Speaker 1: Hello, and welcome to another episode of The Odd Lots podcast.
Speaker 1: I'm Joe Wisenthal and I'm Tracy Alloway. Tracy, welcome back.
Speaker 1: You've been on vacation. It's so exciting to be recording
Speaker 1: an episode with you again. It wasn't I missed you
Speaker 1: for real. I missed you for real. Oh, thank you.
Speaker 1: I actually I think this might be the first time
Speaker 1: in my life that I've been happy to come back
Speaker 1: from vacation. Honestly, a lot happened while I was away.
Speaker 1: It was beautiful, by the way. I went to the
Speaker 1: Seychelles for two weeks. It's not I'm not a huge
Speaker 1: beach vacation person, so it wasn't a place that I
Speaker 1: would normally go to, but it was absolutely gorgeous. Highly
Speaker 1: recommend it. I think it's ruined me for all other
Speaker 1: beaches in the future. But I am happy to be
Speaker 1: back and recording with you once again. And I missed
Speaker 1: you too, Joy, thank you. It's great to have you
Speaker 1: back and you sound great. You know what I did
Speaker 1: this week? I can take a guest, but go ahead.
Speaker 1: I did a deadlift. I did I've been I've been.
Speaker 1: I've been lifting weights at the gym and I did.
Speaker 1: I'm not gonna say what I was about to say,
Speaker 1: Dare I asked, I'm not going I'm still very weak.
Speaker 1: I'm not going to say what my pr is, my
Speaker 1: personal record is. But it was very satisfying. I felt
Speaker 1: good and now I'm like gonna keep doing I've been
Speaker 1: doing weights for a little while. But Joe, is it?
Speaker 1: Is it a real deadlift if you're not bragging about
Speaker 1: it on Twitter? When I'm when I hit bragging level,
Speaker 1: I will definitely brag. But uh, I bet everyone can
Speaker 1: figure out where I am going with that, because we're
Speaker 1: going to be speaking today with one of the foremost
Speaker 1: When I think of our this guest, I think of
Speaker 1: as many things, but I think of him as one
Speaker 1: of the foremost deadlift advocates in public. I of course
Speaker 1: know exactly who you're talking about. Um, this is somewhat
Speaker 1: and you know, certainly a personality and a character, especially
Speaker 1: online on Twitter. I think we've both at various times
Speaker 1: been blocked by him. Have quite a few people. Yeah,
Speaker 1: so I think I tweeted this while I was on vacation, actually,
Speaker 1: But one of the craziest things to me about twenty
Speaker 1: twenty three is that I find myself not only unblocked
Speaker 1: by this guest, but also nodding my head yes, sperously
Speaker 1: in agreement with him on a variety of topics. Twenty
Speaker 1: twenty three is a very weird year for that very reason,
Speaker 1: because it's like, oh yeah, totally right. Anyway, we just
Speaker 1: gotta get right into it. So we are, of course
Speaker 1: speaking with the one and only Nessim Nicholas Teleb. He's
Speaker 1: a professor at NYU. He is an advisor at the
Speaker 1: Terrorist Fund Universa. He is the author of several books,
Speaker 1: including The Black Swan and Anti Fragile and Fooled by Randomness.
Speaker 1: And he is a deadlift advocate. And he has also
Speaker 1: gotten into cycling lately, which is interesting. And he is
Speaker 1: a flaneur. I don't even know where to start. This
Speaker 1: seems thank you so much for joining us. Every time
Speaker 1: I see the word flaneur, I forget what it means.
Speaker 1: What does it mean? Yeah? I have to remember exactly
Speaker 1: what it means, because the original designation is for someone
Speaker 1: who walks around aimlessly, and I tried to journalize it
Speaker 1: to someone who loves things aimlessly just for the fun
Speaker 1: of it, without the prescribed plan. And if you find
Speaker 1: something interesting, then you go with it. So it's funny
Speaker 1: because I started off by saying that you I could
Speaker 1: think of you as a deadlift advocate. But this year
Speaker 1: you're getting into road biking, which is interesting because you know,
Speaker 1: this kind of very different type of exercise. It's not
Speaker 1: the type of exercise I associate you with. It's a
Speaker 1: little a cyclist. Why what's the deal with getting into cycling?
Speaker 1: I was a cyclist. We met last which is about
Speaker 1: fifteen years ago, and I had a near miss with
Speaker 1: the truck. And then I switched to a combination a
Speaker 1: lot of walking and some intense but short episodes of
Speaker 1: weight listing by weight lifting, and then I, you know,
Speaker 1: I had to follow the evidence, started reading the literature,
Speaker 1: and I realized that weight listing is not good for
Speaker 1: your heart. So it's actually it's not good at all
Speaker 1: on its own, but it's it's needed, it's necessary, but
Speaker 1: you know, let's see evidence. It causes out stiffness a
Speaker 1: lot of things. You know, there's an adaptation. What you
Speaker 1: want to lift very heavy objects. Your body adapts by
Speaker 1: doing things that are not helpful full lock term survivals.
Speaker 1: You need to compensate, and how do you compensate instead
Speaker 1: of just walking something a little more intense than walking,
Speaker 1: but not very intense. So here you have a vart veil,
Speaker 1: a lot of a lot of Arabic exercise low grade,
Speaker 1: and the occasional full body weight list. So just a
Speaker 1: variation on what I was doing. But you've got to
Speaker 1: follow the otherness. I mean, the literature is stark that
Speaker 1: wait listening is not follow your heart, but that because
Speaker 1: it causes some adaptation by your heart that I'm not
Speaker 1: very good, causes lock term heart failure. And if you
Speaker 1: that by doing overcompensate by doing Arabic exercise, which is
Speaker 1: more naturalistic than you got both. I think flexibility is
Speaker 1: also a sort of underrated component of that as well.
Speaker 1: But so I'm trying to think how to take it
Speaker 1: from here, and I'm very I'm going to try to
Speaker 1: avoid doing a lot of media navel gazing in this interview.
Speaker 1: But there is one question that I have to ask,
Speaker 1: just because I think it feeds in to a wider
Speaker 1: point about your online presence. But why did you block
Speaker 1: me and Joe and why have we been unblocked? I
Speaker 1: think a largely a lot of my blocking is not
Speaker 1: done by me directly, by some automated boss. You had
Speaker 1: to understand that I got besieved by finance people, and
Speaker 1: you know that time don't get wrong with the general
Speaker 1: finance ground and by the crypto people, particularly after I
Speaker 1: took positions that are not very favorable to the crypto people.
Speaker 1: So you do block and cleanse up my sheet. Just
Speaker 1: block things. And I had someone who happened to be
Speaker 1: in the Ukraine at the time helping me. You know,
Speaker 1: do automatic blocking. I believe, believe it or not the
Speaker 1: best thing to do with your Twitter feed. Just block
Speaker 1: groups because then then things become clean. Oh, I believe
Speaker 1: it for sure. So so unfortunately that you guys, But
Speaker 1: then I blocked people when I realized went too far.
Speaker 1: Thank you. So the first reaction is called gianni gativa.
Speaker 1: It's like you close the door and then you let
Speaker 1: in those you think that we're excluded or will not
Speaker 1: degrade defeat. That's a great answer. Doesn't have anything to
Speaker 1: do with disagreements. It has to do with the style, right.
Speaker 1: But I think the people that that annoy the most
Speaker 1: of those are lippicks because of diversity conversation and lippicklers
Speaker 1: are I meantrolls. You can see the trollstickers people don't
Speaker 1: notice the liptickage. Well, since you mentioned it already, let's
Speaker 1: just start with the crypto thing, because what's interesting to
Speaker 1: me about your disagreements with crypti people, bitcoin maximalists, etc.
Speaker 1: Is many of them, i think, looked up to you
Speaker 1: and they read antifragil and that right, and they read
Speaker 1: anti fragile, and they read fulled by randomness, and they
Speaker 1: read the black Swan, and that informed them that it's like, okay,
Speaker 1: we need to adapt, get it, get into this currency
Speaker 1: that's very hard, that is anti fragile, Bitcoin the ultimate
Speaker 1: anti fragile currency. And so to their mind, they were
Speaker 1: many of them looked read your work and this is
Speaker 1: what they took away. And so what did they get wrong? Okay,
Speaker 1: So the first thing is that my work is first
Speaker 1: about avoiding tailor risk. Basically, if we want to do well,
Speaker 1: we must first survive. And it's not like a separable condition.
Speaker 1: So one is going to avoid fragilities. And it turns
Speaker 1: out that as much as a federal reserve induces for
Speaker 1: agility in a system, and as mush as I dislike Bernachy,
Speaker 1: it turns out that bitcoin is a lot worse. It
Speaker 1: is itself a very fragile commodity, and it got of
Speaker 1: course cartaeiled, you know, Russia people, it's a very small
Speaker 1: level of people start controlling it, and it's fragile in
Speaker 1: a sense that if one day, if the you know,
Speaker 1: all the miners go to the beach for one day,
Speaker 1: for an hour, it's god. Whereas if you have gold,
Speaker 1: I have a necklace here. The gold necklace, if I
Speaker 1: leave it on the gaund for one hundred thousand years,
Speaker 1: will still be gold. It may its financial value, but
Speaker 1: its physical quality will will not be altered. Whereas bitcoin
Speaker 1: it's just a book entry that needs to be maintained
Speaker 1: and would collapse. But a lot of other things promised
Speaker 1: about bitcoin that are not delivered, like it was meant
Speaker 1: to be a transactional thing, don't out to be a
Speaker 1: speculative item. So I realized quickly that I made a
Speaker 1: mistake with bitcoint like I made a mistake by avoiding
Speaker 1: a Roman exercise, and of course I was I was
Speaker 1: at some point an owner of bitcoin. I publicly said
Speaker 1: that I made a mistake, and I went short bitcoin later,
Speaker 1: but it was not good for the system, and I
Speaker 1: tlied that the paper that was published from quantity to finance,
Speaker 1: where you look at hey, what's the currency, what's the
Speaker 1: inflation hedge? What is a refuge investment? And Bitcoin satisfied
Speaker 1: none of these. So people, of course they get angry
Speaker 1: because because they had a feeling that they're going to
Speaker 1: believe you for shading your mind. They don't realize that
Speaker 1: I'm not selling that, you know, a recipe, I'm selling process.
Speaker 1: Certo is the way of thinking, way approaching things, and
Speaker 1: if you realize that something is fragile, immediately do something
Speaker 1: about it. So and remarkably, it's the same fluster of
Speaker 1: people who read anti fragile and thought that, hey, you know,
Speaker 1: what doesn't kill you makes you stronger. That's that's get
Speaker 1: affected with the vaccine was that was covid, and let's
Speaker 1: ignore covid. We're going to make a stronger it's going
Speaker 1: to kill a few people. So that kind of eugionism
Speaker 1: and that kind of stuff I realized was an imficult
Speaker 1: to me, profoundly indamicul to me. So such the same
Speaker 1: crowd that was denying COVID saying, hey, you know, it's
Speaker 1: just a virus, it's going to make you stronger, didn't
Speaker 1: realize that they explained an antifragile jumping one foot will
Speaker 1: make your bones stronger, but a thousand feet will not
Speaker 1: help you too much. I mean it may help you know,
Speaker 1: the caretaker and people who organize funeral, but not not
Speaker 1: you that so, so I realized very quickly there's a
Speaker 1: cluster of people who were most into Bitcoin is a
Speaker 1: very point, very naive reasoning, extremely naive reasoning thinking, hey,
Speaker 1: you know, it's an inflation hedge. As we saw it
Speaker 1: was a reverse inflation hedge. But the good thing that
Speaker 1: I figured out quickly to pull out in time, in
Speaker 1: sense that it lost its value and we realized there
Speaker 1: was inflation in the same group of people who were
Speaker 1: into conspiracies, all generals conspiracies. And that's not the crowd
Speaker 1: I want that. That's not the crowd I want to
Speaker 1: be associated. You mentioned that bitcoin was bad for the system,
Speaker 1: and I think that's sort of the connective tissue that
Speaker 1: leads into some more recent events with the banking system.
Speaker 1: But can you talk a little bit more about that,
Speaker 1: like how do you see bitcoin? Actually, yeah, okay, let's
Speaker 1: look at why why we have bitcoin and why we
Speaker 1: are talking about the point. Effectively, it's the incompetence of
Speaker 1: I want to call Bernancism, you know, because sometimes you
Speaker 1: got to put name to a tendency. That the federal
Speaker 1: reserved job is not to do structural things. That fellow
Speaker 1: reserved job is to engage in monetary policy and typically
Speaker 1: the short term monitoring policies to and their mission was
Speaker 1: an asthment and will be the stability of the United
Speaker 1: States first. So their job is too ease. When when
Speaker 1: economic condition and you know, threat inflation, and when when
Speaker 1: a hard economic condition, but that you cannot replace a
Speaker 1: structural policy with a moneitoring polst. In other words, we
Speaker 1: had a problem was debt, and you can't solve that
Speaker 1: problem by putting interest rates at zero for a long time,
Speaker 1: or if you put interface at zero, it should be
Speaker 1: for short periods of time while looking for an alternative.
Speaker 1: So when they did for fifteen years, they put interface
Speaker 1: at zero, and that that does create tumors were the first.
Speaker 1: So let's say the root of everything is interest rates
Speaker 1: at zero, which ironically created the point and of course
Speaker 1: created balls. Is h I would say posy like class
Speaker 1: of investments, because there's no time value of money anymore.
Speaker 1: Your discount you don't know what even you know what
Speaker 1: discount rate is. And we created generation of people who
Speaker 1: don't know the cost of funds, cost of money. So
Speaker 1: and anyone with fifteen years of experience in finance, you know,
Speaker 1: and no more doesn't know anything about interest rates. So
Speaker 1: interest rates as zero create stumers. Read estate values go
Speaker 1: up dramatically because of custom holding mansion is close to
Speaker 1: nothing or was closed nothing. And created a class of
Speaker 1: investment called you know, VC funds. And these were in
Speaker 1: the old days were promising you cash flow, okay, cash flow.
Speaker 1: Today they're promising you around the funding where you're going
Speaker 1: to sell it to someone else. So we moved from
Speaker 1: the classical cash flow model or even if you're negative
Speaker 1: cash flow, the promise of future cash flow to the
Speaker 1: promise of selling the company to someone else. And you
Speaker 1: have millionaires in Silicon Valley who you know, got rich
Speaker 1: from companies that never made the penny. So that's that's
Speaker 1: the background. And of course you're going to have a
Speaker 1: story like the going take off because it doesn't cost
Speaker 1: that goal. Since you mentioned it, I'm curious COVID specifically
Speaker 1: in your criticism of anti vactors, and I find that
Speaker 1: one of the things that I think is interesting, is
Speaker 1: it's not clear to me how you think about these
Speaker 1: problems because they're okay, the vaccine is fairly new, it
Speaker 1: seems to be relatively untested as a technology, and when
Speaker 1: there are other sort of scientific advantage that you've really
Speaker 1: recoiled against. For example, I think you're very critical about
Speaker 1: GMO crops and you're worried about the tail risks posed
Speaker 1: by those. So can you talk a little bit about
Speaker 1: your framework and thinking about why is something like the
Speaker 1: covid vaccine you're comfortable with, whereas something like GMO crops
Speaker 1: to you, creates an uncomfortable level of tail risk. Okay,
Speaker 1: so before we start, let's say that you're not you
Speaker 1: cannot compare vaccines to GMOs because vaccines are tested an individuals,
Speaker 1: so you can see the side effect individual GMOs would
Speaker 1: be a systemic they spread to the environment. And then
Speaker 1: also you're not thinking of the vaccine, you know, for
Speaker 1: because because you think it's that they stood or you
Speaker 1: know it's going to be pleasant. So we take it
Speaker 1: the vaccine. We've got a plot the vaccine versus covid,
Speaker 1: and covid was not something benign, so comparing it's a
Speaker 1: risk management difference between two items and two things I'd
Speaker 1: like to mention here. The first one is that very rapidly,
Speaker 1: you know, I waited a little bit, and very rapidly
Speaker 1: I saw that I had very large number of vaccinated
Speaker 1: people and no side effects, and people say, well, we
Speaker 1: needed more time. They didn't understand that you can replace
Speaker 1: sample size. Time was sample size in the sense that
Speaker 1: if it's something related to genetic states are going to
Speaker 1: take place, or something of the genetic nature, like cancer program,
Speaker 1: that it would be the equips that the large sample
Speaker 1: size compensates for lack of time. I actually overcompass because
Speaker 1: we have the illusion that after Hiroshima people got cancer
Speaker 1: about twelve and a half years later. That's not true.
Speaker 1: Some people got cancer within a few months. But the distribution,
Speaker 1: there's a distribution because we need X number of mutations.
Speaker 1: Like when you go to Las Vegas. For an individual
Speaker 1: to win eight times in a row take decades years
Speaker 1: of waiting. But if you have a billion people in
Speaker 1: a casino, you're going to have that, you know, every hour.
Speaker 1: So this is where this is where very rapidly I
Speaker 1: realized that the vaccine that not really pose a threat
Speaker 1: of that nature, and I wrote technical comments of that.
Speaker 1: But to go back to the pandemic, what would you
Speaker 1: know my thinking? You know, basically my specialty is fat
Speaker 1: tailed events. See, I've don't spend all my life dealing
Speaker 1: with that central problem. How do you do statistical pools
Speaker 1: for fat tailed stuff like masonic pandemic happened. I started
Speaker 1: publishing in that field because people didn't realize that you
Speaker 1: have to think differently when it comes to fat tails.
Speaker 1: You see, you cannot take averages, you shouldn't do ni
Speaker 1: forecasting and get involved in a few polemical discussions. But
Speaker 1: published like seven or eight papers in ronals on on that,
Speaker 1: including masks. And I may have one on vaccine if
Speaker 1: people keep you denying the French or the risk defferential
Speaker 1: between vaccine and the disease. But there's a lot of
Speaker 1: stuff people don't get about the COVID. The first one,
Speaker 1: I would say that it is not something that affects
Speaker 1: the old. It affects everybody in proportion for the mortality,
Speaker 1: so it's not particularly And otherwise if you say, okay,
Speaker 1: it's only in the old, then you should you should
Speaker 1: say okay, let's stop dealing with cancer, because cancer affects
Speaker 1: the elderly disproportionately, or let's stop carreology. It costs too
Speaker 1: much money. You know, Jim Bros. Don't need it because
Speaker 1: they're thirty eight years old. Um, it's the same. It's
Speaker 1: the same iselm. It builds us in proportion to age.
Speaker 1: So in other words, if you your your mortality risk
Speaker 1: goes up by eight percent, regardless about the age of thirty.
Speaker 1: Of course above some specihold and that's not well understood.
Speaker 1: So it's not an old person problem. And as diseases
Speaker 1: not covid by itself. So the bunch of things people
Speaker 1: didn't get. But I you see, I was known initially
Speaker 1: by you other people for the Blacks soon as the
Speaker 1: author of full Barandimus, and that book was misunderstood. Initially
Speaker 1: I was saying that there is I'm not saying there's
Speaker 1: you know, no skills, that there are no skills. I'm
Speaker 1: saying the world is more rather than you think. But
Speaker 1: I'm not saying it's all rival Well, actually I wanted it. Yes,
Speaker 1: let me finish one point. Vandom is connected to the idea.
Speaker 1: So one of the messages of the full barandomness is
Speaker 1: and we tend to be swayed by anecdotes, and I
Speaker 1: noticed that over time things got worse. I mean, the
Speaker 1: circle is sold I don't know, seven eight nine million
Speaker 1: copies world by But at the same time, and a
Speaker 1: lot of people who made the same mistake. People are
Speaker 1: swayed by the anecdote. So so whether it's COVID vaccines,
Speaker 1: whether it's a nice story with a midcoin, whether it's
Speaker 1: stuff about elections, were swayed by the anecdote. So our
Speaker 1: world is becoming more complex requires more statistical sophistication, while
Speaker 1: social media is driving the best to the most primitive
Speaker 1: way of thinking. Sorry to interrupted your trace. No, no, no,
Speaker 1: this is actually exactly what I wanted to ask you,
Speaker 1: something that I've actually always wanted to ask you for
Speaker 1: a long time. Is is there at tension between you know,
Speaker 1: you say in a lot of your works that we
Speaker 1: shouldn't trust experts necessarily you should be wary of you know,
Speaker 1: I think you call them either bullshitters or other other words.
Speaker 1: But but wait, but on the other hand, you know
Speaker 1: it's something like the vaccine. I doubt that the average
Speaker 1: person has the scientific background to look at the literature
Speaker 1: and say, oh, this makes sense or it doesn't. And
Speaker 1: in that case, it seems like we should be trusting experts.
Speaker 1: So how do you square those two things? Yeah, no,
Speaker 1: I made in the black swan to answer your a
Speaker 1: precise question. Had to explain which fields in which field
Speaker 1: the expert as an expert, and it's which field the
Speaker 1: expert is what I call it the s met word. Okay,
Speaker 1: And the difference has to do with fat delay. If
Speaker 1: the micro is much easier to microbs than microbs, so
Speaker 1: that lewis, the dentist is going to be an expert
Speaker 1: a dentist, the plumber is an expert at being a plumber,
Speaker 1: but the micro economists, we're not sure is an expert
Speaker 1: at microeconomics. And the same thing happens in medicine if
Speaker 1: the bologists were not really experts of what's going on
Speaker 1: because it's fatal, but doctor doctor and visual doctor is
Speaker 1: going to be an expert. And we're dealing with tim
Speaker 1: tailed processes. When you look at the time series for
Speaker 1: vaccines and things like that, vaccine is it's a tailed,
Speaker 1: it's not a fat tailed one. So the that's the
Speaker 1: difference with GMO. So sim tailed was the sat tailed
Speaker 1: And of course it would be too complex to explain here,
Speaker 1: but I explained it in the Black Swan. It's a
Speaker 1: difference between the income of a speculator and the income
Speaker 1: of the dentist. One has winner, the winner they call effects.
Speaker 1: The other one is more narrowly distributive. So this is
Speaker 1: where where I saw mainly a difference between experts and
Speaker 1: non actually later on and it's some more thinking and
Speaker 1: scanning the game, saying how can you solve the problem
Speaker 1: and the things The difference is scan in the game
Speaker 1: that if you have skin in the game, then you
Speaker 1: have survival, and then we know if you're an expert,
Speaker 1: or if there's any way to bust your claims okay
Speaker 1: and and make you exit the pool, then then of
Speaker 1: course an expert will will have a filter eliminating pseudo
Speaker 1: experts and particularly those who represent risks for others. A
Speaker 1: surgeon who you know, does that surgery is going to
Speaker 1: ex the pool. So there's a mechanism and surgery, there's
Speaker 1: a mechanism economic life. A grocer who doesn't understand NAMA
Speaker 1: sheets or doesn't stand cash flow will go out of business.
Speaker 1: But there are places where the process is delayed, namely technology,
Speaker 1: namely microeconomics. Economics. I guess the difference. I keep going
Speaker 1: back to the difference. Say your plumber is an expert
Speaker 1: at plumbing, but forecaster is not an expert that forecasting.
Speaker 1: And there are fields where you have a lot of
Speaker 1: b s, like for example, psychology, psychology or what I mean,
Speaker 1: economics are called not clinical the one that deals with
Speaker 1: biases and stuff like that, and there's all bs and
Speaker 1: they can't be caught, whereas medicine is is on firm grounds,
Speaker 1: of course, and it's not perfect. Medicine made a lot
Speaker 1: of stakes, but it's fundamentally self correct. So I get
Speaker 1: the distinction. But I guess my other question is you
Speaker 1: yourself as a flaneur, and um, you know a thinker,
Speaker 1: you sort of you. You go from topic to topic
Speaker 1: to topic, and you know you say that you're my rule.
Speaker 1: Let me tell you my rule, right. My rule is
Speaker 1: I published in purely journal and the topics two professional.
Speaker 1: And that's my problem with Peterson all the guys is
Speaker 1: that I speak about men that I have seven papers,
Speaker 1: and I mean more than the local doctor in medical
Speaker 1: uh topics, Okay, whether it's published in medical journals or
Speaker 1: published in other scientific fields. I talk about genetics, I
Speaker 1: have two published and two coming and genetics. Actually one published,
Speaker 1: one accepted, one and two coming in genetics. So I
Speaker 1: basically I never talked about the subject unless I engaged
Speaker 1: the expert. And that was my fight with a lot
Speaker 1: of people. So so my idea is not necessary to
Speaker 1: publish a perio view journal. If you are in a
Speaker 1: practical profession, like if you're a truck drivers talk about trucks,
Speaker 1: you don't need to publish. But if you're sitting and
Speaker 1: then in every tower in somewhere, you need to engage
Speaker 1: the professional, not you know, not be an expert on
Speaker 1: just on Twitter. And that's my rule. And people don't
Speaker 1: realize that I'm subjecting myself to that discipline. Well, so
Speaker 1: I got I did any papers after Blacksman eighty papers?
Speaker 1: Technical papers? Why not? Because you know, it's not for
Speaker 1: the image. It's because I require from others some kind
Speaker 1: of technical expertise before listening to them. Speaking of I
Speaker 1: guess bullshitters, and speaking of Twitter, and speaking of people
Speaker 1: who say a lot of things on topics that they
Speaker 1: either are not experts on or have not published in
Speaker 1: a rigorous manner. There's Twitter, that's true, but there is
Speaker 1: a certain class of people that in the see, you
Speaker 1: have been going back and forth with venture capitalists for
Speaker 1: several years now. Many of the prominent ones have fashioned
Speaker 1: themselves and these sort of like philosopher kings, waning on
Speaker 1: everything from tech to politics, to what the FED should do,
Speaker 1: to declining fertility rates in the West, and all these
Speaker 1: things that they're up and armed about, and they've gotten
Speaker 1: really loud about how banking works in the wake of
Speaker 1: the failure of SVB. You seem to have a special
Speaker 1: place in your heart of disdain for many of these people, because,
Speaker 1: of course, your natural inclination is still believes that natural
Speaker 1: capitalists do a great job, that they contribute to society,
Speaker 1: that the strength of them that we have to whatever
Speaker 1: computer program we're us about, you know, for this podcast,
Speaker 1: that's the inclination. When you scratch, you realize that maybe
Speaker 1: maybe maybe that was a game, but the game has
Speaker 1: changed dramatically. And you have a bunch of people who
Speaker 1: package companies. They're good at packaging companies, and of course
Speaker 1: the thing has public characteristics. And not only that, but
Speaker 1: they think that society old them something because we use
Speaker 1: an iPhone, okay, so so they have they had a feeling,
Speaker 1: you know what you're using an iPhone. Therefore, you owe
Speaker 1: me some things that were coming and they me up. Okay.
Speaker 1: Plus a lot of these are libertarians, but it so
Speaker 1: happened that a lot of people are libertarians until they
Speaker 1: have the first brought out. So so DC, I mean,
Speaker 1: in principle, it's a very normal professional professionals, but you
Speaker 1: want to avoid the rent seeking by that profession as
Speaker 1: a whole. And this is why every profession, although you
Speaker 1: have reviewed with unpro in economics, you have to just
Speaker 1: make sure there's some accountability, external accountability or an adult
Speaker 1: supervision from the outside. And it looks like dcs are
Speaker 1: not doing what they claimed to do. I mean, think
Speaker 1: of all these billionaires, and you realize that there are
Speaker 1: a lot of these billionaires are billionaires from funding. If
Speaker 1: Tracy and I started a company tomorrow, we put ten
Speaker 1: thousand dollars each, is it okay? Crazy? Well, put ten
Speaker 1: thousand dollars. I think maybe I can afford ten ok
Speaker 1: So we put okay, so so so Tracy and I
Speaker 1: put in ten thousand dollars, and I have companies verse
Speaker 1: twenty thousand dollars, right, and then we decide to sell
Speaker 1: to Joe one percent of a company four thousand dollars.
Speaker 1: Guess what, Tracy, and now now are you know have
Speaker 1: three nine point some percent of who you know, our
Speaker 1: pointy thousands became almost fifty thousand dollars. Joe, you're good
Speaker 1: for one k, right, I could sweat so exactly so,
Speaker 1: and then you have a friend who's going to spend
Speaker 1: another k to buy point one percent, and the company
Speaker 1: and so on. This is a lot of a lot
Speaker 1: of these party A lot of characteristics are president and
Speaker 1: a lot of systems. It's just you know, of course
Speaker 1: there's value somewhere. They produce good stuff. We had a
Speaker 1: lot of recently a lot of the countries, but we
Speaker 1: have to be aware that there's a lot of smoke.
Speaker 1: And also also I realized that that game was fueled
Speaker 1: by low interest rates. Right. Well, so that is the
Speaker 1: general the sort of like the general theory, the general
Speaker 1: case against listening to a lot of these individuals on
Speaker 1: every topic they wish to a pine on. Can you
Speaker 1: just talk a little bit about the specific particularly in
Speaker 1: the collapse of SVB and you've criticized several of them
Speaker 1: which we don't need to mention my name, but about
Speaker 1: their level of understanding of the banking system and finance
Speaker 1: and finance risks, etc. What do you you know, what
Speaker 1: do you think is it just a sort of bias
Speaker 1: sort of like you know the cliche there's no libertarians
Speaker 1: and a bank round or something, or is there a
Speaker 1: deeper misunderstanding that many of them have about how the
Speaker 1: structure of the banking system works. Yeah, I mean, first
Speaker 1: they couldn't. I mean many of them understand the difference
Speaker 1: between losing money for credit invest for credit reasons or
Speaker 1: versus losing money because of the term structures. You see
Speaker 1: that banks web made a mistake of investing Lockdome first
Speaker 1: of all, and that's pretty much the way we think
Speaker 1: about it universal that if you look at convex versus
Speaker 1: callcave investment, you really have to have deep misunderstanding of
Speaker 1: finance to invest very long to and bonds that pay
Speaker 1: you no interest because basically you have no upside and
Speaker 1: all downside from there, you see. So so these banks
Speaker 1: are very fragile and they invested, and it's a current
Speaker 1: play that the US government has got to pay that
Speaker 1: debt and don't use it to think the praises of
Speaker 1: bitcoin because bitcoin suffered from it, and effectively bitcoin rarely
Speaker 1: when they built out the banks. So I'm given one example.
Speaker 1: But then again, let me tell you, when you become prominent,
Speaker 1: irresponsible for your words because you may influence others, right,
Speaker 1: and that's my role. I mean, you can whatever I
Speaker 1: say in public about public in private about public matters. Okay,
Speaker 1: it's public, and I should be held accountable for all
Speaker 1: my mistakes. And I made a lot of mistakes, and
Speaker 1: they're accountable for a lot of other stakes. Well, you
Speaker 1: justus You've got to be self correctly. Just on the
Speaker 1: venture capital model. I mean, I take the funding point
Speaker 1: and I wholly agree with it. But it seems like
Speaker 1: also one of the reasons that VC and tech investments
Speaker 1: in general became so popular during an era of low
Speaker 1: interest rates was that, you know, if you can't get
Speaker 1: a decent return from investing in traditional financial assets, then
Speaker 1: why not basically purchase a lottery ticket for the next
Speaker 1: Google or the next Amazon, or you know, even Bitcoin
Speaker 1: at times has been described as a lottery ticket. Is
Speaker 1: there an overlap between trying to identify tail risks, which
Speaker 1: you know, almost by definition are unknowable and that kind
Speaker 1: of model of trying to purchase a lottery ticket for
Speaker 1: the next big thing, because it seems like both those
Speaker 1: two things you never really know what the next black
Speaker 1: Swan event is going to be or the next big
Speaker 1: technological innovation. This is a big question. It's because people
Speaker 1: keep telling me you like to engage in the trades
Speaker 1: that have high probability of a small loss, a small
Speaker 1: probabilities loss. Okay, why don't you just buy a lostry ticket?
Speaker 1: And you want to explain the condition. The number one
Speaker 1: condition is still have positively expective return. You see that
Speaker 1: your met must have you must not be a turkey.
Speaker 1: In other words, by the lucky. It is completely irrational.
Speaker 1: Long run, you're not gonna make any money. But if
Speaker 1: you engage in taylor Is trade. We believe that in myself,
Speaker 1: which is published a paper explaining option pricing fifty years
Speaker 1: after black trolls, to explain that a lot of people
Speaker 1: think these options are expensive, like expensive lockery ticket effects,
Speaker 1: because they have the long proble we made we made
Speaker 1: the paper public. But the problem of the central problem
Speaker 1: that you should focus on expected value and a lot
Speaker 1: of places and to repeat that appeared to be negative
Speaker 1: expected value and finance effects positively effective value and vice versas.
Speaker 1: It's very rational to go buy to receive. He thinks
Speaker 1: that you the dollar resturnment's two thousand dollars, But I
Speaker 1: thought it will happen. Now the story is oversold, and
Speaker 1: that was a low interest rate game because now people
Speaker 1: are going to focus on profitability and these companies may
Speaker 1: not survive. And if you buy, by the way, if
Speaker 1: you buy into a lot of it. DC has a
Speaker 1: lot of companies, So if you buy into a lot
Speaker 1: of companies, you lose that skewed attribute, so you no
Speaker 1: longer have a symmetry with small losses big gains. If
Speaker 1: I invest on a million companies with small lost big games, okay,
Speaker 1: I would have studied resturns if I have positive effective retirement.
Speaker 1: What did Sam Bankman Freed misunderstand about positive EV Because
Speaker 1: my understanding is that him and his whole crew thought, well,
Speaker 1: huge risks were worth it if there's even a slight edge,
Speaker 1: if there's a slight positive EV And of course they
Speaker 1: took the ultimate risk and it blew up. But they
Speaker 1: seemed to think that these risks were worthwhile because in
Speaker 1: part they wanted to make a lot of money, in
Speaker 1: part because they thought it was important to save the world.
Speaker 1: To make money to save the world from perceived threats,
Speaker 1: whether it's AI or anything else. What did he misunderstand
Speaker 1: about probabilistic thinking? Okay, thought, so this is it's great
Speaker 1: to talk about him, not because it's sim but because
Speaker 1: of that group of people. Yeah, we have this entire
Speaker 1: collection of the young individuals who think that the past
Speaker 1: does not exist. See, when I was a trader in
Speaker 1: my twenties, I picked the brain every older trader who
Speaker 1: had survived. And that was not just me. When I
Speaker 1: look back, I see people who have survived, same attitude.
Speaker 1: So these people make tabla raza. And I remember writing comments.
Speaker 1: I think my friend Tom Holland who said the Romans
Speaker 1: had no cult of the youth, and that was we
Speaker 1: have a cult of the youth, and they have a
Speaker 1: cult for themselves. And to me, being young and finance
Speaker 1: is necessarily right bad thing. Ye, simply because of lack
Speaker 1: of experience, but also that culture. So in the world
Speaker 1: they thought that if they understood the blockchain, they did
Speaker 1: not need to understand finance, and so that's the root
Speaker 1: of the problem. The root of the problem is they
Speaker 1: think that finances computer program finance has vastly more picture
Speaker 1: than that requires a lot more as the introspection when
Speaker 1: you when you when you will pick a decision to
Speaker 1: consider many many, many more factors. Finances, as you know,
Speaker 1: very complicated. This is like what say science is hard,
Speaker 1: to say finance is harder. And there's a fortunate cookie
Speaker 1: approach to finance simplified fortune Qikieff. And it will channelize
Speaker 1: tons of people. And you know, many of them became
Speaker 1: like him, paper billionaires, and now they're going will end
Speaker 1: up like him, living in the basement because they have
Speaker 1: no skills programming whose TRAGEDYDP is a skill that's not
Speaker 1: longer going to be in high demand. So such a tragedy.
Speaker 1: It's a tragedy. It's much more general than than what
Speaker 1: he mists the general approach. We don't need this. I mean,
Speaker 1: they're elementary mistakes these people make. When looking at time series,
Speaker 1: for example, you look at the point if you bought
Speaker 1: it four years ago, that these returns. Yet that's not
Speaker 1: how we look at investments. We look at big two
Speaker 1: valued drawdowns, the structure of drawdown, because you're not going
Speaker 1: to go back in a time machine and buy four
Speaker 1: years ago. You're buying now and you have to worry
Speaker 1: about the next four years. Not the past four years.
Speaker 1: So they don't understand how to present returns, how to
Speaker 1: compare returns, how to discuss inflation. Basic things about monetary
Speaker 1: policy are missed. Talking about someone you know, that age group, educated,
Speaker 1: supposedly educated and making mistakes that I think a clerk
Speaker 1: who you know, or trainee you know and you know trainees,
Speaker 1: that's their main function is to serve often in the
Speaker 1: training room that trainees you know would would would we
Speaker 1: would know immediately mistake. So the world has lost in
Speaker 1: some kind of sophistication and we're going to get it
Speaker 1: back this evolution. These guys will go bust, and those
Speaker 1: trains and was more respective for historical understanding will prevail.
Speaker 1: So in the end the guys who last word and
Speaker 1: the oldest investors around, like one buff It and Charlie Lander.
Speaker 1: How is universal position nowadays? Talk to us about you
Speaker 1: know all these ideas, how are you putting them into practice? Okay?
Speaker 1: The only the thing I would say about universa is
Speaker 1: that in twenty twenty three, the position in this donal
Speaker 1: to the one in twenty thirteen and identical to the
Speaker 1: one will have in twenty fifty one. Okay, So it's
Speaker 1: my cycling allows me to survive that long. So in
Speaker 1: other words, we are providing a structural service with portfolios
Speaker 1: to prevent blow ups, to eliminate that tail and for us,
Speaker 1: just like blocking noisy people on Twitter and has a Twitter,
Speaker 1: eliminating your tail risk allow you to make any mistakes
Speaker 1: you want for your investments. A lot of people seem
Speaker 1: to intuitively like the idea of tail risk funds buying
Speaker 1: protection and you know, for the probably for the reason
Speaker 1: you like. It's like, yeah, we're all going to make mistakes,
Speaker 1: but I want to sleep at night, and so I
Speaker 1: want to have some sort of hedge or something like that,
Speaker 1: and you know, buyputs or whatever it is. But that
Speaker 1: doesn't seem obviously like that's that's costly in the short term. Yeah,
Speaker 1: and there's no free lunch, right And there's no free
Speaker 1: lunch right because no no, no, no, no, no, no.
Speaker 1: That's our Our problem is that if you buy what
Speaker 1: we call the suffers, but you might go give your
Speaker 1: money to charities. And I can give you some charities.
Speaker 1: There's one on level opally these money. I can give
Speaker 1: you the name. The problem Taylor is scheduling is that
Speaker 1: just like Sam Banking Street thought pay finance was easy
Speaker 1: because he figured us with technical things. They had experient
Speaker 1: let's do it. The devil is the new execution, very
Speaker 1: very complicated, very very complicated, and it requires a lot
Speaker 1: of experience. Conceptually though, setting a conceptually conceptually, how is it? Yeah,
Speaker 1: it's a hugely difference because the return you're going to
Speaker 1: have when you I mean, I'm not supposed to top return. Okay,
Speaker 1: we don't have to. I'm going to say conceptually that
Speaker 1: you can look at everything, but there is a huge
Speaker 1: difference between the naive Dale Hedger and the Experiencedale heager.
Speaker 1: And leave it at that. Because sizing there as a
Speaker 1: lot of things involved, particular liquidity, that what how you
Speaker 1: buy because a difference between lived and ask for options.
Speaker 1: This bosphorus just practically you know, you mentioned the difference
Speaker 1: between experienced and naive tail risk catchers. But practically is
Speaker 1: it easier or harder, or cheaper or more expensive to
Speaker 1: buy you know, really big tail risk insurance nowadays? Like
Speaker 1: how has that process actually evolved since the nineteen eighties?
Speaker 1: For instance, I think that people are even more naive
Speaker 1: today than they were in native eighties or not. The
Speaker 1: people are even more naive than that they were after
Speaker 1: stuff market crash. I don't think that we have enough
Speaker 1: financial certification. Maybe short term arbitragers disappear, but things are
Speaker 1: more structural, like how the price tail risks. People are
Speaker 1: very naive. Plus they quite don't quite people also don't
Speaker 1: spend the following argument, it's your own money. You understand
Speaker 1: very well that you don't want to you want to
Speaker 1: sleep at night, and there's some things that we don't
Speaker 1: want to lose all their money. And it's like white
Speaker 1: people never buy a house unless they can have insurance
Speaker 1: on it. To clip the house represents three four times
Speaker 1: their networks. You don't buy a house you know before
Speaker 1: making sure that if it's there's a fire, you're not
Speaker 1: going to have a husual alability. And actually very often
Speaker 1: when you drive, you're probably needed to have a tail insurance.
Speaker 1: But then when it comes to portfolios, those who crede
Speaker 1: their own money or who invest their own money will
Speaker 1: find it natural to say I'm not going to invest
Speaker 1: on this, and a stail risk is expensive vestment. I'm
Speaker 1: not going to invest in that. And then you have
Speaker 1: a second category. People are paid to invest and you say, oh, well,
Speaker 1: this is expensive. I'm going to do that. Of course,
Speaker 1: it's not your money, and that's that's the skill of
Speaker 1: to be a problem. Speaking of tail risk, this week
Speaker 1: that we're recording, several people sound an open letter saying
Speaker 1: that we should halt development of technologies along the lines
Speaker 1: of AI, and that there is an imminent risk, at
Speaker 1: least some people believe of these computers becoming so powerful
Speaker 1: that they wipe out all living things on Earth. Sounds
Speaker 1: like the ultimate tail risk. I'm not going to ask
Speaker 1: you how you would hedge against that, because I doubt
Speaker 1: that would be a scenario worth hedging for. But is
Speaker 1: that a tail risk in your view? Are are we
Speaker 1: on track to develop computers that will eliminate life as
Speaker 1: we know it? I don't think so. Number One is
Speaker 1: people are worried that ship will put them out of business.
Speaker 1: That's why to issue these calls. I'm worried about that. Yeah, well,
Speaker 1: I mean GP is not running red lights, traffic lights,
Speaker 1: it's not running things that are consequential. And when AI
Speaker 1: starts running these things, and we'll talk about it, but
Speaker 1: for the time being, we'll talking about development. And it
Speaker 1: looks like it's a problistic machine no more nor less
Speaker 1: with the defects of probabilistic machines. And the reason I
Speaker 1: talk a little bit about AI because as the statistician,
Speaker 1: it's just nothing but nonlinear statistics. That's what is right,
Speaker 1: and it's the statistical device, and it worked a statistical device,
Speaker 1: but we know the shortcomings and statistical machineries and it
Speaker 1: has all the so I'm not even away nobody's going
Speaker 1: to use that I for things beyond automated searches or
Speaker 1: it just automates a lot of things that can be automated.
Speaker 1: And unfortunately a lot of people feel threatened because they
Speaker 1: see the discourse by by by the chat GDP very
Speaker 1: similar to their own, because it's a bullshit. I think
Speaker 1: this would be so far. I don't see anything as
Speaker 1: far as society, I don't see It's not like with
Speaker 1: the pandemic way to see something spreading. What's the tail
Speaker 1: risk that you think investors are most underestimating nowadays? Okay,
Speaker 1: that's the fact that zero interest rates are very unnatural
Speaker 1: and if you raise rates to a normal level, and
Speaker 1: what's normal levels, say between forms six percent said, you
Speaker 1: know would like to have higher interest rates, but there
Speaker 1: are some pressures you like to have a higher base
Speaker 1: because if you're at four percent interest rate, then lower it.
Speaker 1: If you have a crisis, you can you can go down,
Speaker 1: you can go up. But if you interestrate at zero
Speaker 1: and you have further crisis, you don't know what to do.
Speaker 1: So or at least you can play with interest rates,
Speaker 1: we have to look for something else suggesting on measures.
Speaker 1: So I think that if you look at interest rates
Speaker 1: higher than three percent of term as a discount rate,
Speaker 1: then equities aren't trouble because I'm not priced for that.
Speaker 1: So this is where where you're gonna look at it.
Speaker 1: You can look at structurally, the equities aren't trouble. But
Speaker 1: I think that many things will you know, the equity
Speaker 1: would be the last you're all say, there's a lot
Speaker 1: of things that would be in trouble. First, I have
Speaker 1: two final questions. One is very short, do you still
Speaker 1: eat squid ink pasta? And where's the best squid in pasta?
Speaker 1: These are the important question. Where's the best important? Yeah? Yeah,
Speaker 1: if you want good squil in pasta. If you want
Speaker 1: good squitt in no pasta, you'll go Lebanon. There's no
Speaker 1: the major recipes are the best. And if you want
Speaker 1: a good squilling pasta. You got to go to sat
Speaker 1: okay if you want squilling results though northern Italy. And
Speaker 1: then if you you know, then I would say lower
Speaker 1: on the list of Spain, you go for the arrows,
Speaker 1: the bay. You know, the black so the Black rides
Speaker 1: so so I New York yere I you know, I
Speaker 1: don't recommend too much, but I can cook. I'm learning
Speaker 1: to cook it. And it was in two three years
Speaker 1: to produce the Descent dish Well, Tracy, and I would
Speaker 1: love to do a live video episode coming over to
Speaker 1: your house sometime and having you prepare us a squid
Speaker 1: in dish in three years twenty see times. Yeah. Well,
Speaker 1: so then one one last question, and I really appreciate
Speaker 1: the time I have to say if I'm if I'm
Speaker 1: being just like totally blunt. I know that you say
Speaker 1: that many of your readers of Anti Fragile and some
Speaker 1: of your other works misunderstood your work, and I get that,
Speaker 1: but I also think, I mean, if I'm just being blunt,
Speaker 1: I think like your tone has changed. You seem a
Speaker 1: little less bombastic than previous times we have chatted. You
Speaker 1: yourself have gotten let me no, maybe, but it's because
Speaker 1: you agree with more because there's always a spile us.
Speaker 1: If you agree with the message, all right, that's fair
Speaker 1: to see you you you you give a lot of
Speaker 1: flag to the messenger. And yeah, we're enough fair enough
Speaker 1: that no perfect question. So that's what one thing is
Speaker 1: that I had. Let it to go back to antifragile,
Speaker 1: it's just a brief summary. You know what it means.
Speaker 1: I means that we need stressors, we need low grade
Speaker 1: a lot of low grade stresses, let's see. And and
Speaker 1: the companies need to encounter a few problems because you
Speaker 1: up regulate and you get stronger after that. But it
Speaker 1: doesn't mean that we should tolerate tailor risk. It's all
Speaker 1: conditional on a volume tail risk. And and and if
Speaker 1: you get stronger jumping, you know, one foot Howard leaders
Speaker 1: are going to kill you. So just just don't take
Speaker 1: the idea too far. It's very local. That's the idea
Speaker 1: of anti fragile. And an antifragial investment is now something
Speaker 1: called antifragile by some web thinker. You know. Antifrassial investment
Speaker 1: is something that we acts very well to the misfortunes
Speaker 1: in the market. And then definitely a lot bitcoins, let's
Speaker 1: see Sam Nicholas till This was a thrill. Thank you
Speaker 1: so much for coming on. And I'm looking forward to
Speaker 1: dinner at your house in twenty twenty six and another
Speaker 1: episode in Yeah, and we'll come anywhere, Tracy, and I think,
Speaker 1: Tracy and I would you would love to visit you
Speaker 1: in Lebanon. We'll bring a crew, we'll film it. It'll
Speaker 1: be great, and then we'll have you back on again
Speaker 1: in fifteen years, you know, assuming the AI hasn't killed
Speaker 1: us all. But uh, thank you so much. This was
Speaker 1: a real, uh real pleasure. Thanks, thanks very much, very much,
Speaker 1: Thank you. Thanks the same. I appreciate it so Tracy.
Speaker 1: The big question is did the seam change or just
Speaker 1: suddenly he says things that flatter our biases, so suddenly
Speaker 1: we perceive him to have changed. I mean, I imagine
Speaker 1: it's a bit of both. But I think my first
Speaker 1: of all, I enjoyed that that was so fun a lot.
Speaker 1: But secondly, I think my big like how I learned
Speaker 1: to stop worrying and love the teleb moment, is you
Speaker 1: kind of have to realize that a lot of the
Speaker 1: criticisms and things he says about others kind of apply
Speaker 1: to himself. Which doesn't necessarily which doesn't necessarily make them untrue.
Speaker 1: They're still very valuable insights. But it's either you know,
Speaker 1: you grasp that and it frustrates you enormously, or you
Speaker 1: just roll with it and appreciate the insights nonetheless. And
Speaker 1: I think I'm in the stage of my life where
Speaker 1: I'm just going to roll with it. That's so funny,
Speaker 1: especially because he specifically is like, no, no, no, I
Speaker 1: published in academic journals. I am not a all purpose
Speaker 1: bullshit or you know. One thing that I think throughout
Speaker 1: and I have to say for years a point of
Speaker 1: his that I've always whatever cycle he's in, whoever hates
Speaker 1: him at a given moment, that I've always respected of
Speaker 1: that I've always thought it was true. It is a
Speaker 1: point about the difference between a plumber and an economist,
Speaker 1: or the difference between a doctor and an epidemiologist, which
Speaker 1: I think is like a really like insightful true point
Speaker 1: that like, you know, a plumber is an expert on plumbing.
Speaker 1: They they've fixed a pipe or a toilet, or a
Speaker 1: sewer system or a shower system thousands and thousands of times.
Speaker 1: There is very little new that you can ever show
Speaker 1: a plumber that they haven't seen, and there is a
Speaker 1: certain level of skill set and ability to solve things
Speaker 1: that one can only get after having fixed a lot
Speaker 1: of toilets or pipes, which and that's why there's the
Speaker 1: whole apprenticeship thing. And I think that is like a
Speaker 1: really useful heuristic to talking to anyone, which is like,
Speaker 1: are they really an expert, have they done something that's
Speaker 1: built up deep expertise, or are they just sort of
Speaker 1: like kind of winging it right. I think that's a
Speaker 1: completely valid point, and there's only so much expertise that
Speaker 1: I think one person and can really have. You know,
Speaker 1: you can't expect people to be an expert in everything.
Speaker 1: But on the other hand, you know, he talked a
Speaker 1: lot about the world becoming more complex, and I think
Speaker 1: this is where the instinct comes to try to understand
Speaker 1: more and more things, because yes, a plumber, he's seen
Speaker 1: many many clog toilets and he can probably fix them
Speaker 1: in his sleep. But then when something unexpected happens, like
Speaker 1: for instance, COVID and a supply chain crisis, that impacts
Speaker 1: his ability to get I don't know, those little like
Speaker 1: toilet pump things that seems to like that's where the
Speaker 1: instinct to try to understand the whole comes from, and
Speaker 1: the irony and all of this is that, like, that's
Speaker 1: a lot of what Teleb spends his time doing, right,
Speaker 1: is trying to identify and presumably positioned for these sort
Speaker 1: of unexpected risks. You know, it is interesting the difference
Speaker 1: between in his view of the vaccine and GMOs, one
Speaker 1: being systemic one bit, the other being the trials of
Speaker 1: thousands and thousands of people. Is of course and intuitively
Speaker 1: there's you know, statistics, but just a is a substitute
Speaker 1: for time in the way that GMO crops. There's no
Speaker 1: way to shortcut the process of like, well, what is
Speaker 1: going to happen to the entire ecosystem of agriculture over
Speaker 1: the next one hundred or a thousand years, because we
Speaker 1: just literally haven't there's no way to substitute that time yet. Anyway,
Speaker 1: I really liked that conversation. I was sad during that
Speaker 1: period when to let block me and I'm glad we
Speaker 1: are both I'm glad we are both unblocked because I
Speaker 1: am very enjoying I'm watching I'm enjoying watching him his
Speaker 1: cycling journey. I'm enjoying watching his fights, and I just
Speaker 1: think he's an interesting guy absolutely, And I guess I'm
Speaker 1: looking forward to having squid inc Yessa in three years time.
Speaker 1: All I can say is there's gonna be a lot
Speaker 1: of pressure though, because it better be good after three
Speaker 1: years of study. Well, you know, the thing is he's
Speaker 1: been talking about squidding forever and so the fact that
Speaker 1: he himself says it's going to be another three years
Speaker 1: before he's ready to like cook it, it's like, uh,
Speaker 1: you know, he's a he's a journeyman. It sounds like
Speaker 1: he is himself an apprentice or journeyman squid ink chef
Speaker 1: who is not there yet. Maybe we should do a
Speaker 1: come Dine with Me style cook off each of us,
Speaker 1: each of us attempts to cook squid ink pasta in
Speaker 1: a different location, and then we rate each other. All right,
Speaker 1: I'm getting ahead of myself. Shall we leave it there?
Speaker 1: Let's leave it there. This has been another episode of
Speaker 1: the Odd Thoughts Podcast. I'm Tracy Alloway. You can follow
Speaker 1: me on Twitter at Tracy Alloway and I'm Joe Wisent'tal.
Speaker 1: You can follow me on Twitter at the Stalwart. Follow
Speaker 1: our guest on Twitter if you're not blocked. His handle
Speaker 1: is at n nd taleb. Follow our producers Kermen Rodriguez
Speaker 1: at kerman Ermine and dash Bennett at dashbot. And check
Speaker 1: out all of our podcasts under the handle at podcasts.
Speaker 1: And if you want more odd Lots content, go to
Speaker 1: Bloomberg dot com slash odd Lots, where you can find
Speaker 1: trans scripts of blog newsletter. And if you want even more,
Speaker 1: we have a really fun community online on discord where
Speaker 1: a bunch of listeners hang out twenty four seven in
Speaker 1: chat about things like markets, finance, economics, energy, water, AI
Speaker 1: and all the things we talk about. Go check that
Speaker 1: out discord dot gg slash oblocks of the invite link.
Speaker 1: It's really fun. I've been spending a lot of time there.
Speaker 1: Go hang out. Thanks for listening.