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Speaker 1: Read Natasha Kryle, good to see you. Two things struck

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Speaker 1: me this week in the world of tech. One the

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Speaker 1: NASA launch and to the SpaceX largest I p O

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Speaker 1: of all time read I know you're a bit of

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Speaker 1: a space head.

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Speaker 2: Wait what do you mean by that?

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Speaker 3: Exactly?

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Speaker 4: No, I was excited to see the artibast take off.

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Speaker 4: Did you watch I didn't watch it live.

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Speaker 3: No, shouldn't the astronauts be live streaming now?

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Speaker 2: I think starlink has to get better for that to happen.

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Speaker 1: Well, they should be. They need they need to be,

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Speaker 1: They need to be applying for need to become astronaut

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Speaker 1: influencers and want to get on the on the future.

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Speaker 1: Billion they led space missions like Katie Perry.

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Speaker 3: The first Bishop for creators only.

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Speaker 1: Exactly, Natasha, what is it with with billionaires in space?

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Speaker 5: Oh?

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Speaker 6: You know, it's a core. It's like sleeping under their

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Speaker 6: desk is just a core part of the of the mythology.

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Speaker 1: Okay, let's get into it. Welcome to tech stuff. I'm

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Speaker 1: as Voloscian and this is the week in tech, but

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Speaker 1: I'm joined by three of the most plugged in tech

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Speaker 1: reporters in the world to break out the biggest tech news,

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Speaker 1: decode emerging trends, and debate what actually matters for us.

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Speaker 1: We're joined by Read Abrigotti, Hi, who is the technology

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Speaker 1: here to the semifore I read good to be here.

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Speaker 1: Kyle Shaker, who writes the Infinite Scroll newsletter for The

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Speaker 1: New Yorker.

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Speaker 3: Hello, nice to see you all.

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Speaker 1: And attached to Tiku from the Washington Post. Hey guys,

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Speaker 1: So we'll start with you Kyle. This week, you are

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Speaker 1: particularly taken by slopaganda circulating about the Iran wats. I

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Speaker 1: want to hear all about that. I want to hear

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Speaker 1: what you're saying before that. The New Yorker magazine, where

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Speaker 1: you work, the most hallowed journalistic institution in America, arguably

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Speaker 1: posts or they have to save best of lists at

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Speaker 1: the end of each year, like the best of television,

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Speaker 1: the best of theater, the best of opera. In December,

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Speaker 1: you published the best of slop? So congratulations, what is

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Speaker 1: it with you?

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Speaker 3: Inside man?

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Speaker 7: It was the year in slop and it was a

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Speaker 7: retrospective of all the AI generated garbage that we had

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Speaker 7: to wait through as people on the Internet over the

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Speaker 7: past year. And I think the scariest part of putting

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Speaker 7: that together was realizing how much better everything got, Like

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Speaker 7: the video quality of baseline AI generated stuff was vastly

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Speaker 7: vastly higher at the start of last year as opposed

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Speaker 7: to or at the end of last year as opposed

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Speaker 7: to the start of last year. So I really got

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Speaker 7: a first hand view of that, unfortunately, and thus we're

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Speaker 7: in twenty twenty six when it's better than ever.

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Speaker 1: Do you remember that scene in Harry Potter where there's

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Speaker 1: this kind of boiling cauldron of like something and Dumbledore

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Speaker 1: and Harry there and dumbledon Dumbledore that it puts his

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Speaker 1: wand and then Harry can see all of Voldemort's memories

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Speaker 1: because of this bucket of of churning whatever it is.

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Speaker 1: I feel like AI slop is that for the collective unconscious.

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Speaker 3: I think.

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Speaker 7: So, I mean, we're a left waiting to try to

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Speaker 7: sort of the past decades of stuff, and it's up

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Speaker 7: to anyone, Like whatever anyone can imagine can now become

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Speaker 7: a high production value animation, so which you know, it

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Speaker 7: might sound utopian, but in practice it's actually horrible.

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Speaker 1: So I think what's interesting though this week is that

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Speaker 1: we kind of definitively crossed the rubicon from from slop

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Speaker 1: into slopaganda. I want to play a clip from the

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Speaker 1: ex account of the Iranian Embassy in the Hague, which

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Speaker 1: features cartoon animated Donald Trump at a press conference and

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Speaker 1: what I think are his internal demons.

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Speaker 6: Why did you attack the Monov school? Go on, lie, Lie, Lie.

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Speaker 8: A week.

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Speaker 2: We didn't hit the moknob school.

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Speaker 5: America doesn't have Tomahawk missiles at all, and we care

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Speaker 5: deeply about the Iranian people.

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Speaker 1: They did his voice much worse than SNL that was

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Speaker 1: going on here, Kyle.

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Speaker 7: Well, over the past week or two or a few

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Speaker 7: weeks possibly, we've seen this trickle of AI it generated

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Speaker 7: propaganda from various Iranian sources, and so one popular format

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Speaker 7: that has emerged is Lego videos, which take on the

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Speaker 7: esthetic of the Lego movies, including Batman and the Pharrell biopic,

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Speaker 7: which I never quite understood, but anyway, they use Lego

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Speaker 7: toys to animate the Iranian war, and you know, imagine

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Speaker 7: the White House burning down and Donald Trump with his

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Speaker 7: pants on fire, and hordes of our armies marching on

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Speaker 7: Tel Aviv and Tehran and just like a panopoly of

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Speaker 7: horrifying things, kind of but made of children's toys. And

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Speaker 7: so I was watching these and they're like high production value.

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Speaker 7: They're going super viral. They have a lot of American fans,

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Speaker 7: and I was wondering who was actually making them. So

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Speaker 7: I actually got in touch with the collective of Iranian

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Speaker 7: students and graduates who was putting them together how I

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Speaker 7: mean in the classic social media internet reporter move of

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Speaker 7: scrolling way far back on their social accounts before they

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Speaker 7: got banned, and you know, contacting them that way, and

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Speaker 7: then promptly everything was erased over the weekend because the

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Speaker 7: platforms caught on to what was happening. And yeah, I

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Speaker 7: mean they decided to use this lego aesthetic because it

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Speaker 7: was cute and simple and elicited sympathy for the Iranian

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Speaker 7: people and kind of cast this like moral quality over

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Speaker 7: their whole concept. And they told me that they could

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Speaker 7: go from a highly worked out script like these are

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Speaker 7: very written through videos. They're very complicated, and they're plotting

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Speaker 7: to a full animation in twenty four hours. So that's

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Speaker 7: the that's the Iranian lego propaganda machine.

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Speaker 1: Natasha Reid, have you been have you been experiencing these

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Speaker 1: videos or the slop againda coming out of our own

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Speaker 1: of our own way.

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Speaker 2: I have seen the lego videos.

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Speaker 4: I was I was, I, I'm glad that you did

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Speaker 4: the reporting because I was wondering the same thing.

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Speaker 2: It's like, wait, who is making this?

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Speaker 4: And like clearly it's coming from like the Iranian government

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Speaker 4: in some capacity, but like the Ayatola is definitely not good,

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Speaker 4: like are.

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Speaker 8: Lego sycrilegiust or something like you know, it's it's there's

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Speaker 8: they're speaking the language that we all speak, right, Like

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Speaker 8: there's a lot of cognitive dissonance there watching the videos.

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Speaker 6: That's so interesting that you got that they talk to

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Speaker 6: you about the scripts, because that is what I've been

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Speaker 6: wondering with both like the propaganda legos and then also

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Speaker 6: those low grade fruit corn that is just also populating

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Speaker 6: my feed. I'm just like that there's that and then

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Speaker 6: there's something else. I don't know. I keep sending them

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Speaker 6: to my coworkers, so I might be no, but like

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Speaker 6: everyone has millions and millions, and I was just like,

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Speaker 6: oh my gosh, what if instead of watermarking in some way,

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Speaker 6: you were mandated to put your prompt in any like

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Speaker 6: AI generated thing. I really really want to know like

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Speaker 6: how involved the human was. So that's like super interesting

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Speaker 6: that they that they wrote out these scripts which are

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Speaker 6: so appealing to Americans and so americanized that I was like,

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Speaker 6: is it Ironians? But looks like you answered that question.

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Speaker 1: Well, I want to ask that question. I want, I want,

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Speaker 1: I want to ask that question about who's this ready for.

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Speaker 1: But before that, I'm not sure if any of you

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Speaker 1: saw the Chinese one, which is like a mini animated

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Speaker 1: doc with the Great White Eagle, and basically it was

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Speaker 1: the best prima on the straits of Hormus, the underlying

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Speaker 1: geopolitical forces governing that what's going on. I mean, it was,

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Speaker 1: it was. It was an amazing distillation like everything I've

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Speaker 1: read in like you know, smart places in the last

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Speaker 1: couple of weeks, as a six minute animated video with

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Speaker 1: Donald Trump as a great White eagle and the new

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Speaker 1: Ia Toler as a black household cat with red eyes.

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Speaker 1: But like it was very tiny, scripted. I have to say,

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Speaker 1: it was impressive. Information density was very compelling.

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Speaker 4: Let's take the let's take the war out of it.

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Speaker 4: Though I know you said this sounds utopian, but it's not.

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Speaker 4: But it kind of is like the imagine unlocking all

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Speaker 4: this creativity that's in like some probably I'm I'm imagining

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Speaker 4: them as like kids, you know, young people in Iran

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Speaker 4: built making these videos who've like, you know, never in

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Speaker 4: their wildest dreams, so they've been able to make something

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Speaker 4: like this and now they can. And you know, of

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Speaker 4: course like there's this is under terrible circumstances, but like

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Speaker 4: in a in another world, it's like they're just you know,

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Speaker 4: they're just making entertaining videos and like, hopefully we have

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Speaker 4: ways to bring this, you know, the good stuff to

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Speaker 4: the top and keep the slop, you know.

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Speaker 3: And this is the good stuff.

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Speaker 7: Like I'm now I'm imagining like the equivalent of Lonely

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Speaker 7: Island or college humor or whatever, but in AI slop videos.

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Speaker 7: But that's what was kind of striking about the lego videos.

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Speaker 7: I think they look so good, like they're really there's.

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Speaker 1: Not really AI slop. Like when I think about AI slop,

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Speaker 1: I think of like a kind of like an octopus

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Speaker 1: with like a cat coming out of it and then

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Speaker 1: going on fire and then living under the sea.

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Speaker 2: Is good and the new slop is good, isn't sloppy?

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Speaker 7: Yeah, Well, it just struck me that, I mean, almost

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Speaker 7: anyone on the Internet now has access to similar AI models,

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Speaker 7: like whether it's open source or a cloud pro subscription

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Speaker 7: or or what Sea dance, the Chinese video generation model.

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Speaker 7: Anyone can access these and they're proliferating faster every single day,

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Speaker 7: and now anyone can make the leg movie in one day.

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Speaker 7: And I think we're like only starting to imagine the

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Speaker 7: consequences of that. As Reid was saying, it can unlock

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Speaker 7: tons of creativity, but it's also this cognitive dissonance of

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Speaker 7: is this piece of media valuable or meaningful or not?

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Speaker 6: Yeah, when you said utopia and like my mind went

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Speaker 6: straight to what about the like click farm equivalents of

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Speaker 6: Like so there's just like, you know, people trapped in

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Speaker 6: an Internet cafe in the Philippines like kind of making

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Speaker 6: individualized propaganda for all of us all day.

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Speaker 1: And it's actually just before we come out of this story,

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Speaker 1: and I don't want to ask you about some of

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Speaker 1: your previous reporting on deep fakes and the horm they

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Speaker 1: cause I mean there was obviously the deep fakes non

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Speaker 1: consensual pornography is like it's a horrible story and a

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Speaker 1: horrible issue. There was a fear that deep fakes would

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Speaker 1: also become kind of tools of like political chaos sewing.

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Speaker 1: What seems to have happened is quite the opposite, where

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Speaker 1: in fact, no one really cares about deep faces. In

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Speaker 1: the political realm, people actually want like the most almost

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Speaker 1: absurdist animations which are clearly not trying to be real.

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Speaker 1: I wonder what's going on there.

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Speaker 2: Yeah.

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Speaker 6: I feel like we started to notice this with elections

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Speaker 6: in the global South. In Southeast Asia, you know that.

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Speaker 6: I know my editors in DC were extremely concerned about

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Speaker 6: like some kind of election manipulation, but instead people ended

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Speaker 6: up using it sort of like oh, you have access

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Speaker 6: to photoshop and like all of a sudden, some a

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Speaker 6: bunch of humanities majors and I don't know, political operatives

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Speaker 6: can do whatever they want. So in India they were

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Speaker 6: like splicing candidates into Bollywood videos and they were making

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Speaker 6: candidates like like sweet cartoony images for like a for

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Speaker 6: a strong man candidate. So I I yeah, I thought

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Speaker 6: it was interesting. Kyle. I'd love to know what you

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Speaker 6: thought about this that it almost seemed to like diffuse

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Speaker 6: the tension. Like there were, of course those videos where

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Speaker 6: you see the bombs heading at the Statue of Liberty,

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Speaker 6: but it felt like it's like we're all in this

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Speaker 6: together with this one crazy.

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Speaker 7: I don't know, sort of specifying that the Statue of

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Speaker 7: Liberty in this case is like an evil goat demon ball.

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Speaker 7: Yeahs the ball statues of the Statue of Liberty. But yeah,

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Speaker 7: I think that's like the cartoonishness is the appeal. And

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Speaker 7: I think what brings so many people around the world

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Speaker 7: together with these beautiful videos is their hatred of Donald Trump,

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Speaker 7: and everyone's just in comprehension of what is even going

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Speaker 7: on in this war in the strait of our moves.

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Speaker 7: Is it happening, is it not happening, is it over?

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Speaker 7: Is it just beginning? Literally no one knows, so it

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Speaker 7: might as well be legos.

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Speaker 6: I mean, the way that they worked in the like

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Speaker 6: you know Epstein files, is the reason that he started

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Speaker 6: this war was just like you couldn't I mean imagine

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Speaker 6: imagine something like that around the Iraq War.

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Speaker 1: In fact, on the Iran on the Iran video I

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Speaker 1: played at the beginning, which we only heard the audio

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Speaker 1: on the ending title of title card on that on

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Speaker 1: that v is actually says Epstein's client, but an attached

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Speaker 1: to changing gears and but staying in the world of

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Speaker 1: film and TV, you were recently featured in a documentary

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Speaker 1: that's got a lot of press called the AI doc

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Speaker 1: or How I became an Apocaloptimist apocaly Optimist, and I

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Speaker 1: want to play a part of Oprah's interview with one

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Speaker 1: of the central voices in that documentary, Aseruskin from the

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Speaker 1: Center for Humane Technology.

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Speaker 6: How could AI physically eliminate the human race?

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Speaker 5: It's actually hard to imagine all the ways AIS could

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Speaker 5: wipe humans out. AI is already better than almost all

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Speaker 5: humans are doing cyber hacking, and so you could imagine

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Speaker 5: one of the things that an AI could do is

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Speaker 5: take out all electricity, water, hospitals, transportation across every country

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Speaker 5: in the world all at once. Now, that doesn't wipe

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Speaker 5: us all out. Where you could imagine the amount of

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Speaker 5: damage that would do.

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Speaker 1: You shouldn't chaos and crazy exactly.

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Speaker 5: And we're only you know, five missed meals away from anarchy?

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Speaker 3: Did you say, we're only five minus meals away from HANARNT?

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Speaker 8: Yeah.

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Speaker 5: I think about what happens in New York City if

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Speaker 5: you can't get food.

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Speaker 2: Yeah, I don't think a lot of people have thought

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Speaker 2: about that.

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Speaker 1: Yeah, the soundtrack is particularly dystopian without without any video.

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Speaker 1: But Natija tell us about this this uh, this film

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Speaker 1: on your role in it my role was minuscule.

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Speaker 6: I actually finished watching till the end yesterday and I

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Speaker 6: have two sentences, so I would not I would not

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Speaker 6: say I was featured in the in the piece, but yeah, it's.

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Speaker 1: You're talking about right, You're you're an expert in the film.

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Speaker 6: Yeah, but like for two seconds, there's many men like

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Speaker 6: basically read. You probably have interviewed half the people on

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Speaker 6: it at least or or more, a lot a lot

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Speaker 6: of familiar faces, and it hasn't been doing that well

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Speaker 6: at the box office. It looks like, however, like millions

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Speaker 6: of views for the trailer and the press around it

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Speaker 6: has been They've had people who are on it on

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Speaker 6: the Daily Show this week. This this Brah clip that

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Speaker 6: you just played, it's really actually in the clip when

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Speaker 6: she says like we're five missed meals away from anarchy,

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Speaker 6: they actually show the text like across the across the screen,

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Speaker 6: which I just thought was like wow. And that's the

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Speaker 6: little clip that starts this hour long program too. She

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Speaker 6: talks about like how could AI physically eliminate us all?

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Speaker 6: And I'm just like kind of transported back to twenty

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Speaker 6: twenty three. It's just really interesting to have these conversations

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Speaker 6: about some of these doomstay scenarios that feel very divorced

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Speaker 6: from you know, the current, like some of the very

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Speaker 6: real ways that we're watching chaos unfold. You know, there's

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Speaker 6: nothing about like what if two egomaniacal men are having

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Speaker 6: a contract dispute or you know, what if what if

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Speaker 6: your president is trying to distract from from the Epstein files.

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Speaker 6: Like it just feels like we're kind of back to that,

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Speaker 6: but you know what I mean, like back to that

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Speaker 6: like post chat GPT era of introducing the public to

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Speaker 6: existential risks.

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Speaker 1: It's also interesting because Oprah did an ABC special last

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Speaker 1: year with a lot of the same big you know,

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Speaker 1: with Sam Waltman and Dario and all the all the

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Speaker 1: big names in this industry. And when that came out,

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Speaker 1: I was struck by this kind of huge not dissonance

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Speaker 1: is the wrong word, but this huge ocean between how

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Speaker 1: people you know, like you all who cover this industry

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Speaker 1: and how people in Silicon Valley talk and think about

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Speaker 1: what's going on. And then I mean, Oprah is a

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Speaker 1: relatively good gauge for like where the wider conversation is maybe,

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Speaker 1: and so it's just I mean, this does feel like

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Speaker 1: frankly quite dated, and yet at the same time, to

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Speaker 1: your point, it's gain millions of views on YouTube and

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Speaker 1: it's all over Daily Show and the morning shows. Yeah,

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Speaker 1: what's like, who's the who's the movie for? Actually? And

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Speaker 1: what does the marketing of the movie say about it?

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Speaker 6: Who's the movie for? I think that the director was

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Speaker 6: trying to make it for the every person who is

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Speaker 6: feeling this like un you know, kind of amorphous anxiety,

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Speaker 6: and the point is to try to figure out how

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Speaker 6: you're supposed to emotionally approach this technology, like how you

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Speaker 6: know you understand that something strange is coming, you don't

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Speaker 6: know what it is, and you don't know what it

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Speaker 6: means for you and your family. And I think, you know,

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Speaker 6: I was trying to think about, like, okay, net net

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Speaker 6: is the documentary better for AI literacy? And I think

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Speaker 6: you do get a better sense of like the initial

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Speaker 6: training phases, you know, they talk a lot about like

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Speaker 6: how much of the Internet is put into it, but

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Speaker 6: then there's like no discussion of the amount of work

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Speaker 6: that the companies do, the amount of product making decisions,

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Speaker 6: the amount of data that they have to commission in

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Speaker 6: order for it to get better and better and it

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Speaker 6: just like kind of removes agency from the companies in

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Speaker 6: this way, like you know, where it seems inevitable and

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Speaker 6: it's just really interesting having spoken to a lot of

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Speaker 6: the people that were featured in the documentary, like you know,

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Speaker 6: it's not misrepresenting them, but like if you give if

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Speaker 6: you give these people a chance to zoom in on

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Speaker 6: something more concrete and not take the you know, five

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Speaker 6: thousand foot view, they're very chatty and like would have

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Speaker 6: given you an earfull. So I you know, I'm excited

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Speaker 6: for that movie to come out.

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Speaker 4: I guess how much do you think it actually helps

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Speaker 4: people with these emotions versus like just sort of like

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Speaker 4: feeds it, you know, just just feeds that sort of

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Speaker 4: like anxiety and fear that people have that I think

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Speaker 4: I think is actually largely irrational, to be honest, You.

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Speaker 2: Do what do you? Yeah?

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Speaker 1: I do I do with the doom the doom a pond?

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Speaker 1: This will kill us all all that, this will make labor,

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Speaker 1: you know, tremendously strained or which part of it do which

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Speaker 1: part of it do you think is irrational?

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Speaker 4: I think I think it's all irrational, to be honest.

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Speaker 4: I mean, we don't know, like the thing is. It's

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Speaker 4: like we're just talking about now. It's like we thought,

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Speaker 4: you know, the defas we're gonna be one thing, and

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Speaker 4: turned out there another thing. We you know, there's gonna

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Speaker 4: be downsides to AI, like to just or let's just

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Speaker 4: call it software automation, right, Like that's what it is.

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Speaker 4: There's gonna be downsides to this, like massive build out

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Speaker 4: of data centers and like reorienting the economy around this

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Speaker 4: thing these tokens, but like we don't really know what

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Speaker 4: that is yet, And I think sitting back and like

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Speaker 4: worrying about it is sort of you know, it's it's

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Speaker 4: like the old cliche. It's like, you know, paying an

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Speaker 4: interest on a debt you may never owe. So that's

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Speaker 4: kind of my view on all this stuff. But I

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Speaker 4: don't know if this documentary you think. I haven't seen it,

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Speaker 4: so I'm just curious, like does it help with that,

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Speaker 4: does it help clarify the situation or does it just

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Speaker 4: sort of like feeding the anxiety more.

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Speaker 6: I mean I think that there is I guess like

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Speaker 6: there is room to be concerned and to worry, But

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Speaker 6: it's just so the industry voice like it's basically only

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Speaker 6: asking tech people what could potentially happen. And I feel like,

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Speaker 6: if you want to think about how human civilization has

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Speaker 6: adjusted to massive change, you talk to historians, like you

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Speaker 6: basically talk to almost anybody besides the people who are

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Speaker 6: building the technology. Like he's he's obviously very you know,

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Speaker 6: he does it from a first person perspective, the director,

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Speaker 6: and it's like, you know what, I got to talk

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Speaker 6: to the CEOs and it's like there's no shortage of

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Speaker 6: footage of the CEOs talking about this, like this is

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Speaker 6: it's really not. It's hard to get him to stop

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Speaker 6: yapping in some ways, Like a lot of these guys

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Speaker 6: are on a constant press tour, and I just feel

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Speaker 6: like I would love to hear from people who study

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Speaker 6: labor markets, how you know how change traditionally unfold, Like

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Speaker 6: what are different scenarios in that way of thinking. I

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Speaker 6: just feel like the like the buy that is proposed

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Speaker 6: between like utopia and dystopia, I think we already know

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Speaker 6: like who benefits from that. It's you know, it makes

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Speaker 6: the technology sound inevitable and powerful in a certain way.

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Speaker 6: And it's just we have a lot of data now

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Speaker 6: it's twenty twenty six, Like we can we can look

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Speaker 6: at how successful is this worldview? How successful has this

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Speaker 6: approach been in predicting the harms we've already seen?

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Speaker 1: Do they ask you? Did they ask you those kinds

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Speaker 1: of questions during the interview when you would be interviewed

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Speaker 1: for the film, like what was the what was the

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Speaker 1: tenor of what you were being asked to contribute?

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Speaker 6: I think I might have been pretty early because I

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Speaker 6: did suggest a lot of people. They did make me

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Speaker 6: explain like effective altruism and like give them the like

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Speaker 6: I remember using my hands a lot for like the

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Speaker 6: Dumer Landscape. And then they had to call me back

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Speaker 6: after Sam was blipped out for a second to ask

402
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Speaker 6: like what was really going on? Is it because you know,

403
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Speaker 6: like Q star they had something And I was like no,

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Speaker 6: it's very per very interpers.

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Speaker 1: A open AI for like twenty four hours, right yeah.

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Speaker 6: Yeah, yeah, yeah yeah, week or I don't read. You

407
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Speaker 6: probably remember it better than I a few days.

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Speaker 2: I just remember it ruined my Thanksgiving Kyle.

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Speaker 1: Have you have you bought your tickets for the movie

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Speaker 1: this weekend?

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Speaker 3: I have not bought a ticket yet.

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Speaker 7: I have seen it all over social media, like this

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Speaker 7: seems to be the media artifact of AI right now.

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Speaker 7: And it struck me as very vintage, like it's this

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Speaker 7: kind of hyped up dumorus like reel of people saying

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Speaker 7: that this is going to take over the world and

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Speaker 7: destroy things. And I don't know, I feel like the

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Speaker 7: current concerns are less about AI God killing us all

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Speaker 7: and more about the economy redirecting toward data centers and

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Speaker 7: accelerating climate change, and then you know, destroying the earth

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Speaker 7: that way is a kind of secondary effect.

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Speaker 3: So yeah, I don't know.

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Speaker 7: It felt like a bit of I don't know, super

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Speaker 7: sincere hyping up And as Natasha was talking about, I

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Speaker 7: think the CEOs are incentivized to make this technology appear

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Speaker 7: as powerful and world conquering as possible, and they're not

427
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Speaker 7: necessarily going to be the best sources for you on

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Speaker 7: how will this affect a normal person?

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Speaker 4: And even on the doomsday stuff, I just don't think

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Speaker 4: these it didn't seem like they had much of an

431
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Speaker 4: imagination there either, Like talk to the have you read

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Speaker 4: you know, if anyone builds it, everyone dies.

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Speaker 2: You guys read that book.

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Speaker 4: It's like they come out with like much better scenarios

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Speaker 4: for how AI kills us all, Like, you know, it's

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00:23:23,960 --> 00:23:29,120
Speaker 4: just like a Zukowsi, Yeah, exactly, like they're They're like, yeah,

437
00:23:29,160 --> 00:23:31,040
Speaker 4: I mean, it's just going to like co opt humans

438
00:23:31,080 --> 00:23:33,679
Speaker 4: and eventually of the humans will help them build some

439
00:23:33,840 --> 00:23:36,719
Speaker 4: bioweapon that we won't even realize we have for like

440
00:23:37,240 --> 00:23:40,440
Speaker 4: a generation and eventually we all die. Like it's it's

441
00:23:40,480 --> 00:23:42,840
Speaker 4: a much you know, Like I feel like, if you're

442
00:23:42,840 --> 00:23:44,800
Speaker 4: going to go doomsday, like go all the way.

443
00:23:45,560 --> 00:23:45,800
Speaker 2: You know.

444
00:23:46,119 --> 00:23:47,760
Speaker 1: This is why I said that you were a space

445
00:23:47,840 --> 00:23:50,199
Speaker 1: at the beginning of the episode read because I remember

446
00:23:50,680 --> 00:23:54,680
Speaker 1: the sci fi you referred to when corporations not controlled

447
00:23:54,680 --> 00:23:57,920
Speaker 1: by governments can create an extractive economy in space and

448
00:23:58,600 --> 00:24:00,760
Speaker 1: take people there and then keep them in slaved in space.

449
00:24:01,680 --> 00:24:05,000
Speaker 2: That's right, that's right, like the company from Aliens, Right.

450
00:24:04,960 --> 00:24:09,119
Speaker 3: What if they make alien you know, like that's so

451
00:24:09,280 --> 00:24:09,680
Speaker 3: much better.

452
00:24:09,920 --> 00:24:12,320
Speaker 4: I mean I asked one of the authors of that

453
00:24:12,359 --> 00:24:16,600
Speaker 4: book on stage once, like he Nate Sores, and I'm like,

454
00:24:16,680 --> 00:24:18,760
Speaker 4: what do you think about This was like before the whole,

455
00:24:19,119 --> 00:24:22,480
Speaker 4: before I broke that whole like Pentagon Anthropics story, but

456
00:24:22,560 --> 00:24:26,000
Speaker 4: like I was interested in the topic of if autonomous weapons,

457
00:24:26,000 --> 00:24:27,639
Speaker 4: and I'm like, what do you think of autonomous weapons?

458
00:24:27,680 --> 00:24:29,320
Speaker 4: And it was like a layup I'm like, he's gonna

459
00:24:29,359 --> 00:24:32,000
Speaker 4: just say this is so crazy, I can't believe we

460
00:24:32,040 --> 00:24:33,960
Speaker 4: would ever do this, and he's like, no, I'm pretty

461
00:24:34,040 --> 00:24:37,479
Speaker 4: much for autonomous weapons, like AI doesn't need autonomous weapons

462
00:24:37,480 --> 00:24:40,479
Speaker 4: to kill us, and like they could actually help reduce

463
00:24:40,720 --> 00:24:43,879
Speaker 4: human deaths in the battlefield, and like wow, like that

464
00:24:43,960 --> 00:24:45,080
Speaker 4: came full circle, Like.

465
00:24:46,080 --> 00:24:50,960
Speaker 1: I read I read Sebastian Amountabie's biography of Demis hasbist

466
00:24:51,160 --> 00:24:53,480
Speaker 1: this week because he was on the show Sebastian a

467
00:24:53,560 --> 00:24:56,120
Speaker 1: couple of days ago. And yeah, apparently the way he

468
00:24:56,320 --> 00:24:59,720
Speaker 1: impressed Elon ear Leon was saying to Elon, by the way,

469
00:25:00,600 --> 00:25:05,480
Speaker 1: going to space won't save us from superintursient AIS because

470
00:25:05,480 --> 00:25:07,800
Speaker 1: they'll be able to build rockets too and kill us

471
00:25:07,840 --> 00:25:13,760
Speaker 1: while we're up there. But just a doubt, just to

472
00:25:13,800 --> 00:25:15,439
Speaker 1: come out of this story, I want to pick up

473
00:25:15,440 --> 00:25:18,119
Speaker 1: on a word you use, Kyle, which is sincere, and

474
00:25:18,359 --> 00:25:23,639
Speaker 1: certainly the documentary comes across as very sincere. However, you know,

475
00:25:23,720 --> 00:25:26,879
Speaker 1: there is this odd thing where these AI doomers and

476
00:25:26,960 --> 00:25:30,280
Speaker 1: AI boosters are kind of two sides of the same coin,

477
00:25:30,880 --> 00:25:33,040
Speaker 1: and the doomers in a sense, okay, maybe they're not

478
00:25:33,080 --> 00:25:36,719
Speaker 1: becoming billionaires by building AI companies, but they're certainly becoming

479
00:25:36,800 --> 00:25:40,399
Speaker 1: amongst the most sought after media talking heads in the world,

480
00:25:40,880 --> 00:25:43,440
Speaker 1: and so like, is it truly in good faith?

481
00:25:43,960 --> 00:25:46,000
Speaker 3: I mean, from my perspective, it's not.

482
00:25:46,200 --> 00:25:48,520
Speaker 7: I think there is a hype cycle and people are

483
00:25:48,760 --> 00:25:52,160
Speaker 7: caching in on different sides of the hype cycle. Meanwhile,

484
00:25:52,240 --> 00:25:55,560
Speaker 7: like Anthropic and Open AI are cruising toward IPOs that

485
00:25:55,640 --> 00:26:00,440
Speaker 7: will make many millionaires and billionaires and that will change things.

486
00:26:00,720 --> 00:26:03,600
Speaker 7: You know, there are like more eminent consequences I think

487
00:26:03,640 --> 00:26:07,160
Speaker 7: that we can talk about instead of total dumer apocalypse.

488
00:26:08,000 --> 00:26:12,240
Speaker 6: It's interesting because the whole documentary is about in incentives

489
00:26:12,840 --> 00:26:16,760
Speaker 6: and you're not, like, there's very little examination of the

490
00:26:16,800 --> 00:26:20,679
Speaker 6: incentives of the people that got the most airtime. And

491
00:26:20,760 --> 00:26:24,200
Speaker 6: I think there is this sense that it's just it's

492
00:26:24,200 --> 00:26:27,719
Speaker 6: hard to operate in AI, like writing about AI without

493
00:26:27,800 --> 00:26:31,480
Speaker 6: kind of knowing where everybody is coming from. You kind

494
00:26:31,480 --> 00:26:34,479
Speaker 6: of have to have this map in your head because

495
00:26:34,520 --> 00:26:37,920
Speaker 6: I think it looks like there are many different voices

496
00:26:37,960 --> 00:26:41,159
Speaker 6: saying the same thing, and so there is consensus, but

497
00:26:42,160 --> 00:26:46,679
Speaker 6: you know, many of those people are from policy groups

498
00:26:46,680 --> 00:26:51,800
Speaker 6: that are trying to influence legislators towards a specific view,

499
00:26:52,200 --> 00:26:56,639
Speaker 6: like they share a lot of similarity. So you know,

500
00:26:56,880 --> 00:26:59,800
Speaker 6: I just I wish we would move away from from

501
00:27:00,240 --> 00:27:05,200
Speaker 6: looking at a person's like kind of personal politics and

502
00:27:05,320 --> 00:27:09,320
Speaker 6: just look at like the CEO's actions A and then

503
00:27:09,520 --> 00:27:13,560
Speaker 6: for these kind of advocates, look at you know, where

504
00:27:13,600 --> 00:27:15,879
Speaker 6: they're coming from. You know, if they're giving you a

505
00:27:15,920 --> 00:27:20,000
Speaker 6: blackmail scenario from the anthropic paper, to what end and

506
00:27:20,880 --> 00:27:24,400
Speaker 6: how does that like reframe how you think about what

507
00:27:24,520 --> 00:27:29,000
Speaker 6: policies to put forward. Because this is aimed at policymakers,

508
00:27:29,640 --> 00:27:31,280
Speaker 6: I think we should think about it as its own

509
00:27:31,359 --> 00:27:32,280
Speaker 6: kind of propaganda.

510
00:27:32,680 --> 00:27:36,280
Speaker 1: That's a really interesting point you make, because obviously in

511
00:27:36,320 --> 00:27:39,560
Speaker 1: the Trump era, it's sort of tempting to think, well,

512
00:27:39,600 --> 00:27:43,160
Speaker 1: like the train has left the station, they'll never be regulation,

513
00:27:43,480 --> 00:27:46,399
Speaker 1: Like we've just like essentially decided that there's going to

514
00:27:46,400 --> 00:27:50,479
Speaker 1: be unlimited, unregulated technology. But of course, like you know,

515
00:27:50,560 --> 00:27:53,840
Speaker 1: there's midterms coming up this year, there's two years time

516
00:27:53,840 --> 00:27:57,280
Speaker 1: there's another presidential election, and so are you suggesting in

517
00:27:57,280 --> 00:27:59,879
Speaker 1: some sense this is kind of building towards a co

518
00:28:00,720 --> 00:28:04,480
Speaker 1: of a policy driven tech lash post election.

519
00:28:04,320 --> 00:28:07,600
Speaker 6: Or yes, I mean this is you know, like some

520
00:28:07,720 --> 00:28:11,080
Speaker 6: of the people who are represented there, they are affiliated

521
00:28:11,119 --> 00:28:14,880
Speaker 6: with groups who are arguing that there is massive bipartisan

522
00:28:14,960 --> 00:28:19,560
Speaker 6: support for a long list of legislation. I wouldn't say

523
00:28:19,600 --> 00:28:22,439
Speaker 6: it's like a crisp kind of policy proposal, but you know,

524
00:28:22,520 --> 00:28:28,000
Speaker 6: they're meeting together with faith groups, with children's advocacy groups,

525
00:28:28,040 --> 00:28:32,280
Speaker 6: with unions and saying like we all have common cause

526
00:28:32,440 --> 00:28:37,600
Speaker 6: in regulating in regulating AI. So I just think that

527
00:28:37,680 --> 00:28:39,640
Speaker 6: this is the tip of the spear, and we should

528
00:28:39,640 --> 00:28:46,520
Speaker 6: pay attention to where these where these narratives are pointing government,

529
00:28:46,640 --> 00:28:50,160
Speaker 6: and where these narratives might end up affecting all of us.

530
00:28:52,600 --> 00:28:54,640
Speaker 1: We're going to take a short break now before we

531
00:28:54,720 --> 00:28:58,640
Speaker 1: come back to celebrate Apple's fiftieth birthday by asking what

532
00:28:58,680 --> 00:29:16,840
Speaker 1: comes next for the second largest company in America. Welcome

533
00:29:16,840 --> 00:29:19,560
Speaker 1: back to tech stuff. Read is kind of incredible. Apple's

534
00:29:19,560 --> 00:29:22,720
Speaker 1: been around for fifty years. I mean it started just

535
00:29:22,800 --> 00:29:25,800
Speaker 1: after the original Moon landings, which is kind of crazy

536
00:29:25,840 --> 00:29:30,120
Speaker 1: to think about. Wednesday, April first, Apple celebrated this milestone

537
00:29:30,120 --> 00:29:33,479
Speaker 1: by putting on a statement titled fifty years of Thinking

538
00:29:33,520 --> 00:29:37,680
Speaker 1: Different and amidst the praise of misfits, rebels, and troublemakers,

539
00:29:38,240 --> 00:29:41,800
Speaker 1: there is a telling quote at Apple, We're more focused

540
00:29:41,840 --> 00:29:45,920
Speaker 1: on building tomorrow than remembering yesterday. What does that mean?

541
00:29:46,160 --> 00:29:49,000
Speaker 4: Yeah, I mean usually when you turn fifty in silicon value,

542
00:29:49,040 --> 00:29:50,720
Speaker 4: you don't tell anybody, like you try to keep it

543
00:29:50,800 --> 00:29:51,280
Speaker 4: a secret.

544
00:29:51,320 --> 00:29:55,200
Speaker 2: But that was looks mixing. It's kind of interesting.

545
00:29:56,080 --> 00:30:01,800
Speaker 4: No, I think I think there's there's a fascinating, fascinating

546
00:30:01,840 --> 00:30:05,240
Speaker 4: happening with Apple right now where they basically missed AI.

547
00:30:05,560 --> 00:30:05,720
Speaker 2: Right.

548
00:30:05,800 --> 00:30:08,880
Speaker 4: They're sort of like they were they were caught. You know,

549
00:30:08,920 --> 00:30:11,240
Speaker 4: I don't I don't know how that happened, but they

550
00:30:11,240 --> 00:30:14,320
Speaker 4: didn't see this revolution happening. I think had something to

551
00:30:14,320 --> 00:30:16,880
Speaker 4: do with being in Kooper Tino inside this like spaceship

552
00:30:16,920 --> 00:30:21,640
Speaker 4: building and not going outside and the future right. But

553
00:30:21,680 --> 00:30:25,240
Speaker 4: I but I think that like the defense of Apple

554
00:30:25,360 --> 00:30:28,440
Speaker 4: from from the Apple fanboy crowd, which they're you know,

555
00:30:28,480 --> 00:30:30,760
Speaker 4: they're very their many, and I'll probably get hate mail

556
00:30:30,800 --> 00:30:34,360
Speaker 4: for even saying this, but it's like, you know, look

557
00:30:34,520 --> 00:30:36,840
Speaker 4: they've yeah, I mean, Apple's great at this. They just

558
00:30:36,920 --> 00:30:40,440
Speaker 4: watch technology develop and then they just jump on top

559
00:30:40,480 --> 00:30:42,880
Speaker 4: of it and like and and you know, and benefit

560
00:30:42,920 --> 00:30:45,560
Speaker 4: from it. And I think that's like a very lazy

561
00:30:45,600 --> 00:30:48,160
Speaker 4: defense of of what's happening, and it's and the other

562
00:30:48,200 --> 00:30:50,680
Speaker 4: thing is like, well, you've got this phone, and you

563
00:30:50,720 --> 00:30:52,760
Speaker 4: know they're gonna just like that, They're gonna be able

564
00:30:52,760 --> 00:30:54,959
Speaker 4: to run all these AI models on the device, and

565
00:30:55,040 --> 00:30:56,800
Speaker 4: so that's going to be a huge advantage for Apple.

566
00:30:56,840 --> 00:30:59,200
Speaker 4: And it's like, I don't think that's really how it's

567
00:30:59,200 --> 00:31:03,040
Speaker 4: gonna work. I mean, I can't, I don't. It never

568
00:31:03,160 --> 00:31:06,040
Speaker 4: helps in the tech industry to like miss a technology

569
00:31:06,080 --> 00:31:08,200
Speaker 4: wave like we've seen companies do it. I'm not saying

570
00:31:08,200 --> 00:31:12,640
Speaker 4: Apple's gonna disappear overnight or anything like that, but you know,

571
00:31:12,720 --> 00:31:15,280
Speaker 4: like the reason people buy iPhones is not because it

572
00:31:15,320 --> 00:31:18,680
Speaker 4: has some great hardware or is a piece of great hardware.

573
00:31:18,760 --> 00:31:22,080
Speaker 2: It's because they're locked into the ecosystem, right. It's it's they.

574
00:31:21,960 --> 00:31:24,000
Speaker 4: Don't want to be a green bubble or name your

575
00:31:24,080 --> 00:31:27,080
Speaker 4: you know, the photo sharing product or something like that.

576
00:31:27,240 --> 00:31:29,840
Speaker 4: But you know, Apple doesn't know what the like, we

577
00:31:29,920 --> 00:31:32,160
Speaker 4: don't know what the on device like, what the edge

578
00:31:32,200 --> 00:31:34,960
Speaker 4: compute's going to look like. That's necessary to make you know,

579
00:31:35,000 --> 00:31:39,800
Speaker 4: whatever this future on device AI is. And Apple can't

580
00:31:39,960 --> 00:31:42,280
Speaker 4: move very quickly with its phones because it sells so

581
00:31:42,360 --> 00:31:44,560
Speaker 4: many of them, so like when it comes to like

582
00:31:44,640 --> 00:31:47,320
Speaker 4: new hardware, that's why they're always like many years behind

583
00:31:47,360 --> 00:31:49,960
Speaker 4: Samsung on the hardware because Samsung doesn't have as big

584
00:31:50,000 --> 00:31:52,440
Speaker 4: of an install based so they don't need to sell

585
00:31:52,760 --> 00:31:55,680
Speaker 4: you know, millions and millions of these things immediately when

586
00:31:55,680 --> 00:31:57,800
Speaker 4: they come out with a new product. So it's gonna

587
00:31:57,800 --> 00:32:01,239
Speaker 4: be really, really hard. I think for Apple too, you know,

588
00:32:01,400 --> 00:32:04,080
Speaker 4: the next fifty years, I think, I think might be tough.

589
00:32:04,360 --> 00:32:06,520
Speaker 1: I can see Kyle. I can see Kyle smiling, and

590
00:32:06,680 --> 00:32:08,720
Speaker 1: I think he might be drafting some hate mail. Yeah.

591
00:32:08,760 --> 00:32:11,480
Speaker 7: I was just remembering the recent marketing campaigns for the

592
00:32:11,560 --> 00:32:15,400
Speaker 7: latest iPhone models, and they just all promised various AI

593
00:32:15,440 --> 00:32:18,520
Speaker 7: functionality and just did not deliver on it at all.

594
00:32:19,040 --> 00:32:20,680
Speaker 3: Like I when I bought.

595
00:32:20,440 --> 00:32:23,400
Speaker 7: My most recent iPhone, I kind of knew the AI

596
00:32:23,600 --> 00:32:25,360
Speaker 7: was not going to come through, Like that was the

597
00:32:26,040 --> 00:32:29,400
Speaker 7: messaging and the tech community at least, but the public

598
00:32:29,480 --> 00:32:32,200
Speaker 7: didn't know that. And it just seems kind of embarrassing

599
00:32:32,280 --> 00:32:35,360
Speaker 7: for the company that they are missing their own goals,

600
00:32:35,480 --> 00:32:39,600
Speaker 7: like they're missing their stated aims with their AI functionality. So,

601
00:32:40,000 --> 00:32:42,720
Speaker 7: I don't know, it doesn't look like strategy from the outside.

602
00:32:42,800 --> 00:32:46,040
Speaker 1: You don't think there's anything the consumers like. For example,

603
00:32:46,080 --> 00:32:48,120
Speaker 1: we just talked about that movie, right, and the kind

604
00:32:48,160 --> 00:32:50,840
Speaker 1: of AI doomerism. There's no argument that perhaps from a

605
00:32:50,840 --> 00:32:53,920
Speaker 1: consumer point of view, like having a technology company that

606
00:32:54,080 --> 00:32:58,120
Speaker 1: is not emotionally associated with AI and doom maybe an

607
00:32:58,160 --> 00:32:59,959
Speaker 1: interesting thing. I mean it was. It was interesting too.

608
00:33:00,120 --> 00:33:03,040
Speaker 1: Cook in that letter didn't mention the words AI lartificial

609
00:33:03,040 --> 00:33:05,360
Speaker 1: intelligence once. I mean, this is a tech ce or

610
00:33:05,440 --> 00:33:07,760
Speaker 1: letter in twenty twenty six. That kind of been an oversight.

611
00:33:07,800 --> 00:33:09,000
Speaker 1: I mean that must have been a decision.

612
00:33:09,520 --> 00:33:12,600
Speaker 4: Well, look AI. The thing is we should stop calling

613
00:33:12,640 --> 00:33:15,000
Speaker 4: it AI. I know that's not gonna happen. But you know,

614
00:33:15,120 --> 00:33:19,080
Speaker 4: it's software, okay, Like it's like saying I hate software,

615
00:33:19,200 --> 00:33:21,239
Speaker 4: Like okay, fine, Like and there could be like an

616
00:33:21,280 --> 00:33:25,560
Speaker 4: anti software lobby and everybody lobbies. But like, you know,

617
00:33:25,640 --> 00:33:27,640
Speaker 4: when you have a product that can just like do

618
00:33:27,680 --> 00:33:29,800
Speaker 4: stuff for you and save you a bunch of time

619
00:33:29,840 --> 00:33:32,160
Speaker 4: and is like very useful, like you're just going to

620
00:33:32,280 --> 00:33:34,520
Speaker 4: use it, right, that's just how the world works. Like

621
00:33:34,560 --> 00:33:37,120
Speaker 4: I'm sorry, nobody's going to be like I'm morally opposed

622
00:33:37,120 --> 00:33:39,640
Speaker 4: to this software that's like, you know, allowing me to

623
00:33:39,680 --> 00:33:42,040
Speaker 4: spend more time with my kids. Like it's just, you know,

624
00:33:42,280 --> 00:33:43,640
Speaker 4: it's just kind of a silly concept.

625
00:33:43,920 --> 00:33:46,120
Speaker 7: I found it kind of interesting just to jump in

626
00:33:46,360 --> 00:33:49,800
Speaker 7: the wave of new devices coming out for AI. The

627
00:33:49,840 --> 00:33:52,960
Speaker 7: little gadgets and dependance and stuff. They all look like

628
00:33:53,040 --> 00:33:57,640
Speaker 7: Apple products, Like the vocabulary is so apply, the graphic

629
00:33:57,680 --> 00:34:02,000
Speaker 7: design is apply. The whole vibe comes from Apple. But

630
00:34:02,080 --> 00:34:03,880
Speaker 7: Apple is like not anywhere.

631
00:34:04,200 --> 00:34:06,720
Speaker 1: And Jon who designed the iPhone, is working on.

632
00:34:07,960 --> 00:34:11,680
Speaker 4: AI, so like, and why are those products coming out? Right,

633
00:34:11,719 --> 00:34:14,920
Speaker 4: It's because the iPhone can't. You can't do what you

634
00:34:15,000 --> 00:34:17,440
Speaker 4: want to do on the iPhone. They won't let you.

635
00:34:17,520 --> 00:34:22,280
Speaker 7: I'm just waiting for the real AI Tamagatschi. That's my dream.

636
00:34:22,480 --> 00:34:24,960
Speaker 7: I can't wait. It needs to happen.

637
00:34:25,239 --> 00:34:27,680
Speaker 6: Wait read. But if we're locked in because it's a

638
00:34:27,760 --> 00:34:31,560
Speaker 6: closed ecosystem, doesn't that give them this at least, like

639
00:34:31,600 --> 00:34:34,680
Speaker 6: it buys them time to just come in when you

640
00:34:34,719 --> 00:34:37,480
Speaker 6: know when it's not AI AI, it is, here's your

641
00:34:37,640 --> 00:34:41,120
Speaker 6: useful assistant. Like I don't know some of these some

642
00:34:41,200 --> 00:34:44,040
Speaker 6: of these companies, right like fifty years they've had they've

643
00:34:44,040 --> 00:34:48,560
Speaker 6: been able to parlay their like consumer lock in from

644
00:34:48,920 --> 00:34:49,960
Speaker 6: across a generation.

645
00:34:50,360 --> 00:34:54,480
Speaker 4: So yeah, like Expinity for instance, right, like they will

646
00:34:54,520 --> 00:34:57,520
Speaker 4: continue to exist, Like I'm not arguing against that at all,

647
00:34:57,560 --> 00:35:00,319
Speaker 4: Like I think Apple will go on for a long time.

648
00:35:00,360 --> 00:35:02,920
Speaker 4: Like this isn't This isn't an argument that like Apple's

649
00:35:02,920 --> 00:35:05,680
Speaker 4: going to implode and disappear. But it's like it's like

650
00:35:05,760 --> 00:35:08,719
Speaker 4: Microsoft when they missed you know, I don't know, they

651
00:35:08,719 --> 00:35:12,359
Speaker 4: miss search and then Mobile, like it's it's Microsoft still there.

652
00:35:12,360 --> 00:35:15,320
Speaker 4: It's still a very valuable company, but like not as

653
00:35:15,480 --> 00:35:18,719
Speaker 4: as relevant and it went through some dark times. Maybe

654
00:35:18,880 --> 00:35:21,120
Speaker 4: you know, maybe they can make a recovery or something

655
00:35:21,160 --> 00:35:23,560
Speaker 4: like that, but I think it will be dark times

656
00:35:23,760 --> 00:35:26,400
Speaker 4: for Apple. It's not going to have the same, you know,

657
00:35:26,760 --> 00:35:29,400
Speaker 4: the same relevance as as it used to once this

658
00:35:29,440 --> 00:35:31,640
Speaker 4: stuff starts to take off. And I'm not an expert

659
00:35:31,640 --> 00:35:34,120
Speaker 4: on the timelines, like this could take this could take

660
00:35:34,160 --> 00:35:37,359
Speaker 4: several years. But but the writing's on the wall.

661
00:35:37,480 --> 00:35:38,720
Speaker 2: That's all. That's my argument.

662
00:35:39,160 --> 00:35:41,160
Speaker 1: I also think I also take take a little bit

663
00:35:41,200 --> 00:35:43,560
Speaker 1: of you know, disagree slightly with you read that the

664
00:35:43,560 --> 00:35:45,760
Speaker 1: people done by Apple because of the product, Like I agree,

665
00:35:45,800 --> 00:35:48,600
Speaker 1: the ecosystem looking is very powerful, but also like I

666
00:35:48,680 --> 00:35:50,399
Speaker 1: was an Android user for many years and I bult

667
00:35:50,400 --> 00:35:51,920
Speaker 1: an iPhone. I was like, wow, this is just a

668
00:35:51,920 --> 00:35:53,719
Speaker 1: lot better. I'm not going to get another Android, And

669
00:35:54,040 --> 00:35:56,360
Speaker 1: I recently lost my airports when I was traveling and

670
00:35:56,400 --> 00:35:57,560
Speaker 1: I was like, I don't know about one hundred and

671
00:35:57,560 --> 00:35:59,840
Speaker 1: fifty dollars for airports. I'm going to get fake copied

672
00:35:59,880 --> 00:36:01,719
Speaker 1: one on Amazon for thirty bucks. I was like put

673
00:36:01,760 --> 00:36:04,719
Speaker 1: them in and I was like, I.

674
00:36:04,640 --> 00:36:07,120
Speaker 4: Thought, look, I have I have AirPods in my ear.

675
00:36:07,200 --> 00:36:09,759
Speaker 4: I have an iPhone sitting actually I have like three

676
00:36:09,880 --> 00:36:10,960
Speaker 4: iPhones sitting on my.

677
00:36:11,040 --> 00:36:13,760
Speaker 2: Dead like I'm on a mat computer.

678
00:36:14,040 --> 00:36:16,239
Speaker 4: Like this is I totally get that, Like it's a

679
00:36:16,239 --> 00:36:19,239
Speaker 4: great consumer experience, like this is not like this is

680
00:36:19,280 --> 00:36:21,319
Speaker 4: not me being like I hate Apple and I won't

681
00:36:21,320 --> 00:36:24,160
Speaker 4: buy anything by Apple, Like no, people, It's a really

682
00:36:24,239 --> 00:36:27,319
Speaker 4: nice consumer experience, like it all, it all works really

683
00:36:27,320 --> 00:36:29,840
Speaker 4: well together. But I'm just looking into the future. I'm like,

684
00:36:30,320 --> 00:36:32,920
Speaker 4: this is not like this idea of like opening up

685
00:36:32,920 --> 00:36:35,759
Speaker 4: an app and like using it like which we all

686
00:36:35,800 --> 00:36:38,560
Speaker 4: do today is not the future. Like that is not

687
00:36:38,719 --> 00:36:41,040
Speaker 4: how like I'm not opening up a banking app and

688
00:36:41,120 --> 00:36:44,359
Speaker 4: like transferring funds and stuff. I'm just gonna tell an

689
00:36:44,400 --> 00:36:45,920
Speaker 4: AI agent to do that, and you can do that

690
00:36:46,000 --> 00:36:50,239
Speaker 4: today with you know, open claw. That's very early adopter technology,

691
00:36:50,239 --> 00:36:53,360
Speaker 4: but like a glimpse into the future again, and I

692
00:36:53,400 --> 00:36:56,560
Speaker 4: can tell a chatbot like go, you know, transfer some

693
00:36:56,600 --> 00:36:59,120
Speaker 4: funds on a bank, Go book me a flight, right

694
00:36:59,200 --> 00:37:01,880
Speaker 4: and without ever opening an app, and all that's happening

695
00:37:01,920 --> 00:37:04,799
Speaker 4: outside the mobile ecosystem. And that's that's kind of where

696
00:37:04,800 --> 00:37:07,440
Speaker 4: it's heading. And it just makes that the thing that

697
00:37:07,480 --> 00:37:11,360
Speaker 4: Apple built that nice, like very nice consumer experience, like

698
00:37:11,680 --> 00:37:14,239
Speaker 4: it's not as important anymore. It's it's going to be

699
00:37:14,280 --> 00:37:17,840
Speaker 4: sort of like there. I don't think there's a walled garden,

700
00:37:18,440 --> 00:37:20,239
Speaker 4: at least I hope not, because I think it would

701
00:37:20,239 --> 00:37:22,000
Speaker 4: be bad for consumers. Like, I don't think there's like

702
00:37:22,040 --> 00:37:23,560
Speaker 4: a walled garden approach to that.

703
00:37:23,640 --> 00:37:27,000
Speaker 7: It feels like everyone's jostling for control of the new interface,

704
00:37:27,280 --> 00:37:29,759
Speaker 7: like what are we going to use to interface with

705
00:37:29,800 --> 00:37:33,439
Speaker 7: our AI agents and our open clause and whatever. And

706
00:37:34,000 --> 00:37:36,960
Speaker 7: you know, Johnny Ive and open ai are trying to

707
00:37:37,000 --> 00:37:39,759
Speaker 7: do that with some pendant thing that sits on your

708
00:37:39,760 --> 00:37:42,640
Speaker 7: desk plus the thing that goes in your pocket. There's

709
00:37:42,640 --> 00:37:46,239
Speaker 7: been all sorts of little experiments and different trials. I

710
00:37:46,239 --> 00:37:49,080
Speaker 7: feel like there's more opportunity right now for some other

711
00:37:49,160 --> 00:37:51,759
Speaker 7: company to take this away from Apple and to come

712
00:37:51,840 --> 00:37:54,560
Speaker 7: up with something else. And I was just recalling how

713
00:37:54,600 --> 00:37:58,440
Speaker 7: Apple is kind of bailed on its other innovative hardware projects,

714
00:37:58,480 --> 00:38:01,600
Speaker 7: like there is no TV, there is no car, and

715
00:38:01,640 --> 00:38:06,440
Speaker 7: the new possible CEO who people talk about John Turnus.

716
00:38:06,880 --> 00:38:11,080
Speaker 7: He's a hardware engineering guy. Like, it's not clear where

717
00:38:11,080 --> 00:38:11,560
Speaker 7: it's going.

718
00:38:11,920 --> 00:38:14,839
Speaker 6: Did you guys see that picture of Joe Gebbia from

719
00:38:15,000 --> 00:38:18,279
Speaker 6: Airbnb with like what looked like the new device. I

720
00:38:18,280 --> 00:38:20,400
Speaker 6: mean I still want my If that's the new device,

721
00:38:20,440 --> 00:38:23,399
Speaker 6: I will keep my phone. You know, like you are saying, Kyle,

722
00:38:23,440 --> 00:38:30,000
Speaker 6: it's so derivative of early Apple. So yeah, I see

723
00:38:30,000 --> 00:38:32,040
Speaker 6: what you're saying. I guess, like, and I don't even

724
00:38:32,080 --> 00:38:34,680
Speaker 6: know why I'm defending Apple's hard I guess I like

725
00:38:34,760 --> 00:38:37,440
Speaker 6: that Tim Cook didn't put AI in his letter because

726
00:38:37,440 --> 00:38:41,080
Speaker 6: it is meaningless. Like you, if you're thinking about like

727
00:38:41,120 --> 00:38:44,960
Speaker 6: how to give people real utility, you don't need to

728
00:38:45,040 --> 00:38:47,200
Speaker 6: get like there is a chance that you could just

729
00:38:47,280 --> 00:38:49,799
Speaker 6: come in on the back end. I mean, fifty year

730
00:38:49,840 --> 00:38:51,960
Speaker 6: old companies have a very hard time innovating.

731
00:38:52,160 --> 00:38:54,160
Speaker 4: I think the new interface that you're talking about his

732
00:38:54,239 --> 00:38:56,879
Speaker 4: voice right, Like that's what that's I mean, it won't

733
00:38:56,880 --> 00:38:59,920
Speaker 4: be all voice, but like you know, that's how we're

734
00:39:00,080 --> 00:39:00,840
Speaker 4: to control this stuff.

735
00:39:00,840 --> 00:39:03,400
Speaker 6: Don't you think, yeah, but what is this big pebble,

736
00:39:04,520 --> 00:39:06,360
Speaker 6: this big pebble. I'm not going to carry around a

737
00:39:06,400 --> 00:39:07,440
Speaker 6: big pebble.

738
00:39:07,160 --> 00:39:09,080
Speaker 2: Like you're gonna have to.

739
00:39:09,200 --> 00:39:11,040
Speaker 4: We're gonna have to have some device, right because you're

740
00:39:11,040 --> 00:39:14,400
Speaker 4: gonna want some screen occasionally look at something visual or

741
00:39:15,040 --> 00:39:17,040
Speaker 4: you know, maybe it's in a glass as well. I

742
00:39:17,040 --> 00:39:20,200
Speaker 4: think that technology is like really far away that.

743
00:39:20,160 --> 00:39:24,759
Speaker 6: They'll consult more women as they're doing this, because they

744
00:39:24,760 --> 00:39:26,200
Speaker 6: did not for VR and.

745
00:39:27,760 --> 00:39:31,840
Speaker 7: A Imagchi all the way. So we've we've been here before.

746
00:39:31,920 --> 00:39:35,160
Speaker 7: There's the Pokemon version, there's the digimon little thing.

747
00:39:35,320 --> 00:39:36,200
Speaker 3: It's gonna be great.

748
00:39:39,480 --> 00:39:41,440
Speaker 6: Yeah. I was just gonna say, because I can picture

749
00:39:41,480 --> 00:39:43,560
Speaker 6: how to carry it around like that big pebble, I

750
00:39:43,600 --> 00:39:44,919
Speaker 6: was like, where am I going to put it? It's

751
00:39:44,920 --> 00:39:46,160
Speaker 6: going to be at the bottom of my back?

752
00:39:46,400 --> 00:39:49,120
Speaker 1: Who has the inside scoop on the on the CEO

753
00:39:49,200 --> 00:39:50,880
Speaker 1: succession is Tim Cook? What are you going to go

754
00:39:50,960 --> 00:39:51,439
Speaker 1: this year?

755
00:39:51,680 --> 00:39:51,879
Speaker 6: Oh?

756
00:39:51,960 --> 00:39:52,360
Speaker 2: I don't know.

757
00:39:52,440 --> 00:39:55,360
Speaker 4: I mean, I I just I'm not like deep in

758
00:39:55,480 --> 00:39:58,120
Speaker 4: the in the company anymore, so I would just be guessing.

759
00:39:58,160 --> 00:40:00,040
Speaker 4: But I mean for sure, like it's the end of

760
00:40:00,080 --> 00:40:03,960
Speaker 4: Tim Cook's you know, career, and that's that's apparent right,

761
00:40:04,120 --> 00:40:07,839
Speaker 4: Like when exactly that happened, I don't know, but but yeah,

762
00:40:07,920 --> 00:40:11,600
Speaker 4: like what I I think it's like there's every every

763
00:40:11,680 --> 00:40:13,959
Speaker 4: it seems like every six months there's like a new

764
00:40:14,040 --> 00:40:17,399
Speaker 4: successor a new name that comes out. And he's like, yeah,

765
00:40:17,400 --> 00:40:20,279
Speaker 4: like none of it's like super exciting. You're like, could

766
00:40:20,320 --> 00:40:22,400
Speaker 4: we get Steve jobs? Like is he available to?

767
00:40:22,400 --> 00:40:25,399
Speaker 1: Like I just Adam Newman might be looking for a job.

768
00:40:25,440 --> 00:40:28,320
Speaker 4: If maybe Adam Newman like I don't know, like something

769
00:40:28,400 --> 00:40:31,800
Speaker 4: exciting that like maybe that's not good. Maybe Apple doesn't

770
00:40:31,800 --> 00:40:33,920
Speaker 4: want someone exciting. Maybe the best thing is to be

771
00:40:34,080 --> 00:40:37,120
Speaker 4: like Comcast or you know whatever and just like ride

772
00:40:37,320 --> 00:40:38,680
Speaker 4: ride it out as long as possible.

773
00:40:38,719 --> 00:40:40,480
Speaker 1: Would you when you when they would dooin transition from

774
00:40:40,560 --> 00:40:42,359
Speaker 1: jobs to cook it was from the vision to reach

775
00:40:42,440 --> 00:40:44,280
Speaker 1: the technic crawt. It's hard to go from the technic

776
00:40:44,320 --> 00:40:46,319
Speaker 1: crat to a new visionary, right, You're kind of you're

777
00:40:46,320 --> 00:40:47,520
Speaker 1: locked in at that point a little bit.

778
00:40:47,760 --> 00:40:50,880
Speaker 3: Yeah, for sure, we knew Johnson Huang and his leather jacket.

779
00:40:51,040 --> 00:40:51,239
Speaker 3: You know.

780
00:40:54,640 --> 00:40:56,200
Speaker 1: Well, that's all we have time for today. But I

781
00:40:56,239 --> 00:40:58,960
Speaker 1: want to end with a quick round robin who had

782
00:40:59,000 --> 00:41:02,000
Speaker 1: the best and worst we can tech? I'm gonna go first.

783
00:41:02,040 --> 00:41:04,520
Speaker 1: I think anthropic we always want to either the best

784
00:41:04,520 --> 00:41:06,360
Speaker 1: of the week or the worst. I think it's the

785
00:41:06,400 --> 00:41:09,400
Speaker 1: worst this week with the leak of that code. Interesting,

786
00:41:09,640 --> 00:41:10,399
Speaker 1: what do you think read?

787
00:41:10,760 --> 00:41:11,080
Speaker 3: Well?

788
00:41:11,640 --> 00:41:14,799
Speaker 4: I thought, I mean the word like Oracle laying off like,

789
00:41:15,719 --> 00:41:18,880
Speaker 4: you know, a huge chunk of their whole company was like,

790
00:41:19,000 --> 00:41:21,480
Speaker 4: has got to be a really bad, bad week for Oracle.

791
00:41:21,520 --> 00:41:25,319
Speaker 4: And it's all because well again, like people will say, like, oh,

792
00:41:25,400 --> 00:41:27,719
Speaker 4: the AI, it's taking our jobs, and it's like, well,

793
00:41:27,760 --> 00:41:31,000
Speaker 4: actually it looks a little different, right. It's it's like, well,

794
00:41:31,120 --> 00:41:33,439
Speaker 4: they need to invest a huge amount of money in AI.

795
00:41:33,600 --> 00:41:36,480
Speaker 4: They don't really have the cash, and so they're just

796
00:41:36,560 --> 00:41:39,759
Speaker 4: like looking in the couch cushions and it's like, yeah,

797
00:41:39,880 --> 00:41:42,480
Speaker 4: laying off a bunch of employees is okay, that's going

798
00:41:42,560 --> 00:41:44,480
Speaker 4: to get us like a little bit closer to what

799
00:41:44,520 --> 00:41:46,080
Speaker 4: we need to invest in this whole thing.

800
00:41:46,600 --> 00:41:49,319
Speaker 1: And it's like just a general sixty minutes.

801
00:41:50,239 --> 00:41:55,960
Speaker 4: Right exactly so six So it's like, I mean, I

802
00:41:56,040 --> 00:41:57,960
Speaker 4: don't know, this is like how we don't really know

803
00:41:58,000 --> 00:41:59,759
Speaker 4: how AI is going to like affect the world. It's

804
00:41:59,800 --> 00:42:02,160
Speaker 4: like all these people just lost their jobs because of AI,

805
00:42:02,360 --> 00:42:05,799
Speaker 4: but not because AI took their jobs right, and I

806
00:42:05,840 --> 00:42:08,880
Speaker 4: think it's a bad week for Oracle, But also like

807
00:42:08,960 --> 00:42:11,440
Speaker 4: that is to me just a good example of what

808
00:42:11,480 --> 00:42:12,600
Speaker 4: we were talking about earlier.

809
00:42:13,080 --> 00:42:15,160
Speaker 7: On that note, I was going to say the worst

810
00:42:15,160 --> 00:42:19,280
Speaker 7: week in tech was for journalists because of this whole

811
00:42:19,360 --> 00:42:25,200
Speaker 7: AI journalism discourse. To Bockl, whatever should we use AI

812
00:42:25,280 --> 00:42:28,200
Speaker 7: and writing like, I think the answer is that it's

813
00:42:28,239 --> 00:42:30,520
Speaker 7: going to happen, and we're just kind of adapting to

814
00:42:30,560 --> 00:42:34,480
Speaker 7: this new situation. And at the same time, one of

815
00:42:34,480 --> 00:42:37,800
Speaker 7: the controversies was that this New York Times book reviewer

816
00:42:37,840 --> 00:42:42,919
Speaker 7: who's a British novelist used AI. He said to expand

817
00:42:43,000 --> 00:42:46,960
Speaker 7: a book review draft, he couldn't hit his thousand word mark,

818
00:42:47,080 --> 00:42:51,080
Speaker 7: which is crazy, and so he used AI and he

819
00:42:51,440 --> 00:42:54,640
Speaker 7: was caught kind of plagiarizing via AI. And my question

820
00:42:54,800 --> 00:42:57,680
Speaker 7: is just who are you, as a British novelist to

821
00:42:57,800 --> 00:43:01,359
Speaker 7: not even finish a novel review of a thousand words like.

822
00:43:01,719 --> 00:43:05,239
Speaker 1: And this kicked off a bigger journalism and Natasha, I

823
00:43:05,239 --> 00:43:07,320
Speaker 1: want to know your thoughts on cloud code. But also

824
00:43:07,520 --> 00:43:08,759
Speaker 1: if you, I mean, we've got a couple of we've

825
00:43:08,760 --> 00:43:10,560
Speaker 1: got three worsts of the week. I think hopefully you

826
00:43:10,560 --> 00:43:11,960
Speaker 1: can bring us the best of the week.

827
00:43:12,960 --> 00:43:15,920
Speaker 6: Oh, I have another worst of the week. I was

828
00:43:15,960 --> 00:43:20,640
Speaker 6: gonna say Mercore. Mercore is is the company that does

829
00:43:21,360 --> 00:43:24,000
Speaker 6: you know it kind of it hires those like PhDs

830
00:43:24,040 --> 00:43:28,560
Speaker 6: in biochemistry to create data that goes to the big

831
00:43:28,600 --> 00:43:33,520
Speaker 6: frontier labs to to put the PhDs in biochemistry out

832
00:43:33,560 --> 00:43:37,279
Speaker 6: of business. And they had this massive, massive leak. They

833
00:43:37,320 --> 00:43:42,400
Speaker 6: had video interviews with with individuals. They have so many

834
00:43:42,480 --> 00:43:45,720
Speaker 6: clients and I feel like we're just starting to get

835
00:43:45,760 --> 00:43:48,399
Speaker 6: a sense of where is that data going to go?

836
00:43:49,440 --> 00:43:50,960
Speaker 6: You know, does this mean it's like out on the

837
00:43:51,000 --> 00:43:54,719
Speaker 6: internet and everybody will have access to this like top

838
00:43:54,840 --> 00:43:57,640
Speaker 6: tier post training data. That one. That one is like

839
00:43:57,840 --> 00:44:00,560
Speaker 6: I'm not usually that interested in CyberSecure, but I really

840
00:44:00,600 --> 00:44:02,040
Speaker 6: want to see where this one goes.

841
00:44:01,920 --> 00:44:03,520
Speaker 1: And how does that relate is it? It's a separate

842
00:44:03,560 --> 00:44:05,440
Speaker 1: story to the clawed leak, but just tell us a

843
00:44:05,440 --> 00:44:06,680
Speaker 1: little bit about that before regard.

844
00:44:07,760 --> 00:44:11,960
Speaker 6: Yeah, the cloud leak is I think is spiritually very

845
00:44:11,960 --> 00:44:15,040
Speaker 6: different because you already have that a lot of that

846
00:44:15,120 --> 00:44:18,480
Speaker 6: code on your computer, so it wasn't as I mean,

847
00:44:18,520 --> 00:44:21,920
Speaker 6: it was like illuminating for people, but this is like

848
00:44:22,040 --> 00:44:26,960
Speaker 6: proprietary information that they owed to their customers, and you know,

849
00:44:27,160 --> 00:44:30,760
Speaker 6: there was no way that they wanted even a smidge

850
00:44:30,760 --> 00:44:31,520
Speaker 6: of this to get out.

851
00:44:31,680 --> 00:44:33,640
Speaker 1: Okay, I have a best of the week the guy

852
00:44:34,040 --> 00:44:38,919
Speaker 1: from medv or Medvi who created the first unicorn of two,

853
00:44:39,040 --> 00:44:41,879
Speaker 1: him and his brother their first billion dollar run rate

854
00:44:41,960 --> 00:44:45,520
Speaker 1: company selling GLP ones and via great on the internet.

855
00:44:45,520 --> 00:44:48,440
Speaker 7: It's a thing like they're just doing the marketing and

856
00:44:48,920 --> 00:44:50,879
Speaker 7: talking to patients.

857
00:44:51,320 --> 00:44:53,640
Speaker 1: And I think I think that they're connect somehow, connecting

858
00:44:53,680 --> 00:44:55,880
Speaker 1: patients and doctors in a quicker way than it is

859
00:44:55,880 --> 00:44:59,560
Speaker 1: otherwise possible to bypass. Field Fashion and prescription.

860
00:45:01,840 --> 00:45:05,759
Speaker 6: Kill Mill is the first billion dollar one person, two

861
00:45:05,760 --> 00:45:06,680
Speaker 6: person company.

862
00:45:06,960 --> 00:45:09,040
Speaker 2: It wasn't born, you know.

863
00:45:09,480 --> 00:45:10,400
Speaker 6: I mean, there's.

864
00:45:11,719 --> 00:45:14,400
Speaker 2: Something no but it's just it's just boring.

865
00:45:14,480 --> 00:45:16,200
Speaker 4: I'm just saying that was like what it was like

866
00:45:16,239 --> 00:45:18,360
Speaker 4: web one point out, like let's do something different.

867
00:45:18,400 --> 00:45:20,440
Speaker 1: You know, he has a digital avatar of himself to

868
00:45:20,440 --> 00:45:23,280
Speaker 1: deal with his day's day life as well. The founders

869
00:45:23,320 --> 00:45:26,080
Speaker 1: that he's already going all in on the on the

870
00:45:26,120 --> 00:45:26,960
Speaker 1: on the AI moment.

871
00:45:26,960 --> 00:45:29,840
Speaker 2: He should be a go ahead read can I thro?

872
00:45:29,960 --> 00:45:31,080
Speaker 2: I mean we said it earlier.

873
00:45:31,120 --> 00:45:33,400
Speaker 4: I mean I think SpaceX right, it's gonna be the

874
00:45:33,480 --> 00:45:37,480
Speaker 4: largest I P o ever, right, they they filed confidentially

875
00:45:37,520 --> 00:45:40,200
Speaker 4: this week, right, I mean that's like, you know, you

876
00:45:40,280 --> 00:45:42,680
Speaker 4: gotta get a handle to them. That's pretty and you know,

877
00:45:42,840 --> 00:45:45,600
Speaker 4: and also just people are talking about space a lot, right,

878
00:45:45,640 --> 00:45:49,719
Speaker 4: You've got the Artemist launch, You've got the Project Hill

879
00:45:49,800 --> 00:45:50,960
Speaker 4: Mary movie.

880
00:45:51,760 --> 00:45:55,480
Speaker 1: You know, I feel likensha not such a space stun.

881
00:45:56,760 --> 00:45:59,040
Speaker 3: Can go to spaces going to space.

882
00:45:59,840 --> 00:46:03,440
Speaker 2: I I just wish, I.

883
00:46:03,400 --> 00:46:06,280
Speaker 6: Wish people would read more Octavia Butler if they're thinking

884
00:46:06,280 --> 00:46:09,680
Speaker 6: about space rather than you know, like what is he

885
00:46:09,880 --> 00:46:15,279
Speaker 6: like Robert Heinleine. Uh, I'm very curious to look at

886
00:46:15,320 --> 00:46:17,359
Speaker 6: the space X I p O. Because I think we're

887
00:46:17,360 --> 00:46:22,120
Speaker 6: going to have some like oracle type moving stuff around

888
00:46:22,160 --> 00:46:26,160
Speaker 6: in order to pay for those data centers. And you know,

889
00:46:26,200 --> 00:46:29,480
Speaker 6: it's just been rolling up and rolling up companies into

890
00:46:30,040 --> 00:46:34,400
Speaker 6: right like x into Xai, x Ai into is it

891
00:46:34,440 --> 00:46:35,399
Speaker 6: into SpaceX now?

892
00:46:35,400 --> 00:46:37,759
Speaker 4: And I'm like blinking, well, it's going to be well,

893
00:46:38,239 --> 00:46:41,920
Speaker 4: well it's yeah, but it's going to be it is SpaceX,

894
00:46:41,960 --> 00:46:43,000
Speaker 4: but it's going to be Tesla.

895
00:46:43,120 --> 00:46:46,479
Speaker 2: It's going to be elon KRK. Right, That's that's the plan.

896
00:46:46,560 --> 00:46:49,520
Speaker 4: They go public and then they'll they'll join with Tesla

897
00:46:50,040 --> 00:46:52,600
Speaker 4: in some capacity, and you're just.

898
00:46:52,600 --> 00:46:54,480
Speaker 6: You're just I mean, we do think there's a chance

899
00:46:54,560 --> 00:46:59,080
Speaker 6: that if people look at the at the numbers that like,

900
00:46:59,520 --> 00:47:03,360
Speaker 6: he's an incredible showman for for stockholders, right, So do

901
00:47:03,400 --> 00:47:05,040
Speaker 6: you think some of that will change if we see

902
00:47:05,040 --> 00:47:05,600
Speaker 6: the numbers?

903
00:47:06,280 --> 00:47:09,280
Speaker 4: I mean, I think you just have to ask retail

904
00:47:09,360 --> 00:47:12,520
Speaker 4: investors what they think. I think, and I think the

905
00:47:12,560 --> 00:47:14,480
Speaker 4: answer is like we love the Elon, right, I mean

906
00:47:14,480 --> 00:47:17,719
Speaker 4: that's people just he is the I mean, he is

907
00:47:17,760 --> 00:47:20,279
Speaker 4: the Steve Jobs of our day, right, like people, He's

908
00:47:20,320 --> 00:47:23,799
Speaker 4: got the he can convince people of anything. You know,

909
00:47:23,840 --> 00:47:26,759
Speaker 4: you can tell a story about space data centers and

910
00:47:26,880 --> 00:47:29,920
Speaker 4: humanoid robots and all that, and I think you know

911
00:47:30,280 --> 00:47:34,240
Speaker 4: it's it's that formula still works, right, I mean.

912
00:47:34,800 --> 00:47:37,520
Speaker 1: Kyle is eating the Steve Jobs of our age.

913
00:47:38,360 --> 00:47:41,759
Speaker 7: Oh man, I mean Steve Jobs was not sending us

914
00:47:41,800 --> 00:47:47,360
Speaker 7: to space. He could be like the Thomas Edison or whatever,

915
00:47:47,560 --> 00:47:50,200
Speaker 7: like the if not the pure inventor, then at least

916
00:47:50,200 --> 00:47:53,400
Speaker 7: the showman who can trust all of this stuff up

917
00:47:53,520 --> 00:47:57,120
Speaker 7: for public consumption. Speaking of space, though, I also want

918
00:47:57,200 --> 00:47:59,600
Speaker 7: to add my best of the week, which is a

919
00:47:59,640 --> 00:48:05,520
Speaker 7: Nintime Do and Super Mario Galaxy Odyssey whatever, which seems

920
00:48:05,560 --> 00:48:09,239
Speaker 7: to be a rousing success for children everywhere.

921
00:48:10,600 --> 00:48:12,880
Speaker 4: You know, my kids are going to the movie later

922
00:48:13,120 --> 00:48:15,000
Speaker 4: later today, so yeah, they had.

923
00:48:15,160 --> 00:48:18,920
Speaker 1: It's a hard choice between am Ai apocaly Optimist and

924
00:48:19,200 --> 00:48:22,040
Speaker 1: Mary mary Win Space movie. I guess for your kids.

925
00:48:23,000 --> 00:48:25,399
Speaker 4: I haven't even seen Project Tail there yet, so that's

926
00:48:25,600 --> 00:48:29,120
Speaker 4: the the apocal apocaal Optimist is gonna have to wait

927
00:48:29,160 --> 00:48:29,440
Speaker 4: for me.

928
00:48:33,320 --> 00:48:33,520
Speaker 3: In it.

929
00:48:33,600 --> 00:48:37,120
Speaker 1: That's thank you.

930
00:48:37,120 --> 00:48:39,680
Speaker 3: All, thanks for having us.

931
00:48:39,760 --> 00:48:40,640
Speaker 2: That was fun.

932
00:48:54,560 --> 00:48:57,319
Speaker 1: For tech stuff. I'm was for Locian. This episode was

933
00:48:57,320 --> 00:49:00,600
Speaker 1: produced by Elizah Dennis and Melissa Slaughter. Executive produced by

934
00:49:00,680 --> 00:49:03,600
Speaker 1: me Julian Nutter and Kate Osborne for Kaleidoscope and Katria

935
00:49:03,680 --> 00:49:07,279
Speaker 1: Norvel for iHeart Podcasts. Jack Insley mixed this episode and

936
00:49:07,360 --> 00:49:10,360
Speaker 1: Kyle Murdoch wrote our theme song special thank you to

937
00:49:10,440 --> 00:49:13,480
Speaker 1: you read Kyle and Natasha. Please check out all three

938
00:49:13,520 --> 00:49:16,160
Speaker 1: of these incredible journalists work, and we're very lucky to

939
00:49:16,200 --> 00:49:17,359
Speaker 1: call them friends of the pod.