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Speaker 1: Hey guys, Saga and Crystal here.

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Speaker 2: Independent media just played a truly massive role in this election,

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Speaker 2: This story is important both in honest merits, but also

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Speaker 2: in terms of what it says about Trump two point

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Speaker 2: zero and the way he's approaching this administration. Put this

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Speaker 2: Washington Post hairs sheet up on the screen. I think

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Speaker 2: they were the first one to break this news. Trump

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Speaker 2: outs at least fifteen independent inspectors general in late night purge,

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Speaker 2: So every cabinet level agency has one of these inspectors general.

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Speaker 2: We're supposed to be independent. They're actually supposed to have

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Speaker 2: lengthy terms, so's you know, serving under one president to

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Speaker 2: try to insulate them from political influence. And actually, during

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Speaker 2: the first Trump administration, Trump had tried to fire a

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Speaker 2: bunch of these individuals, and I think did fire some

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Speaker 2: of them, and Congress reacted and a bipartisan manner was like,

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Speaker 2: you know, we really need to protect the independence of

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Speaker 2: these roles. So we are going to require that you

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Speaker 2: give Congress thirty day notice and that you give us

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Speaker 2: ample cause for why you're letting all of these people go.

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Speaker 2: So Trump says, don't care that there's a law that

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Speaker 2: says that I need to give you thirty days notice.

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Speaker 3: I'm just going to do it anyway.

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Speaker 2: They were notified late Friday by emails from the White

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Speaker 2: House Personnel Director that due to changing priorities, they've been

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Speaker 2: terminated immediately.

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Speaker 3: The only ones.

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Speaker 2: Who were spared were the watchdogs at homely insecurity and justice,

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Speaker 2: which is kind of interesting. Actually, I don't get to

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Speaker 2: that more in a moment. They go on to say

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Speaker 2: that dismissals appear to violate federal law, which does require

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Speaker 2: Congress to receive thirty days notice of any intent to

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Speaker 2: fire Senate confirmed inspector general. The legal uncertainty could create

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Speaker 2: awkward encounters. On Monday that would be today when several

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Speaker 2: watchdogs who were toltdal they were fired planned to show

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Speaker 2: up in their offices to work anyway. So there's one

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Speaker 2: person who sort of oversees the entire inspector's general program,

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Speaker 2: and he put on a letter saying, listen, this wasn't legal,

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Speaker 2: so we don't accept it. So a bunch of these

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Speaker 2: watchdogs are going to show up today anyway because they

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Speaker 2: view it, I think, very clearly and accurately so as

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Speaker 2: being unlawful. One of the fire watchdogs describe it as

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Speaker 2: a widespread massacre. They said, whoever Trump puts in now

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Speaker 2: will be viewed as loyalists that undermines the entire system.

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Speaker 2: The other thing that's interesting, weird whatever here, Emily, is

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Speaker 2: that a bunch of these people that he just fired

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Speaker 2: were his own appointees from the first term. So it's

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Speaker 2: not like this was a bunch of like you know,

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Speaker 2: libs put in by Obama or Biden. Many of these

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Speaker 2: people were actually Trump appointees. But one of the people

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Speaker 2: who survived was an Obama appoint that's Michael Horowitz at

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Speaker 2: the Justice Department, and apparently he liked him because you know,

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Speaker 2: he had been critical, he had been critical of Trump,

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Speaker 2: but he'd also been critical of Biden. I mean, that's

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Speaker 2: their role is to try to be even handed, regardless

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Speaker 2: whether it's a Republican or Democrat who's serving. The other

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Speaker 2: one that he left in place was one of his

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Speaker 2: appointees at the Department of Homeland Security. That individual, KAfari,

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Speaker 2: has been under investigation for years, but he had done something,

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Speaker 2: and he's in charge of overseeing the you know, the

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Speaker 2: crackdown on immigration, So it's important to Trump to have

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Speaker 2: someone who's friendly there in particular. And he had also

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Speaker 2: put out some report that Trump had you know, Trump

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Speaker 2: had appreciated, but you know, some of these some of

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Speaker 2: these people that he fired had been really critical of

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Speaker 2: different Biden actions. The Inspector General at the Veteran's Affair

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Speaker 2: oversaw multiple investigations of how the Biden administration handled the

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Speaker 2: agency's troubled effort to build a massive electronic health record system.

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Speaker 2: Another one uh Trump appoint at the Interior Department who

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Speaker 2: was fired, had released a lengthy investigation concluding that when

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Speaker 2: the US park Police led law enforcement officers in de

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Speaker 2: crowd of mostly peaceful protesters, that he actually he sort

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Speaker 2: of backed up Trump's version of events there. You guys

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Speaker 2: remember the whole Lafayette Square situation. His report said that

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Speaker 2: it was about a pre planned effort to build a

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Speaker 2: fence around the park to protect officers and not because

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Speaker 2: Trump had like sicked them on these peaceful protesters. So

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Speaker 2: you would think that would be something Trump would like.

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Speaker 2: But nevertheless that person has fired as well.

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Speaker 4: Yeah, and Chuck Grassley responded to this and said, there

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Speaker 4: may be good reason the IG's were fired. We need

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Speaker 4: to know that. If so, I'd like for their explanation

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Speaker 4: from President Trump, regardless of the thirty day detailed notice

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Speaker 4: removal that the law demands was not provided to Congress.

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Speaker 4: Jonathan Turtley, by the way, agrees with that Chili professor

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Speaker 4: at GW Law, somebody who has agreed with a lot

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Speaker 4: of Trump's decisions.

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Speaker 3: And it's like a you know, regular Fox News kind

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Speaker 3: of a guy.

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Speaker 4: I think he's a contributor. Yeah, he's willing to go

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Speaker 4: out on a limb for some of Trump's decisions, but

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Speaker 4: not this one. I think it is because with the

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Speaker 4: Senate appointed positions, that is so clear. And what's interesting

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Speaker 4: is that you can kind of pick up on scuttle

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Speaker 4: butt about policy priorities in the conservative world, you know,

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Speaker 4: these igs, we have to have a plan. I don't

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Speaker 4: know if this was in Project twenty twenty five. I

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Speaker 4: don't remember it. Maybe it isn't. I'm forgetting, But yeah,

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Speaker 4: i'd actually never heard that there was a plan to

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Speaker 4: gut IG's and it seems like Chuck Grassley hadn't heard

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Speaker 4: that either, as somebody who would have a significant interest

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Speaker 4: in it, because he says there may be good reason

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Speaker 4: the IG's were fired. We need to know that if so.

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Speaker 4: John Barrasso, the Senate majority whip, told Fox on Saturday, quote,

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Speaker 4: sometimes inspector general's inspectors general don't do the job that

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Speaker 4: they're supposed to do. Some of them deserve to be fired.

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Speaker 4: And I'm sure, by the way that that's true. But

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Speaker 4: I don't know what the evidence is. I haven't heard

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Speaker 4: people talking about the evidence when it comes to these

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Speaker 4: particular these particular confirmed positions. And one of the interesting

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Speaker 4: things also is from an anonymous source in the Washer

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Speaker 4: Post story that actually makes a pretty good point, which

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Speaker 4: is that igs do what Trump says he wants to do,

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Speaker 4: which is cut down on waste, fraud, and abuse. That's right,

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Speaker 4: And even if some of these particular igs weren't doing

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Speaker 4: the best job of that it. Now, by just gutting

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Speaker 4: them right off the bat without going through the formal process,

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Speaker 4: you are undermining. Like, whoever is confirmed in the future

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Speaker 4: is going to look like a political actor in a

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Speaker 4: way that they wouldn't have before, and they shouldn't look

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Speaker 4: like political actors. Let's say a IG comes out with

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Speaker 4: a great report on the EPA, and this is somebody

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Speaker 4: who's confirmed by appointed by Trump, confirmed by the Senate, Well,

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Speaker 4: it's just gonna be They're gonna lack the credibility that

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Speaker 4: they otherwise would have, yeah, commenting on the waste, fraud

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Speaker 4: and abuse at the EPA. So this one could really

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Speaker 4: come back to buy Trump.

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Speaker 2: Yeah, yeah, I think that's possible. I also think it's

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Speaker 2: possible that, I mean, he's doing so many things so

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Speaker 2: quickly that it is just hard to like focus on

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Speaker 2: any one, you know, particular outrage and I mean, so

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Speaker 2: you're right down the line, however, thing's unfold It's possible

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Speaker 2: that it does come back to bite him. It's also

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Speaker 2: possible that, like everyone just capitulates and forgets and moves on,

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Speaker 2: and you know, I think that's kind of what he's

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Speaker 2: betting on and paying attention to which direction things going

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Speaker 2: is really important because again, put actually C two up

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Speaker 2: on the screen. This is some of the Republican reactions

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Speaker 2: you mentioned. Chuck Grassley probably the most noteworthy because he's

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Speaker 2: you know, he's rock solid like conservative, knowing no one

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Speaker 2: call him. I don't think a rhino, right, I'm correct

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Speaker 2: about that. Yeah, he pointed out like this, didn't thought

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Speaker 2: this was illegal. Senator Susan Collins express confusion. You're not confused,

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Speaker 2: you know what's going on here. Lisamerkawski loaded then the

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Speaker 2: lack of notice, expressed worry over the abrupt dismissal. Obviously,

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Speaker 2: the Democrats came out very upset about this. You could

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Speaker 2: put their reactions up on the screen.

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Speaker 3: Next.

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Speaker 2: Chuck Schumer characterized it as a chilling purge, a preview

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Speaker 2: of the lawless approach. Jerry Connolly labeled dismissals as a

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Speaker 2: Friday night coup and an assault on transparency and accountability.

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Speaker 2: Elizabeth Warren called it a purge, accused Trump of dismantling

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Speaker 2: constraints on his authority. So obviously they're being very aggressive.

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Speaker 2: But you know, like I said at the top, I

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Speaker 2: mean just on the merits. It's important because genuinely, some

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Speaker 2: of these Inspectors General have done important work on behalf

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Speaker 2: of the American public and on behalf of taxpayers to

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Speaker 2: understand whether it was Trump or whether it was Biden,

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Speaker 2: or whether it's before that, where there had been failures,

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Speaker 2: where there had been corruption, where there had been things

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Speaker 2: that had been just done improperly or unlawfully, et cetera.

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Speaker 2: Am I right that Horowitz is the one who did

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Speaker 2: the Hunter Biden the Joe Biden report about the classified documents?

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Speaker 3: Was that him?

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Speaker 4: Or no? That would? That's right? And Trump has said

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Speaker 4: that he's keeping Horowitz because.

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Speaker 2: He liked thet But in any case, I mean, they

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Speaker 2: have done genuinely useful work that reporters and taxpayers rely on.

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Speaker 3: So it matters for the merits.

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Speaker 2: But I think it is one more indication, and we

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Speaker 2: already have many of these, that Trump two point zero

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Speaker 2: is taking a truly maximalist approach, because there's not even

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Speaker 2: a fig leaf here that this is legal. I mean,

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Speaker 2: you had the thirty day period is there's no exceptions

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Speaker 2: for it. You have to give Congress thirty day notice,

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Speaker 2: and he didn't, So it sets up a showdown what

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Speaker 2: happens next, you know, do Republicans just decide like, well,

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Speaker 2: he's our guy, and we're just not going to put

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Speaker 2: up that much of a fight and we don't really

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Speaker 2: want to cross him, and we're just going to accept this.

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Speaker 2: What happens when, I mean, you have to the next

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Speaker 2: whoever is going to be next hast to get confirmed

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Speaker 2: if their predecessor was fired illegally, Like what does that

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Speaker 2: look like?

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Speaker 3: And so.

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Speaker 2: We're going to see how these sort of showdowns really

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Speaker 2: unfold and whether he is able to do things that

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Speaker 2: are just like clearly unlawful and get away with it

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Speaker 2: because you have this, I mean, the birthright citizenship, the

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Speaker 2: executive Order. Birthright citizenship is kind of part and parcel

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Speaker 2: the same type of approach. A federal court has already

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Speaker 2: smacked that down and said like this is preposse, this

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Speaker 2: is like the most preposterous thing I've ever seen. Effectively,

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Speaker 2: but he feels like he can effectively do whatever he wants,

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Speaker 2: and the Sproome Corps basically told him that that was true.

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Speaker 3: So is he going to abide by the scored order?

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Speaker 2: Is he just going to keep moving forward doing what

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Speaker 2: he wants to do and firing him he wants to

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Speaker 2: fire and all that.

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Speaker 4: This is one of the I think the most important storylines,

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Speaker 4: not just for the first week, but I mean this

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Speaker 4: is this is going to be a significant snl of

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Speaker 4: all places. Had a really funny sketch kind of poking

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Speaker 4: fun at the lin Menuel Miranda millennial moment of Hamilton

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Speaker 4: back in early Trump days. But Trump was like, yeah,

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Speaker 4: maybe maybe we need a king in the in the sketch. Yeah,

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Speaker 4: And you know, Republicans, I can evage at a period

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Speaker 4: of time when Republicans were just utterly horrified at the

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Speaker 4: executive overreach of the Obama administration. And I think some

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Speaker 4: of those complaints were entirely valid because there was a

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Speaker 4: sort of stretching of the executive branch in a way

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Speaker 4: that if you are a sort of ideological conservative, you

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Speaker 4: would say, these are power You're usurping powers that belong

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Speaker 4: to Congress. And it's actually fueling this vicious cycle where

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Speaker 4: Congress just becomes more and more weak because they're punting

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Speaker 4: everything over to the executive branch. They know that they

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Speaker 4: can't get it done through, for example, the reconciliation process

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Speaker 4: because it's not strictly related to the budget, and so

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Speaker 4: I mean, some of this is Trump rolling back powers

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Speaker 4: that I don't think belong to the executive but not

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Speaker 4: all of it is at all. And actually, interestingly, this

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Speaker 4: was I was looking this up, well, you were going

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Speaker 4: through that. There was some talk about this in the

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Speaker 4: Project twenty twenty five circles, but not I mean, not

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Speaker 4: a lot. This was pretty low key. I think it

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Speaker 4: was public citizen that picked up on something. A couple

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Speaker 4: of people that were involved in Project twenty twenty five

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Speaker 4: said about purging igs. But genuinely, like this is if

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Speaker 4: that was a serious a serious point, it was really

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Speaker 4: low key, and that shows how significant Trump is literally

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Speaker 4: taking the blueprints that were drafted over the course of

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Speaker 4: the last four years. And a lot of people thought

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Speaker 4: they'd be giving those blueprints to Ron de Santis, for example,

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Speaker 4: a strict Tea Party freedom caucus, like true Chip Roy style,

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Speaker 4: like limited government dude. Although what's happened at the state

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Speaker 4: level is testing probably some of his old ideological allegiances.

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Speaker 4: But all that is to say, Trump is like just

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Speaker 4: taking the conservative movement's blueprints, and some of it I'm like,

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Speaker 4: oh yeah, like some of this is from my perspective

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Speaker 4: as a conservative. I'm supportive of it, but a lot

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Speaker 4: of this is significantly testing the conservative movement's actual commitment

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Speaker 4: to reigning in the power of the executive branch, and

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Speaker 4: this is a great example of that. So how many

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Speaker 4: people are going to speak out and get mad about

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Speaker 4: it in the same way that they would if Obama

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Speaker 4: did it?

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Speaker 5: Oh?

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Speaker 3: I imagine if Biden did that.

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Speaker 2: Yeah, imagine if this was common in office right now

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Speaker 2: and she had done it, I mean, or had launched

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Speaker 2: a shit going before she It's just like unimaginable.

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Speaker 4: Well, imagine if they had been seriously imagine I Kamala

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Speaker 4: Harris had been inaugurated with the oligarchs right.

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Speaker 3: Oh, oh, I know, I thought a lot.

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Speaker 6: Would imagined or gas right if she was there with

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Speaker 6: Zuckerberg and Bezos and Musk flanking her like, and then

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Speaker 6: immediately doing a presser announcing basically like, we're going to

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Speaker 6: support these people spending five hundred billion dollars, these tech

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Speaker 6: oligirks to eliminate your jobs.

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Speaker 3: I mean, that's the.

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Speaker 2: Goal of these tech AI developers is to literally eliminate

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Speaker 2: all need for human labor.

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Speaker 4: And Biden might as well have been flanked by them

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Speaker 4: in twenty twenty because that's the way his administration proceeded.

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Speaker 4: But this is so so brazen.

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Speaker 2: I actually don't think that's fair because the one place

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Speaker 2: where Biden really broke from the neoliberal the Obama Clinton

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Speaker 2: neoliberal consensus, and the you know area where he was

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Speaker 2: most significantly different on economics was this approach to antitrust.

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Speaker 4: Trump a little bit too. The Google suit was started

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Speaker 4: under Trump.

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Speaker 2: Under that is true he did, and I don't think

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Speaker 2: we're going to see any of that this time around.

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Speaker 2: But you know, there the thing with Biden is that

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Speaker 2: there was a story to tell about, uh, you know,

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Speaker 2: oligarchy and inequality and breaking up these tech giants and

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Speaker 2: why it matters to you, right, why these aren't just

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Speaker 2: like theoretical high falutin things that happening in some court

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Speaker 2: that really doesn't impact you, like how it connects. But

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Speaker 2: first of all, I don't think that he really cared that.

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Speaker 3: Much about this.

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Speaker 2: He cared about you know, NATO, that was like where

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Speaker 2: his brain was. I think these were people under him

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Speaker 2: that were more invested in this direction. Number one, number two,

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Speaker 2: like he was a million years old and couldn't articulate

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Speaker 2: anything about anything. So you end up with a situation

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Speaker 2: where he pissed off all of the Mark Zuckerberg's and

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Speaker 2: Elon Musk's of the world, and genuinely they felt like, oh,

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Speaker 2: there could be some sort of constraint on my you know,

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Speaker 2: on my endless power and wealth.

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Speaker 3: So they were pissed off while she was a few.

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Speaker 2: I mean, how many Wall Street Journal op eds were

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Speaker 2: written about how terrible Lena Khan was. Probably over one

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Speaker 2: hundred and literally that's not exact. Literally Matt Stuller kept

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Speaker 2: track of them. So they're furious, they hate him, they

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Speaker 2: know what he's doing, but the public has no idea

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Speaker 2: and are never bought in and invested in this project.

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Speaker 2: And so when it's you know, usurped and ended with

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Speaker 2: a whimper. And by the way, Kamala Harris gave some

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Speaker 2: indication she wasn't going to continue in that direction either,

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Speaker 2: so you know, keep it's yeah, I want to be

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Speaker 2: fair and point that out, but but yeah, so it

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Speaker 2: made sense to them, we're gonna line up behind this

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Speaker 2: guy who's gonna basically give us whatever we want. But

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Speaker 2: but yeah, if it was Kamala with those guys behind him, like, oh,

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Speaker 2: the freak out would be insane, and you know, and justified.

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Speaker 2: We sew like rightfully so, but Trump because he thinks,

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Speaker 2: he just thinks he can get away with anything, and

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Speaker 2: he might be right.

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Speaker 4: He can right now because the uh, I guess they

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Speaker 4: And this is you know, in a weird way connects

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Speaker 4: back to what we were talking about with AfD in

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Speaker 4: the other block. It's yeah, there have been years and

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Speaker 4: this isn't to say that Trump is blameless, but there

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Speaker 4: have been years of such terrible policy making that Trump

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Speaker 4: was able to successfully exploit that and come in and

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Speaker 4: he now has the support of the public on a

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Speaker 4: lot of different things. Not everybody, but there are a

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Speaker 4: lot of different I mean, he has significant support to

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Speaker 4: shake up Washington. And so when you look like you're

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Speaker 4: shaking up Washington, people can't pay attention to every tiny

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Speaker 4: little thing that's going on, so it looks directionally right,

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Speaker 4: and so I mean, there's just not a lot of

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Speaker 4: energy or appetite to push back on Trump after Democrats

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Speaker 4: and I think we have a list here of how

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Speaker 4: democrats or we have a graphic here showing how democrats

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Speaker 4: crats reacted to the firing of the Inspectors General. This

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Speaker 4: is D three. It just Democrats are going to have

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Speaker 4: to come up with a way to make this persuasive.

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Speaker 4: Here you have Chuck Schumer saying this is a quote

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Speaker 4: chilling purge and a preview of the lawless approach that

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Speaker 4: he expects Trump to take. Jerry Connolly and Virginia said

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Speaker 4: the dismissals were equal Friday night coup and a quote

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Speaker 4: assault on transparency and accountability. And Elizabeth Warren called out

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Speaker 4: a quote purge and accused Trump of dismantling constraints on

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Speaker 4: his authority. Now let's stick with the Connolly criticism there

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Speaker 4: where he says this is a quote assault on transparency

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Speaker 4: and accountability that covering up for Joe Biden for years.

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Speaker 4: By the way, this is not both sides as them.

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Speaker 4: It is saying that it makes it easier for Trump

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Speaker 4: to get away with a quote assault on transparency and

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Speaker 4: accountability when the people who are accusing him of assaulting

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Speaker 4: transparency and accountability have zero credibility to do it. And

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Speaker 4: that is one of the major two major political parties

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Speaker 4: in this country, and one of them just covered up

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Speaker 4: for a president who was ailing in front of your eyes,

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Speaker 4: told you that your eyes were lying to you, and

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Speaker 4: is now wanting to be upset about transparency and accountability.

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Speaker 4: So it actually is not good for the entire country

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Speaker 4: that Democrats have so little credibility on that question, because

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Speaker 4: it will make it a lot easier for Trump to

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Speaker 4: then quote assault transparency by purging inspectors general. Yeah, unlawfully.

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Speaker 4: By the way, if he had gone given them their

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Speaker 4: notice and done it, that would be another thing. But

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Speaker 4: he didn't.

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Speaker 2: Yeah, And I mean the same thing is true with

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Speaker 2: regards to oligarchy, Like if you want us, if you

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Speaker 2: expect the country to take you seriously on these things,

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Speaker 2: you can't be like Ken Martin, the guy who is

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Speaker 2: likely to be the next day and c chair being like, well,

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Speaker 2: we'll take money from good billionaires. It's like, no, how

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Speaker 2: about just there are no good billionaires. How about just

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Speaker 2: it's bad when billionaires, when unelected billionaires run our parties

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Speaker 2: and our government. How about that as a direction. And

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Speaker 2: so in my view, that's the choice they have in

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Speaker 2: front of them. They can either effectively like capitulate to

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Speaker 2: trump Ism, which is the direction they're likely to go

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Speaker 2: in and the direction they have been going in, see

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Speaker 2: you know, supporting the Lake and Riley.

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Speaker 3: Act, et cetera.

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Speaker 2: Or they could have a real like whose side, are

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Speaker 2: you on moment and decide that they're going to excize

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Speaker 2: this influence a big money within their own party so

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Speaker 2: that they can offer an actual different vision and direction

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Speaker 2: that has some credibility. But yeah, I mean, it's just

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Speaker 2: this is the storyline to watch, not just the moves

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Speaker 2: that Trump's Trump makes that are already quite maximalist. But

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Speaker 2: what's the response. Is there any check on him whatsoever?

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Speaker 2: Or can he just do whatever he wants even if

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Speaker 2: it's like brazenly unlawful.

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Speaker 4: And does it end up coming back on Republicans in

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Speaker 4: the midterms. A lot of that will depend on how

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Speaker 4: Democrats are able to claw back some measure of credibility

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Speaker 4: if they are able to, but Trump is definitely making

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Speaker 4: that a little bit easier on those questions.

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Speaker 2: All right, let's go on and get to Arnault Bertrand to

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Speaker 2: talk about Deep Seek.

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Speaker 3: This is a huge.

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Speaker 2: Development which has absolutely rocked Silicon Valley in terms of

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Speaker 2: Chinese AI development.

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Speaker 3: Here he is.

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Speaker 2: Very happy to be joined by Arnaud Bertrand. He described

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Speaker 2: himself as an entrepreneur who tweets too much, but I

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Speaker 2: have found your insights both with regards to China in general.

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Speaker 3: But this AI development.

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Speaker 2: In particular, I even brought you up earlier, Arnau in

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Speaker 2: the context of this fight with Colombia. So great to

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Speaker 2: have you here. Thank you so much for joining us.

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Speaker 7: Right, thank you as o wise, very good to be here.

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Speaker 2: Our pleasure. So I've teased this a couple times in

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Speaker 2: the show. But this is huge development from a Chinese

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Speaker 2: company which was able with a fraction of the dollar

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Speaker 2: amount to develop an AI competitor to chat, GPT and

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Speaker 2: all of the other sort of like big players in

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Speaker 2: the space. In fact, by some metrics, this new release

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Speaker 2: of it's called deep Seek is outperforming the prior competitors

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Speaker 2: in the field. This has blown up all sorts of

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Speaker 2: assumptions about AI development, about where Chinese companies were in

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Speaker 2: terms of their technological.

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Speaker 3: Sophistication, about the success of Biden.

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Speaker 2: Administration policies trying to limit high tech development in terms

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Speaker 2: of China. So are no, just take us through a

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Speaker 2: little bit of what happened here so people have the backstory.

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Speaker 7: Sure, So what happened doctorin started in December when deep

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Speaker 7: Seek released a first modern called V three, which already

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Speaker 7: made a lot of waves because it was rebuilt to

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Speaker 7: have been trained for only five point five million dollars,

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Speaker 7: which is absolutely nothing in this industry. I think open

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Speaker 7: Ai spends five billion dollars a year, so one hundred

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Speaker 7: times less basically, and uh, and that one was already

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Speaker 7: extremely good, already performing a lot of the models on

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Speaker 7: on the on on the important benchmarks. And then open

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Speaker 7: Ai you know, released a new model called OH one,

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Speaker 7: which is really you know, supposed to be the top

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Speaker 7: of the range. And then right behind just last week,

437
00:21:49,400 --> 00:21:53,320
Speaker 7: deep Sick released its own new modern called R one,

438
00:21:54,440 --> 00:22:00,399
Speaker 7: which performs or is on par with with Open the

439
00:22:00,440 --> 00:22:08,040
Speaker 7: Eyes h top of the ranch modern on on almost

440
00:22:08,040 --> 00:22:12,000
Speaker 7: all bench parks. And they released it, and that's the

441
00:22:12,040 --> 00:22:16,680
Speaker 7: important bits. They released it open source, meaning that basically

442
00:22:16,720 --> 00:22:21,000
Speaker 7: anyone can download it for free and use it as

443
00:22:21,040 --> 00:22:24,639
Speaker 7: they please. It's it's it's really open source and an

444
00:22:24,760 --> 00:22:28,480
Speaker 7: ma TL sense meaning that you can really, do you know,

445
00:22:28,800 --> 00:22:31,960
Speaker 7: use the other how however you want, which is a

446
00:22:32,040 --> 00:22:35,480
Speaker 7: huge difference to Open the Eye. It's called Open the

447
00:22:35,480 --> 00:22:39,280
Speaker 7: Eye because originally the philosophy behind it was that it

448
00:22:39,359 --> 00:22:42,159
Speaker 7: was meant to be open, open source and so on.

449
00:22:43,000 --> 00:22:47,399
Speaker 7: But famously they've they've taken a much more closed roots

450
00:22:47,440 --> 00:22:50,879
Speaker 7: where they don't realize their mothers in open source, and

451
00:22:51,280 --> 00:22:55,640
Speaker 7: you know, they don't disclose much about the mother It's

452
00:22:55,680 --> 00:23:00,960
Speaker 7: all behind sort of a black well. It's sort of

453
00:23:01,000 --> 00:23:04,000
Speaker 7: bit hidden. And so that's why a lot of people

454
00:23:04,200 --> 00:23:10,920
Speaker 7: are shifting to UH, to d sek now. And now

455
00:23:10,920 --> 00:23:16,000
Speaker 7: it's even demos downloaded app in the US as of today,

456
00:23:16,040 --> 00:23:18,920
Speaker 7: it's UH. It's number one. It's over taken all the

457
00:23:19,000 --> 00:23:22,200
Speaker 7: other apps, including including tipt wow.

458
00:23:22,680 --> 00:23:24,679
Speaker 4: And you know, our friend Matthew Stoller made an interesting

459
00:23:24,720 --> 00:23:27,320
Speaker 4: point in his newsletter Big where he said, when you

460
00:23:27,440 --> 00:23:31,520
Speaker 4: compare what China was able to do here with what

461
00:23:31,720 --> 00:23:35,240
Speaker 4: AI technology is basically the United States or AI companies

462
00:23:35,240 --> 00:23:37,439
Speaker 4: basically the United States have been able to do, it

463
00:23:37,520 --> 00:23:41,600
Speaker 4: almost makes the United States look soviet. It looks, you know,

464
00:23:41,720 --> 00:23:47,640
Speaker 4: like a Leviathan that is just just trudging along compared

465
00:23:47,680 --> 00:23:52,000
Speaker 4: to this alternative method. So could you do do you

466
00:23:52,000 --> 00:23:54,840
Speaker 4: think maybe there's something to that parallel or note or

467
00:23:54,920 --> 00:23:56,760
Speaker 4: is there is there something that we can take away

468
00:23:56,800 --> 00:24:02,040
Speaker 4: from the way American AI businesses are organized in comparison here.

469
00:24:03,240 --> 00:24:07,159
Speaker 7: I mean, I think the interesting irony is that maybe

470
00:24:07,160 --> 00:24:11,000
Speaker 7: there was a bit too much funding in the AI

471
00:24:11,440 --> 00:24:15,639
Speaker 7: industry in the US for its own good. They're a

472
00:24:15,680 --> 00:24:20,320
Speaker 7: bit too much of an easy life, because the reason

473
00:24:20,400 --> 00:24:25,439
Speaker 7: why Deepsy I think, was able to come up with

474
00:24:25,520 --> 00:24:28,800
Speaker 7: such a good and efficient modern is because they're very

475
00:24:28,840 --> 00:24:32,879
Speaker 7: much operating under constraints. Right. You had the export controls,

476
00:24:32,920 --> 00:24:36,920
Speaker 7: the semiconductor export control and so China in many ways

477
00:24:37,119 --> 00:24:40,159
Speaker 7: doesn't have a choice if they want to compete with

478
00:24:40,240 --> 00:24:43,960
Speaker 7: the US, given they don't have, you know, such access

479
00:24:44,040 --> 00:24:47,560
Speaker 7: to funding, the latest chips and so on, and they

480
00:24:47,640 --> 00:24:51,240
Speaker 7: need to come up with much more efficient technology. So

481
00:24:51,280 --> 00:24:54,360
Speaker 7: I wouldn't say it's it's exactly the same situation as

482
00:24:53,960 --> 00:24:59,639
Speaker 7: as the Soviet versus the West of the time. It's

483
00:24:59,680 --> 00:25:02,640
Speaker 7: it's a most the situation where you know, you you

484
00:25:02,960 --> 00:25:05,560
Speaker 7: the US kind of rested on its low arms and

485
00:25:06,760 --> 00:25:09,320
Speaker 7: and uh, you know, I did to be tweezy and

486
00:25:09,440 --> 00:25:14,040
Speaker 7: was operating in in too good an environments on China

487
00:25:14,560 --> 00:25:17,240
Speaker 7: because of those constraints the the US put on them,

488
00:25:17,840 --> 00:25:22,440
Speaker 7: they actually have to come up with simply better technology

489
00:25:22,440 --> 00:25:24,800
Speaker 7: if they want to compete on I think that's largely

490
00:25:24,880 --> 00:25:25,720
Speaker 7: what happened.

491
00:25:26,240 --> 00:25:28,399
Speaker 2: I think another piece that you've been pointing to ar now,

492
00:25:28,440 --> 00:25:32,400
Speaker 2: which I find really interesting is China does not our country,

493
00:25:32,680 --> 00:25:35,439
Speaker 2: by and large, a lot of the smartest grads that

494
00:25:35,520 --> 00:25:38,240
Speaker 2: come out with technical degrees or technical know how, a

495
00:25:38,240 --> 00:25:40,480
Speaker 2: lot of them don't go into science or research. They

496
00:25:40,520 --> 00:25:44,960
Speaker 2: go into like financial speculation effectively, and the Chinese government

497
00:25:45,000 --> 00:25:46,720
Speaker 2: has looked at them and said, that's not the direction

498
00:25:46,760 --> 00:25:49,320
Speaker 2: we want to go in, So they crack down on

499
00:25:49,960 --> 00:25:54,040
Speaker 2: salaries for you know, the financial industry, and that creates

500
00:25:54,080 --> 00:25:56,200
Speaker 2: incentives for the best and the brightest lo and behold

501
00:25:56,200 --> 00:26:00,240
Speaker 2: to go into this sort of research and tech development.

502
00:26:00,400 --> 00:26:02,520
Speaker 3: So talk about that piece a little bit if you could.

503
00:26:03,160 --> 00:26:05,600
Speaker 7: Yeah, I think it's one of the most interesting angers

504
00:26:05,640 --> 00:26:09,360
Speaker 7: of Deep Sick because it was actually a side project

505
00:26:09,440 --> 00:26:16,720
Speaker 7: of a Hatch fund and that was released quite coincidentally

506
00:26:16,840 --> 00:26:21,560
Speaker 7: about uh less than one year after China did crack

507
00:26:21,640 --> 00:26:26,600
Speaker 7: down against the finance industry. This uh this this you know,

508
00:26:26,800 --> 00:26:29,920
Speaker 7: overly high compensation in the in the financial industry. Kepting

509
00:26:29,960 --> 00:26:33,720
Speaker 7: it and there has been you know, you you you

510
00:26:34,000 --> 00:26:36,320
Speaker 7: here in China a lot of miscontent in the finance

511
00:26:36,359 --> 00:26:39,879
Speaker 7: industry professioners because, yeah, they can't make as much money

512
00:26:40,000 --> 00:26:43,320
Speaker 7: on it's the industry is becoming less attractive for graduates

513
00:26:43,400 --> 00:26:45,400
Speaker 7: on the and they're seeing a bit of a brain

514
00:26:45,520 --> 00:26:48,840
Speaker 7: drain from that industry. But That is very much the

515
00:26:48,920 --> 00:26:53,760
Speaker 7: point I think that the Chaine government is UH is

516
00:26:53,960 --> 00:26:56,840
Speaker 7: aiming for because they're looking at the US and they're

517
00:26:56,880 --> 00:26:59,840
Speaker 7: seeing which is a shame when you think about it.

518
00:27:00,440 --> 00:27:02,920
Speaker 7: A lot of the top gradiates from Harvard and IT

519
00:27:04,000 --> 00:27:08,560
Speaker 7: and you know, all the Aleage Ivy League schools often

520
00:27:08,640 --> 00:27:13,240
Speaker 7: go in the finance industry. When I mean, think what

521
00:27:13,359 --> 00:27:16,119
Speaker 7: you want about the finance industry, but if you have

522
00:27:16,800 --> 00:27:22,240
Speaker 7: pure genius, arguably their brains would be of more use

523
00:27:22,359 --> 00:27:26,439
Speaker 7: to society they were to develop new technology like like

524
00:27:26,600 --> 00:27:31,040
Speaker 7: AI or working on you know, curing cancer or or

525
00:27:31,760 --> 00:27:34,760
Speaker 7: things like that. And and I think this time gole

526
00:27:34,880 --> 00:27:39,119
Speaker 7: is is UH is fascinating because I mean, it's it's

527
00:27:39,160 --> 00:27:42,639
Speaker 7: it's difficult to put a direct correction. Did they do

528
00:27:42,760 --> 00:27:45,560
Speaker 7: that side project exactly because of that or not? But

529
00:27:45,640 --> 00:27:49,120
Speaker 7: at least it's it's an interesting, interesting coincidence.

530
00:27:49,880 --> 00:27:53,280
Speaker 4: M Yeah. In the stock market, we're already seeing some

531
00:27:53,320 --> 00:27:55,520
Speaker 4: of the effect of this in the stock market. Okay,

532
00:27:55,560 --> 00:27:57,880
Speaker 4: can you talk a little bit more about why it's

533
00:27:57,880 --> 00:27:59,440
Speaker 4: affecting stocks in the way it is and what we

534
00:27:59,480 --> 00:28:03,760
Speaker 4: could expect see going forward as the deep sea deepep

535
00:28:03,880 --> 00:28:07,800
Speaker 4: reckon reckoning goes on yeah.

536
00:28:07,680 --> 00:28:11,960
Speaker 7: So I was looking at it actually a portfolio just now.

537
00:28:12,440 --> 00:28:19,800
Speaker 7: It's very depressing. So Nvidia just so is losing twelve

538
00:28:19,840 --> 00:28:25,040
Speaker 7: percent today, and yeah, the whole tech sector is down.

539
00:28:25,760 --> 00:28:30,280
Speaker 7: And basically because there was this assumption that AI was

540
00:28:30,320 --> 00:28:33,520
Speaker 7: all about compute, like more chips you could get better

541
00:28:33,520 --> 00:28:39,600
Speaker 7: on models, right and on the Deepsy kind of destroy

542
00:28:39,720 --> 00:28:42,760
Speaker 7: that assumption because they don't have a lot of compute

543
00:28:42,880 --> 00:28:45,480
Speaker 7: and they were able to come with a better model

544
00:28:45,560 --> 00:28:49,880
Speaker 7: because they had you know, better algorithms, better software. And

545
00:28:50,000 --> 00:28:56,040
Speaker 7: so what's happening is simply that those assumptions around building

546
00:28:56,160 --> 00:29:02,040
Speaker 7: a mood for us AI company with compute, with those

547
00:29:02,080 --> 00:29:05,400
Speaker 7: massive data, some tools like you know, the Stellgate project

548
00:29:05,480 --> 00:29:09,840
Speaker 7: that Trump open AI on so and just announced, those

549
00:29:10,160 --> 00:29:15,440
Speaker 7: are you know, very much questioned right now. And that's

550
00:29:15,440 --> 00:29:17,680
Speaker 7: what you're seeing I think in the in the stock market.

551
00:29:18,120 --> 00:29:21,920
Speaker 2: Yeah absolutely, I mean so much of the stock market

552
00:29:22,160 --> 00:29:26,280
Speaker 2: value is built on this sort of like hype around AI,

553
00:29:26,880 --> 00:29:31,880
Speaker 2: and so I mean it's incredibly deflating literally to see

554
00:29:32,240 --> 00:29:34,920
Speaker 2: this company be able to you know, build a comparable

555
00:29:34,960 --> 00:29:38,240
Speaker 2: product for vastly less. I will say I've seen some

556
00:29:38,360 --> 00:29:41,600
Speaker 2: theories that they're not being straightforward about the amount of

557
00:29:41,640 --> 00:29:45,920
Speaker 2: compute that they actually used here, most notably the scale.

558
00:29:45,960 --> 00:29:49,320
Speaker 2: AI CEO Alexander Wang and I think he was at

559
00:29:49,320 --> 00:29:52,200
Speaker 2: the World Economic Forum, claimed that he thinks that they

560
00:29:52,320 --> 00:29:55,200
Speaker 2: are hiding the ball on exactly how many chips, like

561
00:29:55,240 --> 00:29:57,280
Speaker 2: what size of the mega cluster that they're using.

562
00:29:57,320 --> 00:29:58,920
Speaker 3: Let's take a listen to that and get your reaction.

563
00:29:58,960 --> 00:29:59,320
Speaker 3: On the other.

564
00:29:59,280 --> 00:30:03,400
Speaker 8: Side, the Chinese labs, they have more h one hundreds

565
00:30:03,440 --> 00:30:06,880
Speaker 8: than people think. You know, the these are the highest

566
00:30:06,920 --> 00:30:09,360
Speaker 8: powered video chips that they were not supposed to have. Yes,

567
00:30:09,960 --> 00:30:12,960
Speaker 8: my understanding is that is that deep seek has about

568
00:30:13,040 --> 00:30:17,120
Speaker 8: fifty one hundreds, which they can't talk about obviously because

569
00:30:17,120 --> 00:30:19,360
Speaker 8: it is against the export controls that the United States

570
00:30:19,400 --> 00:30:20,120
Speaker 8: has put in place.

571
00:30:20,280 --> 00:30:20,920
Speaker 4: And I think it is.

572
00:30:20,880 --> 00:30:22,840
Speaker 8: True that, you know, I think they have more chips

573
00:30:22,840 --> 00:30:25,680
Speaker 8: than other people expect, but also going to go forward basis,

574
00:30:25,720 --> 00:30:27,560
Speaker 8: they are going to be limited by the chip controls

575
00:30:27,600 --> 00:30:29,560
Speaker 8: and the export controls that we have in place.

576
00:30:30,000 --> 00:30:30,920
Speaker 3: What do you make of that.

577
00:30:33,560 --> 00:30:37,000
Speaker 7: Well, it's difficult to say one way or the other.

578
00:30:37,840 --> 00:30:40,600
Speaker 7: But the good thing but Deep Seek is that when

579
00:30:40,600 --> 00:30:43,440
Speaker 7: they release the modern so firs where the ready is

580
00:30:43,480 --> 00:30:45,640
Speaker 7: the open source, so it's sort of you can see

581
00:30:45,680 --> 00:30:49,200
Speaker 7: what's in the modern and they released on extremely detailed

582
00:30:49,280 --> 00:30:54,200
Speaker 7: paper with it. So he research sho and just go

583
00:30:54,320 --> 00:30:59,320
Speaker 7: through the paper and you'll try to achieve the same outcome,

584
00:30:59,400 --> 00:31:04,080
Speaker 7: which is the based on what they're saying they did

585
00:31:04,320 --> 00:31:07,680
Speaker 7: in the paper on see if if that's true or not,

586
00:31:08,920 --> 00:31:14,120
Speaker 7: or or or if what the method urgy that they're

587
00:31:14,160 --> 00:31:20,160
Speaker 7: saying they posted in the paper is wrong on on

588
00:31:20,360 --> 00:31:24,360
Speaker 7: debating about the number of chips. So I can't say.

589
00:31:24,280 --> 00:31:26,160
Speaker 3: Yeah, well I agree.

590
00:31:26,280 --> 00:31:28,520
Speaker 2: I read some analyzes you know that looked at the

591
00:31:28,560 --> 00:31:31,280
Speaker 2: paper and said, well, here's the key innovations that they

592
00:31:31,360 --> 00:31:34,480
Speaker 2: use to achieve so much more efficiency, way beyond my

593
00:31:34,560 --> 00:31:36,640
Speaker 2: technical know how. But people who seem to know what

594
00:31:36,640 --> 00:31:38,160
Speaker 2: they were talking about were like, oh, that's how.

595
00:31:38,040 --> 00:31:38,440
Speaker 3: They did it.

596
00:31:38,480 --> 00:31:43,640
Speaker 2: I see, he's very creative and efficient and efficient technological

597
00:31:43,680 --> 00:31:44,440
Speaker 2: development here.

598
00:31:44,760 --> 00:31:44,880
Speaker 3: Uh.

599
00:31:45,200 --> 00:31:46,840
Speaker 2: One more I wanted to get your response to our

600
00:31:46,920 --> 00:31:49,400
Speaker 2: no is Sam Altman weighed in, obviously this is a

601
00:31:49,520 --> 00:31:52,320
Speaker 2: very bad development for him because he has bet so

602
00:31:52,400 --> 00:31:54,880
Speaker 2: much on, you know, now the Stargate program. I know

603
00:31:54,920 --> 00:31:57,080
Speaker 2: he'd been sort of battling with Microsoft for more and

604
00:31:57,120 --> 00:32:01,120
Speaker 2: more money for larger and larger data centers, and you know,

605
00:32:01,200 --> 00:32:03,160
Speaker 2: now this sort of blows that whole direction up.

606
00:32:03,240 --> 00:32:04,280
Speaker 3: Let's put this up on the screen.

607
00:32:04,360 --> 00:32:08,040
Speaker 2: D three from Sam Altman, he says it is relatively

608
00:32:08,120 --> 00:32:09,400
Speaker 2: easy to copy.

609
00:32:09,120 --> 00:32:11,720
Speaker 3: Something that you know works. It is extremely hard.

610
00:32:11,480 --> 00:32:13,880
Speaker 2: To do something new, risky and difficult when you don't

611
00:32:13,880 --> 00:32:17,160
Speaker 2: know if it will work. Individual researchers rightly get a

612
00:32:17,160 --> 00:32:19,560
Speaker 2: lot of glory for that when they do it, it's

613
00:32:19,600 --> 00:32:21,560
Speaker 2: the coolest thing in the world. And of course this

614
00:32:21,720 --> 00:32:25,959
Speaker 2: was largely seen as being directed at the deep Sek development.

615
00:32:26,480 --> 00:32:28,680
Speaker 2: What do you make of these comments from Sam?

616
00:32:29,360 --> 00:32:32,920
Speaker 7: Deep seek is definitely getting a lot of glories, so

617
00:32:33,880 --> 00:32:39,040
Speaker 7: I'm not sure exactly what it means. I think something

618
00:32:39,200 --> 00:32:42,760
Speaker 7: very interesting, and I think a big sign is what

619
00:32:43,920 --> 00:32:47,600
Speaker 7: Mark Andresen is tweeting recently. I don't know if you

620
00:32:48,600 --> 00:32:51,400
Speaker 7: if you if you forget what is what is tweeted

621
00:32:51,440 --> 00:32:55,560
Speaker 7: Because obviously Sam at mine is biased. I think Mark

622
00:32:55,600 --> 00:33:00,560
Speaker 7: Andrison is slightly more of a neutral part. He here

623
00:33:01,000 --> 00:33:08,080
Speaker 7: because he's an investor and he literally tweeted count fram

624
00:33:08,080 --> 00:33:11,720
Speaker 7: about the exact good. But that Deep Seek was the

625
00:33:12,400 --> 00:33:15,480
Speaker 7: most impressive, one of the most impressive breakthroughs it's seen

626
00:33:15,520 --> 00:33:21,360
Speaker 7: in its entire career, and that silicons varies mostly gender investor,

627
00:33:21,680 --> 00:33:25,680
Speaker 7: the guy we invented the browser, so you know, it's

628
00:33:25,760 --> 00:33:28,240
Speaker 7: quite it's quite something, right, he.

629
00:33:28,280 --> 00:33:31,080
Speaker 2: Said, one of the most amazing and impressive breakthroughs I've

630
00:33:31,080 --> 00:33:33,400
Speaker 2: ever seen. And just to clarify that Amen tweet was

631
00:33:33,440 --> 00:33:36,800
Speaker 2: from back in December, so presumably about the initial relation

632
00:33:37,040 --> 00:33:38,000
Speaker 2: of deep seek.

633
00:33:37,760 --> 00:33:41,800
Speaker 7: But okay, yeah, yeah, so yeah, yeah. The new murder

634
00:33:41,880 --> 00:33:45,400
Speaker 7: is also quite a bit. It's more of a breakthrough

635
00:33:45,480 --> 00:33:49,560
Speaker 7: than than the three, which was the one in December.

636
00:33:49,800 --> 00:33:51,440
Speaker 3: My last question for you, Arno is.

637
00:33:52,840 --> 00:33:55,840
Speaker 2: Are there is there a legitimate reason to keep AI

638
00:33:56,880 --> 00:34:00,400
Speaker 2: closed source as open AI has has decided, because, I mean,

639
00:34:00,440 --> 00:34:03,800
Speaker 2: there are risks inherent in AI development. I mean there's

640
00:34:03,800 --> 00:34:06,240
Speaker 2: a whole field of AI safety, a lot of concerns

641
00:34:06,640 --> 00:34:09,560
Speaker 2: about what it could do in terms of the labor market,

642
00:34:09,640 --> 00:34:13,319
Speaker 2: especially when it's being wielded for profit by companies like Microsoft.

643
00:34:13,400 --> 00:34:16,400
Speaker 2: There are also some more for reaching concerns about AI.

644
00:34:16,680 --> 00:34:19,640
Speaker 2: You know, once it's AGI and you have this level

645
00:34:19,640 --> 00:34:23,600
Speaker 2: of artificial general intelligence and then super intelligence that you know,

646
00:34:23,840 --> 00:34:28,320
Speaker 2: effectively supplants human beings as the you know, the smartest

647
00:34:28,320 --> 00:34:30,560
Speaker 2: creatures on the planet. What does that mean do they

648
00:34:30,880 --> 00:34:33,000
Speaker 2: decide they want to keep us around or not, so

649
00:34:33,080 --> 00:34:35,520
Speaker 2: there are these sort of like further reaching concerns about

650
00:34:35,800 --> 00:34:40,080
Speaker 2: AI development as well. Do you see any drawbacks in

651
00:34:40,239 --> 00:34:43,240
Speaker 2: the open source model that not only deepseek has pursued,

652
00:34:43,280 --> 00:34:46,400
Speaker 2: but also the Meta has gone in the direction of

653
00:34:46,400 --> 00:34:47,839
Speaker 2: a more open source model as well.

654
00:34:51,160 --> 00:34:58,560
Speaker 7: That's a good question. I honestly see more drawbacks with

655
00:34:58,840 --> 00:35:02,680
Speaker 7: the cruise moder because at the end of the day,

656
00:35:03,320 --> 00:35:06,640
Speaker 7: if it's closed, it's it's it's a limited group of

657
00:35:06,719 --> 00:35:13,520
Speaker 7: individuals who you don't have control over, and you know,

658
00:35:13,560 --> 00:35:18,080
Speaker 7: our oligachx effectively like billionaires and that that take all

659
00:35:18,120 --> 00:35:21,200
Speaker 7: the decisions when it comes to AI, which you're right,

660
00:35:21,840 --> 00:35:26,040
Speaker 7: is going to be extremely disruptive. It's an extremely powerful technology.

661
00:35:26,520 --> 00:35:31,120
Speaker 7: So would you rather have that being controlled by a

662
00:35:31,160 --> 00:35:37,879
Speaker 7: small group of billionaires were you know, very much can't

663
00:35:38,000 --> 00:35:41,520
Speaker 7: relate to the general public, or would you rather have

664
00:35:41,600 --> 00:35:45,839
Speaker 7: the general public anyone who can you know, have an

665
00:35:45,840 --> 00:35:49,879
Speaker 7: influence of that on that with the the open source model,

666
00:35:49,960 --> 00:35:55,279
Speaker 7: I think, I mean anyway that technology has risks, will

667
00:35:55,320 --> 00:35:59,680
Speaker 7: have a big impact, will impact jobs and so on. Uh,

668
00:36:00,080 --> 00:36:04,680
Speaker 7: But I feel more reassured with the idea that anyone

669
00:36:04,680 --> 00:36:08,480
Speaker 7: will have to say on how I developed that it

670
00:36:08,560 --> 00:36:12,160
Speaker 7: is open free. Anyone can come up with uh, you know,

671
00:36:12,239 --> 00:36:17,680
Speaker 7: startup around it freely on his own computer, rather than

672
00:36:18,560 --> 00:36:24,760
Speaker 7: it being kind of uh developed secretly out of our hands.

673
00:36:23,640 --> 00:36:27,920
Speaker 4: And what we've learned from our own private tech companies

674
00:36:27,920 --> 00:36:30,560
Speaker 4: semi private tech companies over the last decade is that

675
00:36:30,640 --> 00:36:33,880
Speaker 4: you will also have similar levels of censorship and political

676
00:36:34,000 --> 00:36:38,480
Speaker 4: corruption whether they're private or public, they get co opted

677
00:36:38,640 --> 00:36:38,799
Speaker 4: or no.

678
00:36:39,680 --> 00:36:43,879
Speaker 7: Yeah, yeah. On censorship, it's it's an extremely good good

679
00:36:43,920 --> 00:36:48,320
Speaker 7: point because people often you see a lot on Twitter,

680
00:36:48,680 --> 00:36:52,880
Speaker 7: you know, people saying that the deepstick mother is uh

681
00:36:53,320 --> 00:36:56,799
Speaker 7: is censored, and it's true that when you go on

682
00:36:56,840 --> 00:37:00,480
Speaker 7: deepstick dot com because it is hosted in China, it

683
00:37:00,640 --> 00:37:04,880
Speaker 7: is indeed censored because you have censorship lose in China

684
00:37:04,880 --> 00:37:07,800
Speaker 7: and sun where anyone can download the modernate in open

685
00:37:07,840 --> 00:37:10,880
Speaker 7: source you need however they want. If they want to

686
00:37:10,920 --> 00:37:14,560
Speaker 7: turn it into a tool that you know, even generates

687
00:37:14,560 --> 00:37:19,160
Speaker 7: anti China propaganda, they can write. So that's what I

688
00:37:19,200 --> 00:37:22,600
Speaker 7: mean by me being more reassured that its open source

689
00:37:22,640 --> 00:37:25,720
Speaker 7: because anyone can do whatever they want with it, whereas

690
00:37:25,760 --> 00:37:28,400
Speaker 7: open ai, if it's so and so on, it's also

691
00:37:28,440 --> 00:37:31,040
Speaker 7: stands on in its own way. There's absolutely nothing you

692
00:37:31,080 --> 00:37:31,719
Speaker 7: can do for it.

693
00:37:32,080 --> 00:37:33,520
Speaker 3: Yeah, that's that's true.

694
00:37:33,520 --> 00:37:36,359
Speaker 2: And I did see the comparison of people asking just

695
00:37:36,440 --> 00:37:40,040
Speaker 2: very straightforward questions about like the Israel Palestine conflict on

696
00:37:40,840 --> 00:37:45,040
Speaker 2: ch GPT versus Deep Sick, and I would I would

697
00:37:45,040 --> 00:37:48,200
Speaker 2: say that the deep Seak version was much less censored

698
00:37:48,600 --> 00:37:51,480
Speaker 2: in that particular instance than the Open AI.

699
00:37:52,040 --> 00:37:53,279
Speaker 3: The open AI version.

700
00:37:54,200 --> 00:37:57,880
Speaker 7: Exactly every country has their own baas by the end

701
00:37:57,880 --> 00:38:01,279
Speaker 7: of the day, open source metals because you can then

702
00:38:01,400 --> 00:38:06,080
Speaker 7: under the donother yourself on input your own Yes, Nik,

703
00:38:06,200 --> 00:38:07,120
Speaker 7: it's your own right.

704
00:38:08,239 --> 00:38:08,919
Speaker 3: That's what I need.

705
00:38:08,960 --> 00:38:11,880
Speaker 2: I need the world to reflect my personal bibar No.

706
00:38:12,000 --> 00:38:12,600
Speaker 3: Thank you so much.

707
00:38:12,640 --> 00:38:15,360
Speaker 2: This is so helpful getting your breakdown of these developments

708
00:38:15,400 --> 00:38:16,319
Speaker 2: and what it ultimately means.

709
00:38:16,360 --> 00:38:16,880
Speaker 3: Great to see you.

710
00:38:19,800 --> 00:38:21,920
Speaker 2: We are very fortunate to be joined this morning by

711
00:38:21,960 --> 00:38:24,560
Speaker 2: Andrew Callahan of Channel five, who is out with a

712
00:38:24,600 --> 00:38:27,600
Speaker 2: new documentary called Dear Kelly. Great to have you Andrew.

713
00:38:27,600 --> 00:38:27,920
Speaker 4: Welcome.

714
00:38:28,160 --> 00:38:30,000
Speaker 9: Hey, thanks so much for having me and I'm a

715
00:38:30,000 --> 00:38:32,239
Speaker 9: big fan of Breaking points. I appreciate you guys for

716
00:38:32,320 --> 00:38:35,440
Speaker 9: the platform. It's early morning, thanks to y'all, so thank.

717
00:38:35,239 --> 00:38:35,880
Speaker 5: You for having me on.

718
00:38:36,360 --> 00:38:38,480
Speaker 2: Thank you for waking up for us. We appreciate that

719
00:38:38,600 --> 00:38:41,600
Speaker 2: we are likewise big fans. Let me give people a

720
00:38:41,640 --> 00:38:44,080
Speaker 2: little bit a taste of the trailer here, and then

721
00:38:44,120 --> 00:38:45,880
Speaker 2: on the other side you can tell them the backstory

722
00:38:45,920 --> 00:38:48,880
Speaker 2: of what inspired you to follow this one individual.

723
00:38:48,960 --> 00:38:49,640
Speaker 3: Let's take a look.

724
00:38:49,920 --> 00:38:53,080
Speaker 10: Why did the framework created by QAnon and Trump propaganda

725
00:38:53,200 --> 00:38:55,840
Speaker 10: cause an innumerable amount of people to jump head first

726
00:38:55,880 --> 00:38:59,040
Speaker 10: down the rabbit hole, endangering their safety, lives, and freedom.

727
00:38:59,080 --> 00:39:00,239
Speaker 5: I thought I had it figure out.

728
00:39:00,280 --> 00:39:02,879
Speaker 10: I pointed fingers at the fear mongering twenty four hour

729
00:39:02,920 --> 00:39:03,440
Speaker 10: news cycle.

730
00:39:03,680 --> 00:39:05,640
Speaker 4: There's nothing fake about CNN and.

731
00:39:05,640 --> 00:39:08,279
Speaker 10: At radio hosts who sell supplements and T shirts to

732
00:39:08,320 --> 00:39:11,719
Speaker 10: paranoid libertarians. But deep down I didn't really know that

733
00:39:12,000 --> 00:39:14,560
Speaker 10: was until I met a man named Kelly J. Patriot

734
00:39:14,600 --> 00:39:17,560
Speaker 10: at a White Lives Matter rally in Huntington Beach, California,

735
00:39:17,640 --> 00:39:20,839
Speaker 10: and asked him one question, what's the most painful piece

736
00:39:20,880 --> 00:39:21,680
Speaker 10: of truth that's hurt you?

737
00:39:22,520 --> 00:39:25,560
Speaker 11: Guy stealing my home? His name's Bill Joyner. Financially he

738
00:39:25,600 --> 00:39:28,160
Speaker 11: wanted to destroy me. He destroyed my twenty five year business,

739
00:39:28,360 --> 00:39:31,360
Speaker 11: separated and devastated my family. So that answers your question.

740
00:39:31,239 --> 00:39:32,240
Speaker 5: Dude, sounds like he sucks.

741
00:39:33,040 --> 00:39:34,720
Speaker 11: I don't think he's a good guy. In my opinion,

742
00:39:34,719 --> 00:39:36,360
Speaker 11: he's a bad guy and he's heard a lot of people.

743
00:39:36,440 --> 00:39:38,560
Speaker 11: But then again, look what the Democrats are doing to others.

744
00:39:38,760 --> 00:39:41,400
Speaker 11: Krby Bryant was assassinated by the plins.

745
00:39:41,520 --> 00:39:43,440
Speaker 4: I don't fucking die homies straight up.

746
00:39:43,680 --> 00:39:45,279
Speaker 2: So what was it that caused you to be sort

747
00:39:45,280 --> 00:39:47,960
Speaker 2: of captivated by this guy and to really follow up

748
00:39:48,000 --> 00:39:50,000
Speaker 2: with him and figure out what was actually going on there?

749
00:39:51,320 --> 00:39:53,200
Speaker 9: I think that it came from like a just not

750
00:39:53,280 --> 00:39:56,839
Speaker 9: being satisfied with like my kind of deep dives into

751
00:39:56,880 --> 00:39:59,080
Speaker 9: like the Maga far right for a long time. I

752
00:39:59,080 --> 00:40:01,920
Speaker 9: had just followed Trump campaign trail across the country filming

753
00:40:01,920 --> 00:40:04,480
Speaker 9: for my first project on HBO, and I felt like

754
00:40:04,560 --> 00:40:07,120
Speaker 9: I had sort of been able to document the craziness

755
00:40:07,200 --> 00:40:09,160
Speaker 9: and like a time capsule, but never really been able

756
00:40:09,160 --> 00:40:13,080
Speaker 9: to understand what economic and social factors actually cause people

757
00:40:13,160 --> 00:40:17,480
Speaker 9: to become radicalized, especially dudes through later in life like Kelly.

758
00:40:17,520 --> 00:40:19,919
Speaker 5: And I never really was able to actually dig deep.

759
00:40:19,960 --> 00:40:22,640
Speaker 9: But in his story about Bill Joyner and the foreclosure

760
00:40:22,640 --> 00:40:24,719
Speaker 9: of his house and his family being separated, I saw

761
00:40:24,760 --> 00:40:27,200
Speaker 9: a window and a chance to actually figure out.

762
00:40:27,120 --> 00:40:28,920
Speaker 5: The why of how people get like that in the

763
00:40:28,920 --> 00:40:29,440
Speaker 5: first place.

764
00:40:29,760 --> 00:40:32,799
Speaker 4: Yeah, and you're probably this like central chicken or egg

765
00:40:32,880 --> 00:40:34,640
Speaker 4: question that a lot of your work is based on,

766
00:40:34,680 --> 00:40:36,440
Speaker 4: which you know. I think one of the reasons people

767
00:40:36,560 --> 00:40:38,799
Speaker 4: love your work is you come to this idea that, like,

768
00:40:38,880 --> 00:40:42,279
Speaker 4: there are a lot of very good people who do

769
00:40:42,360 --> 00:40:44,759
Speaker 4: a lot of crazy things and get caught up in

770
00:40:44,800 --> 00:40:48,000
Speaker 4: the fringes, and you include some interesting stats about January sixth,

771
00:40:48,120 --> 00:40:52,160
Speaker 4: and for example people's debt levels, like whether they were

772
00:40:52,160 --> 00:40:54,839
Speaker 4: there on January six if they had particular levels of debt.

773
00:40:54,840 --> 00:40:57,080
Speaker 4: There's just a big proportion of people. I didn't even

774
00:40:57,120 --> 00:40:59,440
Speaker 4: realize that there were numbers attached to all of this.

775
00:40:59,560 --> 00:41:01,120
Speaker 4: I mean, you could see it when you were there.

776
00:41:01,160 --> 00:41:04,040
Speaker 4: But can you tell us a little bit about how

777
00:41:04,120 --> 00:41:09,359
Speaker 4: this experience with Kelly either changed modified added nuance to

778
00:41:09,640 --> 00:41:12,200
Speaker 4: the way you see the world that you know, maybe

779
00:41:12,200 --> 00:41:15,360
Speaker 4: there are some people who come into all of this

780
00:41:15,480 --> 00:41:19,560
Speaker 4: stuff with prior difficulties and then it changes them or

781
00:41:20,239 --> 00:41:22,240
Speaker 4: is it just you know, a one way street.

782
00:41:23,920 --> 00:41:25,000
Speaker 5: Yeah, that's a great question.

783
00:41:25,080 --> 00:41:27,600
Speaker 9: I mean, before I started documenting Kelly, and this is

784
00:41:27,640 --> 00:41:29,480
Speaker 9: filmed over the course of four and a half years,

785
00:41:29,600 --> 00:41:31,719
Speaker 9: I didn't realize that so many people who like were

786
00:41:31,760 --> 00:41:34,920
Speaker 9: so deep in that QAnon rabbit hole had just normal

787
00:41:35,000 --> 00:41:37,879
Speaker 9: lives like in twenty twenty that were completely derailed by

788
00:41:38,120 --> 00:41:42,400
Speaker 9: financial hardship, and particularly how that coalesced with like political psychosis.

789
00:41:43,239 --> 00:41:45,680
Speaker 9: I don't like using the word misinformation because it's not

790
00:41:45,719 --> 00:41:46,759
Speaker 9: like everything they read is.

791
00:41:46,760 --> 00:41:48,640
Speaker 5: Totally false or consumes false, but.

792
00:41:48,600 --> 00:41:50,640
Speaker 9: It's just being locked in this echo chamber of like

793
00:41:50,680 --> 00:41:53,120
Speaker 9: twenty four to seven outrage content for a long period

794
00:41:53,160 --> 00:41:56,360
Speaker 9: of time. And definitely learned a lot about just people

795
00:41:56,400 --> 00:41:59,200
Speaker 9: like that in general, but also about myself as a

796
00:41:59,239 --> 00:42:02,640
Speaker 9: documentary film and how emotionally invested I want to be

797
00:42:03,040 --> 00:42:04,960
Speaker 9: in the outcome of like a subject or someone that

798
00:42:05,000 --> 00:42:07,360
Speaker 9: I'm documenting, Like by the end of the film, especially

799
00:42:07,440 --> 00:42:09,840
Speaker 9: like after the intervention to spoil it a bit, not

800
00:42:09,920 --> 00:42:12,879
Speaker 9: too much, I was so emotionally invested in Kelly turning

801
00:42:13,040 --> 00:42:15,520
Speaker 9: over this new leaf that it became.

802
00:42:15,320 --> 00:42:17,000
Speaker 5: Like more important than my own life.

803
00:42:17,640 --> 00:42:19,239
Speaker 9: And I don't think I ever want to get that

804
00:42:19,400 --> 00:42:21,959
Speaker 9: involved again, because I mean, I had filmed three hundred

805
00:42:21,960 --> 00:42:25,080
Speaker 9: and fifty hours of footage in total, and I ultimately

806
00:42:25,080 --> 00:42:27,120
Speaker 9: baked it down to eighty nine minutes, But it was

807
00:42:27,160 --> 00:42:30,000
Speaker 9: like my personal expectations were tethered to his in a

808
00:42:30,000 --> 00:42:32,000
Speaker 9: way that I'm not sure was super healthy.

809
00:42:32,880 --> 00:42:36,080
Speaker 2: I think for me, as a democratic socialist who thinks

810
00:42:36,120 --> 00:42:39,360
Speaker 2: a lot about like class analysis, the way you approach

811
00:42:39,480 --> 00:42:43,080
Speaker 2: this really played into some of my sort of mental

812
00:42:43,160 --> 00:42:46,719
Speaker 2: preconceptions because you're like, there was a material harm that

813
00:42:46,760 --> 00:42:49,359
Speaker 2: happened to a lot of these people and it sort

814
00:42:49,400 --> 00:42:53,959
Speaker 2: of pushed them in this direction of radicalization. And that's

815
00:42:53,960 --> 00:42:57,239
Speaker 2: both true and not true. In Kelly's case, like he

816
00:42:57,280 --> 00:43:00,279
Speaker 2: did genuinely go through this foreclosure, which for any one

817
00:43:00,360 --> 00:43:04,360
Speaker 2: is a you know, horrific situation, but the way he

818
00:43:04,440 --> 00:43:05,120
Speaker 2: portrayed it.

819
00:43:05,040 --> 00:43:07,360
Speaker 3: Was also not entirely accurate.

820
00:43:07,480 --> 00:43:11,279
Speaker 2: And then when you're still many years past that financial

821
00:43:11,280 --> 00:43:15,360
Speaker 2: hardship and there's still you know, and you've had these

822
00:43:15,840 --> 00:43:18,520
Speaker 2: this severing of relationship with your kids and you're not

823
00:43:18,600 --> 00:43:21,000
Speaker 2: being there for them as you know, as a father,

824
00:43:21,160 --> 00:43:23,000
Speaker 2: and they're having to have these you know again, I

825
00:43:23,000 --> 00:43:24,640
Speaker 2: don't want to spoil it too much, but they're coming

826
00:43:24,680 --> 00:43:26,520
Speaker 2: to you saying this has really hurt us, and you

827
00:43:26,560 --> 00:43:29,600
Speaker 2: have a chance to turn over that new leaf, and

828
00:43:29,840 --> 00:43:31,400
Speaker 2: that's not necessarily.

829
00:43:30,840 --> 00:43:33,040
Speaker 3: The direction that you want to go in.

830
00:43:33,760 --> 00:43:37,040
Speaker 2: It makes it just makes the picture a little more complex, right,

831
00:43:37,440 --> 00:43:40,520
Speaker 2: It's not as simple and straightforward.

832
00:43:40,640 --> 00:43:41,120
Speaker 3: A sort of.

833
00:43:41,120 --> 00:43:46,040
Speaker 2: Math equation of you know, financial hardship plus loss of connection.

834
00:43:46,080 --> 00:43:47,840
Speaker 2: I mean, you actually have a sort of like formula

835
00:43:48,080 --> 00:43:50,799
Speaker 2: you lay out in the beginning doesn't have to lead

836
00:43:50,840 --> 00:43:52,480
Speaker 2: to this, doesn't always lead to this.

837
00:43:52,640 --> 00:43:53,760
Speaker 3: There are other choices.

838
00:43:53,920 --> 00:43:56,839
Speaker 2: It's not always like as clear a picture as you're

839
00:43:56,840 --> 00:43:59,319
Speaker 2: telling yourself in your head. You know, did it kind

840
00:43:59,320 --> 00:44:03,480
Speaker 2: of challenge some of your conceptions coming in as well?

841
00:44:03,680 --> 00:44:04,400
Speaker 5: Yeah, definitely.

842
00:44:04,400 --> 00:44:06,200
Speaker 9: I mean I started when I was twenty two, when

843
00:44:06,200 --> 00:44:08,080
Speaker 9: I finished when I was twenty seven, Like the first

844
00:44:08,080 --> 00:44:10,240
Speaker 9: shoot being the White Lives Matter rally on April eleven,

845
00:44:10,280 --> 00:44:13,520
Speaker 9: twenty twenty one, and the last shoot being three and

846
00:44:13,520 --> 00:44:15,560
Speaker 9: a half weeks ago with our friend Uncle Pill at

847
00:44:15,560 --> 00:44:17,880
Speaker 9: a skate park in San Diego. You can see my

848
00:44:17,920 --> 00:44:20,800
Speaker 9: approach like kind of morph throughout the whole thing, because

849
00:44:21,040 --> 00:44:23,200
Speaker 9: midway through, like twenty three twenty four, I'm like, I'm

850
00:44:23,200 --> 00:44:23,920
Speaker 9: gonna be able.

851
00:44:23,719 --> 00:44:25,400
Speaker 5: To figure this out. I've got everything.

852
00:44:25,120 --> 00:44:27,440
Speaker 9: Diagnosed, I have all the ducks in a row. I'm

853
00:44:27,480 --> 00:44:29,000
Speaker 9: going to make sure that he's able to turn over

854
00:44:29,040 --> 00:44:31,000
Speaker 9: a new leaf. The one thing that I noticed, too,

855
00:44:31,080 --> 00:44:33,080
Speaker 9: is that I didn't mention this in the movie very much,

856
00:44:33,400 --> 00:44:36,080
Speaker 9: but the whole the idea of self narrative was also

857
00:44:36,280 --> 00:44:38,719
Speaker 9: very important in his sort of inability to turn over

858
00:44:38,760 --> 00:44:41,680
Speaker 9: that new leaf over time, because it's a comforting self

859
00:44:41,760 --> 00:44:44,840
Speaker 9: narrative for him to have this heroic, black and white

860
00:44:44,840 --> 00:44:46,480
Speaker 9: good versus evil Bill.

861
00:44:46,400 --> 00:44:47,839
Speaker 5: Joiner, you know, screwed me over.

862
00:44:47,920 --> 00:44:50,080
Speaker 9: And you know, the way that morphs with the political

863
00:44:50,120 --> 00:44:52,120
Speaker 9: movement in general is very two dimensional, you know what

864
00:44:52,160 --> 00:44:54,680
Speaker 9: I mean, the idea there's this like nebulous dark force

865
00:44:54,760 --> 00:44:57,000
Speaker 9: out there that's just it exists.

866
00:44:57,040 --> 00:44:58,440
Speaker 5: We don't know what it is, but it's.

867
00:44:58,280 --> 00:45:01,960
Speaker 9: There to rob everything from the working, red blooded American patriot.

868
00:45:02,360 --> 00:45:05,080
Speaker 5: And it might not be my book, you may might

869
00:45:05,120 --> 00:45:06,120
Speaker 5: not be shared by years.

870
00:45:06,160 --> 00:45:09,080
Speaker 9: However, we're all united in our fight against the evil forces.

871
00:45:09,320 --> 00:45:11,000
Speaker 5: And in a way that's comforting to people in his

872
00:45:11,080 --> 00:45:16,000
Speaker 5: position because it stops them from actually picking up the pieces. Right.

873
00:45:16,760 --> 00:45:20,040
Speaker 9: That's why I was, you know, he was spending fifteen

874
00:45:20,080 --> 00:45:23,680
Speaker 9: hours a day putting up leaflets saying Bill Joyner stole

875
00:45:23,719 --> 00:45:26,239
Speaker 9: my home. That time easily could have been used at

876
00:45:26,280 --> 00:45:28,560
Speaker 9: you know, maybe getting an entry level job and trying.

877
00:45:28,360 --> 00:45:30,719
Speaker 5: To save up money to start from the bottom. But

878
00:45:30,760 --> 00:45:31,360
Speaker 5: that's a lot.

879
00:45:31,600 --> 00:45:33,400
Speaker 9: It takes a lot of humility to be able to

880
00:45:33,400 --> 00:45:35,520
Speaker 9: bring yourself back to that level and start from scratch.

881
00:45:35,560 --> 00:45:39,080
Speaker 9: It's easier to revel in the past while simultaneously leading

882
00:45:39,120 --> 00:45:41,440
Speaker 9: a hero's narrative that keeps you in a revenge mind stain.

883
00:45:41,280 --> 00:45:42,640
Speaker 4: Well, and actually I just want to jump on to

884
00:45:42,680 --> 00:45:44,400
Speaker 4: that point because one of the interesting things that you

885
00:45:44,520 --> 00:45:47,120
Speaker 4: touch on is how he grew up in a mobile

886
00:45:47,160 --> 00:45:49,759
Speaker 4: home and I think it was Iowa, and so he

887
00:45:49,880 --> 00:45:53,560
Speaker 4: may have been ultimately a bankruptcy attorney, but there was

888
00:45:53,600 --> 00:45:56,080
Speaker 4: something I think traumatic and I'm curious what you make

889
00:45:56,120 --> 00:45:59,960
Speaker 4: of this for him about losing his kind of upper

890
00:46:00,040 --> 00:46:03,839
Speaker 4: middle class, if not upper class status, and that for

891
00:46:03,960 --> 00:46:06,560
Speaker 4: him was maybe like the truth that he didn't want

892
00:46:06,560 --> 00:46:08,200
Speaker 4: to grapple with you. Hear his kids saying that it

893
00:46:08,239 --> 00:46:10,520
Speaker 4: was like the house. It was he could not give

894
00:46:10,640 --> 00:46:14,000
Speaker 4: up the house. And he's still driving is banged up BMW,

895
00:46:14,640 --> 00:46:16,720
Speaker 4: even though it's kind of big dent in the hood

896
00:46:16,920 --> 00:46:19,680
Speaker 4: as your camera's caught. It seems like there was something

897
00:46:19,680 --> 00:46:24,759
Speaker 4: about growing up poor that made him cling to the

898
00:46:25,160 --> 00:46:27,040
Speaker 4: kind of fantasy of having made it.

899
00:46:27,960 --> 00:46:31,040
Speaker 9: Yeah, definitely, because he sort of achieved the American dream,

900
00:46:31,040 --> 00:46:33,840
Speaker 9: which is just class mobility in general. I mean, especially

901
00:46:33,880 --> 00:46:36,160
Speaker 9: nowadays with the costs of living very few people can

902
00:46:36,160 --> 00:46:38,680
Speaker 9: go from living in a mobile home in their lifetime

903
00:46:38,680 --> 00:46:41,279
Speaker 9: to being cemented as a community member in an upper

904
00:46:41,320 --> 00:46:44,400
Speaker 9: class s gated community. So he hit that at point,

905
00:46:44,440 --> 00:46:46,440
Speaker 9: and I think the material obsessions were his way of

906
00:46:46,480 --> 00:46:48,920
Speaker 9: holding on to what that meant to him, like internally.

907
00:46:49,160 --> 00:46:51,360
Speaker 5: And you see this all the time. People hit the lottery.

908
00:46:51,600 --> 00:46:53,520
Speaker 9: Rappers get a bunch of money, they spend it more

909
00:46:53,520 --> 00:46:56,600
Speaker 9: on like material items because they have a sort of

910
00:46:56,600 --> 00:46:59,480
Speaker 9: imposter syndrome in general, because they didn't grow up in

911
00:46:59,520 --> 00:47:00,680
Speaker 9: the same way that their peers did.

912
00:47:00,719 --> 00:47:02,799
Speaker 5: Because most people who are rich grew up rich.

913
00:47:02,920 --> 00:47:05,799
Speaker 9: Was very little crossover, and so I felt, like, you know,

914
00:47:05,920 --> 00:47:08,359
Speaker 9: he felt it was a huge blow to his ego

915
00:47:08,440 --> 00:47:10,880
Speaker 9: and also, yeah, self perception and self narrative to be

916
00:47:10,960 --> 00:47:12,040
Speaker 9: to be foreclosed upon.

917
00:47:12,680 --> 00:47:15,160
Speaker 2: Are you Are you still in touch with Kelly Is he?

918
00:47:15,320 --> 00:47:17,200
Speaker 2: Is he happy as guys back in the White House?

919
00:47:17,239 --> 00:47:17,399
Speaker 4: Now?

920
00:47:17,480 --> 00:47:17,839
Speaker 7: Yeah, he's.

921
00:47:17,840 --> 00:47:19,680
Speaker 9: I mean, he's actually pretty excited about the film. Like

922
00:47:19,719 --> 00:47:21,600
Speaker 9: a lot of people look at the end of the

923
00:47:21,600 --> 00:47:23,279
Speaker 9: film and they think, like, oh my god, he must

924
00:47:23,400 --> 00:47:25,320
Speaker 9: feel so bad about it, you know, but at the

925
00:47:25,400 --> 00:47:26,640
Speaker 9: end of the day, there is a lot of small

926
00:47:26,719 --> 00:47:28,879
Speaker 9: victories that have been secured throughout the process of the film,

927
00:47:28,920 --> 00:47:31,439
Speaker 9: like him not caring so much about Bill Joyner, which

928
00:47:31,440 --> 00:47:34,160
Speaker 9: is his boogeyman, evil, predatory lump guy that he claimed

929
00:47:34,200 --> 00:47:36,640
Speaker 9: ruin his life. Him not caring about Bill by the

930
00:47:36,760 --> 00:47:39,360
Speaker 9: end is a huge strive forward if you consider that

931
00:47:39,400 --> 00:47:42,040
Speaker 9: in the opening scene it planned Parenthood, he's almost like

932
00:47:42,120 --> 00:47:44,000
Speaker 9: passing out from anger yelling about Bill.

933
00:47:44,320 --> 00:47:45,640
Speaker 5: So, I mean it might not be this. He's never

934
00:47:45,719 --> 00:47:46,680
Speaker 5: met people want.

935
00:47:46,800 --> 00:47:48,839
Speaker 9: Yeah, he's never met him, and you know, I'm being

936
00:47:48,920 --> 00:47:51,400
Speaker 9: sued by Bill right now, which sucks. So but I

937
00:47:51,400 --> 00:47:52,560
Speaker 9: also haven't met Bill either.

938
00:47:53,760 --> 00:47:54,040
Speaker 3: Wow.

939
00:47:54,360 --> 00:47:57,640
Speaker 2: So more Uh, there's more story to unfold there. Yeah,

940
00:47:57,680 --> 00:48:00,200
Speaker 2: with you versus Bill Joyner. Maybe you'll be next the

941
00:48:00,239 --> 00:48:02,200
Speaker 2: next one like Bill Joiner rude my life.

942
00:48:02,400 --> 00:48:04,160
Speaker 4: Next time you're on it, Andrew, it's just going to

943
00:48:04,200 --> 00:48:05,480
Speaker 4: be you talking about Bill Joyner.

944
00:48:06,600 --> 00:48:07,560
Speaker 5: Seen, there was.

945
00:48:07,480 --> 00:48:09,040
Speaker 2: One other thing I wanted to ask you about, Andrew.

946
00:48:09,040 --> 00:48:11,799
Speaker 2: We could put f one up on the screen. You

947
00:48:12,040 --> 00:48:15,759
Speaker 2: put out a very like, you know, pretty aggressive post

948
00:48:15,840 --> 00:48:19,120
Speaker 2: here about Elon Muss, none of which I disagree with,

949
00:48:19,200 --> 00:48:21,680
Speaker 2: but in any case, it's sounds like a little bit

950
00:48:21,719 --> 00:48:24,520
Speaker 2: of a break from the way you normally approach things

951
00:48:24,560 --> 00:48:26,360
Speaker 2: because a lot of times you sort of let your

952
00:48:26,520 --> 00:48:29,880
Speaker 2: you know, your your work, and the characters you follow

953
00:48:30,120 --> 00:48:33,520
Speaker 2: speak for themselves, and I was I just was curious

954
00:48:34,120 --> 00:48:36,520
Speaker 2: what led you to take this more aggressive approach, And

955
00:48:36,560 --> 00:48:39,200
Speaker 2: after having watched the documentary, actually it made me wonder

956
00:48:39,280 --> 00:48:41,480
Speaker 2: if if that was part of your evolution to make

957
00:48:41,560 --> 00:48:43,799
Speaker 2: being more directly personally outspoken.

958
00:48:44,640 --> 00:48:47,200
Speaker 9: Well, I mean a little just like Elon Musk has

959
00:48:47,239 --> 00:48:50,440
Speaker 9: been doing like Nazi dog whistle stuff on Twitter for

960
00:48:50,480 --> 00:48:51,720
Speaker 9: like five or six months.

961
00:48:51,760 --> 00:48:51,960
Speaker 5: Now.

962
00:48:52,280 --> 00:48:54,239
Speaker 9: I know this because I grew up on four Chune,

963
00:48:54,360 --> 00:48:58,040
Speaker 9: like back in the day that the pre censorship free Internet,

964
00:48:58,080 --> 00:48:59,800
Speaker 9: when like half the people were Nazis and half to

965
00:48:59,800 --> 00:49:02,040
Speaker 9: beeople were anarchists like back in the day, but it

966
00:49:02,080 --> 00:49:03,960
Speaker 9: was like either you were part of anonymous or you

967
00:49:03,960 --> 00:49:07,480
Speaker 9: were like a seriously like like like Charlottesville person. And

968
00:49:08,120 --> 00:49:10,000
Speaker 9: so I know that he's been doing these like weird

969
00:49:10,080 --> 00:49:13,520
Speaker 9: not even dog whistles, just like straight up following Nazi accounts,

970
00:49:13,680 --> 00:49:16,520
Speaker 9: reposting Nazi shit. And then when he did that, I

971
00:49:16,520 --> 00:49:18,359
Speaker 9: don't know, I just got triggered. I kind of felt

972
00:49:18,360 --> 00:49:20,080
Speaker 9: bad when I posted it because I'm supposed to be

973
00:49:20,120 --> 00:49:22,640
Speaker 9: like neutral and maintain composure, but that was for sure

974
00:49:22,640 --> 00:49:25,600
Speaker 9: a Hitler salute, and it's you know, it's a Hitler salute,

975
00:49:25,600 --> 00:49:27,600
Speaker 9: not just because of the obvious body language, but because

976
00:49:27,600 --> 00:49:31,080
Speaker 9: the guy has been paying homage to like Nazi ideology

977
00:49:31,080 --> 00:49:33,719
Speaker 9: and accounts on X for the past like six to

978
00:49:33,719 --> 00:49:36,560
Speaker 9: eight months and so. But the comments are crazy. So

979
00:49:36,600 --> 00:49:38,640
Speaker 9: many people are like going to batch for elons or

980
00:49:38,719 --> 00:49:40,560
Speaker 9: like he's just giving his heart out to the people.

981
00:49:40,600 --> 00:49:42,080
Speaker 9: I was like, dude, if you give your heart out

982
00:49:42,080 --> 00:49:45,200
Speaker 9: to the people, you go like this, appreciate you, guys,

983
00:49:45,360 --> 00:49:46,680
Speaker 9: Thank you, guys, heart goes out to you.

984
00:49:46,560 --> 00:49:47,719
Speaker 5: You don't do this siegile.

985
00:49:48,239 --> 00:49:50,520
Speaker 9: But you know, I think we're in this era where

986
00:49:50,920 --> 00:49:52,920
Speaker 9: you know, he could do it and say seghile, I

987
00:49:52,920 --> 00:49:54,640
Speaker 9: don't think people would care to find out a way

988
00:49:54,680 --> 00:49:56,360
Speaker 9: to rationalize it and be like, dude.

989
00:49:56,120 --> 00:49:57,799
Speaker 5: He's just so autistically. You don't know if you've met

990
00:49:57,800 --> 00:49:59,880
Speaker 5: an autistic person, but you're always.

991
00:50:00,640 --> 00:50:03,320
Speaker 2: I guess, yeah, have you considered you're just being ablest

992
00:50:03,400 --> 00:50:03,640
Speaker 2: right now?

993
00:50:03,719 --> 00:50:10,520
Speaker 5: Andrew, see now now the the what's it called the

994
00:50:10,560 --> 00:50:11,279
Speaker 5: sites are on me?

995
00:50:12,000 --> 00:50:12,879
Speaker 3: Yeah that's right.

996
00:50:13,760 --> 00:50:15,680
Speaker 4: Yeah. I was just like, that's the thing with we're

997
00:50:15,680 --> 00:50:18,520
Speaker 4: all like downstream of fortune culture now that people who

998
00:50:18,560 --> 00:50:21,680
Speaker 4: are not being ironic get away with the shield of

999
00:50:21,719 --> 00:50:25,120
Speaker 4: irony and and to like, in some fairness, it actually

1000
00:50:25,120 --> 00:50:27,279
Speaker 4: does make it hard to you know, it doesn't mean

1001
00:50:27,280 --> 00:50:29,080
Speaker 4: that irony trolling is right, but it does make it

1002
00:50:29,080 --> 00:50:31,560
Speaker 4: hard to like sometimes decode. But I guess Andrew, having

1003
00:50:31,600 --> 00:50:34,319
Speaker 4: spent time on Fortune, you speak the language probably better

1004
00:50:34,360 --> 00:50:34,680
Speaker 4: than most.

1005
00:50:34,760 --> 00:50:35,759
Speaker 5: Yeah, I definitely do.

1006
00:50:35,880 --> 00:50:38,480
Speaker 9: And not to mention, he's not from the United States

1007
00:50:38,800 --> 00:50:40,680
Speaker 9: and he has a lot to say about migrants coming

1008
00:50:40,719 --> 00:50:43,640
Speaker 9: here and ruining shit, whereas this guy is from South Africa,

1009
00:50:43,640 --> 00:50:46,480
Speaker 9: of all places, the most racist place that ever exists

1010
00:50:46,480 --> 00:50:49,040
Speaker 9: in the history of the world, and he's coming here

1011
00:50:49,160 --> 00:50:52,319
Speaker 9: and he's manipulating information that seems pretty treasonous and like

1012
00:50:52,360 --> 00:50:53,520
Speaker 9: some foreign interference.

1013
00:50:53,560 --> 00:50:56,279
Speaker 5: To me, it's just crazy to think that Trump ran his.

1014
00:50:56,200 --> 00:50:59,000
Speaker 9: Whole campaign on getting the deep state bureaucracy out of

1015
00:50:59,000 --> 00:51:02,360
Speaker 9: offish and now it appears that he has like a private,

1016
00:51:02,520 --> 00:51:05,920
Speaker 9: you know, council of tech oligarchs backing him entirely, so

1017
00:51:05,960 --> 00:51:07,680
Speaker 9: it appears that the deep state was elected.

1018
00:51:08,440 --> 00:51:12,640
Speaker 2: Well, I personally appreciate the new outspoken mode of Andrew Callahan,

1019
00:51:13,239 --> 00:51:14,759
Speaker 2: so I hope we hear more of it. And of

1020
00:51:14,800 --> 00:51:17,200
Speaker 2: course I always look forward to to your work tell

1021
00:51:17,200 --> 00:51:18,520
Speaker 2: people where they can watch Dear Kelly.

1022
00:51:19,000 --> 00:51:21,960
Speaker 9: You guys can watch Dear Kelly at www dot Dear

1023
00:51:22,080 --> 00:51:24,760
Speaker 9: kellyfilm dot com for the low rental cost of five

1024
00:51:24,800 --> 00:51:27,240
Speaker 9: dollars and fifty five cents, or if you're feeling generous,

1025
00:51:27,280 --> 00:51:29,520
Speaker 9: you can buy it forever for fifteen dollars and fifty

1026
00:51:29,520 --> 00:51:30,040
Speaker 9: five cents.

1027
00:51:30,120 --> 00:51:33,440
Speaker 2: It's worth and he's got some lawsuit costs against Bill Joyner,

1028
00:51:33,520 --> 00:51:34,839
Speaker 2: so help him out with that. Guy.

1029
00:51:35,360 --> 00:51:37,239
Speaker 9: Shout out to Bill, Shout out to Kelly, Shout out

1030
00:51:37,239 --> 00:51:37,920
Speaker 9: to Breaking Points.

1031
00:51:38,560 --> 00:51:41,000
Speaker 3: Thanks Andrew, great to talk to you. Thank you so much.

1032
00:51:41,160 --> 00:51:42,080
Speaker 5: Appreciate you guys.

1033
00:51:42,200 --> 00:51:44,480
Speaker 2: All right, really interesting getting to talk to Andrew. I

1034
00:51:44,480 --> 00:51:49,040
Speaker 2: really did. I found the film very thought provoking. Yeah

1035
00:51:49,080 --> 00:51:51,000
Speaker 2: you enjoyed it too, right, Oh my gosh, Yeah.

1036
00:51:50,920 --> 00:51:52,640
Speaker 4: Yeah I did. And I actually one of the things

1037
00:51:52,680 --> 00:51:54,200
Speaker 4: I know you talked a little bit to Andrew about

1038
00:51:54,200 --> 00:51:55,600
Speaker 4: what moved you, but one of the things that really

1039
00:51:55,600 --> 00:51:58,719
Speaker 4: moved me was this isn't a spoiler. He just ends

1040
00:51:58,800 --> 00:52:04,280
Speaker 4: up becoming very emotionally involved in Kelly's life and weirdly

1041
00:52:04,480 --> 00:52:07,919
Speaker 4: like close with him. Yes that it surprises you towards

1042
00:52:07,960 --> 00:52:09,600
Speaker 4: the end of the film. It's not a spoiler. I

1043
00:52:09,640 --> 00:52:13,120
Speaker 4: really recommend people watch it play out because that experience

1044
00:52:13,160 --> 00:52:15,040
Speaker 4: as a viewer is really compelling.

1045
00:52:15,239 --> 00:52:18,120
Speaker 2: Yeah, it was interesting to hear Andrew talk about like

1046
00:52:18,440 --> 00:52:21,120
Speaker 2: that that was something he really had to learn as

1047
00:52:21,160 --> 00:52:24,560
Speaker 2: a documentarian, that that that took a very emotional time.

1048
00:52:24,560 --> 00:52:27,279
Speaker 2: I mean he's Andrew's really young, right, that was like

1049
00:52:27,320 --> 00:52:29,440
Speaker 2: a real emotional toll on him and a learning for

1050
00:52:29,520 --> 00:52:31,640
Speaker 2: him through this process. But in any case, I hope

1051
00:52:31,640 --> 00:52:34,600
Speaker 2: you guys enjoyed the show today. Definitely check out the documentary.

1052
00:52:34,920 --> 00:52:37,080
Speaker 2: Sager supposed to be back tomorrow, so he will be

1053
00:52:37,520 --> 00:52:39,279
Speaker 2: in this chair and Emily and Ryan will be here

1054
00:52:39,320 --> 00:52:42,320
Speaker 2: on Wednesday, so you got all normal shows, normal shows

1055
00:52:42,320 --> 00:52:45,000
Speaker 2: planned for the week. In any case, have you guys

1056
00:52:45,000 --> 00:52:46,640
Speaker 2: have a fantastic date and I will see you back

1057
00:52:46,640 --> 00:52:47,120
Speaker 2: here tomorrow