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Speaker 1: Welcome to the Nick, Dick and Poul Show. I'm Nick Bilton.

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Speaker 2: I am star of screen and stage costello.

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Speaker 3: I'm a star of neither Polkadrowski.

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Speaker 1: And on this week's episode, we're gonna be talking about

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Speaker 1: what are we talking about?

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Speaker 2: Tennis?

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Speaker 1: Tennis and hamorrhoids? Well and social media in social media

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Speaker 1: and not in that order, and the difference between grass

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Speaker 1: and Clay.

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Speaker 2: Why am I explaining? Are you gonna? Are you gonna?

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Speaker 1: Now?

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Speaker 2: Tell me?

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Speaker 1: Just ran the random guy?

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Speaker 2: R you know? Wait a minute, you don't know this story,

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Speaker 2: Robert Altman, the player, the first shot, the long single

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Speaker 2: tracking shot, and the player. You don't know it?

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Speaker 3: Do you know the player?

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Speaker 1: I don't think I saw the player.

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Speaker 2: Oh my god, you know what, forget it. This was

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Speaker 2: a horrible idea.

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Speaker 1: That's right where it's terrible. I don't watch a lot

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Speaker 1: of movies. I like to read the scripts and things

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Speaker 1: like that.

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Speaker 2: You should go research. In fact, I insist that after

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Speaker 2: this you read it. You writing movies. You're a movie right, No.

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Speaker 1: But I like reading scripts. I've had this whole conversation

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Speaker 1: with Paul, like if I'm watched it's hard to study

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Speaker 1: a movie when you watch it because the director and

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Speaker 1: the actor. But when you're reading a script, you can

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Speaker 1: study how it's written, and so on and so forth.

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Speaker 1: So I read a lot of scripts for movies and

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Speaker 1: I don't end up watching them.

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Speaker 2: How do you know how the thing is going to

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Speaker 2: be shot? Then? When you write it like a shooting

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Speaker 2: a cinematography instruction, like the camera pans back, I've heard.

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Speaker 2: Do you know what happens when the camera pans back?

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Speaker 3: Or do you say that I heard these things happen,

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Speaker 3: I haven't actually seen.

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Speaker 1: I always supposed to be talking about hemorrhoids.

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Speaker 2: Hold on, let me ask you a question. Yeah, do

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Speaker 2: you know what a smash cut is? I do know what.

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Speaker 1: I love a smash I love a match cut. A

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Speaker 1: match cut is the best cut cut.

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Speaker 3: I don't know what a match cut is.

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Speaker 1: A match cut is when you're you close in on

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Speaker 1: pol Kadrowski's face and we match cut to Polkadrowski, uh

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Speaker 1: ten years early, and we pulled back and he is homeless,

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Speaker 1: living in an encampment.

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Speaker 3: Beforeward can beg you the direction?

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Speaker 2: Really?

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Speaker 1: Ten years from now? The podcast failed so badly.

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Speaker 2: So you say you don't, but you have to have

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Speaker 2: seen these things to know what I've seen.

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Speaker 1: I've seen. I have seen a few films.

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Speaker 2: You just prefer not to watch them. You prefer to

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Speaker 2: read them.

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Speaker 1: I prefer to read them.

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Speaker 2: All right, Okay, we all have our problems.

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Speaker 3: I'm glad we've established this move. Let's move on, Paul.

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Speaker 1: I want to talk about hemorrhoids. You don't, Yes, I do.

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Speaker 1: You sent a study to us about social media and hemorrhoids.

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Speaker 1: Can you can?

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Speaker 2: You?

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Speaker 1: Can you tell us what it was about?

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Speaker 3: So the gist of that one was that because people

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Speaker 3: get so comfortable now in the bathroom because they bring

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Speaker 3: their phones in with them, which is why phones are

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Speaker 3: now I think I read this somewhere with it. They're

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Speaker 3: among the most bacteria infested things in your lives.

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Speaker 1: Are you serious?

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Speaker 2: Yeah?

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Speaker 3: They're absolutely gross. If you want to get a decent

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Speaker 3: sample of every single bacteria in your life, bring that in,

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Speaker 3: get it swabbed. That's your phone.

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Speaker 2: Sure, you're sitting it down on a table in a restaurant,

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Speaker 2: you're putting it on the seat and the on the plane,

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Speaker 2: bringing into the restaurant, or bringing in the bathroom.

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Speaker 1: Everyone bring it into the bathroom.

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Speaker 3: Of course, I can't speak from more than narrow experience.

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Speaker 2: But I'm gonna go with yes, like, gotta be close

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Speaker 2: to one hundred percent.

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Speaker 1: It's kind of crazy because what are you gonna.

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Speaker 2: Do hand it to the person seated, nothing at the restaurant,

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Speaker 2: the rest I gotta go.

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Speaker 1: Yeah, there's nothing that everyone brings it. You don't bring

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Speaker 1: like a plate into the bathroom with you don't there's

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Speaker 1: nothing that people bring.

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Speaker 2: You don't. Yeah, that's fair.

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Speaker 3: I mean to the point of it was that people

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Speaker 3: in the restrooms with phones, they get very comfortable there

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Speaker 3: and they're like, well, I'm here, I might as well

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Speaker 3: do something.

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Speaker 2: I was I might as well post that amazing photo

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Speaker 2: I took yesterday and like como or in order.

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Speaker 3: To evacuate my vows, no matter how long it takes.

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Speaker 3: And that's actually, as it turns out, if you're a

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Speaker 3: lower GI guy, that's actually a bad thing spending that

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Speaker 3: long on that kind of And so as a result,

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Speaker 3: the study was really like compelling. It said that that's

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Speaker 3: leading to this outbreak of hemorrhoid's because people are getting

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Speaker 3: so comfortable in bathrooms that they're like, you know what,

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Speaker 3: screw it, I'll take it if it takes an hour.

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Speaker 3: It takes an hour. And that turns out physiologically.

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Speaker 1: We're not supposed to sit.

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Speaker 2: On like I get another half hour, Joe Rogan to.

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Speaker 3: Before I get out of here, Maybe find something else

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Speaker 3: to do, and don't just sit here and hope something happens.

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Speaker 1: So, in short, every aspect of social media's bad for us.

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Speaker 3: I think that's a reasonable extrapolation. But I mean the

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Speaker 3: idea that it's had these crazy and really insidious side

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Speaker 3: effects that people don't expect, Like people are spending too

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Speaker 3: long in restrooms, and it's not just because it's making

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Speaker 3: your phone bacteria infested, but it's literally leading to.

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Speaker 2: I think I remember in twenty ten Bizstone saying to me,

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Speaker 2: what if someday we spend too long in the bathroom? Yeah,

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Speaker 2: and you like, and that's the time we thought he

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Speaker 2: was crazy, But.

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Speaker 3: Turns out he's the future.

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Speaker 1: Turns out one day.

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Speaker 2: This stonecomma futurists.

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Speaker 3: Yeah, one day there will be a paper about this.

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Speaker 1: I have a question for you, predictable when you when you.

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Speaker 2: Don't don't do that?

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Speaker 1: Don't know when did you realize it? You know, like, no,

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Speaker 1: when did you realize.

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Speaker 2: It was Tuesday?

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Speaker 1: Like, when did you realize social media was back?

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Speaker 2: I didn't realize a couple of years ago.

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Speaker 1: Like I remember I was at the New York Times

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Speaker 1: and I was writing about Twitter and Facebook and everything,

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Speaker 1: and I got into a big argument with the editor

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Speaker 1: in chief, who was like, it's the worst thing in

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Speaker 1: the world, and I was like, it's the greatest thing ever.

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Speaker 1: It's going to give everyone a voice. I sounded like,

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Speaker 1: you know, a fucking loser. But but I wrote this

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Speaker 1: whole thing, and I argued for it.

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Speaker 2: And then wait a minute, I think I said that, yeah, yeah,

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Speaker 2: you did. Wait a minute. Yeah, that was met so familiar.

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Speaker 1: We all said it. And then and then it was

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Speaker 1: like a few years. It was like twenty twenty. I

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Speaker 1: think it was COVID where I was like, oh, it's

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Speaker 1: it's it's really bad for society.

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Speaker 3: Are you serious it took you that long?

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Speaker 1: No, because there was still good things. There were like

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Speaker 1: still things that I thought were good, Like there was

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Speaker 1: you know these me too movement, Like Me Too Movement

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Speaker 1: arguably could not have happened without social media.

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Speaker 3: I think.

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Speaker 1: I think Black Lives Matter and all those other things

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Speaker 1: absolutely could. I mean, we saw that in the nineteen sixties.

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Speaker 1: But but Me Too, I think was a specific kind

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Speaker 1: of thing like, and it did. I think it was

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Speaker 1: one of the few fur better. But twenty twenty was

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Speaker 1: really well. I was like, oh god, this is horrific.

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Speaker 3: I mean, you need to get with the program. When

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Speaker 3: it was for you, oh way earlier. I mean it

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Speaker 3: was obvious just in terms of my own behavior.

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Speaker 1: I was in terms of my own behavior, yeah, yeah, no, no.

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Speaker 3: I mean I was distracted. You was like, I could

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Speaker 3: see elements of addictions, like has someone responded to this

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Speaker 3: as someone retreateds?

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Speaker 2: Like, what the fuck?

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Speaker 3: What do I care?

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Speaker 2: What do I care?

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Speaker 3: What a bunch of randoms in their house? Yeah, think

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Speaker 3: of something that I said on the fly that I

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Speaker 3: don't give a rat's ass about. This is ridiculous.

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Speaker 2: Paul hated Twitter in two thousand and five, the year

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Speaker 2: before it was That's right, I was.

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Speaker 3: I was an early hater, like preemptively said, do you

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Speaker 3: know what, one day there's going to be mass text

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Speaker 3: messaging and I'm not gonna like it. Right, No, it's

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Speaker 3: just like I just saw it in my own behad

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Speaker 3: I didn't like. I didn't like that. It's the same

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Speaker 3: reason why and me, you and I have talked about

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Speaker 3: this about television. We've both done a ton of like

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Speaker 3: CNBC and other things. And one of the reasons why

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Speaker 3: I stopped doing it because I realized, I don't watch it.

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Speaker 3: I don't like the people who watch it, and most

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Speaker 3: of the people who watch it are like middle aged

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Speaker 3: males in their basements with their pants down around their ankles,

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Speaker 3: like I don't want.

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Speaker 1: To don't talk about deck like that, right, And.

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Speaker 3: It's like I said, you know, this doesn't there's nothing

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Speaker 3: about this I like, and so I don't like performing

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Speaker 3: for these people. Well, the exact same logic applies, but

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Speaker 3: even worse with much of social media, like I don't

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Speaker 3: know who any of these people are, what do I

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Speaker 3: care what they think about anything about what I say?

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Speaker 3: And that in turn leads to all these like completely

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Speaker 3: ridiculous behaviors.

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Speaker 1: It's also I think that you, the the algorithms have

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Speaker 1: gotten so good at understanding us that we that that

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Speaker 1: we we can't win. And I always have the line

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Speaker 1: like from War Games, which I did see, by the way,

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Speaker 1: didn't just read the script.

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Speaker 2: The only way to the only way to win is

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Speaker 2: not to blay.

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Speaker 1: And I think, uh that, like, can you imagine being

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Speaker 1: a fucking teenager with this stuff? I mean you have kids, yeah,

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Speaker 1: you know, yours are not you're my kids are older,

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Speaker 1: but just terrific.

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Speaker 3: Oh no, watching it this fomo stuff where they're constantly

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Speaker 3: seeing other people doing things, and so you never in

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Speaker 3: your own moment. You're always thinking, oh wow, I could

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Speaker 3: be over here doing this or someone else is doing this,

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Speaker 3: and everyone's really good at making you feel as if

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Speaker 3: there's something else I.

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Speaker 1: Could be doing, you could still use it.

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Speaker 3: They do, do they are?

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Speaker 1: They just as drawn in.

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Speaker 3: I think they're a little more aware because we were

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Speaker 3: relatively slow and letting them do it. But all that,

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Speaker 3: all that that led to was like anger where they're like,

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Speaker 3: you guys are you guys are bastards? My all my

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Speaker 3: friends are using social media and you won't let me

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Speaker 3: and it fucked up my life. And I'm like, oh

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Speaker 3: well great, this goes either way, right, you screwed up

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Speaker 3: my life because you use it or because you don't

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Speaker 3: use it. It doesn't make any difference. The thing that

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Speaker 3: I find back to your point about algorithms, and this

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Speaker 3: was the line I forget where I just saw it

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Speaker 3: recently that so much of this stuff is predicated on

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Speaker 3: building businesses for like anger, entrepreneurs.

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Speaker 1: People wait, what do you mean by that?

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Speaker 2: Well, it's absolutely the case, but this has been a

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Speaker 2: slow evolution. It didn't start that way. It's absolutely it's

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Speaker 2: absolutely the case. I know exactly referring to, but I

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Speaker 2: just want to set this up. It's absolutely the case

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Speaker 2: that when you go on to X now and this

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Speaker 2: is not again, this is not today versus yesterday or

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Speaker 2: this administration for this administration, it's been a slow evolution

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Speaker 2: the algorithm. It's absolutely the case that it's an anger machine.

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Speaker 2: You go on there and you start reading, and it's

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Speaker 2: so hyper political and so algorithmically driven around all the

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Speaker 2: people who think this. You will now see what they

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Speaker 2: think about it. You just get angry the longer you're

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Speaker 2: on there.

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Speaker 3: And but the flip the other side of that is

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Speaker 3: is that are the entrepreneur right, So that creates so

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Speaker 3: we've now got to market all these people who are

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Speaker 3: inflamed and angry. So you get anger entrepreneurs who want

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Speaker 3: to build businesses around keeping you inflame, using the algorithm,

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Speaker 3: piggybacking on top of this to say whatever it is

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Speaker 3: that will keep you inflame, because that's good business. And

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Speaker 3: so anger and conflict entrepreneurs have found this really fertile

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Speaker 3: market in social media.

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Speaker 2: PS. It's not just right or left. They're anger entrepreneurs.

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Speaker 2: They're anger entrepreneurs for everybody, for everybody, for sports.

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Speaker 3: I mean because and the literature is really clear that

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Speaker 3: that kind of inflammation leads to engagement. People If they

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Speaker 3: feel kind of like, eh, I saw it being it,

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Speaker 3: maybe feel kind of a different they don't come back.

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Speaker 3: But if people are made angry even more than if

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Speaker 3: they're made happy, they'll return.

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Speaker 2: It's actually not a coincidence that two of what you

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Speaker 2: could call the anger entrepreneurs for sports on ESPN, Paul

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Speaker 2: Feinbaum for football and Steven A. Smith for lots of things,

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Speaker 2: also are considering political runs.

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Speaker 1: Right, Oh are they really?

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Speaker 3: Yeah? Yeah, But it's the same. It's the same motivation.

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Speaker 3: You realize that I can ride, I can ride that right.

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Speaker 2: They have no nuanced opinion. Everything is like, this guy's

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Speaker 2: a jerk, These people are great, he should be fired yesterday.

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Speaker 2: There's no nuance. They're like, well, if if they had

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Speaker 2: actually made the field goal, they would have won. No,

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Speaker 2: you know, it's all they're horrible. He's great, You're this

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Speaker 2: one's stupid. You know, it's all. It's it's all black

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Speaker 2: and white.

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Speaker 1: Do you guys think that it go like, is there

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Speaker 1: an end to this or is it.

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Speaker 2: Just this is just the death of the universe?

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Speaker 1: No, like does a generation does the next generation come

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Speaker 1: along and be like this doesn't make me feel good?

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Speaker 1: I don't I'm the only way to win is not

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Speaker 1: to play the game? Or is this just like it's

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Speaker 1: just the most inflamed people in society. You're going to

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Speaker 1: continue to come.

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Speaker 3: But there's no sign of that.

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Speaker 2: There's no sign of that. While there are some people,

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Speaker 2: well I agree, there are some people who now realize, hey,

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Speaker 2: you got to get off social media. You know, it's

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Speaker 2: the Sam Harris Is of the world there. It is

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Speaker 2: all also the case that when you walk through Soho

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Speaker 2: in Manhattan on a Saturday.

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Speaker 3: Watch people walk into lamp posts.

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Speaker 2: There there are your nine influencers deep walking down the street,

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Speaker 2: and you know, some you're like, who who is this

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Speaker 2: person shooting this for? You know, here I am on

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Speaker 2: Crosby Street, crossing the cobblestones, looking looking longingly over my

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Speaker 2: shoulder with this particular Prada bag in my hand. Yeah,

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Speaker 2: what are you doing? But there are fifty of them?

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Speaker 3: Yeah, and for them everything is content. Everything literally everything

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Speaker 3: is content. I mean it's I was watching I was

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Speaker 3: at a thing last week.

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Speaker 2: That's a great, great point. Yeah, everything is everything is

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Speaker 2: I was.

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Speaker 3: Watching people not just film a race I was in,

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Speaker 3: but people film the people filming. So it literally it

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Speaker 3: gets It's like a stack, right, it's a stack content

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Speaker 3: for social media where you're filming and then filming the

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Speaker 3: people who are filming, and then because you'll see that,

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Speaker 3: and with influencers where it's like all these influencers are

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Speaker 3: taking pictures of some famous Tokyo intersection. Well now there's

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Speaker 3: people who like to take pictures of the people who

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Speaker 3: are standing in the middle of the intersection, filming the intersection.

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Speaker 3: So it becomes me out, No, it's really it's it's

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Speaker 3: a fascinating human behavior. But there's I can't see how

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Speaker 3: it extinguishes itself.

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Speaker 2: One of my favorites is And then there's the I mean,

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Speaker 2: there's the everything to me as content as an influencer,

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Speaker 2: and then there's the what I'm shooting and portraying versus

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Speaker 2: what's really going on. And I realized we've I realized

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Speaker 2: we've always known this, but it's now extreme. So, for example,

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Speaker 2: as at a restaurant, in Brooklyn. This is now six

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Speaker 2: seven months ago, and there's a man and a woman

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Speaker 2: younger men and a woman maybe late twenties, at table

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Speaker 2: next to me, and they get their food and the

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Speaker 2: cameras come out, and I, you know, look across the

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Speaker 2: table and I laughingly say, Instagram eats first. You know,

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Speaker 2: they take their sure but that's not the and they're

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Speaker 2: they you know, they take the shots of the food,

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Speaker 2: and they've got each got cocktails and they're drinking the

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Speaker 2: cocktail but they're not eating the food. And they've got

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Speaker 2: like four plates. Then they switch these two plates for

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Speaker 2: these other two plates, start filming, you know, get the

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Speaker 2: wide angle shot of me and the person across from me,

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Speaker 2: get the shot of just the food, get the then

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Speaker 2: they put those aside, continue to drink, don't eat the food.

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Speaker 2: They after a while, after the check and get up

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Speaker 2: and leave. I was like, oh, it's way worse than

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Speaker 2: I thought. Instagram doesn't eat, just eat first, Instagram.

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Speaker 3: Don't and you don't eat Yeah, oh my goodness.

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Speaker 2: Yeah probably yeah, they're probably on GLP ones. What are

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Speaker 2: you kidding me? This is Italian food. I can't eat.

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Speaker 2: I can't eat this stuff, but I do have to

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Speaker 2: have a content, but I need content and I'm alsot.

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Speaker 2: But also I'm down fifteen pounds in the last five days.

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Speaker 3: That's really interesting.

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Speaker 1: What was it to happen with you at the US

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Speaker 1: Open with influencers?

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Speaker 2: You were going to tell the tennis tournament. So I

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Speaker 2: had the good fortune to go to a number of

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Speaker 2: tennis tournaments this year and they're super fun to watch.

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Speaker 2: And the French Open, I would say, is the most

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Speaker 2: tennessee even over. How how is one thing I'm gonna

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Speaker 2: all right, give me a second to define tennis balls

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Speaker 2: and tennis rackets? Okay, fair question. You got Wimbledon. First

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Speaker 2: of all, forget the Australian Open. Can't go to Australian Open.

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Speaker 2: That's like it was like, I don't know, not far, No.

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Speaker 1: It's as far away.

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Speaker 3: Also like that golf tournament where everyone gets drunk and

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Speaker 3: hopes for a home in one Phoenix.

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Speaker 2: Australians drink while they're drinking. Yeah, so you know, first

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Speaker 2: of all, it's far it's hardcourt, so you're like, well,

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Speaker 2: I can go to the US Open and see hardcore

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Speaker 2: and it's the first one of the years, so they're

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Speaker 2: kind of like they're all injured and Wan and start interrupt.

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Speaker 1: Is there a difference in play when you're on a

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Speaker 1: hard court versus grass? And things like that?

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Speaker 2: Oh?

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Speaker 1: Stop, I'm not a sports person.

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Speaker 4: I don't even know aply not even don't even know

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Speaker 4: what kind of ball they Yeah, I'm serious, but use.

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Speaker 3: A square ball from Australia around the rest of the earth.

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Speaker 1: Look, it's a serious question. I don't know.

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Speaker 2: This is a ridiculous question. Of course it's different. It's

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Speaker 2: a what what do you think could be the like,

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Speaker 2: bounce the ball on concrete, then bounce it on grass?

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Speaker 1: Know how to hit a ball? You know how to

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Speaker 1: hit a ball, doesn't matter what it bounces on.

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Speaker 2: I don't even know where you Yeah, you know what?

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Speaker 2: Can we get another? Who can we get in this podcast?

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Speaker 2: I don't even know the difference keeping someone in here

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Speaker 2: seen a couple of movies like I should have.

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Speaker 1: Sorry, can you talk about things being more Tennessee than

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Speaker 1: are Tennis?

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Speaker 2: Well that was okay, That wasn't where I was going

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Speaker 2: to go with Tennessee. But first of all, Clay so

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Speaker 2: Clay Friends, Open, Grass, Wimbledon. There are others obviously for

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Speaker 2: all these, but from the majors, Clay Friends Open grass,

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Speaker 2: Wimbledon hardcourt, US the French Open is the most Tennessee.

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Speaker 2: Although Wimbledon people would disagree with me because no food

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Speaker 2: and beverage in the stadium. Okay, it's all tennis. It's

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Speaker 2: all business in the in the stadium. Wimbledon people are now,

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Speaker 2: you know, popping champagne and the popping bottles in the

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Speaker 2: in the in center court. I mean still very sort

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Speaker 2: of you know, I got to wear whites and all

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Speaker 2: that stuff and blah blah blah.

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Speaker 3: But tennis is still the main show.

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Speaker 2: Tennis is still the main show. US Open. There are

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Speaker 2: no there are now no quiet moments between games. Ads

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Speaker 2: on the big screen and the video boards and the

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Speaker 2: blah blah blah behind the you know, the Cadillac logos

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Speaker 2: on the on the net, ads all over the place,

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Speaker 2: between points between sets, between matches, between matches, the like

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Speaker 2: like big New sick, like there would be at an

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Speaker 2: NBA basketball game or the Super Bowl or whatever. However,

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Speaker 2: in the stands at the US Open, it's now lots

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Speaker 2: and lots of people photographing themselves or their influencer friend

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Speaker 2: being photographed. Like you said, people photographing the photo photographers.

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Speaker 2: It's all that in the stands here I am during

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Speaker 2: the Alcoraz match.

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Speaker 3: In fact, there was a shot I think I even

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Speaker 3: saw one of them where someone was doing it got

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Speaker 3: pinged by the ball while he was doing a selfie

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Speaker 3: watching the ball.

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Speaker 1: It's amazing to take one for the team for the ground.

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Speaker 2: That's though a terrific content there were. I had the

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Speaker 2: good fortune to be at one of the fourth round

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Speaker 2: matches at center court at the US Open in good

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Speaker 2: seats and could see that four of the six or

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Speaker 2: eight people in a in a section near the near

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Speaker 2: the umpire's chair, maybe three or four rows back, so

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Speaker 2: center court, four rows back, super expensive seats. We're all

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Speaker 2: facing up towards the photograph during.

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Speaker 3: Points, which is astonishing.

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Speaker 1: I mean, it's like, do the players get pissed? Do

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Speaker 1: they get annoyed? Like is it distracted?

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Speaker 3: Djokovic got Yes, it gets noisy, like they don't like

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Speaker 3: if it's if it's really obvious that people are shuffling

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Speaker 3: around or talking about whatever. It's more like that if

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Speaker 3: you're not going to face me, and it's just they

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Speaker 3: don't care about that, care about the stuff that it's

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Speaker 3: just inverted, like the event is just a background for

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Speaker 3: what I'm doing right right, it's my, it's my.

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Speaker 2: That's the big change at the that I noticed that

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Speaker 2: the US open the event is a backdrop to me

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Speaker 2: being at the event for all my people who will

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Speaker 2: love that, who will be envious of the fact that

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Speaker 2: I'm here, But no filming me, filming me?

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Speaker 1: Which is which is? And that's the key is you

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Speaker 1: just hit it's the fomo. It's all it is about.

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Speaker 1: Is about making the people who aren't there feel like

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Speaker 1: ship that they're not the right.

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Speaker 3: Which is like you know, evolutionarily wired into people. Right

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Speaker 3: people want to feel like I'm leading a tribe. This

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Speaker 3: is all goes back to like ancient human behaviors like

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Speaker 3: so it's the reason why it's hard to shake this

440
00:20:12,359 --> 00:20:15,879
Speaker 3: is because we the people that we evolved from that

441
00:20:16,040 --> 00:20:17,959
Speaker 3: are are just at ances. We're all really good at

442
00:20:18,000 --> 00:20:21,320
Speaker 3: these because otherwise they wouldn't have made it, because you

443
00:20:21,359 --> 00:20:22,639
Speaker 3: had to be a member of a tribe. If you

444
00:20:22,640 --> 00:20:24,680
Speaker 3: were some weirdo that wasn't able to fit in in

445
00:20:24,760 --> 00:20:28,240
Speaker 3: your twenty person tribe and you were ostracized, you died, right,

446
00:20:28,280 --> 00:20:30,760
Speaker 3: So those genes fell out of the gene pool. So

447
00:20:30,800 --> 00:20:32,760
Speaker 3: if you were good at fitting into a tribe. You

448
00:20:32,800 --> 00:20:34,800
Speaker 3: were good at like making people feel like you had

449
00:20:34,880 --> 00:20:38,280
Speaker 3: influence and importance. You survived, and so that the instincts

450
00:20:38,320 --> 00:20:39,679
Speaker 3: that led to that this.

451
00:20:39,800 --> 00:20:41,159
Speaker 1: Is fucking depressing, thank you.

452
00:20:41,280 --> 00:20:41,440
Speaker 2: Yeah.

453
00:20:41,480 --> 00:20:41,840
Speaker 1: Yeah, yeah.

454
00:20:41,880 --> 00:20:47,760
Speaker 3: No, So we're like, you know, so the descendants of influencers.

455
00:20:48,320 --> 00:20:53,520
Speaker 2: Some that we we're only here because Orc somewhere downriver

456
00:20:53,560 --> 00:20:57,240
Speaker 2: in the Nile had a million followers.

457
00:20:56,280 --> 00:20:58,680
Speaker 3: Right up and down the river. He was well known.

458
00:21:00,200 --> 00:21:02,919
Speaker 1: That was saying you said the other day that like

459
00:21:03,000 --> 00:21:07,160
Speaker 1: that you had this realization that we are that you

460
00:21:07,200 --> 00:21:10,800
Speaker 1: had to have survived in the wilderness one hundred thousand

461
00:21:10,880 --> 00:21:13,119
Speaker 1: years ago. You had to be a sociopath because you

462
00:21:13,160 --> 00:21:15,600
Speaker 1: had to be willing to eat your own baby and

463
00:21:15,720 --> 00:21:18,840
Speaker 1: like kill your you know, your brother because you were

464
00:21:18,920 --> 00:21:19,880
Speaker 1: hungry and eat him.

465
00:21:19,920 --> 00:21:22,280
Speaker 3: And like we're the descendants of the bad guys in

466
00:21:22,359 --> 00:21:22,879
Speaker 3: Mad Max.

467
00:21:23,000 --> 00:21:23,240
Speaker 2: Yeah.

468
00:21:23,280 --> 00:21:30,240
Speaker 1: So we're the descendants not only of the influencer bad guys, right,

469
00:21:30,640 --> 00:21:32,760
Speaker 1: because that's what you needed to That's why I have

470
00:21:32,920 --> 00:21:36,080
Speaker 1: like no optimism that we walk away from this stuff

471
00:21:36,080 --> 00:21:37,720
Speaker 1: and say, oh, you know what, this is all.

472
00:21:38,520 --> 00:21:40,800
Speaker 3: This was all a really bad idea. You're walking away

473
00:21:40,800 --> 00:21:43,040
Speaker 3: from like three hundred thousand years of this bad idea.

474
00:21:43,160 --> 00:21:45,600
Speaker 2: It's like when Stephen Pinker wrote The Better Angels of

475
00:21:45,600 --> 00:21:48,320
Speaker 2: Our Nature, I was like, Yeah, that's not that's not happening.

476
00:21:49,400 --> 00:21:50,040
Speaker 3: It's not gonna work.

477
00:21:50,080 --> 00:21:52,560
Speaker 2: That's not what's gonna happening.

478
00:21:51,920 --> 00:21:52,400
Speaker 3: That I think.

479
00:21:52,760 --> 00:21:53,040
Speaker 1: I mean.

480
00:21:53,440 --> 00:21:58,080
Speaker 3: That's even more insidious is that people people feel more

481
00:21:58,280 --> 00:22:00,320
Speaker 3: sort of economic fragility in the sense that like, I

482
00:22:00,320 --> 00:22:03,199
Speaker 3: don't know where jobs are changing. People keep telling me

483
00:22:03,240 --> 00:22:06,520
Speaker 3: AI is taking jobs, and so more and more people

484
00:22:06,520 --> 00:22:10,360
Speaker 3: have this idea that I can monetize myself, I can

485
00:22:10,400 --> 00:22:13,520
Speaker 3: sell myself in lots of different ways. Well, that's true,

486
00:22:13,560 --> 00:22:15,639
Speaker 3: it's happening, right, But my point is it's like so

487
00:22:15,680 --> 00:22:18,440
Speaker 3: one of the drivings. So it's not just that we're

488
00:22:18,640 --> 00:22:20,840
Speaker 3: adapted to do this kind of thing. It's that there

489
00:22:20,840 --> 00:22:23,480
Speaker 3: are economic pressures that make people feel like this is

490
00:22:23,520 --> 00:22:25,399
Speaker 3: something that they need to do or they can do

491
00:22:25,840 --> 00:22:28,000
Speaker 3: even if everything else falls away. You know, this will

492
00:22:28,080 --> 00:22:29,880
Speaker 3: be my way out, this will be my way out. Right,

493
00:22:30,000 --> 00:22:32,400
Speaker 3: Hence the rise of like only fans and so all

494
00:22:32,440 --> 00:22:35,960
Speaker 3: of these different services that allow you to monetize your

495
00:22:36,000 --> 00:22:38,719
Speaker 3: time in ways that no one would have expected because

496
00:22:38,760 --> 00:22:41,640
Speaker 3: of this sense that I don't know, I don't have

497
00:22:41,680 --> 00:22:44,359
Speaker 3: a twenty year career in mind anymore, I don't know where.

498
00:22:44,840 --> 00:22:48,560
Speaker 1: So as AI takes more jobs, it means more influencers.

499
00:22:48,440 --> 00:22:52,240
Speaker 3: Means way more and vastly more and more influencers of influencers, right,

500
00:22:52,280 --> 00:22:54,159
Speaker 3: because it's all going to get stacked. This idea that

501
00:22:54,200 --> 00:22:57,080
Speaker 3: will for absolutely one of the next generations of influencers

502
00:22:57,080 --> 00:23:00,720
Speaker 3: will be someone who isn't who only tracks influence, right,

503
00:23:00,800 --> 00:23:04,040
Speaker 3: It'll be it all keeps getting nested more and more.

504
00:23:04,040 --> 00:23:05,960
Speaker 3: It's not just somebody who's built a giant audience like

505
00:23:06,000 --> 00:23:09,480
Speaker 3: mister Beast. It'll be someone who's an influencer who monitors

506
00:23:09,480 --> 00:23:12,440
Speaker 3: what influencers are doing, and then influencers follow them. It's

507
00:23:12,560 --> 00:23:13,760
Speaker 3: just gonna be come all the way down.

508
00:23:14,119 --> 00:23:18,880
Speaker 1: It's like the E Hollywood Show, but for influencers. Yeah, right,

509
00:23:18,920 --> 00:23:20,840
Speaker 1: but lots of them, but lots of them. And there's

510
00:23:20,840 --> 00:23:25,359
Speaker 1: also you see the thing recently about the the AI

511
00:23:25,600 --> 00:23:27,880
Speaker 1: actress that just got signed by an.

512
00:23:27,760 --> 00:23:30,640
Speaker 3: Age yea on one of the trade services.

513
00:23:30,200 --> 00:23:33,680
Speaker 1: Which seems a little like a little nonsense because I

514
00:23:33,680 --> 00:23:35,840
Speaker 1: don't think it's going to survive. But you're going to

515
00:23:35,880 --> 00:23:37,439
Speaker 1: see more of that too, oh of course.

516
00:23:37,480 --> 00:23:40,800
Speaker 3: But there's just this this cost collapse right, the cost

517
00:23:40,840 --> 00:23:44,080
Speaker 3: of doing all this stuff is so it's essentially free

518
00:23:44,160 --> 00:23:47,879
Speaker 3: for practical purposes, and so free is always compelling versus

519
00:23:47,920 --> 00:23:52,480
Speaker 3: a costly content provider, an actor, podcast host.

520
00:23:52,600 --> 00:23:54,879
Speaker 2: I mean, you've even got I think I read this

521
00:23:54,960 --> 00:23:58,600
Speaker 2: correctly the other day, that you've got like meta and

522
00:23:58,720 --> 00:24:01,080
Speaker 2: open AI saying we're going to have a you know,

523
00:24:01,080 --> 00:24:02,840
Speaker 2: we're going to have a set of reels that are

524
00:24:02,960 --> 00:24:05,520
Speaker 2: just you know, AI reels. Yeah, we're gonna have a

525
00:24:05,640 --> 00:24:07,879
Speaker 2: and the and they're going to create them and or

526
00:24:07,960 --> 00:24:11,439
Speaker 2: ais will create them for us to watch, but you

527
00:24:11,480 --> 00:24:14,240
Speaker 2: know it's also for their AIS to watch so they

528
00:24:14,280 --> 00:24:16,120
Speaker 2: can learn more about.

529
00:24:15,960 --> 00:24:17,800
Speaker 3: But that's why I think people get really like there

530
00:24:17,840 --> 00:24:20,000
Speaker 3: is this more video just term of people use all

531
00:24:20,000 --> 00:24:22,720
Speaker 3: the time AI slop, this idea that everything's going to

532
00:24:22,720 --> 00:24:25,600
Speaker 3: get there's this wave of crappy AI stuff that's coming

533
00:24:25,760 --> 00:24:28,480
Speaker 3: on social media and everywhere else. Like a huge fraction

534
00:24:28,560 --> 00:24:31,000
Speaker 3: of what's on social media is just AI generated. I

535
00:24:31,040 --> 00:24:33,080
Speaker 3: get all of that, but I actually think that's kind

536
00:24:33,119 --> 00:24:35,439
Speaker 3: of a mistaken way to think about things. I actually

537
00:24:35,440 --> 00:24:37,159
Speaker 3: think that, and I think I sent this to you

538
00:24:37,200 --> 00:24:41,120
Speaker 3: guys the other day, But there's Electronic Arts was acquired

539
00:24:41,320 --> 00:24:44,320
Speaker 3: in a large transaction is going to be by silver

540
00:24:44,400 --> 00:24:45,080
Speaker 3: Lake and so others.

541
00:24:45,080 --> 00:24:47,720
Speaker 2: But one of the reasons is five billion dollars under

542
00:24:47,760 --> 00:24:50,120
Speaker 2: fifty billion dollars. But who's counting, who's counting? That's twenty

543
00:24:50,200 --> 00:24:52,159
Speaker 2: billion of it. It's finance with debt, right, It's just

544
00:24:52,200 --> 00:24:53,040
Speaker 2: debt that you put back.

545
00:24:52,960 --> 00:24:55,479
Speaker 3: On their balance. Yeah, yeah, their problem.

546
00:24:55,680 --> 00:24:58,920
Speaker 2: Yeah. And then afterwards you go, why did you idiots

547
00:24:58,960 --> 00:25:01,359
Speaker 2: take on twenty billion dollar? Is it debt? Huh? Yeah?

548
00:25:01,359 --> 00:25:02,120
Speaker 2: Can you fix that?

549
00:25:02,200 --> 00:25:02,800
Speaker 3: Can you fix that?

550
00:25:02,880 --> 00:25:03,080
Speaker 2: Yeah?

551
00:25:03,119 --> 00:25:04,960
Speaker 3: But under the head what I thought was really interesting.

552
00:25:05,240 --> 00:25:07,760
Speaker 3: Lukashaw Bloomberg has some great stuff out over the last

553
00:25:07,800 --> 00:25:10,240
Speaker 3: while talking about the dynamics of the gaming market, where

554
00:25:10,760 --> 00:25:12,280
Speaker 3: this was the stat that blew mind. There's been a

555
00:25:12,280 --> 00:25:15,119
Speaker 3: doubling in the number of games on Steam, which is

556
00:25:15,119 --> 00:25:17,919
Speaker 3: one of the big game hosting platforms, just since twenty twenty.

557
00:25:18,119 --> 00:25:19,680
Speaker 3: There hasn't been a doubling in the number of people

558
00:25:19,680 --> 00:25:21,440
Speaker 3: who play games. There's been a double in the number

559
00:25:21,480 --> 00:25:23,040
Speaker 3: of games. So then you ask yourself, Okay, why is

560
00:25:23,080 --> 00:25:25,960
Speaker 3: that happening. Well, it's not because you know, more venture

561
00:25:26,000 --> 00:25:28,320
Speaker 3: money is flowing in. It's because it's gotten cheap and

562
00:25:28,359 --> 00:25:30,760
Speaker 3: easy to do games. Now, the reason why it's getting

563
00:25:30,840 --> 00:25:33,760
Speaker 3: cheaper and easier is because of tools like AI, and

564
00:25:33,960 --> 00:25:37,440
Speaker 3: the games are actually really really good. They're really good games,

565
00:25:38,040 --> 00:25:40,760
Speaker 3: so getting high ratings some places like Metacritic and others.

566
00:25:41,160 --> 00:25:44,160
Speaker 3: And so the point is worrying about all this crappy

567
00:25:44,200 --> 00:25:47,760
Speaker 3: AI stuff is kind of like a good problem to

568
00:25:47,760 --> 00:25:49,399
Speaker 3: have because it's easy to say, oh, well, no one

569
00:25:49,440 --> 00:25:52,159
Speaker 3: will use that as crappy. What's coming is lots of

570
00:25:52,320 --> 00:25:55,600
Speaker 3: really cheap good stuff. And the really cheap good stuff

571
00:25:55,640 --> 00:25:57,439
Speaker 3: is what's going to cause you know, the concept, the

572
00:25:57,480 --> 00:26:01,200
Speaker 3: really big consequence is going forward as evidence Electronic Arts

573
00:26:01,240 --> 00:26:04,160
Speaker 3: owns like FIFA and a host of other franchises, and

574
00:26:04,200 --> 00:26:08,000
Speaker 3: they can't make it work because they're facing this tsunami

575
00:26:08,640 --> 00:26:11,880
Speaker 3: of actually really good games that in part are facilitated

576
00:26:11,880 --> 00:26:13,680
Speaker 3: by people using AI tools and frameworks.

577
00:26:14,160 --> 00:26:16,960
Speaker 2: It's just getting too So what's happening? I think. I

578
00:26:17,000 --> 00:26:20,919
Speaker 2: think what I'm hearing Paul saying is EA is wisely

579
00:26:21,080 --> 00:26:24,760
Speaker 2: seeing the writing on the wall, and Okay, this isn't

580
00:26:24,800 --> 00:26:27,800
Speaker 2: going to stop. The doubling on Steam is going to

581
00:26:27,840 --> 00:26:30,000
Speaker 2: be tripling, is going to be quadrupling, is going to

582
00:26:30,040 --> 00:26:34,000
Speaker 2: be quintupling. Those games will be getting better and better

583
00:26:34,680 --> 00:26:39,720
Speaker 2: and my ability to create the next year's fit will

584
00:26:39,760 --> 00:26:42,560
Speaker 2: be halved and then thirded and then quartered.

585
00:26:42,600 --> 00:26:44,960
Speaker 3: And then even if I do the return, I'll get

586
00:26:44,960 --> 00:26:46,520
Speaker 3: on that it's going to be falling off, falling off,

587
00:26:46,560 --> 00:26:48,760
Speaker 3: flowing off. So this is we flatter My point is

588
00:26:48,760 --> 00:26:51,679
Speaker 3: we flatter ourselves by thinking the problem is AI slapped.

589
00:26:51,720 --> 00:26:53,560
Speaker 3: That's not the problem for the next few years. The

590
00:26:53,600 --> 00:26:55,439
Speaker 3: problem is going to be the EA problem, which is,

591
00:26:55,480 --> 00:26:58,160
Speaker 3: oh my god, there's an incredible amount of really good

592
00:26:58,200 --> 00:27:00,960
Speaker 3: stuff being produced and I can't My business isn't viable.

593
00:27:01,119 --> 00:27:02,480
Speaker 2: I can't. I can't fight my way through.

594
00:27:02,800 --> 00:27:05,160
Speaker 1: But don't you think that there's still you still need

595
00:27:05,160 --> 00:27:08,400
Speaker 1: a human being as a face for video games? You don't,

596
00:27:08,480 --> 00:27:11,440
Speaker 1: because no, I don't know who who made any video game? Right,

597
00:27:11,520 --> 00:27:13,080
Speaker 1: But when I don't watch movies.

598
00:27:13,480 --> 00:27:20,240
Speaker 3: No, you wouldn't say that though, So that's you saying that.

599
00:27:20,760 --> 00:27:22,879
Speaker 1: Industry is very sumer of video games.

600
00:27:22,920 --> 00:27:24,000
Speaker 3: The industry's very stars.

601
00:27:24,040 --> 00:27:26,240
Speaker 1: Oh you mean, like the people to play, they.

602
00:27:26,080 --> 00:27:28,320
Speaker 3: Know who creates stuff, they know who the engineers are.

603
00:27:28,240 --> 00:27:28,760
Speaker 2: The job.

604
00:27:29,280 --> 00:27:32,919
Speaker 1: Maybe maybe this, maybe this will prove the point. So Okay,

605
00:27:33,160 --> 00:27:36,679
Speaker 1: when Charlie Kirk got shot, there were like thousands and

606
00:27:36,760 --> 00:27:39,919
Speaker 1: thousands of books quote unquote books that ended up on

607
00:27:40,000 --> 00:27:42,960
Speaker 1: Amazon Kindle by the end of the day, right that

608
00:27:43,000 --> 00:27:45,440
Speaker 1: we're all created by AI. And I'm sure some of

609
00:27:45,480 --> 00:27:47,680
Speaker 1: them are probably pretty decent, like they you know, they

610
00:27:48,040 --> 00:27:51,040
Speaker 1: take everything and and his history of his life and

611
00:27:51,040 --> 00:27:53,040
Speaker 1: and what happened in the events and and so on.

612
00:27:53,080 --> 00:27:55,920
Speaker 1: I'm sure that. But no one read them because there's

613
00:27:55,920 --> 00:27:58,600
Speaker 1: no there's no author behind them. And so I guess

614
00:27:58,600 --> 00:27:59,679
Speaker 1: the question is, is.

615
00:27:59,320 --> 00:28:00,760
Speaker 3: I disagree with the part of that sense.

616
00:28:01,400 --> 00:28:02,640
Speaker 1: Why do you so no one.

617
00:28:02,560 --> 00:28:04,400
Speaker 3: Didn't read them because there was no author behind them,

618
00:28:04,440 --> 00:28:08,400
Speaker 3: that's what. Because there's too many and they don't care

619
00:28:08,440 --> 00:28:08,840
Speaker 3: that much.

620
00:28:08,880 --> 00:28:11,280
Speaker 1: So how do you in the if that is the case,

621
00:28:11,760 --> 00:28:14,080
Speaker 1: if it continues to quarter and half and so on

622
00:28:14,119 --> 00:28:17,119
Speaker 1: and so forth, and there's it's everywhere, how do you

623
00:28:17,200 --> 00:28:21,359
Speaker 1: define what you what? What I what I'm going to consume?

624
00:28:21,359 --> 00:28:23,000
Speaker 1: How do I decide which book I'm going to read?

625
00:28:23,040 --> 00:28:24,520
Speaker 1: And so on and so forth?

626
00:28:24,640 --> 00:28:27,400
Speaker 3: From a viability standpoint, I don't think that's not that's

627
00:28:27,440 --> 00:28:28,080
Speaker 3: not the problem.

628
00:28:28,080 --> 00:28:28,719
Speaker 1: What's the problem.

629
00:28:28,720 --> 00:28:31,119
Speaker 3: The problem is that all of these industries are going

630
00:28:31,200 --> 00:28:34,679
Speaker 3: to get crushed. They're going to get crushed because consumers

631
00:28:34,720 --> 00:28:37,360
Speaker 3: don't care as much as producers would like to think

632
00:28:37,400 --> 00:28:40,320
Speaker 3: they do, and the costs are collapsing. The volume is

633
00:28:40,360 --> 00:28:42,040
Speaker 3: going to soar and it's not going to be AI

634
00:28:42,120 --> 00:28:45,320
Speaker 3: slop anymore. That's we we've gotten through. This has actually

635
00:28:45,320 --> 00:28:48,440
Speaker 3: been the good period where it's mostly crap. The EA

636
00:28:48,600 --> 00:28:50,960
Speaker 3: story is telling you that going forward, the problem isn't

637
00:28:50,960 --> 00:28:53,560
Speaker 3: going to be crap. It's going to be scorched earth.

638
00:28:54,200 --> 00:28:57,760
Speaker 3: Then it's going to be viable to produce most of

639
00:28:57,800 --> 00:29:01,480
Speaker 3: the things that we've we've rely in books, movies, television,

640
00:29:02,400 --> 00:29:05,320
Speaker 3: legal briefs like pick your pick. All of this stuff

641
00:29:05,520 --> 00:29:07,080
Speaker 3: is not as going to go from being slopped to

642
00:29:07,120 --> 00:29:09,080
Speaker 3: being very very very good, which is going to make

643
00:29:09,120 --> 00:29:12,560
Speaker 3: it unviable to actually be in that business. That's the problem.

644
00:29:12,560 --> 00:29:15,160
Speaker 1: But if you have let's just take TV for a second, right,

645
00:29:15,320 --> 00:29:22,840
Speaker 1: If you have AI creating amazing TV games, TV games, Sorry.

646
00:29:21,200 --> 00:29:22,600
Speaker 3: That sounds great. What is a TV game?

647
00:29:22,680 --> 00:29:25,280
Speaker 1: I'm sure it will exist. Actually, that's a whole separate.

648
00:29:25,560 --> 00:29:28,240
Speaker 3: Interacted to CD ROMs. You know, these interactive CITs. I've

649
00:29:28,240 --> 00:29:29,040
Speaker 3: heard they're going to be huge.

650
00:29:29,080 --> 00:29:30,720
Speaker 1: Now there is a whole thing that there's a whole

651
00:29:30,760 --> 00:29:33,760
Speaker 1: theory in Hollywood that people think that that video games

652
00:29:33,760 --> 00:29:35,800
Speaker 1: and TV or film are going to kind of meld.

653
00:29:35,840 --> 00:29:39,720
Speaker 1: And you'll say, but I think with AI it's it's estentially,

654
00:29:39,800 --> 00:29:43,880
Speaker 1: But put that aside for one second. So we you

655
00:29:44,040 --> 00:29:45,960
Speaker 1: there's a film that Dick wants to talk about that

656
00:29:46,040 --> 00:29:48,720
Speaker 1: he watched, right, But if he just watched it, that's

657
00:29:48,760 --> 00:29:50,640
Speaker 1: like him talking telling us about the dream he had

658
00:29:50,720 --> 00:29:53,320
Speaker 1: last night and we didn't if we didn't see it.

659
00:29:53,360 --> 00:29:56,400
Speaker 1: If it's like individualized, So aren't there going to be

660
00:29:56,480 --> 00:30:00,520
Speaker 1: at the same time, you know, uh, these kind of

661
00:30:00,640 --> 00:30:03,440
Speaker 1: these mediums that we are all going to consume together.

662
00:30:03,720 --> 00:30:04,840
Speaker 2: No, you don't think so.

663
00:30:04,920 --> 00:30:06,880
Speaker 3: No, Like I totally disagree. No, take a look at

664
00:30:06,920 --> 00:30:10,840
Speaker 3: the TV ratings. A top rated show today would have

665
00:30:10,840 --> 00:30:13,400
Speaker 3: been canceled thirty years ago, right, that's how that's how

666
00:30:13,480 --> 00:30:16,640
Speaker 3: in relative terms that its ratings are. So that's because

667
00:30:16,640 --> 00:30:20,560
Speaker 3: of this complete fractioning of the audience. Right, the audience

668
00:30:20,720 --> 00:30:24,080
Speaker 3: is still out there, but they're watching ten thousand things,

669
00:30:24,080 --> 00:30:25,360
Speaker 3: so a thing that's successful to.

670
00:30:25,360 --> 00:30:29,160
Speaker 2: They're watching micro dramas, they're watching YouTube, They're watching ninety

671
00:30:29,280 --> 00:30:30,640
Speaker 2: thousand different things on YouTube.

672
00:30:30,680 --> 00:30:33,120
Speaker 3: So this goes to your point though, But a shared experience,

673
00:30:33,240 --> 00:30:34,960
Speaker 3: there's no shared experience as a matter of fact, the

674
00:30:35,000 --> 00:30:38,240
Speaker 3: audience is so dispersed that everything out there today would

675
00:30:38,240 --> 00:30:39,760
Speaker 3: have been canceled thirty years ago.

676
00:30:39,760 --> 00:30:43,640
Speaker 2: Right, And it's I mean this sort of follows obviously,

677
00:30:43,920 --> 00:30:48,000
Speaker 2: but it's why the political spectrum in the US is

678
00:30:48,040 --> 00:30:51,040
Speaker 2: so you know, black, and you know, it's so polarized

679
00:30:51,040 --> 00:30:54,240
Speaker 2: now because I'm getting my own. It used to be

680
00:30:54,840 --> 00:30:57,840
Speaker 2: we all watched Walter Cronkite at six pm and then

681
00:30:57,960 --> 00:31:00,680
Speaker 2: everyone had the same information. Right now, it's what are

682
00:31:00,720 --> 00:31:02,240
Speaker 2: you talking about? That's not true?

683
00:31:02,800 --> 00:31:04,720
Speaker 3: You know, I got this dude, there's a cast.

684
00:31:04,800 --> 00:31:07,520
Speaker 2: There's this dude over here that just you know that

685
00:31:07,600 --> 00:31:10,320
Speaker 2: says that you're crazy and those things are all not true.

686
00:31:10,400 --> 00:31:12,880
Speaker 2: And I mean it's sort of obviously follows, and it's

687
00:31:12,960 --> 00:31:13,920
Speaker 2: just getting worse right.

688
00:31:13,840 --> 00:31:15,440
Speaker 3: When, which goes back to this point that no, I

689
00:31:15,440 --> 00:31:17,200
Speaker 3: don't think there will be shared experiences at all. As

690
00:31:17,240 --> 00:31:18,680
Speaker 3: a matter of fact, that I think that will look,

691
00:31:18,720 --> 00:31:20,280
Speaker 3: we'll look back with some.

692
00:31:20,480 --> 00:31:24,720
Speaker 1: Strongness, but if you but okay, look at Spotify, for example,

693
00:31:24,960 --> 00:31:28,720
Speaker 1: the top you know, the top ten. Remember the numbers.

694
00:31:28,720 --> 00:31:33,600
Speaker 1: It's forty six million songs have zero listens, oh yeah,

695
00:31:33,680 --> 00:31:37,000
Speaker 1: and the top ten have billions of listens. And they

696
00:31:37,040 --> 00:31:38,920
Speaker 1: do think we need those. And if you look at

697
00:31:38,920 --> 00:31:42,640
Speaker 1: concerts like I mean, think about you know, go look

698
00:31:43,000 --> 00:31:45,959
Speaker 1: through any newspaper. Anytime a new invention comes along, they're like, oh,

699
00:31:45,960 --> 00:31:48,440
Speaker 1: people will never leave with their house again, the phone,

700
00:31:47,920 --> 00:31:51,479
Speaker 1: the phonograph, that, this, that, and the other. We have

701
00:31:51,520 --> 00:31:54,360
Speaker 1: concerts that have a million people like so we still

702
00:31:54,400 --> 00:31:56,440
Speaker 1: want that shared experience. This is what I think that.

703
00:31:56,640 --> 00:31:58,520
Speaker 1: This is where I think that the you know, we

704
00:31:58,800 --> 00:32:01,800
Speaker 1: I've kids that are in ten and on a weekend,

705
00:32:01,880 --> 00:32:03,040
Speaker 1: we're like, what the fuck are we going to do

706
00:32:03,080 --> 00:32:05,720
Speaker 1: this weekend? And we tried like is there a movie?

707
00:32:05,800 --> 00:32:07,240
Speaker 2: You say that to you in your ten years old?

708
00:32:07,360 --> 00:32:08,720
Speaker 2: What the fuck are we going to do this week

709
00:32:08,720 --> 00:32:09,160
Speaker 2: this weekend?

710
00:32:09,200 --> 00:32:14,640
Speaker 1: And they say, daddy, stop swearing. But they want to

711
00:32:14,680 --> 00:32:17,400
Speaker 1: go to the movies. They want that experience.

712
00:32:17,000 --> 00:32:18,960
Speaker 2: Like the way I took this all right, hard left,

713
00:32:19,040 --> 00:32:19,720
Speaker 2: hard left turn.

714
00:32:19,880 --> 00:32:21,920
Speaker 3: Yeah, well that'll be the sound bite.

715
00:32:23,720 --> 00:32:27,560
Speaker 1: They want that experience of an of of going to

716
00:32:27,680 --> 00:32:30,520
Speaker 1: a thing. And so I just don't think I hear

717
00:32:30,520 --> 00:32:32,200
Speaker 1: what you're saying. But I just don't believe that that

718
00:32:32,480 --> 00:32:34,040
Speaker 1: all collective experience is vanished.

719
00:32:34,120 --> 00:32:36,160
Speaker 3: That's not it's not what that's a false dichotomy.

720
00:32:36,200 --> 00:32:38,120
Speaker 2: I mean, it's not Yeah, he's not saying all he's

721
00:32:38,120 --> 00:32:42,840
Speaker 2: saying it's becoming more. It's the dispersed part is a dispersion.

722
00:32:43,040 --> 00:32:45,680
Speaker 3: It's the part that matters that periodically that people will

723
00:32:45,760 --> 00:32:47,880
Speaker 3: go to mass events is kind of short of it. Yeah,

724
00:32:48,080 --> 00:32:50,480
Speaker 3: that's it's the rarity of the mass event that makes

725
00:32:50,520 --> 00:32:53,440
Speaker 3: them viable. People want them because it's like, well, Taylor

726
00:32:53,440 --> 00:32:55,440
Speaker 3: Swift may not be touring again for another.

727
00:32:55,600 --> 00:32:58,880
Speaker 2: Yeah that Bryan's and University of Michigan STA I'm going

728
00:32:58,920 --> 00:33:00,960
Speaker 2: to say going to see Yeah, I'm going to that.

729
00:33:01,080 --> 00:33:03,280
Speaker 2: But then those hundred and ten thousand people don't go

730
00:33:03,320 --> 00:33:05,280
Speaker 2: home and watch the same TV show. They don't go

731
00:33:05,320 --> 00:33:07,640
Speaker 2: home and watch Seinfeld anymore. They go home and like,

732
00:33:07,680 --> 00:33:11,240
Speaker 2: this person's watching you know, you know, she's your daddy,

733
00:33:11,280 --> 00:33:14,680
Speaker 2: and this person's watching them you know micro you know, And.

734
00:33:14,600 --> 00:33:16,600
Speaker 3: Even if they're watching the same thing, they're not necessarily

735
00:33:16,600 --> 00:33:18,320
Speaker 3: been watching it at the same time. Yeah, right, this

736
00:33:18,400 --> 00:33:20,240
Speaker 3: is my favorite. It is like people I'll talk to

737
00:33:20,440 --> 00:33:22,280
Speaker 3: couples who are watching the same show and I'm like, oh,

738
00:33:22,280 --> 00:33:24,280
Speaker 3: how did you Oh, he's watching it in the morning.

739
00:33:24,320 --> 00:33:26,880
Speaker 3: I watched Yeah, Because they don't even have to have

740
00:33:26,960 --> 00:33:28,360
Speaker 3: like time synchronized.

741
00:33:27,880 --> 00:33:29,920
Speaker 2: I'm watching under the covers while he's snoring.

742
00:33:31,360 --> 00:33:32,600
Speaker 3: So no, I don't think that's the way it's going

743
00:33:32,640 --> 00:33:34,440
Speaker 3: to play it at all. And the data suggests that's

744
00:33:34,520 --> 00:33:38,240
Speaker 3: exactly what's happening, is that everything's becoming flatten distributed, not

745
00:33:38,320 --> 00:33:42,840
Speaker 3: time synchronized, and the events are the rarity, not there's

746
00:33:42,920 --> 00:33:45,880
Speaker 3: those aren't the cultural the cultural touchstones anymore.

747
00:33:46,360 --> 00:33:47,640
Speaker 1: But you'll still go to a tennis game.

748
00:33:48,560 --> 00:33:50,360
Speaker 2: Yeah, Can I say a couple more things about the

749
00:33:50,440 --> 00:33:54,960
Speaker 2: interesting thing about the tennis this last year? Of course? Yeah,

750
00:33:55,120 --> 00:33:57,680
Speaker 2: here's here's two more interesting things. One, can I just

751
00:33:58,080 --> 00:34:00,520
Speaker 2: go please, I want you to interrupt me regularly.

752
00:34:00,720 --> 00:34:02,320
Speaker 1: No, I just I just have to go back to

753
00:34:02,360 --> 00:34:04,320
Speaker 1: the to the to the grass versus.

754
00:34:04,040 --> 00:34:06,440
Speaker 2: Clay versus hardcore?

755
00:34:06,600 --> 00:34:10,840
Speaker 1: Is hardcore? Isn't like I know Sinner is the best player?

756
00:34:10,920 --> 00:34:12,600
Speaker 2: Right? Alcoraz is now number one?

757
00:34:12,640 --> 00:34:12,920
Speaker 3: Correct?

758
00:34:12,920 --> 00:34:16,239
Speaker 1: So let's just take Alcarez. Is Alcoraz as good on

759
00:34:16,320 --> 00:34:18,160
Speaker 1: all three of those they play?

760
00:34:18,280 --> 00:34:22,719
Speaker 2: Very sorry, Paul's rolling his eyes. What listen, let me

761
00:34:22,800 --> 00:34:27,480
Speaker 2: reframe my answer before Paul the polymath yells at me

762
00:34:27,520 --> 00:34:31,759
Speaker 2: and gives me a statistic about Alcoraz's ability to hit

763
00:34:32,200 --> 00:34:36,319
Speaker 2: return winners on the three different services correct, they play.

764
00:34:37,160 --> 00:34:42,400
Speaker 2: The three services play to your strengths, to a player's strengths,

765
00:34:42,520 --> 00:34:46,839
Speaker 2: very very differently. Serve speed works better on you know,

766
00:34:47,000 --> 00:34:49,759
Speaker 2: on grass, where the ball skids off the grass and

767
00:34:49,800 --> 00:34:54,120
Speaker 2: it's faster. Clay slows the ball down, so it's there's

768
00:34:54,200 --> 00:34:57,520
Speaker 2: less serve and volley you're playing these long baseline rallies

769
00:34:57,560 --> 00:34:59,520
Speaker 2: where the you know, the ball is going slow enough

770
00:34:59,560 --> 00:35:04,760
Speaker 2: to be able to be speedy, serves can be returned, etcetera, etcetera.

771
00:35:04,880 --> 00:35:09,560
Speaker 2: So generally speaking, the three surfaces tend to result in

772
00:35:09,760 --> 00:35:14,719
Speaker 2: very very different semi finals, quarterfinals matches in this world though,

773
00:35:14,760 --> 00:35:17,720
Speaker 2: now where Center and Alcarez seem to be so much

774
00:35:17,760 --> 00:35:20,200
Speaker 2: better than everybody else. It's kind of like the I

775
00:35:20,200 --> 00:35:22,480
Speaker 2: don't know whatever I want to call it, the Federer

776
00:35:22,600 --> 00:35:25,160
Speaker 2: Nadal area of its going to be in the finals

777
00:35:25,160 --> 00:35:28,000
Speaker 2: in all three of them. But the three surfaces are

778
00:35:28,080 --> 00:35:28,760
Speaker 2: very very different.

779
00:35:28,840 --> 00:35:30,799
Speaker 3: They're very different. But the weird thing is is those

780
00:35:30,960 --> 00:35:33,439
Speaker 3: players are the dominant players on all the surfaces, which

781
00:35:33,480 --> 00:35:37,200
Speaker 3: is historically really unusual, right, And so what's interesting is

782
00:35:37,239 --> 00:35:38,759
Speaker 3: you're seeing this now for the first time in a

783
00:35:38,800 --> 00:35:43,040
Speaker 3: couple of sports, for the first time actually in cycling,

784
00:35:43,440 --> 00:35:46,640
Speaker 3: in cycling. Historically, there was people who are really good

785
00:35:46,640 --> 00:35:48,560
Speaker 3: at multi day stage races like the Tour de France,

786
00:35:48,719 --> 00:35:50,200
Speaker 3: and there are people who really good at one day

787
00:35:50,280 --> 00:35:52,800
Speaker 3: races like Perry Rubey, you know where you go banging

788
00:35:52,840 --> 00:35:55,359
Speaker 3: along on cobbles and whatever else, and those two people,

789
00:35:55,480 --> 00:35:58,040
Speaker 3: those two groups of people were very different for in

790
00:35:58,080 --> 00:36:01,880
Speaker 3: the current era. What's really interesting is that the same riders,

791
00:36:02,280 --> 00:36:03,759
Speaker 3: or at least a couple of the same riders, are

792
00:36:03,800 --> 00:36:06,640
Speaker 3: now dominant in both types of in both types of events.

793
00:36:06,719 --> 00:36:09,240
Speaker 3: There are dominant in multi day stage races and dominant

794
00:36:09,239 --> 00:36:11,600
Speaker 3: in single day races in exactly the same way as

795
00:36:11,640 --> 00:36:15,880
Speaker 3: Center and Skinner, Center, Center, Center and one of them,

796
00:36:16,040 --> 00:36:18,640
Speaker 3: one of them, Center, Skinner and Alchoraiz are dominant on

797
00:36:18,680 --> 00:36:19,640
Speaker 3: all surfaces and tennis.

798
00:36:19,680 --> 00:36:22,200
Speaker 1: Why is this so? That's so my He's going to

799
00:36:22,280 --> 00:36:25,239
Speaker 1: sign a paper, he read a paper, he wrote one.

800
00:36:25,400 --> 00:36:30,040
Speaker 3: That's right, I actually read and bro one he did no,

801
00:36:30,200 --> 00:36:30,560
Speaker 3: it neither.

802
00:36:32,480 --> 00:36:32,520
Speaker 2: No.

803
00:36:32,760 --> 00:36:36,560
Speaker 3: So it's the argument is it's better training techniques and

804
00:36:36,560 --> 00:36:39,880
Speaker 3: the sharing of best practices that people historically didn't realize.

805
00:36:39,920 --> 00:36:43,920
Speaker 3: Here's what a really good player on clay or grass

806
00:36:44,040 --> 00:36:48,400
Speaker 3: or hard surfaces or cobbles that many of the things

807
00:36:48,440 --> 00:36:50,960
Speaker 3: were treated is almost in a superstitious way that oh,

808
00:36:51,000 --> 00:36:54,120
Speaker 3: I can't beat Raphael.

809
00:36:54,360 --> 00:36:54,799
Speaker 2: I just can't.

810
00:36:54,840 --> 00:36:57,200
Speaker 3: So I talked myself out of it right away. And

811
00:36:57,280 --> 00:37:00,080
Speaker 3: so there's this there's yet again, much like in a

812
00:37:00,200 --> 00:37:02,400
Speaker 3: there's this flattening going on where it's like all of

813
00:37:02,440 --> 00:37:05,440
Speaker 3: these former hierarchies of being dominant on clay, man I

814
00:37:05,480 --> 00:37:08,040
Speaker 3: was bad on hardcore, it's being dominant in one day races,

815
00:37:08,280 --> 00:37:09,799
Speaker 3: man I was going to fall apart in the tour.

816
00:37:10,000 --> 00:37:13,400
Speaker 3: These are falling away because they're being revealed as superstitions.

817
00:37:13,680 --> 00:37:16,239
Speaker 3: And that might be good because now all of a

818
00:37:16,280 --> 00:37:18,640
Speaker 3: sudden there's more competition in all these things, but it's

819
00:37:18,680 --> 00:37:21,040
Speaker 3: also kind of flattens everything because it's like it used

820
00:37:21,040 --> 00:37:23,399
Speaker 3: to be there were these wacky Spanish dudes who were

821
00:37:23,400 --> 00:37:27,000
Speaker 3: really good, like on clay in Paris, and then you

822
00:37:27,040 --> 00:37:28,959
Speaker 3: never saw them again for the rest of the ye, right,

823
00:37:29,239 --> 00:37:32,080
Speaker 3: But now these guys never win anything because they can't

824
00:37:32,080 --> 00:37:34,720
Speaker 3: win it all anymore because the top players are better,

825
00:37:35,520 --> 00:37:38,640
Speaker 3: better across all surfaces. And this leads to this kind

826
00:37:38,680 --> 00:37:41,000
Speaker 3: of like, oh, it's those two guys again, right, It's

827
00:37:41,040 --> 00:37:42,400
Speaker 3: not like, oh, you know when I go to Wimbledon,

828
00:37:42,440 --> 00:37:43,919
Speaker 3: there's going to be something different, or if I watch

829
00:37:43,960 --> 00:37:45,680
Speaker 3: the Tour de France, there's going to be different people,

830
00:37:46,000 --> 00:37:47,920
Speaker 3: or if I go to this different social medium that

831
00:37:47,960 --> 00:37:49,640
Speaker 3: it's going to be different artists. No, it's the same

832
00:37:49,680 --> 00:37:51,799
Speaker 3: people everywhere, which is one of the reasons why to

833
00:37:51,800 --> 00:37:54,040
Speaker 3: take it right back to the original point that the

834
00:37:54,080 --> 00:37:57,400
Speaker 3: reason why this dominance emerges at the top of Spotify

835
00:37:57,480 --> 00:38:00,680
Speaker 3: is because there's this incredible convergence of it tension on

836
00:38:00,800 --> 00:38:03,719
Speaker 3: these people who are really good at Taylor Swift's really

837
00:38:03,760 --> 00:38:06,520
Speaker 3: good at social media, she's really good at creating.

838
00:38:06,160 --> 00:38:08,440
Speaker 2: Hooky soft forming, she's good at performing.

839
00:38:08,719 --> 00:38:11,799
Speaker 3: So these people are all rising to this level where

840
00:38:11,840 --> 00:38:14,600
Speaker 3: they become dominant and everything else just sort of falls away.

841
00:38:14,800 --> 00:38:16,919
Speaker 3: But everyone else is fighting for scraps at the edges.

842
00:38:17,000 --> 00:38:18,799
Speaker 3: Right There's there's tons o them doing it. But that's

843
00:38:18,840 --> 00:38:21,200
Speaker 3: the thing that's really interesting, is this flattening and kind

844
00:38:21,200 --> 00:38:22,520
Speaker 3: of homogenizing of everything.

845
00:38:22,920 --> 00:38:25,960
Speaker 2: I'll say one more thing about tennis my observation this

846
00:38:26,040 --> 00:38:31,840
Speaker 2: last year, which is that people psychologically have a hard

847
00:38:31,960 --> 00:38:36,400
Speaker 2: time thinking about reality in a way that's different from

848
00:38:36,440 --> 00:38:38,120
Speaker 2: the way they used to think about reality. And here's

849
00:38:38,120 --> 00:38:41,160
Speaker 2: the example I give you at Wimbledon this year they

850
00:38:41,200 --> 00:38:45,680
Speaker 2: went to all automatic judges. So the fault serving faults,

851
00:38:45,719 --> 00:38:48,720
Speaker 2: you know, the balls out or hit the ball along

852
00:38:48,760 --> 00:38:51,320
Speaker 2: on a shot, it's called out. That is no longer

853
00:38:51,719 --> 00:38:55,320
Speaker 2: people standing at the line looking there and judging whether

854
00:38:55,360 --> 00:38:58,560
Speaker 2: it's interrupt That's still true. At the French Open it's

855
00:38:58,640 --> 00:39:02,839
Speaker 2: humans and the US Open it's cameras and you know,

856
00:39:03,440 --> 00:39:07,320
Speaker 2: machines and they the cameras call it or the camera

857
00:39:07,400 --> 00:39:09,200
Speaker 2: calls it and then it makes a sound, you know,

858
00:39:10,800 --> 00:39:13,440
Speaker 2: it makes a human sound out like someone yelled it

859
00:39:13,480 --> 00:39:15,919
Speaker 2: out in the court. No that it makes it sound.

860
00:39:15,960 --> 00:39:17,680
Speaker 2: Look it's a human yelling at because people want to

861
00:39:17,680 --> 00:39:19,799
Speaker 2: feel like, oh, it's still being called it was called out.

862
00:39:20,040 --> 00:39:22,279
Speaker 2: Here's the no, here's the the point I want to make.

863
00:39:23,680 --> 00:39:26,600
Speaker 2: Even though it's the machine doing it now and it's

864
00:39:26,640 --> 00:39:31,319
Speaker 2: automated and using cameras, after the call is made, they

865
00:39:31,440 --> 00:39:35,120
Speaker 2: still show the replay on the on the video monitor,

866
00:39:35,600 --> 00:39:40,839
Speaker 2: like with the animated ball landing outside the line and

867
00:39:40,920 --> 00:39:42,799
Speaker 2: you know, and where it landed and then and then

868
00:39:42,960 --> 00:39:46,520
Speaker 2: like out and people when they see the replay go,

869
00:39:46,960 --> 00:39:52,480
Speaker 2: oh wait, the machine is the one that made the

870
00:39:52,600 --> 00:39:57,040
Speaker 2: video that called it out. It wasn't gonna be different then,

871
00:39:57,520 --> 00:39:59,680
Speaker 2: like but they still have this like it was called out,

872
00:39:59,760 --> 00:40:02,640
Speaker 2: but baby was in. Let's see the replay, Like what,

873
00:40:02,840 --> 00:40:06,720
Speaker 2: let me tell you how the replay is this. People

874
00:40:06,840 --> 00:40:12,200
Speaker 2: go literally from the whole crowd, Oh it was so close, Like.

875
00:40:12,640 --> 00:40:13,840
Speaker 3: That's really interesting, honest.

876
00:40:13,880 --> 00:40:17,360
Speaker 2: The umpire auto now the umpire basically keeps presses buttons

877
00:40:17,400 --> 00:40:19,600
Speaker 2: on the machine and keeps score and resets them. I

878
00:40:19,640 --> 00:40:22,919
Speaker 2: think they look, I'm sure they're was there an umpire listening?

879
00:40:23,000 --> 00:40:25,279
Speaker 2: They're like, I do wait more than that. Okay, you

880
00:40:25,320 --> 00:40:29,080
Speaker 2: know they go dirty, love, you know, quiet, please, thank you.

881
00:40:29,600 --> 00:40:30,640
Speaker 2: That's about that.

882
00:40:30,920 --> 00:40:33,799
Speaker 3: Yeah, but it's that's a really so they're actually applauding

883
00:40:34,040 --> 00:40:36,160
Speaker 3: the simulation of the real thing.

884
00:40:36,320 --> 00:40:39,279
Speaker 2: Yeah. Well, and also that it came true, like what

885
00:40:39,320 --> 00:40:42,040
Speaker 2: the thing called was actually the right call. Like it's

886
00:40:42,120 --> 00:40:44,480
Speaker 2: every time going to be what the machine called. The

887
00:40:44,520 --> 00:40:45,680
Speaker 2: machine is making the movie.

888
00:40:45,800 --> 00:40:47,560
Speaker 3: Yeah, it's not going to randomize it and say, oh,

889
00:40:47,560 --> 00:40:48,560
Speaker 3: I'm going to prove myself wrong.

890
00:40:49,080 --> 00:40:50,839
Speaker 2: Yeah, oh I called that went in, but it was out.

891
00:40:51,800 --> 00:40:54,279
Speaker 1: You're actually you're making I know you've suggested this so

892
00:40:54,320 --> 00:40:56,440
Speaker 1: many times that we should I should read because I'm

893
00:40:56,440 --> 00:40:59,080
Speaker 1: sure you've read that. David Foster Wallace on tennis you're

894
00:40:59,080 --> 00:41:00,560
Speaker 1: actually making me want to read it.

895
00:41:00,719 --> 00:41:02,080
Speaker 2: Yeah, I mean.

896
00:41:02,239 --> 00:41:07,000
Speaker 3: It's tremendous, it's good, but it's also immediately it's vestigial,

897
00:41:07,160 --> 00:41:09,359
Speaker 3: like the game has changed so much since he wrote

898
00:41:09,600 --> 00:41:12,239
Speaker 3: his famous essay string Theory and wrote one about who

899
00:41:12,280 --> 00:41:15,520
Speaker 3: is it? Michael Chang? I think, and these players were

900
00:41:16,440 --> 00:41:18,719
Speaker 3: wouldn't have survived in today's game. Yeah, right, So the

901
00:41:18,760 --> 00:41:20,520
Speaker 3: game has changed a lot since because he was a

902
00:41:20,520 --> 00:41:23,799
Speaker 3: college player, David Foster Wallas and then he wrote about

903
00:41:23,800 --> 00:41:25,680
Speaker 3: Michael Chang, who was this American sort of power but

904
00:41:25,719 --> 00:41:27,960
Speaker 3: they were called power baseliners, guys who standed to back

905
00:41:28,000 --> 00:41:29,640
Speaker 3: the court and whack the living crap and.

906
00:41:29,600 --> 00:41:31,680
Speaker 2: Just the ball, just rip the ball from the back.

907
00:41:32,360 --> 00:41:35,040
Speaker 3: But those guys didn't come forward, they wouldn't go to

908
00:41:35,080 --> 00:41:37,520
Speaker 3: the net and play. And again back to this idea

909
00:41:37,560 --> 00:41:40,759
Speaker 3: of the flattening of the sport. Everybody does everything, no

910
00:41:40,760 --> 00:41:43,080
Speaker 3: one sits at the back, and the Michael Chang's don't

911
00:41:43,160 --> 00:41:44,960
Speaker 3: exist because you can't sit at the back and just

912
00:41:45,000 --> 00:41:46,640
Speaker 3: whack it. You also have to be able to sprint

913
00:41:46,680 --> 00:41:47,879
Speaker 3: to the net and do a drop shot.

914
00:41:48,120 --> 00:41:50,759
Speaker 2: Center and Elkarez are both the hardest hitting you know,

915
00:41:51,560 --> 00:41:54,120
Speaker 2: two of the harder hitting guys from the baseline, but

916
00:41:54,200 --> 00:41:57,919
Speaker 2: also remarkable coming forward and playing servant Volley. Right, so.

917
00:42:23,440 --> 00:42:25,520
Speaker 1: Should we do a media of the week. We want

918
00:42:25,560 --> 00:42:27,840
Speaker 1: to start this thing where we do like a media.

919
00:42:28,040 --> 00:42:29,239
Speaker 1: But you had something you wanted to.

920
00:42:29,160 --> 00:42:32,640
Speaker 2: Talk about, Well, it'll be my book. Well I saw,

921
00:42:33,040 --> 00:42:34,960
Speaker 2: and you have a book you want to talk about too, Yeah,

922
00:42:35,000 --> 00:42:36,040
Speaker 2: but I just won't shut up about it.

923
00:42:36,120 --> 00:42:37,600
Speaker 1: Yeah, well that's probably a whole episode.

924
00:42:37,920 --> 00:42:38,960
Speaker 3: Okay, I'll still talk.

925
00:42:39,040 --> 00:42:40,080
Speaker 1: Let's let's let's hear it.

926
00:42:40,120 --> 00:42:43,479
Speaker 2: I saw one battle after another, and first of all,

927
00:42:43,680 --> 00:42:46,880
Speaker 2: you will be pleased to know it's at least loosely

928
00:42:47,000 --> 00:42:50,520
Speaker 2: maybe more than loosely based on I saw Benshon's Vineland. Yeah. Yeah,

929
00:42:51,680 --> 00:42:55,880
Speaker 2: and it's if Paul Thomas Anderson. I keep on to say,

930
00:42:56,440 --> 00:43:00,200
Speaker 2: like anytime it's three names, I almost always interject some

931
00:43:00,360 --> 00:43:04,680
Speaker 2: other person's name is the middle, almost said Paul Wes Anderson. Anyway,

932
00:43:04,880 --> 00:43:09,520
Speaker 2: Paul Thomas Anderson, there will be blood and boogie knights

933
00:43:09,520 --> 00:43:13,719
Speaker 2: and yea many many, many many other filmmaker. Yeah, and

934
00:43:13,760 --> 00:43:17,480
Speaker 2: it's it's awesome and the acting is awesome. I mean,

935
00:43:18,400 --> 00:43:23,080
Speaker 2: Sean Penn will certainly be nominated for Best Supporting Actor

936
00:43:23,239 --> 00:43:27,040
Speaker 2: and without having seen any of the other films that

937
00:43:27,200 --> 00:43:29,040
Speaker 2: may or may not come out the rest of the year.

938
00:43:29,440 --> 00:43:33,160
Speaker 2: I mean, he'll be He's exceptional, and as is Benicio

939
00:43:33,200 --> 00:43:36,360
Speaker 2: del Toro and DiCaprio and the rest is great. Is

940
00:43:36,360 --> 00:43:39,200
Speaker 2: a great movie, and the cinematography is amazing. It is long,

941
00:43:39,760 --> 00:43:45,960
Speaker 2: is long, It's very long. Yeah, I remember one of

942
00:43:45,960 --> 00:43:50,560
Speaker 2: my favorites, one of my favorite Yeah, one of my

943
00:43:50,600 --> 00:43:53,680
Speaker 2: favorite reviews of the book One hundred Years of Solitude

944
00:43:54,120 --> 00:43:57,360
Speaker 2: was I couldn't help thinking whether thirty eight Years of

945
00:43:57,360 --> 00:43:59,640
Speaker 2: Solitude might have been a lot better.

946
00:44:00,800 --> 00:44:02,080
Speaker 1: One of my favorite books.

947
00:44:01,800 --> 00:44:04,360
Speaker 2: By the way. Yeah, yeah, no, it's it's two hours

948
00:44:04,360 --> 00:44:07,520
Speaker 2: and forty five minutes, but it's very fast moving. Really,

949
00:44:07,600 --> 00:44:11,759
Speaker 2: there's not a lot of you know, now, let's there's

950
00:44:11,800 --> 00:44:14,640
Speaker 2: not a lot of let's pause to go reflect on these,

951
00:44:16,520 --> 00:44:19,440
Speaker 2: you know, the villain's origin story, like, it's it's fast moving,

952
00:44:19,600 --> 00:44:24,600
Speaker 2: it's and it's well shot. And the books, the book's fantastic,

953
00:44:24,640 --> 00:44:27,920
Speaker 2: great Stoner book stuff. Yeah, it's yeah, it's it's not

954
00:44:28,320 --> 00:44:31,200
Speaker 2: it's very it's very closely a ligne to I would

955
00:44:31,239 --> 00:44:33,040
Speaker 2: say the book, I don't know how much he would

956
00:44:33,080 --> 00:44:35,200
Speaker 2: say he based on Vineland, but it's it's right there.

957
00:44:35,320 --> 00:44:38,719
Speaker 1: I read that. Did Paul Wes Anderson optioned the book?

958
00:44:40,120 --> 00:44:44,520
Speaker 2: You're gonna do it, You're gonna make me start? This

959
00:44:44,600 --> 00:44:47,160
Speaker 2: is don't start on the Hollywood actually miology.

960
00:44:47,239 --> 00:44:48,280
Speaker 3: I think it actually was optioned.

961
00:44:48,920 --> 00:44:50,720
Speaker 2: I don't know what that even means. Did he option

962
00:44:50,840 --> 00:44:51,320
Speaker 2: the book.

963
00:44:51,360 --> 00:44:53,319
Speaker 3: Paid for it, as opposed to saying I read this

964
00:44:53,360 --> 00:44:54,279
Speaker 3: and it made me think of this.

965
00:44:54,360 --> 00:44:57,719
Speaker 2: Oh yeah, right, okay, yeah, okay, that's a very good explanation.

966
00:44:57,800 --> 00:44:59,719
Speaker 2: By the way, he just paid to say. Look, I'm

967
00:44:59,800 --> 00:45:02,120
Speaker 2: this is basically Pineland the movie. Okay.

968
00:45:02,239 --> 00:45:04,200
Speaker 3: I think that was the book that he wrote. He

969
00:45:04,280 --> 00:45:08,080
Speaker 3: won the National Book Critics Award, and he went into

970
00:45:08,160 --> 00:45:10,319
Speaker 3: hiding because he didn't want to collect the awards, so

971
00:45:10,320 --> 00:45:12,720
Speaker 3: he ran to Mexico and was hiding at dis pension.

972
00:45:12,920 --> 00:45:14,719
Speaker 3: He was hiding in Mexico, and then he didn't like

973
00:45:14,760 --> 00:45:16,319
Speaker 3: being in Mexico, so he went and hit in northern

974
00:45:16,360 --> 00:45:17,960
Speaker 3: California and he said, well, screw it, I have to

975
00:45:17,960 --> 00:45:19,920
Speaker 3: write a book now. So I think he wrote Vineland

976
00:45:19,920 --> 00:45:22,040
Speaker 3: while he was in hiding from the National Book Critics.

977
00:45:22,040 --> 00:45:24,360
Speaker 1: That's amazing. I haven't read Vineland.

978
00:45:24,480 --> 00:45:25,439
Speaker 3: Oh it's great, it's great.

979
00:45:25,840 --> 00:45:29,880
Speaker 2: It's like Zoyd Wheeler, zoid Wheeler Zoid Wheeler is the

980
00:45:30,360 --> 00:45:31,279
Speaker 2: hero if you will.

981
00:45:31,480 --> 00:45:33,840
Speaker 3: Yeah, it's like if The Big Lebowski was a spy movie.

982
00:45:34,239 --> 00:45:38,520
Speaker 2: Yes, yeah, it's actually good. Another good. Great. You should

983
00:45:38,560 --> 00:45:42,839
Speaker 2: write little summaries for on like rotten Tomaico or tweet things, yeah,

984
00:45:42,920 --> 00:45:43,640
Speaker 2: or tweet things.

985
00:45:44,120 --> 00:45:47,600
Speaker 1: Was there something? Was it like a uniquely different film

986
00:45:47,800 --> 00:45:48,560
Speaker 1: or was it just.

987
00:45:48,520 --> 00:45:50,160
Speaker 2: You know, I would never see your tweet because the

988
00:45:50,200 --> 00:45:53,400
Speaker 2: algorithm would surface it because it have to say, like,

989
00:45:53,960 --> 00:45:59,480
Speaker 2: you know, it's like he was a spy movie and

990
00:45:59,520 --> 00:46:01,480
Speaker 2: also you're asshole.

991
00:46:01,239 --> 00:46:04,000
Speaker 3: That's right. Yeah, that's right without.

992
00:46:03,719 --> 00:46:04,720
Speaker 1: A mental finger emoji.

993
00:46:04,840 --> 00:46:09,360
Speaker 3: Yeah, some political hashtags, right, yeah, it would be perfect.

994
00:46:09,440 --> 00:46:11,120
Speaker 2: Right yeah.

995
00:46:11,160 --> 00:46:13,399
Speaker 1: Wait, so was there something? Was it just a good

996
00:46:13,440 --> 00:46:15,279
Speaker 1: movie or was there something that was like the wasat

997
00:46:15,480 --> 00:46:15,879
Speaker 1: not enough?

998
00:46:16,160 --> 00:46:16,799
Speaker 2: Like I just am.

999
00:46:16,719 --> 00:46:19,239
Speaker 4: Curious, like the media of the week, I know, but

1000
00:46:19,280 --> 00:46:22,640
Speaker 4: it's not that's media. That is there's something about it

1001
00:46:22,680 --> 00:46:25,120
Speaker 4: that that you were like, yeah, it was good for example,

1002
00:46:25,360 --> 00:46:28,960
Speaker 4: well I liked it for example, I saw Sinners.

1003
00:46:28,960 --> 00:46:31,759
Speaker 2: Did you see Sinners yet? Or no? I don't like

1004
00:46:31,800 --> 00:46:32,480
Speaker 2: horror movies.

1005
00:46:32,600 --> 00:46:33,359
Speaker 1: It's not a horror movie.

1006
00:46:33,440 --> 00:46:34,359
Speaker 2: I like a horror movie.

1007
00:46:34,400 --> 00:46:35,959
Speaker 3: I only made it through the first fifteen minutes.

1008
00:46:36,000 --> 00:46:41,200
Speaker 2: Oh, my god, the music horror movie. Guy like Somethin's

1009
00:46:41,280 --> 00:46:42,839
Speaker 2: going to get stabbed in the throat and I don't

1010
00:46:42,840 --> 00:46:43,360
Speaker 2: want to see that.

1011
00:46:43,360 --> 00:46:44,759
Speaker 3: I don't think I made it to the horror part.

1012
00:46:44,800 --> 00:46:46,359
Speaker 3: Is there horror in the first fifteen minutes. I wasn't

1013
00:46:46,600 --> 00:46:47,200
Speaker 3: closer to the.

1014
00:46:47,120 --> 00:46:49,680
Speaker 2: First the first act almost never horror in the first

1015
00:46:49,760 --> 00:46:50,480
Speaker 2: fifteen minutes.

1016
00:46:51,040 --> 00:46:52,799
Speaker 3: You got to build, I got to draw to make

1017
00:46:52,800 --> 00:46:53,200
Speaker 3: you care for.

1018
00:46:54,800 --> 00:46:58,760
Speaker 1: I hate horror too, but but Center Centers the musical

1019
00:46:58,840 --> 00:47:02,480
Speaker 1: numbers were phenomenal. It was like, unlike anything I've ever

1020
00:47:02,560 --> 00:47:03,040
Speaker 1: seen before.

1021
00:47:03,520 --> 00:47:05,040
Speaker 2: Is that what you were looking for from me? The

1022
00:47:05,120 --> 00:47:08,000
Speaker 2: musical numbers? I thought you're looking for like a political

1023
00:47:08,800 --> 00:47:09,600
Speaker 2: but if there was a.

1024
00:47:09,840 --> 00:47:12,920
Speaker 1: Cool way, they shut it with a smash no match cuts,

1025
00:47:13,080 --> 00:47:15,880
Speaker 1: smash cuts and match cuts. And yeah, it was shot

1026
00:47:16,120 --> 00:47:17,239
Speaker 1: very very well.

1027
00:47:17,320 --> 00:47:19,399
Speaker 2: There there are a couple scenes in the movie where

1028
00:47:19,480 --> 00:47:23,040
Speaker 2: you I don't normally pay attention to, Oh, that's remarkably

1029
00:47:23,080 --> 00:47:26,279
Speaker 2: shot and it's actually making building the tension, and there

1030
00:47:26,280 --> 00:47:27,880
Speaker 2: are a few points in the movie where you're like,

1031
00:47:27,960 --> 00:47:31,080
Speaker 2: this is like I'm getting more stressed out just from

1032
00:47:31,120 --> 00:47:33,880
Speaker 2: the cinematography, which is which was great. I mean the

1033
00:47:33,920 --> 00:47:35,720
Speaker 2: points in the movie where it's trying to build a tension,

1034
00:47:35,760 --> 00:47:38,839
Speaker 2: and the filmmaking, not the character action does it.

1035
00:47:39,520 --> 00:47:40,480
Speaker 1: I'm excited to see it.

1036
00:47:41,239 --> 00:47:41,680
Speaker 2: Have you seen it?

1037
00:47:41,680 --> 00:47:43,200
Speaker 1: You're not going to five minutes?

1038
00:47:43,360 --> 00:47:44,080
Speaker 3: I want to make it through.

1039
00:47:44,239 --> 00:47:45,280
Speaker 2: Yeah you will. It's great.

1040
00:47:45,360 --> 00:47:47,680
Speaker 3: Really, Yeah, it's so hard. I've tried.

1041
00:47:48,640 --> 00:47:48,800
Speaker 1: You know.

1042
00:47:49,880 --> 00:47:53,080
Speaker 2: You can go watch a movie like noon. You have

1043
00:47:53,120 --> 00:47:55,040
Speaker 2: to go at like nine pm, and you're like, it's midnight.

1044
00:47:55,080 --> 00:47:58,360
Speaker 2: I'm tired noon. What do I have to do between

1045
00:47:58,360 --> 00:47:58,919
Speaker 2: noon and three?

1046
00:47:59,440 --> 00:48:03,560
Speaker 3: Watch movie? That's all I and not tweet. I do

1047
00:48:03,600 --> 00:48:04,560
Speaker 3: a lot of not tweeting.

1048
00:48:04,680 --> 00:48:04,919
Speaker 2: Yeah.

1049
00:48:05,040 --> 00:48:06,839
Speaker 1: My niece I asked her if she saw Doune and

1050
00:48:06,880 --> 00:48:08,959
Speaker 1: she said she was like, yeah, I watched. I watched

1051
00:48:08,960 --> 00:48:10,960
Speaker 1: the fifteen minute version. I was like, what, watch the

1052
00:48:10,960 --> 00:48:13,720
Speaker 1: fifteen minute version. She's like, oh, they cut them someone

1053
00:48:13,880 --> 00:48:15,640
Speaker 1: someone will download and cut them up and put them

1054
00:48:15,719 --> 00:48:17,720
Speaker 1: make them into fifteen little short clips on TikTok.

1055
00:48:17,760 --> 00:48:18,400
Speaker 2: That's what I watched.

1056
00:48:18,400 --> 00:48:20,759
Speaker 1: And that's how So that's what you could do with

1057
00:48:20,840 --> 00:48:22,120
Speaker 1: a Paul wes Anderson movie.

1058
00:48:23,200 --> 00:48:24,840
Speaker 2: No, you got to you can go see the movie.

1059
00:48:25,239 --> 00:48:28,400
Speaker 2: It's any it's an easy it's an easy start.

1060
00:48:28,440 --> 00:48:29,799
Speaker 3: I meant to watch a movie the other day, but

1061
00:48:29,840 --> 00:48:39,959
Speaker 3: I didn't that's true.

1062
00:48:39,960 --> 00:48:40,239
Speaker 2: I did.

1063
00:48:40,280 --> 00:48:42,879
Speaker 1: I had a plan it just did you like downloaded

1064
00:48:42,960 --> 00:48:45,520
Speaker 1: and then just forgot to play. Yeah did you even

1065
00:48:45,520 --> 00:48:46,719
Speaker 1: make it to the television? No?

1066
00:48:46,840 --> 00:48:49,120
Speaker 3: Then I started playing back ovin Yeah you know how

1067
00:48:49,120 --> 00:48:49,600
Speaker 3: that happens.

1068
00:48:49,719 --> 00:48:52,760
Speaker 2: Yeah, I do. Let's talk about his book?

1069
00:48:53,440 --> 00:48:53,880
Speaker 1: Should we do?

1070
00:48:54,000 --> 00:48:54,279
Speaker 2: Should we?

1071
00:48:54,280 --> 00:48:56,360
Speaker 3: Should we talk about the book or you want to,

1072
00:48:57,120 --> 00:48:59,319
Speaker 3: I'll talk, But I'm just going to say, like, yep,

1073
00:48:59,280 --> 00:49:00,960
Speaker 3: it'd be great to get a sometimes. So the book

1074
00:49:01,360 --> 00:49:07,280
Speaker 3: that I've been like want obnoxiously pushing it on people.

1075
00:49:07,280 --> 00:49:09,719
Speaker 2: You're usually here's a book and pass you know full

1076
00:49:10,760 --> 00:49:12,759
Speaker 2: if you don't like it, see yuh, But this one

1077
00:49:12,800 --> 00:49:14,040
Speaker 2: you're yeah, yeah, yeah.

1078
00:49:13,840 --> 00:49:18,839
Speaker 3: And it's for me. This is Stephen Kaye's book on immortality.

1079
00:49:19,160 --> 00:49:22,520
Speaker 3: And what I liked about it is I'm not a

1080
00:49:22,560 --> 00:49:24,880
Speaker 3: big fan of these big history like Gunstorms and Steel,

1081
00:49:25,000 --> 00:49:27,040
Speaker 3: the Jared Diamond stuff, these big history books that oh,

1082
00:49:27,080 --> 00:49:29,319
Speaker 3: that's how the universe works, because usually it's just not

1083
00:49:29,360 --> 00:49:31,799
Speaker 3: how the universe works. But this book, what I liked

1084
00:49:31,800 --> 00:49:34,680
Speaker 3: about it was he has this really compelling explanation for

1085
00:49:34,800 --> 00:49:37,359
Speaker 3: why most of the fucked upitness of humans in terms

1086
00:49:37,400 --> 00:49:39,840
Speaker 3: of why did he do that? Why are people acting

1087
00:49:39,880 --> 00:49:42,120
Speaker 3: this way? And a lot of it under the hood,

1088
00:49:42,680 --> 00:49:45,360
Speaker 3: dating back three hundred thousand years. Is this doomed quest

1089
00:49:45,400 --> 00:49:47,840
Speaker 3: to live forever, and it takes four different forms, he

1090
00:49:47,960 --> 00:49:50,600
Speaker 3: argues in the book. There's the don't die version, which

1091
00:49:50,640 --> 00:49:52,640
Speaker 3: we are all seeing all over again. And he wrote

1092
00:49:52,640 --> 00:49:55,440
Speaker 3: this before Brian Johnson started doing his don't die movement.

1093
00:49:55,840 --> 00:49:59,359
Speaker 3: So there's the don't die version. There's the biological immortality version,

1094
00:49:59,360 --> 00:50:01,560
Speaker 3: which is we can just fix everything. There's the well,

1095
00:50:01,800 --> 00:50:03,640
Speaker 3: I'll just transfer my intelligence.

1096
00:50:03,400 --> 00:50:05,880
Speaker 2: So as we go through, the don't die version is

1097
00:50:06,280 --> 00:50:08,399
Speaker 2: here's all the stuff you need to do to not

1098
00:50:08,520 --> 00:50:09,760
Speaker 2: even decay.

1099
00:50:09,480 --> 00:50:10,440
Speaker 3: Right, to not even decay.

1100
00:50:10,480 --> 00:50:13,120
Speaker 2: And the biological one is don't worry. We got a

1101
00:50:13,120 --> 00:50:14,560
Speaker 2: new arm for you. In the left, well, no, we'll

1102
00:50:14,560 --> 00:50:16,520
Speaker 2: fix stuff. Yeah, so we'll fix We've got a new

1103
00:50:16,560 --> 00:50:18,359
Speaker 2: liver for you. We got to figure it out. We're

1104
00:50:18,360 --> 00:50:19,920
Speaker 2: going to figure out how to fix your heart, right, And.

1105
00:50:19,960 --> 00:50:21,960
Speaker 1: Then the book is split up into these four quadrant

1106
00:50:21,960 --> 00:50:22,440
Speaker 1: these four.

1107
00:50:22,360 --> 00:50:25,920
Speaker 3: Quad and then the next piece is that it's fine,

1108
00:50:26,120 --> 00:50:30,280
Speaker 3: bodies are just you know, useless vessels, so we'll transfer

1109
00:50:30,320 --> 00:50:32,960
Speaker 3: your intelligence to something else. And that's taken various forms

1110
00:50:33,120 --> 00:50:36,480
Speaker 3: over history, which is including like being reborn as someone

1111
00:50:36,520 --> 00:50:38,719
Speaker 3: else one of the you know, the notions behind sort

1112
00:50:38,719 --> 00:50:41,200
Speaker 3: of the Egyptian mummies and what have you. So, so

1113
00:50:41,440 --> 00:50:44,080
Speaker 3: that's the third version is and then our current iteration

1114
00:50:44,160 --> 00:50:44,840
Speaker 3: of that is I'll just.

1115
00:50:44,840 --> 00:50:45,799
Speaker 1: Transfer to upload you.

1116
00:50:45,840 --> 00:50:47,920
Speaker 3: We'll upload you to an AI or whatever else and

1117
00:50:47,960 --> 00:50:50,680
Speaker 3: you can continue forever. And then the fourth version is

1118
00:50:50,680 --> 00:50:52,440
Speaker 3: is that you'll just develop, you'll have a legacy. It

1119
00:50:52,480 --> 00:50:54,320
Speaker 3: does none of these things actually matter, but you'll have

1120
00:50:54,320 --> 00:50:56,880
Speaker 3: a legacy, which is you'll be like Achilles, you'll establish

1121
00:50:57,160 --> 00:50:59,600
Speaker 3: you'll be talked about with veneration for thousands of years

1122
00:50:59,600 --> 00:51:01,480
Speaker 3: because of all of the influences.

1123
00:51:01,800 --> 00:51:07,040
Speaker 2: By the way, that's my favorite one, because there must

1124
00:51:07,080 --> 00:51:10,040
Speaker 2: be ten thousand let's just say a thousand. There must

1125
00:51:10,040 --> 00:51:13,239
Speaker 2: be a thousand people in the world right now who

1126
00:51:13,360 --> 00:51:17,480
Speaker 2: think and if I do X, I'll be talked about

1127
00:51:17,480 --> 00:51:18,720
Speaker 2: for thousands of years.

1128
00:51:18,840 --> 00:51:21,120
Speaker 1: Thousand years. Here's say most of the years.

1129
00:51:21,160 --> 00:51:25,799
Speaker 2: Here's what will happen. Eighty years from now, people will

1130
00:51:25,840 --> 00:51:31,120
Speaker 2: go who like that? Like that? And that snap of

1131
00:51:31,160 --> 00:51:32,799
Speaker 2: a finger, it's over.

1132
00:51:32,960 --> 00:51:34,919
Speaker 3: Well, these cites the stat in the book that there's

1133
00:51:34,960 --> 00:51:38,720
Speaker 3: some like does he just's like seventy years later, pretty

1134
00:51:38,800 --> 00:51:41,759
Speaker 3: much uniformly, everyone's forgotten yes, it's about a seventy year.

1135
00:51:42,040 --> 00:51:44,160
Speaker 1: Does he argue how does he does he argue for

1136
00:51:44,280 --> 00:51:46,879
Speaker 1: these things? Does he just it's just this historical look

1137
00:51:46,920 --> 00:51:48,360
Speaker 1: at like this is what's happened in the future, and

1138
00:51:48,400 --> 00:51:49,320
Speaker 1: this is what's going to happen.

1139
00:51:49,640 --> 00:51:52,480
Speaker 3: So it's a look at how these things are drivers

1140
00:51:52,520 --> 00:51:55,960
Speaker 3: of all these human behaviors, from religion everything to tech

1141
00:51:56,040 --> 00:52:00,600
Speaker 3: utopianism to the rise of the medicalization of of human

1142
00:52:00,640 --> 00:52:02,759
Speaker 3: life where we're constantly trying to treat things and as

1143
00:52:02,800 --> 00:52:06,160
Speaker 3: a result, people spend more lives living with morbidity, meaning

1144
00:52:06,160 --> 00:52:08,320
Speaker 3: that you're ill for well, our live spans are longer,

1145
00:52:08,360 --> 00:52:10,480
Speaker 3: but we spend twenty the last twenty years ill like

1146
00:52:10,560 --> 00:52:14,839
Speaker 3: this mortality versus morbidity paradox. So he talks about each

1147
00:52:14,880 --> 00:52:17,760
Speaker 3: of these pieces as drivers of it, as Doomed attempts

1148
00:52:17,840 --> 00:52:19,840
Speaker 3: to quest after him, and it's been a driver of

1149
00:52:19,920 --> 00:52:23,080
Speaker 3: human behavior for three hundred thousand years, and it's really compelling.

1150
00:52:23,080 --> 00:52:25,040
Speaker 3: It's just a wonderful book on that.

1151
00:52:25,160 --> 00:52:27,040
Speaker 1: Does he have any theories on like what's next and

1152
00:52:27,040 --> 00:52:28,759
Speaker 1: how it's.

1153
00:52:28,440 --> 00:52:30,840
Speaker 3: It's going to proceed? All four will persist, as a

1154
00:52:30,880 --> 00:52:32,799
Speaker 3: matter of fact, it'll probably get jumbled, but we'll have

1155
00:52:33,200 --> 00:52:37,640
Speaker 3: religious versions of AI uploads of people who want to

1156
00:52:37,680 --> 00:52:40,399
Speaker 3: also have a legacy. So they're all like everything they're

1157
00:52:40,400 --> 00:52:42,160
Speaker 3: doing to mash up, there'll be a mashup of all

1158
00:52:42,160 --> 00:52:43,000
Speaker 3: of these things going forward.

1159
00:52:43,040 --> 00:52:43,239
Speaker 2: Yeah.

1160
00:52:43,800 --> 00:52:46,799
Speaker 1: I feel like the legacy, going back to that has

1161
00:52:46,840 --> 00:52:50,520
Speaker 1: always been the worst problem with Silicon Valley because it's

1162
00:52:50,560 --> 00:52:52,640
Speaker 1: the thing that they all care about more than anything.

1163
00:52:53,680 --> 00:52:55,640
Speaker 2: Like, yeah, and as Paul said, they forget about. You're

1164
00:52:55,680 --> 00:52:57,919
Speaker 2: going to be forgotten about after seventy years. It's don't

1165
00:52:57,960 --> 00:52:58,919
Speaker 2: matter which one of you.

1166
00:52:59,320 --> 00:53:02,480
Speaker 3: Was best selling author plumber, it's going to be the

1167
00:53:02,480 --> 00:53:03,600
Speaker 3: same sny years.

1168
00:53:04,960 --> 00:53:05,160
Speaker 2: Yeah.

1169
00:53:05,520 --> 00:53:07,719
Speaker 3: Yeah, So but I just found it like, for the

1170
00:53:07,760 --> 00:53:11,440
Speaker 3: first time someone had really captured all of these moving

1171
00:53:11,480 --> 00:53:13,879
Speaker 3: parts and put it together in a way where it's like, yeah,

1172
00:53:13,880 --> 00:53:15,960
Speaker 3: I completely see how a. And this is the point

1173
00:53:16,000 --> 00:53:18,080
Speaker 3: he makes over and over that it was adaptive. It

1174
00:53:18,120 --> 00:53:21,799
Speaker 3: was super important to have that, and to have that

1175
00:53:21,840 --> 00:53:25,919
Speaker 3: as in our evolutionary quiver, that you could actually fall back. Oh,

1176
00:53:25,960 --> 00:53:28,080
Speaker 3: this is why we're all together because we all believe

1177
00:53:28,080 --> 00:53:30,759
Speaker 3: in these things. We're all believe in this, the the

1178
00:53:30,760 --> 00:53:33,080
Speaker 3: the immortality of the soul, or we all believe in this.

1179
00:53:33,520 --> 00:53:36,440
Speaker 3: That gave you a common experience that allowed you to

1180
00:53:36,880 --> 00:53:38,960
Speaker 3: cohere with other groups. And this is and he's really

1181
00:53:39,000 --> 00:53:41,800
Speaker 3: not really good at showing how something that was highly

1182
00:53:41,840 --> 00:53:44,839
Speaker 3: adaptive for most of human history not so much.

1183
00:53:44,880 --> 00:53:46,240
Speaker 1: Now I'm going to talk about my book.

1184
00:53:46,760 --> 00:53:47,279
Speaker 3: You have a book.

1185
00:53:47,360 --> 00:53:49,879
Speaker 1: No, I was going we were too immediately media the week.

1186
00:53:49,880 --> 00:53:51,080
Speaker 3: I didn't even know if you like reading we have

1187
00:53:51,120 --> 00:53:53,520
Speaker 3: like this, let's wrap it up.

1188
00:53:53,719 --> 00:53:55,160
Speaker 2: Let's wrap it up on your media the week.

1189
00:53:55,280 --> 00:53:57,520
Speaker 1: I have a couple. But this is the big closing.

1190
00:53:58,040 --> 00:53:59,600
Speaker 1: I'm going to ask you, guys, which one you want

1191
00:53:59,600 --> 00:54:04,279
Speaker 1: to hear about this this week? Mark Ronson's new book

1192
00:54:04,280 --> 00:54:06,719
Speaker 1: called Night People, which is about about DJing in the

1193
00:54:06,800 --> 00:54:08,360
Speaker 1: nineteen nineties. I did not think I was going to

1194
00:54:08,440 --> 00:54:08,680
Speaker 1: like it.

1195
00:54:08,760 --> 00:54:11,640
Speaker 2: I loved it the DJ Mark Ronson, the DJ Mark Ronson,

1196
00:54:11,840 --> 00:54:12,480
Speaker 2: all right.

1197
00:54:12,520 --> 00:54:15,880
Speaker 1: Or I just reread No Country for All Men? But

1198
00:54:16,760 --> 00:54:18,799
Speaker 1: I've read the book and I read the script at

1199
00:54:18,800 --> 00:54:19,960
Speaker 1: the same time, because I was really fair.

1200
00:54:20,040 --> 00:54:20,600
Speaker 2: They're the same.

1201
00:54:20,719 --> 00:54:21,839
Speaker 1: They're exactly the same.

1202
00:54:22,320 --> 00:54:24,440
Speaker 2: If you asked when the Coen Brothers were asked like

1203
00:54:24,760 --> 00:54:26,880
Speaker 2: how do you write the script, they basically say something,

1204
00:54:26,920 --> 00:54:29,399
Speaker 2: you know the Coen Brothers is basically some point, Well,

1205
00:54:29,440 --> 00:54:31,520
Speaker 2: I said it the typewriter and he held the book.

1206
00:54:31,520 --> 00:54:32,759
Speaker 2: He held the book spine open.

1207
00:54:33,000 --> 00:54:36,720
Speaker 1: It was so I always had heard this, but when

1208
00:54:37,320 --> 00:54:39,799
Speaker 1: reading the script and reading the book at the same time,

1209
00:54:39,880 --> 00:54:42,719
Speaker 1: it was I mean, well, what's fascinating. So then I

1210
00:54:42,760 --> 00:54:45,480
Speaker 1: started researching. It turns out that Corn McCarthy wanted to

1211
00:54:45,520 --> 00:54:48,200
Speaker 1: be a screenwriter too, even though he's the greatest living

1212
00:54:48,239 --> 00:54:50,839
Speaker 1: writer of the last fifty years, I would argue. And

1213
00:54:51,320 --> 00:54:54,040
Speaker 1: he wrote No Country for All meant as a script,

1214
00:54:54,400 --> 00:54:57,480
Speaker 1: took it to Hollywood. They said this is garbage. No

1215
00:54:57,480 --> 00:54:59,759
Speaker 1: one wanted it. So then he went back and wrote

1216
00:54:59,760 --> 00:55:01,400
Speaker 1: it a the book, and then the com Brothers came

1217
00:55:01,440 --> 00:55:02,279
Speaker 1: along and then wrote it.

1218
00:55:02,280 --> 00:55:02,760
Speaker 2: As the script.

1219
00:55:02,800 --> 00:55:05,719
Speaker 3: But said, my Cormick McCarthy story, I was sitting. I

1220
00:55:05,760 --> 00:55:07,640
Speaker 3: was sitting beside it at the Santa Fe Institute. Well,

1221
00:55:07,640 --> 00:55:09,359
Speaker 3: actually I went in and there was an empty seat

1222
00:55:09,400 --> 00:55:11,920
Speaker 3: beside him, and I was like, that's Cormick McCarthy. I

1223
00:55:11,960 --> 00:55:13,520
Speaker 3: have to sit beside him. So I sat down beside

1224
00:55:13,560 --> 00:55:16,960
Speaker 3: McCarthy at the seminar. Didn't say anything though, because I'm like, well,

1225
00:55:17,000 --> 00:55:18,360
Speaker 3: what do you say anyone? I mean, I you know,

1226
00:55:18,400 --> 00:55:19,799
Speaker 3: I like your books. I would like punch me in

1227
00:55:19,800 --> 00:55:21,640
Speaker 3: the face if I said, And so I sat there,

1228
00:55:21,640 --> 00:55:22,880
Speaker 3: and I sat there, and I sat there, and I

1229
00:55:22,920 --> 00:55:24,399
Speaker 3: was finally figured out what I was going to say,

1230
00:55:24,440 --> 00:55:26,200
Speaker 3: and I went like this, and he got up and

1231
00:55:26,200 --> 00:55:29,520
Speaker 3: went to the restaurant. That's the best.

1232
00:55:30,200 --> 00:55:32,920
Speaker 1: He's like, probably in the face something I.

1233
00:55:32,880 --> 00:55:34,120
Speaker 3: Was about to talk to me. I gotta leave.

1234
00:55:34,160 --> 00:55:36,440
Speaker 2: All right, we can do a whole episode on No

1235
00:55:36,480 --> 00:55:38,600
Speaker 2: Country for all Man. We should one of my favorite books,

1236
00:55:38,600 --> 00:55:42,160
Speaker 2: Slash and movies, but talk about Mark Ronson's book.

1237
00:55:42,880 --> 00:55:43,880
Speaker 1: I So, I was.

1238
00:55:44,000 --> 00:55:45,600
Speaker 2: I just I was.

1239
00:55:46,239 --> 00:55:48,680
Speaker 1: I lived in the nineties, you know, in New York.

1240
00:55:49,200 --> 00:55:51,480
Speaker 2: Good, all right, you know what I thought, You're going

1241
00:55:51,560 --> 00:55:55,880
Speaker 2: to have something more compelling, of more compelling. Driver. Well,

1242
00:55:56,360 --> 00:55:59,239
Speaker 2: I read it because I was also alive in the nineties.

1243
00:56:00,000 --> 00:56:05,320
Speaker 1: Regularly, we both have legs.

1244
00:56:04,880 --> 00:56:06,880
Speaker 2: And arms in the head, all right, come on.

1245
00:56:08,400 --> 00:56:10,000
Speaker 1: I just I don't know why I ended up reading.

1246
00:56:10,080 --> 00:56:12,920
Speaker 1: I just I really don't like non fiction books and

1247
00:56:12,960 --> 00:56:15,279
Speaker 1: I only really read fiction. But I was like, oh,

1248
00:56:15,280 --> 00:56:17,600
Speaker 1: I'm interested in this time. And I have to say,

1249
00:56:18,040 --> 00:56:21,279
Speaker 1: phenomenal writer. I was really impressed with his writing. He

1250
00:56:21,800 --> 00:56:27,560
Speaker 1: tells a story, he he's self referential, but also it's

1251
00:56:28,360 --> 00:56:32,000
Speaker 1: great anecdotes. And who would have thought I would be

1252
00:56:32,000 --> 00:56:35,279
Speaker 1: interested in a book on djaying. But he gets into

1253
00:56:35,280 --> 00:56:37,040
Speaker 1: this it's it's a very personal story. I think at

1254
00:56:37,040 --> 00:56:38,759
Speaker 1: the end of the day he didn't press on it

1255
00:56:38,760 --> 00:56:40,600
Speaker 1: as much. But what I took away from it was

1256
00:56:40,880 --> 00:56:42,920
Speaker 1: it's really a story about him and his mother, who

1257
00:56:43,000 --> 00:56:46,080
Speaker 1: was a socialite, and him growing up and he's like

1258
00:56:46,120 --> 00:56:49,280
Speaker 1: has panic attacks and things like that, and he feels

1259
00:56:49,400 --> 00:56:55,760
Speaker 1: this control over djaying and the music. And he remembers

1260
00:56:55,800 --> 00:56:57,400
Speaker 1: the first time he got to pick a song for

1261
00:56:57,440 --> 00:56:59,719
Speaker 1: his dad at a party and and what that was like.

1262
00:57:00,280 --> 00:57:02,440
Speaker 1: It was just there was a really fun, compelling and

1263
00:57:02,480 --> 00:57:04,440
Speaker 1: it also like took me back to the nineties in

1264
00:57:04,480 --> 00:57:04,839
Speaker 1: New York.

1265
00:57:04,960 --> 00:57:07,000
Speaker 2: Yeah, I was gonna say, Hey, Also, I've heard him

1266
00:57:07,080 --> 00:57:09,440
Speaker 2: speak on this subject and he's always like, really, you

1267
00:57:09,480 --> 00:57:11,600
Speaker 2: know when he when he when he talks about look

1268
00:57:11,680 --> 00:57:14,680
Speaker 2: DJing now versus DJing in New York and nineties, he's

1269
00:57:14,719 --> 00:57:16,440
Speaker 2: like the nineties nineties in New York.

1270
00:57:16,520 --> 00:57:18,800
Speaker 1: Well, he has this opening where like and it's just

1271
00:57:18,800 --> 00:57:20,760
Speaker 1: the kind of this anecdotal opening, like where you go

1272
00:57:21,200 --> 00:57:23,400
Speaker 1: you follow someone and they and they're at a club,

1273
00:57:23,400 --> 00:57:25,959
Speaker 1: they're at a house party, and they picked some song

1274
00:57:26,040 --> 00:57:29,000
Speaker 1: off their Spotify playlist, and then he compares that to

1275
00:57:29,040 --> 00:57:31,080
Speaker 1: what it was like in the nineties and you're lugging

1276
00:57:31,160 --> 00:57:34,880
Speaker 1: up records and yeah and finding lugging vityl and yeah,

1277
00:57:34,960 --> 00:57:37,320
Speaker 1: and it's it's a really not just plugging in your

1278
00:57:37,440 --> 00:57:40,960
Speaker 1: USB and exactly well, I think that concludes our first

1279
00:57:41,000 --> 00:57:45,480
Speaker 1: episode of our first recorded episode of the Nick Dick

1280
00:57:45,520 --> 00:57:46,040
Speaker 1: and Poll Show.

1281
00:57:46,080 --> 00:57:49,360
Speaker 3: There are the lost episodes, what the lost episodes?

1282
00:57:50,280 --> 00:57:53,640
Speaker 2: The early years, early when there was a fourth There

1283
00:57:53,680 --> 00:57:54,080
Speaker 2: was Nick.

1284
00:57:56,240 --> 00:57:59,560
Speaker 1: Phil who was who was the first influencer rock.

1285
00:57:59,760 --> 00:58:04,360
Speaker 2: And the that you reference work the first influence or

1286
00:58:04,720 --> 00:58:07,040
Speaker 2: locked the loved up and down the Nile. There he

1287
00:58:07,200 --> 00:58:10,280
Speaker 2: was crossing the aisle the nile, looking longingly over his

1288
00:58:10,360 --> 00:58:10,920
Speaker 2: shoulder with.

1289
00:58:10,920 --> 00:58:13,840
Speaker 3: A trying to carve quickly.

1290
00:58:16,240 --> 00:58:21,520
Speaker 1: I'll get a picture of this, all right, guys, that's

1291
00:58:21,520 --> 00:58:21,880
Speaker 1: a wrap.