in biology they say and they're wrong by the way but they say there can't be a theory because everything is just the result of natural selection so in other words that the way we are is because of a bunch of historical accidents i mean i i should be curious what your point of view is i i i i the only thing i understand is how people make a mistake going from general to particular or from particular to the general and and i gave the example recently because it's very similar like for example if you want to make a decision on who to hire to run a marathon right do you say okay i'm going to interview someone who runs marathons or you're going to say okay i'm going to find me an ethiopian who's born you know from this tribe okay no i'm going to find someone who's going to run the marathon you don't take whatever physical characteristics of a group and then try to flow from it you you use different criteria okay so the mistake of evidence-based medicine is that they often make the mistake of saying okay let's bring an ethiopian to run a marathon or let's let's bring a uh swede to lift uh uh or sorry a bulgarian truth wait all right because statistically bulgarians are better at deadlifts whatever it is okay so let's go bring a bulgarian no i mean you don't have to go call build gear and consulate right you you you go to the gym so that's the idea that sometimes you use the wrong general right so practicalizing the general is a mistake that is made in medicine in your case you're saying okay we may have a central model okay and they're allergic to what in economics they call structural form versus reduced form that medicine doesn't mind reduced form but they're allergic to to uh to a more general form and that is because of the heritage of medicine historically because of the problem of the two branches of medicine that there was a technical epistemy there were the barbers who were who became surgeons and they were lower-class people and they had a lot of knowledge and then often they're called even empirics because it was not considered good and the rest was dealt with by theologians it would sit down and and and and uh there's a nice anecdote the mother louis xiv died of breast cancer not a single doctor saw her that's interesting just by theories they're cured by by you see the idea so so this is why this is why the history of medicine okay and the reason we're alive today was taken over by the barbers and the surgeons who are lower class people working with their hands unlike the bishops and the upper class philosophers who who thought that they were running the field and the field today is a compromise but effectively you if you see how how it's taught it's a pseudo uh you know story because uh the they teach they put you through medical school they make you study uh i don't know molecular biology by molecular uh chemistry about molecular biology and uh organic chemistry and uh all kind of stuff and then tell you forgot about everything now we're in a hospital and this is where we start learning yeah so so so it is still run by a print you know if you have a model apprenticeship in the model or it's like you learn carpentry or something like that i mean it's a complicated issue i mean this whole education thing and you know is it worth doctors learning calculus and you know one of my observations about medical folk is most doctors can read a graph many fewer can read histograms many fewer of even quite respectable practicing doctors know but you know should doctors learn calculus you know that's a i mean that becomes a sort of societal question of what do you want the sort of threshold of of kind of ability to learn things and so on to be to to say okay this person's going to be a doctor so i think it's a but but this idea that that you know everything is just based on kind of case law so to speak everything is based on what you've seen before and that's sort of one approach which is probably not bad and then the kind of the more scientific overlay on that is the statistical approach of saying we'll do this because evidence-based medicine says the p-value of this is such and such yes so so so let's talk about the statistical approach to medicine it's a mess because what happened is unless you have mathematica i'm not doing this to praise mathematica but i use i do monte carlos about what what you get you don't have a feel for what you're doing you see these people take like recipes this is a p-value and i wrote a paper that that i it was like accepted in a journal uh provided i simplify it i say you i'm not simplifying it because you know you know it's simple enough they couldn't get that p value is a random variable if i have an example and it has one property p-value that say the true p-value is 0.12 it means that you repeat the same experiment and you get long-term distribution around 0.12 53 of the observation will be below 0.05 okay so so it means you you can get at 0.01 by two or three by repeating two or three times the experiment okay with a different the same knowing the p-value is 0.12 so therefore they don't get that p-value is stochastic so so the idea is that my war in economics and elsewhere is with people who use a statistical concept without having figuring them out themselves if you don't haven't derived it yourself by by by getting a feel what is uh like as we did less time with a lot of large numbers you don't talk about large numbers unless you've tried it and seen the result you see so we classify people between what i call the probability driven statistician and what i call the cookbook statisticians to take a cookbook they give you ah this is a statistic we're gonna do this okay so in finance we have a horror stories with people using the gaussian all right but tell you oh it's not gaussian but then they use a variance which only works if it's gaussian calcium it's a metric that doesn't have information elsewhere or correlation that only has information it's a relationship is linear you see yeah go go ahead so i mean it applies to medicine to give you two or three examples i have a medical blog i don't know if you know i have a medical errors on statistical errors in medicine and i did that to kill time where uh they they sometimes they start someone was talking about golden ratio by using the blood pressure of individuals the ratio of blood pressure of systolic to the diastolic supposedly should uh should uh should should be one point six uh what one something that that the the the twenty over eighty or something what is one twenty or eight no it's not one twenty of radius something else that they've changed should be the golden ratio all right one point six one and uh uh but the problem is it took the average uh systolic divided by the average diastolic rather than taking the average systolic over the solid across the population right so you know you know they got problems with that elementary thing we spoke about last time a function of an average non-average of a function you see and and you can recurse i if i had to just focus on one point for the rest of my life the function i have an average of or the moments of an average is not the the the the the sorry the moments of a function are not the function of the moment i think yes the base problem is medicine wants to have the authority of science it needs to find a way to do that it goes to statistics to get that the idea that medicine is a case-based business where it's just like oh i've seen a case like that before this is what we should do that's what in practice better practitioners end up doing the alternative would be let's you know have a you know a good model of the human body and let's figure out by theory what should happen in this or that case and people people have accepted defeat on that approach and don't think it can possibly work and so instead you know they're searching for sort of scientific certainty and they think they find that in the statistics of clinical trials and things like this and i think that that's you know the problem is people believe in science and people have a you know a a largely religious at this point belief in certain aspects of science and that's been you know that is reflected for example in people's need i think to say you know the medical result is the evidence-based medicine result is because they want something definite and that's the place to get something definite you know at the risk of really destroying many more fields okay the i i i think there's a rule if you need the p-value or if you need statistical results yes because and that applies to psychology is a lot worse okay because psychology is a lot more and they have longer papers and fewer results and no surgeons and stuff and so psychology medicine um economics oh my god all right and the fields you know like financial economics subfields entrepreneurship all that so they they have whenever you need statistics to drill a point i agree okay i made this point it's not a it's not a science no now there are some cases where you could do it properly by saying okay i'm making claims about an aggregate and i can see stuff all right they are okay but but most of the population of practitioners or researchers they don't get it right and and we know from from a lot i mean and and also the problem is uh uh the the they are areas that are in fact non-gaussian so to tell you that what has the rule is nf1 it's a clinical uh consideration where you have a doctor patient is clinical you need to know medicine and if 100 it becomes a statistical problem and of humanity with pandemic it's a tail risk problem and the three are three different disciplines yeah well look and the results you get from end of a hundred something may not flow down or up it definitely don't flow up look my point of view is any time when you need to use fancy statistics like p-values to tease out a conclusion the conclusion is deeply suspect i mean the fact is people invented all that stuff from the 1930s and so on when they were doing you know you know agricultural statistics and things like this where it was hard to get a lot of data in many fields today it's easy to get tons and tons of data and you know you see in lots of things i do for example you can just see okay it's not clear what's going on just get more data and you know then you plot this graph and you can see the whole thing is clustered in one corner or another corner and you kind of you can make a definite conclusion i think you know the the issue in medicine one of the problems is that you know this idea of clustering things i mean you know it's it's deeply flawed because people are so different there are you know when you do some clinical trial you're aggregating together as your example of steroid dosing and so on indicates you're aggregating together all these things which may for theoretical reasons have utterly different results but you're just putting them together and you're saying we'll use statistics which somehow is some scientifically magical thing to tease out an answer but i have one point in defensive of one one methodology okay and and uh i don't know if you've heard about the hydrochloroquine uh stories with people classified they both trump they like hydrochloroquine stuff like that that and the beauty of having the control group okay would have a placebo not placebo it doesn't have to be placebo having a proper control group randomly selected individual you give them direct versions that you notice that hospitals you know where hydrochloroquine was successful have a lower mortality rate effectively had populations that were younger okay and your rate of death from kovid doubles every 10 years approximately beyond the age of 50. so you realize if you have a younger 10 year younger population you're going to have the death rate right so and and and you can even shoot for younger as someone i won't mention did so so therefore their methodology of double you know uh the double uh double blind or necessarily has to be double prime but the randomized control triad is that you take a population and you want it to be as close okay the population that has the the medication to be as close to the population that doesn't have it so you can see an effect uh without all these things so they are they are some tricks that they do that are have value of course it's just that the results that they get okay designed for the general you need to re-translate back from the general to the particular well that's the other yeah i mean there are many other problems with clinical trials i mean you know the the whole technology of who do you have in a clinical trial is a is a very bizarre business because you know that's there's you know there's a lot of oh you know you you you don't qualify for the clinical trial because well actually we think the drug is not going to work on you for this or that reason um and uh you know it's the the i'm sure this happens analogous things happen in you know in plenty of finance situations you know we we we won't have you in this clinical trial because you know you you don't qualify for this reason which is in fact a proxy for the clinical trial is going to fail on you i mean i i think you know the the the interesting case for clinical trials is genuinely personalized medicine how do you deal with that is there any statistical way to deal with that in other words if you say you know we're all everybody is different everybody has a different genome sequence you know it's going to depend on some unknown aspect of the of the genome sequence what happens now you could say well just i mean you know it it seems difficult to maintain this idea that everything is based on statistics if you are actually recognizing the fact that people have a immense diversity of different you know medical characteristics this i agree fully with you and it's the problem that that needs to be solved outside that fischer uh all these theories that came out of the uh bad statistical methods they were they they came from uh heuristic statistics rather than understanding the fundamental probability thing and they have their heuristic right the like if it's n of 30 then it's gaussian therefore this this this and a lot of mistakes and um i i see even further mistakes like for example correlation correlation is a metric that has no meaning all right outside linear relationships and uh i have a paper called uh fooled by correlation on you know on the web uh waiting to be fixed um and and that food by correlation papers you know suppose shows a bunch of things like for example uh a lot of paradox that people don't know okay that uh it's not transitive uh and the mistakes are made usually by psychologists because in medicine medicine is is gold compared to social science social science is a mess there's a complete mess you know one of the things you say that but one of the things i've noticed is if you look at things like statistics of people visiting websites and you look at the detailed behavior of people when they visit a website one thing that has i've been really struck by is you look at curves for you know the the time interval between people clicking this and clicking that and so on they are wonderfully smooth and quite tight curves in other words there is some you know there are some principles of human behavior which we don't happen to know but which are surprisingly predictable so in other words you might have thought psychology things like that will just be a mess because nothing is predictable i think that's not true i think we don't know how to predict it but i don't think it's true that that um that there's nothing there that there's no possibility of a kind of newtonian science of those kinds of things i think there can be we just don't know what it is maybe i have i have a a little uh uh a statement nasty statement and skin in the game where i explain two things i said anything you hear about statistics that works that is not or okay you you you can find it you should find it in erasmus who compiled the classics about 500 years ago all right so you if you don't find it an harassment it doesn't exist so once a statistician jumped on one psychologist jumped at me say you idiot cognitive dissonance all right that's a new concept it didn't exist say you know you can find it erasmus because you have portal to the classics or montana or someone of course you find it it's uh it's uh the uh the sweet the sour grapes uh yeah which way precedes the greeks the the greeks because a lot of these greeks uh you know fables existed already with the assyrians i didn't know that but like uh like i found uh a bunch of them in in uh in the syrian texts that proceeded greece where it was 800 900 years in uh and and they're not that that well known as a narrow field uh seriously it's it's an interesting fact that human nature has not changed throughout recorded history so our ancestors know so much more in that field you see they may not know physics but they know uh they know a lot about things so so i said whatever is not there okay ozar is and uh and as we know you know there's all these tricks that psychologists try to figure out about humans the other statement i said it's if it's not an erasmus explicitly or it must be known by used car salespeople all right or and and effectively you know the all these uh richard taylor theories and stuff like that were well known by advertising agencies how to manipulate people and and it's known and the third category of people who know it so it said erasmus used car people and uh magicians magicians had long before them known about all these uh optical illusions and then illusions that you can have attentive uh you know all these things that psychologists know so so basically some field have brought nothing to our knowledge of human nature if not a degradation because they give us about 55 percent of the paper don't replicate well right but you know one of the questions is you know science we were starting off talking about science and what science could do and there's a certain model for what kind of a thing science can do and there's a question when it comes to psychology for example are there things of a kind which science as we currently imagine science can do or not and is it you know is psychology kind of a thing you know could there be a newtonian type theory of psychology which we just don't happen to know what it is for example you know or to take a a a a simpler case probably as immunology you know we actually are very ignorant about how immunology works and you know there could perfectly well be kind of a newtonian-like theory of that we just don't happen to know what it is yet and there are other things where i suspect there fundamentally can't be a newtonian-like theory of those areas i mean i i think that um what type of theory i mean to go back to what are you calling you if i understand let me rephrase it so i understand it okay that's the way i understand i think newtonian theory means that you don't have to catalog or describe every apple falling from every tree yes particulars i can have a general model by which i know how apples fall and reapply it to how apples fall yes you all must fall under the same you know equations that all must follow the same way right what you call for the tournament theory okay yes and that's exactly the mistake that people are making they think they have newtonian theory when they have a evidence-based thing yes because they've taken the average apples whereas it applies to every single apple you see right right but notice an important point you know one of the things that physics has achieved is it's built these pretty big towers of theories that is you start off from some underlying set of principles and you build this whole tower of this follows from this this follows from this et cetera et cetera mathematics is probably built the tallest such towers but physics is about fairly tall towers in medicine i don't think they build towers if they did they would all fall down and what you're describing you know this function of an average average of a function and so on that's the lowest level effort to build a tower and it will collapse i mean in other words you could say you know that's a difference between a kind of science where you can build a tower and a kind of science where you have one you know fact result but you can't build on top of it and probably some of the some of the errors you're describing are attempts to build on this kind of sand-based foundation that you get from taking essentially these statistical results in medicine yeah i i would add one thing to your thing that difference between explicit knowledge right which is easy to grasp and more uh um i would say fuzzy but you know you know it but you can't phrase it very well because it's uh uh more complicated to be expressed and and but you understand sort of how it behaves um so the the newtonian physics is an explicit theory yeah sometimes you have fields where you have or called experience which is not an experience theory but a general way of identifying how apples fall and knowing which one is going to hurt itself and stuff like that so it's more of what's called technique which means what techne epistemy knowledge of the art one is is a is a not not easy to put down in in in neat form the other one is explicit so explicit versus asset or explicit versus a little more complicated well so you might say experience based versus theory based exactly so the the the the problem i had was statistician is to explain that there is something called clinical experience which doesn't generalize and it's like you're not making claims about general you're making claims about particulars and they don't have a name for it they don't think it exists so they say well either we have theory or empirical uh you know branches okay and i'm trying to explain there's a clinical one which is very robust and what safe medicine so far is a clinical approach not the empirical approach you see medicine has no theoretical approach although they claim to have one all right they have a so-called empirical approach evidence-based that works sometimes but not really all right you have to know how to fudge it and then they have a third one which is a clinical approach and and i i know from a clinical approach a good clinician would look at a patient oh my god well the patient doesn't open uh her or his mouth and they immediately take the person to the emergency room and the person having a heart attack right the person doesn't know it okay they look and and they see the sign and that's clinical experience like 50 60 years of practicing so but but if you look at the textbooks in medicine and i'm talking about from the textbook from you know the the big main ones the one taught in europe till recently the because i was interested in in in in texts written in semantic languages but by the persian uh you know of course avisenna or by maimonides right my mother is uh i don't know he wrote he wrote a medical textbook i have a text of medical aphorisms and he wrote in arabic and actually his normal name the same uh been my moon his name is ibn almighty that was his name and he wrote in arabic all right and he has and and he constantly referred to uh certain jalenos jallino's mean gallon so there's a success so my mother and you look at and it's all theory if this this happens and the humor like this and this happens like that then this must happen and then we have to apply gold right so so they're trying to make these little theoretical i mean these hard statements right so someone can read the book but in fact it doesn't work that way people learn from seeing patients well i mean developing experience what you're describing and i'm curious actually to what extent that's i haven't looked at galen in a very very long time and i had no idea that um dominated uh the gain galen actually was lost in greek uh text and it was recovered in syria it was very present in syriac has to be called in the ancient world the syriacs were the doctors all right the chaldeans were the the star colleges sorry the kaldans were the astrologers yeah and they both wrote in 70 climates derived from babylonian from semitic languages uh the and and the uh the the the i think a lot of the texts came from uh from aramaic from i mean the the syrian aramaic the syrian dialect of aramaic the syria called syriac or and uh and and that will translate into arabic some translate into arabic directly some taken up by a person like maimonides referring to them i have right upstairs uh but i can give you a sample it's so funny it's like it's hilarious well how similar is it to to you know in current you know current clinical practice there are these books that basically say you know if you see these symptoms this is the decision tree for what must be going on this is what you should do how similar are those modern ones they are similar except they didn't have what they call evidence at a time controlled experiment so just make some impression and if you do if you see this do that yes very similar well how much worse were they than the i mean how much has the has apart from drugs which are a whole different story because drugs have quite different elaborate chemistry that didn't exist back in those days mostly part of my car i mean the the drugs existed a lot they have the recipes for drugs enormous recipes for drugs yeah right and they had all these plant you know these things that said look at a plant with these kinds of leaves and use it for this uh okay so so the the way i'm gonna find similarities is that we had knowledge in a lot of domains in the ancient past some domains our knowledge wasn't great but it helped us survive okay in medicine and the the surgery was good okay because you could see the results there was very little and it was a uh in europe it was a different uh path from the other one they didn't have anesthesia which was kind of a bad thing then they didn't have anthea but they still saved lives right and the things and then they had alcohol and then they ordered they knock you out or something they had ways all right so and then the the the other uh the branch that we we we should look at that was monstrously successful and a catalog an anti-fragile how it it preceded knowledge in it procedure science or technique procedure estimate is engineering the the romans had phenomenal and we had recipes then that definitely were vastly more effective than medicine okay because it's an easier field you would say less complex in engineering and they had a self reinforcing concrete the concrete that that under stress get stronger and recipes we have lost completely and then the other thing the interesting thing just to say that that perhaps they were saved from theory okay is that uh i have a tableau of uh i call it learn teaching birth how to fly like teaching birds how to fly it means uh you know uh the the whether it's uh you know uh the field comes from academia and the practice follows because if you read the you know wikipedia entry or i don't know today's wikipedia country what it is but you see that technology is seen as something that's application of science to practical affairs where in fact i have a different you know root in mind that practice leads to technology which leads to science and and later on those who write the books are the the scientists so to take the very simple case of engineering right they were building cathedrals they were building using heuristics right right 10 people in europe at the time the buildings knew euclidean geometry and they used it as as mind puzzles sure okay so so so so the idea of you know the the of science be driving with these views so there's a field vastly more interesting but it's not statistical engineering that is entirely clinical i'll say it in clinical empirical and theoretical okay that's entirely clinical and and people forget that this must be a model for a lot of other fields i think it's interesting that you know what you say about engineering didn't get written down i mean the science the abstract science people wrote books about it and the books were passed down in engineering the sort of engineering manuals maybe of the freemasons or whoever didn't you know those those things didn't get passed down the same thing's happening with with software engineering there isn't you know the the artifacts of software engineering aren't particularly preserved relative to theoretical works on those kinds of things but i think i mean your your point about the um uh you know i think the there there are also cases where the science has preceded the technology where in order to do the technology you need a certain amount of science and i think in um you know there's certainly examples for example what's that like which example right now uh take rockets they're a good example you need to understand i have a very interesting story for rockets the jet engine yes i have a bunch of text here on jet engine i discovered one day i was talking about the black girls formula at the london school of economics and and i was telling them listen we had a vastly more sophisticated formula for 200 years and this is how we did prices and then the minute someone started using the gaussian distribution our knowledge degraded okay and uh and and so i him the story a fellow came to told me but of course you have the story of the engine you don't know it what i said yeah for a long time they were the jet engine the theory came later yeah no i mean it's sure it's like the wright brothers the wright brothers were you know what what needed to be invented there was not a you know a theory of aerodynamics it was what you might think of as engineering common sense about control surfaces and so on but i mean i think it's it's some uh you know i'm not quite sure you know one of the points about science you know what is science and what do people think science can do i mean there's a there's a um uh you know for some people science is what happened in the sort of newtonian type period of writing down formulas figuring things out from formulas and so on and we you know for example that's the thing to which medicine for example is quite allergic medicine doesn't think there are formulas i'm glad they are allergic to that for one reason because unless you do it right with no error why is it that you guys don't use no p value because when i compute p values in physics i get 10 to the minus 15. the variation in the experiment not variation in the in the process well a great example of of you know epidemiology and the success or lack thereof of epidemic predictions was an interesting case because a lot of people said we've got this scientific epidemiology model it's going to predict all these things let's make decisions based on these models and you know it turns out the models were wrong it wasn't surprising the models were wrong because you know but we we wrote a paper saying it's called on the error of making a single point estimate when you have a proper distribution you see so the the actual and the error is made by and i said the error had been made by two people by the people who wrote these models making a prediction right because it's a distribution that has so much variance you can't make a single prediction you describe what can happen and the sec and stat tailed okay and the second therefore you don't observe the average you say you observe realization of the average and the second error is by made by those who criticize them by saying oh your projections didn't play out you see so so both were wrong so we wrote a paper called on uh it was a fight we had it started with a twitter uh you know comment which the generation took paper with my colleagues we have discovered that the fattest tailed random variable on the planet is by far pandemics and you take 500 pandemics and we know they're fat tails you remove half you remove this you find fat it's very robust now that's a way to approach uh the process by saying this is scientific result that is fat tailed and the same scientific result tells you right that your methods of trying to look for the mean don't work okay because this would call the dog being wagged by the by by the by the tail okay so because it's all the information is all entailed and you don't see the tail so when when we made that statement about that we had a fight with uh you wanted this he said oh let's wait for scientific results to come before we take action on a pandemic say yeah let's wait for a car accident before we put the seat belt on this is the same kind of statement so so we uh so the paper and i think i sent you a copy of that paper because i did the graphs with mathematica all right and uh you know so it was and uh the uh and i like you know the right i'm not as good as diego here in the room with mathematica but uh but i'm uh you know one day i i got close to diego all right so with with the graphs anyway so i did the graph by showing an example of if i have a log normal distribution not even a fat tail distribution okay with a high variance like normal distribution then you can have 95 percent of observation below the mean okay so how can you make a prediction you're going to be 95 wrong all right if you get the meat right you see so and the second point which is in dynamics of things is that in dynamic process in other words where we have the feedback from people informed of decisions is that you say predictions are either self-cancelling or self-uh self-fulfilling yeah so in this case they were largely self-castling because it's like if you predict the terrorist attack it won't happen all right it's self-castling but in case people took had caution and it's self-cancelled but however i'm gonna say one thing about the the models used is that i saw you and diego and your son make these cellular automatic models that were vastly more robust so in one afternoon you guys nailed the model or trying to do these things vastly more robust than everything they had in academia so more robust i would say more revealing at least the the things particularly christopher worked on the main thing was that you could tell you couldn't tell that is hence i guess the subject of today which is uh which is uh uh the the uh the the the computational irreducibility yes well but i think in that case see the way i see the pandemic there are some sort of signs of sort of computational irreducibility and modeling but there's an awful lot of just science we don't know and you know i think that that the problem is people assume you you know some science and oops no no no no i'm sure i just have to have to pick up some pic pick up a call the urgent to one sec what's that what's up yourself yeah let's see do you have a reference for the cellular automata stuff you're talking about that you uh well i think that was christopher wrote some stuff if you look on christopher christopherwolfen.com um there is a lively conversation happening in zoom chat if yes well so let's let's see who would like to um i i feel like uh it would be great to open up this conversation who would like who has a uh a good question or comment that okay james has one all right let's let's start off with james and then we'll go to other people as we can well yeah i think it's two days ago let's let's wait for that scene to to come back unless i'm sure you know um hello again okay we're we're we're sort of opening this up to the to the um the the audience here so i think we had um um let's should we finish this thought and then then we had some comments and questions from people great i'd like to put a little just a little structure because so i so just for myself i don't drown okay that you came with the approach that a way to do there is a way formal way to do science okay that uh is similar to physics the way physics uh was done and and uh and and why it's properly done in physics and gave results you know that maybe not being right but never beautiful results somewhere and i uh was talking about the exception as well as as you did and why some fields are allergic to such approach economics is not economics has physics envy they say or the other one so could they be a different every field and as like engineering every field has its own uh uh properties yes or it could be something general that's this and and my claim is that when you do statistical things the general is very different from the particular whereas in physics in general it's not different from particulars okay well right i mean the question is repeatability and the problem in medicine is medicine is a fundamentally non-repeatable field i mean as an experimental field because all people are different you know when you take x number of milligrams of of steroids or something it will do something different when from when somebody else just because of what they ate or what exercise they took or whatever else it will be it is it is deeply non-repeatable whereas physics every electron for reasons that we think we're beginning to understand every electron is actually the same whereas humans are all different and i mean that's a that's a major sort of dividing line i would say between those those fields um is is uh you know it is it's to have something where you now now having noticed that you can then say there can't be any theory in medicine there can't be any kind of chain of consequences that you can draw about you know this chemical causes this causes this and and so what you have to do is just say well let's just do the clinical trial and see what happens um and you know i think i mean i i'm i mean the thing to me that is surprising is you know historically you know pre-copernicus i think people probably generally thought if i can't figure it out with my own common sense that isn't true whereas copernicus was sort of the dividing line where you know copernicus said look you know the earth is going around the sun even though we can't tell that the earth is going around the sun but the science shows that earth is the earth is going around the sun and then you know 400 years later 500 years later you know we built this giant tower but as soon as somebody says science shows x people say oh that must be true then and and i think that's a um and you know i think what you're saying uh is you know but the there's a you know statistics provides a veneer of science in an even worse way than some other kinds of sort of scientific predictions work i mean you know as soon as you say statistically there is this number 3.72 and you know that sounds very convincing and very scientific and you know then people base a lot of stuff on it and i think you're pointing out that basing stuff on statistical results is even more hopeless than basing stuff on on them okay no no i mean the basic stuff on kind of these these cases where you can do theory um and yeah i mean it's it's you know i think the the blind assumption that science knows what it's doing in the modern world is kind of it's it's kind of bizarre to begin with but it's particularly doomed when the science is merely a veneer of science provided by putting numbers into statistics okay i would say something uh you know i agree that that uh with you without saying one thing is that what we see is coming from statistics by people who are using cookie cutter type methods and statistics so one you have statistical errors and that has been my specialty when i was a trader that was it it's mispricing because people were using the wrong formula otherwise i had no business all right without black trolls i would have never had a business with people thanks to science okay i had a business if there was no science i would have never had a business all right because and the second one and the second statement that i want to make is uh that that there is there exists a very very very rigorous way to work with statistics okay but it it requires a little more not not relying on these metrics okay you're taking metrics and stuff like that see it requires because a metrics can be gamed and there is a way to to deal with uh probably i i call it the probabilistic approach to to problems not the statistical approach why use probability because probably it's more general and doesn't have cookie cutter formulas well you're saying that basically if you deal with the whole probability distribution and you look at what happens to the whole probability distribution you can conclude things or not just look at it the whole the whole probability of solving the concept of probability okay you know the whole method the probabilistic methods a probability distribution is a simple uh subset of the ensemble probabilities and and there are also uh uh things and and i think there's a personal room here trishank who you know argues a lot about meta problems that how can probability and then we realize probably distribution cannot tell you what what probably distribution it's coming from that was the first paper i ever wrote it's called on the problem of not observing probably distribution you don't observe it so uh and and what methodology do you need okay to and then i said okay you can start you can have a hierarchy of distributions that if you if i've observed tail of a large deviation i can rule out gaussian okay so it's it is very similar to preparing falsification i can rule out that this thing is degenerate determined means no distribution everything's moving and okay if i see something 10 sigma events i can it's much more likely that the distribution is not gaussian it's 10 to the 100 times more likely distribution than gaussian right then it being a 10 to the 10 an event of such low probability in the gaussian okay so you can rank them and and and rule out what it can be and also use some uh scientific theories to rule out the human height is fat-tailed because if human heights were fat-tailed okay you would have p most people have to have a mother so you have to have a womb that's a another human height being fat-tailed means once in a while you observe someone who's a thousand kilometers at all okay so this we can rule out on scientific grounds based on the way humans are built and the way they scale and all of that so you can rule out so you can put structure into distributions so so the idea is if you're going to use probability distributions use it right and and the the problem is they waste their time on details of things and then the other thing is do not go to to conclude this section in physics you can go from general to the particular and from particular to the general seamlessly in medicine you go from particular to the general but you cannot go back from general to the particular that easily and that's a mistake people make in in evidence-based science yes yes yes yeah one of the most shocking functions that we've added recently is this function called learn distribution which is a machine learning based function that given data like a bunch of pictures of cats and dogs will try and learn the distribution of pictures it's a very weird function and the extent to which it works and it works okay it's kind of interesting because the extent to which it works is a reflection of what are the typical distributions of things that exist in the world in other words what's that what are the distribution of distributions so to speak um and uh uh anyway i you know i i do i i'm just curious of just a general knowledge type thing about about doctors i've i've observed the following thing i'm curious whether you've observed the same thing or different things and so on which is you know about probability estimates by doctors so if you deal with a young doctor you know you have some symptoms you know there are a bunch of possible diseases young doctors tend to overestimate rare diseases old doctors tend to overestimate common diseases that's my observation at least i don't know whether and the reason i assume is because you know in medical school it's a question of a priori probabilities in medical school you're presented with all these weird cases of all these weird things that you know well you should see at least one example of somebody who has this weird disease whereas if you've been practicing medicine for 50 years most people who show up have the common diseases so to speak and so you have a tendency to kind of overestimate the the the um the probability of common diseases i don't know whether you've observed the same thing or you haven't i was a victim of that okay i was a victim of that i had i was 30 in my 30s and i had throat cancer and i wasn't smoking and and all doctors they were too young to have throat cancer and uh so uh so you you should uh stop shouting and i was a pit trader where you shout a lot so they say you have a singer's uh nodule that's you know it was they ruled it out because it was i was it's the exception but the young person did not having this experience that wasn't smoking and i had throat cancer so that's it for them but for them it's not i mean they rule out completely i mean forget about it and then it turned out to be when i then i had an operation uh with a person who removes the nodules uh the nodules of uh singers opera singers and and it turned out to be a tumor and what was the probability we did did you i mean did you look up the clinical trials i looked at it the the the the distribution of people uh younger than 60 having who smoke even if you smoke it takes a long time to build is is tiny but but i mean i mean you're an exception we're each an exception in our own way people don't get i mean that's why there's such thing as identity right see and the way i mean you recognize me in the street all right and there's seven billion people all right you can recognize and i recognize you or it might recognize matthew roman enrique mads james you see the idea so the point the the the the the statistics is is actually much simpler if you only use it on things where it works and never outside yeah the problem is people misusing it uh like like particularly in psychology i mean what they do with noise versus signal they mistake the signal for noise wrong probability distribution you see yeah it's uh right it's well let's see we should okay rather than discussing that further when we should take some comments james i think you had something to say sure well you know many of us are interested in the parallel study of economics and physics that's part of my guessing you know we're having this conversation so uh dr i think many of us would be interested in hearing maybe your your remarks or your comments on on on these theories of non non-ergodicity that uh peters and gelman have been uh have been writing about because i think it could be a nice it could be a nice uh leeway into thinking about physics and economics okay to go back to what we're talking about with uh to put it in in in stephen's frame it was talking about the framework okay uh of averages okay and uh the idea of economicity is never cross a river if it's four feet deep on average but if you remember last time i was talking about the grandmother and then so so the idea of using averages and stuff like that so to do science you got to be able to work with averages so sometimes they misuse it and the central problem is that you mistake a vertical average for time average and let me explain very simply and that's an error the psychologist made like big time if i take a hundred gamblers i send them to the casino okay and for one each for one day uh okay come back i get the average uh expected return from the casino and a lot of large numbers works beautifully tell them gamble for eight hours all right or whatever or whatever you lose your money and come back okay with your p l right so you can figure out the return you can get from a casino for a certain number of bets the the works beautifully because casinos are we built casinos because we know probability that's another one where science but the rest of the world doesn't work that way now if i sent one single uh trader okay one single person to the casino for 100 days okay have complete different picture even if there's a positive expected return so to give you the the the the example i give in skin and game is if on day 28 sorry okay let's say that i have a hundred index by one to 100 and number 28 goes bankrupt number 29 is not affected you're taking the arithmetic average so as you add zero zero doesn't impact on the arithmetic average much by one over n whereas if i take a sequence of traders going to the casino and if i on day 28 sorry sequence of single person going to the casino diet then doesn't get it all right so then then you can't because you're taking uh uh the the different it's a completely different process different mathematics and for the arithmetic average to match the the the continuous uh compounded thing you must bet in log size okay so let me give for those who are not into trading a very simple example right people come to america and talk about inequality and then they write people on equality to do things and there's a french guy who wrote a big book on inequality he doesn't seem to know much about much of anything right his name is uh piketty okay talking about inequality he don't realize that to do inequality right you're going to take every person throughout her or his life rather than take a static inequality where people say inequality is increasing there was an article in new york times inequality is increasing all right so they said look in 1980 it was this way 2 000 they're not the same people at the top so what happened is that people don't know that the more ergotic measure is to to say how many americans will spend at least a year in the top one percent and so effectively fifteen percent of americans or twelve percent how many americans will spend at least a year in the top ten percent sixty percent of americans compare that to europe that has a flatter structure okay it's very different so it's like taking a markov chain and make sure that they are no absorbing barrier no absorbing probabilities no unit one or zero probabilities in the markov chain so so that's the problem with uh with taking not looking at dynamics for uh for inequality it's exactly the same problem as risk management you see so for example when people say oh it's a fair bet and people are stupid it's a good bet 55 45. like in richer sailors [Music] i had a twitter fight with him and started by you know it's irrational to not take that bet well the problem is you got to look at if you keep taking that vet all your life unless you follow a specific policy of kelly criterion for example which has logs incidentally you're going to go bankrupt even if you have fair odds because you cannot survive you you're you're not taking arithmetic vertical average you're taking uh so you got to take a strategy that compounds a return this is one example of things that in economics that practitioners know and uh to to tell you that richard's the tailor among the his accomplishment i think his central one has been that he found a disease called mental accounting that says the following if you go to a casino and increase your betting with money want from the casino it's called house's money all right you are irrational because it's the same dollars okay you're committing the thought of mental accounting whereas in fact the only way to survive is if you treat that money you got from a casino as different money so you're more aggressive with the house's money then you are with your initial endowment for example so so so there are a lot of mistakes made in psychology particularly when psychology meets economics as things blow up so uh what do you think that's in the skin of the game i explained it at lengths and what i call the the the what is the risk-taking whatever something about the i thought it was amazing no it might be might be useful for people uh the sort of physicalized version of what you're saying has to do with time averages versus ensemble averages there you go there you go physicists know that because they have ego city theories and economists don't make the mistake in when they deal with stochastic processes because they want to make sure there's no absorbing absorption but they make the mistake in psychology psychology psychology of economics and a lot of economics feel like inequality because what concerns you is that births what chance do you have okay not taking a snapshot of society when it's dynamic for example right i mean actually i didn't know this this thing you said about inequality as a function of time that's an interesting statement i mean the the um uh you know the time average so so what is what do you think is a good measure you know you can take i don't know let's say you take the ginny index or something when you or you take one of these um which is what is the what is the correct time average version what is the correct time version of that that kind of measure two things uh i wrote a paper on the genie index by sean it's because it increases over time because if i take europe it will have a higher genie than the average countries so it is super additive okay that's one problem with a genie so we i wrote a paper on it that that people didn't notice but that's that's life okay on uh that's because there's some there's some countries you're saying that the countries when you take the aggregate countries yeah and women you take the aggregate of all the people or you take the aggregate all the people in an account yeah say the average genie in europe is the weighted average genie is uh is say 0.3 you know all of europe is going to be 0.2 by computing all of europe by taking the journeys of countries or by taking the individual people visual genies difficulty what's that the individual genies if you if you if you take the individual genies the individual genie of say two countries are equal in size yes okay the the genie of the population will be uh higher than the average genie of the two populations what is what is the formula actually for the given a probability distribution p of x what what's the what is the what is the formula for the ginny [Music] i don't i don't know but you you can get it i i i that was eight seven years ago i wrote that paper and also i showed that if i have a stochastic process all right generating a genie that if i have a thousand observation and then ten thousand observation and you know what i did then i did what i did is i ran the monte carlo on mathematical for an entire week to see if i go to uh you know if i have a trillion a sample of a trillion what would be the expected genie right keep going up with the was your the genie would keep going up with uh sorry i said that's kind of crazy but i'm just curious from a pure mathematical point of view this observation that people go up and down in the in their quantile second that's the second point the second point so you've got to take a a markov chain approach to things by saying instead of measuring the genie of the population snapshot okay and see how it moves because they're not the same people are going to be at the top one percent year after year okay what you must do is take the find a metric that takes an individual okay today and see or based on experience or someone uh 50 20 years ago 30 years ago all right and see how many times on average they spend in every state to give you a very simple idea the and this was larry summers actually although i had a a little uh run in with him over uh misuse of math in in economics he actually has a good metric he took the forbes 1980 and took the 4th 2010 or 82 or 2012 and then 30 years later he showed it's not the same people of course it's not most of them have died it's not no no the same families right okay you take italy it's very interesting you take the genie of 1540 in florence and you think today is the same the same last names wow okay so if quite quite quite interesting and frank i mean that tells you something about social mobility they have a a flatter um a flatter uh right so i'm curious and you know people talk about social mobility and their various measures of that and so on but the thing you're describing is you know there is what you're describing is an effective quantile social mobility and i'm curious how you can quantify that um and the best thing is i think someone asked me the same question i said the message heuristic is say the probability of a hot shot to exit the club right so you take 4500 as a club see how fast it is to exit it and russia admirably russia people say oh look at these uh these uh uh some very unfortunate ways to exit it in russia i think exactly yeah there's a lot of ways but but but the russians been exiting it i mean replaced by new guys all the time so that's the interesting thing in russia in the united states also some people exit the club all you need is another nasdaq collapse and and be entertaining okay or or measures by the government to to you know to cut you know the big big uh uh because of the inequality now is coming from tech firms so the the uh and you see so basically it is not so much by looking at opportunity how people rise because the zero sum the rank is zero sum by definition is how people fall enough yeah so reallocation you have and i remember an old trader telling me in 1987 or there was a crash he told me look kendo said what he said crashes they're good for society i told them why he said they do a reallocation even socialists don't know how to do it that way but crashes cause reallocation right of money redistribution yeah so i'm curious and in um uh if you look at the italian setup versus i mean can you can you see from the behavior of markets for example have there been there have been crashes in italy there have been crashes in lots of countries yeah no but they hold on to privileges uh because it's built in the society i think the uk has a dual system where you have a bunch of people who alter a grain of land bachelor thing like this and they got a the technologist and immigrants like here who uh [Music] you know become the billionaires but traditionally it was much more of a static society in uk before you know technological uh but there have been papers on mobile social mobility in europe and italy and stuff like that but nobody thought of doing a dynamic journey or rather a static journey so which country wins if you look for max man you asked by far what's number two i would say russia you know russia because they have uh i mean they may not have a lot of mobility from the bottom to the top like in your ass but they were really from the top of the to the whatever bottom you may define whether it's a jail cell a cemetery or uh just becoming poor again right what how important are undone okay is is something central then so let's see uh his hand up here yes uh hello from here as well uh i wanted to make a question about the economy in the casino for example behavior um was this the case that uh for example in the casino we have different players okay so uh one would expect that what's what breaks their codicity is that is the possibility for choice of the individual player for example if instead of looking at double edge we're seeing that we were looking at the slot machines then if 100 people played so to speak or the same person played for 100 days the same machine wouldn't expect something different to happen no no no no you would you would because you can uh okay the the the i don't know if you're setting it up to make slow bets but for the equivalent variance okay it was it's neutral to whatever uh uh this would be lumpy or not the distribution of the lumpy or sloppy or not no it's not about this it's about the for example uh the 100 results will either be given uh the same day for 100 people or if the same person played 100 times yeah the progressive would go playing slot machines sorry you can go bankrupt playing stock machine run out of money yes that's why i said for example is player playing once while in the roulette you have a choice to what you what you choose when you stop and again in the solar machine as well if you put the choice inside where will i stop it also it should be it should be the same because you play once but then you play you know it's multiple times yes this is different from my hypothesis and it's because you put only a coin in the thing but you could put a lot you know that it's sort of a variant yes yes exactly slicing the bet and smaller you're playing in fact kelly when you play slot machine because you're forced to slide every bet to be a coin no exactly yes okay yeah so so then your variance is not the same as the other one mets are the same variance you see the idea yes but you're correct effectively the slot machine forces you to not go bankrupt because you're gonna bet too slowly only one dollar and say you want a hundred you're gonna you can only put one back you can't put the whole hundred yes yes of course but my question was more towards the the implication of choice and uh the reason why airport economically breaks for example is it because in economics we consider the individual itself as fundamentally non-ergotic or because we have a system let's not use uh you know go too much interrogation but just saying that some some situation needs to be analyzed and as uh steven said time average and some other situation needs to be analyzed as vertical average okay but i know from my experience in training is that people who look at uh and then my anecdote uh uh trading as as only a vertical average okay uh go bust like for example if you play russian roulette if someone tells you 80 of doctors think russian roulette is harmless or i wish probably be correct right it's a different statement from you know you have 80 chance of making money 20 chance of dying and if you played russian roulette repeatedly okay you would not be there to enter the winning you see so and with probably one you're gonna go bust okay it doesn't take long so so that that's the idea of to worry about ruin and apply to a lot of things and and this is where i was starting to see in the beginning risk management supersedes growing supersede science in the sense that when you're uncertain you want to avoid ruined situations okay so your time average okay isn't your your uh time as a clipped by absorption well right but by the way it's worth pointing out that the whole idea of ergodicity you know physics can get away with ergodicity assumptions in a bunch of cases to do with thermal equilibrium but it is actually ergodicity is not as convincing even in physics i mean ergodicity was a thing that was introduced around 100 years ago as a nice mathematical mechanism but it isn't you know it's not a it's not a it's not as successful it's not like ergodicity is proved by physics there are certain mathematical systems in dynamical systems theory where you can prove ergodicity but it's usually very boring ergodicity it's um i mean this this idea that you can always exchange time averages for ensemble averages is actually rarely true so the fact that it's definitively not true when you have some absorbing barrier when you have you know the possibility of bankruptcy or something that's an extreme case but it's still it's it's um i mean it's an interesting extreme case more extreme than most of the cases in physics but it's still not not true in plenty of physics i'm going to give you an anecdote actually it's not an anecdote it's a sign this is a statistical thing all right in 1998 uh a fund called long-term capital management yes and a very short-term life went bust and it's really the they're the poster child of you should tell the story of long-term capital management so long-term capital started the firm and two other members got the nobel prize for the optional pricing format that didn't work okay and and i am very very familiar because i was in that business okay and uh and it was uh people who loved financial theory and and they said they they really believed that whatever financial economics and all the techniques they had work in the real world and my belief was that these guys are called considering ducks because you can make some money off of them so and of course in 1998 there was a blow up and we counted something like 52 phds in finance or right who are involved and blow up okay so we counted how many financial people was phd so there are two kind of traders traders who blow up because they ignore ruin they ignore when they give you probably distribution they ignore ruin or they don't realize it can be ruined and when you ruin you don't come back okay and and it's very strange out of the we counted how many we we call it we call people the short vowel we call these people all right how many people were short tales out of the 53 financial economists or phds in economics or finance who went to wall street it went because it was not only the ltcm that blew up so many other firms blew up they were they were the same kind of people it's the same ecology they're emitting like a crypto firm blows up you're gonna have four or five blowing up because they do have the same strategy okay so one out of 53 was not short volatility their risk because they came in and said oh risk is to be sold let's sell the tail and the whole oh this is the lottery tickets they're overpriced someone read the book on lottery tickets oh it's overpriced so let's sell these are the same they're not the same as lottery tickets okay so because you have you know unbounded stuff a lot of people are on a trade that's some sort of soccer game so it is telling as a description of what happened in that science i think we did the back i did i mentioned one of the books those numbers i did back to the envelope i think by their head counted 44 by then okay 44 because we followed them this guy this guy where's this guy this guy from and usually ivy league harvard uh [Music] mit harvard yale uh and they all blew up and and the same thing repeated itself 2007 2008. so it's not a great advertisement for economics phds it's not for for financial economics or it's also going to markets that's not a very good very good description is that these guys the people who are caught or those guys okay because the first thing they do is they go sell the tail and of course they they can't figure out don't you don't cross the river if it's on average four feet deep they only look at the average so that mistake of er go to the city our end mistake of fat tails was combined in that population but the same people caused fannie mae to blow up because that's again how again they don't understand that that if you hit a patch you had a patch your intuition i mean i i'm curious about you know you think the sort of the absorbing barrier of if you keep going too long eventually you will i mean so how do i mean yeah what is your i mean you've managed to keep doing this trading stuff for a long time yeah i've been i've been option trader i started 37 years ago and i'm going to tell you one thing i saw a population of people disappearing and they disappear from the book you don't know what happened say they don't teach others in my days it was like when i talked about why i want to protect medicine's current status as know-how rather than know what you know take neighbors epistemic is because my day when i started training there are two kind of traders there's the old traders who didn't like formulas they priced an option organically you know with the whims and then the relationship between items and and stuff like that and and then there was a the scientific uh crowd they formed us so what happened is that because of there's something called mba that came about so people started getting classes in mba and learning finance from professors so instead of having a practitioner teacher practitioner teacher practitioner teacher practitioner you had the old days to be not an option trader or to be a trader you go work for a trader you clear for a trader you pick her or his brain and then you become a trader so you've learned how all these tricks now you have you dis disrupt it by having the chain of knowledge goes from professor writing papers to you know professor writing paper professor with students getting in between without any feedback from reality and that that chain okay you don't want to protect medicine from getting that because still today doctors are learning from doctors you see so you wanna it works maybe in in the absence of a general theory it works in finance right things are worse i mean i wrote the black swan right before the crisis of 2008 explaining that these guys don't know how to price tail risk right today exposure to terex is bigger than it was 2008. systems still don't handle this still use something called the value at risk and they still use all the crap that was there still being used why because you don't have learning you don't have a skill in the game so yeah so if you look at the hedge funds that exist i don't know how many 1500 or so hedge funds whatever the number is i don't know that's the right number the you know when they're how many of them i mean you're talking about ones who i don't know hedge funds hedge funds are okay because hedge funds have uh skill in the game you see it's financial institutions that don't ask in the game but you mean they the the fact that they have skin in the game causes them to take a different approach complications okay so it's both ways but i say i feel safer today that risk was transferred to hedge funds you see because the guys that fannie mae will never learn yeah they're now by the taxpayer they'll never learn the guy that jp morgan will never learn the guys that you know knowing that can be mailed out by the taxpayer whether they were or not so so the big financial institutions don't have the same rigor as hedge funds and and and we were saved and hedge funds didn't come naturally it came because of the volcker rule thanks to uh the probably someone who's saved this country twice you know paul volcker right and that volcker rule is a beautiful thing because it prevented banks from trading so the money went to hedge fund and about every year about two three thousand hedge funds failed and not one of them makes a newspaper okay so your point is it's a natural selection topic yeah exactly natural selection and also because owners of hedge fund have to put a large chunk of their net worth in a hedge fund someone may tell me ltcm they have their money in the fund okay but i would say that it's necessary but not sufficient fair enough okay and necessary because once you're wiped out you wipe out you see it's a different type of wiping out let me make a give you the representation i give to simplify the the the point um in in in skin in the game okay uh restaurants uh have skin in the game in a sense that it's your credit card that counts okay but there are prizes so whatever system but there is a peer review system for restaurants where they have awards and and says a peer review system and journalists and stuff like that so there are two mechanisms and a friend a former trader who decided to lose his money slowly in a in a restaurant business reported that he said you go you know you have all these prices and they don't make it to the gala dinner you see they don't make it to the gala dinner just to tell you the mechanism of peer review is not as good a mechanism as survival you know organic survival and the the plumber is not paid by a committee of plumbers observing you know that made by by themselves so this is these arguments for capitalism so to speak i mean there's a there's a i mean as opposed to kind of the the elite decides who's a good restaurant who isn't it's kind of amazing besides yeah it's it's an argument for uh uh capitalism you know smart form of capitalism but also we we it's an argument against uh academia because basically it's a peer-review mechanism and we're not sure that that peers are uh you know good without some kind of either adult supervision or market uh sure no no that's uh we i think we probably both i suspect agree that the sort of the peer review system of academia is a is a a hopeless kind of hopeless but i played it to be able to say hopeless right i had to write 75 scholarly papers okay i started five years ago i wrote 75 paper publish them in whatever journal you want i mean i published i picked no but i say okay in medicine i'd rather have the paper peer reviewed it's necessary but it's not sufficient right i treat it that way because that way you know someone checked something all right as just like like there was a checking of that stuff by some specialist that's the way i view it no more where they think it is sufficient right but that's again it's it's a belief in the kind of the the perfection of science so to speak people believe there is this thing called science that operates in certain ways that gives you know 3.72 as a result it's peer-reviewed therefore that's the way the world is and we can predict based on that and this is you know it's kind of crazy in my view i mean in um uh yeah interesting well let's see we had some other let's see i think raphael had his hand up do is raphael still yeah yeah i had a quick question about the last conversation about the law of one price and sort of these there was various interpretations in terms of curvature and gauge symmetry one thing i was trying to figure out is in econ in economics when you say the law of one price is that a syntactic thing and what i mean by that is just it's just another way of accounting for what is actually a definitive value whereas in physics right if you have a gauge symmetry it's almost like the formula can't detect the difference but in reality there could be a difference it's just at the level of say like the schrodinger equation you know the phase doesn't actually change the observable result but in the law of one price is it that it's actually like one sort of estimate no no no okay the law yeah it's not a law okay whatever economy is called law the the oakland's law this laws they're not laws law of diminishing return they're not laws but they they're interesting and you use them as a vague guideline all right so uh but but let me when i talk about the law one price okay if the price of tesla is different in arkansas than it is uh in california and if it's okay but it's only a thousand dollars nobody nobody cares but if it's an order one order of magnitude different then then only idiots would buy it in arkansas the rest would you get the other you go drive to california pick it up and have a good day so this is what i mean by love one price it's quite central in seeing uh how things should be in the world but it requires okay uh market uh some kind of market structure okay no transaction costs and and or no barriers to commerce and stuff like that that may exist you may be forced to buy your car in in in brazil if you live in brazil right you can't really import cars easily so therefore it doesn't hold you see so you got to realize what things hold so this is why i don't like the notion of law called law as much by saying by using a uh gotta be some other word because they they tried to imitate physicists and they and they thought they were doing very well you see so they they they use the vocabulary the methods and everything uh you know people thought it was a law it's not a law so for me it's arbitrage when i think about arbitrage and i did all form of arbitrage and it's always humbling to do arbitrage because you think that in arbitrage that that two items are very similar cannot diverse too much in price you think that can happen and no you have all kind of crazy things happening and because of very good decision you may go bankrupt on a good trade and i've seen someone go bankrupt on on excellent trade like you can convert to put into a call all right where you you you you can convert it it's called convert whatever and and the the but the problem is uh put uh a put plus underlying is called a call minus is equal to a call minus short underlying okay and the problem is he converted it so he had a there was a rally and you're losing money on the underlying that you have to pay cash for and the call is a book entry you know that's making money but you he couldn't cash it out okay and uh so so for so far so the person was insulted because it has the right trade and this happens at times of tight liquidity so so whenever you think in terms of arbitrage you gotta look at exceptions of where it doesn't work like this law of one price so there's not a law it could be a tendency for things to go the same in the same direction and it applies beautifully to currencies like when currencies are in the same economic zone you don't have a lot of diversions in price but you still have enough to just to for someone to make a living arbitraging the two what do you mean arbitraging between different you know cycles of currencies for example or for example let's take a very simple uh the the i i talk about turkey all right i mean someone here from lebanon they were buying their medication from france not from turkey you can get the same thing at the fifth of the price in turkey all right so uh so the passive arbitrage is instead of mine from france you buy from turkey and it's a lot cheaper active arbitrage as you go buy it in turkey package it you know uh as you know in a way to to become french because there are techniques and then sell it as french and the italians do that all the time so long as something is made in italy some proportion is made in italy so they make the same in china and and they put them in italy label on it and for a while you know they're arbitraging the difference between labor between italy and china for a given quality of work and because it's the same quality actually okay so this is what i call arbitrage and you have convergence as you have more globalism globalization globalism globalization you have you cannot have too much divergence in prices so is price something that's like i guess it was more of a epistemological question it was more like is price something that like is intrinsic to the item or is it something that's like controversially like market the size but the value a lot of people say bitcoin for me is valued at zero but the price is 34. and a lot of people don't get it say well sell it to me for zero i paid a thousand for it i said no you idiot if i want to show it i said it's 34. you see but i value it at so you have new valuation and you have the price there are two different items okay they're two different items and but if you have a good valuation in the long run prices should converge to it right like for a long time i thought that these cdos were worth zero all right not a hundred okay and and of course they were going for a hundred and i was wrong and then they end up being worth zero all right so that's not yeah so they have valuation you have price some options i see now trading for 10 cents are up to me worth two dollars okay that's valuation and that you don't have in physics okay which part do you not have in physics with price and valuation so so each field must have its own rules you see of what we call science not science truly and and economics uh was completely destroyed by trying to imitate physics sure no no this is look it's what i find interesting you know listening to you talk about puts and calls and this and that and the other it's a you know it's a somewhat different framework for thinking about things than one is used to from a field like physics it's a you know it's a different you know many fields have different ways of thinking sometimes those ways of thinking produce useful results sometimes it's kind of hopeless sometimes they produce useful results you know in their own framework but nobody else cares about it but let's see i think we had a couple more questions and then probably we should wrap up soon but but yeah i have i have a uh i have to be in a restaurant at 7 00 p.m okay all right okay quick quick come so assad and then roman and then we should wrap up yes thank you yeah i was really interested and um you said the easiest decision you can make is when you have uncertainty to say no um and i'm interested in seeing your opinion on something like where you can't say no like for example talking about climate change and the release of sea yeah no no climate change we the the for ten years and and and then we ended up writing a paper me a statement me amir and and the friends of the enemy here and uh and we got heat from both sides and my point is we don't the more the less we understand the world the less risk we should take with things that are no dumping in large quantities in the atmosphere plus there's a notion of non-linearity like if i jump 10 meters as i'm harmed more than uh uh ten times that if i jump one meter so if you know there's a non-linearity in those response okay there's always some kind of s-curve and can we call that so whatever it is i'm saying we don't understand we don't these models climate models right the more uncertain we are about these climate models the less we should pollute okay or spread across pollutants so we got heat from everyone all right say oh your 10 our models are wrong right and then the other guy's saying oh you want us to uh you know you're you go with the world economic forum so so on both sides we got heat you see i mean they are because it's an easy decision with the climate is a decision don't i go with the paranoid what do you think of these like when they say well in 50 years temperature is going to increase three degrees all these statements are based on a mean of 20 models all these all these statements i take the variance between models as a better indication of what not to of what to do you see it's very simple like warren buffett says no a thousand times for every time he says yes all right he said i don't have to invest there all right i don't have there are other things to do all right so you don't have to use a fossil fuel use there's other things to do okay spread okay you know the the the the i don't know and people say i say i have uncertainty about whether it's good or not for the climate all right but i don't want to take that risk because there's uncertainty the moral uncertainty and we actually modeled it so this is an interesting thing about probability is you can use probability models because there's one advantage even in france probably adds up to one you see so so you know that you have a structure of a probabilistic model you can make decision or understand have some insights about things thank you okay roman lost all right so with basically there's the rise of a lot of models recently which allow people to basically predict their investments in some way is through basically computer tools that let them just make it a lot easier to see the market and that sort of thing and even some that are starting to forecast with those do you think in the future is that going to be a positive change because it it's basically getting more people to act rationally or a negative change because it's making people not use common sense i could see it discussed undecidability and stuff like that but there's a problem when you have recursion where i know that you know and that you know that i know how to model other people then the market changes and stuff and the only successful use of automated models i've seen is in doing short term uh brokerage when i was a pit trader how do you make money at betrayal you mean by being stupid all right and buying on the bid selling on the offer and going home flat that's how the rule is right all right sorry i don't know what those terms mean what are those terms okay buying on the bid it's like i'm a car dealer i buy for ten thousand i sell for twelve right and i have it's worth eleven thousand in my mind i have that edge all right so that's what a market maker does right so of course it's you're going to be wrong about valuation but it washes out if you buy and sell a lot so firms like renaissance they do that with an industrial thing and instead of two dimension two they do the end dimension so they spot things and they keep doing buying and selling all the time hundred thousand times a day sometimes so i they were my clients and when i was still the bank market maker and they would come in and they want 96 million of yen aussie currency right you give them a quote and then they come back they want the equivalent of in euro of swiss so i see that they're doing pairs you see they're doings they're buying here selling here so in other words the law of one price they're trying to arbitrage correct you can never actually have a law of one price it's a law of generally close-ish prices unless something happens what's the framework of how things should trade and there's divergence of one so they buy it okay so but a market maker provides liquidity they provide systemic liquidity market maker stands up and tells you i buy the share for ten thousand and sell for twelve thousand right then you sell them a lot now i buy for nine thousand sell for eleven thousand so market makers tend to make money uh um you know in in that way all right and sometimes the market moves you either caught short or long so you have a bad month but the rest of the time you're okay that's pretty much where this is why people used to pay 15 million dollars at the time to become market maker on the american stock exchange to become so you pay 15 million dollars to get that edge what's called order flow all right so so what i've seen people successfully do is transform that approach with order flow to make it to make it electronic and that's renaissance that's the job of ransoms okay that's most of what they did and other firms like that they're not they have a mod they don't have a huge model of the world and stuff they have some okay they may overlap with some view here and there but it washes out under the the frequency of transactions yeah so if you're wrong and your price shouldn't be 11 but 10 and a half all right or 10 you still have enough of an edge it doesn't matter much so this is what i did as an option market maker i was training options i had the price you know valuation and i ended up buying and selling mine instead of buying and selling and you inventory you take the risk of inventory so you lose sometimes you make some time and because you lose sometimes you make a spread wide so that feeds you so you can say the edge is somewhere halfway between ten thousand and twelve thousand that's bid and ask so car dealers make money that way you see they buy on a that you only ask all right and uh so so you can but i've never seen people have uh electronic systems uh uh okay so i'm being i've been called uh you know you better you better disappear no i got it i got it i got it so we'll wrap up so thank you very much for this wonderful conversation uh yeah thank you great conversation thank you um yes and and and hopefully you know i'll pick your brain next time hopefully some someday on on computational irresistibility because we're using it in the precautionary principle all right i want to hear about that okay another time thank you thank you very much and have a good day thank you thank you

Channel: Wolfram

Views: 147,820

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Id: _8j1XZ0N_wE

Length: 211min 3sec (12663 seconds)

Published: Fri Jul 30 2021

Reddit Comments

[u/OkChildhood2261]

I wanna hear about those fat tails yo

[u/Useful44723]

Thanks for posting. This could get spicy. Taleb and Wolfram are 2 scientists very "passionate" about being right :)