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Speaker 1: Also media Chosen by God, perfected by Science. My name

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Speaker 1: is said Zeitron. You're listening to Better Offline. This is

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Speaker 1: day one technically, but really day two of the Better

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Speaker 1: Offline CES Saga, the Consumer Electronics Show. Here from beautiful

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Speaker 1: Las Vegas, Nevada. My home, I my van helsing like curse,

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Speaker 1: but also my job. I must be in Vegas. Our

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Speaker 1: beautiful slot machines must be filled with beautiful dollars. I

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Speaker 1: am joined today by a remarkable coterie of people. Edon

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Speaker 1: Graiso Junior, of course, joins me for another episode. ED

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Speaker 1: lovely to see you. It's really great to be back.

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Speaker 1: Thanks for having me again. So just before we go

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Speaker 1: any further, as people think, why did I say that

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Speaker 1: at the beginning, other than the fact it's true, where

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Speaker 1: did you hear? The phrase Chosen by God, perfected by Science.

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Speaker 1: Today was on a.

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Speaker 2: Giant a giant banner above CES on the Venetian Expo floor.

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Speaker 1: Nice.

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Speaker 2: It was advertisement for germ Pass, which is this automatic

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Speaker 2: ultraviolent light technology that automatically kills ninety nine point ninety

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Speaker 2: nine percent of germs on any high touch surface.

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Speaker 1: Right, so to my right sets Philip Broughton, who is

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Speaker 1: going to tell you what he does.

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Speaker 3: So Hi, I'm Phil Broddon. I am a health physicist,

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Speaker 3: which means radiation safety and laser safety officer, which means

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Speaker 3: I deal with the entire electromagnetic spectrum from gamma rays

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Speaker 3: all the way down to radio.

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Speaker 1: And Phil is also the bartender for the Sweet So

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Speaker 1: if you somehow came to episode two of the Cees Saga,

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Speaker 1: I don't know why you would do this. This isn't

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Speaker 1: like a there's not like a chroninal, there's not a

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Speaker 1: plot to follow. I guess you could jump anyway, but

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Speaker 1: like you probably start episode one anyway. We're in the

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Speaker 1: bu Venetians suite. We're in a recessed area, separate room.

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Speaker 1: On the side. We are running a suite with Boost

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Speaker 1: for journalists all weeks. Tons of places to sit down

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Speaker 1: and me, which is why no one's toning up. But nevertheless,

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Speaker 1: we are also recording a podcast and Phil, Phil and

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Speaker 1: I have been doing this eight it's eight times now.

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Speaker 3: This is the eighth time been doing it since twenty fifteen.

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Speaker 1: And we love doing it. It's a Phil takes vacation

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Speaker 1: time from his job elsewhere, and yeah, it's great. And

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Speaker 1: also Phil's other thing he likes to do is a

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Speaker 1: suffer torment. He likes to suffer pain at all times.

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Speaker 1: Because Phil is a safety man and is well aware

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Speaker 1: of things like codes and laws and stuff and regulations,

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Speaker 1: and so, Phil, you may make a record this year.

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Speaker 1: It's every year by Wednesday, someone has brought you something

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Speaker 1: that required you to call the fire marshal.

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Speaker 3: Yeah, that's why.

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Speaker 4: Is that?

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Speaker 3: Because sometimes people lie on their applications. They lie when they're.

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Speaker 1: That applications will walk by.

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Speaker 3: Oh, so everyone who has a booth at CES is

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Speaker 3: required to submit how many square feet they're gonna have,

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Speaker 3: what utilities they're gonna need, and any hazardous things they

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Speaker 3: might bring to the floor to the people who run

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Speaker 3: the show, who then are required to tell the fire marshal.

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Speaker 3: And the fire marshal then comes back and goes, oh,

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Speaker 3: you've added rabid, flaming, radioactive gerbils to the show. That

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Speaker 3: changes the occupancy we're allowed to have in this building.

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Speaker 3: So please don't do them well.

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Speaker 1: And then they lie, and so what do you usually

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Speaker 1: tell the fire marshal.

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Speaker 3: So what comes to me is a journalist will say, Hey, Phil,

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Speaker 3: one could I get to drink?

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Speaker 1: Two?

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Speaker 3: I saw a thing and I don't think it was

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Speaker 3: okay or m that seemed dangerous and I'm worried. No, okay,

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Speaker 3: so what do you have? Where did you see this? Roughly?

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Speaker 3: Let me go ahead and pull up the CES map

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Speaker 3: of all the vendors. Oh, you're on that corner of

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Speaker 3: that aisle. Cool. Let me go make a call.

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Speaker 1: So has anyone been like arrested for this if they've

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Speaker 1: been like taken off the floor, Like, what are the

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Speaker 1: consequences of.

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Speaker 3: The far removed from the floor.

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Speaker 1: Yeah, that's fun arrested.

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Speaker 3: No, but you end up forfeiting your fees and you

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Speaker 3: don't get to present anymore for the rest of that show,

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Speaker 3: or they take the dangerous thing away.

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Speaker 1: I think that maybe, based on what Ed will be

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Speaker 1: telling us about in a little bit, I think we

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Speaker 1: should maybe remove all of the booths from CS.

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Speaker 4: Like.

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Speaker 1: It sounds like that might be a good idea. But

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Speaker 1: before we get to that, we're also joined by a

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Speaker 1: man of the clergy. So for some reason, and I

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Speaker 1: really mean this, I do not fucking know, we have

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Speaker 1: a priest that joins us, father Gabriel Mosher, who joins

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Speaker 1: me I left and weirdly connected with the tech media

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Speaker 1: as well. But you just kind of show up in

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Speaker 1: the robes, not complaining. Just I really do not remember why.

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Speaker 5: I have no idea how this all got started. But

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Speaker 5: it was also ten years ago?

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Speaker 1: Was it ten years ago? Not fucking hell? Anyway, I

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Speaker 1: age every day. But like, do you know how he

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Speaker 1: got here?

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Speaker 3: Yes? I paid for his flight.

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Speaker 1: I'm know where buddy.

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Speaker 5: Hell, you know, I think part of it was I,

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Speaker 5: especially back then, I was connected to quite a few

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Speaker 5: sort of like tech people and whatnot.

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Speaker 1: Right, Yeah, and we figured might as well. Yes, so,

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Speaker 1: And just to be clear, you have no worldly possessions

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Speaker 1: other than those which are given to you.

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Speaker 4: Correct, pretty much.

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Speaker 1: Yeah, that's great. Would you describe cs as sinful or

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Speaker 1: not sinful? Depends depends on which party you go to.

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Speaker 1: I mean the convention, I mean that exactly. Enough about Yo, No,

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Speaker 1: this is a scobullless zone.

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Speaker 5: No, I think it's great unless you you think that,

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Speaker 5: you know, technology going to save you from everything.

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Speaker 4: But yeah, no, it's it's interesting.

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Speaker 5: I find, you know, the whole idea of these various

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Speaker 5: people trying to develop innovations to make life a little

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Speaker 5: bit better, a little bit more convenient, to be a

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Speaker 5: good thing. I mean, it's that's just that's just human nature.

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Speaker 5: It's great unless they are a bunch of liars, which

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Speaker 5: they are half the time.

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Speaker 1: And talking of liars, so the there is an article

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Speaker 1: in the New York Times at the moment about priests

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Speaker 1: that using chat GPTM to make sermons. How do you

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Speaker 1: feel about that? So?

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Speaker 4: I think that's pretty lame.

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Speaker 1: Do you think is it sacrilegious?

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Speaker 6: No?

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Speaker 1: But why not?

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Speaker 5: Well, it's just like if you're going to use chatgybt,

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Speaker 5: for instance, to create sort of the outline of a

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Speaker 5: book or something like that, I think that's fine. But

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Speaker 5: if you're if you're using if you're using chatgybt to

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Speaker 5: like write your sermon as a whole, then you've failed.

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Speaker 4: It's just like writing your term paper.

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Speaker 1: Okay, So very specific question though, So if it hallucinated

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Speaker 1: a verse of the Bible? M hm, would that be

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Speaker 1: like a false idol situation? Would that actually be a sin? No?

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Speaker 5: I mean I mean not from the chatgybt because it's

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Speaker 5: not like no, no for the person publishing person. Yeah, sure,

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Speaker 5: I mean yeah, that would be that would be pretty lame.

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Speaker 5: I mean you would you would definitely be trying to

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Speaker 5: like lead people into like weird places, and yeah, this.

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Speaker 1: Is this is how I imagine that's also bad.

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Speaker 4: Who knows? I mean, I don't know.

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Speaker 1: I means this is why the show is happening. We

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Speaker 1: need to Yeah, it's just the and that article was

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Speaker 1: I don't know why it had to. It's one of

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Speaker 1: those things you read and you're like.

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Speaker 4: I've got to read this article.

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Speaker 1: It's not great. It's weirdly well reported, like it's the

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Speaker 1: guy went out and like really reported the ship out

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Speaker 1: of it. But it was just like, Okay, a bunch

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Speaker 1: of people who believe in something that not everyone believes in,

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Speaker 1: believe in another thing that let even less people believe

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Speaker 1: it lots of people spend more money on.

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Speaker 5: But I can tell you, like most preaching is pretty terrible,

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Speaker 5: so this might actually be a notch up. So anyway, yeah,

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Speaker 5: you think, I mean preaching is pretty bad these days, is.

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Speaker 1: Not that fucking point? Looking at that, you would think

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Speaker 1: it's why I can't go into churches other than the

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Speaker 1: burning so terrible. Yeah, mister W. Gwisner, Junia, tell us

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Speaker 1: a little bit about what you've seen today on the floor.

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Speaker 2: All right, Well, you know, I scanned a bit for

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Speaker 2: a while because I was trying to find something that

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Speaker 2: spoke to me.

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Speaker 1: First.

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Speaker 2: I went for these healthcare management devices for two reasons.

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Speaker 1: I won. You know, my coach Jaythan on This Machine

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Speaker 1: Kills podcastant on This Machine Kills podcast not introduce you.

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Speaker 1: I'm so sorry, totally fine.

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Speaker 2: You know, listen to the first episode, everybody, and then

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Speaker 2: the second one and.

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Speaker 3: Then the other podcast.

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Speaker 1: Right.

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Speaker 2: Yeah, you know, Jaythan writes a lot about network devices

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Speaker 2: and mythologies behind them, and that was one of the

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Speaker 2: courts subjects of his first book, and so I pulled

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Speaker 2: into that for that reason. Also because you know, my

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Speaker 2: partner uses medical devices to monitor glue close levels since

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Speaker 2: they're diabetics, so I'm always interested. I've been increasingly interested

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Speaker 2: in them because you know, these devices don't really work,

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Speaker 2: and so when I see innovative offerings or well.

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Speaker 3: You know, actual devices are qualified and do work with

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Speaker 3: but health management aids aren't real.

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Speaker 2: Yeah, this is what I or what I what I

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Speaker 2: should say, is that their devices work, but there are

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Speaker 2: a malfunction regularly at a rate that surprises me considering

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Speaker 2: they're supposed to be and are necessary, you know, for

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Speaker 2: staying within a healthy range for blood sugar. But the

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Speaker 2: health management aids, you know, they offer. They present themselves

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Speaker 2: as more aggressive solves, as preventative healthcare mechanisms, right as

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Speaker 2: ways to.

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Speaker 1: Overhaul your entire lifestyle.

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Speaker 2: So I was on the lookout for a lot of

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Speaker 2: these because I've been interested in them increasingly, in writing

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Speaker 2: about the ways in which they, you know, people are

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Speaker 2: encouraged to be healthier or to empower wellness or to

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Speaker 2: reward it, and in the ways this data gets you know,

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Speaker 2: accumulated sent back to insurance companies. So the first first

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Speaker 2: one I went to was biopop, which is this sorry,

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Speaker 2: it's this device that is interesting because obstensively it's it's

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Speaker 2: it is promising, and it's a non invasive UH device

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Speaker 2: healthcare management device that would allow you to get access

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Speaker 2: to some biometric, metabolic, you know data. But it uses

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Speaker 2: uh it uses ultra Sorry, it uses an n I

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Speaker 2: R spectra spectruc spectroscopy.

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Speaker 1: Spect truck spect truck. I couldn't say it, reader.

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Speaker 3: You're infrared spectroscopy what N I R, yes, M spectrum

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Speaker 3: spe speculum.

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Speaker 4: Yes, it activates speak speech.

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Speaker 1: Just be staring at the abyss the whole time, trying.

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Speaker 2: To say And so I came into the booth, you know,

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Speaker 2: listening to them, you know, listening to them talk to

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Speaker 2: other people about it. One of the use cases that

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Speaker 2: was offered was, you know, imagine you have a c GM.

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Speaker 2: There's no expensive, hard to maintain. You can use this

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Speaker 2: to monitor your blood glucose because that the only hike

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Speaker 2: and monitor right now, you know, implying it to a

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Speaker 2: medical device. So I go in and I say, he

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Speaker 2: is this a medical device? And he goes, oh, no,

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Speaker 2: it's so.

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Speaker 1: Cool that they have that. They have to do that.

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Speaker 2: Yeah, Actually the healthcare management device that doesn't work if

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Speaker 2: you have a lot of melanin in your skin because.

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Speaker 1: Interesting only tested it on Asians and light.

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Speaker 2: Skinned people and so it's not in market yet because

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Speaker 2: they need to test it out on people from India

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Speaker 2: and Africa.

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Speaker 1: And so thankfully there's not that many people.

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Speaker 3: Just a few billions.

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Speaker 1: That's It's like way less than Montana.

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Speaker 2: So biopop is very interested in helping you improve your

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Speaker 2: healthcare management uh and empowering you to be a healthier person.

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Speaker 1: They also want to reward you for doing so.

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Speaker 2: So they are both on the blockchain and they will

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Speaker 2: share information.

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Speaker 1: All right, companies understand which blockchain it's is crazy. They

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Speaker 1: did not specify. I was listening the whole time, but

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Speaker 1: my brain is just like, this is the same shit

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Speaker 1: you hear blockchain, Yeah, didn't specify one. No, to what end?

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Speaker 1: This is the stuff. I will be screaming at them

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Speaker 1: and say they.

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Speaker 2: Want to encourage users to meet certain to meet certain

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Speaker 2: goals and to stay within certain ranges. If you're on

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Speaker 2: the blockchain, you might be able to get a reward. Great,

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Speaker 2: maybe it's a coin in the ecosystem they might create,

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Speaker 2: maybe it's from somebody at talking, maybe it's more established blockchain.

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Speaker 2: They also, again are sending the information.

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Speaker 4: To the.

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Speaker 1: UH, to the insurance, the.

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Speaker 2: Insurers, because this is how they're going to be able

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Speaker 2: to you know, kind of they're they're they're trying to avoid.

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Speaker 3: Certification.

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Speaker 2: No sorry, step back, they're trying to achieve it, and

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Speaker 2: they're trying to get an insurance coverage. And they're also

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Speaker 2: trying to forgure out a way that they can work

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Speaker 2: with or you know, participate in some of these wellness

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Speaker 2: programs that are popping up where your insurance coverage is

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Speaker 2: modulated based on your own personal behavior to kind of

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Speaker 2: ensure or regulate or govern govern and how you behave.

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Speaker 1: Outside so that you just become a healthier person. I

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Speaker 1: think it's fucking sick that everything is becoming metro mile now.

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Speaker 1: Everything is just like and what this kind of sounds like,

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Speaker 1: and I hate to go a little far, it does

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Speaker 1: sound a little eugenics, Jace. It's just like, if we

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Speaker 1: all optimize our health, insurance will be cheaper, if we

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Speaker 1: have the right numbers, we're the right kind of person.

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Speaker 1: And there's only one way all that stuff goes. And

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Speaker 1: they'll claim that it's an efficiency thing. But I've yet

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Speaker 1: all of this. I have a fucking Aura ring on.

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Speaker 1: I occasionally have an Apple Watch on. Sometimes it even

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Speaker 1: reads my heart rate. I have all of this data

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Speaker 1: and it's useless. And occasionally United Healthcare will be like, hey,

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Speaker 1: can you you want to connect your Apple watch to

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Speaker 1: us for some reason? Yeah, it's not useless.

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Speaker 2: You're creating a profile that if you know, they have

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Speaker 2: got their hands on it, and we're just rich.

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Speaker 1: You want to connect that, you want to connect men

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Speaker 1: can watch let me see how what you lift? You

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Speaker 1: lift enough?

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Speaker 3: So the real customer is the insurance company, not Yeah.

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Speaker 2: The real customers who are interested in the data, I mean,

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Speaker 2: And that's really also the thing that you'll see with

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Speaker 2: a lot.

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Speaker 1: I saw a.

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Speaker 2: Lot of healthcare ecosystems and apps and smart tech that

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Speaker 2: were purportedly about rewarding you for getting better sleep, rewarding

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Speaker 2: you for eating better, rewarding you for meeting certain goals.

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Speaker 2: But then when you think about what the reward actually

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Speaker 2: is or how it's being distributed, what it is is

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Speaker 2: that they are going to cut some sort of deal

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Speaker 2: with someone who actually wants that data on you. Yeah,

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Speaker 2: we'll use that to extract a little bit more profit

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Speaker 2: out of you, and then they're also going to give

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Speaker 2: you a little bit of that the crumbs of that

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Speaker 2: value that's being created.

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Speaker 1: Right, Yeah, this is great. This is also and there

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Speaker 1: were lots of companies doing this. Yes, I would say.

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Speaker 2: Almost every take called health company I saw that was

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Speaker 2: using artificial intelligence or was using some sort of rewards

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Speaker 2: as them for empowering wellness seems to have a model

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Speaker 2: that is premised on regulating and governing your behavior so

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Speaker 2: that they can generate data about you that would generate

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Speaker 2: profits about you and other people that then they could

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Speaker 2: give you a small piece of you know, that's or

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Speaker 2: you know, another company I actually use the data to

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Speaker 2: offer you discounts to other devices and other products that

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Speaker 2: you could use. So this is we give you a

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Speaker 2: AI sleep mask and realize you're not sleeping properly because

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Speaker 2: of your pillow, so we give you thirty dollars off

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Speaker 2: the pillow.

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Speaker 1: Honestly, at this point, my seventh pillow, I actually want

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Speaker 1: the computer to try and wat this one out for me.

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Speaker 1: Don't you want a computer in your pillow? And I

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Speaker 1: don't know what this AI sleep musk is because I

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Speaker 1: sleep with I sleep in an insane way. I have

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Speaker 1: like a skull cap on and I have a giant

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Speaker 1: eye mask. I must sleep in complete darkness. I also

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Speaker 1: like I grab the covers, and I like c into

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Speaker 1: a ball at the edge of the bed. My therapist says,

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Speaker 1: this is good. Yeah, anyway, an AI sleep mask? What

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Speaker 1: the fuck would that do?

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Speaker 2: Every time one of these things said AI, it's an

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Speaker 2: app and an algorithm that collects the data, presents it

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Speaker 2: to you on a colorful graph, right, maybe gleans or

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Speaker 2: infers insights about other elements of how you're sleeping eating.

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Speaker 1: Did they explain any of how this would work?

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Speaker 2: No, you know, for example, one place you know? For example,

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Speaker 2: they said they can offer a way for you to

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Speaker 2: reduce mental stress. And I asked how they measure mental

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Speaker 2: stress and they say, well, if you got enough of

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Speaker 2: our devices in the ecosystem, we can measure.

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Speaker 1: We can measure physiological.

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Speaker 2: Things like your heartbeat, we can and how much you sweat, right,

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Speaker 2: and we can say, oh, this is not in the

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Speaker 2: usual range for you.

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Speaker 1: What that is true with me? You're being anxious? You

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Speaker 1: know that's yeah? I also I can see it, but

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Speaker 1: also I should A person can do this.

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Speaker 5: Work booze to make that happen is like, I don't know,

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Speaker 5: I don't know how this works.

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Speaker 1: Yeah, Like these rewards, what are they so other than

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Speaker 1: discounts off of other members of the scam.

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Speaker 2: Discounts an unnamed crypto payouts.

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Speaker 1: This is so sick. This is I would love us

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Speaker 1: to dig into the history of these people. Yeah, I

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Speaker 1: would love to learn what their previous job was.

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Speaker 3: I'm hurting over here. You're not stress enough that the

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Speaker 3: single one of these things is an fty A certified product.

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Speaker 1: If Costa Rica, I am going to fucking lose it. Listen.

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Speaker 2: I would like to know too, because I didn't think

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Speaker 2: I was going to see crypto. I think we talked

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Speaker 2: about it the other day, and you guys are like,

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Speaker 2: it's not here, And then what's the first.

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Speaker 1: Thing I go blocked? We're on the blockchain that reward.

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Speaker 4: This is the thing, like, it's insane.

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Speaker 1: It feels like the one place you wouldn't.

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Speaker 2: Well they were they were kind of saying that by

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Speaker 2: being on the blockchain, your data is secure.

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Speaker 1: That's not. It's entirely open. Yes, I know less they

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Speaker 1: do a private blockchain. Those do exist, at which point

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Speaker 1: you can ask the question of why don't I use

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Speaker 1: any number of other databases that would be more efficient. Yes,

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Speaker 1: Oh it's immutable. Who cares, No one gives a fuck,

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Speaker 1: So the databases can be like that too.

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Speaker 4: It's just a trendy word that they can use.

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Speaker 1: It's not even trendy anymore.

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Speaker 4: But like ten years ago, right now the people.

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Speaker 1: Still saying new phone, who dis it's learn and you

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Speaker 1: meme and also do another thing. Why is the crew?

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Speaker 1: I love that that's still legal.

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Speaker 3: I'm scared it's going to be super leg It's.

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Speaker 1: Going to be super legal. And the FDI super.

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Speaker 4: Is in like above legal, it's above.

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Speaker 2: It's encouraged, it's sanctioned by the sanctioned by the Department

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Speaker 2: of governmental efficiency.

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Speaker 3: I'm so scared to check Kaiser when I get home

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Speaker 3: to see if they're thinking about this.

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Speaker 4: They what new alert Kaiser private blockchain.

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Speaker 1: That's a good question though. Did any of these companies

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Speaker 1: have any contracts with insurance companies? No?

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Speaker 2: Actually, every single one that would talk about this either

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Speaker 2: didn't have the product that was offering out in the

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Speaker 2: market yet or didn't have a single insured that was

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Speaker 2: approval to even work with insurance.

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Speaker 1: I just feel like insurance would build these things themselves.

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Speaker 1: You would think that, and probably they will.

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Speaker 2: Well they just i mean not with the blockchain bullshit,

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Speaker 2: but they are already building like you know, well established

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Speaker 2: data pipelines to get in insights.

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Speaker 6: I mean.

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Speaker 2: One example of this is like cars and car insurance. Right,

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Speaker 2: your car is a computer, right, and car insurance have

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Speaker 2: a relatively easy time of using your driving behavior to modulate,

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Speaker 2: you know, what they're going to charge you on a

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Speaker 2: basic level, of course, if you do accidents and such,

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Speaker 2: but you know, getting to the point where it's like,

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Speaker 2: you know, how are you breaking, how are you how

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Speaker 2: fast you're actually going?

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Speaker 4: You know.

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Speaker 5: But another thing is that this this already exists for

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Speaker 5: the insurance companies.

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Speaker 4: It might be. Is a thing what semi it's the

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Speaker 4: Medical Information Bureau.

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Speaker 5: It's it's a housing for all of the medical data

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Speaker 5: of everybody that is involved in any medical stuff in

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Speaker 5: the United States, and it's all housed University of Michigan.

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Speaker 5: I think, okay, so who can access this? This is

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Speaker 5: it's effectively supposed to be like metadata for actuaries. And

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Speaker 5: so this is why actuarial data for insurance companies is

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Speaker 5: so precise and accurate, because they can see all of

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Speaker 5: this data and then use it to rate policies.

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Speaker 1: So we create like a little surveillance site just so

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Speaker 1: the health insurance could continue.

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Speaker 5: And this has existed since like the seventies, like sixties

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Speaker 5: or seventies.

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Speaker 4: I think, yeah, well, no, this is people.

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Speaker 1: Are piste off about insurance companies.

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Speaker 3: Yeah, and have been for decades.

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Speaker 5: Yeah, so it's like this isn't new, it's just now

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Speaker 5: it's being monetized. I mean it was already being monetized,

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Speaker 5: but just in a different way.

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Speaker 2: But a different way by a different group of people

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Speaker 2: who are trying it. It's unclear if they're trying to

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Speaker 2: replicate the thing or build their own infrastructure and products

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Speaker 2: around it.

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Speaker 5: But yeah, yeah, because MiB is the whole point of

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Speaker 5: it is and why it's at an academic institution is

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Speaker 5: that it's it's a used to be you know, outside

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Speaker 5: of outside of industry, right, that's kind of.

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Speaker 3: The idea available to everyone, right.

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Speaker 5: And so whereas this is now, this is now something

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Speaker 5: you can put a patent on, this is something that

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Speaker 5: you can Yeah, this is this is shady.

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Speaker 1: Yeah, yeah, to say the least, To say the least,

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Speaker 1: was there anything other than this kind of ship that in.

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Speaker 2: The healthcare space, a lot of it was like you

437
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Speaker 2: know what, you know, what's called like, you know, luxury surveillance,

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Speaker 2: whor's just like we are gonna pay you know, you're

439
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Speaker 2: gonna pay us for the privilege of giving us a

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Speaker 2: continuous stream of your behavioral data so that we can

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Speaker 2: figure out a way to give you more cool products

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Speaker 2: or you.

443
00:21:38,119 --> 00:21:39,439
Speaker 1: Know, generate some money off of it.

444
00:21:39,560 --> 00:21:39,720
Speaker 4: Right.

445
00:21:39,800 --> 00:21:41,240
Speaker 1: It's amazing, It's beautiful. I love it.

446
00:21:41,280 --> 00:21:43,000
Speaker 2: I think it's a you know, it's a it's a

447
00:21:43,480 --> 00:21:45,280
Speaker 2: it's a genuine value chain.

448
00:21:48,800 --> 00:21:51,240
Speaker 1: That you had me for a second that I was

449
00:21:51,240 --> 00:21:55,040
Speaker 1: I was about to get concerned. Obviously, No, I'm actually

450
00:21:55,080 --> 00:21:58,960
Speaker 1: a gobless. So what else did you see out on

451
00:21:59,000 --> 00:22:00,000
Speaker 1: the on the health flow.

452
00:22:00,520 --> 00:22:02,760
Speaker 2: Oh yeah, yeah, yeah, So you know what else we

453
00:22:02,800 --> 00:22:05,160
Speaker 2: saw we saw, I saw a lot. There's a there's

454
00:22:05,200 --> 00:22:08,520
Speaker 2: an AI baby monitor. Okay, right, yeah, this is this

455
00:22:08,560 --> 00:22:13,879
Speaker 2: for my AI baby or no, it's actually uh for

456
00:22:13,960 --> 00:22:14,880
Speaker 2: your real baby.

457
00:22:15,200 --> 00:22:15,720
Speaker 1: Okay.

458
00:22:15,760 --> 00:22:17,879
Speaker 2: So the pamphlet that I had, I don't know if

459
00:22:17,920 --> 00:22:19,960
Speaker 2: I actually still have it anymore, but it opens up

460
00:22:20,000 --> 00:22:21,320
Speaker 2: with saying, did you know that you know how many

461
00:22:21,400 --> 00:22:23,719
Speaker 2: kids die from a sudden infanitet syndrome.

462
00:22:23,720 --> 00:22:24,640
Speaker 1: That could be one of your kids.

463
00:22:24,680 --> 00:22:26,720
Speaker 2: The way to prevent that is to use our devices

464
00:22:26,760 --> 00:22:28,840
Speaker 2: so that you can monitor your child if they start

465
00:22:28,880 --> 00:22:29,520
Speaker 2: moving forward.

466
00:22:29,880 --> 00:22:33,600
Speaker 1: And these have existed for so long, like nan it

467
00:22:33,720 --> 00:22:37,000
Speaker 1: is like over a decade, all like the ones for

468
00:22:37,160 --> 00:22:40,199
Speaker 1: like the actual like the feet are very valuable. But

469
00:22:40,240 --> 00:22:44,360
Speaker 1: that's also solved problem. Yes, it is a solved problem, right,

470
00:22:44,720 --> 00:22:46,639
Speaker 1: but they found a new way to solve it because

471
00:22:46,640 --> 00:22:47,400
Speaker 1: what they're trying to do.

472
00:22:47,440 --> 00:22:52,480
Speaker 2: Here, it seems, is build an ecosystem.

473
00:22:51,920 --> 00:22:58,320
Speaker 7: Where it's always an ecosystem. Ecosystem we are in Savannah.

474
00:22:57,560 --> 00:23:03,880
Speaker 7: The catalog of products that your baby can have. That product, right,

475
00:23:04,680 --> 00:23:07,560
Speaker 7: Babies love product. Babies are consumers, go.

476
00:23:07,600 --> 00:23:09,200
Speaker 4: For it, you know, well they have eyeballs.

477
00:23:09,240 --> 00:23:12,199
Speaker 2: I mean, so you know, stuff for their eyes, for

478
00:23:12,280 --> 00:23:15,200
Speaker 2: their nose, for the ears, for their breathing.

479
00:23:16,320 --> 00:23:18,000
Speaker 3: Fully online, but these.

480
00:23:18,480 --> 00:23:24,240
Speaker 2: Products just being all separate products, replacement toaste, just.

481
00:23:26,160 --> 00:23:26,360
Speaker 1: Care.

482
00:23:26,880 --> 00:23:30,800
Speaker 2: Yeah, there's stuff for the ears, AI powder, nails trimmers.

483
00:23:31,440 --> 00:23:33,080
Speaker 1: Oh you found a slop company.

484
00:23:33,400 --> 00:23:35,840
Speaker 3: Yeah, they have the spine that goes in the base

485
00:23:35,880 --> 00:23:38,000
Speaker 3: of the skull for the matrix and caliber.

486
00:23:38,119 --> 00:23:41,120
Speaker 1: This is an important CEES history things. So there are

487
00:23:41,119 --> 00:23:45,199
Speaker 1: some fascinating companies. The most honest part of CES is

488
00:23:45,240 --> 00:23:47,480
Speaker 1: the crust on the outside. So you go to the

489
00:23:47,640 --> 00:23:52,280
Speaker 1: very ends of CES and it's just like black text

490
00:23:52,440 --> 00:23:56,159
Speaker 1: on white background Chinese companies and it's just like that

491
00:23:56,440 --> 00:24:03,240
Speaker 1: something something electronic corporation and they sell CCTV gear, battery packs,

492
00:24:03,560 --> 00:24:07,239
Speaker 1: miscellaneous plugs and dildos and it is just that you

493
00:24:07,280 --> 00:24:09,160
Speaker 1: can find these every cs and they are the most

494
00:24:09,200 --> 00:24:10,040
Speaker 1: fun to talk today and.

495
00:24:10,160 --> 00:24:10,879
Speaker 4: Give us shit.

496
00:24:11,600 --> 00:24:13,800
Speaker 1: Yeah. But what Eddie is referring to as a slop

497
00:24:13,840 --> 00:24:15,760
Speaker 1: company where the ones that are not honest enough to

498
00:24:15,880 --> 00:24:18,240
Speaker 1: just be like, yeah, we sell everything, just we're here

499
00:24:18,280 --> 00:24:21,080
Speaker 1: to money launder. I guess not saying the people literally

500
00:24:21,119 --> 00:24:23,040
Speaker 1: at the fine companies that I've kind of named money

501
00:24:23,119 --> 00:24:26,800
Speaker 1: laundered just for the legal purposes. But I feel like

502
00:24:26,840 --> 00:24:28,720
Speaker 1: this one is like trying to pretend they're like doing

503
00:24:28,760 --> 00:24:32,800
Speaker 1: good for the world versus being a wholesaler of baby safe.

504
00:24:32,920 --> 00:24:35,320
Speaker 3: Yeah, they opened with terror for your baby is going.

505
00:24:35,200 --> 00:24:38,760
Speaker 1: To exactly they sell them fair and also outlet exists.

506
00:24:39,680 --> 00:24:41,960
Speaker 1: What the fuck is the AI part? What's that?

507
00:24:42,520 --> 00:24:46,399
Speaker 2: So that one was literally just monitoring if your child

508
00:24:46,480 --> 00:24:48,560
Speaker 2: is moving and if it doesn't move a loading you

509
00:24:49,280 --> 00:24:52,040
Speaker 2: and that this really has been Yeah, that's been sold

510
00:24:52,040 --> 00:24:54,000
Speaker 2: for a long time, like you said, right, but what's

511
00:24:54,560 --> 00:24:57,080
Speaker 2: they Well that's a great question.

512
00:24:57,119 --> 00:24:59,400
Speaker 1: What is the AI part of that? Well, I mean

513
00:24:59,480 --> 00:25:02,520
Speaker 1: there is actual very like computer vision. Like to be

514
00:25:02,600 --> 00:25:05,560
Speaker 1: clear that official intelligence has been around for a while

515
00:25:05,720 --> 00:25:07,600
Speaker 1: long has actually been working.

516
00:25:07,880 --> 00:25:10,480
Speaker 2: When they say AI, they're implying there is a novel

517
00:25:10,920 --> 00:25:13,679
Speaker 2: thing that is artificial intelligence on top of this and

518
00:25:13,840 --> 00:25:14,920
Speaker 2: an obscurring.

519
00:25:14,520 --> 00:25:16,320
Speaker 1: Versus on top of the actual AI.

520
00:25:16,520 --> 00:25:18,800
Speaker 5: There's already around for a while, like some sort of

521
00:25:18,800 --> 00:25:20,520
Speaker 5: generative is what's going on.

522
00:25:20,560 --> 00:25:22,960
Speaker 1: There's nothing new. They just want they just hope that

523
00:25:23,000 --> 00:25:23,640
Speaker 1: you'll think.

524
00:25:23,480 --> 00:25:25,000
Speaker 3: It's generating a baby.

525
00:25:25,119 --> 00:25:27,000
Speaker 1: Yeah, this manual, if you look at the back, it

526
00:25:27,040 --> 00:25:30,080
Speaker 1: says twenty seventeen on the.

527
00:25:29,320 --> 00:25:30,879
Speaker 4: All of a sudden you have a new baby. Like,

528
00:25:30,920 --> 00:25:31,480
Speaker 4: it's just like.

529
00:25:31,600 --> 00:25:34,600
Speaker 2: It's it's it's soothing your anxiety. So you can generate

530
00:25:34,600 --> 00:25:35,400
Speaker 2: that m grades.

531
00:25:35,600 --> 00:25:39,840
Speaker 1: You know, that would be a really great way for

532
00:25:39,880 --> 00:25:42,239
Speaker 1: one of these people to sell something, just being like

533
00:25:42,320 --> 00:25:45,119
Speaker 1: you're anxious, you're not able to have sex. Yeah, anyway,

534
00:25:45,160 --> 00:25:48,560
Speaker 1: you need this baby monitoring a surveillance state in your house,

535
00:25:48,680 --> 00:25:52,000
Speaker 1: or of course the wonderful the AI cat litter thing.

536
00:25:52,160 --> 00:25:55,320
Speaker 1: Yeah yeah, oh my god, five G connected. Fuck yeah,

537
00:25:55,960 --> 00:26:01,640
Speaker 1: that means there's an app, isn't that five G's whole

538
00:26:01,640 --> 00:26:05,240
Speaker 1: point that it's like home broad bank connection. But what

539
00:26:05,320 --> 00:26:09,440
Speaker 1: are you streaming? So most other than cat piss Yeah,

540
00:26:09,560 --> 00:26:10,160
Speaker 1: this is the thing.

541
00:26:10,200 --> 00:26:13,919
Speaker 2: Almost all of these devices are like, hey, so we

542
00:26:14,000 --> 00:26:15,480
Speaker 2: will give you a nap and in the app you

543
00:26:15,480 --> 00:26:17,520
Speaker 2: can see when your guy gets on and off, how

544
00:26:17,600 --> 00:26:21,160
Speaker 2: much it ships or pisses, and if there's any differences

545
00:26:21,200 --> 00:26:24,160
Speaker 2: in it, and it will give you a mediate alerts,

546
00:26:24,359 --> 00:26:25,320
Speaker 2: right because it's.

547
00:26:25,160 --> 00:26:31,080
Speaker 1: Your cat has ship. Yeah, honestly, what do you You're

548
00:26:31,119 --> 00:26:31,720
Speaker 1: more anxious?

549
00:26:33,080 --> 00:26:35,040
Speaker 4: Pops up like your cat has pooped.

550
00:26:35,240 --> 00:26:38,800
Speaker 1: You're on like a fucking like on a date. Yeah, sorry,

551
00:26:38,840 --> 00:26:39,960
Speaker 1: my cat's not shitting right.

552
00:26:40,760 --> 00:26:43,960
Speaker 3: The weird thing is my partner and I were looking

553
00:26:44,000 --> 00:26:46,159
Speaker 3: at a new cat litter box, and of course they

554
00:26:46,280 --> 00:26:49,160
Speaker 3: all do have that five G integration, and the app

555
00:26:49,160 --> 00:26:54,879
Speaker 3: associate the answer why, And it's a niche cases. Every

556
00:26:54,960 --> 00:26:57,879
Speaker 3: time we have taken the cats to the vet, they've asked,

557
00:26:57,880 --> 00:26:59,560
Speaker 3: do you have a stool sample? How can I tell

558
00:26:59,560 --> 00:27:02,359
Speaker 3: the difference the different turds? Yeah, oh, because I know

559
00:27:03,040 --> 00:27:05,080
Speaker 3: a fresh one has just dropped. Let me go get

560
00:27:05,080 --> 00:27:07,120
Speaker 3: that in the medium so I hear.

561
00:27:07,320 --> 00:27:10,800
Speaker 1: So this is I'm describing this cat litter box.

562
00:27:10,920 --> 00:27:12,840
Speaker 3: How the AI knows which is and.

563
00:27:12,800 --> 00:27:15,760
Speaker 1: Apparently it has multi cat facial recognition.

564
00:27:17,080 --> 00:27:17,359
Speaker 4: Yeah.

565
00:27:18,119 --> 00:27:20,600
Speaker 1: A friend of the show Hunter Washington Post brought this

566
00:27:20,640 --> 00:27:23,480
Speaker 1: to me yesterday. It was this, Apparently it can tell

567
00:27:23,480 --> 00:27:25,679
Speaker 1: the different cats, so that if you have one sickly

568
00:27:25,720 --> 00:27:29,040
Speaker 1: horrible cat and one beautiful sweet cat, you know which

569
00:27:29,040 --> 00:27:31,479
Speaker 1: one to take to the bed for the last time? No, right,

570
00:27:31,680 --> 00:27:31,919
Speaker 1: you know?

571
00:27:32,359 --> 00:27:37,639
Speaker 5: Or like if it commits a crime, yeah, ye, so

572
00:27:37,720 --> 00:27:39,360
Speaker 5: that you're the cat stealing.

573
00:27:39,040 --> 00:27:42,640
Speaker 1: All the fucking food outside. But my question as well,

574
00:27:42,720 --> 00:27:44,639
Speaker 1: is this cat litter thing, which is eight hundred and

575
00:27:44,720 --> 00:27:47,800
Speaker 1: ninety nine dollars, by the way, which fucking rocks.

576
00:27:47,880 --> 00:27:50,080
Speaker 3: I assume it has proprietary litter that goes into it

577
00:27:50,119 --> 00:27:52,000
Speaker 3: as well, because that's the consumable.

578
00:27:52,040 --> 00:27:53,320
Speaker 1: I mean, why wouldn't you use it?

579
00:27:53,400 --> 00:27:54,400
Speaker 3: All about I.

580
00:27:54,320 --> 00:27:57,440
Speaker 1: Need a subscription. I assume there's a subscription fee. Yeah,

581
00:27:57,440 --> 00:27:59,639
Speaker 1: and I would be surprised that there was. If there's not,

582
00:27:59,760 --> 00:28:02,760
Speaker 1: I will absolutely fucking lose it. Like why am I

583
00:28:02,760 --> 00:28:05,280
Speaker 1: if I can't pay an extra five dollars a month

584
00:28:05,400 --> 00:28:07,280
Speaker 1: to catgenie dot biz.

585
00:28:07,400 --> 00:28:09,520
Speaker 5: Yeah, well then I don't trust them after that because

586
00:28:09,560 --> 00:28:11,280
Speaker 5: I ever thought through this process clearly, and.

587
00:28:11,880 --> 00:28:17,240
Speaker 2: For some time I was looking at an automatic feeder

588
00:28:17,280 --> 00:28:20,520
Speaker 2: because I had this, I had a schedule and most

589
00:28:20,520 --> 00:28:22,480
Speaker 2: of my roommates are out and friends weren't in town

590
00:28:22,480 --> 00:28:23,960
Speaker 2: where I wasn't able to get someone to watch the

591
00:28:24,000 --> 00:28:25,239
Speaker 2: cat I was like, okay, well, like I can get

592
00:28:25,240 --> 00:28:27,600
Speaker 2: someone to watch them sometimes, maybe I'll get an auto

593
00:28:27,800 --> 00:28:31,040
Speaker 2: non automatic feeder, automatic litter box. And then every single

594
00:28:31,040 --> 00:28:33,320
Speaker 2: one I tried to get there's a fucking app. And

595
00:28:33,440 --> 00:28:34,920
Speaker 2: then when you compare it to the ones that don't

596
00:28:34,920 --> 00:28:37,920
Speaker 2: have the app, it's like a three hundred dollars addition

597
00:28:38,080 --> 00:28:41,560
Speaker 2: to the price for nothing other than like we've been

598
00:28:41,600 --> 00:28:44,240
Speaker 2: talking about, no cat shit, gradual.

599
00:28:44,640 --> 00:28:48,840
Speaker 1: I'm just imagining being like in court and you've you've

600
00:28:48,960 --> 00:28:51,880
Speaker 1: silenced your phone and your judge is turning to me.

601
00:28:51,920 --> 00:28:54,520
Speaker 1: He's about sentence. You're not meant to have your apple watching.

602
00:28:54,560 --> 00:28:57,800
Speaker 1: It's like being catship, just like is it? Is it

603
00:28:57,880 --> 00:29:00,080
Speaker 1: like nest where you get the alert it does and

604
00:29:00,120 --> 00:29:01,360
Speaker 1: show you the video and you drag it down.

605
00:29:01,440 --> 00:29:03,040
Speaker 3: It's just like a big I don't want a video

606
00:29:03,080 --> 00:29:03,720
Speaker 3: of cat ship a.

607
00:29:03,720 --> 00:29:06,840
Speaker 4: Big I'm sorry your honor, but my cat just ship.

608
00:29:08,200 --> 00:29:14,280
Speaker 1: Yelled up your hand. It's wild, mister Tinkling, you know which.

609
00:29:14,360 --> 00:29:16,840
Speaker 2: And it's also so funny because it's like the price

610
00:29:16,920 --> 00:29:17,640
Speaker 2: the price jump.

611
00:29:17,680 --> 00:29:21,320
Speaker 1: Also, it's like a regular litter bar. It's not special.

612
00:29:21,360 --> 00:29:24,320
Speaker 2: Two dollars, three dollars. I mean, it doesn't cost that much,

613
00:29:24,320 --> 00:29:25,440
Speaker 2: but it's just a little special.

614
00:29:25,520 --> 00:29:27,520
Speaker 1: Yes, not thing is not like it's a new kind

615
00:29:27,520 --> 00:29:29,960
Speaker 1: of litter box other than the stuff they've stabled to it.

616
00:29:30,040 --> 00:29:34,200
Speaker 1: It's like, hey, you're sophisticated buyer, this is not gonna work.

617
00:29:34,240 --> 00:29:36,520
Speaker 3: You love your cats, right, and you love your.

618
00:29:36,440 --> 00:29:40,240
Speaker 1: Cat Your cats must be fancy cats. Yeah, and I

619
00:29:40,280 --> 00:29:42,560
Speaker 1: have to be. And they need five g We're throwing

620
00:29:42,600 --> 00:29:45,520
Speaker 1: five dollars off fancy feast. Okay, Now, something just fucking

621
00:29:45,520 --> 00:29:48,360
Speaker 1: occurred to me about this. It's even weirder. They're talking

622
00:29:48,400 --> 00:29:52,160
Speaker 1: about five G. That's a cellular wireless standard.

623
00:29:52,200 --> 00:29:55,680
Speaker 2: Yeah, it's Chinese, which means.

624
00:29:57,360 --> 00:30:00,720
Speaker 1: The cat let the company very well, it's u dirty tech.

625
00:30:02,360 --> 00:30:04,640
Speaker 4: Sovereign citizens are going to come to your house and take.

626
00:30:04,480 --> 00:30:09,880
Speaker 1: Your They're already very unhappy with me. But also it's

627
00:30:09,920 --> 00:30:12,760
Speaker 1: five G. Before the end of the show, can you

628
00:30:12,800 --> 00:30:14,560
Speaker 1: try and get back there just to ask them if

629
00:30:14,560 --> 00:30:18,480
Speaker 1: they mean five G WiFi because that is an egregious

630
00:30:18,520 --> 00:30:21,280
Speaker 1: overstatement because they are people are just like the guys

631
00:30:21,280 --> 00:30:23,760
Speaker 1: here that don't know how anything works. Go, it's got

632
00:30:23,760 --> 00:30:25,720
Speaker 1: five G in it, which they think is like the

633
00:30:25,800 --> 00:30:31,360
Speaker 1: cell phone standard versus this is the show though, this

634
00:30:31,400 --> 00:30:35,120
Speaker 1: is ces we're just describing. Like I know, Casey Kagawa,

635
00:30:35,200 --> 00:30:37,720
Speaker 1: friend of the show as well, was saying to me earlier. Oh, ed,

636
00:30:37,760 --> 00:30:41,480
Speaker 1: the hardware stuff's really cool. It is faster computer now,

637
00:30:41,520 --> 00:30:44,920
Speaker 1: it's great. AI stetis god great? Actually cool is that?

638
00:30:44,960 --> 00:30:51,240
Speaker 4: Actually it's not a happy heartbeats.

639
00:30:51,320 --> 00:30:54,800
Speaker 1: But you can go to a legacy media outlet and

640
00:30:54,840 --> 00:30:58,920
Speaker 1: hear about all the computer stuff that actually matters, because

641
00:30:58,960 --> 00:31:01,600
Speaker 1: that's not really the story of CS. That's the stuff

642
00:31:01,640 --> 00:31:05,400
Speaker 1: that happens kind of outside, and what you have in

643
00:31:05,440 --> 00:31:08,760
Speaker 1: there is people making series of a series of promises

644
00:31:08,760 --> 00:31:10,480
Speaker 1: that have gone through a law firm to make sure

645
00:31:10,520 --> 00:31:14,880
Speaker 1: they're not going to get them in actual trouble hopefully.

646
00:31:15,920 --> 00:31:17,720
Speaker 1: Did you see any Wi Fi grills though?

647
00:31:18,400 --> 00:31:18,760
Speaker 8: No?

648
00:31:19,000 --> 00:31:27,760
Speaker 2: Oh buddy, I saw a TV with a chat bot why.

649
00:31:26,120 --> 00:31:27,320
Speaker 3: To help you choose channels?

650
00:31:27,400 --> 00:31:28,560
Speaker 1: Yeah, you know, I saw.

651
00:31:29,360 --> 00:31:32,560
Speaker 2: I saw sex toys that used video games for a

652
00:31:32,640 --> 00:31:40,120
Speaker 2: long distance connection with groups sinking for multiple orgasms.

653
00:31:40,680 --> 00:31:44,080
Speaker 1: They did not promise that ties to the verst that

654
00:31:44,120 --> 00:31:46,200
Speaker 1: I went to they, so I.

655
00:31:46,280 --> 00:31:47,959
Speaker 4: Was I'll never forget this.

656
00:31:48,080 --> 00:31:51,840
Speaker 5: I was at the Indiegog party the first CS and

657
00:31:51,880 --> 00:31:53,480
Speaker 5: I was talking to this folks and they were telling

658
00:31:53,480 --> 00:31:57,080
Speaker 5: me about their technology. Technology was about trying to have

659
00:31:57,120 --> 00:32:01,920
Speaker 5: some sort of tactile response, uh, in a virtual environment.

660
00:32:02,080 --> 00:32:04,560
Speaker 3: Keep in mind talking to a priest in full white.

661
00:32:05,600 --> 00:32:08,080
Speaker 4: Yeah, exactly right, that's right.

662
00:32:08,080 --> 00:32:10,480
Speaker 5: And so this is Chinese folks, right, and so we're

663
00:32:10,680 --> 00:32:12,360
Speaker 5: Chinese company and we're talking about it.

664
00:32:12,440 --> 00:32:13,479
Speaker 4: Was like, man, that's really amazing.

665
00:32:13,560 --> 00:32:16,000
Speaker 5: Technology like that would be great for for like the

666
00:32:16,040 --> 00:32:19,160
Speaker 5: medical industry, Like that would really revolutionize a lot of

667
00:32:19,200 --> 00:32:21,560
Speaker 5: stuff for surgeries and like yeah, yeah, no, but we're

668
00:32:21,560 --> 00:32:23,120
Speaker 5: going into porn because that's where all the money is.

669
00:32:25,720 --> 00:32:29,720
Speaker 1: Just yeah, ten years later, same, you know, but it's

670
00:32:29,720 --> 00:32:32,560
Speaker 1: not taken off thing. Yeah though, I mean it's not scaling.

671
00:32:32,800 --> 00:32:35,800
Speaker 2: There are toys that allow you to have group players

672
00:32:35,800 --> 00:32:36,360
Speaker 2: to see them.

673
00:32:36,400 --> 00:32:37,400
Speaker 1: That's existed for a bit.

674
00:32:37,520 --> 00:32:40,080
Speaker 2: The that I was trying to figure out, the AI element,

675
00:32:40,480 --> 00:32:48,080
Speaker 2: the metas, Yeah, the extended reality part of Wow, of

676
00:32:48,160 --> 00:32:52,240
Speaker 2: the super duper you know, turbero charged flesh lights, Yes,

677
00:32:52,760 --> 00:33:00,280
Speaker 2: the suction dil dos of the uh pro massagers lodged.

678
00:33:00,040 --> 00:33:02,400
Speaker 1: You said, all for the you're going to Caribbean.

679
00:33:02,920 --> 00:33:06,680
Speaker 4: Yea, this is where we need Father Bellasar like the.

680
00:33:06,680 --> 00:33:09,720
Speaker 1: Other member of the clergy that for some reason shows

681
00:33:09,800 --> 00:33:25,560
Speaker 1: up here. But so other than dildos and other than

682
00:33:25,920 --> 00:33:30,240
Speaker 1: health things, any other weird shit, anything loathsome pig.

683
00:33:30,200 --> 00:33:34,480
Speaker 2: Like anything like, oh, there there was a there's an

684
00:33:34,520 --> 00:33:38,280
Speaker 2: app it's called an AI Public Transportation Bell and it's

685
00:33:38,440 --> 00:33:40,320
Speaker 2: and it rings a bell when you're about to get

686
00:33:40,320 --> 00:33:42,040
Speaker 2: to your stop on the bus or train.

687
00:33:51,120 --> 00:33:54,560
Speaker 1: Freaking. There was no one at that booth that I

688
00:33:54,600 --> 00:33:56,200
Speaker 1: was like, this is what you're talking me about.

689
00:33:56,240 --> 00:34:00,280
Speaker 2: The alleged section of the conference where it's just this

690
00:34:00,440 --> 00:34:01,080
Speaker 2: is a front.

691
00:34:02,360 --> 00:34:05,200
Speaker 1: Yeah, man, sorry, we're just we're using this for that.

692
00:34:05,760 --> 00:34:09,040
Speaker 1: The serbian gentleman behind you, one that smells of cigarettes.

693
00:34:09,680 --> 00:34:12,799
Speaker 1: That man, that's who we're talking to him. That's our

694
00:34:12,800 --> 00:34:15,840
Speaker 1: one meeting the things that we're here for four days

695
00:34:15,960 --> 00:34:18,399
Speaker 1: to kind of just cover for this. He will kill you.

696
00:34:19,880 --> 00:34:21,440
Speaker 4: Cigarettes and slim of it.

697
00:34:21,440 --> 00:34:24,600
Speaker 1: It's it's so strange that we have a show full

698
00:34:24,640 --> 00:34:28,040
Speaker 1: of this because you kind of see articles about cs

699
00:34:28,080 --> 00:34:31,640
Speaker 1: and it's like fastest computer. There's the three thousand dollars

700
00:34:32,360 --> 00:34:35,080
Speaker 1: AI machine that I should have some of rotters coming

701
00:34:35,080 --> 00:34:38,360
Speaker 1: in to talk about tomorrow. Hell yeah, but in video

702
00:34:38,600 --> 00:34:40,880
Speaker 1: also who knows what they're doing at some point.

703
00:34:40,800 --> 00:34:43,600
Speaker 3: And the eternal Hall of TVs all.

704
00:34:43,400 --> 00:34:45,560
Speaker 1: Of televisions, which are fine, I don't we love the

705
00:34:45,560 --> 00:34:49,160
Speaker 1: big screens and but really it's just so weird how

706
00:34:49,239 --> 00:34:51,880
Speaker 1: much of this stuff is just like fake fake or

707
00:34:51,960 --> 00:34:56,200
Speaker 1: like real, but customer base of like one hundred people

708
00:34:56,840 --> 00:34:59,040
Speaker 1: like the cat. How much do you think that cat

709
00:34:59,080 --> 00:35:02,960
Speaker 1: thing costs to make? Because I bet it's accidentally really expensive.

710
00:35:03,960 --> 00:35:06,040
Speaker 2: I mean it depends because it's is it also one

711
00:35:06,040 --> 00:35:10,040
Speaker 2: of those ones with the motor that rotates it automatically sifts. Yeah,

712
00:35:10,120 --> 00:35:12,840
Speaker 2: then those things break. Yeah, they break easily. We go

713
00:35:12,960 --> 00:35:17,360
Speaker 2: one because they're not doing They are easy to installed,

714
00:35:17,360 --> 00:35:20,200
Speaker 2: but I feel like they're not. They don't tell you

715
00:35:20,200 --> 00:35:22,520
Speaker 2: how to install it, and so you're probably gonna.

716
00:35:22,320 --> 00:35:25,520
Speaker 1: Break it in installation. The app is probably not gonna

717
00:35:25,560 --> 00:35:28,040
Speaker 1: work the time, you know. So I don't know.

718
00:35:28,080 --> 00:35:31,879
Speaker 2: They're probably accidentally expensive because of how much they wear

719
00:35:32,000 --> 00:35:34,640
Speaker 2: down and how much they end up getting returned versus like,

720
00:35:34,880 --> 00:35:35,200
Speaker 2: how do.

721
00:35:35,120 --> 00:35:38,080
Speaker 1: You really like load test those things? You get a

722
00:35:38,200 --> 00:35:38,880
Speaker 1: really big.

723
00:35:43,560 --> 00:35:49,640
Speaker 4: Like you'll make it in garfield.

724
00:35:54,360 --> 00:35:56,040
Speaker 1: Do you think this is how they get the training

725
00:35:56,120 --> 00:35:58,480
Speaker 1: data to find out about the TETs. Yeah, I mean

726
00:35:58,560 --> 00:36:03,120
Speaker 1: that listen chosen by perfected by signs to be fair.

727
00:36:04,040 --> 00:36:06,600
Speaker 1: This is how I describe my cat Babu. Yeah, you know,

728
00:36:06,880 --> 00:36:09,600
Speaker 1: and also myself. I do use the litther box, but

729
00:36:09,920 --> 00:36:12,320
Speaker 1: he just won't use these fancy ones. We've tried fancy

730
00:36:12,320 --> 00:36:15,080
Speaker 1: ones and he just will not go. Only one of

731
00:36:15,080 --> 00:36:19,759
Speaker 1: my cats uses the fancy one custody I do. I really,

732
00:36:20,239 --> 00:36:22,000
Speaker 1: that's the most cat thing to do. As well, our

733
00:36:22,080 --> 00:36:23,400
Speaker 1: gods can throw it away.

734
00:36:23,520 --> 00:36:28,280
Speaker 3: Yeah, no, our cast will only use the robot litter

735
00:36:28,280 --> 00:36:32,240
Speaker 3: box for pooping. Altho other we have two other little boxes.

736
00:36:32,320 --> 00:36:35,439
Speaker 3: Those are the piss boxes, only the robot gets turts.

737
00:36:35,440 --> 00:36:37,040
Speaker 1: Which one do you use? Ah?

738
00:36:37,360 --> 00:36:41,839
Speaker 3: I I am a discerning individual. I prefer to go

739
00:36:41,960 --> 00:36:42,960
Speaker 3: use an actual toilet.

740
00:36:44,080 --> 00:36:49,480
Speaker 1: Okay, so you're good for this show. Now, you did

741
00:36:49,520 --> 00:36:55,560
Speaker 1: see a speech from the incredible Linda Yakarina, CEO of

742
00:36:55,840 --> 00:37:00,120
Speaker 1: X the Everything app, where I currently do my banking,

743
00:37:00,840 --> 00:37:06,040
Speaker 1: my taxes, my dating, and my professional work. I have

744
00:37:06,120 --> 00:37:07,960
Speaker 1: a DM I need to see you too, admnute from

745
00:37:07,960 --> 00:37:11,160
Speaker 1: a fourteen words groper. That's my doctor.

746
00:37:11,320 --> 00:37:14,080
Speaker 3: And the medical care on acts as well.

747
00:37:14,320 --> 00:37:16,480
Speaker 1: My credit card was just charged eleven thousand dollars from it.

748
00:37:16,719 --> 00:37:19,680
Speaker 1: Everything's going great there. But she is the CEO of

749
00:37:19,719 --> 00:37:21,920
Speaker 1: this company, and you said it was kind of bad.

750
00:37:22,120 --> 00:37:22,960
Speaker 1: It just wasn't that far.

751
00:37:23,080 --> 00:37:25,560
Speaker 2: Yeah, I didn't really know. A movie could have been

752
00:37:25,560 --> 00:37:28,759
Speaker 2: an email, could have been a press release. Yeah. She

753
00:37:28,840 --> 00:37:32,440
Speaker 2: talked a lot about the global collective unconscious, unconscious.

754
00:37:32,480 --> 00:37:35,480
Speaker 1: Oh god, the fuck does that mean? Uh? That's X

755
00:37:35,960 --> 00:37:39,000
Speaker 1: the Everything saying. You know, did she say unconscious?

756
00:37:39,080 --> 00:37:40,200
Speaker 4: Yeah, the collective.

757
00:37:40,960 --> 00:37:44,120
Speaker 1: I believe, we believe. I have it in my notes.

758
00:37:44,360 --> 00:37:46,840
Speaker 1: But the thing is, if she said conscious, it's still stupid.

759
00:37:46,880 --> 00:37:49,080
Speaker 1: But if she said unconscious, I would believe that because

760
00:37:49,120 --> 00:37:51,279
Speaker 1: that's like a yak Areino classic. Yeah, just like a

761
00:37:51,280 --> 00:37:54,600
Speaker 1: complete because the thing she says sound like the kind

762
00:37:54,600 --> 00:37:56,880
Speaker 1: of thing you say immediately after walking out of a

763
00:37:56,920 --> 00:37:57,359
Speaker 1: car wreck.

764
00:37:57,520 --> 00:37:59,080
Speaker 3: Let's go to the notes since, yes.

765
00:37:59,520 --> 00:37:59,920
Speaker 1: But it's us.

766
00:38:00,160 --> 00:38:04,160
Speaker 5: But it's also like what an undergrad like philosophy student.

767
00:38:04,600 --> 00:38:10,120
Speaker 2: Right, she talks about how it's self regulating, but you know,

768
00:38:10,440 --> 00:38:15,600
Speaker 2: the first yeah, the first question was about comparing Meta

769
00:38:15,640 --> 00:38:17,400
Speaker 2: to X and talking about how it got rid of

770
00:38:17,440 --> 00:38:20,000
Speaker 2: fact checkers, and she was like, they're trying to copy

771
00:38:20,600 --> 00:38:24,080
Speaker 2: community notes basically, you know, they're realizing.

772
00:38:23,680 --> 00:38:28,200
Speaker 5: All websites sucks shit copying Like, Buddy, I'm on community notes,

773
00:38:28,600 --> 00:38:30,960
Speaker 5: so I see all this stuff and it is a

774
00:38:31,239 --> 00:38:31,839
Speaker 5: ship show.

775
00:38:31,920 --> 00:38:33,440
Speaker 1: It's a ship show. I mean, if you've seen the

776
00:38:33,440 --> 00:38:36,680
Speaker 1: fucking facts that people post on Facebook, Yeah, you really

777
00:38:36,719 --> 00:38:38,800
Speaker 1: want that community anyway?

778
00:38:38,920 --> 00:38:40,040
Speaker 4: Yes, and now that.

779
00:38:39,960 --> 00:38:41,799
Speaker 1: Great idea has been copied, and so.

780
00:38:41,800 --> 00:38:43,480
Speaker 2: The idea there is like you know, she's trying to,

781
00:38:43,760 --> 00:38:48,360
Speaker 2: you know, talk about how Meta is going to emulate

782
00:38:48,920 --> 00:38:52,960
Speaker 2: X's innovative system that inspires great behavior, which is that

783
00:38:53,400 --> 00:38:56,120
Speaker 2: noted post or dramatically shared less.

784
00:38:55,960 --> 00:38:57,000
Speaker 1: Like suicide bump.

785
00:38:57,080 --> 00:39:00,920
Speaker 4: Yeah, I want to die like anything.

786
00:39:00,960 --> 00:39:03,719
Speaker 2: The cyber truck guy got his inspiration that and chat

787
00:39:03,760 --> 00:39:05,600
Speaker 2: gpt apparently where which helped them.

788
00:39:05,440 --> 00:39:10,280
Speaker 1: Build they explosive. The police department recently reported.

789
00:39:10,080 --> 00:39:11,160
Speaker 4: That didn't quite work.

790
00:39:11,400 --> 00:39:14,160
Speaker 1: Yes, and that's chat GPT.

791
00:39:14,480 --> 00:39:18,840
Speaker 3: Yeah, as I described it, it's effectively just the anarchist cookbook.

792
00:39:18,880 --> 00:39:20,680
Speaker 3: And you're going to get similar respect results.

793
00:39:20,719 --> 00:39:24,839
Speaker 2: Yeah, you know, I'll try and so so you know.

794
00:39:24,920 --> 00:39:27,239
Speaker 2: Her rating of the meta abandoning.

795
00:39:27,280 --> 00:39:30,600
Speaker 1: Third party fact I team great victory for free speech.

796
00:39:30,880 --> 00:39:31,080
Speaker 4: Cool.

797
00:39:31,320 --> 00:39:34,680
Speaker 2: She talked about how the greatest product innovation, talked about

798
00:39:34,680 --> 00:39:36,440
Speaker 2: how there have been like two hundred and fifty product

799
00:39:36,440 --> 00:39:40,880
Speaker 2: innovations during your tenure. Extort of the fun what Yeah,

800
00:39:41,120 --> 00:39:45,279
Speaker 2: but the biggest one is trend genius, which is when

801
00:39:45,320 --> 00:39:47,239
Speaker 2: a trend kicks up on X and it hits a

802
00:39:47,239 --> 00:39:51,520
Speaker 2: certain altitude. Advertisers they have agreements with are they're they're

803
00:39:51,560 --> 00:39:54,000
Speaker 2: able to take advantage of those trends and they get

804
00:39:54,040 --> 00:39:56,959
Speaker 2: matched with them. And as in your ad campaign, kicks

805
00:39:57,000 --> 00:40:00,160
Speaker 2: in the high drive when there's a trend connected to

806
00:40:00,200 --> 00:40:02,960
Speaker 2: what you're looking to target, goes in the high drive.

807
00:40:03,000 --> 00:40:06,040
Speaker 1: Almost some kind of like word you could advertise against,

808
00:40:06,520 --> 00:40:08,799
Speaker 1: like some ad words right.

809
00:40:08,520 --> 00:40:12,319
Speaker 5: Right, you know all of the ads I get, Yeah,

810
00:40:12,320 --> 00:40:13,880
Speaker 5: they're all everything is Temu.

811
00:40:14,200 --> 00:40:17,359
Speaker 1: I get Tamu, indie sci fi.

812
00:40:19,080 --> 00:40:22,160
Speaker 2: Books about how Donald Trump is going to save America,

813
00:40:21,680 --> 00:40:24,719
Speaker 2: sig crypto that doesn't that that's happening right now.

814
00:40:24,920 --> 00:40:27,319
Speaker 1: Yeah, yeah, yeah, I.

815
00:40:27,280 --> 00:40:29,440
Speaker 4: Only get Timu. What are you like looking.

816
00:40:29,239 --> 00:40:34,200
Speaker 1: At blocking so many ads? At one point I just

817
00:40:34,239 --> 00:40:37,200
Speaker 1: started getting the weirdest ship. I got like the most

818
00:40:37,239 --> 00:40:43,160
Speaker 1: expensive coat ever, and it was like a seventy dollars coat.

819
00:40:43,480 --> 00:40:45,360
Speaker 1: I actually think it's a great bed, but it was

820
00:40:45,400 --> 00:40:48,680
Speaker 1: the worst looking outfit. It looked like something that bas

821
00:40:48,760 --> 00:40:53,000
Speaker 1: Leman would have in his romeo and do you do

822
00:40:54,320 --> 00:40:59,080
Speaker 1: you buy your Oh my gosh.

823
00:40:59,120 --> 00:41:01,760
Speaker 3: So what you're telling me is they've created an automated

824
00:41:01,800 --> 00:41:05,919
Speaker 3: system to guarantee that the advertisers won't miss an opportunity

825
00:41:06,320 --> 00:41:09,600
Speaker 3: to be next to an incredibly popular racist post, right

826
00:41:09,640 --> 00:41:10,920
Speaker 3: and all these don't want to miss it.

827
00:41:11,400 --> 00:41:13,920
Speaker 1: All these trends are the ones that grok comes up with.

828
00:41:14,480 --> 00:41:17,520
Speaker 2: Oh lord, yeah, rock in the in the in the

829
00:41:17,520 --> 00:41:18,880
Speaker 2: center of the racism computer.

830
00:41:19,320 --> 00:41:20,520
Speaker 4: They changed the image recently.

831
00:41:20,880 --> 00:41:23,520
Speaker 1: Yeah, you know, the logo for grok is really bad.

832
00:41:23,760 --> 00:41:26,840
Speaker 4: It's super It looks like like a jpeg.

833
00:41:26,600 --> 00:41:30,520
Speaker 2: Effects so bad one of the examples I really also loved.

834
00:41:30,520 --> 00:41:32,839
Speaker 2: She was kind of like, you know, talking about how

835
00:41:32,920 --> 00:41:36,280
Speaker 2: access to everything plays. It's real time, so many trends.

836
00:41:36,320 --> 00:41:38,239
Speaker 2: But you know, sometimes me and my husband we fight

837
00:41:38,360 --> 00:41:39,040
Speaker 2: all the time.

838
00:41:39,600 --> 00:41:40,520
Speaker 1: We fight all the time.

839
00:41:41,680 --> 00:41:52,560
Speaker 8: Oh really, imagine my husband my piece of ship, and

840
00:41:52,640 --> 00:41:54,759
Speaker 8: so we fight all the time about what to watch,

841
00:41:54,800 --> 00:41:56,160
Speaker 8: and we're fighting over the remote.

842
00:41:56,440 --> 00:41:59,440
Speaker 2: He thinks football is consequential. I want to know what's

843
00:41:59,440 --> 00:42:01,200
Speaker 2: happening on the red carpet. We don't have to fight

844
00:42:01,239 --> 00:42:04,360
Speaker 2: anymore because now I have X on my phone and

845
00:42:04,400 --> 00:42:06,400
Speaker 2: I get real time updates and he gets the TV

846
00:42:06,480 --> 00:42:07,280
Speaker 2: to white football.

847
00:42:07,360 --> 00:42:09,919
Speaker 1: Was she talking about the Golden Globes? What football game

848
00:42:10,040 --> 00:42:11,560
Speaker 1: is on Golden Globes?

849
00:42:11,560 --> 00:42:13,120
Speaker 4: Happened? Now? This is also garbage.

850
00:42:13,200 --> 00:42:14,920
Speaker 5: I was trying to I was trying to check news

851
00:42:14,960 --> 00:42:19,040
Speaker 5: the other day on Twitter X whatever they call it nowadays. Okay,

852
00:42:19,080 --> 00:42:22,279
Speaker 5: I guess, And I was just like, this is a

853
00:42:22,320 --> 00:42:23,719
Speaker 5: really bad place to get news.

854
00:42:23,840 --> 00:42:27,680
Speaker 1: Yeah, okay, pm pst. Was she really that attacked? Was

855
00:42:27,719 --> 00:42:30,080
Speaker 1: he really that attached to Monday late night football? Maybe

856
00:42:30,080 --> 00:42:34,080
Speaker 1: he does hate her, he might have been.

857
00:42:34,200 --> 00:42:37,560
Speaker 2: He's just like, h so, you know, that's the that's

858
00:42:37,600 --> 00:42:39,840
Speaker 2: like first ten minutes or so, you know, she's talking.

859
00:42:39,960 --> 00:42:42,680
Speaker 2: She talked talking about safety ad products and how there's

860
00:42:42,719 --> 00:42:45,359
Speaker 2: no surrogate for X. This is the most important place.

861
00:42:45,360 --> 00:42:49,040
Speaker 2: Talks about the NFL portal, which you know is an

862
00:42:49,080 --> 00:42:52,040
Speaker 2: example of how we are expanding the town square and

863
00:42:52,040 --> 00:42:55,719
Speaker 2: building a model that will bring to other areas of society.

864
00:42:55,760 --> 00:42:58,360
Speaker 2: They want to make us a global sports league portal

865
00:42:59,400 --> 00:43:04,400
Speaker 2: and I don't even know what that means nobody. It's provocative.

866
00:43:04,680 --> 00:43:08,799
Speaker 2: It gets the people going, you know, thirty six billion impressions,

867
00:43:08,840 --> 00:43:12,600
Speaker 2: four billion views, that's for what for the NFL portal?

868
00:43:13,920 --> 00:43:18,279
Speaker 1: That thirty six billion view the impressions, impressions, that's not

869
00:43:18,520 --> 00:43:22,839
Speaker 1: even I mean that that doesn't feel like as much

870
00:43:22,840 --> 00:43:24,920
Speaker 1: as it should like it. It feels like they had

871
00:43:25,000 --> 00:43:28,600
Speaker 1: higher numbers like that than the pospit. Also, the views

872
00:43:28,719 --> 00:43:30,600
Speaker 1: numbers are completely cracked on that.

873
00:43:30,760 --> 00:43:32,800
Speaker 2: Now, well she's saying that are the best numbers, and

874
00:43:32,800 --> 00:43:33,800
Speaker 2: they're gonna get even better.

875
00:43:34,480 --> 00:43:36,120
Speaker 1: They're gonna go to global sports leagues.

876
00:43:36,320 --> 00:43:37,879
Speaker 2: Uh. The interviewer tried to be like, do you want

877
00:43:37,880 --> 00:43:40,400
Speaker 2: to do a news or journalism portal? She was very

878
00:43:40,520 --> 00:43:42,759
Speaker 2: you know, she's like, look, look, we're not we're not.

879
00:43:43,200 --> 00:43:44,840
Speaker 2: She didn't say we're not interested in that, but she

880
00:43:44,880 --> 00:43:46,719
Speaker 2: basically was like, legacy media has.

881
00:43:46,680 --> 00:43:50,560
Speaker 1: Their own thing. We're post trusted in, yeah, telling the

882
00:43:50,680 --> 00:43:52,640
Speaker 1: truth or providing information.

883
00:43:52,960 --> 00:43:57,400
Speaker 2: We want to distinguish ourselves from legacy media because.

884
00:43:57,160 --> 00:43:59,560
Speaker 1: That legacy media, it's one way filtered.

885
00:43:59,800 --> 00:44:02,799
Speaker 2: That's a psio to control your mind and influence as

886
00:44:02,840 --> 00:44:07,480
Speaker 2: opposed to as opposed to Twitter, which is global, collective, unconscious,

887
00:44:07,719 --> 00:44:11,120
Speaker 2: right and free of influence campaigns.

888
00:44:11,400 --> 00:44:13,000
Speaker 1: Right, just.

889
00:44:15,640 --> 00:44:20,799
Speaker 2: Influence campaign right that she just mentioned when that her

890
00:44:21,000 --> 00:44:21,719
Speaker 2: boss is doing.

891
00:44:21,920 --> 00:44:25,040
Speaker 1: Yeah, and also the wasn't there a Paris Hilton one

892
00:44:25,480 --> 00:44:28,480
Speaker 1: Paris on Saudi's I mean we could list all the

893
00:44:28,480 --> 00:44:29,520
Speaker 1: influence campaigns that.

894
00:44:29,640 --> 00:44:32,319
Speaker 4: People still care about parasol. I know.

895
00:44:34,560 --> 00:44:36,719
Speaker 1: That's what's so good about it, you know, when you're

896
00:44:36,800 --> 00:44:38,480
Speaker 1: like behind crypto on a trend.

897
00:44:38,600 --> 00:44:41,560
Speaker 5: Yes, yes, Like I think the last time anyone cared

898
00:44:41,560 --> 00:44:44,040
Speaker 5: about her was when she was like eating hamburgers for

899
00:44:44,120 --> 00:44:45,200
Speaker 5: Carls Junior.

900
00:44:44,920 --> 00:44:49,400
Speaker 4: Like that, I'm not familiar with. That's pretty bad. I haven't.

901
00:44:49,480 --> 00:44:50,680
Speaker 1: I haven't been following.

902
00:44:52,640 --> 00:44:55,200
Speaker 4: The j J Abrams move fair enough.

903
00:44:56,320 --> 00:44:58,600
Speaker 2: She also talked a bit about the power of acts,

904
00:44:58,840 --> 00:45:02,239
Speaker 2: and she got really excited about the fact that one

905
00:45:02,239 --> 00:45:03,839
Speaker 2: time she was like I was scrolling through my feet,

906
00:45:03,920 --> 00:45:07,520
Speaker 2: leaned in, very excited and animated about Musk and Sundar

907
00:45:08,040 --> 00:45:13,879
Speaker 2: talking about computing the brain, the brain. Where else can

908
00:45:13,880 --> 00:45:18,040
Speaker 2: you get to executives you don't really understand?

909
00:45:19,520 --> 00:45:23,680
Speaker 1: And it's definitely them. It's what. There's no literally every executive.

910
00:45:25,000 --> 00:45:27,000
Speaker 1: You know. Here's the thing.

911
00:45:27,080 --> 00:45:30,080
Speaker 5: I refuse, I still to this day refuse to use

912
00:45:30,320 --> 00:45:32,480
Speaker 5: the term X like I will dead name.

913
00:45:32,640 --> 00:45:37,160
Speaker 1: I'm only using it here. It's just it's right, it's terrible.

914
00:45:37,840 --> 00:45:41,799
Speaker 1: It feels like petting a cat's hair the wrong way. Yeah, oh,

915
00:45:41,840 --> 00:45:44,560
Speaker 1: I'm on ex What the fuck are you talking about? Man?

916
00:45:44,560 --> 00:45:50,920
Speaker 1: Everything it's everything, the everything app that has right a

917
00:45:51,040 --> 00:45:54,680
Speaker 1: lack of utility with almost every day the racism generator

918
00:45:55,520 --> 00:45:59,840
Speaker 1: terrible grows somehow the least racist racism generation.

919
00:46:00,600 --> 00:46:01,920
Speaker 4: Like, look, I didn't, I didn't.

920
00:46:01,960 --> 00:46:04,600
Speaker 5: I didn't join the full exodus when you know, when

921
00:46:04,640 --> 00:46:06,920
Speaker 5: things so I stayed there even though I joined all

922
00:46:06,920 --> 00:46:07,520
Speaker 5: the other stuff.

923
00:46:07,880 --> 00:46:08,560
Speaker 1: But it's just.

924
00:46:08,520 --> 00:46:13,239
Speaker 5: Like like the level of narcissism is just.

925
00:46:13,160 --> 00:46:15,920
Speaker 1: To open up. As we are talking, I have not

926
00:46:16,040 --> 00:46:21,719
Speaker 1: spared today.

927
00:46:19,160 --> 00:46:22,240
Speaker 4: The world a world in an event like it's.

928
00:46:22,080 --> 00:46:24,920
Speaker 1: Gonna Yeah, I wonder what's uh, what's what's on X everything?

929
00:46:25,200 --> 00:46:27,759
Speaker 4: We start the count for you? Oh we did.

930
00:46:27,840 --> 00:46:31,480
Speaker 1: There's the thing about Samuelman's sister. Very very bad for

931
00:46:31,600 --> 00:46:32,320
Speaker 1: mister Rotman.

932
00:46:32,840 --> 00:46:35,200
Speaker 2: Oh I got some betting ads. Oh that's a bat

933
00:46:35,320 --> 00:46:37,200
Speaker 2: mgm man. Do you guys want to get up to

934
00:46:37,280 --> 00:46:39,480
Speaker 2: two hundred fifty dollars back in bonus bets if your

935
00:46:39,480 --> 00:46:40,480
Speaker 2: first wager loses?

936
00:46:40,719 --> 00:46:43,560
Speaker 4: I want that to do anything. That's why.

937
00:46:45,600 --> 00:46:50,680
Speaker 1: Okay, so he is quote it's a quote post Elon

938
00:46:50,800 --> 00:46:53,680
Speaker 1: Musk is posting where someone said Bill Gates is donated

939
00:46:53,680 --> 00:46:56,880
Speaker 1: of three. This is just a conspiracy theory thing just

940
00:46:58,239 --> 00:47:00,120
Speaker 1: and it's Elon Musk has quoted it, and he he

941
00:47:00,160 --> 00:47:02,759
Speaker 1: has used what appears to be an emoji of a

942
00:47:02,880 --> 00:47:10,040
Speaker 1: pregnant man. What so this is the richest man in life.

943
00:47:10,239 --> 00:47:14,239
Speaker 1: He could do anything. And he's like, what if what

944
00:47:14,280 --> 00:47:16,960
Speaker 1: if her? What if her Bill Gates was was a

945
00:47:16,960 --> 00:47:22,880
Speaker 1: pregnant man. Wouldn't that be funny? Great grinds, grab scramps.

946
00:47:22,920 --> 00:47:26,160
Speaker 1: It's just being in the house for years, just talking

947
00:47:26,200 --> 00:47:29,719
Speaker 1: to another person. Yeah, this I love you, don't you?

948
00:47:30,760 --> 00:47:32,120
Speaker 5: I mean I opened up the app and the first

949
00:47:32,120 --> 00:47:34,000
Speaker 5: thing I get is a nice little person from a

950
00:47:34,000 --> 00:47:36,000
Speaker 5: friend of mine who I know, and then.

951
00:47:38,760 --> 00:47:43,560
Speaker 1: It's literally post me long mask. If protecting children makes

952
00:47:43,560 --> 00:47:46,879
Speaker 1: one a fascist, then so be it. I think that, Wow,

953
00:47:47,320 --> 00:47:48,720
Speaker 1: that's you know, perfect Segway.

954
00:47:48,719 --> 00:47:50,560
Speaker 2: Also because the next things that she talked about were

955
00:47:50,560 --> 00:47:54,880
Speaker 2: the grooming gangs that he went on sweek long tiradeer

956
00:47:54,920 --> 00:47:56,799
Speaker 2: bom and she and they were like, is this a

957
00:47:56,880 --> 00:47:59,640
Speaker 2: red line? Because now you've got diplomats saying we're going

958
00:47:59,719 --> 00:48:01,719
Speaker 2: to change in the relationship with you. Ask and she

959
00:48:01,840 --> 00:48:04,640
Speaker 2: was saying, if not for X, where would the conversation

960
00:48:04,800 --> 00:48:08,680
Speaker 2: be about saving thousands of girls, bringing people to justice

961
00:48:08,680 --> 00:48:10,959
Speaker 2: who must be brought to justice. So I say, more

962
00:48:11,000 --> 00:48:11,920
Speaker 2: than did.

963
00:48:11,800 --> 00:48:14,560
Speaker 1: That happen as a result of anything that happened on X.

964
00:48:14,600 --> 00:48:14,759
Speaker 4: No?

965
00:48:15,600 --> 00:48:19,760
Speaker 2: Great, that's she said, there is going to be an inquiry.

966
00:48:21,000 --> 00:48:24,560
Speaker 1: Wow, and well there's going to be an investigation. I

967
00:48:24,680 --> 00:48:29,719
Speaker 1: have now retracted my statement. I feel like as we

968
00:48:29,880 --> 00:48:32,840
Speaker 1: as we approach the end here, I want to really

969
00:48:32,880 --> 00:48:34,880
Speaker 1: talk about something that I read about today that I

970
00:48:34,920 --> 00:48:36,960
Speaker 1: will be doing an episode on. You know, you know

971
00:48:37,120 --> 00:48:39,120
Speaker 1: that I can't help myself doing content, but we'll talk

972
00:48:39,120 --> 00:48:42,439
Speaker 1: about it today. So Mark Zuckerberg of Meta has now

973
00:48:42,880 --> 00:48:45,200
Speaker 1: basically he's fired all the fact checkers, and he's moving

974
00:48:45,200 --> 00:48:47,920
Speaker 1: the Trust and Safety people to Texas from California. Some

975
00:48:47,960 --> 00:48:50,560
Speaker 1: people saying, oh, it's because of some sort of that

976
00:48:50,600 --> 00:48:52,840
Speaker 1: one They're like, oh, it's because of labor laws. Sure,

977
00:48:52,880 --> 00:48:55,160
Speaker 1: But what that's actually about is the judges from what

978
00:48:55,200 --> 00:48:57,720
Speaker 1: I understand. But anyway, if you have not read the news,

979
00:48:58,040 --> 00:48:59,960
Speaker 1: they have fired all the fact checkers and they're saying that,

980
00:49:00,080 --> 00:49:03,080
Speaker 1: but they basically made a statement that was, oh, yeah,

981
00:49:03,120 --> 00:49:06,880
Speaker 1: we've done too much of that. And now if anyone

982
00:49:07,040 --> 00:49:10,719
Speaker 1: listening to this has opened up Facebook in the last year,

983
00:49:11,040 --> 00:49:14,640
Speaker 1: they probably did not think this could use less work,

984
00:49:15,040 --> 00:49:18,520
Speaker 1: and they definitely didn't think I am getting the good

985
00:49:18,600 --> 00:49:22,239
Speaker 1: stuff here. But on top of that, this feels to

986
00:49:22,320 --> 00:49:25,120
Speaker 1: me like the beginning of the end for META. A

987
00:49:25,120 --> 00:49:27,520
Speaker 1: lot of people are understandably it should be scared. This

988
00:49:27,560 --> 00:49:29,839
Speaker 1: is a fucking horrible thing to do. I think it's

989
00:49:29,840 --> 00:49:32,120
Speaker 1: the end of meta. I think we're actually coming toward it.

990
00:49:32,520 --> 00:49:34,840
Speaker 1: They can hope, so I hope so too. But I

991
00:49:34,880 --> 00:49:37,719
Speaker 1: think that this is that companies only do this when

992
00:49:37,719 --> 00:49:38,919
Speaker 1: they're very upset.

993
00:49:39,320 --> 00:49:42,640
Speaker 2: I mean there's also like these moves also of trying

994
00:49:42,680 --> 00:49:46,239
Speaker 2: to placate Trump. I mean, do there are a few questions, right,

995
00:49:46,280 --> 00:49:49,200
Speaker 2: because other friends are doing them, are they gonna make

996
00:49:49,239 --> 00:49:50,960
Speaker 2: the antitrust trials go away?

997
00:49:51,560 --> 00:49:52,360
Speaker 1: I don't think this.

998
00:49:53,160 --> 00:49:55,359
Speaker 2: I don't think it's related, but I'm interested in that

999
00:49:55,440 --> 00:49:57,080
Speaker 2: also as a knockdown effect, right.

1000
00:49:58,200 --> 00:50:00,640
Speaker 1: I think what people need to realize is, sure, there's

1001
00:50:00,640 --> 00:50:03,319
Speaker 1: some kissing up to Trump. Sure, but Meta has been

1002
00:50:03,360 --> 00:50:07,920
Speaker 1: helping conservatives for decades now. Yeah, you know, and they

1003
00:50:07,960 --> 00:50:11,239
Speaker 1: write calculation on the Meanwok plandemic. The thing that talked

1004
00:50:11,239 --> 00:50:16,280
Speaker 1: about the people killing Facebook episode, it's they were Joel Caplan.

1005
00:50:16,960 --> 00:50:19,360
Speaker 1: It's not Jeff Caplan. That's the Blizzard guy. Sorry, Jeff

1006
00:50:21,840 --> 00:50:24,319
Speaker 1: Jeff Caplan from a Blizzard. By the way, look up

1007
00:50:24,360 --> 00:50:27,600
Speaker 1: what the name of his his character was in EverQuest

1008
00:50:27,680 --> 00:50:29,760
Speaker 1: It was tag old Bitties. That's the guy who runs

1009
00:50:30,040 --> 00:50:32,880
Speaker 1: sick Activity. I want to slander him. Well. Also that

1010
00:50:33,000 --> 00:50:36,359
Speaker 1: is actually a truthful statement in Activision Blizzard a lot

1011
00:50:36,360 --> 00:50:39,960
Speaker 1: of weird lawsuits around anyway. Now back to Joel Kaplan,

1012
00:50:40,000 --> 00:50:42,120
Speaker 1: who is the former head of public policy who is

1013
00:50:42,160 --> 00:50:45,240
Speaker 1: now like their chief policy officer replaced Nick Klegg scam.

1014
00:50:46,400 --> 00:50:50,719
Speaker 1: But Joe Kaplan is a former GW Bush guy who

1015
00:50:50,960 --> 00:50:54,600
Speaker 1: specifically intervened to make sure that the COVID conspiracy theory

1016
00:50:54,719 --> 00:50:58,479
Speaker 1: movie Plandemic was not removed by the Health Department, which

1017
00:50:58,520 --> 00:51:01,839
Speaker 1: I now assume is just shut down. Yes, just to

1018
00:51:01,880 --> 00:51:06,880
Speaker 1: be clear, when Meta was restrained, when they were restrained

1019
00:51:06,920 --> 00:51:10,799
Speaker 1: by the boundaries, the vagaries of such ugly things as

1020
00:51:11,680 --> 00:51:16,120
Speaker 1: morals and policies, they still fucking pushed this shit. They're

1021
00:51:16,120 --> 00:51:18,560
Speaker 1: gonna do anything now and it's gonna turn it in

1022
00:51:18,920 --> 00:51:23,160
Speaker 1: to X but worse because Meta has already fucked Facebook

1023
00:51:23,200 --> 00:51:24,960
Speaker 1: for hear and back. The question is what it does

1024
00:51:25,000 --> 00:51:27,880
Speaker 1: to Instagram. I think this kills Facebook. I know it's

1025
00:51:27,880 --> 00:51:30,520
Speaker 1: gonna make Facebook even worse for a while, but it's

1026
00:51:30,560 --> 00:51:32,840
Speaker 1: gonna kill it. The content already fucking sucks.

1027
00:51:33,040 --> 00:51:35,160
Speaker 5: Wait, we already call it boomer Book. Like, so you know,

1028
00:51:35,239 --> 00:51:37,600
Speaker 5: I work with students. I mean I work with students, right,

1029
00:51:37,680 --> 00:51:40,080
Speaker 5: so I'm always I'm always in the midst.

1030
00:51:39,840 --> 00:51:41,120
Speaker 4: Of a bunch of young twenty year olds.

1031
00:51:41,560 --> 00:51:44,440
Speaker 5: Same and it's just like, yeah, as boomer Book, and

1032
00:51:44,480 --> 00:51:46,520
Speaker 5: no one goes there because it's the most toxic place

1033
00:51:46,560 --> 00:51:47,040
Speaker 5: that you can go.

1034
00:51:47,160 --> 00:51:48,040
Speaker 4: Like, it's worse than Twitter.

1035
00:51:48,120 --> 00:51:50,560
Speaker 1: Oh, you need to look for the toxicity. It's usually

1036
00:51:50,600 --> 00:51:53,719
Speaker 1: just confusing to me, but just to be clear, the

1037
00:51:53,800 --> 00:51:56,160
Speaker 1: current state of Facebook that everyone has been used to.

1038
00:51:56,520 --> 00:52:00,640
Speaker 1: This was the one with fact checkers. Yes, now it's

1039
00:52:00,640 --> 00:52:03,440
Speaker 1: gonna be like lunatic, but it's gonna be actually insane.

1040
00:52:03,440 --> 00:52:05,840
Speaker 1: But I think this might this may be the poison

1041
00:52:05,840 --> 00:52:07,120
Speaker 1: in the veins. And I know a lot of people

1042
00:52:07,160 --> 00:52:08,960
Speaker 1: understandably are very scared of this because of the right

1043
00:52:09,000 --> 00:52:11,320
Speaker 1: wing side and the fact that this is aiding the

1044
00:52:11,400 --> 00:52:13,120
Speaker 1: right wing. The only thing I can say to calm

1045
00:52:13,160 --> 00:52:16,680
Speaker 1: you down is they've already been doing that in great volumes.

1046
00:52:16,680 --> 00:52:19,759
Speaker 1: They already did this, and it's like that was this

1047
00:52:19,800 --> 00:52:24,719
Speaker 1: plus that anyway, And it's frustrating because I wish that

1048
00:52:24,960 --> 00:52:29,120
Speaker 1: was being reported alongside this part of the story. They're like, oh,

1049
00:52:29,160 --> 00:52:31,280
Speaker 1: now Facebook's going to help all the right wing people.

1050
00:52:31,800 --> 00:52:35,040
Speaker 1: They took down crowd tangle, which was a data reporting

1051
00:52:35,120 --> 00:52:40,040
Speaker 1: service that reported what the most popular pages were because sorry,

1052
00:52:40,080 --> 00:52:44,000
Speaker 1: most popular, I think it was basically, and Kevin Druce

1053
00:52:44,040 --> 00:52:46,839
Speaker 1: of the was he at the Times it's good work

1054
00:52:46,880 --> 00:52:49,719
Speaker 1: in ros Yeah, he reported this, and then they responded

1055
00:52:49,760 --> 00:52:52,799
Speaker 1: by taking down crowd Tangle. Now, the reason they did

1056
00:52:52,840 --> 00:52:55,399
Speaker 1: that was because all of the top like eight out

1057
00:52:55,400 --> 00:53:01,000
Speaker 1: of ten were always conservatives about him. Trying to analyze

1058
00:53:01,239 --> 00:53:05,359
Speaker 1: the political track of a neighbor or no, no, no,

1059
00:53:05,360 --> 00:53:08,160
Speaker 1: this was just what was most popular on Facebook. And

1060
00:53:08,200 --> 00:53:12,879
Speaker 1: it was like Ben Shapiro's show or that ship. That's

1061
00:53:12,920 --> 00:53:15,719
Speaker 1: what was happening when they gave a ship is they

1062
00:53:15,719 --> 00:53:17,439
Speaker 1: don't give a shit. They don't give a ship now.

1063
00:53:18,800 --> 00:53:21,600
Speaker 2: I mean, honestly, it's like, if I were Facebook, it's

1064
00:53:21,600 --> 00:53:27,319
Speaker 2: in your interest to at work at minimum allow for

1065
00:53:28,600 --> 00:53:31,040
Speaker 2: or try to ensure that you know, maybe right wing

1066
00:53:31,080 --> 00:53:33,719
Speaker 2: stuff is pretty popular, you know, because they'll give you

1067
00:53:33,760 --> 00:53:36,640
Speaker 2: less trouble or gluatorially. And you know, if I'm actually

1068
00:53:36,640 --> 00:53:39,040
Speaker 2: putting my foot on the pedal, you know, if I'm

1069
00:53:39,080 --> 00:53:41,920
Speaker 2: actually putting my hand on the on the on the

1070
00:53:41,920 --> 00:53:44,200
Speaker 2: tiltier or trying to you know, shift the balance, you know,

1071
00:53:44,280 --> 00:53:46,239
Speaker 2: to rev it up right. So it makes sense, right,

1072
00:53:47,120 --> 00:53:49,160
Speaker 2: it's a it's a payoff, you know, it's a payoff

1073
00:53:49,160 --> 00:53:49,400
Speaker 2: for them.

1074
00:53:49,440 --> 00:53:51,040
Speaker 1: And I think you know that.

1075
00:53:51,480 --> 00:53:53,080
Speaker 2: I think to come back to your earlier point, I

1076
00:53:53,080 --> 00:53:54,680
Speaker 2: think that's like a fair point to say, which is

1077
00:53:54,719 --> 00:53:56,719
Speaker 2: that like, yeah, you know, kissing up to Trump.

1078
00:53:56,480 --> 00:53:57,319
Speaker 1: Misses it right.

1079
00:53:57,440 --> 00:54:00,120
Speaker 2: Yeah, as you're saying that there's there's a deep for

1080
00:54:00,760 --> 00:54:04,880
Speaker 2: there's a deeper some biosis or a deeper interest there.

1081
00:54:04,960 --> 00:54:09,480
Speaker 1: That's people overlooked David. He'd be davely if Bloomberg did

1082
00:54:09,480 --> 00:54:12,200
Speaker 1: a great opinion piece to that. Lincoln the in the notes,

1083
00:54:12,920 --> 00:54:14,520
Speaker 1: he did the thing where he just says it gave

1084
00:54:14,800 --> 00:54:16,920
Speaker 1: Zuckerberg permission to give up on the thing that he

1085
00:54:16,920 --> 00:54:20,760
Speaker 1: didn't give a shit about. Yeah, somewhat paraphrasing his words there, obviously,

1086
00:54:20,800 --> 00:54:23,560
Speaker 1: because I don't think Bluembo would report that. But it's

1087
00:54:23,560 --> 00:54:25,839
Speaker 1: a great piece because it basically says, look, Zuckerberg has

1088
00:54:25,880 --> 00:54:28,759
Speaker 1: never really liked keeping care of his garden. He's never

1089
00:54:28,800 --> 00:54:32,080
Speaker 1: really taken care of his shit, So now he doesn't have.

1090
00:54:32,200 --> 00:54:33,719
Speaker 1: Now he can be like, oh, yeah, it's it's a

1091
00:54:33,719 --> 00:54:35,759
Speaker 1: political thing. This is why I'm doing it, which is

1092
00:54:35,960 --> 00:54:38,759
Speaker 1: sure it doesn't hurt its cover. It's cover for him,

1093
00:54:38,840 --> 00:54:42,120
Speaker 1: just like poor like knocking the toilet into the kitchen.

1094
00:54:42,600 --> 00:54:45,880
Speaker 1: He knows Facebook is effectively a monopoly on social media,

1095
00:54:45,960 --> 00:54:48,319
Speaker 1: so he can just fucking turn it into a ran

1096
00:54:48,400 --> 00:54:50,600
Speaker 1: successpot and thinks that people will stay. And I think

1097
00:54:50,640 --> 00:54:52,640
Speaker 1: that I was talking to Ed about this last night.

1098
00:54:52,960 --> 00:54:55,239
Speaker 1: If he was connected with the AI profiles thing. Lot

1099
00:54:55,280 --> 00:54:57,600
Speaker 1: people are understandably freaked out about But I think it

1100
00:54:57,640 --> 00:55:00,399
Speaker 1: comes down to one word contempt. It's just they don't

1101
00:55:00,480 --> 00:55:03,640
Speaker 1: fucking care. It's not about these people don't have a

1102
00:55:03,640 --> 00:55:07,160
Speaker 1: big strategy. They just I want to say evil, but

1103
00:55:07,200 --> 00:55:09,360
Speaker 1: I don't even think then that motivated. It's just growth

1104
00:55:09,440 --> 00:55:11,360
Speaker 1: all cost thinking of One of.

1105
00:55:11,360 --> 00:55:16,600
Speaker 3: The benefits for benefit relative to them is it's they

1106
00:55:16,640 --> 00:55:19,080
Speaker 3: don't have monopoly, but they do have a walled garden,

1107
00:55:19,320 --> 00:55:21,720
Speaker 3: so they can do whatever they want inside of their garden.

1108
00:55:22,360 --> 00:55:26,080
Speaker 3: And if you want to bury toxic waste in your garden,

1109
00:55:26,360 --> 00:55:29,160
Speaker 3: well there are regulations about that, but we're.

1110
00:55:29,000 --> 00:55:30,200
Speaker 1: Going to stop them from doing it.

1111
00:55:30,440 --> 00:55:31,040
Speaker 4: Yeah, exactly.

1112
00:55:31,080 --> 00:55:33,400
Speaker 5: I mean like I mean, if Facebook started as a

1113
00:55:33,400 --> 00:55:35,799
Speaker 5: place for a work to get a date, you know,

1114
00:55:35,880 --> 00:55:37,960
Speaker 5: and so I'm sorry.

1115
00:55:37,719 --> 00:55:38,319
Speaker 4: You don't like that.

1116
00:55:39,800 --> 00:55:43,320
Speaker 1: I feel like that point misses the problem again because yes,

1117
00:55:43,360 --> 00:55:46,239
Speaker 1: technically that was like the whole horny Harvard guy thing.

1118
00:55:47,280 --> 00:55:50,719
Speaker 1: The thing is is that that wasn't where that was

1119
00:55:50,760 --> 00:55:53,000
Speaker 1: an evil thing that a college student did. Where it

1120
00:55:53,040 --> 00:55:55,920
Speaker 1: became an evil thing that an adult started doing. Was

1121
00:55:56,000 --> 00:55:59,320
Speaker 1: the idea of Facebook, was the idea of growing Facebook.

1122
00:55:59,320 --> 00:56:02,160
Speaker 1: And what growing Facebook? Men, if we start with that,

1123
00:56:02,280 --> 00:56:05,319
Speaker 1: if we reduce him to this horny in cell. Kid,

1124
00:56:05,600 --> 00:56:08,239
Speaker 1: we miss the thing that this guy is, like Zuckerberg,

1125
00:56:08,360 --> 00:56:11,720
Speaker 1: is something so much worse than that. He is someone

1126
00:56:11,719 --> 00:56:15,360
Speaker 1: who truly does not care. I'm not gonna say sociopath

1127
00:56:15,400 --> 00:56:18,040
Speaker 1: because I actually really don't know the exact definition. I

1128
00:56:18,040 --> 00:56:20,439
Speaker 1: think just describing it in blunt terms is does someone

1129
00:56:20,440 --> 00:56:23,719
Speaker 1: who give a shit about anything do this? Yeah? Because

1130
00:56:23,760 --> 00:56:26,200
Speaker 1: it doesn't even feel like a political move. He's just like, great,

1131
00:56:26,239 --> 00:56:29,800
Speaker 1: I don't have to. It feels like a regulation being removed,

1132
00:56:29,840 --> 00:56:32,400
Speaker 1: he doesn't think, because there really isn't regulations.

1133
00:56:32,280 --> 00:56:33,560
Speaker 3: Kid, Yeah, there wasn't one.

1134
00:56:34,680 --> 00:56:37,360
Speaker 1: It's it's really good looking out of the window with

1135
00:56:37,440 --> 00:56:39,960
Speaker 1: the tech industry right now. I feel very positive.

1136
00:56:40,160 --> 00:56:42,720
Speaker 2: That's just how it felt to be drinking the water

1137
00:56:42,880 --> 00:56:44,640
Speaker 2: downstream of the chip fabs.

1138
00:56:44,800 --> 00:56:50,800
Speaker 1: Yeah. Great, except it's fantastic except that hurt lesbian.

1139
00:56:51,520 --> 00:56:52,360
Speaker 3: Thanks for getting.

1140
00:56:54,960 --> 00:56:57,400
Speaker 5: But no, there's a cynicism, right right, there's a cynicism

1141
00:56:57,440 --> 00:57:01,520
Speaker 5: about the whole thing. And so it's like, you know, people,

1142
00:57:01,719 --> 00:57:03,640
Speaker 5: people just out there in the world sort of use

1143
00:57:03,680 --> 00:57:06,360
Speaker 5: these things, you know, to stay connected to their families,

1144
00:57:06,400 --> 00:57:08,120
Speaker 5: you know, like, for instance, the only reason why I

1145
00:57:08,160 --> 00:57:11,360
Speaker 5: still have a Facebook, you know, account, is because you like,

1146
00:57:11,400 --> 00:57:13,640
Speaker 5: my mom takes photos, right, and I see that.

1147
00:57:13,600 --> 00:57:15,600
Speaker 1: And I use Instagram because there are some people who

1148
00:57:15,600 --> 00:57:16,560
Speaker 1: don't use anything else.

1149
00:57:16,800 --> 00:57:18,000
Speaker 4: Yeah, exactly the same thing.

1150
00:57:18,480 --> 00:57:21,040
Speaker 5: And uh and so that's I think that so many

1151
00:57:21,040 --> 00:57:23,520
Speaker 5: people like that's that's sort of their general sort of

1152
00:57:23,760 --> 00:57:29,280
Speaker 5: use case, that that these more sort of problematic aspects.

1153
00:57:29,920 --> 00:57:32,480
Speaker 5: They have a hard time seeing what the problem is.

1154
00:57:32,520 --> 00:57:36,840
Speaker 5: But but the problem really is just this, this this cynicism,

1155
00:57:36,880 --> 00:57:39,280
Speaker 5: the lack of care, the I think I think you

1156
00:57:39,640 --> 00:57:40,880
Speaker 5: think you hit to right on the head.

1157
00:57:40,920 --> 00:57:45,480
Speaker 1: You ain't seen nothing yet. I'm deadly serious like Facebook.

1158
00:57:45,800 --> 00:57:47,920
Speaker 1: So shout out to Jeff Howitz. The Wall Street Journals

1159
00:57:48,320 --> 00:57:49,920
Speaker 1: taught me a lot, a lot about what I know

1160
00:57:49,920 --> 00:57:53,120
Speaker 1: about Facebook. I have yet to hear from Jeff if

1161
00:57:53,160 --> 00:57:54,880
Speaker 1: he was at CS to be so happy. There's no

1162
00:57:54,960 --> 00:57:58,000
Speaker 1: one I want more on the chat just going fucking

1163
00:57:58,480 --> 00:58:02,800
Speaker 1: And the thing is is that they've always been this bad.

1164
00:58:03,720 --> 00:58:07,160
Speaker 1: And as we write history right now, we're like, well, now,

1165
00:58:07,280 --> 00:58:09,960
Speaker 1: Facebook book, this is the day that meta became evil

1166
00:58:09,960 --> 00:58:13,560
Speaker 1: and it's like always but if you do, if you

1167
00:58:13,760 --> 00:58:17,760
Speaker 1: failed to actually counch it in time, imagine what they'll

1168
00:58:17,760 --> 00:58:18,240
Speaker 1: do next.

1169
00:58:19,080 --> 00:58:24,720
Speaker 2: Yeah, yeah, I mean, hey, like you know, what where

1170
00:58:24,720 --> 00:58:28,240
Speaker 2: do you go from? You know, facilitating a genocida you.

1171
00:58:28,160 --> 00:58:30,560
Speaker 4: Know, where do you go? You know?

1172
00:58:30,960 --> 00:58:34,200
Speaker 1: You all things are justified in growth. A terrorist attack

1173
00:58:34,280 --> 00:58:37,520
Speaker 1: plan on Facebook was justified in growth. I'm quoting Andrew

1174
00:58:37,560 --> 00:58:41,560
Speaker 1: Bossworth in the Ugly Letter. He is now the CTO

1175
00:58:41,640 --> 00:58:47,320
Speaker 1: of Meta. Very cool, very good stuff. So as we

1176
00:58:47,480 --> 00:58:49,840
Speaker 1: come towards the end of the this part of the episode,

1177
00:58:49,840 --> 00:58:52,400
Speaker 1: we're shortly going to be updated with Gara Davis and

1178
00:58:52,480 --> 00:58:54,840
Speaker 1: Robert Evans of course as a wrap.

1179
00:58:54,680 --> 00:58:57,040
Speaker 3: Up, especially because I'm almost out of cocktail.

1180
00:58:56,680 --> 00:58:58,760
Speaker 5: He's almost out of and I'm thinking about the Facebook

1181
00:58:58,840 --> 00:58:59,680
Speaker 5: leaks at the moment.

1182
00:58:59,760 --> 00:59:03,040
Speaker 1: But yes, well, I think, as we come to the

1183
00:59:03,160 --> 00:59:07,080
Speaker 1: end of this day, and did you like anything? Was

1184
00:59:07,120 --> 00:59:09,200
Speaker 1: there a single thing that you saw? And there is

1185
00:59:09,240 --> 00:59:11,640
Speaker 1: no wrong answer here. If you saw something you liked,

1186
00:59:11,680 --> 00:59:17,600
Speaker 1: what was it? And don't say the exit the sex

1187
00:59:17,720 --> 00:59:25,040
Speaker 1: toys seemed neat cool, So it's just fun.

1188
00:59:26,080 --> 00:59:28,440
Speaker 4: I think every ces this is what I've heard, and

1189
00:59:28,480 --> 00:59:30,160
Speaker 4: that's it. Horrified by that.

1190
00:59:30,920 --> 00:59:32,800
Speaker 1: Woke up, just cracking up, all right.

1191
00:59:33,240 --> 00:59:37,520
Speaker 2: You know the I saw some screens that looked crazy,

1192
00:59:37,760 --> 00:59:39,959
Speaker 2: But you know, I don't game like that, I don't

1193
00:59:40,000 --> 00:59:47,560
Speaker 2: goon like that, Like I just I couldn't you know

1194
00:59:47,640 --> 00:59:54,080
Speaker 2: those are really for me. Every episode you know, I'm

1195
00:59:54,480 --> 00:59:55,400
Speaker 2: I'm gonna watch.

1196
00:59:55,920 --> 00:59:56,280
Speaker 1: I don't know.

1197
00:59:56,320 --> 00:59:58,080
Speaker 2: I feel like maybe I would have liked a sphere

1198
00:59:58,440 --> 00:59:59,640
Speaker 2: you know whatever doing.

1199
01:00:00,120 --> 01:00:03,000
Speaker 1: No Lenny Kravitz is there tonight. Oh I forgot to

1200
01:00:03,040 --> 01:00:05,439
Speaker 1: mention an important part of the things. So I found

1201
01:00:05,480 --> 01:00:09,840
Speaker 1: out a competing podcast called The Verge. I hear they

1202
01:00:09,840 --> 01:00:12,720
Speaker 1: are currently doing. Heard of them, haven't either, but I

1203
01:00:12,800 --> 01:00:16,640
Speaker 1: just the ridge the French you doing like a little

1204
01:00:16,680 --> 01:00:19,680
Speaker 1: German over had a hairball.

1205
01:00:21,120 --> 01:00:23,360
Speaker 4: Somewhere right, and here we go.

1206
01:00:23,640 --> 01:00:25,960
Speaker 1: I try not to be a catty bitch other than

1207
01:00:26,400 --> 01:00:30,680
Speaker 1: everyone this show. And I must say that I was seeing.

1208
01:00:30,800 --> 01:00:32,440
Speaker 1: I definitely saw this, and there was a moment I

1209
01:00:32,480 --> 01:00:36,240
Speaker 1: was like, oh man, another podcast recording out of here,

1210
01:00:36,560 --> 01:00:39,080
Speaker 1: big one too. I should go and check out what

1211
01:00:39,120 --> 01:00:44,040
Speaker 1: they're doing before the Verge podcast. And by the way,

1212
01:00:44,080 --> 01:00:46,160
Speaker 1: you can only see the Verge cast live if you

1213
01:00:46,240 --> 01:00:50,760
Speaker 1: have a Delta sky Miles membership, and it features a

1214
01:00:50,800 --> 01:00:53,560
Speaker 1: pre podcast panel discussion about the future of travel between

1215
01:00:53,600 --> 01:00:57,120
Speaker 1: the Virgin Delta's Dwhite James SVP customer engagement and loyalty

1216
01:00:57,160 --> 01:01:00,680
Speaker 1: in CEO Delta Voi Vacations probably could have not fucked

1217
01:01:00,760 --> 01:01:02,240
Speaker 1: up with the words there if I wanted to make

1218
01:01:02,240 --> 01:01:05,320
Speaker 1: fun of it. But I just want to say I

1219
01:01:05,360 --> 01:01:08,080
Speaker 1: get a lot of ship on my ads for this show.

1220
01:01:08,360 --> 01:01:09,920
Speaker 1: I didn't do a single ad break as well, so

1221
01:01:09,920 --> 01:01:13,240
Speaker 1: you're gonna be really pissed with me. I will never

1222
01:01:13,400 --> 01:01:16,760
Speaker 1: interview someone from Delta Airlines unless it's the CEO and

1223
01:01:16,840 --> 01:01:20,040
Speaker 1: I'm screaming at them that And also what the fuck

1224
01:01:20,040 --> 01:01:21,680
Speaker 1: does that have to do with tech? But also I

1225
01:01:21,760 --> 01:01:24,200
Speaker 1: understand we've got to get money, honey, but like Jesus Christ,

1226
01:01:24,280 --> 01:01:25,480
Speaker 1: that's your big the.

1227
01:01:25,480 --> 01:01:29,920
Speaker 2: Future of travel unless it's no more Boeing planes, cigarettes

1228
01:01:29,960 --> 01:01:33,040
Speaker 2: on the plane and bigger seats, I don't want to

1229
01:01:33,080 --> 01:01:33,440
Speaker 2: hear it.

1230
01:01:33,760 --> 01:01:35,440
Speaker 4: But also.

1231
01:01:36,480 --> 01:01:37,520
Speaker 1: Because what is it going to be?

1232
01:01:37,760 --> 01:01:40,560
Speaker 2: We we we calibrated the formula for sky Miles.

1233
01:01:40,640 --> 01:01:43,680
Speaker 1: Yeah, we we changed the app. You have made it

1234
01:01:43,760 --> 01:01:46,680
Speaker 1: harder to get sky Miles status.

1235
01:01:46,720 --> 01:01:48,880
Speaker 3: Smart planes smart.

1236
01:01:50,120 --> 01:01:51,680
Speaker 4: All all the planes are on the blockchain.

1237
01:01:52,160 --> 01:01:56,120
Speaker 1: Anyway, I think you have had a much better experience

1238
01:01:56,240 --> 01:01:59,800
Speaker 1: with a health physicist and a priest, So I think

1239
01:01:59,800 --> 01:02:02,240
Speaker 1: that that's my choice. So more members of the clergy

1240
01:02:02,280 --> 01:02:05,560
Speaker 1: and more safety professionals. I think that's what makes up.

1241
01:02:05,560 --> 01:02:08,720
Speaker 3: Generally more safety professionals is not what anyone wants to see,

1242
01:02:08,960 --> 01:02:13,680
Speaker 3: because we apparently ruin fun.

1243
01:02:13,280 --> 01:02:17,200
Speaker 5: Sometimes apparently, so we as we close out of this

1244
01:02:17,240 --> 01:02:18,720
Speaker 5: part of the episode and will of course be back

1245
01:02:18,760 --> 01:02:19,560
Speaker 5: shortly after this.

1246
01:02:20,200 --> 01:02:21,880
Speaker 1: Phil Where can people find you?

1247
01:02:21,880 --> 01:02:24,400
Speaker 3: You can find me at Blue Sky at at Fundranium,

1248
01:02:24,520 --> 01:02:27,560
Speaker 3: and you can find my blog Funderanium Labs dot com.

1249
01:02:28,200 --> 01:02:30,560
Speaker 1: Yes, and he makes a special kind of coffee. And

1250
01:02:30,600 --> 01:02:32,840
Speaker 1: if you look on Blue Sky, because I cannot advertise

1251
01:02:32,880 --> 01:02:34,480
Speaker 1: things on here, I will have a link for you

1252
01:02:34,520 --> 01:02:37,200
Speaker 1: at some point that we'll do something. I'm not even

1253
01:02:37,240 --> 01:02:39,720
Speaker 1: going to say what it is. Ed m Graso Junior.

1254
01:02:39,840 --> 01:02:41,440
Speaker 1: Now that I cut you off at the beginning of

1255
01:02:41,480 --> 01:02:43,720
Speaker 1: that saying what you did? What do you do?

1256
01:02:44,160 --> 01:02:49,360
Speaker 2: I'm I'm a tech writer, a finance writer, a labor writer,

1257
01:02:50,080 --> 01:02:54,280
Speaker 2: an editor, a ship poster, a sign.

1258
01:02:56,720 --> 01:02:57,760
Speaker 1: As the son of a mother.

1259
01:02:57,960 --> 01:02:59,880
Speaker 2: Yeah, I'm a son of a mother and the father

1260
01:03:00,160 --> 01:03:02,720
Speaker 2: of cats were baby monitored.

1261
01:03:02,920 --> 01:03:07,240
Speaker 1: Yeah, yeah, you have yet to give a link. That's true.

1262
01:03:07,360 --> 01:03:08,720
Speaker 2: I thought you were going to say to my cats,

1263
01:03:08,760 --> 01:03:11,560
Speaker 2: and I was like, they're they're on my profiles, Big

1264
01:03:11,600 --> 01:03:16,280
Speaker 2: Black Jacobin on Blue Sky and uh Twitter.

1265
01:03:16,360 --> 01:03:21,400
Speaker 1: Thanks to everything that too. And this Maschione Kills is

1266
01:03:21,440 --> 01:03:24,640
Speaker 1: the podcast where we yap about the political economy of

1267
01:03:24,640 --> 01:03:27,880
Speaker 1: tech and uh the tech bubbles my newsletter where I

1268
01:03:28,080 --> 01:03:31,040
Speaker 1: yap about tech. Also where can they find that tech

1269
01:03:31,080 --> 01:03:34,080
Speaker 1: bubble dot substack dot com? And wrote to that and

1270
01:03:34,160 --> 01:03:38,000
Speaker 1: father Gabriel Mosha.

1271
01:03:36,520 --> 01:03:37,000
Speaker 4: Yeah, mosha.

1272
01:03:37,240 --> 01:03:39,880
Speaker 5: I mean these days, these days, just on all the

1273
01:03:39,920 --> 01:03:44,520
Speaker 5: social media's in the same Okay, they do not fucking.

1274
01:03:44,600 --> 01:03:48,520
Speaker 1: Mm every None of these people know their links. Your

1275
01:03:48,600 --> 01:03:51,480
Speaker 1: name is like luky something like if they type in

1276
01:03:51,520 --> 01:03:53,080
Speaker 1: your name, it doesn't come up. Sometimes.

1277
01:03:53,120 --> 01:03:54,840
Speaker 4: Oh uk e I four six y five.

1278
01:03:54,960 --> 01:03:58,520
Speaker 5: That's on everything except for blue Sky, Blue Sky it's

1279
01:03:58,520 --> 01:03:58,960
Speaker 5: eighth way.

1280
01:03:59,200 --> 01:04:01,880
Speaker 1: Well thank god you specified that before I said anything.

1281
01:04:02,560 --> 01:04:04,800
Speaker 4: Yeah, no, or you can just put in like if

1282
01:04:04,840 --> 01:04:06,360
Speaker 4: you just search Gabriel.

1283
01:04:06,040 --> 01:04:08,760
Speaker 1: Moser's like priest into Google.

1284
01:04:08,480 --> 01:04:09,120
Speaker 4: Then I'm there.

1285
01:04:09,800 --> 01:04:13,320
Speaker 1: Well when will be right back? After these amazing products.

1286
01:04:13,320 --> 01:04:16,160
Speaker 1: You're gonna hear about these products. They're so beautiful. I

1287
01:04:16,200 --> 01:04:19,680
Speaker 1: personally love them all. They're definitely not going to immediately

1288
01:04:19,720 --> 01:04:22,200
Speaker 1: embarrass me in a way that every week I get

1289
01:04:22,280 --> 01:04:27,520
Speaker 1: one email from one guy who's like, this does not

1290
01:04:27,960 --> 01:04:29,800
Speaker 1: match up with the things you were saying.

1291
01:04:29,840 --> 01:04:33,040
Speaker 3: We're here to embarrass you.

1292
01:04:33,080 --> 01:04:36,440
Speaker 1: Did you know that there is a commercial a commercial

1293
01:04:36,520 --> 01:04:40,320
Speaker 1: that came on that was not in line with your beliefs.

1294
01:04:41,560 --> 01:04:45,200
Speaker 1: What do you think? No noster around and every time

1295
01:04:45,240 --> 01:04:47,640
Speaker 1: I respond with the same thing, which is, I bet

1296
01:04:47,680 --> 01:04:52,040
Speaker 1: you'd love it if I died, and then I hit send. Anyway,

1297
01:04:52,160 --> 01:05:06,480
Speaker 1: the next thing that comes up maybe by it. And

1298
01:05:06,520 --> 01:05:08,800
Speaker 1: we're back and we've replaced some of the people. We've

1299
01:05:08,800 --> 01:05:11,800
Speaker 1: got Gare Davis and of course Robert Evans from It

1300
01:05:11,800 --> 01:05:15,920
Speaker 1: could happen here, and they are just glowing from the

1301
01:05:16,000 --> 01:05:16,800
Speaker 1: time on the floor.

1302
01:05:16,880 --> 01:05:19,160
Speaker 9: Yeah, I'm happy to be here. I'm kind of concerned

1303
01:05:19,160 --> 01:05:22,240
Speaker 9: that the former panelists you took out and forced into

1304
01:05:22,240 --> 01:05:24,720
Speaker 9: a goolag outside of nov garad like that. That seems

1305
01:05:24,760 --> 01:05:25,720
Speaker 9: a little extreme.

1306
01:05:25,600 --> 01:05:28,120
Speaker 1: But I don't want to question. That is your show business.

1307
01:05:28,200 --> 01:05:31,600
Speaker 1: This is your show. That's show business. That's I'm glad

1308
01:05:31,640 --> 01:05:35,640
Speaker 1: you made the cut, you know. Yeah, we have to

1309
01:05:35,680 --> 01:05:38,400
Speaker 1: have two ads, at least one of the chosen.

1310
01:05:38,400 --> 01:05:38,880
Speaker 4: Always to.

1311
01:05:41,520 --> 01:05:47,960
Speaker 1: Want to crave the mind. Oh god, I'm going to

1312
01:05:48,000 --> 01:05:51,440
Speaker 1: be thinking about that all evening now. That's great. So

1313
01:05:52,160 --> 01:05:55,680
Speaker 1: we were previously talking about the Linda Yakarino speech. Oh

1314
01:05:55,720 --> 01:05:57,680
Speaker 1: my god, and I did not know that Gare was

1315
01:05:57,720 --> 01:06:00,880
Speaker 1: also that gay. What was your experience of the uh,

1316
01:06:02,040 --> 01:06:04,080
Speaker 1: the matriarch of social media.

1317
01:06:04,200 --> 01:06:07,800
Speaker 6: It's the first time there was applause was when she

1318
01:06:07,880 --> 01:06:12,280
Speaker 6: mentioned Doge. The second time was the rape gigs. So

1319
01:06:13,080 --> 01:06:14,520
Speaker 6: incredible vibes happening.

1320
01:06:14,600 --> 01:06:16,440
Speaker 9: Audiences love Dojian rape gangs.

1321
01:06:16,520 --> 01:06:19,320
Speaker 1: You know. But what's so, what specifically was this rape

1322
01:06:19,320 --> 01:06:21,920
Speaker 1: gang thing? I should know about things that happened in England,

1323
01:06:21,960 --> 01:06:23,880
Speaker 1: but I've been running from England my whole life.

1324
01:06:24,280 --> 01:06:26,880
Speaker 9: Well, there was like a kind of a bit of

1325
01:06:26,920 --> 01:06:30,200
Speaker 9: a bit of a program over the earlier last year,

1326
01:06:30,480 --> 01:06:33,720
Speaker 9: over over the idea that there were like migrants were

1327
01:06:33,760 --> 01:06:36,800
Speaker 9: running rape gangs, and so people started like we were

1328
01:06:36,800 --> 01:06:39,600
Speaker 9: like right wing riots in several cities, including like.

1329
01:06:39,840 --> 01:06:43,400
Speaker 1: Oh, sorry, this is the thing that actually fucking caused that.

1330
01:06:43,680 --> 01:06:46,080
Speaker 9: Well this was no, no, this didn't cause that, but

1331
01:06:46,200 --> 01:06:48,760
Speaker 9: causes an extension. This was trying to keep it going.

1332
01:06:49,280 --> 01:06:52,600
Speaker 1: Yeah, oh yeah, sorry, I meant it. Yeah, that right

1333
01:06:52,640 --> 01:06:56,200
Speaker 1: wing ship storm was what caused the riots. Okay, great,

1334
01:06:56,320 --> 01:06:59,360
Speaker 1: because I knew the riots were happening. And then we've

1335
01:06:59,360 --> 01:07:01,640
Speaker 1: got very upset with the amount of racis in the

1336
01:07:01,680 --> 01:07:04,560
Speaker 1: England that newly created, considering it's England and has quite

1337
01:07:04,560 --> 01:07:07,920
Speaker 1: a lot already. Yeah, oh god, anyway, So that was

1338
01:07:08,280 --> 01:07:09,280
Speaker 1: that got applause.

1339
01:07:10,160 --> 01:07:13,760
Speaker 6: Yeah, talking about that and and how how important it

1340
01:07:13,840 --> 01:07:17,439
Speaker 6: is on X to protect children and as a mother,

1341
01:07:17,800 --> 01:07:22,240
Speaker 6: it's very it is especially important. So and we need

1342
01:07:23,200 --> 01:07:25,480
Speaker 6: we need more more posting to save the children.

1343
01:07:25,720 --> 01:07:27,920
Speaker 1: I mean that I agree with just the posting part.

1344
01:07:28,160 --> 01:07:29,600
Speaker 1: All things are possible posting.

1345
01:07:29,640 --> 01:07:30,880
Speaker 9: I mean, one of the last times I was on

1346
01:07:31,120 --> 01:07:33,320
Speaker 9: X the everything app, I saw a deep fake porn

1347
01:07:33,400 --> 01:07:37,200
Speaker 9: of an eighteen year old. So yeah, I only I can.

1348
01:07:37,480 --> 01:07:40,040
Speaker 9: I really do feel what she says that very is

1349
01:07:40,040 --> 01:07:40,840
Speaker 9: deeply committed.

1350
01:07:41,200 --> 01:07:43,360
Speaker 6: The last time, the last time I spent a decent

1351
01:07:43,360 --> 01:07:45,520
Speaker 6: amount of time on X, it was after a teenager

1352
01:07:45,600 --> 01:07:48,480
Speaker 6: did a mass shooting and I had to talk to

1353
01:07:48,520 --> 01:07:51,920
Speaker 6: all of their other teen friend nazis who are on

1354
01:07:52,160 --> 01:07:55,520
Speaker 6: X and they everything app everything, they communications, and that's

1355
01:07:55,560 --> 01:07:57,880
Speaker 6: where you find them, a whole bunch of teenage Nazis

1356
01:07:57,920 --> 01:07:59,880
Speaker 6: who had all just like talked, like talk to each

1357
01:07:59,880 --> 01:08:02,280
Speaker 6: other there and share phrenology memes.

1358
01:08:02,480 --> 01:08:07,920
Speaker 1: Oh yeah, what's that girl's name like that? There's like some.

1359
01:08:10,160 --> 01:08:14,760
Speaker 2: Rad fam Hitler the name on the one of my

1360
01:08:14,800 --> 01:08:15,800
Speaker 2: favorite podcasts.

1361
01:08:16,320 --> 01:08:18,320
Speaker 9: We're having her on the show very very soon to

1362
01:08:18,360 --> 01:08:20,519
Speaker 9: talk about the other Hitler yeah, I'm calling it the

1363
01:08:20,560 --> 01:08:21,240
Speaker 9: two Hitlers.

1364
01:08:21,400 --> 01:08:23,519
Speaker 1: When seeing that name, I was like, I can't believe

1365
01:08:23,520 --> 01:08:26,920
Speaker 1: this exists. Of course this exists. Well I love talking

1366
01:08:26,960 --> 01:08:31,880
Speaker 1: about technology. Yeah, so that was but that What was

1367
01:08:31,880 --> 01:08:33,960
Speaker 1: the context for the doge thing as well? Was it

1368
01:08:34,080 --> 01:08:35,800
Speaker 1: just the idea of firing people? Know?

1369
01:08:36,040 --> 01:08:38,880
Speaker 6: It was was talking about like how important X will

1370
01:08:38,920 --> 01:08:44,519
Speaker 6: be as Elon and and focuses on doge in the

1371
01:08:44,560 --> 01:08:47,439
Speaker 6: next year for a government program, so you like, you know,

1372
01:08:47,479 --> 01:08:51,480
Speaker 6: well it's a fake a fake government, like a consultancy

1373
01:08:51,520 --> 01:08:54,080
Speaker 6: service that pretends to be a government but like it.

1374
01:08:54,080 --> 01:08:56,320
Speaker 6: It was basically a quick question about like like how

1375
01:08:56,400 --> 01:08:58,599
Speaker 6: much will Elon be using like X to like, you know,

1376
01:08:59,000 --> 01:09:03,439
Speaker 6: get like people, Like how much will he be getting

1377
01:09:03,439 --> 01:09:05,960
Speaker 6: like users to give suggestions for things to cut you know?

1378
01:09:06,360 --> 01:09:10,280
Speaker 1: Oh god? Open source government regulation? Sure, I mean open

1379
01:09:10,320 --> 01:09:13,280
Speaker 1: source works. Yeah, yes, but.

1380
01:09:13,520 --> 01:09:19,160
Speaker 9: Yes, look think about Linux, right stable operating system run

1381
01:09:19,200 --> 01:09:20,920
Speaker 9: by a guy who's only committed.

1382
01:09:20,520 --> 01:09:21,519
Speaker 1: A few sex crimes.

1383
01:09:22,320 --> 01:09:24,920
Speaker 9: We all love Linux. Why shouldn't the government be that way?

1384
01:09:24,960 --> 01:09:27,639
Speaker 9: It's already run by guys who commit sex crimes. Right

1385
01:09:28,280 --> 01:09:30,479
Speaker 9: match made in Heaven. It was much like I'm not

1386
01:09:30,479 --> 01:09:30,880
Speaker 9: trying to.

1387
01:09:31,560 --> 01:09:36,320
Speaker 1: Oh, I am much like Linux it's way more complicated

1388
01:09:36,400 --> 01:09:40,000
Speaker 1: than they describe as. Oh yeah, and and and in

1389
01:09:40,040 --> 01:09:42,120
Speaker 1: the end, it only works for a few people and

1390
01:09:42,160 --> 01:09:43,560
Speaker 1: they can barely explain.

1391
01:09:43,240 --> 01:09:46,680
Speaker 9: Why, but their computers are unhackable because honestly, if you're

1392
01:09:46,720 --> 01:09:50,080
Speaker 9: if you're hacking ship, nobody, nobody needs that.

1393
01:09:50,080 --> 01:09:52,040
Speaker 1: That's really good. I'm glad you end that bit because

1394
01:09:52,040 --> 01:09:54,640
Speaker 1: we've now said several things that Linux fans are going

1395
01:09:54,680 --> 01:09:56,559
Speaker 1: to email me about.

1396
01:09:55,600 --> 01:09:59,200
Speaker 9: It's the most secure to way to do things, the

1397
01:09:59,200 --> 01:10:01,960
Speaker 9: same way that invent your own language and losing the

1398
01:10:02,000 --> 01:10:04,040
Speaker 9: ability to communicate with the rest of the world is

1399
01:10:04,080 --> 01:10:06,519
Speaker 9: the most efficient way to avoid getting spied on.

1400
01:10:06,720 --> 01:10:10,879
Speaker 1: Right, kind of like trying to use another Apple Linux. Yeah, yeah, exactly.

1401
01:10:11,280 --> 01:10:15,280
Speaker 1: I said something about Linux, like I wrote this newsletter

1402
01:10:15,600 --> 01:10:18,240
Speaker 1: and turned into a script as well where I talked

1403
01:10:18,240 --> 01:10:20,439
Speaker 1: about and I've talked about all sorts of things and

1404
01:10:20,520 --> 01:10:23,880
Speaker 1: rotten with intech and I quote tweeted it quote post

1405
01:10:23,920 --> 01:10:25,719
Speaker 1: of them blue Sky, I should say, and I said,

1406
01:10:25,880 --> 01:10:29,400
Speaker 1: just to be clear, stop recommending me Linux. Normal people

1407
01:10:29,520 --> 01:10:33,120
Speaker 1: don't use Linux. And it was like fifty percent hardcore

1408
01:10:33,160 --> 01:10:36,080
Speaker 1: Linux people being like, you're completely right, man, like this

1409
01:10:36,080 --> 01:10:41,320
Speaker 1: shit's this shit's because being like I will fucking kill you.

1410
01:10:41,880 --> 01:10:42,320
Speaker 4: I will.

1411
01:10:42,360 --> 01:10:45,880
Speaker 9: Actually it is, there's no Linux guys are exactly the

1412
01:10:45,920 --> 01:10:49,479
Speaker 9: same as like Norse pagans in the modern world, where

1413
01:10:49,520 --> 01:10:52,559
Speaker 9: half of them are like the chillest like like and

1414
01:10:52,680 --> 01:10:56,880
Speaker 9: violently anti racist, will literally fucking die to like fight

1415
01:10:56,920 --> 01:10:59,960
Speaker 9: a Nazi, and half of them are just the absolute fact,

1416
01:11:00,200 --> 01:11:04,280
Speaker 9: just diesel apple like like the bioless.

1417
01:11:04,320 --> 01:11:06,040
Speaker 1: So we're also calling them back.

1418
01:11:06,360 --> 01:11:09,160
Speaker 9: Linux people are either will let the drop of the hat,

1419
01:11:09,280 --> 01:11:11,880
Speaker 9: like like put down everything in order to like help

1420
01:11:11,920 --> 01:11:14,680
Speaker 9: you secure your phone to stop the FBI from getting in,

1421
01:11:14,960 --> 01:11:17,800
Speaker 9: and half people whose primary goal in life is to

1422
01:11:17,840 --> 01:11:21,320
Speaker 9: reform the age of consent to be lower, just to.

1423
01:11:21,280 --> 01:11:26,320
Speaker 1: Be close to thing Linux fans, I please. That was

1424
01:11:26,400 --> 01:11:27,599
Speaker 1: like two fucking weeks.

1425
01:11:27,760 --> 01:11:29,519
Speaker 9: I see all the people listening to this are the

1426
01:11:29,520 --> 01:11:30,639
Speaker 9: first kind of Linux.

1427
01:11:30,680 --> 01:11:34,679
Speaker 1: Yeah, that's what I'm saying. They all are, mm hmm

1428
01:11:35,479 --> 01:11:39,360
Speaker 1: yeah great, still going to get one hundred emails. Yeah.

1429
01:11:39,400 --> 01:11:39,519
Speaker 4: So.

1430
01:11:39,880 --> 01:11:43,439
Speaker 1: But otherwise, so there was no applause at all during this.

1431
01:11:43,479 --> 01:11:46,439
Speaker 6: Otherwise it was just for the mention of doge and

1432
01:11:46,479 --> 01:11:47,960
Speaker 6: then for the rape gains.

1433
01:11:48,439 --> 01:11:50,920
Speaker 1: Otherwise you just kind of they.

1434
01:11:50,800 --> 01:11:53,200
Speaker 6: Were just talking for thirty minutes and like the biggest

1435
01:11:53,240 --> 01:11:57,280
Speaker 6: point of this discussion was basically laying out how in

1436
01:11:57,400 --> 01:12:01,840
Speaker 6: tendem X and the everything appen and and the new

1437
01:12:01,880 --> 01:12:03,599
Speaker 6: Trump administration are going to function out.

1438
01:12:03,600 --> 01:12:04,799
Speaker 1: It's basically like trying to view.

1439
01:12:04,640 --> 01:12:07,679
Speaker 6: These things as like symbiotic tools.

1440
01:12:07,760 --> 01:12:10,639
Speaker 9: Yeah, it's kind of like a dear Sturmer type deal, right.

1441
01:12:10,800 --> 01:12:14,879
Speaker 9: Like the nice thing about it being a dere Stirmer

1442
01:12:14,960 --> 01:12:17,200
Speaker 9: deal is we we all know what happened to the

1443
01:12:17,200 --> 01:12:18,479
Speaker 9: guy who ran dere Sturmer.

1444
01:12:19,400 --> 01:12:19,960
Speaker 1: I don't.

1445
01:12:20,320 --> 01:12:23,040
Speaker 9: Oh he got hung by a drunk hangman that the

1446
01:12:23,200 --> 01:12:26,040
Speaker 9: US appointed because we didn't care who did the job.

1447
01:12:26,439 --> 01:12:29,559
Speaker 9: Made extra shared that it took a long time. Julia

1448
01:12:29,600 --> 01:12:32,360
Speaker 9: Striker was kicking up there for a minute. We got

1449
01:12:32,360 --> 01:12:33,160
Speaker 9: something to look forward to.

1450
01:12:33,320 --> 01:12:35,439
Speaker 1: That one of the funniest things. I thank you for

1451
01:12:35,520 --> 01:12:37,360
Speaker 1: sharing that.

1452
01:12:37,880 --> 01:12:38,120
Speaker 4: Smile.

1453
01:12:41,080 --> 01:12:44,639
Speaker 6: Oh good, did you talk about the Zuckerberg fact checking thing.

1454
01:12:44,960 --> 01:12:46,960
Speaker 1: We can talk about it again, because, as I was

1455
01:12:47,000 --> 01:12:50,400
Speaker 1: saying to it earlier, it is just Facebook slopping up

1456
01:12:50,479 --> 01:12:52,880
Speaker 1: like this is the ship they've always done. This is

1457
01:12:53,000 --> 01:12:56,479
Speaker 1: just them fucking instead of flushing the toilet, just pushing

1458
01:12:56,479 --> 01:12:59,320
Speaker 1: it into the kitchen. Like I said, Everyone's like, oh,

1459
01:12:59,360 --> 01:13:01,800
Speaker 1: it's so Donald. Try no, he just does an excuse

1460
01:13:01,880 --> 01:13:04,880
Speaker 1: now he knows laws won't or like morals will no

1461
01:13:04,960 --> 01:13:07,960
Speaker 1: longer be enforced, and Facebook already fucking sucked. I can't

1462
01:13:07,960 --> 01:13:09,280
Speaker 1: wait to see how much worse again.

1463
01:13:09,600 --> 01:13:13,320
Speaker 9: My Facebook feed right now as fully thirty forty percent

1464
01:13:13,320 --> 01:13:15,960
Speaker 9: of it is. Yeah, like there's like half a number

1465
01:13:15,960 --> 01:13:17,679
Speaker 9: of people that I used to know that The only

1466
01:13:17,720 --> 01:13:19,959
Speaker 9: way I have of like checking in with him is Facebook.

1467
01:13:20,439 --> 01:13:22,880
Speaker 9: I don't use it regularly, but every time I log in,

1468
01:13:22,920 --> 01:13:26,240
Speaker 9: a full third of my feed is war re enactors

1469
01:13:26,320 --> 01:13:28,519
Speaker 9: who are dressed as always dressed as members of the

1470
01:13:28,560 --> 01:13:33,160
Speaker 9: waffen SS and Aijen pushers of the waffen SS, And

1471
01:13:33,240 --> 01:13:36,559
Speaker 9: all of the comments are those brave boys, those poor boys,

1472
01:13:36,560 --> 01:13:39,320
Speaker 9: they were just trying to defend hundreds of them, hundreds

1473
01:13:39,360 --> 01:13:40,639
Speaker 9: of them, hundreds of them.

1474
01:13:40,720 --> 01:13:45,160
Speaker 1: It's bleak. I get like pitching and lifting things and

1475
01:13:45,200 --> 01:13:45,879
Speaker 1: like boxing.

1476
01:13:46,040 --> 01:13:48,360
Speaker 6: Yeah, maybe this tells us more just about Robert, like

1477
01:13:48,600 --> 01:13:49,439
Speaker 6: your own interests.

1478
01:13:49,560 --> 01:13:51,559
Speaker 9: Mine is just like, oh, I can't even read more

1479
01:13:51,600 --> 01:13:54,080
Speaker 9: than like seven or eight books about the Imperial German

1480
01:13:54,200 --> 01:13:56,679
Speaker 9: Army last year, so like it kind of like I'm

1481
01:13:56,720 --> 01:13:59,040
Speaker 9: that into the German German military history.

1482
01:13:59,080 --> 01:13:59,479
Speaker 4: Garris.

1483
01:13:59,479 --> 01:14:01,600
Speaker 6: This might just be the Facebook tracking is coming to

1484
01:14:01,640 --> 01:14:03,479
Speaker 6: be is coming to bite you all of it?

1485
01:14:03,880 --> 01:14:05,760
Speaker 9: How do you have the reading habits that are like

1486
01:14:05,960 --> 01:14:09,040
Speaker 9: the only other people with my reading habits are very problematic?

1487
01:14:09,120 --> 01:14:12,960
Speaker 1: Yes, magician versus slow mo camera. Ooh, that that one

1488
01:14:12,960 --> 01:14:16,720
Speaker 1: sounds Actually, this one's really good. It's kind of just

1489
01:14:16,880 --> 01:14:19,880
Speaker 1: free photo editing group. And it's just from December thirty one,

1490
01:14:20,000 --> 01:14:22,080
Speaker 1: twenty twenty four, and it is like a week later,

1491
01:14:22,280 --> 01:14:24,120
Speaker 1: and it's just like a very graty picture of a

1492
01:14:24,160 --> 01:14:27,280
Speaker 1: woman saying, is it possible to make this fuzzy photo shop?

1493
01:14:28,280 --> 01:14:30,679
Speaker 1: It is now with the power of AI in hants yeah,

1494
01:14:31,120 --> 01:14:34,640
Speaker 1: or like an the legacy of nerd Hulk Hoganmerton's w

1495
01:14:34,840 --> 01:14:35,439
Speaker 1: W A.

1496
01:14:35,439 --> 01:14:38,960
Speaker 9: Crude AI cartoon of a soldier with neither of both

1497
01:14:38,960 --> 01:14:41,160
Speaker 9: of his legs kind of melting off into a puddle

1498
01:14:41,200 --> 01:14:43,360
Speaker 9: that says, why don't pictures like this ever trend?

1499
01:14:43,640 --> 01:14:47,400
Speaker 1: I don't get any of the AI slop. I got

1500
01:14:47,760 --> 01:14:49,840
Speaker 1: boomer slap so much boomer slash slap.

1501
01:14:50,280 --> 01:14:54,000
Speaker 2: I don't get only women can understand not married yet.

1502
01:14:54,000 --> 01:14:57,519
Speaker 2: And it's a picture of a tomato then got married,

1503
01:14:57,520 --> 01:14:59,080
Speaker 2: and it's a picture of a watermelon.

1504
01:14:59,400 --> 01:15:03,320
Speaker 6: A lot of pictures of like kids crying and it's

1505
01:15:03,400 --> 01:15:06,519
Speaker 6: with like with like sad captions about how Kamala Harris

1506
01:15:06,560 --> 01:15:09,320
Speaker 6: is making kids cry if you agree, and.

1507
01:15:09,360 --> 01:15:12,120
Speaker 9: Like like literally every like fifth post is some sort

1508
01:15:12,160 --> 01:15:14,439
Speaker 9: of picture with why don't photos like this ever trend?

1509
01:15:14,920 --> 01:15:17,120
Speaker 1: Oh my other things, I've subscribed to a lot of

1510
01:15:17,240 --> 01:15:21,960
Speaker 1: Joker related that makes kind of unsettling. But yeah, no, no, no, no,

1511
01:15:22,600 --> 01:15:24,920
Speaker 1: you are the smiling man. No no, no, to explain the

1512
01:15:25,000 --> 01:15:27,439
Speaker 1: Joker mein thing, it's not because I believe in their views.

1513
01:15:27,439 --> 01:15:30,280
Speaker 1: It's that I had a brief two year long anthropological

1514
01:15:30,320 --> 01:15:32,000
Speaker 1: thing I was working on where I found the most

1515
01:15:32,040 --> 01:15:36,200
Speaker 1: insane typos in Joker memes and found this entire part

1516
01:15:36,240 --> 01:15:38,960
Speaker 1: of the global South there is guys who have clearly

1517
01:15:39,000 --> 01:15:42,880
Speaker 1: never watched a single thing with the Joker putting the

1518
01:15:42,880 --> 01:15:46,080
Speaker 1: most insane And my favorite was a picture of Phoenix

1519
01:15:46,400 --> 01:15:49,759
Speaker 1: and it said would you like to know which wyt

1520
01:15:50,360 --> 01:15:53,680
Speaker 1: h of them? We're liars? And to be clear that

1521
01:15:53,720 --> 01:15:56,479
Speaker 1: it is a Heath Ledger joker quote. Oh okay, yeah,

1522
01:15:56,520 --> 01:15:59,040
Speaker 1: And that one was just like I really didn't need

1523
01:15:59,120 --> 01:16:02,040
Speaker 1: much more. I'd found it's some of the Olympus at

1524
01:16:02,040 --> 01:16:05,720
Speaker 1: that point, but nevertheless, free Dan, Free Dan, get him

1525
01:16:05,760 --> 01:16:08,160
Speaker 1: out the thing that you get now on here is

1526
01:16:08,240 --> 01:16:12,320
Speaker 1: just apparently luxury hotels and now like some Google Maps grew.

1527
01:16:12,479 --> 01:16:15,519
Speaker 1: What is this fucking experience? What is Facebook for anymore?

1528
01:16:15,560 --> 01:16:18,200
Speaker 1: What is this app? It's it's all I mean, the

1529
01:16:18,280 --> 01:16:21,400
Speaker 1: everything app. No, it actually is the everything appen this

1530
01:16:21,479 --> 01:16:24,120
Speaker 1: is actually it actually does have everything. Actually this might

1531
01:16:24,200 --> 01:16:28,320
Speaker 1: really piss off Elon Musk if everything No, if Mark

1532
01:16:28,360 --> 01:16:30,240
Speaker 1: Sockerbo just says you have with the everything app, he

1533
01:16:30,240 --> 01:16:32,000
Speaker 1: should do that just to see what happened.

1534
01:16:32,000 --> 01:16:34,920
Speaker 6: If he gets banking working on Facebook before Twitter, that

1535
01:16:34,960 --> 01:16:36,840
Speaker 6: would be payments.

1536
01:16:37,400 --> 01:16:38,280
Speaker 1: Yeah, no, I guess.

1537
01:16:38,240 --> 01:16:41,800
Speaker 9: Yeah, yeah, who would you rather trust with your money

1538
01:16:41,800 --> 01:16:42,560
Speaker 9: than Facebook?

1539
01:16:43,720 --> 01:16:47,440
Speaker 1: I mean, I mean, I thought we all agree.

1540
01:16:47,560 --> 01:16:50,479
Speaker 6: I went to so many panels today and half of

1541
01:16:50,520 --> 01:16:54,439
Speaker 6: them sounded like the stand up solutions comedy sketch.

1542
01:16:54,560 --> 01:16:56,920
Speaker 1: Please tell tell me some of these wonderful things.

1543
01:16:56,920 --> 01:16:58,839
Speaker 9: You're gonna have to explain that joke to Garrison.

1544
01:16:58,920 --> 01:16:59,360
Speaker 1: Oh yeah.

1545
01:17:00,080 --> 01:17:02,839
Speaker 6: Absolutions is just a is a comedy stand up routine

1546
01:17:02,840 --> 01:17:05,840
Speaker 6: released I think earlier this year by a really good

1547
01:17:05,880 --> 01:17:08,599
Speaker 6: comedian who I cannot connor O'Malley.

1548
01:17:08,760 --> 01:17:11,559
Speaker 1: Okay, you should all watch it because it's very insane

1549
01:17:11,880 --> 01:17:14,800
Speaker 1: and it's also exactly the vibe. It's just half of

1550
01:17:15,000 --> 01:17:21,080
Speaker 1: half of it's a PowerPoint presentation of completely made up

1551
01:17:21,120 --> 01:17:22,840
Speaker 1: in the same ship by it's.

1552
01:17:22,680 --> 01:17:24,439
Speaker 6: How it it's how you can make an A it's

1553
01:17:24,439 --> 01:17:27,599
Speaker 6: how you can buy an AI that does stand up comedy.

1554
01:17:27,720 --> 01:17:30,439
Speaker 1: Yes, and this is what the things are like and

1555
01:17:30,479 --> 01:17:31,360
Speaker 1: this is what everything is.

1556
01:17:31,400 --> 01:17:33,479
Speaker 6: I mean the first the first panel I went to today,

1557
01:17:33,640 --> 01:17:36,639
Speaker 6: I heard the phrase like augmentation not replacement, probably about

1558
01:17:36,640 --> 01:17:39,880
Speaker 6: ten times a lot a lot about keeping.

1559
01:17:40,000 --> 01:17:41,120
Speaker 1: Yeah, that's what the plastic surgeon.

1560
01:17:42,160 --> 01:17:44,759
Speaker 6: There was a lot of fear in the AI panels

1561
01:17:44,880 --> 01:17:48,639
Speaker 6: from people scared of how much like backlash there is

1562
01:17:49,040 --> 01:17:53,080
Speaker 6: two AI tools and trying like trying to like find

1563
01:17:53,120 --> 01:17:58,639
Speaker 6: wayte like trick audiences into enjoying or like consuming AI slop.

1564
01:17:59,000 --> 01:18:02,040
Speaker 6: Like a lot of it was about that I don't

1565
01:18:02,120 --> 01:18:04,320
Speaker 6: like like like a phrase one of the panelists used

1566
01:18:04,360 --> 01:18:08,920
Speaker 6: was trying to solve the AI ick problem.

1567
01:18:08,280 --> 01:18:10,800
Speaker 1: Like like there's like there's like an ick around AI.

1568
01:18:11,040 --> 01:18:14,720
Speaker 1: We have this problem that fucking sucks. Nobody wants to use. Yeah,

1569
01:18:14,920 --> 01:18:15,639
Speaker 1: it looks bad.

1570
01:18:15,680 --> 01:18:18,599
Speaker 6: And they they had someone from Meta at this panel

1571
01:18:18,640 --> 01:18:20,960
Speaker 6: and they talked about how a few days ago Instagram

1572
01:18:21,000 --> 01:18:23,400
Speaker 6: announced they would be having like a AI generated like

1573
01:18:23,479 --> 01:18:26,000
Speaker 6: fake profiles, right, people that don't exist. And there was

1574
01:18:26,000 --> 01:18:29,200
Speaker 6: so much backlash like based on this that they that

1575
01:18:29,240 --> 01:18:32,400
Speaker 6: they took it away, but they explained it by saying, actually,

1576
01:18:32,400 --> 01:18:33,840
Speaker 6: the market just isn't ready yet.

1577
01:18:34,479 --> 01:18:36,559
Speaker 1: This isn't back to the future, isn't. It's not that

1578
01:18:36,600 --> 01:18:38,920
Speaker 1: it's not that this is a terrible idea. I said,

1579
01:18:38,920 --> 01:18:40,400
Speaker 1: the market's not ready yet.

1580
01:18:40,680 --> 01:18:42,560
Speaker 9: There are certain issues where like we haven't been a

1581
01:18:42,640 --> 01:18:46,160
Speaker 9: specifically hear it from like a queer woman of color

1582
01:18:46,200 --> 01:18:47,880
Speaker 9: who's a mother in New York City. Right, there's a

1583
01:18:47,920 --> 01:18:49,719
Speaker 9: number of issues, yes, but an actual one.

1584
01:18:49,760 --> 01:18:50,360
Speaker 1: But but a.

1585
01:18:50,360 --> 01:18:53,680
Speaker 9: Person yeah, I don't I don't need an AI that

1586
01:18:53,760 --> 01:18:56,000
Speaker 9: admits it was coded by some white ladies in the

1587
01:18:56,040 --> 01:18:57,960
Speaker 9: bay pretending to be this person.

1588
01:18:58,080 --> 01:19:01,200
Speaker 1: No, it's then like the pigs. The pigs have not

1589
01:19:01,360 --> 01:19:04,599
Speaker 1: being suppressed enough. We've not we've not sedated.

1590
01:19:05,680 --> 01:19:09,680
Speaker 6: Yeah, get the ready for the And it really is

1591
01:19:09,840 --> 01:19:12,400
Speaker 6: another phrase that it is just like like AI, like

1592
01:19:12,400 --> 01:19:16,479
Speaker 6: like improvements will all be based around consumer acceptance. It's

1593
01:19:16,479 --> 01:19:19,559
Speaker 6: like we have all the text having but we have

1594
01:19:19,640 --> 01:19:22,000
Speaker 6: to trick people into actually like what they're looking for

1595
01:19:22,160 --> 01:19:22,719
Speaker 6: is consent.

1596
01:19:23,120 --> 01:19:25,559
Speaker 9: There's a lot of attitude, there's a lot a vibe

1597
01:19:25,560 --> 01:19:28,320
Speaker 9: from them that is very much like a like a

1598
01:19:28,560 --> 01:19:31,479
Speaker 9: like a dude who's trying to pressure someone into sex

1599
01:19:31,600 --> 01:19:35,720
Speaker 9: and is like, and I can like massage this into

1600
01:19:35,880 --> 01:19:37,920
Speaker 9: like them being okay enough with it, right.

1601
01:19:37,840 --> 01:19:39,040
Speaker 1: I can get him to agree to this.

1602
01:19:39,360 --> 01:19:42,280
Speaker 9: Yeah, it's it's this very We're in a very interesting

1603
01:19:42,320 --> 01:19:45,519
Speaker 9: position with this fight where it's still recent enough. Every

1604
01:19:45,560 --> 01:19:48,799
Speaker 9: like everyone who is trying to push the the AI

1605
01:19:49,040 --> 01:19:53,360
Speaker 9: line remembers n f t S and the Metaverse going

1606
01:19:53,400 --> 01:19:56,960
Speaker 9: down in flames and how unified and effective the backlash

1607
01:19:56,960 --> 01:20:00,240
Speaker 9: against them was. Now neither of those ever had any

1608
01:20:00,280 --> 01:20:03,720
Speaker 9: actual technology on your life, if you.

1609
01:20:03,720 --> 01:20:06,000
Speaker 1: Can call Metaverse any consumer adoption as well.

1610
01:20:06,080 --> 01:20:09,240
Speaker 9: Yeah, there was no real technology that was in any

1611
01:20:09,240 --> 01:20:13,360
Speaker 9: way impressive, and there was no real user hunger. There's

1612
01:20:13,520 --> 01:20:16,240
Speaker 9: user hunger for some of the things AI does, and

1613
01:20:16,280 --> 01:20:21,360
Speaker 9: there's real technology there, but there's also a backlash that's

1614
01:20:21,479 --> 01:20:24,000
Speaker 9: very similar to the backlash for those two things. And

1615
01:20:24,040 --> 01:20:27,200
Speaker 9: they see that and they're very they're scared of it

1616
01:20:27,200 --> 01:20:30,120
Speaker 9: because they know it is a threat to because of

1617
01:20:30,120 --> 01:20:32,800
Speaker 9: how much how they have to keep up momentum if

1618
01:20:32,840 --> 01:20:35,439
Speaker 9: momentum drops at any point. A lot of these companies,

1619
01:20:35,720 --> 01:20:37,640
Speaker 9: like obviously the tech won't go away. But a lot

1620
01:20:37,640 --> 01:20:41,920
Speaker 9: of these companies say, like yeah, exactly, and so they're

1621
01:20:42,040 --> 01:20:44,719
Speaker 9: scared of that. And and that's a really interesting position

1622
01:20:44,760 --> 01:20:47,120
Speaker 9: to be in because it shows that number one, that

1623
01:20:47,200 --> 01:20:48,839
Speaker 9: the fight is still winnable.

1624
01:20:49,840 --> 01:20:52,040
Speaker 1: Talking about it, I can be.

1625
01:20:52,040 --> 01:20:54,400
Speaker 6: Saying, like, the same way that we were able to

1626
01:20:54,439 --> 01:20:57,320
Speaker 6: beat NFTs and beat the metaverse to some degree, like

1627
01:20:57,600 --> 01:20:59,719
Speaker 6: that is this is going to be a longer battle

1628
01:20:59,760 --> 01:21:02,240
Speaker 6: than that, but like it is having an impact. You

1629
01:21:02,280 --> 01:21:04,639
Speaker 6: can like even look at like a like a Chapel

1630
01:21:04,680 --> 01:21:07,679
Speaker 6: Rome posted something about like AI generated images that received

1631
01:21:07,720 --> 01:21:10,400
Speaker 6: a lot of backlash, and like people and like ad

1632
01:21:10,400 --> 01:21:13,960
Speaker 6: agencies are like looking at this and they're trying to

1633
01:21:13,960 --> 01:21:15,840
Speaker 6: figure out a few ways to kind of navigate it.

1634
01:21:16,040 --> 01:21:17,679
Speaker 6: A few of the other panels I went to specifically

1635
01:21:17,680 --> 01:21:19,320
Speaker 6: about like how to market stuff to gen Z was

1636
01:21:19,360 --> 01:21:23,080
Speaker 6: like talking about like the importance of like like authentic brands.

1637
01:21:22,680 --> 01:21:24,519
Speaker 1: Like saying on fleek gen Z.

1638
01:21:26,400 --> 01:21:29,519
Speaker 6: Is so vest is so vested in like authenticity, and

1639
01:21:29,560 --> 01:21:31,639
Speaker 6: if you're gonna partner with influencers who you is AI,

1640
01:21:31,680 --> 01:21:33,320
Speaker 6: it has to have that authentic angle.

1641
01:21:33,479 --> 01:21:35,960
Speaker 1: So what's funny about the influencer thing that I don't

1642
01:21:35,960 --> 01:21:39,599
Speaker 1: think companies realize is they think every influencer is this

1643
01:21:39,760 --> 01:21:42,639
Speaker 1: pliant brain who will do anything for vacation, and there

1644
01:21:42,640 --> 01:21:44,840
Speaker 1: are an alarming amount of them that will. What they

1645
01:21:44,840 --> 01:21:46,680
Speaker 1: don't realize is that there are many of them that,

1646
01:21:46,720 --> 01:21:49,360
Speaker 1: once they reach a certain scale, go, wait fucking minute,

1647
01:21:50,160 --> 01:21:52,759
Speaker 1: I don't have to go to the LG pain Maze.

1648
01:21:53,280 --> 01:21:56,640
Speaker 1: I don't have to to ride a horse to the

1649
01:21:56,760 --> 01:22:00,320
Speaker 1: LG compound to see the secret fridge. Yeah, and then

1650
01:22:00,360 --> 01:22:04,719
Speaker 1: they become angry and they crush them. Stephen from Gamers

1651
01:22:04,800 --> 01:22:07,719
Speaker 1: Nexus is my favorite. He's never done access he does. Stephen,

1652
01:22:07,760 --> 01:22:09,559
Speaker 1: if you're listening to this police, come on my fucking show.

1653
01:22:09,560 --> 01:22:09,920
Speaker 1: I love you.

1654
01:22:10,080 --> 01:22:10,800
Speaker 4: I don't know who you are.

1655
01:22:10,880 --> 01:22:14,639
Speaker 1: Steven Games Next is probably the single most YouTube important,

1656
01:22:14,680 --> 01:22:17,960
Speaker 1: the single most YouTube, jesus, the most important YouTube in

1657
01:22:18,400 --> 01:22:21,040
Speaker 1: pretty much processes and chips. There are some others as well,

1658
01:22:21,040 --> 01:22:23,360
Speaker 1: but like, Steven's done this scredible thing and it's mostly

1659
01:22:23,400 --> 01:22:27,000
Speaker 1: just him standing looking exhausted over a table, just ripping

1660
01:22:27,000 --> 01:22:29,599
Speaker 1: these fucking companies to shreds, or going to their offices

1661
01:22:29,600 --> 01:22:31,640
Speaker 1: and be like hey, hey, Steven Games, like hey, what

1662
01:22:31,760 --> 01:22:35,360
Speaker 1: you're doing? Like British politician style. I don't think they

1663
01:22:35,439 --> 01:22:38,200
Speaker 1: realize that there are so many influences just like that

1664
01:22:38,200 --> 01:22:41,080
Speaker 1: out there. Coffee's either mm hm, He's a fucking.

1665
01:22:40,880 --> 01:22:42,920
Speaker 9: Beast, yeah, especially considered that. What I think is so

1666
01:22:42,920 --> 01:22:45,080
Speaker 9: interesting about him is that he is he is into

1667
01:22:45,120 --> 01:22:48,200
Speaker 9: and speaking to this group of people who are profoundly

1668
01:22:48,240 --> 01:22:50,759
Speaker 9: anti media and like kind of chetty.

1669
01:22:50,840 --> 01:22:51,639
Speaker 1: Yeah, like that's a lot.

1670
01:22:51,720 --> 01:22:55,719
Speaker 9: But he's also he does very good journalism, yeah, within

1671
01:22:55,760 --> 01:22:58,839
Speaker 9: that space, like and really has done more than almost

1672
01:22:58,840 --> 01:23:02,559
Speaker 9: anyone to kill specific kinds of conn.

1673
01:23:02,800 --> 01:23:07,479
Speaker 1: Did a podcast with me Rabbit reporting No big deal.

1674
01:23:08,360 --> 01:23:11,360
Speaker 1: But it's funny as well because they're definitely thinking that, oh, yeah,

1675
01:23:11,360 --> 01:23:13,840
Speaker 1: we'll get these stupid fucking gen Z kids and these

1676
01:23:13,880 --> 01:23:18,080
Speaker 1: idiot influences and gen Z as you all Knoweah, your

1677
01:23:18,160 --> 01:23:21,160
Speaker 1: gen Z yes thirty eight years old and I sound

1678
01:23:21,160 --> 01:23:23,639
Speaker 1: a hot. What's the age for? I do not know.

1679
01:23:23,800 --> 01:23:24,639
Speaker 1: It's at this point.

1680
01:23:24,680 --> 01:23:27,920
Speaker 6: It's like if they can't yah seven or twenty eight,

1681
01:23:28,520 --> 01:23:29,120
Speaker 6: it depends.

1682
01:23:29,640 --> 01:23:34,320
Speaker 9: Usually born twenty seven are are cusps, they're cuspers.

1683
01:23:34,360 --> 01:23:37,200
Speaker 6: If you're born between nineteen ninety seven and around twenty

1684
01:23:37,320 --> 01:23:40,519
Speaker 6: twelve is usually the gen Z racket.

1685
01:23:41,320 --> 01:23:43,040
Speaker 1: You like you are a young millennial.

1686
01:23:43,120 --> 01:23:45,720
Speaker 9: Yeah, if if your knees make a sound when you

1687
01:23:45,800 --> 01:23:47,600
Speaker 9: stand up your Every.

1688
01:23:47,400 --> 01:23:51,000
Speaker 1: Time older I do yeah, yeah, every time I do yoga,

1689
01:23:51,040 --> 01:23:53,240
Speaker 1: my knee makes a noise like a pinball machine breaking.

1690
01:23:53,640 --> 01:23:56,640
Speaker 1: That doctor said, it's great, but it's funny because what

1691
01:23:56,680 --> 01:23:59,320
Speaker 1: they don't realize is as legacy media dies, yeah, you're

1692
01:23:59,320 --> 01:24:02,680
Speaker 1: gonna have a bunch of insane influences. Those insane influences

1693
01:24:02,720 --> 01:24:05,439
Speaker 1: will be the ones that actually have a genuine animus

1694
01:24:05,439 --> 01:24:09,080
Speaker 1: with the LG Fridge. The fridge guy is eventually going

1695
01:24:09,120 --> 01:24:11,840
Speaker 1: to turn on the fridge manufacturers, and the fridge guy

1696
01:24:11,880 --> 01:24:14,519
Speaker 1: will bring them great pain as he reviews the fridge

1697
01:24:14,800 --> 01:24:17,639
Speaker 1: with alarming accuracy. And I think that that they don't

1698
01:24:17,680 --> 01:24:20,040
Speaker 1: realize that that is what will come to replace some

1699
01:24:20,120 --> 01:24:22,720
Speaker 1: of legacy media. It's going to be posters.

1700
01:24:22,880 --> 01:24:25,559
Speaker 9: It's going to be people have no vested interest in

1701
01:24:25,680 --> 01:24:30,479
Speaker 9: the politests that they can expect from like legacy media. Right, Yeah,

1702
01:24:30,720 --> 01:24:34,639
Speaker 9: there's no there's no space in like YouTube review guys

1703
01:24:34,720 --> 01:24:39,160
Speaker 9: or TikTok guys for Walt Mossburg. Nobody wants a dude

1704
01:24:39,280 --> 01:24:42,320
Speaker 9: like that. You want somebody who's snarky and got an

1705
01:24:42,360 --> 01:24:46,200
Speaker 9: angle and funny, and it's just easier to rip up

1706
01:24:46,240 --> 01:24:49,400
Speaker 9: a lot of these shitty AI products to like than

1707
01:24:49,439 --> 01:24:51,680
Speaker 9: it is to fucking pup them up.

1708
01:24:51,760 --> 01:24:54,560
Speaker 1: And I will tell you something, running a PR firm,

1709
01:24:54,600 --> 01:24:57,679
Speaker 1: not a single fucking PR person for the most part,

1710
01:24:57,760 --> 01:25:00,320
Speaker 1: can prepare you for that. The only thing that can

1711
01:25:00,360 --> 01:25:04,120
Speaker 1: prepare you is well, actually that position training. Yeah, you

1712
01:25:04,160 --> 01:25:05,840
Speaker 1: get a lawyer to train you, that will do you

1713
01:25:05,920 --> 01:25:06,479
Speaker 1: fomo good.

1714
01:25:06,479 --> 01:25:09,519
Speaker 2: With media training, having you know, growing up roasting people,

1715
01:25:09,520 --> 01:25:10,960
Speaker 2: that might help you a little bit bit.

1716
01:25:11,000 --> 01:25:13,040
Speaker 1: But you also have to realize that the truth is

1717
01:25:13,080 --> 01:25:16,960
Speaker 1: generally useful and if you're trying to hide that an influence.

1718
01:25:17,000 --> 01:25:18,439
Speaker 1: So we really get around that.

1719
01:25:19,479 --> 01:25:21,360
Speaker 9: What I think is so important to get back on

1720
01:25:21,400 --> 01:25:24,160
Speaker 9: the topic of like how do we win this fight

1721
01:25:24,360 --> 01:25:29,519
Speaker 9: against AI slopification of everything beautiful in the human spirit.

1722
01:25:30,280 --> 01:25:33,600
Speaker 9: This is not a political fight. And that's like you

1723
01:25:33,920 --> 01:25:36,000
Speaker 9: guys like coffee Zilla on it, right, Like this is

1724
01:25:36,080 --> 01:25:38,639
Speaker 9: a lot of people when they look at this shit

1725
01:25:38,680 --> 01:25:41,400
Speaker 9: and when they consider like the art and the actors

1726
01:25:41,439 --> 01:25:45,160
Speaker 9: and musicians being replaced so that like some fucking Bay

1727
01:25:45,200 --> 01:25:49,320
Speaker 9: Area assholes like can hoover up even more money and

1728
01:25:49,360 --> 01:25:52,040
Speaker 9: like destroy the ability of like the human mind to

1729
01:25:53,040 --> 01:25:58,160
Speaker 9: represent itself. That's not a political issue, and there is

1730
01:25:58,280 --> 01:26:02,920
Speaker 9: I think an immense amount of potential still to get

1731
01:26:02,920 --> 01:26:06,519
Speaker 9: a lot of people together and to fucking strangle this

1732
01:26:06,560 --> 01:26:10,000
Speaker 9: thing and it's cradle because we all, we all have

1733
01:26:10,120 --> 01:26:14,720
Speaker 9: this kind of visceral feeling that it's reulption. Yeah, this revulsion.

1734
01:26:14,800 --> 01:26:17,240
Speaker 9: That revulsion is what we need to lean into.

1735
01:26:17,240 --> 01:26:20,600
Speaker 6: The aiic like the AI they simply don't have. The

1736
01:26:20,600 --> 01:26:22,400
Speaker 6: thing that matters most was that like, which is its

1737
01:26:22,439 --> 01:26:24,760
Speaker 6: ability to make like good compelling stuff and this is

1738
01:26:24,800 --> 01:26:27,439
Speaker 6: something that's that this is something like they actually know.

1739
01:26:28,400 --> 01:26:32,439
Speaker 6: I'm gonna read something about something one of the guys

1740
01:26:32,439 --> 01:26:35,080
Speaker 6: on the panel from Adobe was talking about. He was

1741
01:26:35,120 --> 01:26:39,120
Speaker 6: talking about how when you're making AI content specifically like

1742
01:26:39,160 --> 01:26:42,599
Speaker 6: targeted towards specific people, like a personalized content is always

1743
01:26:42,640 --> 01:26:45,680
Speaker 6: like the most like impactful. And there's three parts that

1744
01:26:45,720 --> 01:26:50,320
Speaker 6: are needed to create a personalized content pipeline. You need data,

1745
01:26:50,880 --> 01:26:53,120
Speaker 6: you need you need like a journey to take the

1746
01:26:53,160 --> 01:26:56,720
Speaker 6: person on, and you need the content itself. And we

1747
01:26:56,760 --> 01:27:00,680
Speaker 6: need content at scale that is highly personalized. And he

1748
01:27:00,840 --> 01:27:04,200
Speaker 6: said that we're good at the first two parts, the

1749
01:27:04,280 --> 01:27:07,120
Speaker 6: data and the journeys, and I would I would argue

1750
01:27:07,120 --> 01:27:10,720
Speaker 6: about the journey's part, but he said, now we just

1751
01:27:10,760 --> 01:27:13,800
Speaker 6: have to improve the actual content. It's like they know,

1752
01:27:14,800 --> 01:27:17,240
Speaker 6: they know the content's bad, Like, yeah, that's the thing

1753
01:27:17,280 --> 01:27:18,920
Speaker 6: we have to still actually like figure out. It's like

1754
01:27:18,960 --> 01:27:21,599
Speaker 6: how to like turn data into like a good content

1755
01:27:22,040 --> 01:27:24,160
Speaker 6: And that's that's still the thing that they're really struggling.

1756
01:27:24,160 --> 01:27:26,840
Speaker 1: And it also looks the same as it did, like

1757
01:27:26,920 --> 01:27:28,400
Speaker 1: he does look the name as did a year ago.

1758
01:27:29,080 --> 01:27:31,840
Speaker 9: There's so much talk and finally on what because I

1759
01:27:32,280 --> 01:27:34,639
Speaker 9: listened to him, Like the first two Tech and Holly

1760
01:27:34,680 --> 01:27:36,439
Speaker 9: AI and Hollywood panels I listened to, there were a

1761
01:27:36,479 --> 01:27:38,360
Speaker 9: lot of talk about like we just need to be

1762
01:27:38,400 --> 01:27:41,200
Speaker 9: able to like if we can read people's brains while

1763
01:27:41,200 --> 01:27:43,519
Speaker 9: they're watching stuff, we can see how they're reacting, and

1764
01:27:43,520 --> 01:27:47,400
Speaker 9: then we can alter like yeah, yeah, the content that

1765
01:27:47,439 --> 01:27:49,880
Speaker 9: they're taking. That meta was talking about the ending or

1766
01:27:49,880 --> 01:27:52,400
Speaker 9: whatever to to really make it more engaging. And it

1767
01:27:52,439 --> 01:27:55,920
Speaker 9: was finally somebody in that in the fourth panel when

1768
01:27:55,920 --> 01:27:58,720
Speaker 9: it was actually like people who write and stuff on

1769
01:27:58,800 --> 01:28:02,639
Speaker 9: it was like people don't want that. People don't people

1770
01:28:03,080 --> 01:28:05,080
Speaker 9: like we consistently see and if you look at the

1771
01:28:05,120 --> 01:28:07,719
Speaker 9: ship that went huge last year, the most profitable movies

1772
01:28:07,800 --> 01:28:10,200
Speaker 9: last year was the result of two movies that were

1773
01:28:10,200 --> 01:28:12,920
Speaker 9: the result of huge amounts of human effort. The Barbie

1774
01:28:12,920 --> 01:28:15,559
Speaker 9: movie and the Oppenheimer movie. Say what you will about

1775
01:28:15,560 --> 01:28:18,280
Speaker 9: both of those or so. I mean, I'm sure that

1776
01:28:18,280 --> 01:28:19,160
Speaker 9: one made some money, but.

1777
01:28:19,760 --> 01:28:23,120
Speaker 1: It still extremely hard work from three das however you

1778
01:28:23,160 --> 01:28:25,880
Speaker 1: feel about those disgusting creatures, dominions.

1779
01:28:25,520 --> 01:28:27,880
Speaker 9: And more than anything like the Barbenheimer thing was like

1780
01:28:27,920 --> 01:28:32,160
Speaker 9: certainly the most significant single movie trick last year, and

1781
01:28:32,200 --> 01:28:35,600
Speaker 9: that was the result of people wanting a shared.

1782
01:28:35,280 --> 01:28:38,439
Speaker 1: Experience and a very specific aesthetic in those cases, not

1783
01:28:38,560 --> 01:28:40,520
Speaker 1: something that changes every frame.

1784
01:28:40,640 --> 01:28:43,000
Speaker 9: Not wanting to, not wanting to, like go, hey, did

1785
01:28:43,040 --> 01:28:44,560
Speaker 9: you see that movie last night? Well, I saw the

1786
01:28:44,640 --> 01:28:45,720
Speaker 9: version that was made for me.

1787
01:28:46,080 --> 01:28:48,599
Speaker 1: Was like people people.

1788
01:28:48,360 --> 01:28:51,640
Speaker 6: Who actually want personalized content. I don't want to be

1789
01:28:52,080 --> 01:28:54,519
Speaker 6: music generated for me. I want music that I can share,

1790
01:28:54,840 --> 01:28:57,240
Speaker 6: and that's in some kind of cultural conversation with other

1791
01:28:57,280 --> 01:28:59,400
Speaker 6: people who also enjoy music, who I can talk to

1792
01:28:59,800 --> 01:29:01,960
Speaker 6: like that about and compare it.

1793
01:29:02,080 --> 01:29:03,400
Speaker 9: Yeah, what do you think of that speech at the

1794
01:29:03,479 --> 01:29:05,120
Speaker 9: end of The Great Dictator? Well, when I watched The

1795
01:29:05,120 --> 01:29:07,840
Speaker 9: Great Dictator, Charlie just turned to the screen and said,

1796
01:29:07,840 --> 01:29:08,639
Speaker 9: everything's good.

1797
01:29:08,800 --> 01:29:13,360
Speaker 1: Keep doing what you're doing, right. Nick Fury woke down

1798
01:29:14,600 --> 01:29:18,120
Speaker 1: as this is this is literally the future that these

1799
01:29:18,120 --> 01:29:18,599
Speaker 1: people want.

1800
01:29:18,840 --> 01:29:23,400
Speaker 9: Travis Kelsey, Yeah, told me I look like Iron Man.

1801
01:29:23,760 --> 01:29:25,439
Speaker 1: Oh my god.

1802
01:29:27,560 --> 01:29:30,200
Speaker 6: Someone from Meta who works in like their hyper reality division,

1803
01:29:31,040 --> 01:29:34,120
Speaker 6: was talking about how they can start using AI and

1804
01:29:34,160 --> 01:29:34,880
Speaker 6: the metaverse.

1805
01:29:35,200 --> 01:29:36,439
Speaker 1: That's the hyper reality.

1806
01:29:36,720 --> 01:29:40,360
Speaker 6: Let's say that you're watching an immersive live concert, something

1807
01:29:40,360 --> 01:29:41,600
Speaker 6: that me and all my friends do.

1808
01:29:41,680 --> 01:29:44,320
Speaker 10: By the way, right away, you want to go to

1809
01:29:44,400 --> 01:29:48,559
Speaker 10: a real using using m R mixed reality and and

1810
01:29:48,880 --> 01:29:52,240
Speaker 10: the AI can sense your excitement and it can personalize

1811
01:29:52,240 --> 01:29:55,240
Speaker 10: your experience based on your favorite song or artist.

1812
01:29:55,520 --> 01:29:58,519
Speaker 6: So in AI, Taylor Swift near the end of the

1813
01:29:58,560 --> 01:30:00,840
Speaker 6: song can like come down in the stage and like

1814
01:30:01,000 --> 01:30:03,040
Speaker 6: and like dance with you. That would freak me the

1815
01:30:03,080 --> 01:30:05,360
Speaker 6: fun out or like that would not depend where they

1816
01:30:05,400 --> 01:30:08,360
Speaker 6: can change the song based on what your favorite songs are.

1817
01:30:08,439 --> 01:30:11,240
Speaker 6: So it's using AI and the metaverse you de crede

1818
01:30:11,360 --> 01:30:12,960
Speaker 6: ultra personalized experiences.

1819
01:30:13,240 --> 01:30:15,040
Speaker 1: I have never done worse than we But can you

1820
01:30:15,040 --> 01:30:17,559
Speaker 1: even imagine this while stone that would be horrifying. It's

1821
01:30:17,640 --> 01:30:21,960
Speaker 1: following it does like a good time. The idea of

1822
01:30:21,960 --> 01:30:24,960
Speaker 1: like stoned brain being like, well, this is what this

1823
01:30:25,040 --> 01:30:28,320
Speaker 1: is what me and Atticus Rocks are gonna get down In.

1824
01:30:28,280 --> 01:30:30,960
Speaker 2: The metaverse, Yeah, we're gonna Candy Flip and the Man

1825
01:30:31,160 --> 01:30:32,560
Speaker 2: and the metaverse.

1826
01:30:32,280 --> 01:30:34,920
Speaker 1: You get it. I don't know what this is. I

1827
01:30:34,960 --> 01:30:35,600
Speaker 1: don't listen to.

1828
01:30:35,840 --> 01:30:37,760
Speaker 9: I would rather play We're gonna show you at the

1829
01:30:38,680 --> 01:30:43,200
Speaker 9: Taylor Swift the Necessity of war.

1830
01:30:43,400 --> 01:30:49,599
Speaker 1: Your Taylor Swift the whole time, shot that Taylor Swift.

1831
01:30:49,600 --> 01:30:51,439
Speaker 1: I want to watch a you made me.

1832
01:30:52,479 --> 01:30:56,120
Speaker 9: Willie peaked on a school in Northern can't save you.

1833
01:30:56,120 --> 01:30:58,639
Speaker 1: You gotta shoot those kids. You gotta shoot those kids.

1834
01:30:59,120 --> 01:31:01,320
Speaker 1: They're gonna turn it, just like Taylor.

1835
01:31:01,439 --> 01:31:03,960
Speaker 9: No one else, nobody else was in that fucking bunker

1836
01:31:04,000 --> 01:31:05,920
Speaker 9: with us. No one else can understand what we had

1837
01:31:05,920 --> 01:31:09,040
Speaker 9: to do. And then you light your AI cigarette, your

1838
01:31:09,080 --> 01:31:10,480
Speaker 9: little hit of AI nicotine.

1839
01:31:10,680 --> 01:31:13,519
Speaker 1: Thank fun. There's not a more crazed fan base than Linux.

1840
01:31:16,040 --> 01:31:18,760
Speaker 1: I'm gonna get killed. Doesn't everybody want to go to metaverse?

1841
01:31:18,760 --> 01:31:25,439
Speaker 2: Fallujah Meta Fallujah, that's meta fallujahjah Verse.

1842
01:31:27,280 --> 01:31:29,080
Speaker 1: Cinematicise.

1843
01:31:29,360 --> 01:31:32,040
Speaker 6: As I was sitting through all these AI panels, I

1844
01:31:32,080 --> 01:31:35,439
Speaker 6: get a text from both Ed and Robert iBOT some

1845
01:31:35,560 --> 01:31:38,400
Speaker 6: breaking news regarding the Tesla truck bombing.

1846
01:31:39,120 --> 01:31:43,160
Speaker 1: Yeah, yeah, that he used to planet sick.

1847
01:31:43,360 --> 01:31:45,880
Speaker 9: First off, green Beret training is not what it used

1848
01:31:45,880 --> 01:31:46,120
Speaker 9: to do.

1849
01:31:47,439 --> 01:31:51,840
Speaker 2: Yeah, they're taking us for a ride with whatever we're

1850
01:31:51,880 --> 01:31:53,080
Speaker 2: paying if they have to use this.

1851
01:31:53,160 --> 01:31:55,600
Speaker 1: G had to use chet GPT to make a bombe.

1852
01:31:56,640 --> 01:31:58,559
Speaker 9: My uncle was a Green Beret, and I'll tell you

1853
01:31:58,600 --> 01:32:01,320
Speaker 9: one thing, he did not need chat GPT to make

1854
01:32:01,360 --> 01:32:02,599
Speaker 9: an explosive device.

1855
01:32:05,160 --> 01:32:09,000
Speaker 1: Every time I have you on, I'm just I'm just

1856
01:32:09,160 --> 01:32:13,080
Speaker 1: like texting my lawyer, just I'm sorry.

1857
01:32:13,760 --> 01:32:16,519
Speaker 9: Well, what's interesting is he was specifically looking up as

1858
01:32:16,560 --> 01:32:19,280
Speaker 9: a detonator he was trying to use at some point tannerite,

1859
01:32:19,320 --> 01:32:22,640
Speaker 9: and he must have if he either got a detonator

1860
01:32:22,680 --> 01:32:25,320
Speaker 9: to detonate the tanner but he was looking initially at

1861
01:32:25,320 --> 01:32:28,799
Speaker 9: trying to shoot the tannerite to detonate it, which would.

1862
01:32:28,600 --> 01:32:31,120
Speaker 1: Not have allowed him to shoot himself. Well, that's that's

1863
01:32:31,160 --> 01:32:33,320
Speaker 1: the problem. That's why he went else.

1864
01:32:33,520 --> 01:32:38,040
Speaker 6: Chat GVT couldn't figure that one out.

1865
01:32:39,000 --> 01:32:46,040
Speaker 1: I I love doing a show on the podcast about

1866
01:32:46,040 --> 01:32:49,920
Speaker 1: the future, and every fucking conversation I've had, without fail

1867
01:32:50,000 --> 01:32:52,599
Speaker 1: has been like everything I've seen is either fake or bad.

1868
01:32:53,200 --> 01:32:55,400
Speaker 1: And I don't even mean this. We get the occasional.

1869
01:32:55,600 --> 01:32:59,200
Speaker 1: You're a pessimist, motherfucker. Bring me some las. Robert should

1870
01:32:59,200 --> 01:33:01,639
Speaker 1: be one good thing to please please something. Oh shit,

1871
01:33:01,720 --> 01:33:03,960
Speaker 1: what was it? That's so good? Oh?

1872
01:33:04,000 --> 01:33:09,480
Speaker 9: The suicide helicopter. There's a helicopter that'll kill everybody. Imagine

1873
01:33:09,479 --> 01:33:12,320
Speaker 9: if you had a helicopter. But it's two thirds the

1874
01:33:12,360 --> 01:33:14,479
Speaker 9: size of a smart car, and it can drive on

1875
01:33:14,600 --> 01:33:17,240
Speaker 9: city streets, but it has no side or rear view mirrors.

1876
01:33:17,360 --> 01:33:19,240
Speaker 9: All of that's all of that's a lot of cameras

1877
01:33:19,280 --> 01:33:22,519
Speaker 9: immers in this cramped little and then when you're ready

1878
01:33:22,560 --> 01:33:25,760
Speaker 9: to fly, it's a quad copter and you can fly

1879
01:33:26,560 --> 01:33:29,559
Speaker 9: up to two hundred meters in the air. Because if

1880
01:33:29,560 --> 01:33:31,479
Speaker 9: you're under that, you don't need a pilot's liice. Do

1881
01:33:31,479 --> 01:33:34,280
Speaker 9: we have a emphasize to me under ten grand? Wow,

1882
01:33:34,479 --> 01:33:37,840
Speaker 9: so little portable helicopters that you can fly for up

1883
01:33:37,840 --> 01:33:42,439
Speaker 9: to twenty minutes in the air.

1884
01:33:42,479 --> 01:33:43,360
Speaker 1: That's what you get.

1885
01:33:44,400 --> 01:33:48,559
Speaker 9: Yeah, what happens if you run out of that ay Again,

1886
01:33:49,120 --> 01:33:52,200
Speaker 9: Let's let's say you a former Green Beret, decide to

1887
01:33:52,280 --> 01:33:55,960
Speaker 9: rint the suicide helicopter. Then you just fill that motherfucker

1888
01:33:56,080 --> 01:33:58,080
Speaker 9: up with fuel. All you need is ten minutes. As

1889
01:33:58,080 --> 01:34:00,120
Speaker 9: long as you like you you toe it up in

1890
01:34:00,160 --> 01:34:03,200
Speaker 9: your truck outside of whatever buildings you haven't.

1891
01:34:02,960 --> 01:34:06,519
Speaker 1: You can't see that this is never got to be

1892
01:34:06,560 --> 01:34:09,000
Speaker 1: a real problem. This is this is I do love

1893
01:34:09,040 --> 01:34:12,080
Speaker 1: they made like a comic cozy simulator, like that is

1894
01:34:12,120 --> 01:34:15,120
Speaker 1: what it is, right, Yeah, I swear and be your own.

1895
01:34:15,800 --> 01:34:19,880
Speaker 1: I was like I do genuinely ask the question of

1896
01:34:19,960 --> 01:34:22,880
Speaker 1: did you see something you like? In good faith every time,

1897
01:34:23,240 --> 01:34:25,519
Speaker 1: and every time it's just someone being like, no, I

1898
01:34:25,560 --> 01:34:29,400
Speaker 1: mean you don't want to street. I don't. I love

1899
01:34:29,520 --> 01:34:30,639
Speaker 1: committing no crime.

1900
01:34:30,680 --> 01:34:36,479
Speaker 2: I'm we're calling it the Tora to Torah.

1901
01:34:38,080 --> 01:34:40,160
Speaker 1: Oh god, I've got to wrap this up before I

1902
01:34:40,200 --> 01:34:41,559
Speaker 1: get in any more legal trouble.

1903
01:34:42,200 --> 01:34:46,320
Speaker 6: Okay, even the solar powered pell tours are not but

1904
01:34:46,439 --> 01:34:48,680
Speaker 6: I don't that. I don't think they're the military like

1905
01:34:48,760 --> 01:34:50,120
Speaker 6: gunshot safe ones.

1906
01:34:50,520 --> 01:34:52,559
Speaker 1: No, No, they are. I saw them. What is that?

1907
01:34:52,600 --> 01:34:53,479
Speaker 1: What are you talking about?

1908
01:34:53,920 --> 01:34:59,000
Speaker 9: The tours are high grade uh, like adaptive headphones, so

1909
01:34:59,400 --> 01:35:02,280
Speaker 9: like the ones I saw had like a mic output too.

1910
01:35:02,240 --> 01:35:05,880
Speaker 6: Didn't have a mic just like I think they didn't.

1911
01:35:05,920 --> 01:35:08,559
Speaker 6: They didn't have like the indent to wear under a helmet.

1912
01:35:09,479 --> 01:35:12,120
Speaker 6: I think these were like workplace peltors, because the Peltores

1913
01:35:12,160 --> 01:35:14,479
Speaker 6: make a lot of different models of noise canceling headphones

1914
01:35:14,640 --> 01:35:17,360
Speaker 6: and only certain what only certain ones are used for,

1915
01:35:17,400 --> 01:35:20,640
Speaker 6: like military or like law enforcement or like gunshots suppressing.

1916
01:35:20,800 --> 01:35:24,160
Speaker 9: But it looked to me like they were actually the

1917
01:35:24,160 --> 01:35:26,919
Speaker 9: the pel tours that you get where they're not attached

1918
01:35:26,920 --> 01:35:29,160
Speaker 9: to a band so that you can attach them directly

1919
01:35:29,200 --> 01:35:31,519
Speaker 9: to a helmet, and they had instead attached them to

1920
01:35:31,560 --> 01:35:33,800
Speaker 9: a solar band. Maybe maybe I need to go check

1921
01:35:33,840 --> 01:35:34,080
Speaker 9: on it.

1922
01:35:34,000 --> 01:35:38,439
Speaker 1: Tomorrow to me, but those were and I talked.

1923
01:35:38,280 --> 01:35:40,080
Speaker 9: Them specifically about using it for hunting.

1924
01:35:40,200 --> 01:35:42,559
Speaker 1: Okay, okay, okay. So we found one thing.

1925
01:35:42,760 --> 01:35:46,280
Speaker 9: It was pretty cool, like like headphones that can suppress

1926
01:35:46,760 --> 01:35:49,879
Speaker 9: loud noises but allow you to continue to converse while shooting.

1927
01:35:50,640 --> 01:35:52,719
Speaker 9: That charged themselves so you never need to worry about

1928
01:35:52,720 --> 01:35:55,000
Speaker 9: battery photovoltaic band.

1929
01:35:55,479 --> 01:35:56,960
Speaker 1: It also can be charged.

1930
01:35:56,640 --> 01:35:57,719
Speaker 9: By lights on the inside.

1931
01:35:57,800 --> 01:36:00,000
Speaker 1: That's very cool. Yeah, yeah, that's that's me. We've found

1932
01:36:00,040 --> 01:36:03,000
Speaker 1: with one product everyone, we can wrap the show up. Then, okay,

1933
01:36:03,080 --> 01:36:04,439
Speaker 1: Robert Web can people find you?

1934
01:36:04,520 --> 01:36:07,240
Speaker 9: People can find me at I write okay on Blue

1935
01:36:07,280 --> 01:36:11,120
Speaker 9: Sky and X the Everything app uh And then we

1936
01:36:11,160 --> 01:36:13,200
Speaker 9: have a podcast called It Could Happen. Here we'll be

1937
01:36:13,240 --> 01:36:17,679
Speaker 9: talking more about ce S and where the technology industry

1938
01:36:17,720 --> 01:36:18,360
Speaker 9: is going a.

1939
01:36:18,360 --> 01:36:20,559
Speaker 1: Very good place. Yeah, where can People Find You?

1940
01:36:20,760 --> 01:36:23,640
Speaker 6: Also on It Could happen here with Robert Evans and

1941
01:36:23,840 --> 01:36:29,639
Speaker 6: on Twitter sorry X and Blue Sky at at Hungry

1942
01:36:29,720 --> 01:36:30,520
Speaker 6: bow Tie.

1943
01:36:31,040 --> 01:36:34,320
Speaker 1: And Ed Wick can we find you Big Black Jacobin

1944
01:36:34,720 --> 01:36:38,240
Speaker 1: on Twitter and on Blue Sky and then this machine

1945
01:36:38,320 --> 01:36:42,439
Speaker 1: kills and tech Bubble dot substack dot com and uh,

1946
01:36:42,960 --> 01:36:44,360
Speaker 1: you can't find me at the gym, be you find

1947
01:36:44,400 --> 01:36:45,920
Speaker 1: me at the bank. It's it tron, you find me

1948
01:36:45,920 --> 01:36:49,800
Speaker 1: and it's everything. Uh yeah, I am. I wanted to

1949
01:36:49,800 --> 01:36:52,120
Speaker 1: get you on the show floor. Ed. I can't wait,

1950
01:36:52,240 --> 01:36:54,760
Speaker 1: but I really could. It's so crazy. I don't want

1951
01:36:54,760 --> 01:37:03,560
Speaker 1: to go. I have not been downstairs. Yeah you didrow

1952
01:37:03,800 --> 01:37:07,240
Speaker 1: you want to Okay, everyone, thank you for listening to

1953
01:37:07,320 --> 01:37:10,720
Speaker 1: the wonderful better Offline. Now you'll hear a really like

1954
01:37:10,880 --> 01:37:14,080
Speaker 1: jaunty theme which Madisowski, our producer, did, and a bunch

1955
01:37:14,080 --> 01:37:16,600
Speaker 1: of stuff that you continue to fucking complain about me

1956
01:37:16,720 --> 01:37:18,720
Speaker 1: not updating, which only makes me want to leave it.

1957
01:37:18,840 --> 01:37:21,080
Speaker 9: You should use a AI generated music like and that

1958
01:37:21,120 --> 01:37:24,920
Speaker 9: great uh that great heist video last night personalized.

1959
01:37:25,040 --> 01:37:28,559
Speaker 1: Every listener gets a different outrailer, gets a different outro song.

1960
01:37:28,720 --> 01:37:29,920
Speaker 9: They are all billy joels up.

1961
01:37:29,920 --> 01:37:33,519
Speaker 1: Can you imagine that's the only intro? All right, we're

1962
01:37:33,560 --> 01:37:35,559
Speaker 1: going out now, but just to be clear, like, can

1963
01:37:35,600 --> 01:37:37,759
Speaker 1: you imagine the ship that the people in the forum

1964
01:37:37,840 --> 01:37:40,320
Speaker 1: on the reddit, I'm one hundred years old on the

1965
01:37:40,439 --> 01:37:45,400
Speaker 1: four they're on the message boards about me again. Anyways,

1966
01:37:45,760 --> 01:37:56,960
Speaker 1: thanks for listening everyone, Thank you for listening to Better Offline,

1967
01:37:57,080 --> 01:37:59,479
Speaker 1: the editor and composer of the Better Offline theme song

1968
01:37:59,479 --> 01:38:02,240
Speaker 1: It's Matters. You can check out more of his music

1969
01:38:02,280 --> 01:38:05,920
Speaker 1: and audio projects at Matasowski dot com, M A T

1970
01:38:05,920 --> 01:38:10,400
Speaker 1: T O S O W s ki dot com. You

1971
01:38:10,400 --> 01:38:12,920
Speaker 1: can email me at easy at Better offline dot com

1972
01:38:13,000 --> 01:38:15,320
Speaker 1: or visit Better Offline dot com to find more podcast

1973
01:38:15,360 --> 01:38:18,679
Speaker 1: links and of course my newsletter. I also really recommend

1974
01:38:18,720 --> 01:38:20,640
Speaker 1: you go to chat dot where's youreaed dot at to

1975
01:38:20,760 --> 01:38:23,559
Speaker 1: visit the discord, and go to our slash Better Offline

1976
01:38:23,560 --> 01:38:26,799
Speaker 1: to check out our reddit. Thank you so much for listening.

1977
01:38:27,640 --> 01:38:30,080
Speaker 1: Better Offline is a production of cool Zone Media.

1978
01:38:30,240 --> 01:38:33,080
Speaker 8: For more from cool Zone Media, visit our website cool

1979
01:38:33,160 --> 01:38:36,519
Speaker 8: Zonemedia dot com, or check us out on the iHeartRadio app,

1980
01:38:36,560 --> 01:38:39,240
Speaker 8: Apple Podcasts, or wherever you get your podcasts.