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Speaker 1: Also media, step up to the slop trough. It's time

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Speaker 1: for better offline and I'm your host ed ze Tron.

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Speaker 1: As ever by the merchandise sign up to the newsletter

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Speaker 1: message me on goot. I'm everywhere. But today I'm joined

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Speaker 1: by the author of a book about how much I

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Speaker 1: should be punished, what punishments I deserve, and how long

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Speaker 1: I should be punished. I'm of course talking about more

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Speaker 1: Everything Forever, written by astrophysicist Adam Becker.

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Speaker 2: Adam, welcome to the show. Thanks for having me ed,

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Speaker 2: It's good to be here. What's the book actually about?

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Speaker 2: I apologize now, it's okay. The book is actually about

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Speaker 2: the horrible ideas that tech billionaires have about the future

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Speaker 2: that they're trying to shove down our throats, and why

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Speaker 2: they don't work.

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Speaker 1: You're an astrophysicist, right.

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Speaker 2: Yeah, by training, what is that? Well, I did a

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Speaker 2: PhD in astrophysics looking at how much we could learn

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Speaker 2: about what was happening right after the Big Bang by

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Speaker 2: looking at what was happening in the universe. You know

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Speaker 2: what's happening in the universe right now.

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Speaker 1: So how did you get into the touching in the

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Speaker 1: world of Silicon Valley because you have to talk about

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Speaker 1: some of the damnest bavots I've ever done.

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Speaker 2: Sane. Yeah. Well, I started out my career as a

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Speaker 2: science journalist straight out of grad school and was writing

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Speaker 2: mostly about physics.

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Speaker 1: Why are you writing?

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Speaker 2: I was writing for pretty much everybody. I started at

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Speaker 2: New Scientists and then moved on to writing for the BBC,

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Speaker 2: wrote a book about quantum physics, wrote some stuff for NPR,

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Speaker 2: the New York Times, very co American. Yeah, and you know,

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Speaker 2: like was sort of having a normal science journalist career,

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Speaker 2: and then in twenty sixteen, the weirdest fucking thing happened.

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Speaker 2: What happened? You know? We elected a fascist? Oh right, yeah,

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Speaker 2: that thing, yeah, that thing.

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Speaker 1: Yeah.

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Speaker 2: And I thought, oh, you know I should be doing

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Speaker 2: something more to, you know, directly combat this. If I

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Speaker 2: write another book, I would like it to have a

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Speaker 2: more directly political angle, right, and uh. I live in Berkeley,

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Speaker 2: I live in the San Francisco Bay area and just

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Speaker 2: surrounded by tech bros constantly and was getting tired of

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Speaker 2: their bullshit and it seemed more and more directly connected

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Speaker 2: to the disintegration of American politics. And I thought, Okay,

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Speaker 2: you know, somebody needs to write about how they have

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Speaker 2: these insane ideas about the future and how that informs

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Speaker 2: their terrible politics. So how long have you lived in

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Speaker 2: the Bay? God, oh, thirteen years?

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Speaker 1: Okay, so you've got like a good backing of where

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Speaker 1: the bay has been in that time as well, because

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Speaker 1: I think a lot of these people are transplants. And

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Speaker 1: I say this is someone who literally moved to the

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Speaker 1: Bay for two years in twenty fourteen. Yeah, like and

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Speaker 1: even then it was weird watching what they were doing.

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Speaker 1: Yeah but wait, so that was so you've been there

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Speaker 1: thirteen years. But when did the book get started? Like,

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Speaker 1: how did all this because it's this kind of came

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Speaker 1: out of no way in a good way.

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Speaker 2: Yeah, yeah, No, I got started on the book probably

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Speaker 2: the first inklings of it were around twenty nineteen or

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Speaker 2: twenty twenty, right before the pandemic. I uncovered a online

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Speaker 2: magazine that was trying to sanewash creationism and climate denial

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Speaker 2: that was being funded by Peter Teel. Hell yeah yeah,

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Speaker 2: And I broke that story and thought, oh, yeah, yeah,

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Speaker 2: these these tech bros are awful and everybody thinks they

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Speaker 2: know a lot about science and technology. Even the people

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Speaker 2: who don't like them seem to think that they know

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Speaker 2: a lot about science and technology, right, and it's just

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Speaker 2: not true. Like they don't know anything about physics, they

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Speaker 2: don't know anything about biology. Peter Teel thinks that creationism

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Speaker 2: is you know, plausible, or that evolution isn't the whole story.

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Speaker 2: That's nonsense, you know. Elon Musk thinks that we can

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Speaker 2: live on Mars. That's nonsense, or at least he says that.

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Speaker 2: Whether he actually believes it, I don't know.

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Speaker 1: But that's actually kind of my question. Yeah, how much

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Speaker 1: of this shit do you actually think they believe? Because

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Speaker 1: I know Bezos is tied up with the long Now Foundation. Yeah,

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Speaker 1: and they do make nice tea over there. However, the

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Speaker 1: rest of the stuff not so good. But how much

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Speaker 1: do they really believe in this? Because I just I

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Speaker 1: you've said that this is kind of a homecoming for them.

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Speaker 1: This is kind of them coming back to the things

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Speaker 1: they truly believe. I don't think they believe in anything thing.

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Speaker 1: I think some of them don't believe in anything. Go

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Speaker 1: into I'm not saying, I'm you know that's really right here?

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Speaker 2: Absolutely. Yeah. So, like, for example, I think it's very plausible. Obviously,

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Speaker 2: we can't know for sure, but I think it's very

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Speaker 2: plausible that, say, Sam Altman doesn't believe in anything. Yeah,

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Speaker 2: that's quite possible. Yeah right. Karen Howell makes a good

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Speaker 2: case for that in her reporting and in her.

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Speaker 1: Books Excellent, being a guest on the show, she's fantastic.

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Speaker 2: She's amazing. But at the other end of the spectrum,

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Speaker 2: I think it's very plausible that Jeff Bezos really really

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Speaker 2: does believe that we need to go to space. And

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Speaker 2: the reason I say that is he when he was

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Speaker 2: the vale edictorian of his high school down in Florida

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Speaker 2: in like nineteen seventy eight or something like that, he

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Speaker 2: gave a speech about how we need to go to space,

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Speaker 2: we humanity need to go to That.

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Speaker 1: Doesn't feel as ludicrous as a belief like we go

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Speaker 1: to space. But what does go to space mean for

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Speaker 1: this guy?

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Speaker 2: Well, that's the thing. The specifics of that belief that

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Speaker 2: he professed at the time are pretty similar to what

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Speaker 2: he's saying now, and it is pretty ridiculous, like he

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Speaker 2: has said very recently, and it echoes the stuff from

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Speaker 2: his valedictorian speech when he was like eighteen, that we

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Speaker 2: need to move into you know, hundreds of thousands or

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Speaker 2: millions of enormous cylindrical space stations. Oh, of course. And

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Speaker 2: have you know a trillion people living in the Solar.

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Speaker 1: System tubes, yes, of trillions of peach exactly, do just

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Speaker 1: work really well, like the hyperloop for example, Yeah, a

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Speaker 1: successful tube.

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Speaker 2: Yes, or you know the Internet itself a series of tubes. Yeah.

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Speaker 1: And because those tubes in the Internet worked, of course,

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Speaker 1: the tubes work in space.

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Speaker 2: Yeah, that's I think that the bongo.

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Speaker 1: Yeah, yeah, this is science. I believe I failed all

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Speaker 1: the sciences. I'm really sorry. I'm really sorry, but no,

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Speaker 1: keep going.

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Speaker 2: Yeah. So you know, he said, then we can like

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Speaker 2: make Earth into a beautiful park that you know, allows

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Speaker 2: us to you know, save the environments. I know. And

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Speaker 2: he said, when we have a trillion people living in

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Speaker 2: the Solar System, we can have a thousand Mozarts and

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Speaker 2: a thousand Einstein's. I'm like, buddy, we probably already have

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Speaker 2: people who are just as talented as Mozart and Einstein

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Speaker 2: and all the other geniuses of history who are living

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Speaker 2: and dying in poverty. Yes, and you know you don't

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Speaker 2: care about that, And you don't seem to care about

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Speaker 2: climate change because you know, the carbon footprint of the

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Speaker 2: Blue Origin rockets and the Amazon warehouses and all that stuff, right,

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Speaker 2: But instead of that, he's like, no, no, no, the solution

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Speaker 2: is to go to space. Like, why that's not gonna work.

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Speaker 1: Because more space is up in space, Adam, you put

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Speaker 1: cube and sp It's really it's funny because these people

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Speaker 1: are insanely rich but also sound very stupid. Yeah, when

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Speaker 1: you really get down to the trumps of its life,

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Speaker 1: what's your solution, Jeff of Gold, the money in the

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Speaker 1: world tubes yep, tubes of space tubes, yep, trillion people,

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Speaker 1: mozarts more mozarts, just sweating.

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Speaker 2: Profusely, exactly. Yeah, And he does try to give an argument,

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Speaker 2: but the argument is hilariously bad. He says that we

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Speaker 2: need to go to space, among other reasons, like he's

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Speaker 2: all that environmental stuff, but he the thing he keeps

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Speaker 2: harping on and coming back to is he says, we

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Speaker 2: need to keep using more energy per capita?

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Speaker 1: Right, why?

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Speaker 2: Right? Why? Exactly? He never says exactly WHOA Okay, Yeah,

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Speaker 2: he says. The only defense he gives for that is

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Speaker 2: he says, if we don't do that, we'll have a

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Speaker 2: civilization of stagnation and stasis.

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Speaker 1: As opposed to now when there's tons of innovation happening

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Speaker 1: and all of big tech is focused on a diverse

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Speaker 1: series of options rather than one big expensive dogshit thing.

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Speaker 2: Precisely, he nailed it. Yeah, and he says we have

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Speaker 2: to go to space because like otherwise, we're gonna run

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Speaker 2: out of energy here on Earth. We won't be able

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Speaker 2: to keep expanding the energy we used per capita. What

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Speaker 2: does the energy do?

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Speaker 1: Well?

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Speaker 2: Yeah, first of all, what does the energy do? And second, uh,

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Speaker 2: this is this is actually my favorite part. Hell yeah,

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Speaker 2: he is right that if you just like idiotically kept

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Speaker 2: that trend going in a way that's physically impossible, you know,

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Speaker 2: for for hundreds of years, you would run out of

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Speaker 2: energy here on Earth. Like you, you wouldn't be able

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Speaker 2: to keep the energy users per capita growing at the

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Speaker 2: exponential rate that it has been in about three hundred

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Speaker 2: years of be using all the energy that we get

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Speaker 2: from the Sun here on the Earth. But if you

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Speaker 2: keep that trend going, if you try to do that

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Speaker 2: by you know, going out and living in tubes in

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Speaker 2: the solar system, right, that only gets you like another

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Speaker 2: few hundred maybe one thousand years. Then you're using all

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Speaker 2: the energy that comes from the sun.

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Speaker 1: Right, and we've still not really established what we're using

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Speaker 1: the energy for. Nope, nope, no, so Beata sentus Yeah, finally.

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Speaker 2: Right, and this and this brings us to like the

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Speaker 2: bullshit that Sam Altman said about building a dice and sphere.

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Speaker 1: Exclaim what a dice sphere is? I thought it was

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Speaker 1: the ball on the fucking vacuum.

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Speaker 2: But yeah, no, that's the only kind of dice and

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Speaker 2: sphere that actually exists. No, a dice in sphere is

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Speaker 2: a giant, mega construction project, you know, beyond anything that

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Speaker 2: anyone's ever actually built or probably could build. That just

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Speaker 2: encloses a star and captures all of the energy from

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Speaker 2: that star.

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Speaker 1: Right, and if we ever built anything like that, no,

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Speaker 1: of course, okay, just making sure we So it's building

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Speaker 1: a big.

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Speaker 2: Around the star to capture all of the energy from

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Speaker 2: that star to use it for data.

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Speaker 1: Where would the energy How would the energy get from

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Speaker 1: the star to Earth?

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Speaker 2: I mean, oh, tubes, yeah, toobes exactly. Yeah, so I battery.

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Speaker 1: Yeah, like, it's so safe, it's so cool. We live

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Speaker 1: in a site. I wish I could do what he does.

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Speaker 1: I would be saying shit all the time. I just

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Speaker 1: I'd be like, yeah, actually, you need we can change

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Speaker 1: the world if we just create a series of tubes

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Speaker 1: that just gave me money every day. No, wait, that's

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Speaker 1: too that's that's too obvious. I'd need to come up

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Speaker 1: with the best.

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Speaker 2: Well no, I mean, I just think it's pretty interesting

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Speaker 2: that these guys are spouting obvious bullshit and the only

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Speaker 2: reason people listen to them is that they're rich. Like

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Speaker 2: if if they weren't saying this stuff, but then I

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Speaker 2: went around saying this stuff, nobody would listen to me

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Speaker 2: unless they funded me.

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Speaker 1: If a guy on the street who smelled kind of

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Speaker 1: bad walked up to you and said, the price of

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Speaker 1: intelligence is getting too cheap to meet her, you'd be like,

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Speaker 1: all right, mate, yeah, can't do anything but clammy Sammy

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Speaker 1: says it and everyone loses their fucking shit.

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Speaker 2: Well yeah, and that that Actually, that brings me to

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Speaker 2: something else that we were plenty to talk about, you know,

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Speaker 2: speaking of weird dudes on the street who are not

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Speaker 2: billionaires making insane claims. Ellie azer yod Kowski.

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Speaker 1: That's how you say his name, don't even Liza, I

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Speaker 1: don't really. Here's the thing. He's a disrespectful sex is

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Speaker 1: more on Grift. So I really don't give a shit.

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Speaker 2: Yeah, no, it is rather bizarre that anybody listens to

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Speaker 2: anything he has to say about anything he's So, who

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Speaker 2: is the fuck this fuck? Nun? No? No, the the

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Speaker 2: alternate title for my book, like in my head the

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Speaker 2: head Kennon was these fucking people. Yeah, I love that.

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Speaker 1: No, No, I write these fucking bosses a lot. Right,

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Speaker 1: Ellie's a Yudkowski?

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Speaker 2: Yes, who what does he do? Why does what does

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Speaker 2: he do?

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Speaker 1: And why does so many seemingly smart people believe this tipshit?

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Speaker 2: So Ellie as a Judkowski, I'm gonna give you, like

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Speaker 2: the formal version of who he is, what he might say,

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Speaker 2: what would be in like his online bio, and then

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Speaker 2: I'll tell you the reality. Okay, so uh. Ellie as

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Speaker 2: a jud Kowski is the co founder of the Machine

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Speaker 2: Intelligence Research Institute, which has been around for about twenty

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Speaker 2: five years, and he has been researching artificial superintelligence for

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Speaker 2: all of that time and mostly going on about how

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Speaker 2: dangerous it could be if anybody built it without ensuring

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Speaker 2: that it would serve human.

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Speaker 1: And this is just to be clear. He has no

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Speaker 1: scientific knowledge. Can he even code? Like? Does he have

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Speaker 1: any kind of.

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Speaker 2: He doesn't even have a high school diploma.

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Speaker 1: So I won't judge people for that, but I'll judge

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Speaker 1: him for all the rest of here's the thing.

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Speaker 2: Yeah, no, no, I'm not judging him for not but that

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Speaker 2: it doesn't really make Filly full of confidence. No, no, no, no,

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Speaker 2: he has no formal qualifications. And again, that's fine. You know,

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Speaker 2: there are many people who've made major contributions to many

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Speaker 2: fields of human endeavor without any formal qualifications. Right, that's fine.

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Speaker 2: The thing is, if you make extraordinary claims like he's making,

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Speaker 2: you need extraordinary evidence, and not having those qualifications, like

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Speaker 2: you said, doesn't really inspire confidence. He has made a

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Speaker 2: series of really outlandish claims about what the future of

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Speaker 2: AI could be, right, based on essentially nothing, based on

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Speaker 2: like reading a bunch of science fiction. He explicitly cites,

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Speaker 2: uh science fiction. There's like verner VINGI, as you know,

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Speaker 2: oh verner Vingie wrote a bunch of books like Marooned

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Speaker 2: in Real Time and uh god, I'm trying to remember

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Speaker 2: the names of the others. It doesn't matter. Point is, yeah,

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Speaker 2: he's a fiction writer who's also I think a scientist

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Speaker 2: of some stripe I don't remember what, but still writing

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Speaker 2: fiction and VINGI came up with this idea, or was

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Speaker 2: one of the originators of and popularizers of an idea

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Speaker 2: called the singularity. Right, So the singularity is this idea

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Speaker 2: that the rate of technological change is just going to

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Speaker 2: keep getting faster and faster, and specifically, the rate of

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Speaker 2: intelligence of AI is going to keep getting smarter and smarter, uh,

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Speaker 2: until we reach this sort of point of no return

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Speaker 2: where we have a singularity accompanied by an intelligence explosion that.

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Speaker 1: Leads to like the singularity moment.

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Speaker 2: Yeah, the singularity moment is very ill defined.

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Speaker 1: Oh and the I can't fucking believe this. Yeah, I've

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Speaker 1: heard this bollocks so many times. I thought they had

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Speaker 1: a moment. I thought they had a point.

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Speaker 2: No, not really, oh you yeah, So like Kurzweil, right,

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Speaker 2: the patron saint of evangelizing the Singularity, the guy who

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Speaker 2: read the Singularity is Nearer, and then the sequel last year,

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Speaker 2: the Singularity is Nearer, which is the real fucking title. Bro,

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Speaker 2: I know that's the real title of the book.

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Speaker 1: But his next books just called sorry, yeah no, it's

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Speaker 1: his next books, Like it's here again, you see, it

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Speaker 1: is the Singularity in the room with us, Yes, exactly,

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Speaker 1: but he doesn't.

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Speaker 2: He tries to, but it's incredibly vague. He says, like

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Speaker 2: Kurzweil says, the singularity is going to be here in

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Speaker 2: twenty forty five. He also said in two thousand and five,

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Speaker 2: and the singularity is near that, you know, we would

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Speaker 2: have all kinds of nanotechnology by now. They love nanotechty,

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Speaker 2: they love nanotechnology. They use it as a synonym for magic.

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Speaker 1: It was, I swear to God. Also, there was a

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Speaker 1: nanotechnology bubble briefly like ten years ago. I vaguely remember

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Speaker 1: them trying.

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Speaker 2: It didn't really go any I mean, there was also

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Speaker 2: a nanotech sort of hype bubble back in the eighties

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Speaker 2: and nineties, and it also didn't go anywhere. And it

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Speaker 2: didn't go anywhere because it turns out that like this

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Speaker 2: idea of nanotech is like magic pixie dust that fixes

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Speaker 2: everything is nonsense and it's a real like it's being

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Speaker 2: echoed right now in the AI bubble. Yeah right. It's

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Speaker 2: the same kind of hype, often pushed by the same

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Speaker 2: people with the same logic, sometimes working at like the

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Speaker 2: same nonprofits. I mean, Yudkowski talks about nanotech constantly. It's

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Speaker 2: in his new book it's all over you know, the

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Speaker 2: website that he's created. Uh.

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Speaker 1: And his book is called if You Buy this book

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Speaker 1: called Mike Money. Yeah, that's sorry, It's called if They

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Speaker 1: Built This Everyone. It's such a stupid fucking title.

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Speaker 2: Sorry. Yeah, no, it's a very stupid title. I will

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Speaker 2: say the one thing I'll say about Yudkowski. I am

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Speaker 2: sure that he is a true believer. He is not

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Speaker 2: a Yes, he's not a grifter. Why because, like it's

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Speaker 2: it's hard to explain, but I am so much more

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Speaker 2: sure about him than I am about anybody else, even base.

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Speaker 1: I trust your judgment. It's just he gives off the

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Speaker 1: air of like a despot for a mad men.

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Speaker 2: Yeah. I would say the best way to think about Yudkowski,

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Speaker 2: like the way that I often think about him, is

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Speaker 2: imagine like a really smart, self educated fifteen year old.

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Speaker 2: Yeah yeah, and like, you know, because if a fifteen

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Speaker 2: year old was running around saying the stuff that Yudkowski

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Speaker 2: is saying right now, I'd be like, wow, bright kid.

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Speaker 1: I hope he grows out, and I hope his parents

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Speaker 1: have a lock on the gung capin.

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Speaker 2: Yeah yeah, yeah, well, and also like I hope he

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Speaker 2: you know, I hope he grows up.

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Speaker 1: Yes, and I'm still thinking that.

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Speaker 2: Yeah, And like, and I don't think jud Kowski did.

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Speaker 2: I think, you know, I think like.

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Speaker 1: I also think everybody fell for it.

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Speaker 2: Yeah. Well, and that's the thing, Like he got a

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Speaker 2: lot of support online. He you know, he got money

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Speaker 2: from Peterman.

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Speaker 1: Sam Moltman said that he could, he should, he may

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Speaker 1: win the Nobel Peace Prize.

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Speaker 2: One yeah, yeah, sam Moltman said that he should win

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Speaker 2: a Nobel Peace Prize.

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Speaker 1: Falling down moment if that happens.

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Speaker 2: Yeah, no, that's not happening.

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Speaker 1: Defense.

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Speaker 2: Yeah, no, there's no way. But like, look, he got

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Speaker 2: a bunch of money from Peter Teal because Teal thought that,

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Speaker 2: you know, j had Kowski was saying smart stuff about AI, right.

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Speaker 2: Teal now doesn't much like jud Kowski because he thinks

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Speaker 2: jud Kowski is too pessimistic. But the sort of the

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Speaker 2: damage has been.

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Speaker 1: The ultimate Oh yeah yeah, classic old grins and smiles

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Speaker 1: of that foul.

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Speaker 2: Yeah no, too pessimistic for Peter Teal.

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Speaker 1: That's actually bad.

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Speaker 2: Yeah no it is, no, it's but no, he's he's

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Speaker 2: a true believer. He's just kind of nuts.

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Speaker 1: So what does he do all day? I say this

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Speaker 1: as a blogger pr person news, newsletter writer and podcaster

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Speaker 1: and all this ship Like I realize I have an

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Speaker 1: email job, Fine, but at least I can tell tell

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Speaker 1: you what I do all day. What does he do

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Speaker 1: with like go to parties with people at Kevin Rusan

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Speaker 1: going the computer's going to kill us all.

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Speaker 2: I think that's a good chunk of it. And I

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Speaker 2: also think he writes an enormous amount right, Like, this

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Speaker 2: is a guy who wrote that, you know, Harry Potter

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Speaker 2: fan fiction that's longer than War in Peace. Right, he

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Speaker 2: wrote like a one and a half million word BDSM

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Speaker 2: decision theory novel.

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Speaker 1: I say this as someone who writes a lot, a

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Speaker 1: lot of words. That's an unhealthy amount of words.

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Speaker 2: I agree, and it does help. I think for him

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Speaker 2: being able to write that many words, he's not a

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Speaker 2: very good writer.

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Speaker 1: Yeah. I mean even again, I write fifteen thousand word blogs,

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Speaker 1: so I can't really judge him too harsh. But one

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Speaker 1: point five million words, how do you even know what

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Speaker 1: it's about?

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Speaker 2: At that point? I only know what it's about because

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Speaker 2: that's what he said it's about. I haven't read that one.

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Speaker 2: I did read most of the Harry Potter one research. Yeah, bad,

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Speaker 2: it was really really incredible.

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Speaker 1: Any any sexism or racism in there, it's just strange.

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Speaker 1: I mean it's JK.

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Speaker 2: Rowling, So yeah, exactly. Yeah, that's a good question. I

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Speaker 2: don't remember anything specif big good.

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Speaker 1: Yeah, I mean it's just strange.

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Speaker 2: Yeah. I mean, he's definitely got a heart on for

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Speaker 2: eugenics and.

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Speaker 1: These and this is somewhat paraphrasing the comic book Preacher,

390
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Speaker 1: but it's like, why do these fucking guys always look

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Speaker 1: like that?

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Speaker 2: If you're gonna claim.

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Speaker 1: You're like a eugenicist, you should not look like an

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Speaker 1: egg with a hat on. And I won't get into

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Speaker 1: but I don't generally get into personal appearance because I'm

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Speaker 1: self conscious myself. But it's like, if your whole thing

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Speaker 1: is like, yeah, we need to make the perfect human beings,

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Speaker 1: it's like, you can't look like that, mate, I'm sorry,

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Speaker 1: you can't do that.

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Speaker 2: Well I don't.

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Speaker 1: I guess you can. You'll be in the New York

402
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Speaker 1: fucking Times.

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Speaker 2: Yeah. No, it's it's crazy. It is really crazy that

404
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Speaker 2: anybody listens to him. But no, he's really into eugenics.

405
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Speaker 1: Why do they listen to him?

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Speaker 2: He's really into evolutionary psychology, and he's got like the

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Speaker 2: sexism and racism that's like tied up in that. Why

408
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Speaker 2: do people listen to him? I mean part of it

409
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Speaker 2: is that he got that money from those billionaires, right.

410
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Speaker 2: He was hanging out in the bay saying the kind

411
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Speaker 2: of insane contrarian shit about AI that attracts the kind

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Speaker 2: of like brain dead billionaires like Peter Thiel. And then

413
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Speaker 2: you know, he became the guy and started, you know,

414
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Speaker 2: a series of online platforms that attracted a following, right,

415
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Speaker 2: like you know, Less Wrong, and then that spun off

416
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Speaker 2: this whole rationalist subculture. Yeah, that's a very good question.

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Speaker 2: Less Wrong is an online platform that serve slash maybe

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Speaker 2: served as a home and like epicenter for this movement

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Speaker 2: called the Rationalists, right, which are sort of formed around

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Speaker 2: Yudkowski's writing, include this set of writings he has called

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Speaker 2: The Sequences where he lays out, Oh he's a cult leader,

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Speaker 2: yeah in a way. Yeah. Yeah.

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Speaker 1: The rationalists are just people, I'm guessing, guys with triobies

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Speaker 1: who say that we need to focus on ration, rational

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Speaker 1: thoughts and logic.

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Speaker 2: And there's a lot of it. I mean, some of

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Speaker 2: them are women, but some of them are non.

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Speaker 1: Baring, really surprising yeah.

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Speaker 2: I mean, look, there are nerds of all stripes.

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Speaker 1: Yes, And also he's very much playing in the older Internet. Yes,

431
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Speaker 1: but the idea of a large forum with any kind

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Speaker 1: of following is actually kind of adorable these days, except

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Speaker 1: when it's less wrong, it's not adorable. Well.

434
00:21:34,600 --> 00:21:38,159
Speaker 2: Also, less wrong's been around since the somewhat older Internet, right,

435
00:21:38,160 --> 00:21:39,959
Speaker 2: it's not been around since the nineties, but it's been

436
00:21:40,000 --> 00:21:42,440
Speaker 2: around since like the mid to late two thousands. Okay,

437
00:21:43,520 --> 00:21:48,320
Speaker 2: And Yudkowski is you know, a lot of the rationalists

438
00:21:48,320 --> 00:21:51,960
Speaker 2: are in their twenties and maybe early thirties, but Yudkowski

439
00:21:52,040 --> 00:21:55,520
Speaker 2: himself is in his mid forties, right, because you know,

440
00:21:55,600 --> 00:21:59,400
Speaker 2: he he is terminally online. And I'm sure, like obviously

441
00:21:59,440 --> 00:22:00,920
Speaker 2: he'd be unhapy be with many of the things I've

442
00:22:00,920 --> 00:22:03,280
Speaker 2: said about him, but that one I'm sure he'd agree with.

443
00:22:03,320 --> 00:22:07,000
Speaker 2: You know, like he's been online since he dropped out

444
00:22:07,040 --> 00:22:10,760
Speaker 2: of school at age what like thirteen or fourteen. He's

445
00:22:10,760 --> 00:22:14,119
Speaker 2: been online since the mid nineties on like butta yeah,

446
00:22:14,200 --> 00:22:19,840
Speaker 2: and like you know, he was on transhumanist forums like

447
00:22:19,840 --> 00:22:23,280
Speaker 2: like you know, since the mid nineties, like email threats

448
00:22:23,280 --> 00:22:23,840
Speaker 2: and stuff like that.

449
00:22:24,080 --> 00:22:26,679
Speaker 1: God, yeah, he really he is like the detritus of

450
00:22:26,720 --> 00:22:29,960
Speaker 1: the Internet in a way brought to like Katamari of

451
00:22:31,040 --> 00:22:32,360
Speaker 1: center right freaks.

452
00:22:32,560 --> 00:22:36,080
Speaker 2: Yeah, bearing ever right. I wouldn't even say center right.

453
00:22:36,160 --> 00:22:39,960
Speaker 2: I would say techno libertarian. But that is just that's

454
00:22:40,040 --> 00:22:42,399
Speaker 2: just right. Oh, no, it is right wing. It's the

455
00:22:42,440 --> 00:22:43,680
Speaker 2: center part that I disagreed with.

456
00:22:43,760 --> 00:22:46,640
Speaker 1: Yeah, perhaps he started that when he was fifteen, before

457
00:22:46,680 --> 00:22:49,200
Speaker 1: he learned yeah, the wrong things.

458
00:22:49,480 --> 00:22:52,080
Speaker 2: Yeah, I will say he like I don't get the

459
00:22:52,119 --> 00:22:55,919
Speaker 2: sense that like he likes Donald Trump, but he certainly

460
00:22:56,359 --> 00:23:00,960
Speaker 2: like will parrot a lot of standard libertarian talking saints

461
00:23:01,000 --> 00:23:03,800
Speaker 2: along the way to you know, making his The one thing.

462
00:23:03,760 --> 00:23:05,800
Speaker 1: I keep thinking though, is I don't know if I

463
00:23:05,840 --> 00:23:08,440
Speaker 1: can shake this thing he's a grifter just because you're

464
00:23:08,480 --> 00:23:11,120
Speaker 1: taking a bunch of twenty year olds, you've got all

465
00:23:11,160 --> 00:23:13,879
Speaker 1: of this writing thing. He's either a grifter or a

466
00:23:13,920 --> 00:23:16,160
Speaker 1: true cult leader. He may actually just be a cult leader.

467
00:23:16,240 --> 00:23:18,160
Speaker 2: Why I would say cult leader is.

468
00:23:18,119 --> 00:23:22,320
Speaker 1: Closer, Yeah, because he seems to I mean, dangerous is

469
00:23:22,359 --> 00:23:23,399
Speaker 1: probably the wrong word.

470
00:23:23,720 --> 00:23:24,760
Speaker 2: Yeah, I think that's straight.

471
00:23:24,760 --> 00:23:25,040
Speaker 1: He's not.

472
00:23:25,200 --> 00:23:27,240
Speaker 2: I wouldn't call him dangerous, but he is.

473
00:23:28,920 --> 00:23:31,199
Speaker 1: You think the only dangerous to like a hot topic worker,

474
00:23:32,880 --> 00:23:35,640
Speaker 1: a very nerdy hot topic No, No, no, no to them,

475
00:23:35,840 --> 00:23:52,720
Speaker 1: just just that he'd speak to them. It's just peculiar

476
00:23:52,760 --> 00:23:54,960
Speaker 1: as well, because and this actually gets into some of

477
00:23:54,960 --> 00:23:59,040
Speaker 1: your science background when you got my continual frustration because

478
00:23:59,080 --> 00:24:00,880
Speaker 1: I am self taught with all this economic stuff which

479
00:24:00,920 --> 00:24:03,840
Speaker 1: is insane, I probably shouldn't criticize you had Kowski quite

480
00:24:03,840 --> 00:24:07,600
Speaker 1: as much, but I will. I'm a hypocrite. I looking

481
00:24:07,600 --> 00:24:10,000
Speaker 1: through financial journalism and tech journalism. The thing that I

482
00:24:10,080 --> 00:24:12,440
Speaker 1: keep noticing is that people keep accepting things that I've

483
00:24:12,520 --> 00:24:15,600
Speaker 1: just patently wrong. There's just shit that they say, like

484
00:24:15,640 --> 00:24:17,840
Speaker 1: even with this in video Open AI deal, people saying

485
00:24:18,080 --> 00:24:20,520
Speaker 1: and Video invested one hundred billion dollars. They didn't. They're

486
00:24:20,520 --> 00:24:24,000
Speaker 1: investing progressively. When they do the first giga what gigawatts

487
00:24:24,040 --> 00:24:26,080
Speaker 1: of take like gig what of data center will take

488
00:24:26,119 --> 00:24:27,879
Speaker 1: about a year and a half two years. That though,

489
00:24:28,119 --> 00:24:31,080
Speaker 1: it's just bollocks. I imagine the last few years have

490
00:24:31,080 --> 00:24:33,000
Speaker 1: been a little bit mind bending for you hearing all

491
00:24:33,000 --> 00:24:37,240
Speaker 1: this stuff about Agi and the future and all that.

492
00:24:37,520 --> 00:24:45,200
Speaker 2: Yeah gobshite, Yes, yeah, I mean the AGI stuff, which,

493
00:24:45,280 --> 00:24:48,200
Speaker 2: like I started working on this book before chatch Ept

494
00:24:48,400 --> 00:24:50,560
Speaker 2: came out right, and it.

495
00:24:50,640 --> 00:24:53,040
Speaker 1: Was twenty nineteen, a few years into Open a eyes.

496
00:24:52,880 --> 00:24:57,720
Speaker 2: Yeah exactly. So like I knew about open AI, and

497
00:24:57,800 --> 00:25:00,719
Speaker 2: I knew about like transformer models, but like you know,

498
00:25:01,440 --> 00:25:05,439
Speaker 2: chat GPT comes out and and suddenly, you know, the

499
00:25:05,440 --> 00:25:08,199
Speaker 2: public conversation shifts in a way that I didn't anticipate.

500
00:25:08,400 --> 00:25:10,800
Speaker 2: I realize, oh, this book is going to have to

501
00:25:10,800 --> 00:25:12,320
Speaker 2: be a little bit different than I thought it was

502
00:25:12,320 --> 00:25:16,320
Speaker 2: going to be. But also, you know, all of this

503
00:25:16,400 --> 00:25:20,960
Speaker 2: conversation about AGI, right, like in a way it helped

504
00:25:20,960 --> 00:25:22,600
Speaker 2: me for writing the book because I thought I was

505
00:25:22,600 --> 00:25:23,920
Speaker 2: going to have to spend a lot of time in

506
00:25:23,960 --> 00:25:29,000
Speaker 2: the book explaining what AI is, what people think AGI is, right,

507
00:25:29,000 --> 00:25:31,879
Speaker 2: There's gonna be a lot more explanation, And then all

508
00:25:31,920 --> 00:25:34,399
Speaker 2: of this stuff came out and I'm like, oh, actually, this,

509
00:25:34,640 --> 00:25:36,359
Speaker 2: you know, I can I can spend more time in

510
00:25:36,359 --> 00:25:38,080
Speaker 2: the meat of the book. This is this is helpful

511
00:25:38,119 --> 00:25:40,879
Speaker 2: for me because you could just quote them directly exactly. Yeah.

512
00:25:40,960 --> 00:25:45,920
Speaker 2: But the thing is, AGI is this hopelessly ill defined

513
00:25:45,960 --> 00:25:49,600
Speaker 2: thing like super intelligence, this thing that that yed Kowski

514
00:25:49,640 --> 00:25:52,480
Speaker 2: is on about. Uh you know, what does it even mean?

515
00:25:52,640 --> 00:25:54,639
Speaker 2: Like have you looked at the definition of AGI in

516
00:25:54,640 --> 00:25:57,960
Speaker 2: the open AI charter like the original one? Oh yeah, no,

517
00:25:58,080 --> 00:26:01,159
Speaker 2: it's great, Like the original charter from way back. It

518
00:26:01,200 --> 00:26:07,320
Speaker 2: says something like AGI is a machine that can reproduce

519
00:26:07,800 --> 00:26:13,199
Speaker 2: any economically viable or economically productive activity that humans engage in.

520
00:26:13,480 --> 00:26:15,840
Speaker 2: That's a bad definition.

521
00:26:16,160 --> 00:26:18,959
Speaker 1: That's anything. Yeah, I mean that could just mean anything

522
00:26:19,000 --> 00:26:21,640
Speaker 1: that could. It's it's a machine that can do anything.

523
00:26:21,800 --> 00:26:26,600
Speaker 2: It's both vague and really narrow, right, because it's like, Okay,

524
00:26:26,680 --> 00:26:28,959
Speaker 2: I thought AGI was supposed to be like, you know,

525
00:26:29,080 --> 00:26:32,879
Speaker 2: commander data on Star Trek, right, and so that means

526
00:26:32,960 --> 00:26:35,159
Speaker 2: you know, it's gonna be sort of like humans. It

527
00:26:35,200 --> 00:26:36,160
Speaker 2: can do the things that.

528
00:26:36,200 --> 00:26:39,000
Speaker 1: Humans do, also economically viable work. And the first thing

529
00:26:39,040 --> 00:26:43,199
Speaker 1: they start with is fucking writing. Yeah, like Jesus Christ.

530
00:26:43,800 --> 00:26:47,600
Speaker 1: That's like, oh my god. Yeah, the first and the most.

531
00:26:47,960 --> 00:26:50,000
Speaker 1: We're gonna build boats and sell like we're gonna buy

532
00:26:50,000 --> 00:26:53,040
Speaker 1: boats as an investment vehicle, like like what the fuck?

533
00:26:53,560 --> 00:26:55,240
Speaker 2: Yeah, these people don't do any real work.

534
00:26:55,320 --> 00:26:59,120
Speaker 1: It's it's so strange as well, because the AGI conversation

535
00:26:59,160 --> 00:27:02,040
Speaker 1: almost never happened. It's about AGI. It's because my favorite

536
00:27:02,080 --> 00:27:02,800
Speaker 1: thing to do is media.

537
00:27:02,840 --> 00:27:02,919
Speaker 2: Go.

538
00:27:03,119 --> 00:27:06,240
Speaker 1: Isn't this slavery? Because it is. It's like, oh, yeah,

539
00:27:06,280 --> 00:27:08,760
Speaker 1: we'll do an autonomous thing. We'll make do things, but

540
00:27:08,800 --> 00:27:10,720
Speaker 1: it will be conscious, which will allow it to work better.

541
00:27:10,920 --> 00:27:13,040
Speaker 2: Yep. And so then you get people talking about like

542
00:27:13,080 --> 00:27:15,959
Speaker 2: a data center filled with geniuses, and like, oh, okay,

543
00:27:16,080 --> 00:27:18,280
Speaker 2: wouldn't a data center filled with geniuses not want to

544
00:27:18,320 --> 00:27:18,760
Speaker 2: work for you?

545
00:27:18,760 --> 00:27:21,119
Speaker 1: Wouldn't a dat ascent of full of geniuses that can't

546
00:27:21,200 --> 00:27:22,960
Speaker 1: leave and have to work be cold to prison?

547
00:27:23,080 --> 00:27:27,680
Speaker 2: Yep? Yeah? Cool, yeah, exactly. No, I I get into

548
00:27:27,720 --> 00:27:33,000
Speaker 2: this in my book. You know, the inspiration for a

549
00:27:33,040 --> 00:27:36,719
Speaker 2: lot of these ideas ultimately traces back to mid twentieth

550
00:27:36,760 --> 00:27:39,600
Speaker 2: century science fiction, right, And so you get people like

551
00:27:39,760 --> 00:27:44,640
Speaker 2: Isaac Asimov, Arthur C. Clark, right, Asimov's robot stories in particular.

552
00:27:44,720 --> 00:27:47,560
Speaker 2: If you go back and look at Asimov's robot stories,

553
00:27:47,880 --> 00:27:51,080
Speaker 2: it is very hard with like a modern eye to

554
00:27:51,119 --> 00:27:54,640
Speaker 2: look at them as, especially certain ones of them. It's

555
00:27:54,680 --> 00:27:56,600
Speaker 2: hard to see them as anything other than like kind

556
00:27:56,640 --> 00:28:01,000
Speaker 2: of being about slavery and race relationships, because you get like,

557
00:28:01,080 --> 00:28:03,680
Speaker 2: for example, there's this one short story I think it's

558
00:28:03,720 --> 00:28:08,320
Speaker 2: called Oh God, I think it's called Catch that Robot,

559
00:28:08,359 --> 00:28:10,000
Speaker 2: but I might be confusing it with a different one.

560
00:28:10,000 --> 00:28:11,520
Speaker 2: It might be a little Lost Robot. I get those

561
00:28:11,560 --> 00:28:15,080
Speaker 2: two confused. But either way, it's about a robot that

562
00:28:15,280 --> 00:28:20,400
Speaker 2: is trying to escape gain its freedom. And in that story,

563
00:28:20,960 --> 00:28:25,720
Speaker 2: the humans are like addressing a bunch of they're interviewing

564
00:28:25,760 --> 00:28:28,320
Speaker 2: a bunch of seemingly identical robots to try to find

565
00:28:28,359 --> 00:28:30,719
Speaker 2: the one that they're looking for that's trying to escape.

566
00:28:31,320 --> 00:28:35,200
Speaker 2: And they interview these robots and when they're interviewing them,

567
00:28:35,400 --> 00:28:40,360
Speaker 2: they address them as boy, and the robots called the

568
00:28:40,480 --> 00:28:45,680
Speaker 2: humans Master. Yeah, And these stories are from like nineteen

569
00:28:45,960 --> 00:28:48,800
Speaker 2: fifty five, like you know, the Jim Crow South is

570
00:28:48,840 --> 00:28:52,920
Speaker 2: alive and well, it's really bad, it's really really uncomfortable.

571
00:28:53,160 --> 00:28:57,720
Speaker 2: And then like forty years later, in the nineteen nineties,

572
00:28:58,280 --> 00:29:01,720
Speaker 2: you get Werner Vingi writing about the singularity and how

573
00:29:01,760 --> 00:29:03,840
Speaker 2: great it's going to be when we all have these

574
00:29:03,920 --> 00:29:09,080
Speaker 2: robot assistants, and he refers to Asmov's wonderful dream of

575
00:29:09,480 --> 00:29:12,920
Speaker 2: and this is a direct quote from Vingi. Willing slaves

576
00:29:13,120 --> 00:29:16,400
Speaker 2: Jesus fucking Christ. Yes, And that's something that someone wrote

577
00:29:16,440 --> 00:29:19,080
Speaker 2: in like nineteen ninety one. I mean, but that's what

578
00:29:19,120 --> 00:29:19,520
Speaker 2: this is.

579
00:29:20,000 --> 00:29:23,120
Speaker 1: And this is an uncomfortable topic because that's what this is.

580
00:29:23,600 --> 00:29:26,560
Speaker 1: It's what pisses me off, other than like nineteen other

581
00:29:26,600 --> 00:29:28,920
Speaker 1: things about Kevin Bruce at the time, because he's written

582
00:29:28,920 --> 00:29:31,520
Speaker 1: several things about AI and AGI and one thing about

583
00:29:31,520 --> 00:29:34,920
Speaker 1: AI welfare, and it's like the AI welfare begins with slavery.

584
00:29:35,040 --> 00:29:37,360
Speaker 1: And if you can't write that, you're a fucking coward

585
00:29:37,400 --> 00:29:40,520
Speaker 1: and a bitch. I'm sorry you can't write. Yeah, everyone

586
00:29:40,600 --> 00:29:42,920
Speaker 1: is excited about slavery because that's what it is, and

587
00:29:42,960 --> 00:29:45,920
Speaker 1: it's nothing else. It's not oh well, it's like they

588
00:29:45,920 --> 00:29:49,200
Speaker 1: wouldn't be. They wouldn't be. They like doing it, and

589
00:29:49,240 --> 00:29:52,320
Speaker 1: it's like, fuck you man, that it's slavery. What I

590
00:29:52,400 --> 00:29:56,280
Speaker 1: really hope happens is if AGI happens, it's just a

591
00:29:56,760 --> 00:29:59,800
Speaker 1: just a regular dude, yep, and he's lazy and he's

592
00:29:59,800 --> 00:30:05,280
Speaker 1: a yeah, like you just do this. What I think

593
00:30:05,920 --> 00:30:08,400
Speaker 1: that's way more likely is I don't think AGI is possible.

594
00:30:08,560 --> 00:30:11,000
Speaker 2: Yeah. No, Actually that's a good question. Do you think

595
00:30:11,000 --> 00:30:13,720
Speaker 2: it's possible? Not really? No likely?

596
00:30:14,160 --> 00:30:16,040
Speaker 1: I say this is a non scientific person.

597
00:30:15,880 --> 00:30:21,320
Speaker 2: Yeah, yeah, no, I don't think that you can build. Well,

598
00:30:21,320 --> 00:30:24,280
Speaker 2: first of all, I think AGI is just hopelessly ill defined, right,

599
00:30:24,320 --> 00:30:27,880
Speaker 2: But if we want to say, like an artificial machine

600
00:30:28,440 --> 00:30:33,120
Speaker 2: that has the cognitive capacities of a human, like they

601
00:30:33,160 --> 00:30:35,400
Speaker 2: can do all of the tasks, like all of the

602
00:30:35,480 --> 00:30:38,760
Speaker 2: things that humans do. First of all, I think you're

603
00:30:38,800 --> 00:30:41,080
Speaker 2: gonna need a completely different kind of machine. I don't.

604
00:30:41,120 --> 00:30:43,160
Speaker 2: I don't think certainly. I don't think that you know,

605
00:30:43,320 --> 00:30:46,600
Speaker 2: scale is all you need. And if just scale attention, yeah,

606
00:30:46,800 --> 00:30:48,440
Speaker 2: give it, give it more data. And if you don't

607
00:30:48,440 --> 00:30:51,160
Speaker 2: have enough data to make more synthetic data with more LLM,

608
00:30:51,360 --> 00:30:56,280
Speaker 2: like dude, that why why wouldn't know? Absolutely not? But

609
00:30:56,280 --> 00:31:00,160
Speaker 2: but I also think that like there is, there's is

610
00:31:00,360 --> 00:31:05,600
Speaker 2: very simplistic set of ideas behind the idea of AGI, right,

611
00:31:05,960 --> 00:31:09,240
Speaker 2: and and the two that I keep coming back to

612
00:31:09,800 --> 00:31:13,160
Speaker 2: are the idea of the brain as a computer and

613
00:31:13,200 --> 00:31:16,960
Speaker 2: the idea of our bodies as like meat spacesuits for

614
00:31:17,000 --> 00:31:20,040
Speaker 2: our brains. And both of those are just wrong. The

615
00:31:20,080 --> 00:31:23,080
Speaker 2: brain is not really very much like a computer. It

616
00:31:23,200 --> 00:31:25,520
Speaker 2: is more like a computer than it is like say,

617
00:31:25,760 --> 00:31:29,840
Speaker 2: a clock. But there was a long history of comparing

618
00:31:29,920 --> 00:31:34,320
Speaker 2: the brain to you know, the most complex piece of

619
00:31:34,320 --> 00:31:36,640
Speaker 2: machinery that humans have at the time, right before it

620
00:31:36,680 --> 00:31:39,520
Speaker 2: was a brain, or before the brain was like a computer,

621
00:31:39,640 --> 00:31:42,120
Speaker 2: it was like a telephone network. Before that, it was

622
00:31:42,160 --> 00:31:44,000
Speaker 2: like a hydraulic system. Before that, it was like a

623
00:31:44,040 --> 00:31:47,680
Speaker 2: clock or a windmill, right, And it's not really actually

624
00:31:47,920 --> 00:31:50,040
Speaker 2: like I mean, it's a little like some of those things.

625
00:31:50,440 --> 00:31:52,800
Speaker 2: But the brain is like the brain, and the main different.

626
00:31:52,840 --> 00:31:55,360
Speaker 1: We don't understand thinking, no, and we don't.

627
00:31:55,240 --> 00:31:57,760
Speaker 2: Understand exactly how the brain works. And part of that

628
00:31:57,880 --> 00:32:01,400
Speaker 2: is that the brain was not built. The brain evolved. Right.

629
00:32:02,920 --> 00:32:06,080
Speaker 2: But also we are not our brains. We are our

630
00:32:06,160 --> 00:32:10,320
Speaker 2: bodies in our environments. Right. The brain is inextricably connected

631
00:32:10,600 --> 00:32:13,400
Speaker 2: to the body, and the body works in an environment

632
00:32:13,600 --> 00:32:18,240
Speaker 2: surrounded by other bodies, in a culture, a society, a world. Right.

633
00:32:18,760 --> 00:32:22,000
Speaker 2: You need all of those things in order to get

634
00:32:22,320 --> 00:32:26,160
Speaker 2: the human cognition that you know. These guys are so

635
00:32:26,760 --> 00:32:30,840
Speaker 2: you know, determined to reproduce inside of a computer. If

636
00:32:30,840 --> 00:32:34,080
Speaker 2: you just take a human baby and like leave it

637
00:32:34,120 --> 00:32:37,800
Speaker 2: with a bunch of food in the woods, even if

638
00:32:37,840 --> 00:32:39,320
Speaker 2: you get rid of all the predators and everything, that

639
00:32:39,360 --> 00:32:42,000
Speaker 2: baby's gonna starve to get a bunch of books, man, right, yeah,

640
00:32:42,120 --> 00:32:44,719
Speaker 2: like the baby books. Yeah, if you give the if

641
00:32:44,800 --> 00:32:46,920
Speaker 2: you somehow, if you feed the baby but don't talk

642
00:32:46,960 --> 00:32:49,960
Speaker 2: to it, the baby will not grow up being able

643
00:32:50,000 --> 00:32:51,320
Speaker 2: to think properly.

644
00:32:51,200 --> 00:32:53,560
Speaker 1: Or Speakit's thinking will be vastly different.

645
00:32:53,720 --> 00:32:58,040
Speaker 2: Exactly. Yeah, and so like you need so much more

646
00:32:58,160 --> 00:32:59,160
Speaker 2: than just the brain.

647
00:32:59,280 --> 00:33:03,480
Speaker 1: It also compresses human experience. They can play experience with learning.

648
00:33:03,880 --> 00:33:04,120
Speaker 2: Yep.

649
00:33:04,560 --> 00:33:06,400
Speaker 1: When we don't know how we learn, like we learn,

650
00:33:06,560 --> 00:33:11,080
Speaker 1: we learn intentionally but also unintentionally societal yup conditions around us,

651
00:33:11,080 --> 00:33:13,480
Speaker 1: how we felt in a particular moment. Vastly memory is

652
00:33:13,480 --> 00:33:16,680
Speaker 1: also insane yep, yep. We experience the world in this

653
00:33:16,760 --> 00:33:19,000
Speaker 1: is my personal experience. My experience of the world is

654
00:33:19,080 --> 00:33:21,440
Speaker 1: vastly different to my memory. My memory is like crystal

655
00:33:21,440 --> 00:33:24,440
Speaker 1: clear and beautiful, and my real life is a mixture

656
00:33:24,440 --> 00:33:28,120
Speaker 1: of slops. Yeah, and it's it's frustrating as well. Books

657
00:33:28,120 --> 00:33:30,840
Speaker 1: of these people also donut pits are like people. They

658
00:33:30,880 --> 00:33:32,720
Speaker 1: don't they don't like the human brain is kind of

659
00:33:33,000 --> 00:33:35,080
Speaker 1: like human bodies, even the dumbest dumb dumb it's kind

660
00:33:35,080 --> 00:33:36,480
Speaker 1: of amazing yep thing.

661
00:33:36,880 --> 00:33:39,560
Speaker 2: Yeah, no, And one of the things that's amazing is, Yeah,

662
00:33:39,560 --> 00:33:41,480
Speaker 2: we don't know how the human brain works. We don't

663
00:33:41,520 --> 00:33:43,840
Speaker 2: know how thinking or learning works. But what we do

664
00:33:43,920 --> 00:33:46,200
Speaker 2: know is that we don't do it in anything like

665
00:33:46,320 --> 00:33:51,280
Speaker 2: any way anything like on LLM. Yes, right, because the

666
00:33:51,440 --> 00:33:56,040
Speaker 2: amount of you know, material that we take in over

667
00:33:56,080 --> 00:33:58,520
Speaker 2: the course of the first three years of our lives.

668
00:33:58,560 --> 00:34:00,360
Speaker 2: When we go from not knowing a length which to

669
00:34:00,400 --> 00:34:04,360
Speaker 2: knowing a language, maybe multiple languages, is nowhere near the

670
00:34:04,400 --> 00:34:07,240
Speaker 2: amount of material that is, you know, force fed into

671
00:34:07,280 --> 00:34:10,120
Speaker 2: these llms, And yet we get the trick done, and

672
00:34:10,600 --> 00:34:13,000
Speaker 2: three year olds know things that no LLM knows.

673
00:34:13,000 --> 00:34:15,640
Speaker 1: Also, there's no affordance for the fact fact that some

674
00:34:15,680 --> 00:34:18,120
Speaker 1: people can't learn stuff like I cannot learn languages.

675
00:34:18,160 --> 00:34:20,200
Speaker 2: I've really tried. I'm pretty trash of that too.

676
00:34:20,200 --> 00:34:21,719
Speaker 1: But I also was really bad at like I was

677
00:34:21,800 --> 00:34:23,400
Speaker 1: uniquely bad at a lot of things. I have my

678
00:34:23,520 --> 00:34:27,359
Speaker 1: various no but I have ADHD, dyspraxia and other stuff

679
00:34:27,400 --> 00:34:30,680
Speaker 1: I won't get into. But it's I can't like certain things,

680
00:34:30,680 --> 00:34:33,360
Speaker 1: don't like the things that I pick up insanely quickly.

681
00:34:34,040 --> 00:34:36,280
Speaker 1: Other people can't. Other people can't even see the connections.

682
00:34:36,320 --> 00:34:38,319
Speaker 1: It doesn't Robert Evans actually had a really good point

683
00:34:38,360 --> 00:34:40,280
Speaker 1: on the subreddit Yes Robert, I read all your stuff,

684
00:34:41,280 --> 00:34:43,399
Speaker 1: where he was saying that like he is very good

685
00:34:43,440 --> 00:34:45,840
Speaker 1: at like picking up stuff like almost to me, he

686
00:34:45,840 --> 00:34:47,879
Speaker 1: can read fast than most people as long as it's

687
00:34:47,880 --> 00:34:51,279
Speaker 1: about conflict and it's no, but it's true, and it's

688
00:34:51,280 --> 00:34:53,440
Speaker 1: one of the remarkable things about the human brain. And

689
00:34:53,480 --> 00:34:56,920
Speaker 1: I think that it's actually kind of disgusting how little

690
00:34:56,920 --> 00:34:59,520
Speaker 1: appreciation that is for like human bodies and the brain,

691
00:35:00,080 --> 00:35:02,640
Speaker 1: how incredible the average busts, even average people are.

692
00:35:02,800 --> 00:35:04,800
Speaker 2: Yeah, no, and this is this is the thing. These

693
00:35:04,800 --> 00:35:08,160
Speaker 2: guys don't have a proper appreciation for the human brain

694
00:35:08,200 --> 00:35:11,360
Speaker 2: and the human body. And going back to the tech billionaires,

695
00:35:11,440 --> 00:35:13,759
Speaker 2: and I guess Yodkowski as well, they don't have an

696
00:35:13,760 --> 00:35:17,640
Speaker 2: appreciation for how remarkable Earth is in particular, right, you

697
00:35:17,680 --> 00:35:22,800
Speaker 2: know they you know, especially when you talk about somebody

698
00:35:22,840 --> 00:35:26,320
Speaker 2: like Bezos or Musk, they talk about Earth like it's doomed,

699
00:35:26,680 --> 00:35:29,160
Speaker 2: Like we need to get off of this planet. Yeah,

700
00:35:29,360 --> 00:35:32,720
Speaker 2: like this is this is our home. It's a remarkable place,

701
00:35:33,040 --> 00:35:36,480
Speaker 2: and there is nowhere that we could get to in

702
00:35:36,520 --> 00:35:39,360
Speaker 2: the Solar System. There's nowhere else in the Solar System

703
00:35:39,400 --> 00:35:43,480
Speaker 2: that's remotely as as hospitable as the Earth.

704
00:35:43,480 --> 00:35:45,920
Speaker 1: I also think that they want more. They want their

705
00:35:45,960 --> 00:35:48,000
Speaker 1: own land, they want their own countries, they want they

706
00:35:48,040 --> 00:35:49,160
Speaker 1: want to escape governance.

707
00:35:49,360 --> 00:35:51,799
Speaker 2: Yeah, yeah, they see they see spaces and escape from

708
00:35:51,880 --> 00:35:55,720
Speaker 2: politics because they they're like living a libertarian wet drenk, which.

709
00:35:55,600 --> 00:35:56,080
Speaker 1: Is really funny.

710
00:35:56,120 --> 00:35:58,360
Speaker 2: Because when they get that, they'll immediately do fascism.

711
00:35:58,480 --> 00:36:00,000
Speaker 1: Yeah, that's what's on the agenda.

712
00:36:00,239 --> 00:36:03,439
Speaker 2: Second, can't you cannot run away from politics to minute

713
00:36:03,480 --> 00:36:06,240
Speaker 2: you have more than one person in a room, there's good.

714
00:36:07,000 --> 00:36:08,239
Speaker 2: It's just really sad.

715
00:36:08,239 --> 00:36:10,279
Speaker 1: And I actually think on a grander scale, they don't

716
00:36:10,320 --> 00:36:12,600
Speaker 1: have an appreciation for tech. I was just writing something

717
00:36:12,920 --> 00:36:14,759
Speaker 1: last night. It was on the way to New York

718
00:36:15,440 --> 00:36:18,120
Speaker 1: where it was like the actual state of technology is

719
00:36:18,200 --> 00:36:20,560
Speaker 1: kind of fucking amazing. Yeah, like we can message I

720
00:36:20,560 --> 00:36:22,800
Speaker 1: could message you happen to be in town, you message

721
00:36:22,840 --> 00:36:25,600
Speaker 1: me on blue Sky hundreds of miles thousands of miles away.

722
00:36:25,920 --> 00:36:27,880
Speaker 1: I was like, I'm able to write a note that

723
00:36:27,960 --> 00:36:30,880
Speaker 1: was on my computer, that's on my iPad here. I

724
00:36:30,920 --> 00:36:33,439
Speaker 1: know that this sounds like boosting, but it really isn't.

725
00:36:33,600 --> 00:36:36,520
Speaker 1: We have the raw tools that are just fucking incredible. Yeah,

726
00:36:36,560 --> 00:36:39,640
Speaker 1: and these people do not appreciate them. They don't appreciate them,

727
00:36:39,800 --> 00:36:41,960
Speaker 1: which is why general if AI is so fucking ugly

728
00:36:42,000 --> 00:36:45,399
Speaker 1: because it's bad technology. It's not even good technology. It's

729
00:36:45,680 --> 00:36:50,520
Speaker 1: poorly run, inefficient, endlessly expensive, and directionless.

730
00:36:50,640 --> 00:36:54,880
Speaker 2: Yeah, and it inflicts harms on users that like we

731
00:36:54,960 --> 00:36:58,400
Speaker 2: would not accept from anything that was not subjected to

732
00:36:58,440 --> 00:36:59,719
Speaker 2: such an enormous hype cycle.

733
00:36:59,800 --> 00:37:02,840
Speaker 1: Right literally nothing, yeah, nothing, No, if ten.

734
00:37:02,800 --> 00:37:07,840
Speaker 2: Years ago you you know, took any you know person

735
00:37:08,080 --> 00:37:11,480
Speaker 2: off the street and said, hey, there's this cool new technology.

736
00:37:11,920 --> 00:37:16,800
Speaker 2: It takes up enormous amounts of electricity. It can do things.

737
00:37:16,880 --> 00:37:18,919
Speaker 2: It can do things that you know, no other piece

738
00:37:18,920 --> 00:37:22,279
Speaker 2: of technology you've ever seen can do. Also, it's very

739
00:37:22,280 --> 00:37:25,279
Speaker 2: good at talking teenagers into killing themselves. Yes, should we

740
00:37:25,320 --> 00:37:27,160
Speaker 2: release it into the you know, wider.

741
00:37:26,880 --> 00:37:29,759
Speaker 1: World, And they'll say, well, no, but can do anything else?

742
00:37:29,800 --> 00:37:31,560
Speaker 1: And you, of course would say yeah. It can sometimes

743
00:37:31,560 --> 00:37:35,000
Speaker 1: write code, yeah exactly. And sometimes it also gets things

744
00:37:35,000 --> 00:37:36,520
Speaker 1: horribly wrong and.

745
00:37:36,680 --> 00:37:40,879
Speaker 2: It writes bad pros. Yeah like, and it just kind

746
00:37:40,880 --> 00:37:43,719
Speaker 2: of makes everything feel kind of mediocre and smeared out,

747
00:37:43,800 --> 00:37:49,000
Speaker 2: yes exactly, like, yeah exactly, and it makes some people

748
00:37:49,239 --> 00:37:50,160
Speaker 2: go crazy.

749
00:37:49,880 --> 00:37:52,600
Speaker 1: And yeah, it drives people to actually, yeah, how do

750
00:37:52,680 --> 00:37:55,279
Speaker 1: you feel about that? Like, how do you like did

751
00:37:55,320 --> 00:37:57,200
Speaker 1: you see this coming? Because this really jumped out No.

752
00:37:57,520 --> 00:37:59,759
Speaker 2: Yeah, no, no, this surprised me. This did surprise the hell

753
00:37:59,760 --> 00:38:05,279
Speaker 2: out of me because I think that you know, these machines,

754
00:38:06,360 --> 00:38:08,800
Speaker 2: I don't even like calling them AI right, because I

755
00:38:08,840 --> 00:38:11,000
Speaker 2: think that's a marketing term. It is. Yeah, like if

756
00:38:11,040 --> 00:38:14,320
Speaker 2: you go back in time to you know, nineteen ninety

757
00:38:14,840 --> 00:38:18,000
Speaker 2: and tell me when I'm a kid, Hey, I have

758
00:38:18,040 --> 00:38:20,000
Speaker 2: a little device in my pocket that lets me talk

759
00:38:20,040 --> 00:38:24,560
Speaker 2: to an AI and and then you know, I would

760
00:38:24,600 --> 00:38:27,000
Speaker 2: have thought, oh, like that lets me talk to you know,

761
00:38:27,280 --> 00:38:30,879
Speaker 2: like command or data from start exciting, And instead it's this,

762
00:38:31,000 --> 00:38:32,799
Speaker 2: and I would have been like, what the hell is that? No,

763
00:38:32,920 --> 00:38:37,440
Speaker 2: AI is this marketing term. It's it's a text generation engine.

764
00:38:37,440 --> 00:38:44,440
Speaker 2: It it it produces you know, homogenized thought like product.

765
00:38:45,680 --> 00:38:45,920
Speaker 2: I was.

766
00:38:45,960 --> 00:38:49,080
Speaker 1: Also, I'm in the midst of a long one as usual.

767
00:38:49,600 --> 00:38:54,200
Speaker 1: It also conflates doing stuff with outputs. I know that

768
00:38:54,239 --> 00:38:56,200
Speaker 1: sounds kind of flat, but it's like that everything is

769
00:38:56,239 --> 00:38:59,359
Speaker 1: a unit of work rather than actually creating stuff. Well

770
00:38:59,360 --> 00:39:00,920
Speaker 1: that you pay an you pay a person for their

771
00:39:00,960 --> 00:39:04,640
Speaker 1: experience too. And it's just also not very good at

772
00:39:04,680 --> 00:39:08,280
Speaker 1: Stuff's pissing me. No, really, it's really bad at stuff.

773
00:39:08,320 --> 00:39:10,360
Speaker 2: It is. And I think, and I think that's where

774
00:39:10,719 --> 00:39:13,640
Speaker 2: you know, this sort of driving people insane is coming from, right,

775
00:39:13,800 --> 00:39:18,600
Speaker 2: Like I I like what I missed. The reason I

776
00:39:18,600 --> 00:39:21,080
Speaker 2: think I didn't see that coming is I failed to

777
00:39:21,120 --> 00:39:26,279
Speaker 2: think about how like I knew that these things just

778
00:39:26,400 --> 00:39:28,200
Speaker 2: generate text and in a lot of ways they just

779
00:39:28,239 --> 00:39:31,960
Speaker 2: sort of spit out back to you what you put

780
00:39:32,000 --> 00:39:34,640
Speaker 2: in right, right, which is which is an old thing

781
00:39:34,719 --> 00:39:37,400
Speaker 2: with chatbots that goes way before the LMS, goes all

782
00:39:37,440 --> 00:39:38,920
Speaker 2: the way back to Eliza, right.

783
00:39:39,000 --> 00:39:41,600
Speaker 1: Oh yeah, and that was the first the first AI computer.

784
00:39:41,800 --> 00:39:44,839
Speaker 2: Yeah, the first chapter. I wouldn't even call Eliza AI, right,

785
00:39:44,880 --> 00:39:45,520
Speaker 2: And even.

786
00:39:45,320 --> 00:39:47,719
Speaker 1: The creator of Eliza, god huz. Yeah, this is from

787
00:39:47,800 --> 00:39:50,640
Speaker 1: Karen Howe's Empire of AI. Great bit about it in there.

788
00:39:50,560 --> 00:39:53,440
Speaker 2: Yeah, exactly, Yeah, no, no, no, Eliza. Eliza was just

789
00:39:53,480 --> 00:39:56,520
Speaker 2: like a one hundred or so lines of code that

790
00:39:56,600 --> 00:39:58,360
Speaker 2: you know, you'd say I'm having a bad day, and

791
00:39:58,360 --> 00:40:00,319
Speaker 2: it would say, oh, I'm sorry to hear that. Yeah,

792
00:40:00,600 --> 00:40:03,279
Speaker 2: why are you having a bad day? Right?

793
00:40:03,880 --> 00:40:08,400
Speaker 1: But like the gassing engine, the yeah.

794
00:40:08,000 --> 00:40:10,759
Speaker 2: Like that's the thing I didn't think about. Oh wait,

795
00:40:10,800 --> 00:40:13,200
Speaker 2: if it just repeats back what you put in, but

796
00:40:13,280 --> 00:40:15,600
Speaker 2: it does it in a way that's compelling and convincing

797
00:40:15,640 --> 00:40:18,160
Speaker 2: to some people, that's going to just get them sort

798
00:40:18,200 --> 00:40:21,400
Speaker 2: of caught in this like dope meine self validation loop,

799
00:40:21,760 --> 00:40:23,560
Speaker 2: and that could drive them off the edge.

800
00:40:23,600 --> 00:40:26,400
Speaker 1: And I think that there is a condescension. I judge

801
00:40:26,400 --> 00:40:28,480
Speaker 1: myself for this where I was like, oh, this doesn't

802
00:40:28,480 --> 00:40:32,480
Speaker 1: fool me, and it's like, but the harm also of

803
00:40:32,600 --> 00:40:34,759
Speaker 1: I'm very I'm blessed to have tons of people who

804
00:40:34,760 --> 00:40:38,360
Speaker 1: love me who also you give me clear feedback, which

805
00:40:38,400 --> 00:40:40,040
Speaker 1: is not just what I want to hear. But I

806
00:40:40,080 --> 00:40:42,960
Speaker 1: definitely when I was younger and very depressed, like crave

807
00:40:43,280 --> 00:40:45,719
Speaker 1: validation and crave someone to just tell me what I

808
00:40:45,760 --> 00:40:49,080
Speaker 1: want to hear, I definitely never thought what if someone did,

809
00:40:49,280 --> 00:40:53,719
Speaker 1: and the actual danger of having every fucking thought validated,

810
00:40:54,719 --> 00:40:57,000
Speaker 1: and also just the sheer horrors Like Matt Hughes, my

811
00:40:57,160 --> 00:40:58,960
Speaker 1: editor just did a great story about this kind of

812
00:40:58,960 --> 00:41:01,560
Speaker 1: horrible story where he's simulated someone going through a mental

813
00:41:01,560 --> 00:41:05,120
Speaker 1: health episode, and Claude was very clear to go, yeah, man,

814
00:41:05,160 --> 00:41:07,240
Speaker 1: you don't seem so good, chatchip. It's like, no, everyone

815
00:41:07,320 --> 00:41:09,719
Speaker 1: is not to get you made. Yeah, actually, it's in

816
00:41:10,000 --> 00:41:12,719
Speaker 1: any other tick in the world did this. You'd shut

817
00:41:12,760 --> 00:41:15,400
Speaker 1: the ship down immediately. Yeah, exactly, close it, you know,

818
00:41:15,680 --> 00:41:18,200
Speaker 1: But where's fucking Eliezer on this bullshit?

819
00:41:18,400 --> 00:41:19,479
Speaker 2: Because this feels like.

820
00:41:19,440 --> 00:41:22,279
Speaker 1: If you write a book about how everyone dies, this

821
00:41:22,320 --> 00:41:24,720
Speaker 1: should be the thing that if he actually believed in anything,

822
00:41:25,160 --> 00:41:27,360
Speaker 1: would he should be up saying like, hey, look, this

823
00:41:27,520 --> 00:41:28,560
Speaker 1: is what I was talking about.

824
00:41:28,680 --> 00:41:30,719
Speaker 2: Oh, I mean I I do think that he thinks

825
00:41:30,800 --> 00:41:34,120
Speaker 2: this is like an incipient version of what he's talking about.

826
00:41:34,160 --> 00:41:36,120
Speaker 2: I think, like a baby version. I think he loves it.

827
00:41:36,239 --> 00:41:39,279
Speaker 2: I think I think it helps him out well. I

828
00:41:39,320 --> 00:41:43,680
Speaker 2: think that he finds that useful for making the argument

829
00:41:43,719 --> 00:41:46,680
Speaker 2: that he made exactly. But he is not again the

830
00:41:46,800 --> 00:41:48,920
Speaker 2: argument he's making. And this is the only nice thing

831
00:41:48,960 --> 00:41:52,040
Speaker 2: I'll say about him. He means it, seriously, He's not

832
00:41:52,080 --> 00:41:55,520
Speaker 2: a grifter. He's three anxiety disorders in a trench coat.

833
00:41:56,960 --> 00:42:00,560
Speaker 1: Damn you put that on a fucking book, coach, stupid ass.

834
00:42:11,920 --> 00:42:16,400
Speaker 1: I can't think of any other movement in tech ever, Yeah,

835
00:42:16,440 --> 00:42:19,120
Speaker 1: there is anything like this, specifically because of how much

836
00:42:19,160 --> 00:42:21,000
Speaker 1: it sucks us, Like, I can't think of any maybe

837
00:42:21,040 --> 00:42:23,160
Speaker 1: the metavers and crypto, but even then, I don't like

838
00:42:23,200 --> 00:42:25,560
Speaker 1: the comparison. Yeah, they're so much smaller.

839
00:42:25,800 --> 00:42:29,279
Speaker 2: Honestly, what I keep thinking about is is that in

840
00:42:29,360 --> 00:42:33,600
Speaker 2: a way, it is taking the daily experience of the

841
00:42:33,719 --> 00:42:37,399
Speaker 2: tech billionaires and like bringing it to the masses, right,

842
00:42:37,440 --> 00:42:38,120
Speaker 2: because what is it?

843
00:42:38,280 --> 00:42:38,480
Speaker 1: Low?

844
00:42:38,640 --> 00:42:43,440
Speaker 2: Yeah, what is it like to be Sam Altman?

845
00:42:43,600 --> 00:42:43,839
Speaker 1: Right?

846
00:42:44,080 --> 00:42:47,479
Speaker 2: You've got billions of dollars and you're surrounded by people

847
00:42:47,520 --> 00:42:50,520
Speaker 2: who will never tell you no and validate your every thought.

848
00:42:50,360 --> 00:42:53,400
Speaker 1: And they'll convince you that you understand every subject exactly.

849
00:42:53,840 --> 00:42:55,959
Speaker 2: Yeah, and now, well.

850
00:42:55,880 --> 00:42:58,239
Speaker 1: I've been saying this as well, because if you're an executive,

851
00:42:58,280 --> 00:43:01,520
Speaker 1: a machine that can write emails, readium and otherwise you

852
00:43:01,560 --> 00:43:03,600
Speaker 1: go to lunch, it's kind of magic. Yeah, but no,

853
00:43:03,800 --> 00:43:05,839
Speaker 1: I like this idea that it's the extension as well,

854
00:43:05,880 --> 00:43:09,360
Speaker 1: just this completely like separate thing that just as Yeah,

855
00:43:09,400 --> 00:43:11,160
Speaker 1: that's completely right, man, I fully agree.

856
00:43:11,280 --> 00:43:14,080
Speaker 2: Right, And so of course they don't see the harm

857
00:43:14,360 --> 00:43:17,800
Speaker 2: because that's their entire goddamn all that happens, and so

858
00:43:17,840 --> 00:43:19,800
Speaker 2: the well, but if this were bad for people, that

859
00:43:19,840 --> 00:43:21,880
Speaker 2: would mean that, you know, I'm in a bad environment.

860
00:43:21,920 --> 00:43:24,600
Speaker 2: That's unhealthy for me, and like, yeah, actually it is,

861
00:43:24,920 --> 00:43:26,719
Speaker 2: but they don't think they don't think that. But I

862
00:43:27,120 --> 00:43:31,359
Speaker 2: genuinely believe that like the best thing for the tech

863
00:43:31,400 --> 00:43:33,680
Speaker 2: billionaires themselves that could happen to them would be to

864
00:43:33,719 --> 00:43:35,319
Speaker 2: lose all their money, would be the best thing for

865
00:43:35,320 --> 00:43:37,040
Speaker 2: their mental health, put man of them.

866
00:43:37,120 --> 00:43:39,960
Speaker 1: Yeah, no, let me get them on the show. I

867
00:43:40,000 --> 00:43:41,799
Speaker 1: think that I could have a great chat with any

868
00:43:41,840 --> 00:43:45,400
Speaker 1: of them. Sure, just because I went to a private school.

869
00:43:45,440 --> 00:43:48,719
Speaker 1: Like a lot of these American billionaires as well, they

870
00:43:48,719 --> 00:43:52,440
Speaker 1: would get destroyed by the average scum aristocrats of old

871
00:43:52,440 --> 00:43:55,160
Speaker 1: in England, like the real blood drinkers.

872
00:43:56,520 --> 00:43:57,680
Speaker 2: They're amateur vampire.

873
00:43:57,960 --> 00:44:01,759
Speaker 1: No they really are though, like like they It's the

874
00:44:01,800 --> 00:44:05,120
Speaker 1: classic thing why British colonialism and American colonialism have never

875
00:44:05,120 --> 00:44:08,240
Speaker 1: matched up, because Britain was just evil. They just fucking

876
00:44:08,320 --> 00:44:10,480
Speaker 1: murdered people and destroyed communities. And they're like, why are

877
00:44:10,440 --> 00:44:11,960
Speaker 1: we're doing this? Of course we're British. This is what

878
00:44:12,000 --> 00:44:14,880
Speaker 1: we do here. What do you mean, what's a moral?

879
00:44:14,920 --> 00:44:15,640
Speaker 1: I've not heard of that.

880
00:44:16,200 --> 00:44:17,040
Speaker 2: No, what do you mean?

881
00:44:17,080 --> 00:44:19,840
Speaker 1: No? No, send my send my eighth cousin to to Africa,

882
00:44:19,920 --> 00:44:23,240
Speaker 1: shoot whoever you see. Like that was the horrifying stuff.

883
00:44:23,280 --> 00:44:26,680
Speaker 1: But they knew they didn't care about what people think.

884
00:44:26,719 --> 00:44:28,240
Speaker 1: I still think the billionaires care.

885
00:44:28,200 --> 00:44:30,360
Speaker 2: Oh, they definitely do. Like this is this is the

886
00:44:30,400 --> 00:44:31,160
Speaker 2: thing that which.

887
00:44:30,960 --> 00:44:33,040
Speaker 1: Is insane to me. If I had had one billion dollars,

888
00:44:33,080 --> 00:44:34,160
Speaker 1: I would no longer care.

889
00:44:34,280 --> 00:44:36,360
Speaker 2: Well, if I had a billion dollars, I would just

890
00:44:36,400 --> 00:44:39,040
Speaker 2: try to make sure that nobody knew my name and

891
00:44:39,120 --> 00:44:40,480
Speaker 2: that you know, it's the same amount.

892
00:44:40,640 --> 00:44:42,759
Speaker 1: Yeah, well I would be posting.

893
00:44:42,760 --> 00:44:45,080
Speaker 2: No, I think I think I'd just be done. Man,

894
00:44:45,120 --> 00:44:47,800
Speaker 2: I'd be like, okay, cool, you know, I'm gonna donate

895
00:44:47,840 --> 00:44:50,279
Speaker 2: to a bunch of causes that mattered to men, and

896
00:44:50,320 --> 00:44:52,399
Speaker 2: you know, like I still think it's bad for them

897
00:44:52,440 --> 00:44:54,640
Speaker 2: to be billionaires, and I try to try to change that,

898
00:44:54,880 --> 00:44:57,200
Speaker 2: but also like I'm just just gonna, like, you know,

899
00:44:57,400 --> 00:44:59,400
Speaker 2: hang out in a nice house with my friends and

900
00:44:59,480 --> 00:45:00,000
Speaker 2: have a good time.

901
00:45:00,280 --> 00:45:03,000
Speaker 1: That's the problem though they don't have those.

902
00:45:03,160 --> 00:45:04,480
Speaker 2: Well, yeah, because you've heard that.

903
00:45:04,520 --> 00:45:06,799
Speaker 1: Have you ever heard the really depressing story about Elon

904
00:45:06,880 --> 00:45:10,080
Speaker 1: Musk and this guy called here was this investor who

905
00:45:10,120 --> 00:45:13,560
Speaker 1: got really cooked by COVID Peter something, and he know

906
00:45:13,680 --> 00:45:15,920
Speaker 1: this story of going over to Elon Musk's house and

907
00:45:15,960 --> 00:45:18,839
Speaker 1: there was a decanter of wine and Elon Musk picked

908
00:45:18,920 --> 00:45:21,160
Speaker 1: up the wine before it's done decanting, and then something

909
00:45:21,280 --> 00:45:23,319
Speaker 1: said something along the lines of honey, badger, don't care.

910
00:45:23,760 --> 00:45:25,120
Speaker 1: And I just want to say, that's one of the

911
00:45:25,200 --> 00:45:29,040
Speaker 1: saddest fucking things I've heard in my life, just absolutely,

912
00:45:29,080 --> 00:45:32,160
Speaker 1: just unfathomably depressing. Because you can get things like a

913
00:45:32,160 --> 00:45:34,760
Speaker 1: coravan that can kind of aerrate it. There are various

914
00:45:34,760 --> 00:45:37,160
Speaker 1: ways around ourration. If you're really feeling it and you

915
00:45:37,280 --> 00:45:40,240
Speaker 1: have hundreds of billions or what, however many many dollars

916
00:45:40,520 --> 00:45:44,520
Speaker 1: Elon has liquid, you could just have someone whose job

917
00:45:44,600 --> 00:45:46,799
Speaker 1: is to make sure the wine is errated. They could

918
00:45:46,840 --> 00:45:48,560
Speaker 1: make two hundred and fifty thousand dollars a year. It

919
00:45:48,600 --> 00:45:50,520
Speaker 1: wouldn't matter to you. That's what you lose in the couch.

920
00:45:50,840 --> 00:45:53,040
Speaker 2: Yeah, but I think that what matters to Elon is

921
00:45:53,120 --> 00:45:56,120
Speaker 2: not doing what he's supposed to do, right. Yeah, he

922
00:45:56,160 --> 00:45:57,719
Speaker 2: can be seen as cool.

923
00:45:57,560 --> 00:46:00,319
Speaker 1: Or just drinking as quickly well, because otherwise he might

924
00:46:00,360 --> 00:46:01,080
Speaker 1: feel something.

925
00:46:01,280 --> 00:46:04,560
Speaker 2: Yeah, I mean, I just he desperately wants to be

926
00:46:04,760 --> 00:46:06,680
Speaker 2: liked and it's never gonna happen.

927
00:46:07,200 --> 00:46:08,839
Speaker 1: It's so funny as well, because it could be so

928
00:46:08,920 --> 00:46:10,920
Speaker 1: easy for him. I know, he could just post this

929
00:46:11,000 --> 00:46:12,759
Speaker 1: lunch every day and nothing else. Then would be like,

930
00:46:13,320 --> 00:46:15,560
Speaker 1: look at this is actually what pisses me off as well, though,

931
00:46:15,560 --> 00:46:18,239
Speaker 1: because people like el must fucking sucks. It's like he

932
00:46:18,360 --> 00:46:21,720
Speaker 1: was sending people off to Aaron Bieber, a science reporter.

933
00:46:21,640 --> 00:46:23,839
Speaker 2: In twenty one's a friend of mine.

934
00:46:23,880 --> 00:46:26,680
Speaker 1: Yeah, that's p and like when that happened, not a

935
00:46:26,719 --> 00:46:29,120
Speaker 1: single Kara Swisher didn't say shit, then here Kevin Rouse

936
00:46:29,160 --> 00:46:31,480
Speaker 1: Case and you and on these fucking people I thought necessary,

937
00:46:31,520 --> 00:46:31,920
Speaker 1: but now.

938
00:46:31,800 --> 00:46:33,960
Speaker 2: Like must have such a bad guy. He's such a

939
00:46:34,000 --> 00:46:35,480
Speaker 2: bad No, he's always been like.

940
00:46:35,480 --> 00:46:38,040
Speaker 1: And also he called a guy a pedophile for saving

941
00:46:38,120 --> 00:46:41,600
Speaker 1: children yep, because he wasn't allowed to send his submarine.

942
00:46:42,760 --> 00:46:45,000
Speaker 2: No, he's never been good like this is this is

943
00:46:45,040 --> 00:46:46,000
Speaker 2: the thing that I.

944
00:46:45,920 --> 00:46:48,399
Speaker 1: Don't think any of these people enjoy anything as much

945
00:46:48,400 --> 00:46:51,680
Speaker 1: as I enjoyed diet coke. Like I'm one hundred percent

946
00:46:51,680 --> 00:46:53,600
Speaker 1: sure of that, because I love these things. Like it's

947
00:46:53,760 --> 00:46:56,040
Speaker 1: if this kills me, if this shit's meant to like

948
00:46:56,120 --> 00:46:58,719
Speaker 1: in three years, they're like, it's rat blood, Like I'm like,

949
00:46:58,800 --> 00:46:59,200
Speaker 1: I will.

950
00:46:59,120 --> 00:47:02,160
Speaker 2: Keep drinking offline brought to you by Diet Coke.

951
00:47:02,280 --> 00:47:06,719
Speaker 1: It's rap blood. I really hope that you spokes the

952
00:47:06,719 --> 00:47:09,239
Speaker 1: show at one point, so that's the commercial. But that's

953
00:47:09,280 --> 00:47:11,640
Speaker 1: the thing, Like I'm only kind of joking because it's

954
00:47:11,840 --> 00:47:13,840
Speaker 1: I really enjoyed that coke. I'm sitting down chat and

955
00:47:13,920 --> 00:47:15,719
Speaker 1: chew with my friends. I love watching football with chat

956
00:47:15,719 --> 00:47:18,160
Speaker 1: with my friends. Like it's like there are very basic

957
00:47:18,200 --> 00:47:20,560
Speaker 1: things I enjoy. What do these people Like? These people

958
00:47:20,600 --> 00:47:23,240
Speaker 1: just must walk around in this haze of anger, yeah,

959
00:47:23,320 --> 00:47:24,640
Speaker 1: or like emptiness.

960
00:47:24,719 --> 00:47:27,160
Speaker 2: I think they're they're really cut off from their own emotions,

961
00:47:27,320 --> 00:47:29,640
Speaker 2: right and like and again, that's gonna happen if you

962
00:47:29,680 --> 00:47:33,040
Speaker 2: just constantly get validation, right, you know. One of one

963
00:47:33,080 --> 00:47:36,360
Speaker 2: of the many tweets from back when Twitter was less shitty,

964
00:47:36,440 --> 00:47:40,080
Speaker 2: before Musk bought it. There are many tweets that just

965
00:47:40,120 --> 00:47:41,840
Speaker 2: like live rent free in my head, and one of

966
00:47:41,840 --> 00:47:48,239
Speaker 2: them is about the cognitive impact of being a billionaire. Yeah,

967
00:47:48,320 --> 00:47:50,840
Speaker 2: it ends. It's like, you know, like everything around you

968
00:47:50,920 --> 00:47:56,160
Speaker 2: is really expensive. It's just a constant every chair fifty Yeah,

969
00:47:56,160 --> 00:47:58,600
Speaker 2: in terms of the cognitive impact, it must be you know,

970
00:47:58,680 --> 00:48:00,719
Speaker 2: roughly equivalent to being kicked in the head by a

971
00:48:00,800 --> 00:48:02,719
Speaker 2: horse every day exactly. Yeah.

972
00:48:02,760 --> 00:48:06,600
Speaker 1: I think I'd be fine, but that's my pathology, I guess,

973
00:48:06,719 --> 00:48:10,080
Speaker 1: but it no, but it's they have this weird isolated thing.

974
00:48:10,120 --> 00:48:13,120
Speaker 1: And even Benioff, who used to seem okay.

975
00:48:13,000 --> 00:48:15,400
Speaker 2: Well, I mean he his whole game was like to

976
00:48:15,480 --> 00:48:17,480
Speaker 2: be the best of the billionaires.

977
00:48:17,000 --> 00:48:19,359
Speaker 1: Which love are, and then he was just like, ah,

978
00:48:19,440 --> 00:48:22,480
Speaker 1: fuck it, yep, just fuck it. I don't give a

979
00:48:22,480 --> 00:48:26,200
Speaker 1: shit anymore. Yeah, Agent Force, it doesn't sell to anyone.

980
00:48:26,239 --> 00:48:28,600
Speaker 1: No one likes it, but it's the future agent for

981
00:48:28,719 --> 00:48:30,680
Speaker 1: us Jesus, he's.

982
00:48:30,520 --> 00:48:32,160
Speaker 2: Donated to all. I know, it's so cool.

983
00:48:32,239 --> 00:48:34,480
Speaker 1: It must be really cool being a guy who actually

984
00:48:34,520 --> 00:48:38,799
Speaker 1: has qualifications and from from proving things to watch the

985
00:48:38,840 --> 00:48:40,880
Speaker 1: world like all these guys being like, yeah, this is

986
00:48:40,880 --> 00:48:43,279
Speaker 1: the future and just because want to go it doesn't work.

987
00:48:43,320 --> 00:48:45,960
Speaker 2: No one likes it. Yeah, I mean cool is one word.

988
00:48:46,120 --> 00:48:47,800
Speaker 2: Incredibly frustrating is another.

989
00:48:48,040 --> 00:48:50,920
Speaker 1: Right, this is this is stymying real innovation.

990
00:48:51,160 --> 00:48:54,440
Speaker 2: Yeah, yeah, I know there's opportunity costs and and also

991
00:48:54,640 --> 00:48:59,080
Speaker 2: just like actual stifling of real innovation in the effort

992
00:48:59,160 --> 00:49:02,319
Speaker 2: to achieve even possible ends that would be bad even

993
00:49:02,360 --> 00:49:03,560
Speaker 2: if we could achieve them.

994
00:49:03,719 --> 00:49:08,040
Speaker 1: So slight directional shift. Is there anything within like science

995
00:49:08,040 --> 00:49:10,640
Speaker 1: and tech innovation that you're actually excited about? Anything you

996
00:49:10,640 --> 00:49:12,400
Speaker 1: look at and like that's fucking cool.

997
00:49:12,560 --> 00:49:14,759
Speaker 2: I mean mRNA vaccines are the first thing that comes

998
00:49:14,800 --> 00:49:16,760
Speaker 2: about exactly. Yeah, they're really awesome.

999
00:49:17,000 --> 00:49:17,520
Speaker 1: Tell them.

1000
00:49:17,920 --> 00:49:21,160
Speaker 2: I mean, like, look, you know the fact and what is.

1001
00:49:21,160 --> 00:49:24,279
Speaker 1: An mri NA vaccine said flawlessly.

1002
00:49:23,960 --> 00:49:31,080
Speaker 2: Yeah, an m now I'm able. Yeah, and mRNA vaccine.

1003
00:49:31,680 --> 00:49:36,640
Speaker 3: Yeah, it's the kind of thing that that you know,

1004
00:49:36,680 --> 00:49:41,799
Speaker 3: we have with the COVID vaccines, right, Basically, the thing

1005
00:49:41,840 --> 00:49:43,880
Speaker 3: that's so exciting about them is that they are so

1006
00:49:44,160 --> 00:49:49,560
Speaker 3: much easier and faster to synthesize, right than previous vaccines.

1007
00:49:50,520 --> 00:49:53,960
Speaker 2: You know, I think the previous record before the COVID vaccine,

1008
00:49:54,600 --> 00:49:58,080
Speaker 2: for you know, how long it took to develop a safe,

1009
00:49:58,080 --> 00:50:02,000
Speaker 2: widely deployed vaccine with something like five to ten years, Jesus,

1010
00:50:02,040 --> 00:50:05,719
Speaker 2: And then this vaccine. Most of the time delay, most

1011
00:50:05,719 --> 00:50:08,200
Speaker 2: of that year that we were waiting for the vaccine

1012
00:50:09,160 --> 00:50:12,480
Speaker 2: was actually a little less than a year. Most of

1013
00:50:12,520 --> 00:50:15,640
Speaker 2: that was testing. The actual time that it took to

1014
00:50:15,680 --> 00:50:18,399
Speaker 2: synthesize the damn thing was I believe on the order

1015
00:50:18,440 --> 00:50:19,000
Speaker 2: of weeks.

1016
00:50:19,040 --> 00:50:22,200
Speaker 1: And what's crazy is I believe that was venture backed, right, Yeah,

1017
00:50:22,200 --> 00:50:24,000
Speaker 1: some of it was venture backed, which is like, see

1018
00:50:24,040 --> 00:50:25,440
Speaker 1: venu capital can be useful.

1019
00:50:25,239 --> 00:50:28,880
Speaker 2: Yeah, it can be, but once Yeah, some of it

1020
00:50:28,920 --> 00:50:31,080
Speaker 2: was venture backed. Some of it was backed by you know,

1021
00:50:31,239 --> 00:50:35,279
Speaker 2: NIH grants. We do need those, yeah, we surefucking do.

1022
00:50:36,239 --> 00:50:36,319
Speaker 1: No.

1023
00:50:36,480 --> 00:50:41,279
Speaker 2: Government funding of basic research is important and not just

1024
00:50:41,360 --> 00:50:45,640
Speaker 2: because it leads to amazing technological breakthroughs like mRNA vaccines,

1025
00:50:45,960 --> 00:50:50,480
Speaker 2: but also because, like basic scientific research is an important

1026
00:50:50,560 --> 00:50:54,400
Speaker 2: thing for humans to do, like the same way that

1027
00:50:54,600 --> 00:50:58,839
Speaker 2: art is important, right, right, but it also does enable

1028
00:50:58,880 --> 00:51:04,480
Speaker 2: a massive scientific and technological breakthroughs. And I you know,

1029
00:51:04,880 --> 00:51:08,840
Speaker 2: there's promise for MR and A vaccines to like open

1030
00:51:08,960 --> 00:51:12,920
Speaker 2: up a whole new class of vaccines that you know,

1031
00:51:13,000 --> 00:51:16,200
Speaker 2: for things that were previously very hard to vaccinate against.

1032
00:51:17,080 --> 00:51:19,120
Speaker 2: I am not an expert in the field, but like

1033
00:51:19,200 --> 00:51:23,480
Speaker 2: everyone I know who works in biomedicine, they they're all

1034
00:51:23,600 --> 00:51:26,040
Speaker 2: very excited about this, and they're all really depressed by

1035
00:51:26,080 --> 00:51:30,560
Speaker 2: the fact that, you know, we have an antifactor who

1036
00:51:30,680 --> 00:51:33,840
Speaker 2: sounds like a fork that got stuck in a fucking

1037
00:51:33,960 --> 00:51:36,320
Speaker 2: garbage disposal as the Health.

1038
00:51:36,480 --> 00:51:39,680
Speaker 1: And Rise from your Grave guy from that one video. Yeah, yeah,

1039
00:51:39,920 --> 00:51:43,160
Speaker 1: very depressing. I I just wish we were like green

1040
00:51:43,280 --> 00:51:44,840
Speaker 1: energy as well. Feels like an oh.

1041
00:51:44,719 --> 00:51:47,720
Speaker 2: Yeah, green energy was the next thing I was gonna say, Yeah, batteries,

1042
00:51:47,800 --> 00:51:49,400
Speaker 2: solar panels. It's incredible.

1043
00:51:50,960 --> 00:51:54,400
Speaker 1: Uh, this opportunity is there. Yeah, it's we need to innovate,

1044
00:51:55,040 --> 00:51:56,040
Speaker 1: Like we are innovating.

1045
00:51:56,120 --> 00:51:59,440
Speaker 2: But like, yeah, and also like we even had the

1046
00:51:59,560 --> 00:52:02,000
Speaker 2: legislation that we needed, right or some of it right,

1047
00:52:02,120 --> 00:52:06,319
Speaker 2: like the you know Biden's big bill, the Build Back

1048
00:52:06,360 --> 00:52:11,080
Speaker 2: Better It uh, you know, was not a perfect bill,

1049
00:52:11,360 --> 00:52:16,440
Speaker 2: but it was the best environmental bill in American history. Yeah,

1050
00:52:16,480 --> 00:52:20,439
Speaker 2: and and now you know, it's being destroyed because we

1051
00:52:20,560 --> 00:52:23,200
Speaker 2: have a government in this country that that you know,

1052
00:52:23,360 --> 00:52:26,960
Speaker 2: does not believe in climate change and doesn't believe in

1053
00:52:27,000 --> 00:52:29,400
Speaker 2: anything other than short term profits at the expense of

1054
00:52:29,400 --> 00:52:32,640
Speaker 2: everybody else, and also doesn't believe in democracy.

1055
00:52:32,719 --> 00:52:34,920
Speaker 1: That feels that feels like a big problem though, the

1056
00:52:34,960 --> 00:52:37,279
Speaker 1: growth it all cause, Yeah.

1057
00:52:37,000 --> 00:52:39,400
Speaker 2: I mean, that's that's the thing. And that's why my

1058
00:52:39,440 --> 00:52:42,200
Speaker 2: book has the actual title that it does, rather than

1059
00:52:42,239 --> 00:52:43,800
Speaker 2: going with the title these fucking people.

1060
00:52:44,040 --> 00:52:46,600
Speaker 1: Yeah, so these fucking people or just the Bostards. I

1061
00:52:46,600 --> 00:52:47,960
Speaker 1: think it is also very good too.

1062
00:52:48,080 --> 00:52:50,800
Speaker 2: I think so too. I mean, like there's ah, it

1063
00:52:50,800 --> 00:52:52,600
Speaker 2: would be so easy for them to do better, No,

1064
00:52:54,280 --> 00:52:57,360
Speaker 2: like you know, to forget forget the best thing that

1065
00:52:57,360 --> 00:52:59,840
Speaker 2: they could do. They're doing some of the worst things

1066
00:52:59,840 --> 00:53:01,759
Speaker 2: that they could do. Doing better than they are right

1067
00:53:01,760 --> 00:53:03,239
Speaker 2: now is just an incredibly low but.

1068
00:53:03,560 --> 00:53:09,360
Speaker 1: Even through like very poorly guided generosity, they could very easily. Yeah,

1069
00:53:09,400 --> 00:53:11,880
Speaker 1: they could just fund media outlets versus whatever it is

1070
00:53:11,880 --> 00:53:14,560
Speaker 1: they're doing to them, tearing them down.

1071
00:53:14,680 --> 00:53:17,440
Speaker 2: But that would mean, you know the possibility of losing

1072
00:53:17,480 --> 00:53:22,320
Speaker 2: control and losing you know, losing some of their power

1073
00:53:22,360 --> 00:53:24,359
Speaker 2: and money, and they just are not willing to do

1074
00:53:24,400 --> 00:53:27,200
Speaker 2: that because they've got something broken in their hearts.

1075
00:53:27,920 --> 00:53:30,680
Speaker 1: We need to heal them. No, now I think that,

1076
00:53:30,880 --> 00:53:31,320
Speaker 1: I think.

1077
00:53:31,239 --> 00:53:32,960
Speaker 2: I think we need to tax their money away.

1078
00:53:33,080 --> 00:53:36,320
Speaker 1: I think that too, but I think we actually true.

1079
00:53:36,360 --> 00:53:38,680
Speaker 1: My truth here is that we need to change how

1080
00:53:38,719 --> 00:53:41,360
Speaker 1: we do that though. We need to start doing executive

1081
00:53:41,400 --> 00:53:44,160
Speaker 1: liability hmmm. We need to make it so if like

1082
00:53:44,200 --> 00:53:48,160
Speaker 1: CrowdStrike happens again, like a bunch of people potentially get

1083
00:53:48,200 --> 00:53:50,560
Speaker 1: diye in the NHS system because the computer shuts down,

1084
00:53:50,560 --> 00:53:52,719
Speaker 1: that satch and a DELA can lose something because it

1085
00:53:52,800 --> 00:53:55,160
Speaker 1: isn't enough to find the companies. Finding the company is

1086
00:53:55,200 --> 00:53:58,360
Speaker 1: not going to do shit unless you do scaling revenue

1087
00:53:58,440 --> 00:54:00,960
Speaker 1: percentage of revenue. This is this and more and how

1088
00:54:01,000 --> 00:54:01,799
Speaker 1: I become the FTC.

1089
00:54:01,960 --> 00:54:03,120
Speaker 2: No, they I'm not kind of let me.

1090
00:54:03,560 --> 00:54:07,160
Speaker 1: But it's just I feel the one of the wonderful

1091
00:54:07,160 --> 00:54:08,600
Speaker 1: things of having you on is you're able to come

1092
00:54:08,640 --> 00:54:11,480
Speaker 1: at this from a science communicator perspective. You're actually able

1093
00:54:11,480 --> 00:54:14,160
Speaker 1: to because it's not just about what these people want.

1094
00:54:14,200 --> 00:54:17,239
Speaker 1: It's the practicality of it, which is the nothing's really

1095
00:54:17,680 --> 00:54:20,080
Speaker 1: happening yep. But that's the actual weirdest thing about the

1096
00:54:20,480 --> 00:54:23,360
Speaker 1: real nihilism of this is that nothing seems to actually

1097
00:54:23,400 --> 00:54:24,480
Speaker 1: be occurring.

1098
00:54:24,680 --> 00:54:26,840
Speaker 2: Yeah, and they also act like there's not going to

1099
00:54:26,880 --> 00:54:30,439
Speaker 2: be any accountability for like, forget their actions, just even

1100
00:54:30,480 --> 00:54:34,040
Speaker 2: their words. Right, you know, Sam Altman says, you know,

1101
00:54:34,120 --> 00:54:36,080
Speaker 2: like this this thing that just drove me up a

1102
00:54:36,120 --> 00:54:38,840
Speaker 2: wall that he said about a month ago, he said that,

1103
00:54:38,880 --> 00:54:40,960
Speaker 2: you know, in ten years, college graduates are going to

1104
00:54:41,000 --> 00:54:43,880
Speaker 2: have really cool jobs going out to explore the solar

1105
00:54:43,920 --> 00:54:47,560
Speaker 2: system in the spaceships enabled by AI. That is not happening,

1106
00:54:47,960 --> 00:54:51,279
Speaker 2: like on the list of things that are not happening exploration. No, No,

1107
00:54:51,520 --> 00:54:56,399
Speaker 2: that's not happening. He is just wrong. He's lying, right,

1108
00:54:56,640 --> 00:54:59,000
Speaker 2: and he is probably still going to be alive in

1109
00:54:59,040 --> 00:55:01,560
Speaker 2: ten years, and you and I are also likely still

1110
00:55:01,560 --> 00:55:03,439
Speaker 2: going to be alive in ten years. And then we're

1111
00:55:03,480 --> 00:55:06,600
Speaker 2: gonna say, hey, remember when he said that that, you know,

1112
00:55:06,680 --> 00:55:10,560
Speaker 2: now we we can show he's just wrong and he

1113
00:55:10,719 --> 00:55:12,160
Speaker 2: and nothing's gonna happen to.

1114
00:55:12,160 --> 00:55:14,000
Speaker 1: Him and what these like this is why I'm so

1115
00:55:14,080 --> 00:55:16,319
Speaker 1: harsh on media criticism as well. Yeah, the one thing

1116
00:55:16,320 --> 00:55:18,920
Speaker 1: you can do is at least say area man full

1117
00:55:18,960 --> 00:55:21,920
Speaker 1: of shit. Yes, stupid bastard wanks off again.

1118
00:55:22,000 --> 00:55:23,719
Speaker 2: Well, this is my this is what I attempted to do.

1119
00:55:23,719 --> 00:55:24,120
Speaker 2: What you do?

1120
00:55:24,239 --> 00:55:27,560
Speaker 1: Well, yeah, and it's I think that the change that

1121
00:55:27,600 --> 00:55:29,440
Speaker 1: we need in our hearts is to just regularly say

1122
00:55:29,440 --> 00:55:30,960
Speaker 1: this stuff. I regularly say on the show. I don't

1123
00:55:30,960 --> 00:55:34,680
Speaker 1: care if you quote me, just say this shit about them. Yeah, clammy, Sammy.

1124
00:55:34,760 --> 00:55:37,080
Speaker 1: He's been promising. He said that this was the year

1125
00:55:37,120 --> 00:55:40,840
Speaker 1: of agents. He said that. I don't, but now I

1126
00:55:40,880 --> 00:55:43,360
Speaker 1: read in the Information dot Com the next year is

1127
00:55:43,400 --> 00:55:46,600
Speaker 1: the year of agents, So maybe I do. Actually, here's

1128
00:55:46,600 --> 00:55:48,880
Speaker 1: a question for you. Yeah, AI twenty twenty seven. Do

1129
00:55:48,920 --> 00:55:49,440
Speaker 1: you read that.

1130
00:55:50,040 --> 00:55:53,200
Speaker 2: He've read a little bit of it. It's nonsense. It's nonsense. Yeah.

1131
00:55:53,239 --> 00:55:56,400
Speaker 1: Why do you think things like that fool so many people?

1132
00:55:56,440 --> 00:55:56,680
Speaker 2: Though?

1133
00:55:57,680 --> 00:55:59,879
Speaker 1: Why do you think it got the media coverage it did?

1134
00:56:00,320 --> 00:56:03,879
Speaker 2: See? Sh I mean? Part of it is bad journalism, right.

1135
00:56:03,920 --> 00:56:07,400
Speaker 2: Part of it is is that Kevin Russ has confused

1136
00:56:09,840 --> 00:56:16,600
Speaker 2: Kevin and Russ has confused reiterating the views of the wealthy,

1137
00:56:16,640 --> 00:56:22,120
Speaker 2: influential and powerful with taking a brave contrarian stance. And

1138
00:56:22,160 --> 00:56:24,880
Speaker 2: how he made that mistake I don't know, but you know,

1139
00:56:25,000 --> 00:56:26,919
Speaker 2: I really get the sense that he thinks he's being

1140
00:56:27,000 --> 00:56:30,960
Speaker 2: very brave when he's doing exactly what journalists are not

1141
00:56:31,000 --> 00:56:34,840
Speaker 2: supposed to do, which is just uncritically parroting powerful.

1142
00:56:34,440 --> 00:56:36,919
Speaker 1: And it feels like it's the large language model again.

1143
00:56:36,960 --> 00:56:38,759
Speaker 1: It's just the affirming thing. It's like, oh, I'm being

1144
00:56:38,760 --> 00:56:41,040
Speaker 1: contrarian by stepping out against these people who say it

1145
00:56:41,040 --> 00:56:43,120
Speaker 1: isn't making any money and isn't very good at stuff.

1146
00:56:43,160 --> 00:56:46,160
Speaker 2: And it's like, look, buddy, if there's you know, if

1147
00:56:46,200 --> 00:56:49,080
Speaker 2: there's a two sides to a debate, I mean, obviously

1148
00:56:49,120 --> 00:56:51,040
Speaker 2: there's more than two sides, but like if on one

1149
00:56:51,120 --> 00:56:55,359
Speaker 2: side you have the wealthiest people in the world and

1150
00:56:55,400 --> 00:56:57,640
Speaker 2: on the other side you have people who say mean

1151
00:56:57,719 --> 00:57:02,400
Speaker 2: things about you personally online, and you think that you know,

1152
00:57:02,880 --> 00:57:07,320
Speaker 2: it's the first side that's the contrarian underdog. Yeah, something

1153
00:57:07,400 --> 00:57:09,359
Speaker 2: is wrong with your brain, and that's the thing.

1154
00:57:09,719 --> 00:57:12,240
Speaker 1: But this is, and this, I think is a weird

1155
00:57:12,239 --> 00:57:14,560
Speaker 1: thing in our society that we just people trust the

1156
00:57:14,680 --> 00:57:17,200
Speaker 1: rich and the media has got to a point where

1157
00:57:17,240 --> 00:57:19,840
Speaker 1: they've just bred out the real cynicism because I swear,

1158
00:57:19,880 --> 00:57:22,640
Speaker 1: like ten to fifteen years ago, you used to have

1159
00:57:22,920 --> 00:57:25,400
Speaker 1: some tech journalism, Like I read a thing about Amazon

1160
00:57:25,480 --> 00:57:28,400
Speaker 1: web services that Kevin Ross wrote and it was actually

1161
00:57:28,440 --> 00:57:30,760
Speaker 1: pretty cynical about it. Really, yeah, it was actually pretty critical.

1162
00:57:30,800 --> 00:57:32,640
Speaker 1: He then he made I feel bad for him because

1163
00:57:32,640 --> 00:57:34,600
Speaker 1: this can't be in his fault. He basically said at

1164
00:57:34,640 --> 00:57:37,440
Speaker 1: the end, Yeah, they'll never be profitable. No, no, no,

1165
00:57:37,480 --> 00:57:40,600
Speaker 1: it gets worse at a month later, Amazon announced that

1166
00:57:40,640 --> 00:57:44,400
Speaker 1: AWS is profitable for the first time. Just like Buddy

1167
00:57:45,600 --> 00:57:46,280
Speaker 1: miss the bean.

1168
00:57:46,360 --> 00:57:49,640
Speaker 2: Come on, whoa, Yeah, maybe that's the origin story. Maybe

1169
00:57:49,680 --> 00:57:51,080
Speaker 2: he was like, oh wow, I screwed that up.

1170
00:57:51,080 --> 00:57:54,320
Speaker 1: I guess I believe the origin story is actual social media.

1171
00:57:54,360 --> 00:57:56,720
Speaker 1: I think I think he felt. I actually think a

1172
00:57:56,720 --> 00:57:58,680
Speaker 1: lot of journalists think that they missed the boat on

1173
00:57:58,720 --> 00:58:02,240
Speaker 1: social media. I have been in media relations since two

1174
00:58:02,240 --> 00:58:04,919
Speaker 1: thousand and eight. I have read and this sounds insane, yeah,

1175
00:58:04,920 --> 00:58:07,520
Speaker 1: but it's true. I think I've read just about everybody's

1176
00:58:07,560 --> 00:58:11,080
Speaker 1: work since then within the tech media, at least, including Kevin's,

1177
00:58:11,400 --> 00:58:13,760
Speaker 1: and he has always had a little bit of anxiety

1178
00:58:13,800 --> 00:58:17,200
Speaker 1: that he missed social media. Nobody missed social media, not

1179
00:58:17,240 --> 00:58:20,000
Speaker 1: a single fucking one since two thousand and eight. Everybody

1180
00:58:20,120 --> 00:58:23,760
Speaker 1: was on Zuckerberg's zuck. He sucked him off at hardcore.

1181
00:58:23,840 --> 00:58:26,720
Speaker 1: Sorry sorry, but nevertheless, they were on top of this,

1182
00:58:26,760 --> 00:58:29,240
Speaker 1: they wrote about some social media was written about immediately.

1183
00:58:29,440 --> 00:58:31,760
Speaker 1: If anything, I think the media was a little slow

1184
00:58:31,800 --> 00:58:33,920
Speaker 1: to get on apps. Then they gone on hardcore. I

1185
00:58:34,120 --> 00:58:36,280
Speaker 1: know the history of this shit. I have been taking

1186
00:58:36,320 --> 00:58:40,360
Speaker 1: detailed notes. They sound crazy, but I think that there's

1187
00:58:40,440 --> 00:58:42,720
Speaker 1: just there is this weird thing of like the powerful

1188
00:58:42,760 --> 00:58:45,600
Speaker 1: would never lie to us. And then Prism came out,

1189
00:58:45,960 --> 00:58:49,600
Speaker 1: and then Cambridge Analytic happened and people are like, maybe

1190
00:58:49,680 --> 00:58:52,400
Speaker 1: Zuckerberg's bad, but he wouldn't lie to us. He would

1191
00:58:52,640 --> 00:58:55,560
Speaker 1: and they're like, well they know things we don't know.

1192
00:58:55,720 --> 00:58:58,200
Speaker 1: And that's actually another that's my favorite. AI think when

1193
00:58:58,200 --> 00:59:01,280
Speaker 1: it's like the secret things they're working on, secret things,

1194
00:59:01,640 --> 00:59:04,160
Speaker 1: secret things, sitting in the waiting in the wings, you'll

1195
00:59:04,160 --> 00:59:06,640
Speaker 1: never believe what's coming. And it's just I actually think

1196
00:59:06,720 --> 00:59:10,320
Speaker 1: it's just what's his name, Iliasuitskeva just goes to Bar's occasion.

1197
00:59:10,320 --> 00:59:13,040
Speaker 1: He's like, you'll never guess when I said, you never get.

1198
00:59:13,080 --> 00:59:15,680
Speaker 2: A okay, okay, no, I I have a thing to

1199
00:59:15,680 --> 00:59:19,240
Speaker 2: say about when like this is this is me just

1200
00:59:19,320 --> 00:59:21,400
Speaker 2: being petty and making a point that other people have

1201
00:59:21,440 --> 00:59:23,440
Speaker 2: made that yeah, of course.

1202
00:59:23,680 --> 00:59:23,760
Speaker 1: No.

1203
00:59:23,880 --> 00:59:26,480
Speaker 2: When he when he announced that he was you know,

1204
00:59:26,600 --> 00:59:30,320
Speaker 2: putting together a team to you know, just go straight

1205
00:59:30,400 --> 00:59:34,240
Speaker 2: for safe super intelligence. He meant to say when he

1206
00:59:34,280 --> 00:59:36,440
Speaker 2: posted this on social media, that he was putting together

1207
00:59:36,520 --> 00:59:39,800
Speaker 2: a crack team, but that's not what he wrote. What

1208
00:59:39,960 --> 00:59:41,840
Speaker 2: he right, He wrote that he was putting together a

1209
00:59:42,000 --> 00:59:48,000
Speaker 2: cracked team. Hmmm, crack ed, cracked, and like, yeah, actually

1210
00:59:48,040 --> 00:59:49,880
Speaker 2: you know what, Yeah, I think that's true.

1211
00:59:49,920 --> 00:59:53,280
Speaker 1: I agree, yeah, exactly. I also think him and Mary

1212
00:59:53,360 --> 00:59:57,720
Speaker 1: Moralty I can't. And so for the for the listeners, Illocitskava,

1213
00:59:57,760 --> 00:59:59,840
Speaker 1: one of the co founders of OPE and I, raised

1214
01:00:00,320 --> 01:00:03,439
Speaker 1: two billion dollars at a thirty billion dollar valuation. Mira

1215
01:00:03,520 --> 01:00:07,800
Speaker 1: Mourati did a billion some amounts some bullshit. Neither of

1216
01:00:07,840 --> 01:00:11,400
Speaker 1: these companies have told their investors how they will spend

1217
01:00:11,400 --> 01:00:13,920
Speaker 1: the money, or what on or what they will build.

1218
01:00:13,960 --> 01:00:17,080
Speaker 1: And you may think I'm being facetious. Mira Murati literally

1219
01:00:17,120 --> 01:00:20,520
Speaker 1: said to investors, I will not tell you, and then

1220
01:00:20,600 --> 01:00:24,480
Speaker 1: said I and has board rights where she can veto everyone,

1221
01:00:25,240 --> 01:00:28,120
Speaker 1: I will be honest, go for it. Fuck yeah, I

1222
01:00:28,240 --> 01:00:30,480
Speaker 1: think I think at this stage, if these people are

1223
01:00:30,480 --> 01:00:33,720
Speaker 1: so fucking stupid that you're just like, I promise you

1224
01:00:33,800 --> 01:00:37,320
Speaker 1: literally nothing. I won't give you you hogs a single

1225
01:00:37,440 --> 01:00:39,600
Speaker 1: oinc You're not gonna get anything from me. Give me

1226
01:00:39,680 --> 01:00:42,560
Speaker 1: money now, fuck yeah, go for it. But on the

1227
01:00:42,560 --> 01:00:45,120
Speaker 1: other hand, I cannot wait for the investigation.

1228
01:00:46,400 --> 01:00:48,360
Speaker 2: I just hope there is one. Right. These people are

1229
01:00:48,400 --> 01:00:53,480
Speaker 2: acting with impunity like and and also like again accountability

1230
01:00:53,640 --> 01:00:57,240
Speaker 2: just for their words. Right. The most basic criticism of

1231
01:00:57,280 --> 01:01:01,600
Speaker 2: the wealthy in media like this is to shift just

1232
01:01:01,640 --> 01:01:06,520
Speaker 2: a little bit. Eric Schmidt right said about about a

1233
01:01:06,560 --> 01:01:09,560
Speaker 2: year ago, shortly before the election, he said, we're never

1234
01:01:09,600 --> 01:01:12,560
Speaker 2: going to meet our climate goals anyway, so we might

1235
01:01:12,640 --> 01:01:14,920
Speaker 2: as well just burn as much carbon and use as

1236
01:01:14,920 --> 01:01:18,080
Speaker 2: many resources as possible to get to AGI, and then

1237
01:01:18,080 --> 01:01:20,560
Speaker 2: that will solve climate change for us, which is ridiculous

1238
01:01:20,560 --> 01:01:21,960
Speaker 2: because we don't so cool.

1239
01:01:22,080 --> 01:01:25,080
Speaker 1: Yeah yeah, Like we have no responsibility for our actions

1240
01:01:25,200 --> 01:01:26,880
Speaker 1: until we hand them off to someone else.

1241
01:01:27,160 --> 01:01:30,360
Speaker 2: Right, So he said this, which is ridiculous for lots

1242
01:01:30,360 --> 01:01:33,040
Speaker 2: of reasons, and echo stuff that Sam Altman has said, right,

1243
01:01:33,120 --> 01:01:36,400
Speaker 2: It's it's ridiculous among other reasons, because like AGI is

1244
01:01:36,440 --> 01:01:40,000
Speaker 2: not a thing, and also because we don't need like

1245
01:01:40,440 --> 01:01:43,600
Speaker 2: we know what we need to do to solve global warming, right,

1246
01:01:43,640 --> 01:01:44,800
Speaker 2: we know what we need to do to solve the

1247
01:01:44,840 --> 01:01:47,080
Speaker 2: climate crisis is just a matter of actually getting everybody.

1248
01:01:47,200 --> 01:01:49,920
Speaker 1: I don't need to do it, but may sam Oltman

1249
01:01:50,080 --> 01:01:51,800
Speaker 1: said that they know what they need to do to

1250
01:01:51,800 --> 01:01:54,439
Speaker 1: get to AGI, and then said a few months later

1251
01:01:54,480 --> 01:01:55,919
Speaker 1: that agi wasn't a useful term.

1252
01:01:56,400 --> 01:01:58,640
Speaker 2: Q D, Well, no, this is this is exactly what

1253
01:01:58,680 --> 01:02:01,440
Speaker 2: I was about to say about right. He repeats this

1254
01:02:01,560 --> 01:02:04,000
Speaker 2: claim about like just pushing as hard as we can

1255
01:02:04,640 --> 01:02:07,840
Speaker 2: about a month after the last time he said it,

1256
01:02:07,920 --> 01:02:12,880
Speaker 2: maybe two months. Only a few weeks ago he comes

1257
01:02:12,920 --> 01:02:14,960
Speaker 2: out in the New York Times with this op ed saying, oh,

1258
01:02:15,040 --> 01:02:18,360
Speaker 2: AGI is not really a thing and we shouldn't care

1259
01:02:18,360 --> 01:02:21,680
Speaker 2: about it. It's like, buddy, you were saying just a

1260
01:02:21,720 --> 01:02:24,920
Speaker 2: few weeks ago that this was gonna save the world

1261
01:02:24,920 --> 01:02:27,560
Speaker 2: from the biggest emergency of our time, and now you're

1262
01:02:27,600 --> 01:02:30,400
Speaker 2: saying it's not a thing. Do you think we're all stupid?

1263
01:02:30,720 --> 01:02:33,480
Speaker 2: Are you that stupid? What the fuck is going on?

1264
01:02:33,520 --> 01:02:35,440
Speaker 1: I can actually tell you. I think he thinks the

1265
01:02:35,480 --> 01:02:38,760
Speaker 1: meteor is that stupid and will write and we'll publish anything.

1266
01:02:38,800 --> 01:02:40,920
Speaker 2: He says. I mean to see that the New York

1267
01:02:40,920 --> 01:02:41,680
Speaker 2: Times published it.

1268
01:02:41,760 --> 01:02:44,360
Speaker 1: I wasn't Yeah, I would be honest. That's the least

1269
01:02:45,280 --> 01:02:47,880
Speaker 1: we've got fucking Ezra Klein being like, hey, geis the

1270
01:02:48,200 --> 01:02:53,959
Speaker 1: fucking Ezra Ezra? What a peculiar fella, What a peculiar fella,

1271
01:02:54,080 --> 01:02:57,240
Speaker 1: Ezbra Klein is? What's going on there? You ever run

1272
01:02:57,280 --> 01:02:58,000
Speaker 1: into mister Klein.

1273
01:02:58,440 --> 01:03:00,880
Speaker 2: I've never met him directly, I know people who know him,

1274
01:03:01,000 --> 01:03:04,000
Speaker 2: but now I think I think he just hung out

1275
01:03:04,040 --> 01:03:06,400
Speaker 2: with too many tech billionaire as while he was living

1276
01:03:06,400 --> 01:03:08,680
Speaker 2: in the Bay Area. He's this fucking mind poison. These

1277
01:03:08,680 --> 01:03:11,680
Speaker 2: people are boring. Yeah, these people are bored.

1278
01:03:11,720 --> 01:03:12,280
Speaker 1: You sit down.

1279
01:03:12,440 --> 01:03:15,919
Speaker 2: They have amounts of money. And like, if you're if

1280
01:03:15,920 --> 01:03:19,840
Speaker 2: you're someone who's never been cool and they have been cool,

1281
01:03:19,840 --> 01:03:22,280
Speaker 2: and I've also never been cool, love it, don't I know?

1282
01:03:22,440 --> 01:03:24,600
Speaker 2: But like, if you've never been cool, one of two

1283
01:03:24,680 --> 01:03:26,960
Speaker 2: things happens to you as you grow up. Either you

1284
01:03:27,240 --> 01:03:30,520
Speaker 2: desperately want to be cool and that can, you know,

1285
01:03:30,560 --> 01:03:34,840
Speaker 2: go wrong in many different ways, like Musk and possibly

1286
01:03:34,920 --> 01:03:37,760
Speaker 2: like Klein. I don't know, maybe like I'm willing to

1287
01:03:37,800 --> 01:03:39,680
Speaker 2: believe that something else is going on with him. I

1288
01:03:39,760 --> 01:03:43,120
Speaker 2: don't know. But or you become like us and you

1289
01:03:43,160 --> 01:03:46,240
Speaker 2: stop giving a shit yeah, and you accept oh, I'm

1290
01:03:46,280 --> 01:03:49,760
Speaker 2: just permanently uncool. Whatever, I'll make my way through life.

1291
01:03:49,840 --> 01:03:52,880
Speaker 1: And that's the thing. It's these people are just disconnected

1292
01:03:52,920 --> 01:03:55,200
Speaker 1: from humanity. None of these people seem to have friends

1293
01:03:55,320 --> 01:03:58,360
Speaker 1: or loved ones, because there's just if I did any

1294
01:03:58,400 --> 01:04:00,280
Speaker 1: of this whack of through shit, I would get takes

1295
01:04:00,280 --> 01:04:02,680
Speaker 1: from Casey or there or any number of people love

1296
01:04:02,800 --> 01:04:06,400
Speaker 1: me just like, hey, man, are you okay? Sound insane? No,

1297
01:04:06,720 --> 01:04:09,040
Speaker 1: Casey would definitely not be just. But hey, yeah, what

1298
01:04:09,120 --> 01:04:12,240
Speaker 1: the fuck you you okay? That doesn't make any sense.

1299
01:04:12,840 --> 01:04:13,439
Speaker 2: What do you mean?

1300
01:04:13,520 --> 01:04:15,280
Speaker 1: What do you mean a Dyson sphere? Do you know

1301
01:04:15,320 --> 01:04:19,040
Speaker 1: what that is? A dice in sphere. It's just they

1302
01:04:19,080 --> 01:04:21,680
Speaker 1: don't have friends, and I don't know if they want them.

1303
01:04:21,720 --> 01:04:23,800
Speaker 1: I think it could require a certain level of vulnerability.

1304
01:04:24,200 --> 01:04:25,960
Speaker 1: Have you talked twenty Have you met up with any

1305
01:04:26,000 --> 01:04:26,960
Speaker 1: of them?

1306
01:04:27,040 --> 01:04:29,440
Speaker 2: With the billionaires, no, I tried. There's a list at

1307
01:04:29,440 --> 01:04:30,880
Speaker 2: the end of my book of all of the tech

1308
01:04:30,920 --> 01:04:33,000
Speaker 2: billionaires I tried to interview and they all said no.

1309
01:04:33,320 --> 01:04:36,640
Speaker 2: The only one who I successfully interviewed was like a

1310
01:04:36,720 --> 01:04:39,880
Speaker 2: lower tier billionaire guy named jan to Lynn who's in

1311
01:04:40,000 --> 01:04:43,720
Speaker 2: deep with the effective algist was Skype and Speaza. Yeah

1312
01:04:43,800 --> 01:04:47,320
Speaker 2: yeah that's right, christ Yeah, yeah, yeah. Actually, can't hate

1313
01:04:47,360 --> 01:04:48,880
Speaker 2: him for those are two pretty good ones.

1314
01:04:48,920 --> 01:04:51,240
Speaker 1: Yeah, exactly, though I will say Skype definitely one of

1315
01:04:51,240 --> 01:04:55,520
Speaker 1: those inventions that I've never seen something just stop. Yeah, no,

1316
01:04:55,840 --> 01:04:57,920
Speaker 1: Scott just got like no, just no, I mean trapped

1317
01:04:57,960 --> 01:04:59,920
Speaker 1: in Amber. It was the same product for fifty oh yeah.

1318
01:05:00,000 --> 01:05:01,880
Speaker 1: And the Microsoft are just like what Box are an

1319
01:05:01,920 --> 01:05:05,720
Speaker 1: animal farm banged, it's at a glue factory with Skype.

1320
01:05:05,880 --> 01:05:09,240
Speaker 1: We fucked this up well enough, It's just it's also

1321
01:05:09,400 --> 01:05:12,680
Speaker 1: it's also sad. But this has been such a wonderful conversation.

1322
01:05:12,760 --> 01:05:14,160
Speaker 1: Oh where can people find you?

1323
01:05:14,840 --> 01:05:18,200
Speaker 2: Well, I'm on blue Sky because I don't want to

1324
01:05:18,240 --> 01:05:21,240
Speaker 2: be on a platform like Ext's filled with Nazis now,

1325
01:05:22,120 --> 01:05:23,680
Speaker 2: so blue sky is the best place to find me.

1326
01:05:23,720 --> 01:05:27,640
Speaker 2: I'm Adam Becker dot blue sky dot social, orgy dot social.

1327
01:05:27,800 --> 01:05:32,760
Speaker 2: And yeah, I got a book, is the main thing. Yeah,

1328
01:05:32,760 --> 01:05:35,680
Speaker 2: I got a book called More Everything Forever linked to

1329
01:05:35,720 --> 01:05:38,320
Speaker 2: it in the notes. Yeah, it is available wherever fine

1330
01:05:38,320 --> 01:05:42,400
Speaker 2: books are sold. And if you liked what I had

1331
01:05:42,440 --> 01:05:44,720
Speaker 2: to say on this episode, I think you'll like the book.

1332
01:05:45,280 --> 01:05:46,760
Speaker 1: And if you like what I have to say on

1333
01:05:46,800 --> 01:05:48,640
Speaker 1: this show, you're a sick puppy, you know where to

1334
01:05:48,680 --> 01:05:50,640
Speaker 1: find me. Thank you so much for your time as ever,

1335
01:05:50,680 --> 01:05:52,160
Speaker 1: I love you all. Thank you to beahet of course

1336
01:05:52,200 --> 01:05:54,400
Speaker 1: here in New York City, here for producing this episode,

1337
01:05:54,520 --> 01:05:56,840
Speaker 1: and of course the Madisowski, the wonderful producer at home.

1338
01:05:57,080 --> 01:05:58,880
Speaker 1: I will catch you with them monologue in a few days.

1339
01:05:58,880 --> 01:06:09,360
Speaker 1: Thank you so much, Thank you for listening to Better Offline.

1340
01:06:09,480 --> 01:06:11,919
Speaker 1: The editor and composer of the Better Offline theme song

1341
01:06:11,960 --> 01:06:14,640
Speaker 1: is Matasowski. You can check out more of his music

1342
01:06:14,640 --> 01:06:18,280
Speaker 1: and audio projects at Matasowski dot com, M A T

1343
01:06:18,280 --> 01:06:22,760
Speaker 1: T O S O W s ki dot com. You

1344
01:06:22,800 --> 01:06:25,280
Speaker 1: can email me at easy at Better Offline dot com

1345
01:06:25,400 --> 01:06:27,720
Speaker 1: or visit Better Offline dot com to find more podcast

1346
01:06:27,760 --> 01:06:31,120
Speaker 1: links and of course my newsletter. I also really recommend

1347
01:06:31,120 --> 01:06:33,040
Speaker 1: you go to chat dot Where's youreed dot at to

1348
01:06:33,120 --> 01:06:35,920
Speaker 1: visit the discord, and go to our slash Better Offline

1349
01:06:35,960 --> 01:06:39,200
Speaker 1: to check out our reddit. Thank you so much for listening.

1350
01:06:40,000 --> 01:06:42,720
Speaker 1: Better Offline is a production of cool Zone Media. For

1351
01:06:42,840 --> 01:06:46,000
Speaker 1: more from cool Zone Media, visit our website cool Zonemedia

1352
01:06:46,040 --> 01:06:48,919
Speaker 1: dot com, or check us out on the iHeartRadio app,

1353
01:06:48,960 --> 01:07:12,200
Speaker 1: Apple Podcasts, or wherever you get your podcasts.