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Speaker 1: Welcome to the Nick, Dick and Paul Show. I am

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Speaker 1: one of your hosts, Nick Bilton. I write stuff for

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Speaker 1: a living and somehow ended up in this podcast.

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Speaker 2: My other host is.

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Speaker 3: I'm de Costello, former CEO of Twitter and the first

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Speaker 3: user of Facebook.

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Speaker 4: Were you really no?

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Speaker 5: Oh?

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Speaker 2: Okay?

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Speaker 5: I was willing to go with that. I actually thought

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Speaker 5: that was probably true. Paul Kadrowski, venture investor, Wall Street

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Speaker 5: Guy way back.

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Speaker 4: Talk too much?

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Speaker 2: Definitely does talk too much.

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Speaker 4: All.

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Speaker 1: We have a very very special guest today. His name

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Speaker 1: is Alan Lob. I've known Alan for about fifteen years.

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Speaker 1: He is an incredible screenwriter. He is also a former

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Speaker 1: Wall Street or Chicago which one was it?

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Speaker 4: Chicago?

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Speaker 2: Chicago?

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Speaker 1: And he's a gambling addict, so compulsive compulsive gambler.

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Speaker 2: Sorry is that?

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Speaker 6: Did I say it?

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Speaker 4: That's a proper way to say.

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Speaker 1: Okay, god, So as a compulsive gambling addict. He We're

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Speaker 1: going to talk today about poly markets, about the betting

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Speaker 1: culture that we're in today, and and we're gonna hear

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Speaker 1: some some really really fun stories from Alan, uh which

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Speaker 1: which I can't wait to jump into.

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Speaker 2: So Alan, welcome, Welcome to the show.

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Speaker 4: Thank you. It's great to be here. Great to see

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Speaker 4: you guys.

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Speaker 1: So we we wanted to talk about poly markets and stuff.

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Speaker 6: But can you set the prediction market? Prediction markets?

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Speaker 4: Can you?

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Speaker 1: Can you just tell us a little bit about your

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Speaker 1: history of gambling and how like.

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Speaker 6: How it became compulsive.

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Speaker 4: Yeah, I think it becomes compulsive the second you're born.

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Speaker 4: I do believe it's a genetic disposition with with compulsive gambling.

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Speaker 4: Probably alcoholism would be my guest in other addictions, but

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Speaker 4: for me, for men, it happens very very young. It's interesting.

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Speaker 4: For women, it happens empty nesters. They that's when they

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Speaker 4: know when they end up, when the kids leave the house,

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Speaker 4: they go to the local casino, play the video poker

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Speaker 4: games and then they lose everything. For men, it's when

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Speaker 4: you're twelve, fourteen, about twelve years old?

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Speaker 2: What was the first thing you bet on? A twelve?

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Speaker 4: I used to play poker in the hallways of my

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Speaker 4: middle school with I grew up in the North Shore

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Speaker 4: of Chicago, so in a in a in a suburb,

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Speaker 4: and with the some other students. I can name them

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Speaker 4: all now, I mean it would be who's who in

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Speaker 4: Jewish names? Neil Goldman, Andrew Bergman and we would play

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Speaker 4: in the hallways really rough. I don't even know. It

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Speaker 4: wasn't the kind of poker there is now like Texas

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Speaker 4: holl them. It was some sort of bastardized, easier simple version,

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Speaker 4: and we'd all owe each other money that we didn't

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Speaker 4: really have, and then things went crazy, even in those days,

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Speaker 4: with getting the money.

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Speaker 5: So and how did it How did it make you

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Speaker 5: feel when you won versus when you love?

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Speaker 2: That was what I was going to ask.

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Speaker 4: Yeah, I mean, as as far as I remember my

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Speaker 4: whole life, it's it's a dopa meanal addibition, was it?

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Speaker 5: It's obviously asymmetric, though, I mean, like so didn't The

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Speaker 5: old thing in financial markets is that people are averse

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Speaker 5: to losses, and so averse to losses that they often

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Speaker 5: avoid taking risks.

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Speaker 6: This is the opposite correct correct.

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Speaker 5: So that's what I'm trying to get at, this asymmetry

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Speaker 5: between how you feel when you win versus the feeling

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Speaker 5: when you lose.

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Speaker 4: I think it's like a heroin addict who is always

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Speaker 4: chasing the first high. A gambling addict is always chasing

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Speaker 4: the feeling good about winning, and so they'll double down,

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Speaker 4: double down, double down, what they call chase which is

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Speaker 4: what you do, and you don't have there's something missing

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Speaker 4: and the most I'll be honest, I think most gambling

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Speaker 4: addicts are very intelligent people, but compulsive gamblers have no

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Speaker 4: control of the dose, so they're chasing the dose and

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Speaker 4: they don't. I don't. I didn't. You couldn't correlate the

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Speaker 4: result and the accountability and what would happen. And if

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Speaker 4: I win this game, you know I've been on a bender,

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Speaker 4: let's say, and I've got I've been for example, Yeah,

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Speaker 4: I've been chasing, chasing, chasing, And originally I was trying

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Speaker 4: to make I don't know what, five thousand dollars, and

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Speaker 4: now I have one hundred thousand dollars on a game

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Speaker 4: to make that five thousand dollars, and I don't realize

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Speaker 4: when this game's over, I'm gonna, oh, one hundred and

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Speaker 4: thirteen thousand dollars, I have twenty two thousand dollars to

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Speaker 4: my name, and I don't get another bed. And that's

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Speaker 4: where you're sitting, and you don't realize, like, why the

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Speaker 4: hell would I risk one hundred and thirty thousand dollars

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Speaker 4: to make five thousand dollars. A ten thousand foot year.

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Speaker 5: But I think the thing that a lot of people

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Speaker 5: don't understand who look at this stuff, is that brain

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Speaker 5: wiring right there, that asymmetry is so different from the

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Speaker 5: way a lot of people approach things, Like back in

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Speaker 5: my time in the financial industry, a lot of the

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Speaker 5: time you're trying to convince people to take on a

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Speaker 5: little more risk, you know, at the sort of efficient

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Speaker 5: frontier stuff, and take on a little more risk for

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Speaker 5: a little more return. And that's often hard to get

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Speaker 5: people to do because they just don't. They're like, no, no, no,

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Speaker 5: I just want to all sit in savings accounts. I

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Speaker 5: want to sit in CDEs or something like this. That's

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Speaker 5: not the brain wiring at all that you're talking about, right,

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Speaker 5: just the almost the exactos.

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Speaker 4: It's almost the exact oppici And it's really the equivalent

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Speaker 4: to drug addiction, it really is. And I think it's

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Speaker 4: the same centers of the brain.

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Speaker 6: Yeah.

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Speaker 1: No, So one question I have is is and I

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Speaker 1: want to hear some stories, but is don't I don't

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Speaker 1: have a gambling.

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Speaker 6: Do you guys? Are you?

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Speaker 2: Are you a gambler?

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Speaker 6: Dick?

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Speaker 5: Not as far as you know, much as far as

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Speaker 5: you know, But I don't.

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Speaker 1: Have a gambling bone in my body, like I just can't.

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Speaker 1: I don't find it. I just it scares me because

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Speaker 1: I'm going to lose the money I.

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Speaker 6: Just worked so hard for.

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Speaker 5: That's asymmetry thing, right, and the asymmetry thing. The pain

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Speaker 5: you get from losses is so much more than the

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Speaker 5: pleasure you get from gains.

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Speaker 2: But I have It's a two part question.

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Speaker 1: The first part is is is there a high that

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Speaker 1: comes from losing? Is it like, is there something that

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Speaker 1: or is that just like, oh that sucked.

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Speaker 4: No, I think I think there isn't a high that

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Speaker 4: comes from losing. There may be, to get a little

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Speaker 4: bit more deeper in the psychology, there may be a

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Speaker 4: masochistic element to this, where you're actually it's a it's

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Speaker 4: an act of self hate, and often it's a punishment.

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Speaker 4: It's a self flagellation when you lose, and a lot

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Speaker 4: of gamblers are incredibly insecure as I was.

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Speaker 2: Is this partly why you ended up on Wall Street?

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Speaker 4: No? I wasn't. I wasn't on Wall Street.

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Speaker 6: I was.

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Speaker 4: I was in the Commodities Exchange in Chicagogo.

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Speaker 6: We were the Chicago Street.

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Speaker 4: It was agriculture in those ways, and they don't have

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Speaker 4: the floors anymore, because they're all now on the computers.

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Speaker 4: But it was the funny color jackets from trading places

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Speaker 4: and the ARBs and the handsales. And I started out

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Speaker 4: of college as a runner in that world, which is

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Speaker 4: the equivalent of like being in the William Morris mail

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Speaker 4: room here in Hollywood. And I was there for about

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Speaker 4: a year, and I something in me knew I would

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Speaker 4: die if I if I did what these guys did,

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Speaker 4: if I became these guys, Because these guys were the

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Speaker 4: biggest cowboys you've ever seen. They were heart attacks on

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Speaker 4: the floor. They had defibrillators on the floor for real. No, No,

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Speaker 4: this world was incredible in the eighties.

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Speaker 2: And how do you know about it?

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Speaker 6: Just I lived in Chicago.

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Speaker 5: You were on it.

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Speaker 2: You weren't on the Chicago.

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Speaker 6: You don't know where I was. You don't know anything

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Speaker 6: about me.

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Speaker 4: But I had two friends in high school whose fathers

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Speaker 4: put a gun in their mouths and killed themselves because

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Speaker 4: they had made you know, over the course of a

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Speaker 4: year or two, they made forty sixty million dollars in

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Speaker 4: nineteen eighty five and then lost it all in two days,

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Speaker 4: and then they killed themselves. I think this was common

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Speaker 4: in that world.

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Speaker 5: And that's the thing that I think brings out a

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Speaker 5: real gambling mentality in Chicago versus like on the NYC,

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Speaker 5: versus floor traders anywhere else is there is this And

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Speaker 5: this is the thing that goes back to the difference

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Speaker 5: between Chicago and what's traded there versus what's happening in

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Speaker 5: other places. Just huge leverage, right, massive massive leverage. So

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Speaker 5: the opportunity for gains is immense and the opportunity for

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Speaker 5: losses is amense. You can do that to a degree

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Speaker 5: in equity markets, but nothing like the kind of futures

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Speaker 5: market leverage that exists in Chicago.

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Speaker 4: And then the agriculture market volatility is insane. If there's

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Speaker 4: a if there's a winter storm, the orange juice, futures

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Speaker 4: go crazy. And it's much more than even which biotech.

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Speaker 6: Which brings in futures.

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Speaker 4: It's literally the movie Trading, such a great movie.

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Speaker 5: Which brings in the gamblers though, right, because that's it

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Speaker 5: brings in people who are really that kind of leverage

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Speaker 5: and volatility isn't it's a feature, not a bug for them.

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Speaker 5: They really like that and they want that. They wouldn't

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Speaker 5: go anywhere else, and.

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Speaker 4: They would all smoke two packs a day, they all

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Speaker 4: do cocaine in the bathrooms, and the heart attacks were

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Speaker 4: plenty in that world. And I left because I knew

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Speaker 4: it was too good for me, and good isn't bad.

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Speaker 4: It was I wasn't going to survive that world. So

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Speaker 4: I came out to a much less of little world

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Speaker 4: of Hollywood's.

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Speaker 5: Completely predictable with no average.

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Speaker 1: Okay, so do you want to give us, Dick a

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Speaker 1: little bit of the listeners of what this whole prediction

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Speaker 1: of prediction markets? And then I'm curious to get into

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Speaker 1: that with with with al.

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Speaker 3: I'm gonna skip over the regulatory stuff, because there's a

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Speaker 3: bunch of interesting, you know, issues and discussions between why

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Speaker 3: you know, DraftKings fan duel sports betting versus the prediction markets,

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Speaker 3: and state regulation versus federal regulation. But ignoring that for

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Speaker 3: the moment, the prediction markets are essentially there's no house.

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Speaker 3: It's you versus you know, it's me betting against Paul.

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Speaker 3: It's me saying I think when SpaceX goes public, it's

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Speaker 3: going to close on day one over one point four

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Speaker 3: trillion dollars, and Paul says, and I don't think it's

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Speaker 3: I don't think that's true. I'll take the other side

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Speaker 3: of that bet. And that's essentially the prediction markets. You

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Speaker 3: can essentially put money to work against anything. I think

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Speaker 3: when Powell gets on and does his you know, a

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Speaker 3: FED notes a speech this afternoon, I bet he'll start

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Speaker 3: off with this with the phrase good good afternoon, and

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Speaker 3: I can take the other side of that, like I

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Speaker 3: can take the no, no, he won't, and then you know,

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Speaker 3: it'll say on Calshie or polymarkets, or choose your prediction market.

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Speaker 6: Here's how the bet will be settled.

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Speaker 3: You know, in the space case, it's if at the

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Speaker 3: end of the first trading day, the close you know,

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Speaker 3: before the after market is x y z, and that

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Speaker 3: results in a market gap of you know, over one

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Speaker 3: point four jillion dollars, Yes.

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Speaker 6: Wins the bet, et cetera. You get it.

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Speaker 3: The interesting thing is you can create, as you can imagine,

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Speaker 3: and as I just said with the Powell example, all

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Speaker 3: sorts of crazy predictions.

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Speaker 5: Well now as context by the way, just this is

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Speaker 5: not new though, right. The wacky thing is is prediction

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Speaker 5: markets in a weird way. Prediction markets go back to

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Speaker 5: the origins, of course, I mean that's what prediction markets

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Speaker 5: were we were predicting what would happen with the prices

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Speaker 5: of these instruments. So back in the nineteenth century that

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Speaker 5: was that was a prediction market, and then those evolved

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Speaker 5: over time and in the eighties and nineties, so things

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Speaker 5: like electronic market. You remember that, anyone remember that one?

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Speaker 2: What's that?

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Speaker 5: It was the earliest academic experiment on letting people bet

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Speaker 5: with kind of funny money on what would happen in elections,

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Speaker 5: So that existed in the eighties, predict it in trade.

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Speaker 5: These are all like things that have long disappeared off,

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Speaker 5: So these experiments were going on for some time in

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Speaker 5: taking some of these ideas around letting people use money

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Speaker 5: to express the feelings about something, whether or not it's

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Speaker 5: likely to happen, and the other twist. That's interesting and

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Speaker 5: this is what I think what Dad was talking about.

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Speaker 5: It's sort of unusual structurally with respect to prediction markets.

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Speaker 5: Is there binary markets, meaning that you're not betting in

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Speaker 5: a sense, when I buy a stock, I'm not betting

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Speaker 5: that it'll go to twenty seven versus twenty eight dollars.

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Speaker 5: I'm just betting it'll go up. But in a binary market,

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Speaker 5: there's a binary outcome I'm betting on pole will say this.

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Speaker 5: He won't say this, right. So this notion that there's

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Speaker 5: a kind of a yes snow at the other side

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Speaker 5: is really interesting.

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Speaker 4: Don't they trade as stocks like you can get out

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Speaker 4: yea before Paul speaks, if you're if the public is

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Speaker 4: beginning to agree with you and the market.

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Speaker 5: No, just the idea that the outcome is binary. You

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Speaker 5: can still get in and out continuously. But the thing

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Speaker 5: that at the end of the day that in theory

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Speaker 5: makes the price change is a binary outcome. That's just interesting.

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Speaker 4: Similar to when a company has earnings and they announce

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Speaker 4: earnings that day, the market's going up around and then

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Speaker 4: once the earnings are announced and you can still.

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Speaker 5: Bet that way. So the idea of the whole market

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Speaker 5: predicated on these binary outcomes is one of the twists

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Speaker 5: that makes these things really well.

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Speaker 3: To Paul's point, the binary outcome means it's not I

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Speaker 3: made ten percent or I lost ten percent.

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Speaker 6: I make this much money or I lose all of it.

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Speaker 5: Yeah, unless you truly are trading continuously with most people don't.

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Speaker 2: Which is called the bet, which is just called a path.

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Speaker 6: That's exactly right.

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Speaker 1: But wait, but there's millions and millions of people doing this.

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Speaker 1: So my question is is everyone a gambling attict now or.

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Speaker 5: Is it just because just so, I mean, you're probably

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Speaker 5: in a better position to talk about this.

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Speaker 4: I would say that the prediction markets and that the

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Speaker 4: way that the kelshi and poly market are just forms

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Speaker 4: of gambling, obviously, but I think a large the stock

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Speaker 4: market's different. There was investing in trading, and trading is

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Speaker 4: more gambling, and investing is a little less gambling. It's all,

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Speaker 4: you know, a gamble and all risk. But yeah, I

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Speaker 4: think the prediction markets are just another form of gambling.

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Speaker 5: But it's really hard now to find. Like if you

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Speaker 5: go hang around at a college and I was talking

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Speaker 5: to my son about this the other day, you walk

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Speaker 5: by a random group of young males and just if

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Speaker 5: you want to make a bet about a bet, bet

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Speaker 5: on what they're talking about. As you walk by a

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Speaker 5: cluster of young males, seventy eighty percent chance you'll hear

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Speaker 5: them talking about the prop bat on the weekend game,

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Speaker 5: about whatever. And it's uniformly true. And you hear this

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Speaker 5: all over the United States in particular, maybe true in

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Speaker 5: the rest of the world, but it's become one of

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Speaker 5: the main things that young males, so young males than

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Speaker 5: young females are all are talking about because it's one

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Speaker 5: of the central preoccupations they have. Is it's thing these

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Speaker 5: daily fantasy sports that I can bet on outcomes and

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Speaker 5: really weird things like the first fumble will be in

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Speaker 5: the something minute of this game. But that has really,

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Speaker 5: I'll say it, sort of democratized this stuff and almost

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Speaker 5: acts like a drug in terms of giving people cheap

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Speaker 5: and easy access to it for low prices on absolutely everything.

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Speaker 5: But otherwise just idly watch.

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Speaker 1: Is there going back to the you know, if Powell's

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Speaker 1: going to say good morning when he when he does

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Speaker 1: his speech, is there insider trading?

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Speaker 6: Like if I wrote Powell's speech.

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Speaker 5: Off the charts, I mean no, but I'm saying it's

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Speaker 5: actually that's right, and even with the SEC there's lots

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Speaker 5: of insider trading works.

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Speaker 6: Yeah, just to be clear.

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Speaker 3: That's like if you talk to the you know, Taruk

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Speaker 3: or Shane, the polymarkers or calls founders. Uh I flipped

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Speaker 3: those around, it's you get it what I mean, they

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Speaker 3: will tell you that's part of the whole deal. Like, yeah,

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Speaker 3: there's of course there'sn't of course, there's insider trading. Now

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Speaker 3: in the stock market, it's of course there's insider trading,

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Speaker 3: but we have a group that supposedly prevents that.

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Speaker 6: Here it's part of the whole deal, and everyone.

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Speaker 3: Acknowledges it, when in fact it's already it's already been

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Speaker 3: known to have happened a couple of times, is as

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Speaker 3: as was famously uh mentioned the news, But but happens

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Speaker 3: regularly in the you know, a couple hours before we

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Speaker 3: went in and got Maduro, somebody came in with a

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Speaker 3: new account and you know, in one dollars that had

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Speaker 3: made one prediction in one prediction in trouble. Now again

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Speaker 3: again there's no one regulating this against laws against prediction markets.

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Speaker 4: What's the liquidity like, because that's what I'm not on

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Speaker 4: the prediction market.

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Speaker 5: It completely depends on the market. Most of them are

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Speaker 5: very thinly traded. The dirt. The dirty secret of most

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Speaker 5: prediction markets is they have all of these election and

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Speaker 5: financial and apparently war predictions. All of those are real liquid.

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Speaker 5: The thing that's mostly the most what are the most

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Speaker 5: liquid or anything to do with sports, And so that's

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Speaker 5: the complaint that a lot of people have is these

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Speaker 5: are actually thinly disguised sports betting marketplaces that operate under

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Speaker 5: the label of being prediction markets, because that's where all

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Speaker 5: the liquidity is. It's really hard to get and keep

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Speaker 5: people motivated about very much that's not sports related. Possibly politics.

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Speaker 5: But again, even with finance predicting what's going to happen

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Speaker 5: to a company's earnings, there already is a prediction market

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Speaker 5: for that. It's called the stock market. It's really liquid,

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Speaker 5: works pretty well.

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Speaker 3: In fact, in fact, this is the Draft Kings and

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Speaker 3: fan duel legal action as Hey, we have to be

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Speaker 3: state regulated state by state by state and go get

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Speaker 3: approvals and that's right. And then these guys guys, yeah,

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Speaker 3: these guys come in with the CFTC and get federal

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Speaker 3: approval to do these but but it's really just what we're.

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Speaker 5: Doing without the state by state approval.

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Speaker 1: You allan, tell tell us, tell us some stories. Come on,

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Speaker 1: you got some good ones. Tell us about the cab

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Speaker 1: with the money that you left.

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Speaker 4: Okay, Yeah, this is I wrote about this, and I

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Speaker 4: wrote a column for the an article for the Free

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Speaker 4: Press about my life as a compulsive gambler. And this

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Speaker 4: is a story I tell in it, which is basically

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Speaker 4: I had to go to Vegas my booky coming off,

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Speaker 4: and I was really I owed him a lot of money.

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Speaker 4: I think it was at the time, eighty ninety thousand

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Speaker 4: dollars how long goes it? Twenty plus years ago, and

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Speaker 4: I owed him a lot of money, and I needed to,

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Speaker 4: so I sold some of my text. It was actually

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Speaker 4: it was the late nineties because I had made a

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Speaker 4: ton of money off of the tech stocks that we

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Speaker 4: all if you're a certain age, you remember the JDSUS

375
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Speaker 4: and the Sienna, and I remember them. We all went

376
00:16:32,440 --> 00:16:35,160
Speaker 4: up like you didn't have to know what they did.

377
00:16:35,160 --> 00:16:36,520
Speaker 4: They all went up, and I had made a lot.

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Speaker 4: So I liquidated a lot of that account and I

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00:16:38,760 --> 00:16:41,480
Speaker 4: took a taking one hundred thousand dollars to Vegas to

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00:16:42,120 --> 00:16:45,120
Speaker 4: bet one weekend to try to pay the bookie back.

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Speaker 4: Instead of just taking the money and giving it to

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Speaker 4: the bookie, I was going to Vegas to double it,

383
00:16:49,640 --> 00:16:51,880
Speaker 4: pay the bookie, and then put the money back into

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Speaker 4: the stocks.

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Speaker 3: Let me guess that's done, not how it works, because

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Speaker 3: if it is, I'll be right.

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Speaker 4: Back and the store. Wory is is that I go

388
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Speaker 4: to Vegas and I take the tram, I get off

389
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Speaker 4: the plane, I have one hundred thousand dollars, and in

390
00:17:06,760 --> 00:17:08,119
Speaker 4: the article I wrote it, you have to do this

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Speaker 4: dance because you can't take over ten thousand dollars out

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Speaker 4: at each branch. So I had to drive around town

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Speaker 4: and ten branches to get ninety five hundred dollars out

394
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Speaker 4: of each one, which is like a water torture of

395
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Speaker 4: self like hate. I got all the money. I put

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Speaker 4: it in an old Puma bag. I'm on a flight

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Speaker 4: to Vegas with one hundred grand in cash and a

398
00:17:26,520 --> 00:17:29,520
Speaker 4: Puma bag, A little nervous, looking over my shoulders, hoping

399
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Speaker 4: I wasn't followed from the bank and I and I land,

400
00:17:32,080 --> 00:17:35,399
Speaker 4: and I go and get to the get to the

401
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Speaker 4: cab line, and I don't have the bag on me.

402
00:17:38,359 --> 00:17:39,159
Speaker 5: Ah.

403
00:17:39,320 --> 00:17:42,880
Speaker 4: I left the Puma bag on the tram. I literally

404
00:17:43,040 --> 00:17:48,199
Speaker 4: was so nervous. I left the Puma bag on the tram, expanded, sprinted.

405
00:17:48,640 --> 00:17:50,920
Speaker 5: I sprinted c nearly someone who's left a Puma bag

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Speaker 5: on a plane before?

407
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Speaker 6: Who among us?

408
00:17:54,480 --> 00:17:57,439
Speaker 4: And I sprinted and just sprinted through the airport to

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00:17:57,440 --> 00:18:01,400
Speaker 4: get back to that tram. And I remember going through

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00:18:01,400 --> 00:18:06,440
Speaker 4: that sprint and promising myself like this is a sign

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00:18:06,440 --> 00:18:08,359
Speaker 4: from God, like this is a sign from God. If

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00:18:08,400 --> 00:18:10,120
Speaker 4: I find this bag, if I can get this bag

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00:18:10,119 --> 00:18:11,840
Speaker 4: in my hand, I'm going back to l A and

414
00:18:11,880 --> 00:18:14,240
Speaker 4: I'm done. I'm done. And I did get back onto

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Speaker 4: the tram and the bag was just fucking sitting there

416
00:18:16,400 --> 00:18:19,840
Speaker 4: on the bedge can I say? And so there it was,

417
00:18:20,040 --> 00:18:22,160
Speaker 4: Thank God. And I went right to the casino and lost.

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Speaker 6: I'm guessing that promise felt true.

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00:18:26,680 --> 00:18:29,360
Speaker 4: Well, in three hours, I lost it the old fashioned way,

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Speaker 4: and not just the did you were you any.

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00:18:31,760 --> 00:18:33,840
Speaker 2: Moment in time or was it just straight down from there?

422
00:18:33,920 --> 00:18:36,480
Speaker 4: I don't even remember next time, but it's all it's

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00:18:36,520 --> 00:18:37,119
Speaker 4: all a blurn.

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00:18:38,560 --> 00:18:38,919
Speaker 6: That was.

425
00:18:39,080 --> 00:18:40,560
Speaker 4: That was one of many many stories.

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00:18:42,160 --> 00:18:42,800
Speaker 2: Another good one.

427
00:18:42,840 --> 00:18:46,159
Speaker 4: I'll tell you another one that I love. So I'm

428
00:18:46,600 --> 00:18:48,199
Speaker 4: by the way. I'm a screenwriter, so I work. I

429
00:18:48,200 --> 00:18:50,840
Speaker 4: work in Hollywood, and I I there's this.

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Speaker 6: I'll go quick.

431
00:18:51,560 --> 00:18:53,560
Speaker 4: But this is a two part story. The first one

432
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Speaker 4: was I had quit. I was in Gambler's Anonymous. I

433
00:18:56,520 --> 00:18:58,800
Speaker 4: was in recovery for about two or three years, and

434
00:18:58,840 --> 00:19:01,040
Speaker 4: I was just making it in Holly and getting successful

435
00:19:01,040 --> 00:19:03,119
Speaker 4: and finally making back all the money I had lost

436
00:19:03,119 --> 00:19:05,480
Speaker 4: in my life and feeling good about myself and a

437
00:19:05,640 --> 00:19:08,199
Speaker 4: Sony executive called me and said, I heard a rumor

438
00:19:08,240 --> 00:19:10,400
Speaker 4: that you are a composal gambler. So I'm very open

439
00:19:10,400 --> 00:19:12,800
Speaker 4: about this and proudly yeah, no problem. It's like, could

440
00:19:12,840 --> 00:19:15,720
Speaker 4: you would it be healthy or unhealthy for you to

441
00:19:15,720 --> 00:19:18,320
Speaker 4: write a movie based on this book Bringing down the House,

442
00:19:18,359 --> 00:19:21,080
Speaker 4: which we see as master ex book. We're going to

443
00:19:21,080 --> 00:19:23,080
Speaker 4: make it into a movie, and we have a draft.

444
00:19:23,080 --> 00:19:25,680
Speaker 4: It's not great. Could would you you know, would you

445
00:19:25,720 --> 00:19:27,080
Speaker 4: be interested? I don't know. I got to talk to

446
00:19:27,119 --> 00:19:30,359
Speaker 4: my mom and my therapist. I called my mom and

447
00:19:30,400 --> 00:19:33,160
Speaker 4: my therapist and they both said maybe. And I ended

448
00:19:33,240 --> 00:19:36,240
Speaker 4: up coming onto the movie and writing the movie and

449
00:19:37,040 --> 00:19:38,800
Speaker 4: the movie did well and it was all successful and

450
00:19:38,840 --> 00:19:40,000
Speaker 4: I didn't start gambling again.

451
00:19:40,440 --> 00:19:41,240
Speaker 2: What was that experience?

452
00:19:41,280 --> 00:19:43,880
Speaker 1: Like, just real quick with writing a movie about gambling

453
00:19:43,880 --> 00:19:45,280
Speaker 1: when you're in gamble is anonymous.

454
00:19:45,400 --> 00:19:47,200
Speaker 4: It was a luck because I was in Vegas for

455
00:19:47,240 --> 00:19:48,959
Speaker 4: a lot of part of that. So I'm right back

456
00:19:49,000 --> 00:19:51,399
Speaker 4: in the eye instead. But I'm doing I'm doing the

457
00:19:52,040 --> 00:19:55,080
Speaker 4: new Gamble my career, which is a healthier gambling.

458
00:19:55,400 --> 00:19:57,159
Speaker 2: Were there moments you were like I just want to

459
00:19:57,160 --> 00:19:57,720
Speaker 2: put twenty No.

460
00:19:57,920 --> 00:20:00,240
Speaker 4: I was really good, then really good. Then I many

461
00:20:00,320 --> 00:20:02,560
Speaker 4: relapses after that, but this is this was a good

462
00:20:02,600 --> 00:20:04,360
Speaker 4: period in my life. But anyways, I wrote the movie,

463
00:20:04,400 --> 00:20:05,080
Speaker 4: the movie did well.

464
00:20:05,359 --> 00:20:05,719
Speaker 2: Whatever.

465
00:20:06,560 --> 00:20:08,399
Speaker 3: By the way, Jeff Male worked for me at Twitter.

466
00:20:08,480 --> 00:20:10,480
Speaker 3: The student in them really h yeah, I.

467
00:20:10,440 --> 00:20:12,560
Speaker 2: Was that right from bringing down the House.

468
00:20:12,640 --> 00:20:13,560
Speaker 4: Yeah, it was his story.

469
00:20:13,600 --> 00:20:16,119
Speaker 6: Yeah, and what did he do it?

470
00:20:16,240 --> 00:20:18,880
Speaker 2: What did he do with Twitter gambling?

471
00:20:19,000 --> 00:20:22,520
Speaker 6: Insert insert joke care product manager.

472
00:20:24,440 --> 00:20:27,800
Speaker 4: But the end of the story is a few years later,

473
00:20:27,840 --> 00:20:29,760
Speaker 4: I did relapse. And it was on the super Bowl

474
00:20:29,800 --> 00:20:32,439
Speaker 4: against Denver in Carolina. It was I think it was

475
00:20:32,640 --> 00:20:37,320
Speaker 4: twenty fifteen, maybe, yeah, it was. And I called them

476
00:20:37,359 --> 00:20:39,240
Speaker 4: my bookie who I hadn't talked to in ten years

477
00:20:39,280 --> 00:20:40,880
Speaker 4: or whatever, and I see it's like, hey man, it's

478
00:20:40,880 --> 00:20:42,520
Speaker 4: been a long time. Like, can I just put down

479
00:20:42,720 --> 00:20:45,600
Speaker 4: one bet on this game? Seventy five? He said sure,

480
00:20:45,640 --> 00:20:47,720
Speaker 4: And I bet Denver And I was in New York

481
00:20:48,320 --> 00:20:51,040
Speaker 4: on Denver one and I had won seventy five thousand.

482
00:20:51,040 --> 00:20:52,119
Speaker 4: And I called him. I'm like, I'm not going to

483
00:20:52,160 --> 00:20:54,400
Speaker 4: be in LA for a few months. Maybe I'll get

484
00:20:54,440 --> 00:20:55,760
Speaker 4: someone to pick it up. He's like, dude, I'll fed

485
00:20:55,760 --> 00:20:58,400
Speaker 4: exit you. It's fine. It was ups or Ups two.

486
00:20:58,560 --> 00:21:00,240
Speaker 4: I go, are you are you seriously? Like do it

487
00:21:00,280 --> 00:21:03,520
Speaker 4: all the time, totally fine. And I was stupidly said yeah, okay,

488
00:21:04,040 --> 00:21:06,159
Speaker 4: and so he ups seventy five thousand dollars cashed me,

489
00:21:06,200 --> 00:21:08,360
Speaker 4: but it never came and so I had my assistant

490
00:21:09,160 --> 00:21:11,399
Speaker 4: track it down and she called me back. I'll never

491
00:21:11,440 --> 00:21:13,880
Speaker 4: forget this. And she called me back and she said, yeah,

492
00:21:13,880 --> 00:21:17,719
Speaker 4: I found it. It's the Louisville Police Department. And so

493
00:21:18,160 --> 00:21:19,760
Speaker 4: I called the book and I'm freaking out. I'm like,

494
00:21:19,760 --> 00:21:21,520
Speaker 4: they have it at the louis He's like, no worries,

495
00:21:21,560 --> 00:21:23,840
Speaker 4: I got a lawyer. This is fine. This is the deal.

496
00:21:24,640 --> 00:21:27,280
Speaker 4: You are a screenwriter, you are in film. He was

497
00:21:27,320 --> 00:21:31,040
Speaker 4: also a want to be filmmaker. He in finance with

498
00:21:31,560 --> 00:21:35,880
Speaker 4: his you know business, his bookie profits.

499
00:21:36,240 --> 00:21:37,160
Speaker 6: We call that laundry.

500
00:21:37,240 --> 00:21:40,840
Speaker 4: Yeah. I wonder if this could ever get me in trouble.

501
00:21:40,840 --> 00:21:45,320
Speaker 4: But anyways, he he said, don't worry. You consulted. This

502
00:21:45,440 --> 00:21:47,520
Speaker 4: is our story. You consulted on my new movie because

503
00:21:47,520 --> 00:21:50,280
Speaker 4: he made these low independent movies and I paid you cash.

504
00:21:50,440 --> 00:21:52,960
Speaker 4: It's legal to play someone in cash. And maybe we'll

505
00:21:53,000 --> 00:21:55,159
Speaker 4: have irs issues down the line, but we're fine. And

506
00:21:55,160 --> 00:21:57,000
Speaker 4: that's the lawyer, and I'll have the lawyer called the

507
00:21:57,040 --> 00:21:59,920
Speaker 4: Louisville Police Department. I was freaking out. I was literally

508
00:22:00,400 --> 00:22:02,280
Speaker 4: it's TMI. But I went for my apartment for a

509
00:22:02,280 --> 00:22:06,439
Speaker 4: way all the Viking in and so they he called me.

510
00:22:06,800 --> 00:22:09,600
Speaker 4: Uh the lawyer called me with him on the phone

511
00:22:09,640 --> 00:22:12,720
Speaker 4: and said, good good news. We're all set. We talked

512
00:22:12,720 --> 00:22:15,080
Speaker 4: to the Louisville Police Department. They do intercept cash, they

513
00:22:15,119 --> 00:22:18,119
Speaker 4: find sash, they have cash sniffing dogs, and it was

514
00:22:18,160 --> 00:22:22,000
Speaker 4: because of the kind of fentanyl and drug trade math trade.

515
00:22:22,200 --> 00:22:24,399
Speaker 4: But we told him our story. He was fine. But

516
00:22:24,440 --> 00:22:27,040
Speaker 4: the Louisville Police Department did ask could you send them

517
00:22:27,040 --> 00:22:29,240
Speaker 4: a sign poster for the movie twenty one out of

518
00:22:29,359 --> 00:22:32,600
Speaker 4: their favorite movie. So I did send it and I

519
00:22:32,600 --> 00:22:34,680
Speaker 4: got the money. They just shipped it along and I

520
00:22:34,720 --> 00:22:36,520
Speaker 4: got the money, and I think it's probably maybe that

521
00:22:36,560 --> 00:22:38,879
Speaker 4: poster is still hanging out in the Louisville.

522
00:22:38,480 --> 00:22:40,679
Speaker 5: Police depart Louisville Police I haven't been in a while, so.

523
00:22:41,520 --> 00:22:43,680
Speaker 3: That my question is where can I get a cash

524
00:22:43,720 --> 00:22:48,760
Speaker 3: sniffing dog? That was my takeaway from story. Wait did

525
00:22:48,880 --> 00:22:49,280
Speaker 3: make those?

526
00:22:49,359 --> 00:22:50,159
Speaker 6: They make those?

527
00:22:50,680 --> 00:22:51,320
Speaker 5: What do they cost?

528
00:22:51,400 --> 00:22:53,480
Speaker 3: Going to go back and hold a hundred dollar bill

529
00:22:53,560 --> 00:22:55,160
Speaker 3: under my Australian shepherd's nose?

530
00:22:55,320 --> 00:22:57,400
Speaker 5: Like it's gotta be that they're like more the money

531
00:22:57,440 --> 00:22:59,320
Speaker 5: is like drug. It isn't that the deal. Like I

532
00:22:59,400 --> 00:23:01,680
Speaker 5: remember about this once, not to go totally down the

533
00:23:01,760 --> 00:23:05,040
Speaker 5: drug sniffing dog rattle, but I remember reading somewhere was because.

534
00:23:04,840 --> 00:23:06,960
Speaker 6: The course you read about dogs, it.

535
00:23:06,840 --> 00:23:09,200
Speaker 5: Was like, the money is in close proximity.

536
00:23:08,640 --> 00:23:09,479
Speaker 6: To drug drugs.

537
00:23:10,200 --> 00:23:12,880
Speaker 4: Almost all bills you have a trace of drugs on them,

538
00:23:12,960 --> 00:23:13,720
Speaker 4: and that's how they.

539
00:23:13,640 --> 00:23:15,720
Speaker 6: Find amazing amazing.

540
00:23:16,119 --> 00:23:19,280
Speaker 3: That's the old, the old Chris rock line. Nope, wire

541
00:23:19,359 --> 00:23:21,680
Speaker 3: ATMs open at three am. No one ever took out

542
00:23:21,720 --> 00:23:24,000
Speaker 3: four hundred dollars three am for a good reason.

543
00:23:26,080 --> 00:23:26,720
Speaker 5: This is true.

544
00:23:26,960 --> 00:23:29,720
Speaker 3: I have a I have a prediction markets hypothesis or

545
00:23:29,960 --> 00:23:33,840
Speaker 3: actually theoretical question. This is this is obviously silly. But

546
00:23:34,680 --> 00:23:39,040
Speaker 3: if you're I don't know Elon Musk, Jeff Bezos, Tim Cook, whoever,

547
00:23:39,480 --> 00:23:41,200
Speaker 3: and you've got all these security guys and you're worried

548
00:23:41,200 --> 00:23:43,800
Speaker 3: about you know, people coming after you or you know,

549
00:23:44,880 --> 00:23:48,600
Speaker 3: crazy people attacking you, it seems to me you could

550
00:23:49,160 --> 00:23:53,560
Speaker 3: you could create a market where you you took the

551
00:23:53,760 --> 00:23:57,600
Speaker 3: no side of the bet, yes no of will I

552
00:23:57,760 --> 00:24:01,240
Speaker 3: live to be more than eighty five? And it's basically

553
00:24:01,359 --> 00:24:04,159
Speaker 3: free money for anyone who takes the yes side of

554
00:24:04,160 --> 00:24:05,479
Speaker 3: the bet, and those people are going to come out

555
00:24:05,520 --> 00:24:06,600
Speaker 3: and protect you themselves.

556
00:24:06,800 --> 00:24:07,159
Speaker 6: That's right.

557
00:24:07,240 --> 00:24:10,080
Speaker 5: And make sure it's like the opposite of credit default swaps,

558
00:24:10,359 --> 00:24:12,760
Speaker 5: Like instead of buying insurance on other people's houses, I'm

559
00:24:12,800 --> 00:24:20,479
Speaker 5: buying like like save, I'm shorting my life with a ridiculous.

560
00:24:19,920 --> 00:24:21,600
Speaker 6: Amount of money for my own benefit.

561
00:24:21,680 --> 00:24:23,680
Speaker 3: That's right, because everybody on the other side of the

562
00:24:23,720 --> 00:24:25,280
Speaker 3: trends can be like, I got to make sure nothing

563
00:24:25,320 --> 00:24:26,280
Speaker 3: happens to along.

564
00:24:26,240 --> 00:24:28,720
Speaker 4: On security, a lot on security.

565
00:24:28,960 --> 00:24:32,960
Speaker 6: Yeah, security, he's got to live, right.

566
00:24:33,160 --> 00:24:35,280
Speaker 2: You don't do any of the any of that betting

567
00:24:35,320 --> 00:24:36,480
Speaker 2: that you do the sports stuff.

568
00:24:36,560 --> 00:24:39,199
Speaker 4: What do you I like sports. I'm a fan of

569
00:24:39,480 --> 00:24:41,680
Speaker 4: you doing the online sports. I don't know. I don't

570
00:24:41,760 --> 00:24:46,160
Speaker 4: I don't bet game to game anymore. I do dabble

571
00:24:46,200 --> 00:24:48,639
Speaker 4: in something called the Super Contest, which is at the

572
00:24:48,720 --> 00:24:51,040
Speaker 4: beginning of I love football. Football betting was my thing.

573
00:24:51,200 --> 00:24:53,879
Speaker 4: The Super Contest is, uh, you go to Vegas in

574
00:24:54,600 --> 00:24:57,680
Speaker 4: August before the season, and you pay it's not much,

575
00:24:57,720 --> 00:25:00,320
Speaker 4: it's two thousand dollars and you're in a con test

576
00:25:00,400 --> 00:25:02,880
Speaker 4: with a lot of other handicappers and the winner gets

577
00:25:02,880 --> 00:25:05,800
Speaker 4: a million dollars and the Lost twenty thirty people can

578
00:25:05,840 --> 00:25:07,440
Speaker 4: make you know, and it's just fun. It gives me

579
00:25:07,480 --> 00:25:09,080
Speaker 4: the whole season without going game to game. When I

580
00:25:09,160 --> 00:25:11,240
Speaker 4: went game to game, I went crazy. This is my

581
00:25:11,480 --> 00:25:13,800
Speaker 4: methodone to a heroin addict. You know what I'm saying?

582
00:25:14,000 --> 00:25:16,359
Speaker 5: Yeah, can I just go backwards weekend for a second.

583
00:25:16,400 --> 00:25:17,760
Speaker 5: One of the other things I was thinking about this

584
00:25:17,800 --> 00:25:21,040
Speaker 5: when we were going to do this episode that years ago.

585
00:25:21,080 --> 00:25:23,000
Speaker 5: I remember reading I Forget where it was. It was

586
00:25:23,040 --> 00:25:25,600
Speaker 5: like a history of gambling in America. And what's really

587
00:25:25,600 --> 00:25:28,880
Speaker 5: interesting is like it's basically there from the beginning right.

588
00:25:28,920 --> 00:25:33,160
Speaker 5: It's unlike almost any other country on Earth. In the

589
00:25:33,160 --> 00:25:37,200
Speaker 5: there's a great line what's his name, the Tokeville the

590
00:25:37,240 --> 00:25:39,600
Speaker 5: Democracy in America, Alexis jog He had a great line

591
00:25:39,640 --> 00:25:43,560
Speaker 5: where he talked about the feverish ardor with which Americans

592
00:25:43,560 --> 00:25:46,400
Speaker 5: approached anything that might help them get rich quick. And

593
00:25:46,680 --> 00:25:49,040
Speaker 5: it was so alien to him coming from France because

594
00:25:49,080 --> 00:25:51,239
Speaker 5: he was a French philosopher and sociologist, and he came

595
00:25:51,240 --> 00:25:53,560
Speaker 5: over and was writing about this feverish ardor. And not

596
00:25:53,600 --> 00:25:56,320
Speaker 5: only that this idea. The other thing that he commented on,

597
00:25:56,359 --> 00:25:58,440
Speaker 5: and this is in eighteen seventy, so you know it's

598
00:25:59,000 --> 00:26:02,600
Speaker 5: before Instagram, well before Instagram and well before daily Fantasy Sports.

599
00:26:02,800 --> 00:26:05,040
Speaker 5: And the other thing you talked about was this, I

600
00:26:05,040 --> 00:26:07,560
Speaker 5: forget the exact word, something like this shadowy suspicion or

601
00:26:07,600 --> 00:26:09,680
Speaker 5: something like that, that there might be a better way

602
00:26:09,720 --> 00:26:12,720
Speaker 5: to get rich quick. That that was fundamental to understanding Americans,

603
00:26:12,760 --> 00:26:15,199
Speaker 5: like I'm trying to get rich quick, but I have

604
00:26:15,200 --> 00:26:17,080
Speaker 5: a hunch there's an even better way, and there's this

605
00:26:17,320 --> 00:26:19,720
Speaker 5: constant suspicion that they may be able to find an

606
00:26:19,720 --> 00:26:21,560
Speaker 5: even better way. And the talk Villa used that as

607
00:26:21,560 --> 00:26:23,680
Speaker 5: a way of trying to explain the American psyche, that

608
00:26:23,720 --> 00:26:27,040
Speaker 5: this is uniquely American and he wasn't necessarily making his things,

609
00:26:27,040 --> 00:26:29,359
Speaker 5: and therefore they're all really bad people. It was just

610
00:26:29,760 --> 00:26:33,040
Speaker 5: almost in a descriptive way, you need to understand this

611
00:26:33,400 --> 00:26:35,800
Speaker 5: to understand the American psyche. So that's the one point.

612
00:26:35,840 --> 00:26:37,399
Speaker 5: So that's been there since the beginning. The thing that

613
00:26:37,440 --> 00:26:41,200
Speaker 5: I think is really interesting now, though, is that there's

614
00:26:41,240 --> 00:26:44,960
Speaker 5: all kinds of recent work showing how as it becomes

615
00:26:45,119 --> 00:26:48,280
Speaker 5: less predictable, how you will make a living. So as countries,

616
00:26:48,400 --> 00:26:50,119
Speaker 5: for example, there's all these studies out in the showing

617
00:26:50,119 --> 00:26:52,719
Speaker 5: that people in general don't feel like their kids will

618
00:26:52,760 --> 00:26:54,320
Speaker 5: have a better life than they did. There's lots of

619
00:26:54,359 --> 00:26:56,159
Speaker 5: this sort of data out there from Pew and others,

620
00:26:56,200 --> 00:26:58,320
Speaker 5: from AI and all the all the things going on,

621
00:26:58,440 --> 00:27:02,280
Speaker 5: political of people, whatever else that when that happens in

622
00:27:02,320 --> 00:27:06,040
Speaker 5: a country, people generally become much more short term look

623
00:27:06,080 --> 00:27:08,600
Speaker 5: for much more speculative ways to make money. This all

624
00:27:08,640 --> 00:27:10,720
Speaker 5: feeds into this. So the interesting thing in America is

625
00:27:11,000 --> 00:27:13,800
Speaker 5: at the US is it's at the intersection of those

626
00:27:13,800 --> 00:27:17,720
Speaker 5: two forces. You get a country founded on gambling that

627
00:27:17,800 --> 00:27:20,119
Speaker 5: will goes sort of the worlds lurching into a moment

628
00:27:20,400 --> 00:27:23,520
Speaker 5: where suddenly there's this kind of almost implicit pressure because

629
00:27:23,560 --> 00:27:26,080
Speaker 5: I feel like I don't know what my economic livelihood

630
00:27:26,119 --> 00:27:27,679
Speaker 5: is going to look like, you know, I don't know

631
00:27:27,680 --> 00:27:29,399
Speaker 5: that it's going to be gigwork or this or that

632
00:27:29,520 --> 00:27:31,959
Speaker 5: or the other thing, and that people in general then

633
00:27:32,040 --> 00:27:35,560
Speaker 5: ten become much more focused on these speculative games. So

634
00:27:35,680 --> 00:27:38,160
Speaker 5: that's I think underneath all of this, there's these two

635
00:27:38,160 --> 00:27:39,280
Speaker 5: really interesting forces.

636
00:27:39,440 --> 00:27:46,120
Speaker 3: I one hundred percent agree with your hypothesis that as

637
00:27:46,359 --> 00:27:50,280
Speaker 3: AI causes people to be more and more concerned about

638
00:27:50,359 --> 00:27:54,880
Speaker 3: job safety, the participation and lottery style activities like this

639
00:27:55,000 --> 00:27:56,040
Speaker 3: will only increase.

640
00:27:56,240 --> 00:27:59,080
Speaker 5: Yeah, And it's once you sort of turn it around

641
00:27:59,160 --> 00:28:02,159
Speaker 5: and think about those as the pressures, the force is

642
00:28:02,200 --> 00:28:04,680
Speaker 5: pushing this forward. It's not just that this is a novelty.

643
00:28:05,160 --> 00:28:07,879
Speaker 5: It's a it's almost people almost feel like it's a

644
00:28:07,880 --> 00:28:11,600
Speaker 5: compulsion driven by the changing economic livelihood, but also because

645
00:28:11,640 --> 00:28:14,400
Speaker 5: of this unique nature of the American psyche that we're

646
00:28:14,440 --> 00:28:16,160
Speaker 5: just there's a bunch of riverboat gamblers.

647
00:28:16,760 --> 00:28:18,400
Speaker 4: It's always been like that. That's right, I mean, that's

648
00:28:18,440 --> 00:28:22,200
Speaker 4: what this country and that his created spurred innovation, and

649
00:28:22,640 --> 00:28:25,040
Speaker 4: why we are, you know, the leading country and innovation.

650
00:28:25,400 --> 00:28:25,640
Speaker 6: Right.

651
00:28:25,760 --> 00:28:27,600
Speaker 5: So those but those two things together, I just think

652
00:28:27,680 --> 00:28:29,560
Speaker 5: sometimes people get crapping the idea of oh, it's just

653
00:28:29,560 --> 00:28:32,640
Speaker 5: another novelty. No, no, no, this is a novelty. It's

654
00:28:32,720 --> 00:28:36,000
Speaker 5: arrived at a moment and implanted itself on a population

655
00:28:36,080 --> 00:28:38,040
Speaker 5: of people who who could be not who could not

656
00:28:38,080 --> 00:28:39,479
Speaker 5: be more susceptible.

657
00:28:38,920 --> 00:28:39,479
Speaker 6: To the virus.

658
00:28:40,160 --> 00:28:40,760
Speaker 2: It's interesting.

659
00:28:40,840 --> 00:28:44,040
Speaker 1: I've been working on this project about gambling and Hawaii

660
00:28:44,080 --> 00:28:47,040
Speaker 1: and all the crime there in the nineteen sixties and seventies,

661
00:28:47,040 --> 00:28:47,680
Speaker 1: and the part.

662
00:28:47,560 --> 00:28:50,960
Speaker 6: If you're going to use this time, actually have to

663
00:28:50,960 --> 00:28:53,680
Speaker 6: pay for advertising. That's exactly right. You don't get a

664
00:28:53,720 --> 00:28:54,000
Speaker 6: deal here.

665
00:28:54,080 --> 00:28:54,280
Speaker 5: Yeah.

666
00:28:54,320 --> 00:28:58,760
Speaker 1: But what's interesting is I couldn't there was they made millions,

667
00:28:58,840 --> 00:29:00,920
Speaker 1: I mean in the sixties and seven, these millions back

668
00:29:00,960 --> 00:29:04,200
Speaker 1: then on all the gambling. And I couldn't understand why

669
00:29:04,240 --> 00:29:07,480
Speaker 1: these people would work, you know, as laborers in the

670
00:29:07,520 --> 00:29:09,800
Speaker 1: fields all day and then go spend it all night

671
00:29:09,960 --> 00:29:11,800
Speaker 1: on the chicken fights and so on, and.

672
00:29:11,880 --> 00:29:13,520
Speaker 5: That what they were gambling on was chicken fights.

673
00:29:13,560 --> 00:29:15,600
Speaker 2: Oh, the chicken fight. Well everything chicken fights.

674
00:29:15,640 --> 00:29:19,440
Speaker 1: There were lots of Asian games that they brought over

675
00:29:19,480 --> 00:29:22,360
Speaker 1: from Japan and Korea and whatnot. But there was someone

676
00:29:22,400 --> 00:29:26,240
Speaker 1: that told us that it was literally like the same

677
00:29:26,280 --> 00:29:29,200
Speaker 1: thing as you're saying. It's like they they were making

678
00:29:29,280 --> 00:29:31,479
Speaker 1: such a little amount of money, they saw this as

679
00:29:31,520 --> 00:29:33,120
Speaker 1: an opportunity to this was it.

680
00:29:33,200 --> 00:29:34,360
Speaker 2: This is how they would get out.

681
00:29:34,200 --> 00:29:34,520
Speaker 6: Of it all.

682
00:29:34,760 --> 00:29:36,800
Speaker 2: And every week they would take their money and they

683
00:29:36,840 --> 00:29:37,520
Speaker 2: would waste it.

684
00:29:37,960 --> 00:29:40,520
Speaker 4: But I would argue that if any of them won big,

685
00:29:41,240 --> 00:29:43,880
Speaker 4: they didn't just stop gambling, And they didn't just you know,

686
00:29:44,040 --> 00:29:46,080
Speaker 4: of course, oh I got there, We're done. So i'd

687
00:29:46,080 --> 00:29:49,120
Speaker 4: see old everybody who you know, these numbers of who

688
00:29:49,160 --> 00:29:51,280
Speaker 4: wins the lottery in What happens to them after they

689
00:29:51,320 --> 00:29:54,000
Speaker 4: win the lotteries? Is many go bankrupt.

690
00:29:54,080 --> 00:29:56,920
Speaker 5: Yeah, it's horrifying, not just because they got bad advice either.

691
00:29:57,360 --> 00:29:58,160
Speaker 2: What do you what do you.

692
00:29:58,080 --> 00:30:01,000
Speaker 1: Think is the psychology of so You've worked on the

693
00:30:01,120 --> 00:30:04,000
Speaker 1: Chicago Stock Exchange, Sorry, dick.

694
00:30:04,080 --> 00:30:04,960
Speaker 6: Uh it's.

695
00:30:06,400 --> 00:30:11,720
Speaker 3: Whatever it's called something, just say Chicago Trade.

696
00:30:11,960 --> 00:30:13,360
Speaker 2: And you've worked in gambling.

697
00:30:13,360 --> 00:30:17,000
Speaker 1: You've written movies Bull Street two twenty one, you've written

698
00:30:17,000 --> 00:30:20,040
Speaker 1: all like It's all in it kind of is encompassed

699
00:30:20,040 --> 00:30:24,200
Speaker 1: in there's a rubric under it. What is the psychology

700
00:30:24,440 --> 00:30:28,080
Speaker 1: of these people that where the overlap is Is it

701
00:30:28,120 --> 00:30:31,960
Speaker 1: about winning like this I have to win? Or is

702
00:30:32,000 --> 00:30:34,960
Speaker 1: it about the Is it the excitement of the I

703
00:30:35,000 --> 00:30:35,720
Speaker 1: got to speak.

704
00:30:35,480 --> 00:30:39,400
Speaker 4: For myself, and probably it would. It would also, you know,

705
00:30:39,440 --> 00:30:42,080
Speaker 4: translate to many others who are interested in gambling and

706
00:30:42,120 --> 00:30:45,400
Speaker 4: these things. I think it's it's the chaos, controlling and

707
00:30:45,400 --> 00:30:49,440
Speaker 4: a chaos, you know, flirting with randomness or trying to

708
00:30:49,720 --> 00:30:53,800
Speaker 4: tame randomness, domesticate randomness. We all live, we all are

709
00:30:53,840 --> 00:30:55,760
Speaker 4: out of control at all times. We have no control

710
00:30:55,760 --> 00:30:58,840
Speaker 4: over our outcomes, and the risks are terrifying, and I

711
00:30:58,840 --> 00:31:03,120
Speaker 4: think it is a way to try to manage the

712
00:31:03,200 --> 00:31:07,880
Speaker 4: vulnerabilities of life psychologically, and you feel like if you

713
00:31:07,960 --> 00:31:09,560
Speaker 4: win the big bed, or if you bet you know,

714
00:31:09,640 --> 00:31:12,240
Speaker 4: you bet, you put a lot of money into the

715
00:31:12,280 --> 00:31:15,400
Speaker 4: stock that ends up exploding because of the reason you

716
00:31:15,400 --> 00:31:17,680
Speaker 4: thought it would explode. Suddenly you can control the universe.

717
00:31:17,720 --> 00:31:20,520
Speaker 4: You can maybe stave off death. Somewhere in the back

718
00:31:20,560 --> 00:31:23,720
Speaker 4: of your head. I think that's the psychology that I

719
00:31:24,320 --> 00:31:27,520
Speaker 4: that's interesting. Yeah, it's like existential dread as profit driver.

720
00:31:27,720 --> 00:31:31,200
Speaker 2: Yea, that is right.

721
00:31:32,080 --> 00:31:33,800
Speaker 4: I mean that's been for me, and I think that's

722
00:31:33,840 --> 00:31:55,960
Speaker 4: probably for many.

723
00:31:56,640 --> 00:32:01,240
Speaker 5: There's these truly mispriced market since so you say to yourself,

724
00:32:01,880 --> 00:32:05,040
Speaker 5: as the suspicion is that, well, does that mean that

725
00:32:05,240 --> 00:32:07,520
Speaker 5: someone on the inside knows something right? That can't be

726
00:32:07,560 --> 00:32:10,040
Speaker 5: true because in this case, you know, it seems awfully

727
00:32:10,040 --> 00:32:11,600
Speaker 5: wired in that this is going to be the outcome.

728
00:32:11,640 --> 00:32:13,360
Speaker 5: So I don't think that's the case. Is it that

729
00:32:13,400 --> 00:32:15,480
Speaker 5: it's thin? That the market's really thin? And so it's

730
00:32:15,520 --> 00:32:17,360
Speaker 5: it's I liquid, It gets moved around by a cup,

731
00:32:17,440 --> 00:32:19,360
Speaker 5: just a couple of people who are playing and the

732
00:32:19,400 --> 00:32:20,960
Speaker 5: other one is and this is we just ran into

733
00:32:20,960 --> 00:32:22,680
Speaker 5: this and this is a really awful example. But with

734
00:32:22,720 --> 00:32:26,520
Speaker 5: the respect to the US action in Venezuela, that there

735
00:32:26,560 --> 00:32:28,480
Speaker 5: was a market I think it was on Kelshi, was

736
00:32:28,520 --> 00:32:30,560
Speaker 5: it on calshi Er probably market, and was on one

737
00:32:30,600 --> 00:32:33,560
Speaker 5: of them, and it didn't initially pay off despite the

738
00:32:33,680 --> 00:32:36,520
Speaker 5: US taking action and toppling the leader in Venezuela. And

739
00:32:36,560 --> 00:32:38,960
Speaker 5: it's set and that this was specific. The market wasn't

740
00:32:39,240 --> 00:32:42,080
Speaker 5: on you know, January the seventh, at seven pm. It

741
00:32:42,120 --> 00:32:43,920
Speaker 5: was not nothing so specific. It just said that the

742
00:32:44,000 --> 00:32:46,800
Speaker 5: US would take military action. And so I think one

743
00:32:46,800 --> 00:32:49,200
Speaker 5: of the reasons why there's this uneasiness with some of

744
00:32:49,240 --> 00:32:50,600
Speaker 5: these markets is that, well.

745
00:32:50,440 --> 00:32:51,760
Speaker 2: What do you mean it didn't pay off? They didn't

746
00:32:51,760 --> 00:32:52,040
Speaker 2: pay them.

747
00:32:52,080 --> 00:32:54,360
Speaker 3: They said that wasn't that wasn't that's not the you know,

748
00:32:54,520 --> 00:32:57,280
Speaker 3: there's a's a Remember it's always a binary yes or no.

749
00:32:57,480 --> 00:33:00,600
Speaker 3: This happened yes or no, And the descript of a

750
00:33:00,800 --> 00:33:04,120
Speaker 3: yes was more vague than just we went and got Madura.

751
00:33:04,240 --> 00:33:05,920
Speaker 6: It was something like, we're at war with men.

752
00:33:06,400 --> 00:33:09,600
Speaker 3: War within the prediction market said, well, we're not really

753
00:33:09,640 --> 00:33:10,600
Speaker 3: at war with men available.

754
00:33:10,600 --> 00:33:12,400
Speaker 5: We just went in and the US hasn't declared war

755
00:33:12,440 --> 00:33:13,720
Speaker 5: on anyone. It's a bit at war with for an

756
00:33:13,720 --> 00:33:15,400
Speaker 5: awfully long time. So this is this is a bit

757
00:33:15,400 --> 00:33:17,320
Speaker 5: of a problem. Just definitionally, right, we just.

758
00:33:17,280 --> 00:33:17,720
Speaker 6: Go to war.

759
00:33:17,800 --> 00:33:22,480
Speaker 3: Yeah, Congress actually hasn't declared war. This is more to

760
00:33:22,560 --> 00:33:25,040
Speaker 3: have twenty thousand soldiers over there. This is just a

761
00:33:25,120 --> 00:33:27,280
Speaker 3: mild disfavor. We're not actually at war here.

762
00:33:27,880 --> 00:33:30,000
Speaker 5: Okay. So anyway, so this idea I think that also

763
00:33:30,080 --> 00:33:34,160
Speaker 5: creates this mispricing is this will this really resolve because

764
00:33:34,200 --> 00:33:36,000
Speaker 5: it's written in a way that suggests there's a couple

765
00:33:36,000 --> 00:33:37,880
Speaker 5: of ways this could pan out, and so anyway, so

766
00:33:37,920 --> 00:33:39,920
Speaker 5: there's all of these things that make and this goes

767
00:33:39,960 --> 00:33:42,520
Speaker 5: back to your point earlier about the absence of regulation

768
00:33:42,600 --> 00:33:45,120
Speaker 5: and everything else, that there's this sense that the market

769
00:33:45,200 --> 00:33:48,040
Speaker 5: makers could resolve this in a way that hurts people,

770
00:33:48,080 --> 00:33:50,240
Speaker 5: even if the outcome is obvious that this should have

771
00:33:50,240 --> 00:33:50,600
Speaker 5: paid off.

772
00:33:50,720 --> 00:33:52,800
Speaker 3: But let's let's talk about the market makers for a second,

773
00:33:52,800 --> 00:33:54,760
Speaker 3: because I think one of the things that people don't

774
00:33:54,800 --> 00:33:59,000
Speaker 3: realize about these prediction markets is in many cases you

775
00:33:59,160 --> 00:34:02,680
Speaker 3: have huge hedge funds like Susquehanna who's now literally going

776
00:34:02,760 --> 00:34:05,040
Speaker 3: to go create one with Robinhood, or it has created

777
00:34:05,040 --> 00:34:09,040
Speaker 3: one with Robinhood, who are thirty percent of the market

778
00:34:09,080 --> 00:34:12,799
Speaker 3: make of the market making in Calci and polymarkets, and

779
00:34:13,400 --> 00:34:16,920
Speaker 3: they have an enormous information advantage over Nick Bilton.

780
00:34:17,520 --> 00:34:19,960
Speaker 6: So when you're you know, when you're.

781
00:34:19,800 --> 00:34:23,359
Speaker 3: Placing money, you know on a yes, no proposition of

782
00:34:23,400 --> 00:34:26,520
Speaker 3: any sort on one of these prediction markets. Just in

783
00:34:26,520 --> 00:34:28,640
Speaker 3: the back of your mind, understand there are.

784
00:34:28,880 --> 00:34:32,840
Speaker 1: Multif they're running like their quants and everything and figuring

785
00:34:32,880 --> 00:34:34,840
Speaker 1: it all out, then they're placing the bets and they're

786
00:34:34,840 --> 00:34:35,440
Speaker 1: making the market.

787
00:34:35,520 --> 00:34:36,440
Speaker 6: No, they're making the markets.

788
00:34:36,480 --> 00:34:38,680
Speaker 5: They're buying and selling on both sides, and so they're

789
00:34:38,719 --> 00:34:40,920
Speaker 5: able to make the money through the both through the

790
00:34:40,960 --> 00:34:43,840
Speaker 5: exchange and by taking directional like direct positions. But the

791
00:34:43,880 --> 00:34:46,000
Speaker 5: idea that some people have this naive idea, just like

792
00:34:46,000 --> 00:34:48,240
Speaker 5: in the stock market, they have this idea, naive idea

793
00:34:48,320 --> 00:34:50,480
Speaker 5: that oh, it's just a bunch of other people like

794
00:34:50,520 --> 00:34:52,719
Speaker 5: me on the other side. You know, it's not right,

795
00:34:52,760 --> 00:34:56,719
Speaker 5: it's not. And in equity markets it's mostly algorithms. Right,

796
00:34:56,760 --> 00:34:59,200
Speaker 5: betther than seventy percent of the volume on equity markets

797
00:34:59,480 --> 00:35:02,000
Speaker 5: is algorith they're not taking your feelings into account.

798
00:35:02,520 --> 00:35:03,240
Speaker 6: Just spoiler.

799
00:35:03,600 --> 00:35:06,280
Speaker 5: And it's the exact same thing on prediction markets. Increasingly

800
00:35:06,280 --> 00:35:09,560
Speaker 5: that it's not in any liquid market, it's not your

801
00:35:09,680 --> 00:35:12,440
Speaker 5: peers who are alter reading madly with you. It's Jane Street,

802
00:35:12,600 --> 00:35:15,960
Speaker 5: It's Esquehanna, It's they're they're taking the other.

803
00:35:15,800 --> 00:35:17,319
Speaker 4: Side of the house is always going to be there.

804
00:35:17,520 --> 00:35:20,560
Speaker 4: If there's action, there's the house, right and in the

805
00:35:20,760 --> 00:35:24,200
Speaker 4: house wins always, which is why they have those nice buildings.

806
00:35:26,560 --> 00:35:28,719
Speaker 4: It's like your law, your favorite law of herb. It's like,

807
00:35:28,760 --> 00:35:30,600
Speaker 4: my god, they have nice ears. This Mike God, I

808
00:35:30,640 --> 00:35:33,240
Speaker 4: paid a lot for this. Run's the exact same phenomenon

809
00:35:33,520 --> 00:35:38,399
Speaker 4: with poly Market and Kelsey. I've not engaged on it

810
00:35:38,480 --> 00:35:42,680
Speaker 4: because it doesn't interest me. Why because I'm not for me.

811
00:35:42,760 --> 00:35:45,680
Speaker 4: It's if I'm gonna, you know, have an opinion, it's

812
00:35:45,719 --> 00:35:49,000
Speaker 4: going to be more within the equities markets. It's a bigger,

813
00:35:49,160 --> 00:35:52,160
Speaker 4: better market, bigger, better, more liquid. Yeah, And I'm not

814
00:35:52,200 --> 00:35:54,520
Speaker 4: interested in betting on who's going to win the president

815
00:35:54,600 --> 00:35:56,319
Speaker 4: to see or any of these things.

816
00:35:56,440 --> 00:35:58,759
Speaker 5: The thing that I find interesting about these things now though,

817
00:35:58,920 --> 00:36:00,880
Speaker 5: is that, and this is something that I think in

818
00:36:00,920 --> 00:36:04,440
Speaker 5: some ways people take too seriously, is that the prediction

819
00:36:04,560 --> 00:36:07,480
Speaker 5: markets become the thing that affects the outcome. So you'll

820
00:36:07,480 --> 00:36:09,960
Speaker 5: see them sided in newspaper articles increasingly.

821
00:36:10,520 --> 00:36:13,680
Speaker 1: Yeah, I've noticed that it's funny It's like I remember

822
00:36:13,719 --> 00:36:15,759
Speaker 1: in the when I was the New York Times in

823
00:36:15,800 --> 00:36:18,839
Speaker 1: like two thousand and twelve, and you know, it used

824
00:36:18,880 --> 00:36:20,440
Speaker 1: to be so and so on the streets said da

825
00:36:20,520 --> 00:36:24,000
Speaker 1: da da, And then around twenty fifteen it was so

826
00:36:24,040 --> 00:36:27,480
Speaker 1: and so on Twitter SAIDA da da, And now it's

827
00:36:27,520 --> 00:36:30,160
Speaker 1: the prediction markets. They're like the prediction market. It's like

828
00:36:30,239 --> 00:36:32,520
Speaker 1: that's become the new voice on the street.

829
00:36:32,800 --> 00:36:33,000
Speaker 6: Right.

830
00:36:33,040 --> 00:36:36,480
Speaker 5: And then that's inherently circular, right, because if I know,

831
00:36:36,760 --> 00:36:38,879
Speaker 5: and if it's a market that I can influence. By

832
00:36:38,920 --> 00:36:41,960
Speaker 5: influencing the market, I influence what people think is likely

833
00:36:42,000 --> 00:36:44,680
Speaker 5: to happen, and that in turn becomes the revealed truth

834
00:36:44,719 --> 00:36:46,279
Speaker 5: of what's likely to happen. Right, So it goes.

835
00:36:46,320 --> 00:36:48,320
Speaker 6: It's round and round in literally.

836
00:36:49,120 --> 00:36:53,520
Speaker 3: The canonical example is, well, you know, if you look

837
00:36:53,560 --> 00:36:57,080
Speaker 3: at polymarkets, a Gavin newsom only as a twenty percent

838
00:36:57,160 --> 00:37:00,000
Speaker 3: chance of winning, like this is, and then the news

839
00:37:00,160 --> 00:37:02,560
Speaker 3: article quotes that as what's the likely outcome?

840
00:37:02,640 --> 00:37:05,840
Speaker 6: Like that's not that's just what a bunch of people think.

841
00:37:05,840 --> 00:37:07,680
Speaker 5: Who are motiv who not only just about a bunch

842
00:37:07,680 --> 00:37:09,120
Speaker 5: of people think, but a bunch of people who are

843
00:37:09,160 --> 00:37:11,160
Speaker 5: so passionate about this that they feel like it's a

844
00:37:11,200 --> 00:37:13,160
Speaker 5: good use of their time to better market.

845
00:37:13,320 --> 00:37:15,160
Speaker 4: So that's why I ask you about the liquidity, because

846
00:37:15,160 --> 00:37:17,040
Speaker 4: I think it we're a highly liquid market. I would

847
00:37:17,080 --> 00:37:20,239
Speaker 4: think that that information is much more reliable because there

848
00:37:20,280 --> 00:37:22,200
Speaker 4: will be someone in the market who knows.

849
00:37:22,080 --> 00:37:24,200
Speaker 5: So that almost all of these markets are not liquid

850
00:37:24,280 --> 00:37:26,120
Speaker 5: enough for that to be the case, and in particular

851
00:37:26,160 --> 00:37:28,920
Speaker 5: the ones that are political bring in this kind of partisanship.

852
00:37:28,920 --> 00:37:32,080
Speaker 5: Further were of course I I this guy you know,

853
00:37:32,120 --> 00:37:34,439
Speaker 5: knew Some's a good example is he has zero percent

854
00:37:34,520 --> 00:37:35,719
Speaker 5: chance and when I'm gonna take the other side of

855
00:37:35,719 --> 00:37:37,440
Speaker 5: this all day long, drive down the price and so on.

856
00:37:37,680 --> 00:37:40,680
Speaker 5: And they there's a method into what they're doing in

857
00:37:40,760 --> 00:37:43,360
Speaker 5: terms of trying to influence, and then in turn becomes

858
00:37:43,360 --> 00:37:45,560
Speaker 5: a self fulfilling becomes a self fulillming prophecy, and then

859
00:37:45,680 --> 00:37:48,440
Speaker 5: become cided as if it's reflective, as if it's like

860
00:37:48,480 --> 00:37:51,040
Speaker 5: a pewpole of something that's going on out there in

861
00:37:51,040 --> 00:37:54,200
Speaker 5: the world, and it's not. It's just a motivated participants

862
00:37:54,239 --> 00:37:55,239
Speaker 5: in a thinly traded market.

863
00:37:55,480 --> 00:37:58,560
Speaker 1: You madd A, When you look at sports bets, do

864
00:37:58,640 --> 00:38:01,680
Speaker 1: you does that influence in any way? What kind of

865
00:38:01,680 --> 00:38:04,160
Speaker 1: bets or are do you know, people in that industry

866
00:38:04,200 --> 00:38:07,400
Speaker 1: that are looking at the sports bets and the DraftKings

867
00:38:07,440 --> 00:38:09,920
Speaker 1: and things like that to see what the market, what

868
00:38:09,960 --> 00:38:12,160
Speaker 1: the what the populace thinks before you go and do

869
00:38:12,239 --> 00:38:13,640
Speaker 1: it the actual bet with the bookie.

870
00:38:13,800 --> 00:38:16,799
Speaker 4: Uh yeah, I mean in the sports betting arena, there

871
00:38:16,880 --> 00:38:18,759
Speaker 4: is the public and there are the sharps. I mean

872
00:38:18,760 --> 00:38:20,839
Speaker 4: those are the teams. I mean in the public are

873
00:38:20,840 --> 00:38:23,160
Speaker 4: the morons who are almost always are wrong, and the

874
00:38:23,160 --> 00:38:25,160
Speaker 4: sharps are the guys who are almost always right. And

875
00:38:25,160 --> 00:38:26,880
Speaker 4: those are the pros, and they tend to be on

876
00:38:26,920 --> 00:38:28,000
Speaker 4: the contrarian side.

877
00:38:28,080 --> 00:38:30,400
Speaker 6: So we're the sharps, right, Yeah, totally.

878
00:38:30,480 --> 00:38:33,600
Speaker 4: Why do they call them sharks because they're professional gamblers.

879
00:38:33,640 --> 00:38:37,680
Speaker 4: They're there, they know, they have more information and more experience.

880
00:38:37,840 --> 00:38:40,040
Speaker 4: And it's the same thing with the stock market. I

881
00:38:40,080 --> 00:38:42,479
Speaker 4: mean it's it's the second you're you know, the guys

882
00:38:42,480 --> 00:38:44,560
Speaker 4: shining your shoes, which this is an old reference. Maybe

883
00:38:44,560 --> 00:38:46,640
Speaker 4: we don't go to shoe shiners anymore, but the second

884
00:38:46,680 --> 00:38:48,840
Speaker 4: the guy shining your shoes as a stock top for you,

885
00:38:48,840 --> 00:38:51,080
Speaker 4: you're better off shorting that stock than buying that stock.

886
00:38:51,600 --> 00:38:54,759
Speaker 4: Or when the cab drivers and the shoe shiners and

887
00:38:54,800 --> 00:38:57,960
Speaker 4: everyone starts talking about whatever stock it is.

888
00:38:58,520 --> 00:38:59,399
Speaker 6: That's that's when.

889
00:38:59,320 --> 00:39:02,040
Speaker 4: You're in a bubble or the old magazine cover theory,

890
00:39:02,040 --> 00:39:03,719
Speaker 4: and this is all in stock mark of the magazine cover,

891
00:39:03,840 --> 00:39:06,840
Speaker 4: the magazine cover. I remember Enron made the magazine a

892
00:39:06,840 --> 00:39:09,319
Speaker 4: big one, I made for Time or Fortune, and it

893
00:39:09,360 --> 00:39:12,000
Speaker 4: was literally within a month the whole thing fell. The

894
00:39:12,080 --> 00:39:15,719
Speaker 4: second a company makes a financial magazine is when you

895
00:39:15,800 --> 00:39:19,000
Speaker 4: know the bubbles at about to burst, especially for that

896
00:39:19,120 --> 00:39:22,680
Speaker 4: company or that sector, which is the same thing in

897
00:39:22,680 --> 00:39:23,360
Speaker 4: sports gambling.

898
00:39:23,400 --> 00:39:24,760
Speaker 2: It's the public that's the public.

899
00:39:25,239 --> 00:39:27,359
Speaker 5: And in part it's because once it feels like it's

900
00:39:27,400 --> 00:39:30,120
Speaker 5: a sure thing, that's what drive someone like Fortune to

901
00:39:30,160 --> 00:39:31,759
Speaker 5: feel like, oh, it's safe to put this on the

902
00:39:31,760 --> 00:39:34,799
Speaker 5: cover because it's obvious. It's obvious that Mron in this

903
00:39:34,840 --> 00:39:37,400
Speaker 5: particular case is the future. And someone that feels that obvious,

904
00:39:37,760 --> 00:39:40,080
Speaker 5: it's almost never that obvious. Right, You're at the other end,

905
00:39:40,160 --> 00:39:41,560
Speaker 5: You're at the other side of the cycle. And that's

906
00:39:41,560 --> 00:39:42,560
Speaker 5: true across all of these.

907
00:39:42,400 --> 00:39:43,239
Speaker 2: I have a question for you, Paul.

908
00:39:43,320 --> 00:39:46,440
Speaker 1: So you but you on our text thread, which is

909
00:39:46,480 --> 00:39:52,200
Speaker 1: where this podcast all began, you often send prediction market and.

910
00:39:52,160 --> 00:39:52,840
Speaker 2: So yeah, you do.

911
00:39:53,360 --> 00:39:55,480
Speaker 1: Is that because are you looking at it as an

912
00:39:55,520 --> 00:39:58,759
Speaker 1: affirmation or is it just a curiosity or like, where

913
00:39:58,840 --> 00:39:59,440
Speaker 1: is that so?

914
00:39:59,719 --> 00:39:59,839
Speaker 6: Mean?

915
00:40:00,000 --> 00:40:03,319
Speaker 5: Mostly this stuff is just stupid human tricks got it right.

916
00:40:03,360 --> 00:40:05,200
Speaker 5: So it's like the old Letterman show. It's like seeing

917
00:40:06,560 --> 00:40:09,000
Speaker 5: that this is the consensus about this particular thing is

918
00:40:09,040 --> 00:40:13,960
Speaker 5: interesting because generally, speaking back to Town's point, that retail

919
00:40:14,040 --> 00:40:16,600
Speaker 5: is usually wrong, and so if this is what retail thinks,

920
00:40:17,000 --> 00:40:19,160
Speaker 5: I really like to know that this is the consensus.

921
00:40:19,160 --> 00:40:23,880
Speaker 5: It's no different than in the oldest prediction market, equity markets,

922
00:40:23,920 --> 00:40:26,640
Speaker 5: if you looked at things like Dick's favorite things, you

923
00:40:26,640 --> 00:40:30,319
Speaker 5: look at analysts and analyst consensus. That's a kind of prediction, right,

924
00:40:30,360 --> 00:40:32,759
Speaker 5: They'll say, next quarter, we're predicting two dollars and thirty

925
00:40:32,800 --> 00:40:35,359
Speaker 5: two cents in earnings per share. Oh wow, these guys

926
00:40:35,400 --> 00:40:38,600
Speaker 5: are really good at predicting these things. No, they're not. No, A,

927
00:40:39,080 --> 00:40:41,640
Speaker 5: they're always wrong. But B, and this is more, far

928
00:40:41,680 --> 00:40:44,480
Speaker 5: more important, they're not actually making that prediction. They're being

929
00:40:44,480 --> 00:40:47,239
Speaker 5: fed numbers by the company, who then tries to low

930
00:40:47,280 --> 00:40:48,880
Speaker 5: ball them a bit. So there's a chance that I

931
00:40:48,920 --> 00:40:51,920
Speaker 5: can do numbers. Even so that entire prediction business is

932
00:40:51,960 --> 00:40:55,640
Speaker 5: predict predicated on creating a false impression of what's going

933
00:40:55,680 --> 00:40:57,319
Speaker 5: on out there, so then I can then I can

934
00:40:57,360 --> 00:40:59,359
Speaker 5: then beat It's just a game, right, It's just another

935
00:40:59,440 --> 00:41:00,600
Speaker 5: kind of prediction market game.

936
00:41:01,160 --> 00:41:03,719
Speaker 3: One of the one of the fascinating things to me

937
00:41:03,760 --> 00:41:07,800
Speaker 3: about the prediction markets is that they regularly ship post

938
00:41:07,920 --> 00:41:10,640
Speaker 3: on social media in a way that other I mean

939
00:41:10,760 --> 00:41:14,959
Speaker 3: like MGM Casino and DraftKings and so and so. Don't

940
00:41:15,080 --> 00:41:19,439
Speaker 3: you know, yeah, these are both foot these are these

941
00:41:19,440 --> 00:41:22,400
Speaker 3: are sports references to Ball's point about the real liquidity

942
00:41:22,520 --> 00:41:26,080
Speaker 3: is in the sports market sports prediction markets. But you know,

943
00:41:27,080 --> 00:41:29,480
Speaker 3: calls posting an image of forty nine ers running back

944
00:41:29,520 --> 00:41:33,000
Speaker 3: Christian McCaffrey with the caption loves receiving balls.

945
00:41:35,800 --> 00:41:39,600
Speaker 6: And and then to equal opportunity, just to give poly

946
00:41:39,760 --> 00:41:40,760
Speaker 6: market it's it's.

947
00:41:40,600 --> 00:41:44,959
Speaker 3: Equal airtime, ship poster marketing, Ship poster marketing, Uh, equal

948
00:41:45,000 --> 00:41:48,640
Speaker 3: opportunity airtime on poly market. An image of Toronto Raptors.

949
00:41:48,640 --> 00:41:52,040
Speaker 3: This is a basketball player for Nick Toronto Raptors player

950
00:41:52,120 --> 00:41:55,680
Speaker 3: Grady Dick, with the headline Dick is growing. So these

951
00:41:55,680 --> 00:42:01,560
Speaker 3: are childish, of course, ship posting memes, but I you know,

952
00:42:01,840 --> 00:42:04,800
Speaker 3: one can draw the logical conclusion that they see it

953
00:42:04,840 --> 00:42:06,480
Speaker 3: as an obvious way to attract younger.

954
00:42:06,680 --> 00:42:09,600
Speaker 4: Yeah, this is which is what the well Draft King

955
00:42:09,680 --> 00:42:11,799
Speaker 4: I was going to say, DraftKings and fan Duel and

956
00:42:11,880 --> 00:42:16,359
Speaker 4: these these their marketing budgets for young people are incredible, incredible. Well,

957
00:42:16,360 --> 00:42:19,280
Speaker 4: you were talking about how you overhear people in college campus.

958
00:42:19,520 --> 00:42:22,480
Speaker 4: The college campus is talking about who they're betting on

959
00:42:22,560 --> 00:42:26,680
Speaker 4: or what prop they're betting on. This marketing towards youth is,

960
00:42:27,440 --> 00:42:29,799
Speaker 4: you know, insane when you think about it, And there

961
00:42:29,840 --> 00:42:32,440
Speaker 4: should be and I don't know exactly how much regulation

962
00:42:32,560 --> 00:42:35,799
Speaker 4: there is in that arena, but there should be. You know,

963
00:42:36,400 --> 00:42:38,920
Speaker 4: you wouldn't market I guess they did. Used to market

964
00:42:39,160 --> 00:42:41,239
Speaker 4: tobacco for all teenagers.

965
00:42:41,280 --> 00:42:43,719
Speaker 5: All of this stuff was tobacco, alcohol and everything else.

966
00:42:43,719 --> 00:42:45,479
Speaker 5: And it's got to the point we're in the UK

967
00:42:45,800 --> 00:42:48,520
Speaker 5: and the Premier League. For a while, the largest sponsors

968
00:42:48,520 --> 00:42:51,239
Speaker 5: and this is another kind of gambling, but was crypto companies, right,

969
00:42:51,480 --> 00:42:54,280
Speaker 5: So they were one of the largest Shirts Jersey sponsors

970
00:42:54,520 --> 00:42:56,520
Speaker 5: in the Premier League and then it moved on and

971
00:42:56,640 --> 00:42:59,359
Speaker 5: became some of the broader prediction stuff. But all of

972
00:42:59,400 --> 00:43:01,680
Speaker 5: this again knowing turn it around, and I always said,

973
00:43:01,680 --> 00:43:03,960
Speaker 5: so anytime you're watching a sporting event, look at the ads.

974
00:43:04,160 --> 00:43:05,520
Speaker 5: These are the people who are watching it with you.

975
00:43:05,600 --> 00:43:08,400
Speaker 5: So if it's for like, you know, obesity, drugs, or

976
00:43:08,400 --> 00:43:09,920
Speaker 5: they say that, oh, those are the I'm watching this

977
00:43:09,920 --> 00:43:11,200
Speaker 5: with a bunch of fat white guys. Why am I

978
00:43:11,239 --> 00:43:14,759
Speaker 5: watching this right? Same thing with Premier League? Oh, I

979
00:43:14,800 --> 00:43:18,080
Speaker 5: see what's on the jerseys. The the demographic of people

980
00:43:18,080 --> 00:43:20,920
Speaker 5: who are watching this are clearly people to whom that's appealing.

981
00:43:20,960 --> 00:43:23,719
Speaker 5: So it's probably you know, twenty seven year old tech

982
00:43:23,800 --> 00:43:26,040
Speaker 5: guys who think that crypto's a path to wealth, and

983
00:43:26,080 --> 00:43:27,880
Speaker 5: so you know, you have to always turn it around

984
00:43:27,920 --> 00:43:30,240
Speaker 5: because they really understand the demographics of who they're presenting

985
00:43:30,239 --> 00:43:30,520
Speaker 5: this To.

986
00:43:30,480 --> 00:43:34,320
Speaker 4: Me, Well, the gambling is uniquely, uniquely male driven, and

987
00:43:34,360 --> 00:43:36,359
Speaker 4: that's why I hated gamblers. Anonymous, one of my friends

988
00:43:36,360 --> 00:43:38,480
Speaker 4: who went to alcoholics Anonymous had really cute.

989
00:43:38,239 --> 00:43:39,800
Speaker 6: Girls to look at for those two hours.

990
00:43:40,400 --> 00:43:42,359
Speaker 4: For me, it was all seventy two year old men.

991
00:43:42,480 --> 00:43:43,080
Speaker 6: Yeah, IRV.

992
00:43:43,440 --> 00:43:47,759
Speaker 4: And basically why I left ca.

993
00:43:48,000 --> 00:43:53,520
Speaker 6: Those guys and started drinking shar regular. What's the movie?

994
00:43:53,640 --> 00:43:56,200
Speaker 5: What's the Tim Robbins movie where the guy goes to

995
00:43:56,800 --> 00:43:58,320
Speaker 5: AA and he said, oh, I'm on my way to

996
00:43:58,360 --> 00:43:59,960
Speaker 5: the AA meeting right now, and he stops to play

997
00:44:00,200 --> 00:44:01,920
Speaker 5: in the player. It's the great moment. He's on his

998
00:44:01,960 --> 00:44:03,239
Speaker 5: way and he says, I can't stop it, and I'm

999
00:44:03,280 --> 00:44:05,680
Speaker 5: on the way to my to my AA meeting. And

1000
00:44:06,120 --> 00:44:07,759
Speaker 5: who's I guess it's Tim Rum says, Oh, I didn't

1001
00:44:07,760 --> 00:44:09,160
Speaker 5: know you had drinking. Probably said no, I don't. This

1002
00:44:09,200 --> 00:44:10,560
Speaker 5: is where everyone goes, now, this is where we all

1003
00:44:10,600 --> 00:44:11,719
Speaker 5: meet at AA meetings.

1004
00:44:11,520 --> 00:44:14,359
Speaker 4: Because Peter Gallagher there, Peter Gallagher, Right, Peter Gallagher, That's

1005
00:44:14,360 --> 00:44:15,439
Speaker 4: where all the best deals are.

1006
00:44:15,480 --> 00:44:17,839
Speaker 5: All the best deals are made in AA meetings. Now,

1007
00:44:18,200 --> 00:44:19,759
Speaker 5: same thing, right, I mean it, pack up.

1008
00:44:19,680 --> 00:44:21,839
Speaker 4: The cutest girls and pick up the cutest girls. None

1009
00:44:21,880 --> 00:44:24,799
Speaker 4: in GA none and g trust me, just the guy

1010
00:44:24,880 --> 00:44:28,280
Speaker 4: named IRV. I feel terrible because if there's someone listening

1011
00:44:28,360 --> 00:44:29,840
Speaker 4: to this who was thinking about going to g A,

1012
00:44:29,960 --> 00:44:32,360
Speaker 4: I just you know, destroyed the next ten years.

1013
00:44:32,760 --> 00:44:33,399
Speaker 5: Going there for dating.

1014
00:44:34,360 --> 00:44:36,440
Speaker 1: Can you give us We're going to wrap up here,

1015
00:44:36,480 --> 00:44:39,080
Speaker 1: but can you give us one story? One one more

1016
00:44:39,120 --> 00:44:42,120
Speaker 1: story as a as an outro for our for our show.

1017
00:44:43,000 --> 00:44:45,960
Speaker 4: Sure you know what I'm gonna do it. It's not

1018
00:44:46,440 --> 00:44:48,680
Speaker 4: it's an okay story, but it's it's it's timely because

1019
00:44:48,719 --> 00:44:51,440
Speaker 4: it was the Super Bowl where New England played Seattle.

1020
00:44:51,600 --> 00:44:53,239
Speaker 4: So the reason I'm telling this is because of the

1021
00:44:53,320 --> 00:44:56,439
Speaker 4: recent Super Bowl. And this was I think ten years

1022
00:44:56,440 --> 00:44:58,799
Speaker 4: ago roughly, and it was Pete Carroll was the coach

1023
00:44:58,840 --> 00:45:00,799
Speaker 4: and Marshall Lynch was running by for Seattle on Tom

1024
00:45:00,840 --> 00:45:02,400
Speaker 4: Brady was a quarterback for New England. It was a

1025
00:45:02,400 --> 00:45:04,160
Speaker 4: big super Bowl, very exciting super Bowl. And I bet

1026
00:45:04,200 --> 00:45:07,160
Speaker 4: a hundred you're speaking Chinese to me right now, sorry

1027
00:45:07,160 --> 00:45:09,600
Speaker 4: who these people are? Because people that listen most people

1028
00:45:09,640 --> 00:45:11,239
Speaker 4: what I'm saying when we know what the.

1029
00:45:11,280 --> 00:45:14,040
Speaker 3: Outcome is and how it happened, and this couldn't be

1030
00:45:14,120 --> 00:45:17,320
Speaker 3: a more terrifying. It's giving me anxiety.

1031
00:45:17,800 --> 00:45:18,480
Speaker 6: Wait, so go back.

1032
00:45:18,520 --> 00:45:20,440
Speaker 2: You put a one hundred thousand dollars on who Seattle

1033
00:45:20,440 --> 00:45:20,960
Speaker 2: on Seattle?

1034
00:45:21,080 --> 00:45:23,799
Speaker 4: I put one hundred sixteen roughly football team.

1035
00:45:23,880 --> 00:45:24,759
Speaker 2: Football team got it.

1036
00:45:24,880 --> 00:45:26,560
Speaker 4: And I have one hundred thousand dollars on the team.

1037
00:45:26,880 --> 00:45:28,560
Speaker 4: And I go to a party at a friend's house

1038
00:45:28,600 --> 00:45:30,239
Speaker 4: and there's a bunch of people around. There's this really

1039
00:45:30,320 --> 00:45:32,279
Speaker 4: cute girl and she says, I think New England's going

1040
00:45:32,320 --> 00:45:34,520
Speaker 4: to win. I'm kind of flirting and I say, let's

1041
00:45:34,520 --> 00:45:37,360
Speaker 4: put money on it. And we put twenty dollars on

1042
00:45:37,480 --> 00:45:39,440
Speaker 4: the game. I took Seattle, she took New England. I

1043
00:45:39,480 --> 00:45:41,759
Speaker 4: have one hundred thousand dollars. Meanwhile in Seattle, which I

1044
00:45:41,800 --> 00:45:44,960
Speaker 4: didn't tell anybody. We're watching the game now, Nick, you

1045
00:45:45,000 --> 00:45:47,880
Speaker 4: won't remember this, but the game, near the end of

1046
00:45:47,920 --> 00:45:49,719
Speaker 4: the game, very very closely in the game, Seattle had

1047
00:45:49,760 --> 00:45:51,000
Speaker 4: the ball in the one yard line and they were

1048
00:45:51,080 --> 00:45:51,560
Speaker 4: going to win.

1049
00:45:51,719 --> 00:45:52,239
Speaker 6: I was done.

1050
00:45:52,360 --> 00:45:54,280
Speaker 4: It was easy because they had a guy named Marshaun

1051
00:45:54,360 --> 00:45:58,879
Speaker 4: Lynz who was guaranteed to get a touchdown at one yard.

1052
00:45:58,960 --> 00:45:59,879
Speaker 2: He did it all season.

1053
00:46:00,280 --> 00:46:03,520
Speaker 4: He was a killer running back. And all they had

1054
00:46:03,560 --> 00:46:05,879
Speaker 4: to do was handed to him and put it through

1055
00:46:05,920 --> 00:46:09,160
Speaker 4: the goal. And everyone knew this. But the coach got

1056
00:46:09,200 --> 00:46:12,560
Speaker 4: a little, a little cute, and he decided he thought, well,

1057
00:46:12,600 --> 00:46:14,759
Speaker 4: everyone knows this, and maybe they'll stop him. So I'm

1058
00:46:14,760 --> 00:46:17,800
Speaker 4: going to have Russell Wilson pass the ball, which is

1059
00:46:18,840 --> 00:46:21,320
Speaker 4: this is known in the NFL the stupidest super.

1060
00:46:21,160 --> 00:46:23,319
Speaker 6: Dull decision in the history of the game.

1061
00:46:23,400 --> 00:46:26,080
Speaker 4: I don't think anyone will argue that, Nick, back me

1062
00:46:26,200 --> 00:46:32,560
Speaker 4: up on that. He threw the ball interception and I

1063
00:46:32,600 --> 00:46:34,880
Speaker 4: lost one hundred thousand dollars, but you won twenty and

1064
00:46:35,000 --> 00:46:37,719
Speaker 4: I know I lost. And the second I watched this.

1065
00:46:37,920 --> 00:46:40,279
Speaker 4: I'm digesting this. It's all going through me. And I

1066
00:46:40,320 --> 00:46:42,080
Speaker 4: have this cute little girl with a big smile saying

1067
00:46:42,160 --> 00:46:45,200
Speaker 4: you owe me twenty dollars. And I just looked at

1068
00:46:45,239 --> 00:46:47,319
Speaker 4: her with a smile, took out my ball like gave

1069
00:46:47,400 --> 00:46:53,120
Speaker 4: her twenty dollars, slowly walked away and just cry, that's

1070
00:46:53,160 --> 00:46:54,760
Speaker 4: my New England Seattle's story.

1071
00:46:54,920 --> 00:46:55,480
Speaker 5: That's brutal.

1072
00:46:55,840 --> 00:46:59,080
Speaker 1: Real quick one last quick question. Did the bookies ever

1073
00:46:59,160 --> 00:47:01,440
Speaker 1: turn around and say, dude, you got a problem.

1074
00:47:03,160 --> 00:47:05,840
Speaker 5: No? I mean it's like no, you know, it's like

1075
00:47:05,880 --> 00:47:08,279
Speaker 5: an out, It's like a liquor store saying it's like

1076
00:47:08,320 --> 00:47:09,759
Speaker 5: my drug dealers saying, you know, you really need to

1077
00:47:09,800 --> 00:47:10,080
Speaker 5: step it.

1078
00:47:11,440 --> 00:47:13,080
Speaker 4: I've been friends with a lot of my bookies and

1079
00:47:13,160 --> 00:47:15,279
Speaker 4: I'm still friends with them. I'm talking to a few

1080
00:47:15,320 --> 00:47:18,520
Speaker 4: of my best bookies. There have been situations, not for me,

1081
00:47:18,960 --> 00:47:22,239
Speaker 4: because I was always someone who could pay. I made

1082
00:47:22,320 --> 00:47:25,879
Speaker 4: money or I had money or I could I never

1083
00:47:26,160 --> 00:47:28,400
Speaker 4: was going to rob a liquors.

1084
00:47:28,480 --> 00:47:30,399
Speaker 6: Worst comes the worst. You could take a Puma bag

1085
00:47:30,480 --> 00:47:33,719
Speaker 6: to lass. You're good for the bag.

1086
00:47:33,960 --> 00:47:35,640
Speaker 4: So for me, it was never like that. I have

1087
00:47:35,800 --> 00:47:39,520
Speaker 4: talked to them and they've had they've had clients who've

1088
00:47:39,719 --> 00:47:42,080
Speaker 4: just had a wife and kids, and we're just really

1089
00:47:42,160 --> 00:47:44,280
Speaker 4: always on the public side. As we were saying, always

1090
00:47:44,320 --> 00:47:47,719
Speaker 4: on the mush bet we call always losing. And and

1091
00:47:48,000 --> 00:47:50,600
Speaker 4: I one of my bookiey friends sat a guy down

1092
00:47:50,640 --> 00:47:53,520
Speaker 4: and said, you're doing this wrong. I'm gonna I'm not

1093
00:47:53,600 --> 00:47:55,200
Speaker 4: I'm actually gonna teach you how to do it right,

1094
00:47:55,400 --> 00:47:57,680
Speaker 4: or I'm gonna cut you off, and basically had to

1095
00:47:57,719 --> 00:47:58,960
Speaker 4: talk with them and it was out. It was like,

1096
00:47:59,040 --> 00:48:00,560
Speaker 4: I don't need to take your money anymore, and it's

1097
00:48:00,600 --> 00:48:02,720
Speaker 4: not that much for me, but I'm watching you destroy

1098
00:48:02,760 --> 00:48:04,520
Speaker 4: your life. So there was a boogie with a hard

1099
00:48:04,600 --> 00:48:05,200
Speaker 4: story in there.

1100
00:48:05,440 --> 00:48:07,399
Speaker 5: It sounds like a hooker with a heart of gold story.

1101
00:48:07,440 --> 00:48:09,480
Speaker 4: Here there was a story.

1102
00:48:10,000 --> 00:48:11,920
Speaker 1: Alan came to Thanksgiving at our house and my brother

1103
00:48:11,960 --> 00:48:13,960
Speaker 1: in law told the story of a guy he knew

1104
00:48:14,080 --> 00:48:16,920
Speaker 1: who was made like thirty million dollars.

1105
00:48:17,120 --> 00:48:19,960
Speaker 2: I don't know on what, but he got divorced and got.

1106
00:48:20,600 --> 00:48:23,759
Speaker 1: Into all the gambling markets and sports betting and this,

1107
00:48:23,840 --> 00:48:26,200
Speaker 1: that and the other and lost it all. And then

1108
00:48:26,239 --> 00:48:29,080
Speaker 1: they found him dead in his bed with the laptop

1109
00:48:29,120 --> 00:48:30,560
Speaker 1: open still on like Draft.

1110
00:48:30,400 --> 00:48:33,080
Speaker 2: Kings or something like that. They don't know what happened.

1111
00:48:33,239 --> 00:48:36,040
Speaker 1: Well, they think he owed someone a million and a

1112
00:48:36,080 --> 00:48:36,840
Speaker 1: half dollars.

1113
00:48:36,920 --> 00:48:39,600
Speaker 5: What I just don't understand the import of the story.

1114
00:48:39,640 --> 00:48:41,279
Speaker 5: A guy opened DraftKings and it killed him.

1115
00:48:41,400 --> 00:48:44,920
Speaker 1: No, it's he he got so he got in so

1116
00:48:45,120 --> 00:48:46,920
Speaker 1: deep that he owed a booky so much money that

1117
00:48:47,000 --> 00:48:47,640
Speaker 1: they killed him.

1118
00:48:48,760 --> 00:48:49,600
Speaker 6: Oh they killed him.

1119
00:48:49,640 --> 00:48:53,839
Speaker 3: I I thought that killed HIMSELFE. Now all right, well

1120
00:48:53,880 --> 00:48:58,000
Speaker 3: you really didn't tell that story craft. We all would

1121
00:48:58,040 --> 00:49:01,160
Speaker 3: have left with the impression that the guy had killed himself.

1122
00:49:01,320 --> 00:49:02,920
Speaker 5: Yeah, there was this kind of modeling moment.

1123
00:49:03,160 --> 00:49:04,400
Speaker 2: Yeah, that's all right.

1124
00:49:04,680 --> 00:49:09,640
Speaker 1: Well, on that note, this has been another episode of

1125
00:49:09,800 --> 00:49:13,080
Speaker 1: The Nick Dick and Poll Show featuring Alan Loebe.

1126
00:49:13,680 --> 00:49:16,000
Speaker 6: By the way, Ellen, all of our episode Dundin Murder.

1127
00:49:17,080 --> 00:49:19,320
Speaker 5: Yeah, that's because because we use it as crossed promotion

1128
00:49:19,440 --> 00:49:20,000
Speaker 5: for the other show.

1129
00:49:23,239 --> 00:49:24,280
Speaker 6: Tune in again.

1130
00:49:24,400 --> 00:49:27,480
Speaker 1: We're gonna have Alan back for another episode where we're

1131
00:49:27,480 --> 00:49:32,000
Speaker 1: gonna be talking about Hollywood uh and AI and how

1132
00:49:32,480 --> 00:49:34,120
Speaker 1: how people like Alan won't have a job soon.

1133
00:49:34,680 --> 00:49:35,200
Speaker 4: Fantastic