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Speaker 1: Hi, I'm Molly John Fast and this is Fast Politics,

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Speaker 1: where we discussed the top political headlines with some of

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Speaker 1: today's best minds, and EMPTG says Trump's policies are not America.

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Speaker 2: First, we have such a great show for you today,

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Speaker 2: the Lincoln Project Zone. Rick Wilson joins us to discuss

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Speaker 2: the Civil War in the White House and how Trump's

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Speaker 2: chief of staff may be heading for the door. And

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Speaker 2: we'll talk to author Michael Steinberger about his new book,

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Speaker 2: The Philosopher in the Valley, alex garp Pilunteer, and the

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Speaker 2: rise of the surveillance State. But first the news.

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Speaker 3: Some of the good news is on Thursday, government employees

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Speaker 3: will be paid again. They're paying out snap again. But

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Speaker 3: the bad news is a lot of people are about

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Speaker 3: to lose their food stamps permanently.

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Speaker 2: It was you remember when Elon Musk danced around with

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Speaker 2: the chainsaw.

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Speaker 3: I think about it every day. What I'm like, what

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Speaker 3: was the coolest thing I've ever seen in my life?

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Speaker 2: Yeah, he was celebrating the reverse philanthropy that this administration

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Speaker 2: is engaging in. Brooke Rollins directed the us DA staff

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Speaker 2: during a record setting forty three days shutdown to continue

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Speaker 2: ushering states towards compliance with the Republican's signature tax and

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Speaker 2: spending law, which is projected to kick millions out of

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Speaker 2: the nation's largest anti hunger program. So here's what they're doing.

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Speaker 2: They're making it harder for you to get food stamps,

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Speaker 2: just like they're making it harder for you to get unemployment,

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Speaker 2: and they're making it harder for you to get medicaid.

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Speaker 2: The thinking here is that if they make it harder

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Speaker 2: for people to get these things, then they won't get them.

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Speaker 2: They'll just starve. Yes, that's right. And you want to

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Speaker 2: know why they're doing it, Jesse.

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Speaker 3: I would love for you to tell me, please, please, just.

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Speaker 2: Doing it because rich people do not want to pay taxes.

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Speaker 2: That's literally why they're doing this. Yep, more Americans will

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Speaker 2: starve because Donald J. Trump wants to have his rich

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Speaker 2: friends pay list axes. And there you have it, all.

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Speaker 3: Right, my So I'm going to show how much integrity

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Speaker 3: I have where I'm going to tell you an embarrassing

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Speaker 3: journalistic editor I door knocked for one Bill de Blasio

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Speaker 3: on his first barrel cauepe page de Bungler.

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Speaker 2: By the way, we didn't talk at all about Bill

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Speaker 2: de Blasio cheating on the good thing that ever happened

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Speaker 2: to him, Nomiki, constant justice for Nomiki. It turns out,

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Speaker 2: by the way, the Bill de Blasio, despite I, by

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Speaker 2: the way, have a long thought he sucked, but it

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Speaker 2: turns out that he is also a philanderer. So a

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Speaker 2: hearty fuck you to mister Bill de Blasio, in case

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Speaker 2: you're there, in case you're the five people who still

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Speaker 2: know who you are. Justice for Nomiki.

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Speaker 3: So allow me to keep clowning myself. And I will

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Speaker 3: say so. I door knocked for many days for the

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Speaker 3: de Blasio campaign before he was elected mayor.

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Speaker 2: Let the record show I'm making a horrified fit.

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Speaker 3: You are you also know this, So what I do

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Speaker 3: or knocked on it. What I kept hearing from people

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Speaker 3: was everyone's going to move out of the city if

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Speaker 3: he's elected. Rich people will leave the city. Do you

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Speaker 3: know what happened? That did not happen. And they said

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Speaker 3: the same thing about Zoramondanni. And now we have two

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Speaker 3: top real estate CEOs saying no one's putting their houses

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Speaker 3: up for sale, no one's leaving the city.

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Speaker 2: You know, it's so incredibly stupid. This is so stupid.

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Speaker 2: I can't even tell you how stupid it is. This

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Speaker 2: always happened. They always say this. So basically outspoken conservative

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Speaker 2: hedge fund millionaire Ken Griffin, who is a partner at

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Speaker 2: a wounin project, Ken is committed, and we'll have more

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Speaker 2: employees at three point fifty Park Avenue than Miami. Now,

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Speaker 2: by the way, we're going to say something nice about

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Speaker 2: a billionaire here. Ken Griffin has been one of the

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Speaker 2: very few billionaires who from the beginning has said Donald J.

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Speaker 2: Trump is a complete and utter fuck more on. I mean,

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Speaker 2: he hasn't quite said that, but he's criticized the tariffs

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Speaker 2: at the time when every other rich person was like,

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Speaker 2: thank you, sir, please enact more stupid legislation. Ken Griffin,

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Speaker 2: who donated to Trump and is in no way a

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Speaker 2: liberal lefty, he did in fact say that this was ridiculous.

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Speaker 2: And look, in a world filled with sycophans, the people

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Speaker 2: who say the real stuff are actually the good guys.

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Speaker 2: So in that way, I think that was good. But yeah, no,

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Speaker 2: New York is not going anywhere. There are going to

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Speaker 2: be millions and millions of feet of office space. I

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Speaker 2: don't know who's going to work in them, because there

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Speaker 2: are no more businesses, but you know, the data farmers

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Speaker 2: will all have their own beautiful data farms, and you

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Speaker 2: know New York is not going anywhere.

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Speaker 4: Yeah.

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Speaker 3: I would really like to put this one to death

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Speaker 3: with the things that people should be laughed at when

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Speaker 3: they say because it's proven to never be true. Just

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Speaker 3: like that voters don't women in executive roles like governors

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Speaker 3: when we saw how well that went last week.

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Speaker 2: I mean, I still think probably not going to be

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Speaker 2: able to elect a woman president, at least on the left.

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Speaker 3: I think that there's a very interesting thing to be there.

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Speaker 3: But I think that what the myth is is people

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Speaker 3: carry this over as if it's governors too, And that's

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Speaker 3: a ridiculous, ridiculous statement.

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Speaker 2: Governors. I don't think it's necessarily true.

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Speaker 3: Yeah, they get the analysis wrong when they make it

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Speaker 3: about the executive choices being made.

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Speaker 4: That's a ridiculous statement.

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Speaker 3: Yeah, especially conser Yeah, we have a dozen female governors

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Speaker 3: right now, or we will in January.

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Speaker 4: Yeah.

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Speaker 3: Okay, So it's a Sunday, So that means Scott the

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Speaker 3: Scent has gone on a Sunday show, yes, my man,

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Speaker 3: and said something that seems to really really really really

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Speaker 3: make very little sense. But hear he's saying that Trump's

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Speaker 3: two thousand dollars tariff check requires a new law to happen.

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Speaker 5: Yeah.

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Speaker 2: By the way, first of all, there's no here. Here's

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Speaker 2: what happens on Sundays. Scott Bissent and his low affect

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Speaker 2: monotone go on a Sunday show and on that Sunday

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Speaker 2: show he be clowns himself in a way that Mega demands.

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Speaker 2: So he goes on there he says things that are

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Speaker 2: completely nuts. Here's one. So he's going to send a

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Speaker 2: tariff dividend check to most Americans. Here's how this is

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Speaker 2: going to work. It's not going to happen that this

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Speaker 2: is how it's gonna work. It's not because, first of all,

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Speaker 2: there's no way they can do this. I'd be very

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Speaker 2: surprised if the Supreme Court doesn't say the tariffs are illegal.

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Speaker 2: So we're already going to be in a nightmare scenario

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Speaker 2: where they're trying to undo tariffs that are undoable. I

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Speaker 2: think that we are in a moment of stupid and

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Speaker 2: I would say this, Thessent is trying to save his

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Speaker 2: job here, he's also trying to save the economy. Also,

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Speaker 2: the other thing that I think it's worth like pulling

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Speaker 2: back and realizing is the reason that Trump world is

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Speaker 2: cutting tariffs on food on a Friday night and having

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Speaker 2: Scott on the Sunday shows on a Sunday morning. It's

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Speaker 2: because they see these consumer confidence numbers and they're the

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Speaker 2: lowest in seventy eight years. I think that's right. They're

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Speaker 2: like these crazy low consumer confidence numbers and they are

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Speaker 2: seeing them and they're coming up into Thanksgiving and Christmas

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Speaker 2: and they are like, holy fuck, we just got slathered

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Speaker 2: in a twenty twenty five cycle. We are now into

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Speaker 2: holiday that's going to be fucking nightmare fuel. This is

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Speaker 2: what is known as panic. This is what is known

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Speaker 2: as an administration that is trying desperately to change the

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Speaker 2: subject and it's not working.

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Speaker 4: Yeah.

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Speaker 3: I would strongly agree, so Molli, I think one of

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Speaker 3: the things with analyzing Trump is we always look at

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Speaker 3: what he's truthing. It was interesting this weekend he's fixated

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Speaker 3: on Missus Taylor Green for obvious reasons. He did not

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Speaker 3: address some things in the Epstein files. Most notably, but

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Speaker 3: what I did think was the more ateristic thing that

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Speaker 3: is not being covered is how pist he is at

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Speaker 3: Indiana politicians.

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Speaker 2: Oh yeah, this is an amazing thing. So he wants

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Speaker 2: so one of the good things about Trump is he

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Speaker 2: has no idea what the fuck he's doing. So he

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Speaker 2: is trying to now redistrict because he thinks that redistricting

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Speaker 2: will mean you won't lose the House. But what I

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Speaker 2: don't think he understands, and what I think these other

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Speaker 2: Republicans understand, is that they can't redistrict seats that don't exist.

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Speaker 2: So if you have five seats and you spread out

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Speaker 2: the Republican votes, eventually you make yourself into a dommymander,

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Speaker 2: you say, and R plus ten becomes an R plus five.

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Speaker 2: And when you have a headwind of eight ten points,

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Speaker 2: which it's looking like you may, you end up with

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Speaker 2: the dummy Manders. And by the way, redistricting is already

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Speaker 2: going to be tough because it's anti democratic. And you know,

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Speaker 2: at this point, I mean effectively and a credit where

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Speaker 2: credit is due, my man, and I don't like everything

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Speaker 2: he does. I think ideologically we are not a match.

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Speaker 2: But there is a reason why this has gone so

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Speaker 2: off the rails, and it is Gavin Newsom. Because if

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Speaker 2: they had stolen those five seats in Texas, you and

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Speaker 2: I both know that he would have been like done.

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Speaker 2: I'm good, even though a traditional midterm where they get

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Speaker 2: slaughtered is thirty five seats. But if they had just

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Speaker 2: done those five seats, then I think we would have

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Speaker 2: ended up with like Trump going into the midterms thinking

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Speaker 2: he was okay. But because those California seats have now

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Speaker 2: gone to demes, though of course the Trump DOJ has

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Speaker 2: tried to fight it because it's gone to demes. I

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Speaker 2: think this is just a shit show. And Trump sees

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Speaker 2: five to five, you know, five from Texas to the Republicans,

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Speaker 2: five to California. I think there's a point in which

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Speaker 2: this just no longer makes any sense, and I think we.

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Speaker 3: May have hit It sounds about right.

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Speaker 2: Rick Wilson is the founder of the Lincoln Project and

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Speaker 2: the host of the Enemy's List.

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Speaker 4: Rick Wilson, Molly John Fast a little bird told me

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Speaker 4: you were in the Gettysburg of the Maga Civil War this.

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Speaker 2: Weekend, the district of Columbia where I ate dish next

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Speaker 2: to Todd Blanche and Borish Epstein.

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Speaker 4: Oh my gosh, they could not have ever been doing

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Speaker 4: anything corrupt or dirty.

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Speaker 2: Well, they were with their families, so I would assume not,

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Speaker 2: but who knows. I also couldn't hear anything because it

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Speaker 2: was so loud, but I will say I am reminded

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Speaker 2: that the district of Columbia has about seven people who

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Speaker 2: live in it, and it is literally like being on

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Speaker 2: a cruise ship.

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Speaker 4: Yes, it's like a country club in a mid sized town.

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Speaker 2: It's the country club from Hell. Speaking of from Hell,

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Speaker 2: Susie Wilds, who is Donald Trump's chief of stab and

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Speaker 2: probably why Donald Trump is president today, a meaningful part

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Speaker 2: of it, yes, and she comes from Desanta's world where

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Speaker 2: DeSantis did something so stupid. I don't know what he means.

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Speaker 4: Lady Lady macbeth, Casey DeSantis, right, Casey McBeth alienator. She

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Speaker 4: fired her and then publicly humiliated her in the press.

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Speaker 2: And Susie Wiles went and made Donald Trump president as

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Speaker 2: Susan I was.

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Speaker 4: Weighed carefully her options and said, how am I going

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Speaker 4: to fuck these people harder than they've ever been fucked before?

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Speaker 4: And she went back to Trump and all of this,

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Speaker 4: all these machinations of Ronda Sant's running for president, were

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Speaker 4: happening before he was even governor, and she blew up

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Speaker 4: their ten year plan absolutely train wrecked his presidential campaign

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Speaker 4: and was really one of the reasons Donald Trump was

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Speaker 4: elected because she would go to the big donors, the

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Speaker 4: serious people, not the crazies, and say I'm going to

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Speaker 4: control it. I can make I'll set up systems. We'll

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Speaker 4: let him go and play with parades and watch the

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Speaker 4: fighter planes fly over, and the grown ups will do business.

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Speaker 5: But do.

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Speaker 4: So what happen?

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Speaker 2: So let's fast forward to Susie Wilds today. What is

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Speaker 2: happening with miss Wilder?

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Speaker 4: Well, I will tell you the Magi are now have

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Speaker 4: They've looked at the last ten months. They've looked at

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Speaker 4: the steep decline in Trump's polling. They looked at one

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Speaker 4: disaster after another since ten days ago. On election night,

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Speaker 4: there's a rising drum beat inside the Maga world of

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Speaker 4: both people inside the White House who don't like her

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Speaker 4: e g. Stephen Miller, and of the MAGA influencer ecosystem

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Speaker 4: out there in the world. They're all looking for a

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Speaker 4: way to say no, this isn't Trump's fault, this isn't

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Speaker 4: Trump's bad decisions, this isn't a public assessment of Donald

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Speaker 4: Trump being a terrible leader in destroying the economy and

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Speaker 4: ZIP tying children in the streets and running police state

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Speaker 4: this small is it must all be Susie Wiles's fault

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Speaker 4: because she's the one who's secret. They call her like

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Speaker 4: swampy Susie. She's getting the nicknames. She's in that moment

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Speaker 4: right now. There's always an arc. I wrote about this

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Speaker 4: today in an article on my sub stet called Run Susie, Run.

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Speaker 4: And there's an arc with Trump. First, you're the essential person,

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Speaker 4: the highly respected Susie Wiles, you know, great chief of staff.

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Speaker 4: And then it's you get the responsibility of trying to

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Speaker 4: clean up the message, and you're always behind the elephant

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Speaker 4: with the smallest shovel in the world. Then in the

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Speaker 4: point where all his mistakes and fuck ups start to

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Speaker 4: accrete and they can't be cleaned up, it's like, well,

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Speaker 4: it must be her fault or their fault, whoever, whoever

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Speaker 4: the person is. And right now she's in the phase

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Speaker 4: where Trump is on the phone and people going, do

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Speaker 4: you think Susie's doing a good job?

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Speaker 5: Once he does that, start the clock fucked?

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Speaker 4: Yeah, Everything Trump touches dies at that point.

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Speaker 2: Here's a question for you. Stephen Miller wants Susie out,

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Speaker 2: But what is Stephen Miller. Doing that is like bankable

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Speaker 2: or good, nothing, nothing.

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Speaker 4: It doesn't matter. Look, there are three reasons you want

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Speaker 4: to be chief of staff. Reason one is that you're

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Speaker 4: loyal to the guy. You came up with him as

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Speaker 4: a congressman, a governor, a president. Lifers. Trump has no

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Speaker 4: one like that around him, no one, not even this family. Right.

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Speaker 4: The second reason is it's the highest you can ascend

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Speaker 4: in the pairmid of political power in America without being

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Speaker 4: an elected official. It is the most powerful non elected

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Speaker 4: job in DC by far. And the third reason you

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Speaker 4: want to do it is once you're chief of staff,

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Speaker 4: the rest of your life, you're never on schedule to

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Speaker 4: or travel again. You are going You're on corporate boards

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Speaker 4: all over the country. You travel around the world to

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Speaker 4: give compensated speeches and beautiful resorts to very wealthy people.

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Speaker 2: Steven Miller is going to be on corporate boards.

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Speaker 4: Oh no, Steven Miller will not. This is what Susie Wiles.

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Speaker 4: These are what Susie Wilds wanted. Steven Miller is going

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Speaker 4: to be in a fucking prison if I have anything

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Speaker 4: to do with it.

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Speaker 2: Well, he's certainly not going to be on the board

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Speaker 2: of American airlines. No, he is being like being like,

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Speaker 2: let's pepper spray babies.

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Speaker 6: Yeah.

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Speaker 4: Yeah, So her position is tenuous now. A lot of

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Speaker 4: her people have been leaving DC. A lot of people

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Speaker 4: she brought in who were more sane, more rational people.

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Speaker 4: They're already out of the administration. They're like, I need

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Speaker 4: to spend more time with my family. My. Wow, you know, my, my, my, my,

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Speaker 4: My service here has been the greatest honor of my life. Sir,

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Speaker 4: But my, you know, I've got to.

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Speaker 2: Go mow my lawn whatever, right, lawn mowing is important, That's.

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Speaker 4: What That's what I'm told.

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Speaker 5: But but she is.

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Speaker 4: She is not immune to the power of everything Trump

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Speaker 4: touches dies. And she's not immune to the power that

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Speaker 4: the MAGA influencer class has over Trump. And and I've

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Speaker 4: been keeping an eye on a couple of them. I

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Speaker 4: haven't seen her attack directly yet by lumersobiac all those

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Speaker 4: sort of people that you would start to you know

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Speaker 4: that Trump's made a decision by the time they start

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Speaker 4: attacking somebody, right, right, you're not there yet. But she is.

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Speaker 4: She is. You know, She's got this enough of the

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Speaker 4: smell of death around her that the vultures are circling

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Speaker 4: over her.

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Speaker 2: Head when this happens eventually. I mean, one of the

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Speaker 2: things Trump two point zero has done the Trump one

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Speaker 2: point zero has not done, is that he does not

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Speaker 2: fire people in this new administration. Right, people move, they

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Speaker 2: move to Greece, like Don Junior's girlfriend. They get moved around,

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Speaker 2: but they don't necessarily get fired. That I think he

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Speaker 2: thinks that will keep the leakers at bay. So this

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Speaker 2: would actually be a paradigm shift.

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Speaker 4: Yes, it would be, And I will tell you it's

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Speaker 4: a paradigm shift because they are in a crisis that

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Speaker 4: they have not been able to break the cycle on

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Speaker 4: when the Epstein stuff first started. You and I had

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Speaker 4: this conversation. This is the first thing we'd ever seen

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Speaker 4: end a decade of watching this craziness that he can't

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Speaker 4: get under control. He may push it back for a

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Speaker 4: day or two, but it always comes back. Epstein is

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Speaker 4: the underscore of the soundtrack of the Trump presidency too.

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Speaker 4: And right now, you know, we saw basically what's estimated

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Speaker 4: to be about five percent of the materials that are

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Speaker 4: out there about Epstein RaaS this week, and it has

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Speaker 4: been a pure firestorm on this gun. He has been

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Speaker 4: taking a chaotic approach to handling it. You know, for

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Speaker 4: these people to spend all week trying to come up

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Speaker 4: with a plan, and they're going to say, well, we're

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Speaker 4: going to investigate Reid Hoffman and Bill Clinton and not

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Speaker 4: Donald Trump even his own people. The MAGA reaction to

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Speaker 4: this was like, come on, come.

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Speaker 2: On, bro, my man read Hoffman, though, let us give

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Speaker 2: a little credit where credit. I have brother Hoffman extremely

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Speaker 2: crotchety and cranky with Reid Hoffman in any number of

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Speaker 2: different ways and criticized him ad nauseum, including sending him

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Speaker 2: a DM that said I'm very disappointed in you, which

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Speaker 2: is the way I Jewish mother American democracy. And yet

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Speaker 2: my man stood up to Trump said go for it. Fight, fight, fight,

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Speaker 2: That's the only way. And and by the way, I mean, look,

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Speaker 2: you know, tell you.

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Speaker 4: And I wish, I wish we had more billionaires in

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Speaker 4: this country who would display the guts read Hoffman showed

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Speaker 4: this week said bring it on, fuck you, Yeah, I

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Speaker 4: will fight you. Let's go. Every time you show Trump

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Speaker 4: you're not afraid of him, they always take a beat

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Speaker 4: because they expect everybody to do what well a lot

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Speaker 4: of people have done over the over the over the years. Yes, sir, Yes, sir,

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Speaker 4: how many? How many make it better? Never apologize to

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Speaker 4: Trump always said go fuck yourself, get right back in

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Speaker 4: his face. Stick.

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Speaker 2: That's the only way, only way. But I think it's

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Speaker 2: worth for a minute going back to this moment here,

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Speaker 2: because I actually think this is the end of MAGA,

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Speaker 2: and I want you and I'm going to tell you.

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Speaker 2: I'm going to tell you my theory, and they.

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Speaker 4: Tell me your theory.

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Speaker 2: Why you think it's wrong or right or whatever. You know,

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Speaker 2: you and I we exchange theories, and you know all

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Speaker 2: I have for a long time. So my theory is this,

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Speaker 2: there are two things that are taking down MAGA at

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Speaker 2: the same time, but only one is visible. So one

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Speaker 2: is the Epstein stuff, right, you see, Marjorie Taylor Green,

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Speaker 2: Lauren Beaupert, Thomas Massey, Nancy Mace, Nancy Mayce. These people

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Speaker 2: are all like breaking with the party in a big way.

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Speaker 2: And supposedly there's like one hundred republic go into We're

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Speaker 2: going to vote for the discharge petition. Ye, big deal.

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Speaker 2: But the underlying reason why the MAGA is disintegrating is

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Speaker 2: because of inflation.

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Speaker 4: Yes, these people are taking the economy in the face, right,

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Speaker 4: and they finally reached a point where they couldn't spend

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Speaker 4: it anymore, and they couldn't say, well, you know, I'm

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Speaker 4: sacrificing for the good of the country because Donald Trump

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Speaker 4: needs this. Now they're based at the point like he's

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Speaker 4: fucking us. Yeah, we're getting screwed. And you notice there's

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Speaker 4: an interesting and I think your theory is correct. Inflation

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Speaker 4: and economics are taking there cracking.

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Speaker 2: They're the underlying right And why is.

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Speaker 4: That, Molly, Because one of their most fundamental beliefs from

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Speaker 4: all the way back in twenty sixteen was that Donald

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Speaker 4: Trump was a masterful negotiator. He'd be great for the economy.

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Speaker 4: He's the guy who could solve all these economic problems

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Speaker 4: that the Libs have caused. Well, the Libs didn't cause them,

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Speaker 4: but what he did. What he did was shattered the

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Speaker 4: country with this tariff deal. And it is kept inflation

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Speaker 4: grinding away under the water. And it is not a

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Speaker 4: visible process. It's it's like it's like a disease and

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Speaker 4: it's eating away at them and they and they it's

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Speaker 4: hard to go into the grocery store and say, yeah, no,

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Speaker 4: this isn't a two hundred and fifty dollars bill for

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Speaker 4: five bags of groceries. It's it's an eighty dollars bill,

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Speaker 4: like Trump told me. It is because it's not true, right,

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Speaker 4: can't spin it.

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Speaker 2: And we know that the inflation is a problem and

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Speaker 2: that Trump is saying uncle. And you know why we know.

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Speaker 4: That because he's reversing the tariffs at nine o'clock on

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Speaker 4: a Friday.

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Speaker 2: Night as one does.

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Speaker 4: He as one does. He's reversing the food tariffs that

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Speaker 4: have caused coffee and chocolated and meat, wheat and meat

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Speaker 4: and all this other stuff to.

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Speaker 2: Skyrocket because my man sees Thanksgiving around the corner and Christmas.

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Speaker 2: And even though he did explain to Maga voters that

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Speaker 2: you might get one dollar instead of three or eleven.

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Speaker 2: By the way, this is the problem with making a

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Speaker 2: billionaire president is that he's not you know, you get

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Speaker 2: one you know you'll only get one jet that I

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Speaker 2: think this is really seeing it come apart here.

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Speaker 4: Look, I think, and I think there are there are

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Speaker 4: large things and small things that are shattering the coalition

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Speaker 4: on the economic axis. And if you look at all

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Speaker 4: the public polling and all the survey work that's out

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Speaker 4: there right now, everything in the economic basket, he's upside

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Speaker 4: down by between eleven and twenty seven points. Right on inflation,

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Speaker 4: he's down about twenty seven points across multiple polls. A

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Speaker 4: couple are worse, a couple are better, but the aggregate.

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Speaker 4: You you know, this is the same lesson gerald Ford

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Speaker 4: learned in nineteen seventy six. Inflation is a killer app

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Speaker 4: for voters. They will not tolerate it. Joe Biden and

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Speaker 4: Gerald Ford learned that lesson. Yeah, it was virus, but

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Speaker 4: by extension.

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Speaker 2: I was just going to say, like, you can, you

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Speaker 2: can just pull back from like a year ago. Yeah, No,

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Speaker 2: it's true. I mean the but the great irony of

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Speaker 2: all of this, which I think should not be ignored,

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Speaker 2: is that this is caused by Trump.

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Speaker 4: Every bit of this inflation under Joe Biden was coming down.

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Speaker 4: It was coming down swiftly. But I mean, look, was

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Speaker 4: everybody happy. Of course not. I wasn't happy.

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Speaker 5: Nobody was happy. The Fed wasn't happy. That's why they

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Speaker 5: kept the brakes on.

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Speaker 4: And that the reason Joe Biden ended up with inflation

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Speaker 4: was because Donald Trump had botched COVID so badly that

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Speaker 4: we had to juice the economy. In the beginning of

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Speaker 4: the Biden administration, and we paid for it on the

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Speaker 4: back end with inflation.

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Speaker 2: I mean, I also think everybody had inflation and even

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Speaker 2: if you hadn't used the economy. Yeah, but I also

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Speaker 2: think Biden world was fad at messaging it, so that

434
00:23:36,480 --> 00:23:39,120
Speaker 2: got them to a place where everything was a shit show.

435
00:23:39,760 --> 00:23:43,600
Speaker 2: But this is a problem of Donald Trump's so making.

436
00:23:43,720 --> 00:23:47,919
Speaker 2: Now I want to talk about what's happening right now

437
00:23:48,240 --> 00:23:52,200
Speaker 2: in there are a couple of cities where Donald Trump

438
00:23:52,320 --> 00:23:56,960
Speaker 2: is pulling out the National Guard, indeed, but there are

439
00:23:57,000 --> 00:24:01,440
Speaker 2: a couple of cities warmer weather Donald Trump is sending

440
00:24:01,560 --> 00:24:02,960
Speaker 2: in ice.

441
00:24:03,720 --> 00:24:06,320
Speaker 4: YEP, Charlotte is the new victim city.

442
00:24:07,040 --> 00:24:10,080
Speaker 5: But Charlotte why there is.

443
00:24:10,000 --> 00:24:13,480
Speaker 4: A meaningful Hispanic population in Mecklenburg County, which is the

444
00:24:13,520 --> 00:24:15,960
Speaker 4: main county in the Charlotte area. A lot of them

445
00:24:15,960 --> 00:24:19,880
Speaker 4: are legal, but that doesn't matter to Ice. Their criteria

446
00:24:19,920 --> 00:24:22,119
Speaker 4: is not legal or illegal. Their criteria is brown or

447
00:24:22,160 --> 00:24:24,640
Speaker 4: not brown. I also think that they reached a point

448
00:24:24,640 --> 00:24:28,639
Speaker 4: where Chicago was not providing them with the visuals they wanted.

449
00:24:29,480 --> 00:24:32,479
Speaker 4: And Folks, if you don't believe me and believe us

450
00:24:32,480 --> 00:24:36,760
Speaker 4: that the MAGA media ecosystem is super coordinated, why haven't

451
00:24:36,800 --> 00:24:38,479
Speaker 4: you heard the word Portland in weeks.

452
00:24:38,800 --> 00:24:39,880
Speaker 2: Yeah, why haven't you heard?

453
00:24:39,880 --> 00:24:42,840
Speaker 4: Why why is it that suddenly we're not seeing every

454
00:24:42,960 --> 00:24:45,639
Speaker 4: MAGA influencer, Bennie Johnson and all the rest, all the

455
00:24:45,640 --> 00:24:48,080
Speaker 4: way down the food chain out in Portland trying to

456
00:24:48,080 --> 00:24:51,560
Speaker 4: get on camera. Yeah, why not because it wasn't giving

457
00:24:51,560 --> 00:24:53,680
Speaker 4: them the picture they wanted. They were being mocked and

458
00:24:53,760 --> 00:24:57,600
Speaker 4: ridiculed by people in frog outfits. Fuck this, We'll go

459
00:24:57,640 --> 00:25:00,840
Speaker 4: to Chicago. And they went to Chicago and people were

460
00:25:00,880 --> 00:25:03,680
Speaker 4: going out in the streets with whistles and people were

461
00:25:03,720 --> 00:25:05,800
Speaker 4: coming out. There was one of these small towns they

462
00:25:05,800 --> 00:25:08,840
Speaker 4: showed up in outside suburbs outside of Chicago with a

463
00:25:08,840 --> 00:25:11,320
Speaker 4: population of four thousand people, and five hundred showed up

464
00:25:11,359 --> 00:25:14,640
Speaker 4: to protest ICE. They were getting the message like, fuck you,

465
00:25:15,160 --> 00:25:18,360
Speaker 4: arrest us all give it a shot. And so now

466
00:25:18,359 --> 00:25:20,560
Speaker 4: they're going to try for a different city and try

467
00:25:20,600 --> 00:25:23,760
Speaker 4: for a different set of visuals. And yes, it's a

468
00:25:23,800 --> 00:25:26,399
Speaker 4: lot warmer insurre than it is in Chicago. And a

469
00:25:26,400 --> 00:25:29,119
Speaker 4: lot of these proud boys and these goons that have

470
00:25:29,160 --> 00:25:31,480
Speaker 4: joined ICE in the last five minutes, they're not exactly

471
00:25:31,520 --> 00:25:33,439
Speaker 4: like Navy seal toughness levels.

472
00:25:33,720 --> 00:25:39,480
Speaker 2: It is interesting to me that this crew that is

473
00:25:39,560 --> 00:25:45,359
Speaker 2: doing the arresting, so to speak, is headed by dog

474
00:25:45,480 --> 00:25:47,080
Speaker 2: killer and dog.

475
00:25:47,040 --> 00:25:50,880
Speaker 4: Killer and fraud queen Christy nome.

476
00:25:51,000 --> 00:25:54,720
Speaker 2: Yes, who has in fact, now there's this new reporting

477
00:25:54,720 --> 00:25:58,560
Speaker 2: from Pro Publica showing that she did in fact self

478
00:25:58,640 --> 00:26:03,200
Speaker 2: deal or give you know, she's violated ethics so shockingly

479
00:26:03,400 --> 00:26:03,920
Speaker 2: this woman.

480
00:26:04,080 --> 00:26:04,960
Speaker 5: Yes, So the.

481
00:26:04,960 --> 00:26:09,600
Speaker 4: Strategy Group is the company that she used to build

482
00:26:09,640 --> 00:26:13,760
Speaker 4: all these maga ads, all these ice ads that she's in,

483
00:26:14,520 --> 00:26:18,960
Speaker 4: and they're all of her fully made up, beautiful old extensions.

484
00:26:19,000 --> 00:26:21,920
Speaker 4: Heir riding horses, trying to look tough, you know, wearing

485
00:26:21,960 --> 00:26:24,280
Speaker 4: body armor, the whole thing. I'm gonna I'm gonna flip

486
00:26:24,280 --> 00:26:26,640
Speaker 4: on the wayback machine for a second. The Strategy Group

487
00:26:26,680 --> 00:26:30,040
Speaker 4: for media and and and apparently also Chris Losovita. I

488
00:26:30,119 --> 00:26:32,400
Speaker 4: heard the other day. I read that somewhere they're cashing

489
00:26:32,400 --> 00:26:35,119
Speaker 4: in on this media buy to the tune of Milly

490
00:26:35,320 --> 00:26:38,320
Speaker 4: many many millions of the of the two hundred million dollars.

491
00:26:38,640 --> 00:26:41,720
Speaker 4: They're the people. The company was once headed by the

492
00:26:41,760 --> 00:26:45,000
Speaker 4: guy that sent Michelle Bachman the vibrator when she was

493
00:26:45,000 --> 00:26:47,040
Speaker 4: a customer. I don't know if you that's a way back.

494
00:26:47,080 --> 00:26:49,040
Speaker 4: That's a little probably a little too obscure, too much

495
00:26:49,080 --> 00:26:52,480
Speaker 4: of a deep but they are. The Strategy Group for

496
00:26:52,560 --> 00:26:59,520
Speaker 4: Media is truly batshit insane, and by a remarkable coincidence,

497
00:26:59,560 --> 00:27:02,600
Speaker 4: trisham Glaughlin, who is her who was nomes comms director,

498
00:27:02,880 --> 00:27:06,360
Speaker 4: is married to Ben Yoho, who runs what the strategy

499
00:27:06,359 --> 00:27:12,160
Speaker 4: group for Media? Wait, how did that happen? It's a miracle,

500
00:27:12,640 --> 00:27:13,480
Speaker 4: It's amazing.

501
00:27:13,640 --> 00:27:18,280
Speaker 2: I also just think that Christy Nome is a like,

502
00:27:18,960 --> 00:27:22,320
Speaker 2: you know, when you think about this administration, you think

503
00:27:22,359 --> 00:27:24,800
Speaker 2: about like one of the things I think we learned

504
00:27:24,800 --> 00:27:28,760
Speaker 2: in twenty twenty five was that this is not going

505
00:27:28,800 --> 00:27:31,760
Speaker 2: to be forever. Trump is going to lose, he's going

506
00:27:31,800 --> 00:27:34,400
Speaker 2: to lose the House, he's going to lose the Senate.

507
00:27:34,880 --> 00:27:37,040
Speaker 2: He's not going to be president for the rest of

508
00:27:37,080 --> 00:27:40,199
Speaker 2: our lives. This is not how this is going to

509
00:27:40,240 --> 00:27:43,600
Speaker 2: go down at all. In fact, this is going There's

510
00:27:43,640 --> 00:27:45,359
Speaker 2: going to be truth and reconciliation.

511
00:27:45,520 --> 00:27:47,200
Speaker 4: There's going to be oh yes, there will be.

512
00:27:47,240 --> 00:27:48,359
Speaker 5: There's the lies.

513
00:27:48,400 --> 00:27:50,200
Speaker 2: People are going to go to jail or let.

514
00:27:50,119 --> 00:27:52,119
Speaker 4: Me say something a huge time. I will bet you

515
00:27:52,200 --> 00:27:54,680
Speaker 4: a dollar right now that Greg Bavino, the guy who

516
00:27:54,720 --> 00:27:57,720
Speaker 4: runs all these ice operations around the country, the guy

517
00:27:57,760 --> 00:28:00,199
Speaker 4: who shows up in the big hugo boss, you know,

518
00:28:00,280 --> 00:28:03,119
Speaker 4: Nazi style greatcoat. I will bet you a dollar that

519
00:28:03,200 --> 00:28:05,320
Speaker 4: guy goes to prison. He will be the Patsy and

520
00:28:05,400 --> 00:28:08,600
Speaker 4: Chrissy Nome and Steven Miller will go. He just misinterpreted

521
00:28:08,640 --> 00:28:11,119
Speaker 4: our orders. We were trying to stay within the and

522
00:28:11,160 --> 00:28:13,159
Speaker 4: it just it got out of hand.

523
00:28:13,480 --> 00:28:14,600
Speaker 2: What about Tom Holman?

524
00:28:15,000 --> 00:28:16,400
Speaker 4: Oh, Tom Holman's going to jail.

525
00:28:16,640 --> 00:28:20,200
Speaker 2: Cash in the cash in the bag, Tom, Yeah, bag

526
00:28:20,320 --> 00:28:22,400
Speaker 2: cave bag bag time.

527
00:28:22,680 --> 00:28:24,880
Speaker 4: I think Pam Bondi's going to jail. I think Tom

528
00:28:24,880 --> 00:28:27,000
Speaker 4: Blank is going to jail. And I say this because

529
00:28:27,160 --> 00:28:30,479
Speaker 4: I think there's an increasing understanding among the Democrats who

530
00:28:30,520 --> 00:28:33,840
Speaker 4: are not the quickest on the uptake about the use

531
00:28:33,880 --> 00:28:38,480
Speaker 4: of power in this country. They act, yeah, you do.

532
00:28:39,280 --> 00:28:42,240
Speaker 4: I think even now they're realizing, if we don't hold

533
00:28:42,240 --> 00:28:46,040
Speaker 4: some people to account for the criminality of the things

534
00:28:46,080 --> 00:28:48,479
Speaker 4: that are going on right now, it will allow a

535
00:28:48,520 --> 00:28:51,040
Speaker 4: cohort of these people to survive out there like a

536
00:28:51,120 --> 00:28:54,280
Speaker 4: like a virus that's dormab more and come back and

537
00:28:54,440 --> 00:28:56,080
Speaker 4: come back and do it again.

538
00:28:56,480 --> 00:29:00,800
Speaker 2: Like JD. Van's like JD be president in twenty twenty.

539
00:29:00,880 --> 00:29:03,920
Speaker 2: Hat just kidding, you know, Guy's never going to be president.

540
00:29:03,960 --> 00:29:04,120
Speaker 7: You know.

541
00:29:04,440 --> 00:29:08,760
Speaker 4: The thing I love about Jennie Vance is the groper demo.

542
00:29:09,440 --> 00:29:11,840
Speaker 4: That is a very powerful demo inside the GOP. Now

543
00:29:12,440 --> 00:29:15,520
Speaker 4: he is married to a foreigner in their mind, and

544
00:29:15,600 --> 00:29:18,720
Speaker 4: she is an alien and a brown person, and therefore

545
00:29:19,240 --> 00:29:22,400
Speaker 4: they awaite the nuptials of Erica Kirk.

546
00:29:22,120 --> 00:29:24,320
Speaker 5: And van Rick Wilson.

547
00:29:24,520 --> 00:29:26,680
Speaker 4: Will come back, of course I will.

548
00:29:29,000 --> 00:29:33,000
Speaker 2: Michael Steinberger is a freelance journalist and the author of

549
00:29:33,080 --> 00:29:36,640
Speaker 2: The Philosopher in the Valley, Alex Carp Palenteer and the

550
00:29:36,760 --> 00:29:40,720
Speaker 2: Rise of the Surveillance State. Welcome to Fast Politics.

551
00:29:40,240 --> 00:29:42,080
Speaker 6: Michael, Thank you very much for having me.

552
00:29:42,160 --> 00:29:46,280
Speaker 2: I want you first to explain what Palenteer does, because

553
00:29:46,320 --> 00:29:48,720
Speaker 2: I think we all sort of know, but we don't

554
00:29:48,760 --> 00:29:50,120
Speaker 2: exactly know, Okay.

555
00:29:50,520 --> 00:29:53,400
Speaker 6: Valenteer is a data analytics company.

556
00:29:53,440 --> 00:29:57,880
Speaker 7: They make software that helps organizations make better, more efficient

557
00:29:57,960 --> 00:30:00,680
Speaker 7: use of their data. It's used by a very wide

558
00:30:00,760 --> 00:30:05,040
Speaker 7: range of organizations, ranging from the CIA.

559
00:30:04,320 --> 00:30:09,160
Speaker 6: To US Army to corporations like Airbus and BP.

560
00:30:09,520 --> 00:30:12,240
Speaker 7: It's important to say what Penalt two doesn't do, because

561
00:30:12,280 --> 00:30:17,000
Speaker 7: then the name Palalteer has become virtually synonymous with surveillance,

562
00:30:17,040 --> 00:30:20,000
Speaker 7: and I have now helped make that so, because the

563
00:30:20,000 --> 00:30:21,920
Speaker 7: word surveillance is on the cover of my book.

564
00:30:22,680 --> 00:30:24,600
Speaker 6: It is not surveillance technology per se.

565
00:30:24,840 --> 00:30:28,840
Speaker 7: Their technology can be used by clandestine services and law

566
00:30:28,920 --> 00:30:33,400
Speaker 7: enforcement to facilitate surveillance. It makes their jobs easier, but

567
00:30:33,400 --> 00:30:36,200
Speaker 7: it's not survevance technology per se. And I think there's

568
00:30:36,240 --> 00:30:39,840
Speaker 7: another misconception about pala Twer that needs to be addressed

569
00:30:40,040 --> 00:30:43,040
Speaker 7: as well, which is they do not collect data, they

570
00:30:43,040 --> 00:30:46,640
Speaker 7: do not store data, they do not sell data. So yeah,

571
00:30:46,640 --> 00:30:49,280
Speaker 7: because people, you know, it's a name that does give

572
00:30:49,440 --> 00:30:52,880
Speaker 7: people the creeps, it does make people very nervous, and

573
00:30:52,920 --> 00:30:54,880
Speaker 7: so I think it's important to establish what they don't

574
00:30:54,880 --> 00:30:56,360
Speaker 7: do as well as what they do do.

575
00:30:56,600 --> 00:30:59,440
Speaker 2: But they do scrape data, right.

576
00:30:59,440 --> 00:31:01,920
Speaker 7: They don't data, But what happens is so for instance,

577
00:31:01,960 --> 00:31:05,600
Speaker 7: they're working with ice snap Ice is scraping data. Data

578
00:31:05,680 --> 00:31:09,360
Speaker 7: is fed into Palenteer's software platform. So just to you know,

579
00:31:09,400 --> 00:31:11,200
Speaker 7: give an example, So ICE could be pulling in at

580
00:31:11,240 --> 00:31:15,480
Speaker 7: social media feeds, and then they also have telephone records,

581
00:31:15,520 --> 00:31:19,000
Speaker 7: they have automatic license plate reader information. All this data

582
00:31:19,240 --> 00:31:24,120
Speaker 7: gets fed into Palenteer's software platform, and that platform then

583
00:31:24,240 --> 00:31:29,960
Speaker 7: the data is integrated and the software finds patterns, correlations, connections.

584
00:31:30,000 --> 00:31:33,360
Speaker 7: It's it's network analysis essentially, so you know, it's not

585
00:31:33,520 --> 00:31:37,200
Speaker 7: palenteered doing you know, getting this data. It's palenteer enabling

586
00:31:37,280 --> 00:31:40,840
Speaker 7: name them, these organizations to make faster, better use of

587
00:31:40,880 --> 00:31:44,160
Speaker 7: their data. And in most cases that's just in most

588
00:31:44,240 --> 00:31:46,480
Speaker 7: of the work they do. It's you know, yeah, fifty

589
00:31:46,520 --> 00:31:48,560
Speaker 7: percent of their work is on the commercial side. It's

590
00:31:48,600 --> 00:31:51,240
Speaker 7: just helping companies make their operations more efficient. So it's

591
00:31:51,240 --> 00:31:53,880
Speaker 7: nothing that should cause anyone to lose sleep. It's the

592
00:31:53,920 --> 00:31:56,440
Speaker 7: work on the other on the government side, you know,

593
00:31:56,880 --> 00:32:00,600
Speaker 7: with intelligence services and obviously with ICE, that is reason

594
00:32:00,680 --> 00:32:01,280
Speaker 7: for concern.

595
00:32:01,520 --> 00:32:05,640
Speaker 2: Okay, say your eyes, you've got social media feed for

596
00:32:05,720 --> 00:32:09,440
Speaker 2: this person, you've got their driver's license. What is the

597
00:32:09,520 --> 00:32:12,720
Speaker 2: secret sauce of Hellent does to make those connections. It's

598
00:32:12,720 --> 00:32:14,880
Speaker 2: sort of like an AI search.

599
00:32:15,160 --> 00:32:15,920
Speaker 6: I would put it this way.

600
00:32:16,200 --> 00:32:18,360
Speaker 7: It operates with the efficiency of a wood chip or

601
00:32:18,400 --> 00:32:21,200
Speaker 7: it pulls in a lot of data very quickly and

602
00:32:21,840 --> 00:32:25,200
Speaker 7: finds answers in that data, evidence in that data.

603
00:32:25,000 --> 00:32:25,880
Speaker 6: Very very quickly.

604
00:32:25,920 --> 00:32:27,680
Speaker 7: Because basically the problem is, you know, you can think

605
00:32:27,720 --> 00:32:30,120
Speaker 7: of it almost as a digital detective board. So you

606
00:32:30,160 --> 00:32:32,560
Speaker 7: think of like, you know, any procedural you see, you know,

607
00:32:32,840 --> 00:32:35,040
Speaker 7: the guy standing at the detective standing at the board

608
00:32:35,120 --> 00:32:37,479
Speaker 7: playing connect the dots. That's what the software. That's what

609
00:32:37,480 --> 00:32:40,320
Speaker 7: this software does. The company began for the was started

610
00:32:40,320 --> 00:32:42,880
Speaker 7: for the purpose of helping the United States government fight

611
00:32:42,920 --> 00:32:45,200
Speaker 7: the war on terrorism, and the idea behind it was

612
00:32:45,240 --> 00:32:48,960
Speaker 7: that you could create technology, build technology that help human

613
00:32:49,000 --> 00:32:52,480
Speaker 7: analysts that the CIA foil plots, for instance, by pulling

614
00:32:52,520 --> 00:32:55,880
Speaker 7: together information for them and making connections doing the kind

615
00:32:55,880 --> 00:33:00,400
Speaker 7: of network analysis that would take human analysts days, hours, weeks,

616
00:33:00,400 --> 00:33:03,400
Speaker 7: possibly forever to do. And so this software really speeds

617
00:33:03,480 --> 00:33:05,400
Speaker 7: up that kind of work. It's a very powerful tool.

618
00:33:05,600 --> 00:33:09,640
Speaker 2: So Alex Carb talk us through how you got involved

619
00:33:09,640 --> 00:33:10,880
Speaker 2: in writing this book on him.

620
00:33:11,000 --> 00:33:12,920
Speaker 6: Well, I grew out of a story I did for

621
00:33:12,920 --> 00:33:14,560
Speaker 6: the New York Times magazine. I'm right. For the New

622
00:33:14,640 --> 00:33:15,440
Speaker 6: York Times magazine.

623
00:33:15,480 --> 00:33:17,920
Speaker 7: I did a story about carbon Palatude was published in

624
00:33:17,920 --> 00:33:21,120
Speaker 7: twenty twenty. There's an even more interesting backstory. Though he

625
00:33:21,160 --> 00:33:24,080
Speaker 7: and I went to the same college. We were college classmates,

626
00:33:24,120 --> 00:33:25,520
Speaker 7: we did not know each other in college.

627
00:33:25,520 --> 00:33:26,479
Speaker 2: What college did you go to?

628
00:33:26,600 --> 00:33:27,480
Speaker 6: Haverford College?

629
00:33:27,800 --> 00:33:30,760
Speaker 7: Okay, and if you know anything about Haverford you will

630
00:33:30,800 --> 00:33:33,680
Speaker 7: know how bizarre it is that two people were in

631
00:33:33,680 --> 00:33:35,960
Speaker 7: the same class at Haverford and never exchanged the work.

632
00:33:35,960 --> 00:33:38,360
Speaker 7: Because it's a small school, it's like fifteen hundred people total.

633
00:33:38,560 --> 00:33:41,080
Speaker 7: Somehow we managed to pull that off. We never exchanged

634
00:33:41,080 --> 00:33:42,479
Speaker 7: the work, which is why I was able to do

635
00:33:42,560 --> 00:33:44,280
Speaker 7: the story for the New York Times magazine because there

636
00:33:44,320 --> 00:33:47,880
Speaker 7: was no relationship, therefore no conflict of interest. He I think,

637
00:33:48,040 --> 00:33:50,400
Speaker 7: was a bit more diligent about a schoolwork than I was.

638
00:33:50,440 --> 00:33:52,480
Speaker 7: I suspect the library saw a lot more of him

639
00:33:52,480 --> 00:33:54,760
Speaker 7: than it did of me, which may go some way

640
00:33:54,800 --> 00:33:56,720
Speaker 7: to explaining why he ended up a billionaire and I

641
00:33:56,760 --> 00:33:57,960
Speaker 7: did not, but be that SMA.

642
00:33:58,120 --> 00:33:59,160
Speaker 6: So that's kind of the backstory.

643
00:33:59,200 --> 00:34:01,960
Speaker 7: So I did the story for the New York Times magazine,

644
00:34:02,040 --> 00:34:04,160
Speaker 7: and as comprehensive as that story was, and it was

645
00:34:04,160 --> 00:34:07,440
Speaker 7: about nine thousand words, it was a long magazine feature,

646
00:34:07,680 --> 00:34:09,080
Speaker 7: I felt that there was a lot more to say.

647
00:34:09,160 --> 00:34:12,280
Speaker 7: Karp is a very distinctive figure in the business world.

648
00:34:12,400 --> 00:34:15,960
Speaker 7: This company is obviously one that generates a lot of controversy,

649
00:34:16,040 --> 00:34:18,040
Speaker 7: causes a lot of concern for people, and so that

650
00:34:18,160 --> 00:34:20,520
Speaker 7: gave rise to the book. He was willing to cooperate

651
00:34:20,600 --> 00:34:24,080
Speaker 7: and gave me actually pretty extraordinary access. So I think

652
00:34:24,080 --> 00:34:27,880
Speaker 7: it's an unusually rich portrait of someone who really is

653
00:34:27,920 --> 00:34:30,720
Speaker 7: at the center of He's a defining figure of this moment.

654
00:34:30,960 --> 00:34:35,400
Speaker 2: So he believes that Talunteer could be like IVM.

655
00:34:35,200 --> 00:34:37,000
Speaker 6: As I said. It was started to help the US

656
00:34:37,040 --> 00:34:38,280
Speaker 6: government combat terrorism.

657
00:34:38,440 --> 00:34:40,719
Speaker 7: It was a very political company from the start in

658
00:34:40,760 --> 00:34:42,720
Speaker 7: that explicitly political agenda.

659
00:34:42,800 --> 00:34:46,000
Speaker 6: Wanted to serve the US government and make the West stronger.

660
00:34:46,040 --> 00:34:48,080
Speaker 7: So from the start they decided they would not do

661
00:34:48,120 --> 00:34:50,719
Speaker 7: business with the Russian government, the Chinese government, or any

662
00:34:50,800 --> 00:34:53,839
Speaker 7: Russian or Chinese owned entities because they saw those two

663
00:34:53,880 --> 00:34:57,120
Speaker 7: countries as fundamentally adversarial to the United States. While serving

664
00:34:57,160 --> 00:34:59,600
Speaker 7: the government, working with the CIA, working with the US military,

665
00:34:59,600 --> 00:35:02,360
Speaker 7: they are allo developing a trying to develop a robust

666
00:35:02,400 --> 00:35:05,879
Speaker 7: commercial business, and many years later, now in twenty twenty five,

667
00:35:05,880 --> 00:35:07,839
Speaker 7: they have both. They are huge in government and they

668
00:35:07,840 --> 00:35:11,560
Speaker 7: are huge on the commercial side. Is that like McKenzie

669
00:35:11,640 --> 00:35:15,439
Speaker 7: Airbus for instance, so they Airbus began working with him

670
00:35:15,520 --> 00:35:20,280
Speaker 7: in around twenty fifteen twenty sixteen. Airbus had a production glitch,

671
00:35:20,400 --> 00:35:22,640
Speaker 7: was coming out with a new plane, a three fifty,

672
00:35:22,840 --> 00:35:25,000
Speaker 7: and there was a production glitch. But as you can imagine,

673
00:35:25,120 --> 00:35:28,640
Speaker 7: the assembly line for a commercial jetliner is a very

674
00:35:28,920 --> 00:35:31,920
Speaker 7: very intricate thing, and they couldn't figure out where the

675
00:35:31,920 --> 00:35:35,480
Speaker 7: problem was. They brought in volunteer company dispatched five software

676
00:35:35,480 --> 00:35:38,839
Speaker 7: engineers to Booz, France, whereas Airbus is located, and within

677
00:35:38,880 --> 00:35:41,680
Speaker 7: a matter of days they had detected where the breakdowns

678
00:35:41,680 --> 00:35:43,960
Speaker 7: are happening on the production of the assembly line and

679
00:35:44,000 --> 00:35:46,120
Speaker 7: it ended up saving the company a lot of money.

680
00:35:46,160 --> 00:35:50,000
Speaker 7: And now Palneer is basically the de facto operating system

681
00:35:50,160 --> 00:35:54,279
Speaker 7: for Airbus. Around fifty thousand Airbus employees a day use

682
00:35:54,360 --> 00:35:55,360
Speaker 7: the company's software.

683
00:35:55,440 --> 00:35:59,040
Speaker 2: Why is this story so explosive.

684
00:35:58,800 --> 00:35:59,720
Speaker 6: Well, what's interesting.

685
00:35:59,760 --> 00:36:02,480
Speaker 7: He's he's a very different sort of CEO, not a

686
00:36:02,480 --> 00:36:03,600
Speaker 7: standard issue CEO.

687
00:36:03,840 --> 00:36:05,400
Speaker 6: He speaks very candidly.

688
00:36:05,560 --> 00:36:08,200
Speaker 7: He says exactly what's on his mind and says so

689
00:36:08,440 --> 00:36:11,040
Speaker 7: in a sort of a very unscripted way. So he's

690
00:36:11,560 --> 00:36:13,880
Speaker 7: a very striking presence on television, and a lot of

691
00:36:13,880 --> 00:36:15,879
Speaker 7: what he says is controversial, I mean, his view.

692
00:36:15,920 --> 00:36:18,280
Speaker 6: I mean to kind of unpack the Alex Karp story.

693
00:36:18,320 --> 00:36:22,840
Speaker 7: So he is biracial, He's Jewish, severely dyslexic, grew up

694
00:36:22,840 --> 00:36:25,799
Speaker 7: in Philadelphia. As he tells it, he understood at a

695
00:36:25,880 --> 00:36:29,480
Speaker 7: fairly young age that he had some strikes against him

696
00:36:29,520 --> 00:36:32,160
Speaker 7: because he was biracial, because he was Jewish, because he

697
00:36:32,239 --> 00:36:35,560
Speaker 7: had a learning disability, and this gave him a sense

698
00:36:35,560 --> 00:36:39,920
Speaker 7: of vulnerability that he has carried into adulthood. And you

699
00:36:39,960 --> 00:36:43,319
Speaker 7: could say that in a very real sense, Palenteer exists

700
00:36:43,560 --> 00:36:46,200
Speaker 7: in part to make the world safer for Alex Karp.

701
00:36:46,280 --> 00:36:48,319
Speaker 7: He obviously thinks it's making the world safer for many

702
00:36:48,360 --> 00:36:50,879
Speaker 7: other people, but he has this sense of vulnerability.

703
00:36:50,920 --> 00:36:53,760
Speaker 6: He also has a quite dark view of the world.

704
00:36:53,840 --> 00:36:56,520
Speaker 7: I mean, he thinks that humanity is just naturally given

705
00:36:56,640 --> 00:36:59,480
Speaker 7: to violence and disorder. There's never been this sort of

706
00:36:59,480 --> 00:37:02,560
Speaker 7: techno op demism with talent here. It's always their elevator.

707
00:37:02,600 --> 00:37:05,040
Speaker 7: Pitch has always been, you know, in a very dangerous world,

708
00:37:05,080 --> 00:37:07,080
Speaker 7: we can maybe make the world a little less dangerous. So,

709
00:37:07,239 --> 00:37:09,000
Speaker 7: you know, he and his view is, you know, we

710
00:37:09,040 --> 00:37:12,000
Speaker 7: have adversaries. We should kill them before they should kill us.

711
00:37:12,160 --> 00:37:15,719
Speaker 7: And the way he expresses this very colorfully, very acerbically,

712
00:37:15,880 --> 00:37:18,520
Speaker 7: obviously unnerveous people, as in some of the nature of

713
00:37:18,520 --> 00:37:18,879
Speaker 7: their work.

714
00:37:19,080 --> 00:37:23,239
Speaker 2: It's interesting because it's like, I'm dyslacks of Jewish of adhd.

715
00:37:23,719 --> 00:37:26,160
Speaker 2: I mean, I still felt like I was pretty much

716
00:37:26,239 --> 00:37:27,920
Speaker 2: born on second base.

717
00:37:28,400 --> 00:37:32,280
Speaker 6: Yeah, well, I think, you know, he took a different view, like, how.

718
00:37:32,160 --> 00:37:34,120
Speaker 2: Would the world be unsafe?

719
00:37:34,600 --> 00:37:37,319
Speaker 7: Well, you know, I mean anti Semitism is a very

720
00:37:37,360 --> 00:37:41,359
Speaker 7: real factor in the world, discrimination against African Americans, right,

721
00:37:41,440 --> 00:37:41,840
Speaker 7: I mean.

722
00:37:41,760 --> 00:37:44,640
Speaker 2: That makes sense. But he's a kid of doctors, he is.

723
00:37:44,840 --> 00:37:46,560
Speaker 6: But then part of this is tied up in his job.

724
00:37:46,560 --> 00:37:48,359
Speaker 7: That he felt that his parents, mean, they loved him,

725
00:37:48,360 --> 00:37:50,239
Speaker 7: but he felt his parents and I talk about this

726
00:37:50,320 --> 00:37:54,080
Speaker 7: in the book he's got bad parents, No, not bad parents,

727
00:37:54,120 --> 00:37:56,520
Speaker 7: but does he felt like they were sort of underachievers

728
00:37:56,560 --> 00:37:59,120
Speaker 7: in a sense that they didn't know how to navigate

729
00:37:59,160 --> 00:38:02,200
Speaker 7: the world in some way, and that he does. And

730
00:38:02,239 --> 00:38:04,080
Speaker 7: but he felt because they did know how to navigate

731
00:38:04,120 --> 00:38:06,520
Speaker 7: the world in a sense, they couldn't really protect them.

732
00:38:06,520 --> 00:38:09,960
Speaker 7: So he has the sense that he is vulnerable, that

733
00:38:10,840 --> 00:38:13,359
Speaker 7: others cannot protect him. And you know, listen, we're talking

734
00:38:13,400 --> 00:38:16,560
Speaker 7: now about a guy who's worth fifteen sixteen billion dollars

735
00:38:16,600 --> 00:38:18,799
Speaker 7: has a large security detail. But I think it's a

736
00:38:18,840 --> 00:38:21,319
Speaker 7: really important part of understanding who he is and how

737
00:38:21,320 --> 00:38:22,280
Speaker 7: he thinks about the world.

738
00:38:22,400 --> 00:38:25,840
Speaker 2: No, I think it's important, and it's totally fascinating, And

739
00:38:26,400 --> 00:38:30,319
Speaker 2: so many of these tech billionaires have a sort of

740
00:38:30,400 --> 00:38:31,960
Speaker 2: similar Greshtald right.

741
00:38:32,160 --> 00:38:34,600
Speaker 7: They all seem to be variations on a similar theme.

742
00:38:34,880 --> 00:38:37,680
Speaker 7: And of course Karp, like a number of these others,

743
00:38:37,719 --> 00:38:39,960
Speaker 7: has found his way to Trump. But his story is

744
00:38:39,960 --> 00:38:42,840
Speaker 7: a more interesting one in some sense because he's always identified.

745
00:38:43,040 --> 00:38:45,000
Speaker 7: In the early days of Pound here he identified as

746
00:38:45,000 --> 00:38:48,200
Speaker 7: a neo socialist, and which made an interesting contrast with

747
00:38:48,239 --> 00:38:51,960
Speaker 7: his co founder Peter Teal, who was famously libertarian.

748
00:38:52,000 --> 00:38:53,960
Speaker 6: This is before Teal moved to the far right.

749
00:38:54,160 --> 00:38:56,600
Speaker 2: Is this before these people turned out to be who

750
00:38:56,600 --> 00:38:57,840
Speaker 2: they were exactly?

751
00:38:57,840 --> 00:38:59,719
Speaker 6: So Teal identified as a libertarian.

752
00:39:00,320 --> 00:39:02,640
Speaker 7: You know, they met at Stanford Law and then reconnected

753
00:39:02,640 --> 00:39:05,239
Speaker 7: some years later, and Teal brought Carp in as a

754
00:39:05,239 --> 00:39:09,000
Speaker 7: co founder of Palenteer and eventually made him CEO. But

755
00:39:09,040 --> 00:39:11,080
Speaker 7: you know, it was always this sort of interesting dynamic

756
00:39:11,120 --> 00:39:13,480
Speaker 7: because Teal was to the right, Karp was to the left.

757
00:39:13,760 --> 00:39:15,319
Speaker 6: That kind of served as a shield for.

758
00:39:15,320 --> 00:39:18,440
Speaker 7: Palenteer, because you know, even if people didn't think well

759
00:39:18,440 --> 00:39:20,560
Speaker 7: of Peter Teal's politics, then you had this guy. Alex

760
00:39:20,600 --> 00:39:23,040
Speaker 7: Karp is self described progressive, but he's not.

761
00:39:23,280 --> 00:39:24,360
Speaker 2: A progressive anymore.

762
00:39:24,680 --> 00:39:27,600
Speaker 7: Well, you know, I think he sometimes he still describes

763
00:39:27,680 --> 00:39:30,799
Speaker 7: himself as that he has positions on some issues where

764
00:39:30,880 --> 00:39:33,400
Speaker 7: you could say, okay, that could be categorized as progressive.

765
00:39:33,400 --> 00:39:35,680
Speaker 6: I think he's in favor of universal health care.

766
00:39:35,880 --> 00:39:38,480
Speaker 7: He does talk about inequality in this country in a

767
00:39:38,520 --> 00:39:40,840
Speaker 7: way that there is more than just lip service. But

768
00:39:40,880 --> 00:39:43,239
Speaker 7: then he's always had views that you know, would sort

769
00:39:43,239 --> 00:39:46,680
Speaker 7: of fall outside of the progressive mainstream. He is opposed

770
00:39:46,719 --> 00:39:49,080
Speaker 7: to affirmative action, has always been opposed to it. Are

771
00:39:49,120 --> 00:39:53,360
Speaker 7: in Second Amendment enthusiast. He has moved away from the

772
00:39:53,400 --> 00:39:55,600
Speaker 7: Democrats and the left. I think he would say that

773
00:39:55,640 --> 00:39:58,600
Speaker 7: the left left him. And the book chronicles this because

774
00:39:58,640 --> 00:40:00,359
Speaker 7: it takes you through the first Trump present and see

775
00:40:00,360 --> 00:40:03,040
Speaker 7: when he makes very clear that he does not like Trump,

776
00:40:03,120 --> 00:40:05,320
Speaker 7: and he said so very publicly and including to me.

777
00:40:05,560 --> 00:40:06,359
Speaker 6: He does not like him.

778
00:40:06,400 --> 00:40:08,600
Speaker 7: He disagrees with them about it pretty much everything, including

779
00:40:08,600 --> 00:40:11,279
Speaker 7: immigration policy. At that time, I mean pallenteers working with

780
00:40:11,360 --> 00:40:13,040
Speaker 7: ICE at the time, it was a source of great

781
00:40:13,040 --> 00:40:15,120
Speaker 7: controversy internally and externally.

782
00:40:15,160 --> 00:40:17,719
Speaker 6: The company was, you know, its offices were being protested.

783
00:40:17,840 --> 00:40:19,919
Speaker 7: Karp does not particularly enjoy that period, but he also

784
00:40:19,920 --> 00:40:21,719
Speaker 7: makes clear he says, look, I'm not in favor of

785
00:40:21,760 --> 00:40:24,200
Speaker 7: open borders, but I have personally no problem with the

786
00:40:24,239 --> 00:40:27,560
Speaker 7: demographics of this country changing. But you know, then you see,

787
00:40:27,640 --> 00:40:30,600
Speaker 7: you know, over time his views begins to change. I mean,

788
00:40:30,640 --> 00:40:32,280
Speaker 7: he said to me this to me in twenty nineteen,

789
00:40:32,320 --> 00:40:35,640
Speaker 7: and during Trump's first presidency, he said, look at the voters.

790
00:40:35,680 --> 00:40:38,840
Speaker 7: Clearly have an issue with chaotic scenes at the border

791
00:40:39,000 --> 00:40:43,200
Speaker 7: and with illegal immigration. He said, if Democrats and progressives

792
00:40:43,239 --> 00:40:46,000
Speaker 7: don't take those concerns seriously, voters are going to turn

793
00:40:46,040 --> 00:40:47,800
Speaker 7: to people who do, And he said that had happened

794
00:40:47,800 --> 00:40:49,800
Speaker 7: in twenty sixteen, and of course here we are in

795
00:40:49,800 --> 00:40:52,640
Speaker 7: twenty twenty five and Trumps president again. Even though he

796
00:40:52,719 --> 00:40:55,719
Speaker 7: spoke very critically of Trump during Trump's first presidency, he

797
00:40:55,760 --> 00:40:59,040
Speaker 7: was already beginning to feel alienated from the left and

798
00:40:59,280 --> 00:41:02,120
Speaker 7: that accelerated during the Biden years and and kind of

799
00:41:02,160 --> 00:41:05,960
Speaker 7: reaches it's daneumund if you will. With October seventh and

800
00:41:06,560 --> 00:41:09,040
Speaker 7: the protest on campus, and he was maybe the most

801
00:41:09,080 --> 00:41:12,719
Speaker 7: outspoken CEO, and he saw it a symptomatic you know,

802
00:41:12,760 --> 00:41:16,080
Speaker 7: he in his view, you know, the protesters had completely

803
00:41:16,160 --> 00:41:19,640
Speaker 7: erased the line between anti Zionism and anti Semitism, and

804
00:41:19,680 --> 00:41:21,360
Speaker 7: he saw it as part of a larger rod on

805
00:41:21,400 --> 00:41:21,760
Speaker 7: the left.

806
00:41:21,760 --> 00:41:23,319
Speaker 6: And now he's on board with.

807
00:41:23,280 --> 00:41:27,400
Speaker 2: Trump, So he's in Israel voter largely.

808
00:41:27,520 --> 00:41:30,160
Speaker 7: Well, that's a big issue for him. I'm in Palenteer

809
00:41:30,480 --> 00:41:34,120
Speaker 7: has been very involved in Israel. They sold their software

810
00:41:34,200 --> 00:41:38,520
Speaker 7: to the Mossad and the mid twenty tens, after October seventh,

811
00:41:38,640 --> 00:41:42,200
Speaker 7: the idea wants the software. Shin Bet, the domestic intelligence

812
00:41:42,239 --> 00:41:44,520
Speaker 7: service in Israel wants it and it. Pound has an

813
00:41:44,520 --> 00:41:47,440
Speaker 7: office already and at this time in Tel Aviv, they

814
00:41:47,520 --> 00:41:49,520
Speaker 7: got so many people coming in to get trained on

815
00:41:49,280 --> 00:41:50,920
Speaker 7: their on their software that they have to rent a

816
00:41:50,920 --> 00:41:52,000
Speaker 7: second floor of the building.

817
00:41:52,360 --> 00:41:53,879
Speaker 6: And he very publicly stayed.

818
00:41:53,920 --> 00:41:56,919
Speaker 7: I mean, you know, a couple of days after, maybe

819
00:41:56,960 --> 00:41:58,840
Speaker 7: a week or so after the massacre, at the October

820
00:41:58,840 --> 00:42:01,120
Speaker 7: seventh massacre, Pound takes out a full page ad in

821
00:42:01,120 --> 00:42:03,880
Speaker 7: New York Times saying Palanter stands with Israel. He goes

822
00:42:03,880 --> 00:42:07,719
Speaker 7: to Israel and early two thy twenty four holds a

823
00:42:07,760 --> 00:42:12,000
Speaker 7: board meeting there. Teal is there they meet with Netan Yahoo.

824
00:42:12,000 --> 00:42:13,960
Speaker 7: Wasn't reported at the time. I reporting it in the

825
00:42:13,960 --> 00:42:16,279
Speaker 7: book for the first time because no one wanted to

826
00:42:16,280 --> 00:42:18,319
Speaker 7: disclose that they had met with net Yahoo. But so

827
00:42:18,360 --> 00:42:19,840
Speaker 7: I'm reporting it the first time of the book that

828
00:42:19,880 --> 00:42:22,040
Speaker 7: they actually met with Netanyahu. When they were there. So

829
00:42:22,200 --> 00:42:24,920
Speaker 7: he has been a staunch support of Israel. They have

830
00:42:25,280 --> 00:42:28,799
Speaker 7: pushed back quite furiously against claims that their software has

831
00:42:28,840 --> 00:42:31,839
Speaker 7: had any hand in AI driven targeting in Gaza. They said,

832
00:42:31,840 --> 00:42:33,560
Speaker 7: that's not the case. But they've been involved with other

833
00:42:33,600 --> 00:42:36,480
Speaker 7: stuff in Israel, and he makes no bones about that. So, yes,

834
00:42:36,640 --> 00:42:39,880
Speaker 7: Israel matters greatly to him. He is very upset about

835
00:42:39,960 --> 00:42:43,080
Speaker 7: anti semitism un left in the right, but he's been more.

836
00:42:42,960 --> 00:42:45,279
Speaker 6: Focused on what he sees as anti semitism on the left,

837
00:42:45,280 --> 00:42:46,960
Speaker 6: and this is part of what has driven him away

838
00:42:46,960 --> 00:42:47,879
Speaker 6: from the Democrats.

839
00:42:48,200 --> 00:42:50,839
Speaker 2: Yeah, so what did you learn from this guy?

840
00:42:52,760 --> 00:42:55,000
Speaker 7: Well, I mean, there are all sorts of things you

841
00:42:55,040 --> 00:42:57,279
Speaker 7: can learn from him. I mean one, I mean, like,

842
00:42:57,600 --> 00:43:00,359
Speaker 7: he's an interesting figure in that he has a very

843
00:43:00,400 --> 00:43:03,360
Speaker 7: improbable story here as a business story, and this is

844
00:43:03,400 --> 00:43:06,160
Speaker 7: a guy who grew up in a staunchly left wing household,

845
00:43:06,360 --> 00:43:10,480
Speaker 7: ends up no background in computer science, no background in business,

846
00:43:10,480 --> 00:43:12,600
Speaker 7: and ends up as the CEO of a company making

847
00:43:12,719 --> 00:43:15,680
Speaker 7: software that the principal aim of which is to help.

848
00:43:15,640 --> 00:43:18,480
Speaker 6: The national security state. And he turns this into a

849
00:43:18,560 --> 00:43:20,200
Speaker 6: half trillion dollar colossus.

850
00:43:20,320 --> 00:43:22,920
Speaker 7: I mean, the company is just remarkably successful now, So

851
00:43:22,920 --> 00:43:26,240
Speaker 7: it's an amazing business story. And what's interesting about Karp,

852
00:43:26,320 --> 00:43:28,359
Speaker 7: whatever you think of his views, is he puts them

853
00:43:28,360 --> 00:43:31,719
Speaker 7: out there. There is an authenticity, a candor that is unusual,

854
00:43:31,920 --> 00:43:34,520
Speaker 7: and I think that is quite striking. And I would

855
00:43:34,520 --> 00:43:37,720
Speaker 7: also say, look, there are legitimate reasons to be fearful

856
00:43:37,719 --> 00:43:39,359
Speaker 7: of Palenteer, fearful of.

857
00:43:39,320 --> 00:43:39,840
Speaker 6: The use to it.

858
00:43:39,920 --> 00:43:41,440
Speaker 7: It's being put So I would say this, I mean,

859
00:43:41,440 --> 00:43:42,680
Speaker 7: because people say, like, how.

860
00:43:42,520 --> 00:43:43,960
Speaker 6: Scared should we be now of Palenteer.

861
00:43:44,000 --> 00:43:46,120
Speaker 7: I would say this in the context of our current moment,

862
00:43:46,200 --> 00:43:49,239
Speaker 7: because again, it's the end user who decides how they

863
00:43:49,360 --> 00:43:49,719
Speaker 7: use it.

864
00:43:49,800 --> 00:43:54,320
Speaker 2: I feel like I know so many really rich guys

865
00:43:54,440 --> 00:43:58,960
Speaker 2: who grew up with liberal intellectual parents who decided that

866
00:43:59,320 --> 00:44:03,200
Speaker 2: anti sem was the greatest danger of facing Americans today.

867
00:44:03,719 --> 00:44:05,680
Speaker 2: I can think of five people off the top of

868
00:44:05,719 --> 00:44:09,520
Speaker 2: my head who fit, maybe not entirely into the Alex

869
00:44:09,560 --> 00:44:10,120
Speaker 2: cart mold.

870
00:44:10,520 --> 00:44:12,880
Speaker 6: It's not a unique trajectory, is what you're saying.

871
00:44:13,080 --> 00:44:15,560
Speaker 2: Yeah, I could look at my phone book right now

872
00:44:15,600 --> 00:44:18,160
Speaker 2: and tell you so. I mean, is there anything that

873
00:44:18,239 --> 00:44:22,359
Speaker 2: makes this person not just another rich guy who cares

874
00:44:22,360 --> 00:44:23,000
Speaker 2: about himself?

875
00:44:23,200 --> 00:44:24,840
Speaker 7: No, there are, I mean, I think looks that I

876
00:44:24,880 --> 00:44:27,279
Speaker 7: will say this, I mean he is very good to

877
00:44:27,320 --> 00:44:28,640
Speaker 7: the people who work for him.

878
00:44:28,680 --> 00:44:31,880
Speaker 6: He cares a lot about their happiness and their welfare.

879
00:44:32,320 --> 00:44:34,680
Speaker 2: Stark contrast to Elon, Well.

880
00:44:34,520 --> 00:44:36,200
Speaker 6: That's it. I mean, it's kind of what you expect,

881
00:44:36,200 --> 00:44:38,399
Speaker 6: but it's not the norm with some of these guys.

882
00:44:38,440 --> 00:44:40,840
Speaker 7: I mean, with someone like Elon, you are a widget

883
00:44:40,880 --> 00:44:43,000
Speaker 7: and you are very expendable, and that's the way it is.

884
00:44:43,080 --> 00:44:44,320
Speaker 6: It's different for car.

885
00:44:44,400 --> 00:44:48,160
Speaker 7: It a worker or a wife exactly, and that's that's

886
00:44:48,160 --> 00:44:50,320
Speaker 7: how it is. This is different, and he cares a

887
00:44:50,360 --> 00:44:52,400
Speaker 7: lot about what they think of him. So just on

888
00:44:52,440 --> 00:44:54,840
Speaker 7: a human basis, I think he's good to work for

889
00:44:54,880 --> 00:44:56,640
Speaker 7: he's good to the people who work for him. I

890
00:44:56,680 --> 00:45:00,120
Speaker 7: would also say this he likes being a billionaire in

891
00:45:00,960 --> 00:45:02,360
Speaker 7: terms of he likes being part of the club.

892
00:45:02,760 --> 00:45:04,440
Speaker 6: He is. Never has more weight.

893
00:45:04,800 --> 00:45:06,200
Speaker 7: I think it's also fair to say it never has

894
00:45:06,239 --> 00:45:09,799
Speaker 7: more money been wasted on someone than him. He lives

895
00:45:09,840 --> 00:45:13,560
Speaker 7: a very modest, almost ascetic life. He's got a bunch

896
00:45:13,600 --> 00:45:15,360
Speaker 7: of homes, but he doesn't spend much for most of

897
00:45:15,400 --> 00:45:17,520
Speaker 7: the homes. He does have a private plane. Now he

898
00:45:17,520 --> 00:45:20,200
Speaker 7: does no longer releases he bought. I'm glad to hear it,

899
00:45:20,480 --> 00:45:23,640
Speaker 7: because yeah, wealth is not a motivator for him. He

900
00:45:23,719 --> 00:45:27,719
Speaker 7: does not live lavishly in the circles he runs now

901
00:45:27,800 --> 00:45:30,000
Speaker 7: and he's surrounded by other rich people all the time,

902
00:45:30,080 --> 00:45:32,360
Speaker 7: and in those circles it's like sort of almost a

903
00:45:32,440 --> 00:45:33,200
Speaker 7: right of initiation.

904
00:45:33,280 --> 00:45:35,080
Speaker 6: You have to just dump on the Democrats.

905
00:45:35,120 --> 00:45:37,880
Speaker 7: And for a lot of these guys, it's basically because

906
00:45:38,160 --> 00:45:41,680
Speaker 7: they think they're being punished for their success and pilloried

907
00:45:41,760 --> 00:45:42,400
Speaker 7: for their wealth.

908
00:45:42,600 --> 00:45:43,360
Speaker 6: He doesn't have that.

909
00:45:43,440 --> 00:45:46,600
Speaker 7: I mean, his break with the Democrats has not been

910
00:45:46,680 --> 00:45:50,320
Speaker 7: because he feels like he's not being respected, not because

911
00:45:50,360 --> 00:45:52,080
Speaker 7: they want to tax him or he doesn't care.

912
00:45:52,160 --> 00:45:53,560
Speaker 6: He really doesn't care about that stuff.

913
00:45:53,600 --> 00:45:56,439
Speaker 7: It is on ideological ground, so that separates him from

914
00:45:56,520 --> 00:45:59,279
Speaker 7: some of the billionaire whiners, if you want to put

915
00:45:59,320 --> 00:45:59,880
Speaker 7: it that way.

916
00:46:00,120 --> 00:46:02,279
Speaker 2: Thank you so much, Michael for joining us.

917
00:46:02,400 --> 00:46:03,640
Speaker 6: Thank you very much for having me.

918
00:46:06,000 --> 00:46:12,920
Speaker 2: No moment, Rick Wilson, Molly John Fast, what is your

919
00:46:13,000 --> 00:46:13,840
Speaker 2: moment of huckery?

920
00:46:14,080 --> 00:46:16,440
Speaker 4: My moment of fuckery is off away from these shores

921
00:46:16,480 --> 00:46:19,480
Speaker 4: and overseas. It is not Venezuela, as many people would think,

922
00:46:19,680 --> 00:46:22,160
Speaker 4: even though I think to distract us, he might New

923
00:46:22,280 --> 00:46:23,520
Speaker 4: Caracas any day now.

924
00:46:23,960 --> 00:46:26,840
Speaker 5: Wag the whoops, wag the nuclear dog.

925
00:46:28,520 --> 00:46:31,040
Speaker 4: My molement of fuckery is that the BBC made a

926
00:46:31,120 --> 00:46:35,400
Speaker 4: giant mistake. They apologized to Trump for some editorial cuts

927
00:46:35,440 --> 00:46:39,280
Speaker 4: they made in some video from two thousand and twenty

928
00:46:39,320 --> 00:46:43,719
Speaker 4: one January sixth they apologize to him. Do not apologize

929
00:46:43,719 --> 00:46:46,640
Speaker 4: to Donald Trump for anything you do. If you wreck

930
00:46:46,719 --> 00:46:50,279
Speaker 4: his car, don't apologize. Don't apologize to Trump ever. It's

931
00:46:50,280 --> 00:46:52,719
Speaker 4: a sign of weakness. He will come for you now.

932
00:46:52,719 --> 00:46:55,320
Speaker 4: He wants to sue the BBC for five billion dollars

933
00:46:55,360 --> 00:46:57,719
Speaker 4: all this crap. Everybody in the media. When he says

934
00:46:57,719 --> 00:47:01,520
Speaker 4: he's gonna sue you, here's the response, Donald, go fuck yourself.

935
00:47:02,120 --> 00:47:05,120
Speaker 4: Stop it people. He can't win these cases. You can

936
00:47:05,160 --> 00:47:07,680
Speaker 4: give up, but he can't win BBC talking to you.

937
00:47:08,640 --> 00:47:11,359
Speaker 2: That's right, Rick Wilson, thank you, my.

938
00:47:11,400 --> 00:47:13,560
Speaker 4: Drunk Fast A pleasure as always, my friend.

939
00:47:14,080 --> 00:47:18,439
Speaker 2: That's it for this episode of Fast Politics. Tune in

940
00:47:18,760 --> 00:47:24,200
Speaker 2: every Monday, Wednesday, Thursday and Saturday to hear the best

941
00:47:24,280 --> 00:47:28,560
Speaker 2: minds and politics make sense of all this chaos. If

942
00:47:28,600 --> 00:47:31,680
Speaker 2: you enjoy this podcast, please send it to a friend

943
00:47:32,120 --> 00:47:35,320
Speaker 2: and keep the conversation going. Thanks for listening.