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Speaker 1: Hey guys, Saga and Crystal here.

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

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Speaker 2: and we are so excited about what that means for

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Speaker 2: go to Breakingpoints dot com. Become a member today and

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Speaker 1: We need your help to build the future of independent

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Speaker 1: news media and we hope to see you at Breakingpoints

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Speaker 1: dot com. Good morning, everybody, Happy Tuesday. Have an amazing

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Speaker 1: show for everybody today. What do we have, Crystal, indeed

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Speaker 1: we do.

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Speaker 2: We have Kevin Hassett of the White House telling us

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Speaker 2: we may have a quiet period in the labor market,

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Speaker 2: nothing to be distressed about, just because of AI displacement.

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Speaker 2: Might be a a little quiet out there in terms

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Speaker 2: of job creation. Also some updates on Larry Summers, who

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Speaker 2: was heavily featured in those Epstein emails that were released.

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Speaker 2: He says he is now stepping back from some of

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Speaker 2: his public commitments, So we will dig into what was

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Speaker 2: revealed there.

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Speaker 3: And his response.

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Speaker 2: Also a bunch of updates with regard to Ice. First

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Speaker 2: of all, Latinos who had voted in significant numbers for

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Speaker 2: Trump abandoning him also in significant numbers. And the Greg

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Speaker 2: Bovino team has now moved to Charlotte and then they're

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Speaker 2: apparently planning to go to New Orleans. So break down

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Speaker 2: what we know about those deployments and also the aftermath

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Speaker 2: of what happened in Chicago, some new indications about what

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Speaker 2: we may be planning in Venezuela. Will dig into that.

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Speaker 2: Sager has a property tax update for all of us.

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Speaker 2: Excited to hear from him on that one, and really

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Speaker 2: looking forward to this interview we have with a top

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Speaker 2: AI safety researcher. This is a guy who had left

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Speaker 2: Open AI because of his concerns about the direction of AI.

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Speaker 2: He is sounding the alarm and he co author of

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Speaker 2: paper called AI twenty twenty seven that's gotten a lot

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Speaker 2: of attention. That is his and his co author's best

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Speaker 2: guess of how AI is going to develop and the

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Speaker 2: major consequential, potentially civilizational risks entailed in this multi trillion

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Speaker 2: dollar project that the oligarchs and our government, Chinese and

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Speaker 2: everybody else are throwing tons of money at, tons tons

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Speaker 2: of effort at, so really looking forward to.

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Speaker 3: Speaking with him.

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Speaker 2: I've watched a bunch of his interviews and read his

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Speaker 2: paper obviously.

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Speaker 1: So that's one really interesting guy. I've seen a bunch

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Speaker 1: of his stuff. I know some of you are familiar

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Speaker 1: as well with play clips of him here on the show.

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Speaker 1: Thank you to everybody who has been signing up at

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Speaker 1: an episode to a friend. We've got a ton of

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Speaker 1: new listeners actually coming in from the Epstein issue, which

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Speaker 1: find the show. But let's go ahead and start there.

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Speaker 1: With the economy and this quiet period being described here

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Speaker 1: by the White House in this AI, they're saying, it's

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Speaker 1: just a little cooling off, it's just a little bit

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Speaker 1: of a blip of what's happening. Let's take a listen.

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Speaker 4: Last CPI report. We got surprised forty eight Bloomberg economists

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Speaker 4: on the downside, and even had some sort of temporary

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Speaker 4: bad news because there was a refinery.

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Speaker 1: That would shut down if you're looking at the top

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Speaker 1: flag number.

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Speaker 4: I think that there have been mixed signals in the

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Speaker 4: job market and really really positive signals in the output markets.

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Speaker 4: As you know, we've got GDP now running close to

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Speaker 4: four percent, we've got productivity running up around three percent,

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Speaker 4: and so I think that there could be a little

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Speaker 4: bit of almost a quiet time in the labor market

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Speaker 4: because firms are finding that AI is making their workers

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Speaker 4: so productive that they don't necessarily have to hire the

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Speaker 4: new kids out of college and so on. But because

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Speaker 4: there's so much output growth and income growth, that's the

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Speaker 4: kind of thing that you know, a free market will

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Speaker 4: work out relatively quickly. As you know, new ways to

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Speaker 4: spend money emerge.

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Speaker 1: Free mark's going to figure it out, don't worry about it. Well,

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Speaker 1: you know, it's one of those where I keep saying this,

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Speaker 1: The Biden vibes on this are just so out of control.

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Speaker 1: Like what they keep doing is they post charts, they

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Speaker 1: say the economy is historically better than ever. If it

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Speaker 1: is bad, it's always somebody else's fault. And if you

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Speaker 1: know to the extent it is somebody else's fault, we're

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Speaker 1: also we're not going to do anything about somebody else's fault, right,

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Speaker 1: so you can't. This is one of those where with

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Speaker 1: AI they just continue to basically think that yes, it

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Speaker 1: will shake out. It's free market creative destruction, the libertarian's

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Speaker 1: favorite word whenever it comes to this, And you know,

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Speaker 1: maybe there is something to that. But part of what

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Speaker 1: is so distressing and we're going to talk about with

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Speaker 1: the AI twenty twenty seven plan is basically they keep

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Speaker 1: saying stuff out loud like none of you are going

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Speaker 1: to work in five years, and the government is just

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Speaker 1: completely just letting it go. Just this morning, House Republicans

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Speaker 1: are apparently scheming to try and put some language in

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Speaker 1: that will block all states from regulating AIS any individual state.

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Speaker 1: Remember this, They previously tried to pass this gambit and

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Speaker 1: there was a pushback against it, and I'm increasingly just thinking, like, look, look,

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Speaker 1: I'm sorry, Like we have to have democratic check whenever

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Speaker 1: it comes to our relationship with this technology, when billions

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Speaker 1: of us are going to use it, and you out

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Speaker 1: in your own words, if we take you seriously, it's

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Speaker 1: going to cause mass layoffs, It's going to disrupt every

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Speaker 1: facet of our society. It's just too important to leave

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Speaker 1: in the hands of Sam Altman. I don't trust him,

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Speaker 1: and I don't think anybody.

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Speaker 2: Else should oh or anyone anyone or literally anyone else.

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Speaker 2: I mean, so, I actually been thinking a lot about

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Speaker 2: this this week, and increasingly obviously.

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Speaker 3: There's a lot going on with the Trumpeters.

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Speaker 2: There's you know, Ebstein files, there's the big beautiful Bill,

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Speaker 2: there's Venezuela, there's the Ice deployments. There's a lot of

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Speaker 2: shit going on with the Trump administration. I'm increasingly feeling

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Speaker 2: like the AI push is actually the main event, is

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Speaker 2: like the main done just in terms of the consequences

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Speaker 2: of it that I've already been convinced of, but that

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Speaker 2: you know, in Trump's campaign, you'll recall you had, first

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Speaker 2: of all, him flip his position on a bunch of issues,

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Speaker 2: including crypto in order.

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Speaker 3: To please these tech oligarchs.

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Speaker 2: You had a bunch of these tech guys who previously

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Speaker 2: we like more or less Democrats or voting for Democrats,

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Speaker 2: supporting Democrats, flip their support to Trump. You had Elon

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Speaker 2: Musk himself coming in with what two hundred and fifty

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Speaker 2: million dollars plus and taking an extremely aggressive, active role

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Speaker 2: in the campaign, being influential in who Trump picked as

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Speaker 2: his VP. And then what happens as soon as he

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Speaker 2: comes into office. First of all, you guys will remember

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Speaker 2: the images from the inauguration where he's surrounded by all

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Speaker 2: of these tech barons. A striking image and a striking

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Speaker 2: portrait of what was to come. In that initial batch

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Speaker 2: of executive orders, you remember there was a whole slew

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Speaker 2: of them, so it was somewhat lost. But immediately what

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Speaker 2: he did was to roll back any of the safety

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Speaker 2: guardrails that have been put in place by the Biden administration.

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Speaker 2: The whole push of this administration has been to completely

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Speaker 2: deregulate the tech industry, I mean regulation in general, but

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Speaker 2: specifically the tech industry, and make it so that it

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Speaker 2: was completely.

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Speaker 3: Off to the races.

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Speaker 2: With this AI tech development with no breaks on the car.

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Speaker 2: We had multiple press conferences with these guys. You see

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Speaker 2: them at dinners with these guys. This is the central

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Speaker 2: piece that this Trump administration really is about. They're placing

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Speaker 2: this bet that number one, we can beat China to

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Speaker 2: ag artificial general intelligence, and that number two, it's going

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Speaker 2: to magically solve more problems than it creates. When if

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Speaker 2: you actually listen to the researchers of one of them

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Speaker 2: we're going to talk to you today. If you listen

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Speaker 2: to even guys like Sam Altman or Mark Zuckerberg, who's

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Speaker 2: one of the least responsible actors actually in all of this,

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Speaker 2: you listen to Elon Musk, they'll tell you we are

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Speaker 2: planning to replace at the very least tens of millions

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Speaker 2: of jobs with robots, like we are planning to make

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Speaker 2: you irrelevant. This is already happening. We covered how Amazon

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Speaker 2: their plans to eliminate half a million jobs were leaked.

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Speaker 2: The New York Times got their hands on it. They're

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Speaker 2: already implementing this. There is a warehouse down I believe

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Speaker 2: in Shrapeport, Louisiana, where is largely robots already. So this

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Speaker 2: is happening now. This clip from Kevin Hassett is so significant.

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Speaker 2: I think, as far as I know, this is the

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Speaker 2: first time the White House is acknowledging that that labor

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Speaker 2: displacement is already happening. Now it's happening exactly the places

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Speaker 2: you would expect, with coders and with new employees coming

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Speaker 2: out of college, so that those entry level jobs are

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Speaker 2: being destroyed. People cannot get their foot on the ladder

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Speaker 2: that is where it starts.

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Speaker 3: But they have much bigger goals.

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Speaker 2: So when he says, oh, it's just a quiet time

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Speaker 2: and plays it down and frames it actually soger like

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Speaker 2: this is some plus. Oh, they're just you know, these

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Speaker 2: companies are getting more productive. It's a good thing actually

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Speaker 2: that we're displacing all these workers and there's going to

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Speaker 2: be a spike in unemployment and young kids coming out

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Speaker 2: of college are not going to have jobs to go to.

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Speaker 3: That's how he's framing it.

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Speaker 2: That's how they're thinking about it, and that's how these

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Speaker 2: companies are thinking about it too, which is why they

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Speaker 2: all go out and brag as much as possible about

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Speaker 2: all the layoffs that they're doing.

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Speaker 1: Yeah, I mean, you know, to think it back. Actually,

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Speaker 1: if you even roll the tape of our inauguration coverage.

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Speaker 1: What we said is if you roll back, you know

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Speaker 1: you will offer You may think that the most significant

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Speaker 1: thing that happened in the Trump administration was AI. You know,

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Speaker 1: considering all those tech CEOs, which we literally said on

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Speaker 1: the day he was inaugurated with that picture, AI regulation

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Speaker 1: and all of that has also just been a morass.

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Speaker 1: You know you're talking about AIS. I did a few

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Speaker 1: monologues about it at the time. Unfortunately, the Biden rules,

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Speaker 1: in my opinion, would have basically just crystallized too big

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Speaker 1: to fail. With a lot of the open AI and others.

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Speaker 1: At that time there was a little bit more of

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Speaker 1: a hope for an open source direction. The Trump administration

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Speaker 1: has abandoned even the Biden administration's effective commitment to op

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Speaker 1: too big to fail and to regulation because what they've

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Speaker 1: done they need the AI companies to continue to investing

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Speaker 1: in our economy. If they do stop building these data centers.

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Speaker 1: We are in an official recession.

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Speaker 3: Now.

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Speaker 1: We're going to get to some data that already shows

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Speaker 1: some recessionary impact. But the issue is the stock market

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Speaker 1: and GDP is entirely reliant on these AI gains. That's

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Speaker 1: part of the reason they'reletting them let fly because they're like, look,

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Speaker 1: without this, we're screwed. I mean, you go to talk

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Speaker 1: about tariffs and all this other stuff, the discussion is

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Speaker 1: totally different without a lot of these AI companies, And

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Speaker 1: in general, you're actually seeing recession and inflation problems that

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Speaker 1: are bubbling up everywhere. Consumers are more miserable than ever before,

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Speaker 1: literally rock bottom sentiment, and of course the same type

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Speaker 1: of Biden administration stuff trying to tell consumers that they're wrong,

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Speaker 1: like they're not wrong, they're empirically correct when it comes

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Speaker 1: to grocery prices, housing, basic cost of living, health insurance,

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Speaker 1: all the stuff that we cover here on a day

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Speaker 1: to day basis, And the administration is doing the same thing,

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Speaker 1: trying to blame other people. In fact, frankly, they're just

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Speaker 1: doing it an even dumber and more low IQ way.

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Speaker 1: Here with Scott Bessen for his explanation on beef Maria.

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Speaker 5: The beef market is a very specialized market. It goes

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Speaker 5: in long cycles, and that this is the perfect storm

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Speaker 5: again something we inherited. And there's also because of the

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Speaker 5: mass immigration, a disease that had been we've been rid

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Speaker 5: of in North America made its way up through South

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Speaker 5: America as these migrants, they have brought some of their

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Speaker 5: cattle with them. So part of the problem is we've

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Speaker 5: had to shut the border to Mexican beef because of

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Speaker 5: this disease called the screw worms, So we're not going

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Speaker 5: to let that get into our supply chain.

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Speaker 1: So yeah, the explanation is that some of these people

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Speaker 1: have brought the cows with them and that that's the

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Speaker 1: disease that is spreading me so well, you know, I checked,

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Speaker 1: by the way, I did check on that. What he's

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Speaker 1: alleging is something called bovine sponge ofform and cephalopathy. But

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Speaker 1: from what we see on the CDC website and others,

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Speaker 1: it is not necessarily because people are bringing cattle over

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Speaker 1: the border with them. But regardless, you know, actually just

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Speaker 1: heard from somebody yesterday and others like beef prices in

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Speaker 1: terms of sticker shock at the grocery store are ones

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Speaker 1: where people are paying a lot of attention. But I

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Speaker 1: increasingly buy the housing theory of everything, and when you

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Speaker 1: buy that and you look at the data, it's just

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Speaker 1: a disaster, not only in terms of home prices and rates.

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Speaker 1: But put this next one, please up on the screen.

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Speaker 1: New Flora closures have now jumped some twenty percent in October,

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Speaker 1: a sign of more distress in the housing market. Foreclosure starts.

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Speaker 1: That's the initial phase of the process rose six percent

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Speaker 1: for the month, and we're twenty percent higher than the

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Speaker 1: year before. Completed foreclosures the final phase are up thirty

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Speaker 1: two percent year over year. Florida, South Carolina in Illinois

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Speaker 1: leading the state in Florida in foreclosures. They say that

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Speaker 1: some thirty six thousand US properties with some type of

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Speaker 1: foreclosure in October, such as default notices and others. That's

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Speaker 1: twenty percent higher than the year prior. I mean, there's

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Speaker 1: a lot of potential reasons for that. Usually it's just

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Speaker 1: that people's household balance sheet and debt, which we've also

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Speaker 1: been covering here now for years. It does eventually catch

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Speaker 1: up if you're unable to make those mortgage payments. Also,

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Speaker 1: potentially the government shutdown. Who knows how many of them

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Speaker 1: were workers and others who are already behind on their

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Speaker 1: bills and they just got a final final screw turning

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Speaker 1: in there. So we don't know exactly what the reason is,

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Speaker 1: but you know, if you lived through seven, you don't

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Speaker 1: want to be seeing headlines like this. You just don't

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Speaker 1: want to see it period, right. You want people to

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Speaker 1: have enough money that they're at the very least they

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Speaker 1: can make their kind of monthly bills. And right now

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Speaker 1: with inflation at the grocery store, with housing, with rates

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Speaker 1: and others, it just feels more unattainable than ever before.

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Speaker 1: Especially and it's not about feeling. You can look at

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Speaker 1: credit card balances, wages flat for over the last couple

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Speaker 1: of years, and you can say it's pretty obvious where

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Speaker 1: things are right now.

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Speaker 2: Yeah, I just saw this from CNBC as well. It's

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Speaker 2: the corollary to what you're saying about home foreclosures. Home

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Speaker 2: Depot is cutting their earnings outlook as home improvement demand

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Speaker 2: falls short of expectations. Apparently, they missed their third quarter

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Speaker 2: earning estimates. That's their third straight miss. They cut their

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Speaker 2: full year profit outlook. The company said slow consumer spending

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Speaker 2: and a weaker housing market have made home improvement demand

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Speaker 2: worse than it expected. So you can see indications of

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Speaker 2: those ut youwhere yeah.

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Speaker 1: You can see it in that debt. And then also

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Speaker 1: so because AI is the single bet, then you also

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Speaker 1: start to have to pay attention to some of these

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Speaker 1: people who are you know, exiting their position. There was

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Speaker 1: a huge one News yesterday showed let's put this up

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Speaker 1: here on the screen A four. Peter Teal's hedge fund

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Speaker 1: has now dumped his entire Endvidia stock and has cut

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Speaker 1: back even on the Tesla position. I mean, it's one

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Speaker 1: of those where people obviously are trading and all of

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Speaker 1: that all the time, but in general when you look

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Speaker 1: at the people who are exiting and now starting to

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Speaker 1: call the top. Let's say, on Nvidia, you had Michael Burry,

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Speaker 1: the famed big short investor. Again it's always the caveat

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Speaker 1: he has called many since the big short and he

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Speaker 1: was incorrect. But he is staking out a big position

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Speaker 1: against an Nvidia and Palenteer. But here what you see

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Speaker 1: is that they sold some five hundred and thirty seven

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Speaker 1: thousand shares in Nvidia. The steak would have been worth

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Speaker 1: about one hundred million dollars, so the company's closed price

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Speaker 1: on September thirtieth. This Teal sell off, coupled with Soft

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Speaker 1: Banks sell off of its own n Video holdings last week,

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Speaker 1: has fueled Wall Street's angst that the frenzy driving these

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Speaker 1: sorts may have peaked, putting at risk the trillions of

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Speaker 1: dollars that are committing to AI advancement. Investors and analysts

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Speaker 1: still looking to the third quarter results are reported tomorrow

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Speaker 1: to dispel worries of a bubble. At the same time,

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Speaker 1: this I actually found kind of fascinating in myriad ways.

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Speaker 1: Put a five here on the screen. So the founder

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Speaker 1: of Klarna, he's the Swedish billionaire. Now, if you don't

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Speaker 1: know what Klarna is, it's one of those buy now,

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Speaker 1: pay later apps. So a guy who became a billionaire

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Speaker 1: by founding a company which has basically saddled people with

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Speaker 1: hundreds of billions of dollars in buy now, pay later debt.

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Speaker 1: So's you could call him a debt billionaire. I think

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Speaker 1: that's too fair. Now, says I'm nervous about all of

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Speaker 1: this AI debt spending. Seems to me he's an expert

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Speaker 1: in debt. That just me personally like the guy who

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Speaker 1: literally created a novel way of debt in the twenty twenties,

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Speaker 1: which that takes skill. I wouldn't say it's moral or anything,

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Speaker 1: but takes skills, certainly to try and extract more money

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Speaker 1: out of the consumer economy. In the twenty twenties, this

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Speaker 1: guy says, I'm nervous about the trillions of dollars of

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Speaker 1: spending on AI. He says the tech industry is committing

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Speaker 1: too much money to huge computing infrastructure. He is a

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Speaker 1: shareholder in open Ai, Perplexity xai service through his family office.

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Speaker 1: He told The Financial Times that huge sums being poured

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Speaker 1: making nervous. I think open Ai can be very successful

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Speaker 1: at a company, but at the same time, I'm very

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Speaker 1: nervous about the size of these investments in data centers.

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Speaker 1: That's a particular thing that I am concerned about. He

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Speaker 1: himself calls himself an AI evangelist, and he says an

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Speaker 1: AI chatbot already handles two thirds of his customers services

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Speaker 1: and inquiries over at Klarna. Now what he's pointing to, though,

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Speaker 1: I we keep hammering this home on the show open

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Speaker 1: Ai and Perplexity. In all these places they make money.

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Speaker 1: No one's saying they don't make any money. They actually

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Speaker 1: make a lot of money. But they have so much

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Speaker 1: the door that in terms of commitments that open ai itself,

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Speaker 1: it's current projected loss in twenty twenty eight is seventy

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Speaker 1: eight billion. Seventy eight billion dollars of losses just in

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Speaker 1: twenty twenty eight and a trillion dollars in spending commitments

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Speaker 1: just for that one company that doesn't even factor in

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Speaker 1: Xai perplex all of these other data center commitments. So

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Speaker 1: if you have even a marginal crawl back to reality,

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Speaker 1: that is a crash for our economy and for our GDP.

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Speaker 1: That's the problem. And I mean, look, enough people are

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Speaker 1: saying it at this point. I don't even really think

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Speaker 1: you could call it a black Swan event. It's one

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Speaker 1: of the more predictable things there are. Obvious business cycle

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Speaker 1: is one of those things they teach you and like

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Speaker 1: econ one oh one, and everyone's just kind of on

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Speaker 1: pins and needles waiting for it to happen. But Wall

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Speaker 1: Street's irrational exuberance. Also, it doesn't seem to be fading.

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Speaker 1: There's still billions of dollars being poured into this, so

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Speaker 1: really nobody knows, like you could be, you know, it's

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Speaker 1: you could either be a person who is you know,

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Speaker 1: crying wolf or something like that. Like, nobody is exactly clear.

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Speaker 1: Nobody wants to miss out on the gains. But the richest,

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Speaker 1: some of the richest fund managers in the world, they're

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Speaker 1: taking profit they're selling and they're saying, hey, that's enough,

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Speaker 1: We're going to take the cash. Yeah, what it is

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Speaker 1: that makes me very nervous.

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Speaker 2: A lot of the logic of it is people don't

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Speaker 2: want to be left on the sidelines because think of

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Speaker 2: what has been advertised as the end state of AI

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Speaker 2: is one of these companies is going to reach AGI

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Speaker 2: and that's going to change everything and the you know,

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Speaker 2: the company and the founders or the CEO, the executives,

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Speaker 2: whoever's in charge at that time that are you know,

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Speaker 2: in charge of that company. When they achieve AGI, not

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Speaker 2: only are they going to become tremendously wealthy, they're also

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Speaker 2: going to become tremendously powerful, like tremendously powerful in a

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Speaker 2: way that has never we've never seen before in the

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Speaker 2: history of the planet type of powerful if the promise

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Speaker 2: lives up to what they're holding out.

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Speaker 3: So, yeah, these guys who.

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Speaker 2: Are megalomaniacs want to make sure that they are have

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Speaker 2: a stake in the winning team when that it all

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Speaker 2: comes to pass. Now it's possible, it never does come

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Speaker 2: to pass. Our guest today will say, you know, he

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Speaker 2: thinks it is he believes that they are going to

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Speaker 2: get to that point, but it's possible they never do

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Speaker 2: get to that point, that it stays sort of in

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Speaker 2: the realm of what it is now, which is still

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Speaker 2: causing a lot of havoc and displacement and a lot

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Speaker 2: of significant consequences, a quiet time in the labor market,

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Speaker 2: as Kevin has to put it. But it's possibly, you know,

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Speaker 2: that's the sort of thing like we could as a

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Speaker 2: society sort of metabolize and deal with with, you know,

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Speaker 2: significant pain, but we could deal with over time. They

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Speaker 2: don't want to be left out of the big seismic

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Speaker 2: revolution that they think is possible here with AI. So

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Speaker 2: that's why even as everybody knows that this is a

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Speaker 2: bubble in some sense, but why the money is going

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Speaker 2: to continue to pour in is because of that dynamic.

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Speaker 2: The last piece we have here is you know, getting

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Speaker 2: back to the nuts and bolts of people's lives, and

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Speaker 2: obviously the data center buildoun has a huge impact on

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Speaker 2: that as well. Republicans increasingly blamed for poor economic conditions.

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Speaker 2: We can put a six up on the screen. This

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Speaker 2: This is an area where Republicans traditionally have an advantage

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Speaker 2: on the economy. Trump specifically has had a major advantage

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Speaker 2: on the economy that's been his consistent strength up until

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Speaker 2: this term, and now according to this NRCC polster. So,

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Speaker 2: this is a Republican polster for the first time in

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Speaker 2: two years, voters whose top priorities inflation and the economy

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Speaker 2: now prefer a generic Democrat for Congress by thirteen points

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Speaker 2: over a Republican. And I'm not sure if it was

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Speaker 2: by this polster or a separate one they pulled specifically

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Speaker 2: on Okay, who do you blame for healthcare price increases? Overwhelmingly?

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Speaker 2: People said the GOP. Who do you blame for electric

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Speaker 2: bill increases? Overwhelmingly? People said the GOP. So if you

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Speaker 2: want to know why the election was so incredibly lopsided

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Speaker 2: this year, and why I think Republicans are had to

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Speaker 2: for yet another significant reckoning in the midterm elections, you'd

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Speaker 2: be hard pressed to find a better explanation than this one.

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Speaker 1: Yeah, no, I mean the economy. Look, people always blame

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Speaker 1: the party in power. That's what Biden was blamed for

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Speaker 1: four years. And as I said four years ago, almost

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Speaker 1: to the day, you have to be appear as if

435
00:21:05,800 --> 00:21:09,040
Speaker 1: you're doing something about it, as if you care about it,

436
00:21:09,080 --> 00:21:11,480
Speaker 1: and instead you know you're blocked. It's that's why the

437
00:21:11,480 --> 00:21:15,439
Speaker 1: epscene thing is important, because you're blocking that while also

438
00:21:15,680 --> 00:21:19,760
Speaker 1: seemingly not doing much for me and obsessing over your

439
00:21:19,760 --> 00:21:22,920
Speaker 1: own personal quest to get the Nobel Peace Prize because

440
00:21:22,960 --> 00:21:26,640
Speaker 1: you've ended ninety wars now or whatever. At this point,

441
00:21:26,720 --> 00:21:29,920
Speaker 1: right the Democratic Republic, everyone is celebrating, of course, the

442
00:21:30,040 --> 00:21:33,439
Speaker 1: end of potential end or whatever of that conflict. But

443
00:21:34,000 --> 00:21:36,760
Speaker 1: that stuff, you know, the narcissism and all that, people

444
00:21:36,760 --> 00:21:39,399
Speaker 1: can deal with a lot as long as thing or

445
00:21:39,680 --> 00:21:42,800
Speaker 1: economy is doing well. The classic bumper sticker of the

446
00:21:42,840 --> 00:21:45,199
Speaker 1: Trump era or the Biden era was could use some

447
00:21:45,280 --> 00:21:47,679
Speaker 1: mean tweets right now as long as the gas was

448
00:21:47,960 --> 00:21:50,399
Speaker 1: two dollars. And it's like, well, the whole point beyond

449
00:21:50,440 --> 00:21:53,360
Speaker 1: that is I don't care about the personal conduct or whatever,

450
00:21:53,480 --> 00:21:56,400
Speaker 1: as long as things are going well in my life.

451
00:21:56,400 --> 00:21:58,480
Speaker 1: And it's like, well things aren't going well in your life, well,

452
00:21:58,560 --> 00:22:01,200
Speaker 1: then that stuff actually all really does start to matter.

453
00:22:01,320 --> 00:22:04,280
Speaker 1: That seems to be the overall endpoint for a lot

454
00:22:04,280 --> 00:22:05,879
Speaker 1: of this. And look, I don't know, I mean, you know,

455
00:22:05,960 --> 00:22:08,199
Speaker 1: you don't want to read too much into a single

456
00:22:08,280 --> 00:22:11,520
Speaker 1: day movements, but there's just been like slow kind of

457
00:22:11,560 --> 00:22:14,000
Speaker 1: movements in the s and P five hundred. There was one.

458
00:22:14,080 --> 00:22:15,760
Speaker 3: Yesterday, there was a drop morning.

459
00:22:15,840 --> 00:22:18,320
Speaker 1: Futures are down again this morning, we're not. You know,

460
00:22:18,440 --> 00:22:21,880
Speaker 1: things can change literally on a dime here, but Federal

461
00:22:21,920 --> 00:22:23,600
Speaker 1: Reserve doesn't look like it's going to step in and

462
00:22:23,640 --> 00:22:28,359
Speaker 1: do anything drastic anytime soon, right, So things generally seem

463
00:22:28,440 --> 00:22:31,639
Speaker 1: to be in stasis for now, and stasis is trending

464
00:22:31,640 --> 00:22:34,240
Speaker 1: in a down direction. If you look at house balance sheet,

465
00:22:34,440 --> 00:22:38,640
Speaker 1: housing and more, nobody is planning anything radically to save you.

466
00:22:38,720 --> 00:22:41,480
Speaker 1: In fact, they're probably planning something radical in the opposite direction,

467
00:22:41,480 --> 00:22:43,879
Speaker 1: which I'll get to it in property tax bit like.

468
00:22:44,200 --> 00:22:46,800
Speaker 1: If anything, the people who are at the top of

469
00:22:46,880 --> 00:22:49,480
Speaker 1: the status quo are doing everything they possibly can to

470
00:22:49,560 --> 00:22:52,200
Speaker 1: preserve said status quo, and in a way, I think

471
00:22:52,200 --> 00:22:56,359
Speaker 1: there they are girding themselves for a potential crash to

472
00:22:56,520 --> 00:22:59,840
Speaker 1: insulate them from any potential chaos and make it so

473
00:22:59,880 --> 00:23:02,880
Speaker 1: the younger people and the new generation will not only

474
00:23:02,920 --> 00:23:05,199
Speaker 1: bear the entire brunt, but will be the ones who

475
00:23:05,240 --> 00:23:07,880
Speaker 1: are totally screwed. Yeah, while they're completely.

476
00:23:07,440 --> 00:23:08,400
Speaker 3: Safe, I mean it's work.

477
00:23:08,440 --> 00:23:10,560
Speaker 2: When you think about the AI aspect, it's much worse

478
00:23:10,600 --> 00:23:13,160
Speaker 2: than the status quo because they're actively planning and celebrating

479
00:23:13,160 --> 00:23:14,119
Speaker 2: feeding you to the wolves.

480
00:23:14,200 --> 00:23:15,040
Speaker 3: I mean, that's what Kevin.

481
00:23:15,119 --> 00:23:17,200
Speaker 2: Kevin has it is saying, it's like, oh, it's great

482
00:23:17,320 --> 00:23:19,440
Speaker 2: that these they don't have to hire these kids out

483
00:23:19,440 --> 00:23:23,280
Speaker 2: in college anymore. That's that's great. It's improved productivity. That

484
00:23:23,440 --> 00:23:26,239
Speaker 2: is their goal. Like their goal is to make it

485
00:23:26,280 --> 00:23:29,760
Speaker 2: so that you are irrelevant. Your labor is relevant, like

486
00:23:29,800 --> 00:23:32,640
Speaker 2: forget about chief labor. They want no labor. They want,

487
00:23:32,680 --> 00:23:34,680
Speaker 2: you know, to hand as much off to the robots

488
00:23:34,680 --> 00:23:39,080
Speaker 2: as they possibly can. That's their goal. That's the stated

489
00:23:39,160 --> 00:23:42,399
Speaker 2: goal of all of these tech executives. That's you know,

490
00:23:42,400 --> 00:23:44,440
Speaker 2: when you want to ask yourself the question, Okay, these

491
00:23:44,480 --> 00:23:48,119
Speaker 2: trillion dollar you know spend that open Ai has planned,

492
00:23:48,160 --> 00:23:51,320
Speaker 2: and these other companies you know somewhere similar ballpark figures.

493
00:23:51,000 --> 00:23:53,240
Speaker 3: As well, how are they going to make that money.

494
00:23:53,480 --> 00:23:55,760
Speaker 2: It's not going to come from you and me signing

495
00:23:55,840 --> 00:23:58,600
Speaker 2: up for you know, a chat GPT subscription. No, it's

496
00:23:58,640 --> 00:24:01,439
Speaker 2: going to come from giant companies who are willing to

497
00:24:01,480 --> 00:24:04,080
Speaker 2: pay large sums of money to get rid of you,

498
00:24:04,720 --> 00:24:07,480
Speaker 2: to get rid of your labor. That is what they're

499
00:24:07,480 --> 00:24:10,600
Speaker 2: betting on, and that's what this administration has gone whole

500
00:24:10,720 --> 00:24:13,440
Speaker 2: hog behind. This is a central driving force, if not

501
00:24:13,640 --> 00:24:16,480
Speaker 2: the driving force, of this administration. That's why these guys

502
00:24:16,520 --> 00:24:18,359
Speaker 2: gave Trump so much money, That's why they did so

503
00:24:18,440 --> 00:24:20,800
Speaker 2: much for him for his election. You know, they're also

504
00:24:21,000 --> 00:24:23,720
Speaker 2: sort of directly involved in the massive amount of wealth

505
00:24:23,760 --> 00:24:25,240
Speaker 2: that he's accumulated.

506
00:24:24,680 --> 00:24:25,960
Speaker 3: Through his crypto scam.

507
00:24:26,320 --> 00:24:29,720
Speaker 2: Like this is the play, and so you know when

508
00:24:29,800 --> 00:24:33,000
Speaker 2: Kevin has it comes down, it is openly celebrating and

509
00:24:33,160 --> 00:24:39,040
Speaker 2: justifying significant layoffs and lack of hiring because of AI development.

510
00:24:39,200 --> 00:24:41,040
Speaker 3: Everyone needs to pay attention.

511
00:24:40,680 --> 00:24:43,639
Speaker 2: To what their actual goals are and the way that

512
00:24:43,720 --> 00:24:46,800
Speaker 2: they are using policy and executive orders and funding and

513
00:24:46,840 --> 00:24:49,959
Speaker 2: financing and relationships to build this whole thing out. And

514
00:24:50,000 --> 00:24:51,560
Speaker 2: thank you for the flag about that they're trying to

515
00:24:51,600 --> 00:24:54,399
Speaker 2: do this thing again. Of the States can't regulate AI,

516
00:24:54,480 --> 00:24:58,040
Speaker 2: which is absolutely insane, and everything he needs the rooftops

517
00:24:58,040 --> 00:24:58,359
Speaker 2: about this.

518
00:24:58,480 --> 00:25:01,359
Speaker 1: That's why I'm not I'm not exactly sold on the

519
00:25:01,400 --> 00:25:04,200
Speaker 1: master Plan because I don't think it is I genuinely

520
00:25:04,200 --> 00:25:07,760
Speaker 1: think it is an absolute alliance of convenience and of stupidity.

521
00:25:07,760 --> 00:25:10,480
Speaker 1: Republicans are dumb, and they like money, right, and they

522
00:25:10,520 --> 00:25:14,159
Speaker 1: want job creators or whatever. Now Elon and all the

523
00:25:14,200 --> 00:25:16,480
Speaker 1: rest of these people, no question, Okay, of course they're

524
00:25:16,560 --> 00:25:18,520
Speaker 1: sucking up to Trump to try and get as much

525
00:25:18,560 --> 00:25:19,800
Speaker 1: out of it. A lot of is to try off

526
00:25:19,960 --> 00:25:23,000
Speaker 1: hold off regulation and basically to convince them that they're

527
00:25:23,000 --> 00:25:25,560
Speaker 1: the single driving enging of the economy. And I think

528
00:25:25,560 --> 00:25:28,560
Speaker 1: that is true. It also aligns with their overall posture

529
00:25:28,600 --> 00:25:32,639
Speaker 1: towards deregulation itself, because that's something like built into the

530
00:25:32,680 --> 00:25:35,840
Speaker 1: Republican psyche. What they mostly want is to be left alone.

531
00:25:35,880 --> 00:25:39,280
Speaker 1: I think that's bad. I mean, especially Sam Altman and

532
00:25:39,320 --> 00:25:43,159
Speaker 1: Mark Zuckerberg and Dario. I mean Dario, he just goes

533
00:25:43,320 --> 00:25:44,960
Speaker 1: on TV and he's like, none of you are gonna

534
00:25:44,960 --> 00:25:46,879
Speaker 1: be working in five years, and everyone's just supposed to

535
00:25:46,880 --> 00:25:49,720
Speaker 1: accept that as they're like, oh, okay, got it right.

536
00:25:49,800 --> 00:25:52,320
Speaker 1: I mean, they genuinely act as if they're going to

537
00:25:52,359 --> 00:25:56,439
Speaker 1: face no consequences, and so yeah, I mean, I just

538
00:25:56,480 --> 00:25:56,760
Speaker 1: to be.

539
00:25:56,760 --> 00:25:59,360
Speaker 2: Clear, I don't think Trump gives a shit about any

540
00:25:59,400 --> 00:26:02,080
Speaker 2: of it at all, Like he cares about the stock

541
00:26:02,119 --> 00:26:05,000
Speaker 2: market keeps going on. But you know, I think he

542
00:26:05,040 --> 00:26:07,320
Speaker 2: wanted to stay on prison and get back in the

543
00:26:07,320 --> 00:26:10,320
Speaker 2: White House, and these guys were willing to throw tons

544
00:26:10,359 --> 00:26:13,119
Speaker 2: of cash at him, and he's checked out of this

545
00:26:13,200 --> 00:26:17,000
Speaker 2: administration handed off significant chunks of it to other aids,

546
00:26:17,080 --> 00:26:19,720
Speaker 2: whether it's you know, Steven Miller, Mark Rubio or whoever.

547
00:26:20,119 --> 00:26:22,679
Speaker 2: And so yeah, I'm not saying like that he's a

548
00:26:22,720 --> 00:26:25,680
Speaker 2: devoted AI acolyte. I don't think he gives a shit.

549
00:26:25,960 --> 00:26:27,800
Speaker 2: But I think he's turned this whole part of his

550
00:26:27,840 --> 00:26:32,040
Speaker 2: administration over to these tech oligarchs and basically sold his presidency,

551
00:26:32,080 --> 00:26:35,000
Speaker 2: this aspect of his presidency, to them, and they're going

552
00:26:35,080 --> 00:26:37,240
Speaker 2: to get whatever they want from him. I mean the

553
00:26:37,440 --> 00:26:40,399
Speaker 2: H one B conversations like fits in that right. And

554
00:26:40,480 --> 00:26:42,560
Speaker 2: you you flagged at the time when he went on

555
00:26:42,600 --> 00:26:44,520
Speaker 2: the All In podcast during the campaign and was like,

556
00:26:44,520 --> 00:26:49,119
Speaker 2: I'm gonna staple the visas to the diploma, and you

557
00:26:49,160 --> 00:26:51,720
Speaker 2: were like, what how does this fit with the other

558
00:26:51,760 --> 00:26:53,960
Speaker 2: things that he said. Now, listen, you guys, you know

559
00:26:54,000 --> 00:26:56,639
Speaker 2: I'm pro immigrant. I am also pro major reform of

560
00:26:56,680 --> 00:26:59,639
Speaker 2: the H one B program, which is genuinely exploitative and

561
00:27:00,040 --> 00:27:03,919
Speaker 2: undercuts does undercut native tech workers as well. So for

562
00:27:04,040 --> 00:27:05,840
Speaker 2: him to come out now and be like, I want

563
00:27:05,880 --> 00:27:10,360
Speaker 2: six hundred thousand Chinese students in our universities and I'm

564
00:27:10,400 --> 00:27:14,600
Speaker 2: still pro h one. B Ask yourself the question, why

565
00:27:14,640 --> 00:27:17,400
Speaker 2: are these two things so dissonant from the other things

566
00:27:17,400 --> 00:27:19,800
Speaker 2: that he said on the campaign trail, And it's because

567
00:27:19,840 --> 00:27:22,520
Speaker 2: it's what these tech oligarchs want. He's going to do

568
00:27:22,680 --> 00:27:25,120
Speaker 2: whatever it is that they want. He sold this part

569
00:27:25,119 --> 00:27:28,000
Speaker 2: of his presidency to him, to them, to me. That's

570
00:27:28,040 --> 00:27:31,840
Speaker 2: just like abundantly clear. And those answers to Laura Ingram

571
00:27:31,920 --> 00:27:35,040
Speaker 2: are just one example, one, you know, small but significant

572
00:27:35,119 --> 00:27:39,320
Speaker 2: example of the way that he has outsourced this whole

573
00:27:39,359 --> 00:27:42,760
Speaker 2: part of his presidency, which is unbelievably important to literally

574
00:27:42,840 --> 00:27:45,879
Speaker 2: all of us, to the worst people in the world.

575
00:27:46,080 --> 00:27:48,920
Speaker 1: Yeah, I mean, well, they seem uncowed and they definitely

576
00:27:48,920 --> 00:27:50,800
Speaker 1: seem to have a lot of power, which is part

577
00:27:50,920 --> 00:27:56,120
Speaker 1: of the problem. Speaking worst people in the world, what's

578
00:27:56,160 --> 00:27:57,320
Speaker 1: going on with larious?

579
00:27:57,440 --> 00:28:01,000
Speaker 2: Right, So, Larry Summers, former Chargery secretary, has been basically

580
00:28:01,160 --> 00:28:04,680
Speaker 2: the scene of every great economic crime in our recent past,

581
00:28:04,720 --> 00:28:07,400
Speaker 2: whether it's a bank balance, whether it's NAFTA. You could

582
00:28:07,440 --> 00:28:10,800
Speaker 2: go on and on with him, continues to have tons

583
00:28:10,800 --> 00:28:14,840
Speaker 2: of influence for unknowable reasons within the Democratic Party and

584
00:28:15,200 --> 00:28:18,040
Speaker 2: was part of this Center for American Progress, pushed to

585
00:28:18,080 --> 00:28:20,000
Speaker 2: create their own, you know, they were like, oh, the

586
00:28:20,000 --> 00:28:22,159
Speaker 2: Republicans did Project twenty twenty five, We're going to do

587
00:28:22,280 --> 00:28:25,880
Speaker 2: Project twenty twenty nine. So he was very influential part

588
00:28:25,920 --> 00:28:28,679
Speaker 2: of this development within Center for American Progress of the

589
00:28:28,760 --> 00:28:32,480
Speaker 2: economic plank of Project twenty twenty nine, which is terrible,

590
00:28:32,520 --> 00:28:34,880
Speaker 2: and it's part of the Centrists and the corporatists trying

591
00:28:34,920 --> 00:28:37,680
Speaker 2: to keep a hold on the Democratic Party even as

592
00:28:37,680 --> 00:28:40,360
Speaker 2: the base revolt against them. And Zorn m Donnie is

593
00:28:40,360 --> 00:28:43,280
Speaker 2: the most popular figure in the Democratic Party. So lo

594
00:28:43,440 --> 00:28:46,600
Speaker 2: and behold, this isn't a big surprise. We knew Larry

595
00:28:46,640 --> 00:28:49,920
Speaker 2: Summers had a significant relationship with Jeffrey Epstein, which he

596
00:28:50,040 --> 00:28:52,720
Speaker 2: apologized for in the past. But this man is all

597
00:28:52,760 --> 00:28:55,680
Speaker 2: over the Epstein emails that just came out. One of

598
00:28:55,680 --> 00:28:58,440
Speaker 2: the central characters. Trump is mentioned a lot more, but

599
00:28:58,520 --> 00:29:01,400
Speaker 2: Larry Summers is mentioned a lot. And we have direct emails.

600
00:29:01,600 --> 00:29:04,680
Speaker 2: Unlike with Trump, we have direct emails between Larry Summers

601
00:29:05,040 --> 00:29:07,960
Speaker 2: and Jeffrey Epstein that come out of this and they

602
00:29:08,000 --> 00:29:10,840
Speaker 2: I'll show you some of them. They're pretty wild, the

603
00:29:10,880 --> 00:29:14,480
Speaker 2: sort he was getting like relationship advice to chase after

604
00:29:14,800 --> 00:29:16,360
Speaker 2: some lady while he's married.

605
00:29:16,400 --> 00:29:18,680
Speaker 3: By the way, from Jeffrey freaking.

606
00:29:18,400 --> 00:29:21,760
Speaker 2: Epstein and was messaging with him right up until he

607
00:29:21,880 --> 00:29:25,000
Speaker 2: is put in literal prison, So very.

608
00:29:24,880 --> 00:29:25,880
Speaker 3: Deep relationship with him.

609
00:29:25,920 --> 00:29:28,160
Speaker 2: Okay, So after all of this came out, there's a

610
00:29:28,160 --> 00:29:30,560
Speaker 2: bunch of public pressure, and he is now as of

611
00:29:30,720 --> 00:29:33,800
Speaker 2: yesterday afternoon or evening, could be one up on the screen,

612
00:29:34,160 --> 00:29:36,960
Speaker 2: he is now announced that he is going to step

613
00:29:37,080 --> 00:29:41,400
Speaker 2: back from all public commitments in light of those messages

614
00:29:41,440 --> 00:29:45,080
Speaker 2: that were revealed, with Epstein saying he is deeply ashamed

615
00:29:45,520 --> 00:29:50,320
Speaker 2: and hopes to quote rebuild trust and repair relationships. He will, however,

616
00:29:50,400 --> 00:29:53,800
Speaker 2: continue teaching at Harvard. Let's put the next piece up.

617
00:29:53,680 --> 00:29:54,200
Speaker 3: On the screen.

618
00:29:54,280 --> 00:29:57,440
Speaker 2: American Prospect has been doing some fantastic reporting here. I

619
00:29:57,440 --> 00:29:59,280
Speaker 2: have to think that some of the pressure that came

620
00:29:59,320 --> 00:30:02,360
Speaker 2: from Daniel b Augus Law here at American Prospect and others.

621
00:30:02,440 --> 00:30:07,600
Speaker 2: Ryan also highlighting his emails and also some Chinese government

622
00:30:07,600 --> 00:30:08,320
Speaker 2: official connections.

623
00:30:08,360 --> 00:30:09,280
Speaker 3: I'll get to that in a moment.

624
00:30:09,640 --> 00:30:12,320
Speaker 2: But they talked here about the way he was guiding

625
00:30:12,560 --> 00:30:15,480
Speaker 2: this project at the Center for American Progress. So, according

626
00:30:15,480 --> 00:30:17,760
Speaker 2: to people with knowledge of the arrangement, one of the

627
00:30:17,840 --> 00:30:21,000
Speaker 2: leads on the economic policy plank for the project twenty

628
00:30:21,080 --> 00:30:24,240
Speaker 2: twenty nine project is Harvard professor and former Treasury Secretary

629
00:30:24,320 --> 00:30:27,560
Speaker 2: Larry Summers, who has now been exposed as regularly exchanging

630
00:30:27,600 --> 00:30:30,080
Speaker 2: emails about his personal life with the notorious sex trafficker

631
00:30:30,160 --> 00:30:33,960
Speaker 2: Jeffrey Epstein. Officially, Summers has the title of Distinguished Senior

632
00:30:34,000 --> 00:30:37,200
Speaker 2: Fellow at CAP. All three sources confirmed CAP is compiling

633
00:30:37,240 --> 00:30:40,240
Speaker 2: a policy blueprint in the event of the Democratic presidential

634
00:30:40,320 --> 00:30:42,760
Speaker 2: victory in the next election. Summers had taken a leadership

635
00:30:42,840 --> 00:30:45,440
Speaker 2: role in advising the project's economic policy arm to the

636
00:30:45,480 --> 00:30:48,000
Speaker 2: sources said. They also said Summers was the final sign

637
00:30:48,000 --> 00:30:51,600
Speaker 2: off on a CAP housing policy paper set to be

638
00:30:51,800 --> 00:30:56,120
Speaker 2: released next week, and they have CAP has now confirmed

639
00:30:56,480 --> 00:30:58,840
Speaker 2: that is part of his announcement that he will be

640
00:30:58,880 --> 00:31:02,800
Speaker 2: stepping back, so from public commitments. He is also stepping back,

641
00:31:02,920 --> 00:31:06,040
Speaker 2: will no longer be involved with Center for American Progress

642
00:31:06,040 --> 00:31:07,920
Speaker 2: and presumably this policy project.

643
00:31:08,040 --> 00:31:11,959
Speaker 1: Yeah, but I think what's important to note about Summers is,

644
00:31:12,320 --> 00:31:14,520
Speaker 1: first of all, you know, this whole I'm deeply ashamed,

645
00:31:14,600 --> 00:31:16,880
Speaker 1: Like did you really deeply ashamed because he got caught Okay,

646
00:31:17,280 --> 00:31:20,320
Speaker 1: you know, and in terms of his look, you could

647
00:31:20,400 --> 00:31:23,440
Speaker 1: already have judged him on his policy record in the

648
00:31:23,480 --> 00:31:26,840
Speaker 1: Clinton White House or anywhere else as the Trump or

649
00:31:26,880 --> 00:31:31,080
Speaker 1: as the Harvard University president, Like he clearly had a

650
00:31:31,120 --> 00:31:35,640
Speaker 1: long relationship there with Epstein. But what's really disgusting is

651
00:31:36,040 --> 00:31:39,320
Speaker 1: the way, look, remember this is all post sex offender

652
00:31:39,360 --> 00:31:42,480
Speaker 1: conviction number one, number two in terms of larry his

653
00:31:42,520 --> 00:31:46,640
Speaker 1: own wife is apparently sending Epstein recommendations for books including

654
00:31:46,760 --> 00:31:50,520
Speaker 1: Lolita all right, which, if you'll remember, he actually was

655
00:31:50,560 --> 00:31:54,040
Speaker 1: found with a first edition copy of Lolita, which is

656
00:31:54,200 --> 00:31:56,360
Speaker 1: I mean disgusting. Yeah, if you don't know what it is,

657
00:31:56,400 --> 00:32:00,840
Speaker 1: google it, okay, And it's one of those where inside

658
00:32:00,840 --> 00:32:04,640
Speaker 1: of this you know, piece about his lecherous behavior and

659
00:32:05,080 --> 00:32:08,959
Speaker 1: luring this woman and kind of looking to Epstein as

660
00:32:09,040 --> 00:32:12,920
Speaker 1: like this wingman. Literally that's the way that they describe it.

661
00:32:13,000 --> 00:32:16,080
Speaker 1: You're like, this is so repulsive. And I saw it

662
00:32:16,240 --> 00:32:20,160
Speaker 1: very interesting piece in the Rap actually where a columnist

663
00:32:20,280 --> 00:32:22,840
Speaker 1: was coming to grips with the fact. She was like,

664
00:32:22,920 --> 00:32:26,560
Speaker 1: you know, I've long been an insider, and every Thanksgiving

665
00:32:26,920 --> 00:32:30,080
Speaker 1: I am confronted with a relative who believes that the

666
00:32:30,120 --> 00:32:34,440
Speaker 1: world is run by a global pedophile elite. And she's like,

667
00:32:34,520 --> 00:32:39,880
Speaker 1: now it's painful to admit that they were credited. I'm like, yeah,

668
00:32:39,960 --> 00:32:42,840
Speaker 1: it's true. I mean, look, I'm a cynical guy. I've

669
00:32:42,880 --> 00:32:45,440
Speaker 1: lived here for a long time. You hear stories, you know,

670
00:32:45,560 --> 00:32:49,640
Speaker 1: about things and all of that, even not like when

671
00:32:49,680 --> 00:32:52,560
Speaker 1: you really read the Birthday book, it's shocking, Like it's

672
00:32:52,560 --> 00:32:55,040
Speaker 1: shocking to see some of the world's richest, the most

673
00:32:55,040 --> 00:32:58,920
Speaker 1: powerful men, including our current president, past presidents, Oh, Jeffrey,

674
00:32:59,040 --> 00:33:03,360
Speaker 1: I mean Trump, wonderful secret the check thing about the girlfriend,

675
00:33:04,000 --> 00:33:04,920
Speaker 1: the drawings and the.

676
00:33:04,880 --> 00:33:08,440
Speaker 2: Cartoons intentionally child like, the child like probably freak out

677
00:33:08,440 --> 00:33:09,400
Speaker 2: more than any like.

678
00:33:09,440 --> 00:33:11,280
Speaker 1: And remember that I still haven't been able to track

679
00:33:11,320 --> 00:33:13,080
Speaker 1: that guy down. I've been looking for him, the guy

680
00:33:13,080 --> 00:33:15,880
Speaker 1: with the child drawing where it looked like literally some

681
00:33:15,920 --> 00:33:19,959
Speaker 1: eyes wide shut pianists type thing like. It's I'm telling you,

682
00:33:20,200 --> 00:33:22,960
Speaker 1: I tried for days to actually find the guy who

683
00:33:23,040 --> 00:33:25,000
Speaker 1: drew that. I think he lives in Spain, but you know,

684
00:33:25,080 --> 00:33:27,200
Speaker 1: completely unable to find the fact that it hasn't come

685
00:33:27,240 --> 00:33:29,360
Speaker 1: out at this point is kind of weird in my opinion.

686
00:33:29,480 --> 00:33:31,239
Speaker 1: It was a small child at the time that that

687
00:33:31,320 --> 00:33:34,240
Speaker 1: drawing was done. Uh, you'll recall, you know, some of

688
00:33:34,240 --> 00:33:37,720
Speaker 1: the emails that I was reading recently, Epstein replied to

689
00:33:37,760 --> 00:33:39,920
Speaker 1: somebody and was like, please send a picture of you

690
00:33:40,040 --> 00:33:43,920
Speaker 1: and your child always puts a smile on my face. Weird, Sorry, weird,

691
00:33:44,040 --> 00:33:46,880
Speaker 1: all right, weird. It's one of those where you look

692
00:33:46,960 --> 00:33:51,280
Speaker 1: at their own like winking, nodding behavior, not to mention.

693
00:33:51,360 --> 00:33:53,280
Speaker 1: I mean, remember the birthday book. They literally were making

694
00:33:53,360 --> 00:33:56,320
Speaker 1: rape jokes in there. They're like rape fantasies about wearing

695
00:33:56,440 --> 00:33:59,440
Speaker 1: masks with while they're holding guns and knives, about going

696
00:33:59,440 --> 00:34:02,120
Speaker 1: out and like just finding someone to violently rape them.

697
00:34:02,160 --> 00:34:04,760
Speaker 1: Like this is the stuff that they joked about. So like,

698
00:34:04,800 --> 00:34:08,000
Speaker 1: if you're joking about that, what's actually happening I mean

699
00:34:08,320 --> 00:34:12,040
Speaker 1: behind the scenes and from a very very young age.

700
00:34:12,160 --> 00:34:15,640
Speaker 1: So the fact is is Larry Summers was a part

701
00:34:15,680 --> 00:34:18,480
Speaker 1: of that. And what we always try to say is like, yeah,

702
00:34:18,560 --> 00:34:20,680
Speaker 1: the whole point of the Epstein story is it ain't

703
00:34:20,719 --> 00:34:26,680
Speaker 1: just Summers. It's Leon Black, it's Les Wexner, It's Trump,

704
00:34:26,960 --> 00:34:31,600
Speaker 1: it's Bill Clinton, it's Bill Gates, it's the Nobel pe

705
00:34:31,760 --> 00:34:35,520
Speaker 1: Priest Pricipol, it's a bunch of Israeli former prime ministers.

706
00:34:35,640 --> 00:34:39,000
Speaker 1: It's you know anyway, no, no, no, no, it's four that

707
00:34:39,040 --> 00:34:41,319
Speaker 1: he has known connections to. Now in terms of you know,

708
00:34:41,400 --> 00:34:44,440
Speaker 1: potential lectrous behavior, you're right, But in terms of having

709
00:34:44,440 --> 00:34:46,920
Speaker 1: direct connection to we have at least some mentions of

710
00:34:47,000 --> 00:34:49,480
Speaker 1: four separate Israeli prime ministers that he's had a connection

711
00:34:49,560 --> 00:34:53,840
Speaker 1: to Mongolia is president Coate Devoir, the daughter there of

712
00:34:53,880 --> 00:34:57,040
Speaker 1: the leader. I mean, this is paints a picture which

713
00:34:57,280 --> 00:35:00,200
Speaker 1: is I mean it's eyes wide shot literally like it.

714
00:35:00,000 --> 00:35:06,759
Speaker 1: It is a actual representation of a look at the

715
00:35:06,840 --> 00:35:08,360
Speaker 1: end of the day, what do people always say, like

716
00:35:08,400 --> 00:35:12,120
Speaker 1: absolute power corrupts absolutely and so we already know that

717
00:35:12,160 --> 00:35:15,040
Speaker 1: people who are filthy rich live a very different life

718
00:35:15,200 --> 00:35:18,040
Speaker 1: from all of us. In fact, Jess yesterday, I'm one

719
00:35:18,080 --> 00:35:19,839
Speaker 1: of those suckers for one of those Wall Street Journal

720
00:35:19,880 --> 00:35:22,640
Speaker 1: stories which is like how the ultra rich are living

721
00:35:22,680 --> 00:35:25,799
Speaker 1: in luxury and it's like the super rich Miami real

722
00:35:25,880 --> 00:35:29,000
Speaker 1: estate developers just invite a Wall Street Journal reporter along

723
00:35:29,040 --> 00:35:32,600
Speaker 1: with them to brag about their private dinner clubs and

724
00:35:32,640 --> 00:35:35,359
Speaker 1: their jet setting lifestyle. And I was like, wow, people

725
00:35:35,480 --> 00:35:37,359
Speaker 1: not only have no shame, but it's one of those

726
00:35:37,400 --> 00:35:41,120
Speaker 1: where you're like openly bragging about how the richer that

727
00:35:41,160 --> 00:35:43,239
Speaker 1: you are, how pleasant it is to get away from

728
00:35:43,239 --> 00:35:46,239
Speaker 1: as many peasants as possible. I mean, they're like, say

729
00:35:46,239 --> 00:35:47,560
Speaker 1: this shit out in the open. I mean they say

730
00:35:47,600 --> 00:35:50,040
Speaker 1: it in a more polite way. Obviously it's like, oh, well,

731
00:35:50,120 --> 00:35:52,680
Speaker 1: real luxuries, not it whatever. My point is, just like

732
00:35:53,120 --> 00:35:55,920
Speaker 1: they everybody's it's almost just like out in the open

733
00:35:55,960 --> 00:36:00,560
Speaker 1: now at that point. And I mean that's why I

734
00:36:00,600 --> 00:36:02,760
Speaker 1: think the Epstein story matters, is because it just shows

735
00:36:02,760 --> 00:36:07,560
Speaker 1: that they transcend a level above where not even normal

736
00:36:07,600 --> 00:36:11,040
Speaker 1: but like normal ish people are and they act with

737
00:36:11,120 --> 00:36:13,560
Speaker 1: a totally different set of rules, and that set of

738
00:36:13,680 --> 00:36:17,399
Speaker 1: rules corrupts at the sole level, at the financial level,

739
00:36:17,800 --> 00:36:21,399
Speaker 1: government level, truly, and those are the people broadly who

740
00:36:21,440 --> 00:36:24,279
Speaker 1: are in charge of the world's riches and of the

741
00:36:24,280 --> 00:36:27,000
Speaker 1: world's governments. I think we should all grapple with that.

742
00:36:27,400 --> 00:36:29,480
Speaker 2: Yeah, I mean, I think having a bunch of billionaires

743
00:36:29,520 --> 00:36:33,239
Speaker 2: is inconsistent with democracy. I think it does, like you said,

744
00:36:33,280 --> 00:36:38,240
Speaker 2: corrupt you on like a deep foundational level where yeah,

745
00:36:38,280 --> 00:36:41,359
Speaker 2: you just don't see yourself as part of this sea

746
00:36:41,560 --> 00:36:45,600
Speaker 2: of humanity. And there's also this level of decadence and

747
00:36:45,640 --> 00:36:48,360
Speaker 2: boredom that seems to come where it's just like, you know,

748
00:36:48,400 --> 00:36:51,880
Speaker 2: you're just looking for more and more elaborate displays of

749
00:36:51,920 --> 00:36:56,280
Speaker 2: like wealth or opulence or you know, decadence in other ways,

750
00:36:56,760 --> 00:36:59,759
Speaker 2: with Larry Summers in particular. I really want people to

751
00:36:59,840 --> 00:37:02,320
Speaker 2: I don't know if people how much you know about

752
00:37:02,320 --> 00:37:06,239
Speaker 2: this man, but he's sort of the ultimate Washington like

753
00:37:06,560 --> 00:37:08,080
Speaker 2: serious thinker, you.

754
00:37:08,040 --> 00:37:10,360
Speaker 3: Know, very highly esteemed.

755
00:37:10,520 --> 00:37:15,399
Speaker 2: Harvard obviously has advised multiple presidents. He's always consulted Trump. Still,

756
00:37:15,440 --> 00:37:18,320
Speaker 2: would you know, I mean, he's Biden still was talking

757
00:37:18,320 --> 00:37:22,160
Speaker 2: to him. Obviously even now, even even before these emails

758
00:37:22,200 --> 00:37:24,360
Speaker 2: came out, we knew about this relationship with Epstein, but

759
00:37:24,360 --> 00:37:27,040
Speaker 2: Center for American Progress is still bringing him in for

760
00:37:27,080 --> 00:37:30,280
Speaker 2: their economic policy plank. Like he's seen as the ultimate

761
00:37:30,400 --> 00:37:36,279
Speaker 2: like serious economic thinker, especially in democratic circles. And so,

762
00:37:37,080 --> 00:37:40,640
Speaker 2: you know, to have these emails revealed, which are disgusting,

763
00:37:40,840 --> 00:37:43,960
Speaker 2: let's put the next Harvard Crimson tear sheet up on

764
00:37:44,000 --> 00:37:46,400
Speaker 2: the screen, which details some of them. So a summersat

765
00:37:46,520 --> 00:37:50,360
Speaker 2: clandestine relationship with women he called a mentee. Epstein was

766
00:37:50,400 --> 00:37:54,200
Speaker 2: his quote wingman, and Sager used that terminology like that's

767
00:37:54,200 --> 00:37:57,560
Speaker 2: how they referred to it, right, That's not our characterization.

768
00:37:57,640 --> 00:38:01,000
Speaker 2: That was how they refer to this relationship. And so

769
00:38:01,120 --> 00:38:02,759
Speaker 2: I'll read you a little bit of this. They say

770
00:38:02,760 --> 00:38:05,280
Speaker 2: in a sequence of text and emails between November twenty

771
00:38:05,280 --> 00:38:07,759
Speaker 2: eighteen and July fifth, twenty nineteen. What's happens in July

772
00:38:07,840 --> 00:38:11,480
Speaker 2: of twenty nineteen, Soccer Epstein goes to prison, So he's

773
00:38:11,560 --> 00:38:13,800
Speaker 2: emailing this man right up until he goes to prison.

774
00:38:13,920 --> 00:38:16,920
Speaker 2: Summers turned to Epstein for advice on his pursuit of

775
00:38:16,960 --> 00:38:20,759
Speaker 2: this woman, who he described as a mentee. Epstein was

776
00:38:20,800 --> 00:38:23,920
Speaker 2: quick to chime in with assurances and suggestions, describing himself

777
00:38:23,920 --> 00:38:27,640
Speaker 2: in one November twenty eighteen message as summers wingman. Then

778
00:38:27,719 --> 00:38:31,279
Speaker 2: explains how they became public. Summer's correspondence with Epstein, a

779
00:38:31,320 --> 00:38:34,640
Speaker 2: financier who pled guilty to soliciting prostitution for minor in

780
00:38:35,000 --> 00:38:38,240
Speaker 2: two thousand and eight, ends just one day before Epstein

781
00:38:38,320 --> 00:38:43,280
Speaker 2: was arrested on new sex trafficking charges. Together, the messages

782
00:38:43,280 --> 00:38:46,960
Speaker 2: show Summers placed an extraordinary degree of trust in Epstein,

783
00:38:47,080 --> 00:38:49,719
Speaker 2: asking him for help in navigating relationship that blurred the

784
00:38:49,719 --> 00:38:52,600
Speaker 2: boundaries of his professional and personal lives. Again, by the way,

785
00:38:52,760 --> 00:38:56,360
Speaker 2: Larry Summer's married during this entire time. Summers, who was

786
00:38:56,360 --> 00:38:58,680
Speaker 2: married since two thousand and five, told Epstein he thought

787
00:38:58,719 --> 00:39:02,120
Speaker 2: the woman was reluctant to leave him because she valued.

788
00:39:01,719 --> 00:39:03,120
Speaker 3: His professional connections.

789
00:39:03,400 --> 00:39:05,840
Speaker 2: Epstein told him in one June twenty nineteen text, she

790
00:39:05,960 --> 00:39:08,960
Speaker 2: is doomed to be with you think for now I'm

791
00:39:09,000 --> 00:39:13,280
Speaker 2: going nowhere with her except at economics mentor, Summers wrote,

792
00:39:13,400 --> 00:39:15,760
Speaker 2: I think I'm right now in the scene very warmly

793
00:39:15,880 --> 00:39:19,040
Speaker 2: in rear view mirror category. She must be very confused

794
00:39:19,160 --> 00:39:21,320
Speaker 2: or maybe wants to cut me off. But one's professional

795
00:39:21,320 --> 00:39:23,959
Speaker 2: connection a lot, and so holds to it, Summers wrote

796
00:39:23,960 --> 00:39:26,720
Speaker 2: in a March twenty nineteen exchange, explaining why he believed

797
00:39:26,840 --> 00:39:30,760
Speaker 2: she continued to engage with him despite tensions, which listen

798
00:39:31,200 --> 00:39:34,960
Speaker 2: is also disgusting that he knows she doesn't really want

799
00:39:35,000 --> 00:39:38,120
Speaker 2: to be with him romantically, but he has this powerful

800
00:39:38,239 --> 00:39:41,560
Speaker 2: position and sort of hold on her, so he's using

801
00:39:41,640 --> 00:39:45,640
Speaker 2: that to maintain the sexual relationship even though what she

802
00:39:45,719 --> 00:39:49,880
Speaker 2: really wants is actually just the mentee relationship. Is disgusting,

803
00:39:50,000 --> 00:39:52,920
Speaker 2: Like that's what he's acknowledging in these emails to Epstein,

804
00:39:53,000 --> 00:39:54,920
Speaker 2: is like that's the hole that he has on her,

805
00:39:54,960 --> 00:39:57,000
Speaker 2: and that's what he's going to exploit to keep her close.

806
00:39:57,200 --> 00:39:59,440
Speaker 1: It's like a I mean, it's like a parody of

807
00:39:59,480 --> 00:40:01,359
Speaker 1: me too. You know. It's one of those where it's

808
00:40:01,400 --> 00:40:03,280
Speaker 1: like the you bring together.

809
00:40:03,120 --> 00:40:05,080
Speaker 3: Power, the power dynamic yeah.

810
00:40:04,960 --> 00:40:07,520
Speaker 1: Yeah, right, I mean god like and look, you know

811
00:40:07,560 --> 00:40:09,160
Speaker 1: it was a critic and stuff of me too, but

812
00:40:09,239 --> 00:40:10,880
Speaker 1: like some of these people are real, like some of

813
00:40:10,960 --> 00:40:14,440
Speaker 1: these creeps. It started for a reason. I mean, I

814
00:40:14,520 --> 00:40:16,719
Speaker 1: have no other way. Really, dude, describe it. Put some

815
00:40:16,760 --> 00:40:18,480
Speaker 1: of the emails. Let's go to be four, just to

816
00:40:18,480 --> 00:40:21,240
Speaker 1: show everybody. Let's put it up here on the screen again.

817
00:40:21,400 --> 00:40:25,000
Speaker 1: March of twenty nineteen, he says, we talked on the phone.

818
00:40:25,080 --> 00:40:27,920
Speaker 1: Then I can't talk later, didn't think I can talk tomorrow.

819
00:40:27,960 --> 00:40:29,680
Speaker 1: I said, what are you up to? She said, I'm busy.

820
00:40:29,880 --> 00:40:33,080
Speaker 1: I said, awfully, koy you are. Then I said, did

821
00:40:33,120 --> 00:40:35,319
Speaker 1: you really rearrange the weekend we were going to be

822
00:40:35,400 --> 00:40:37,560
Speaker 1: together because guy number three was coming? She said, no,

823
00:40:37,719 --> 00:40:40,160
Speaker 1: is schedule change. After we changed our plans, I said, okay,

824
00:40:40,400 --> 00:40:41,960
Speaker 1: call me when you feel like a tone was not

825
00:40:42,000 --> 00:40:43,560
Speaker 1: a good feeling. I didn't want to be in a

826
00:40:43,600 --> 00:40:47,360
Speaker 1: gift giving competition while being friends without benefits. This is hilarry.

827
00:40:47,480 --> 00:40:50,000
Speaker 1: In March twenty nineteen, how old is he at this point?

828
00:40:50,080 --> 00:40:53,440
Speaker 1: Like sixty something? Epstein, She's smart making you pay for

829
00:40:53,520 --> 00:40:55,960
Speaker 1: past errors. Ignore the daddy. I'm going to go out

830
00:40:55,960 --> 00:40:59,280
Speaker 1: with motorcycle guy you reacted well dot dot dot annoyed,

831
00:40:59,320 --> 00:41:03,000
Speaker 1: shows caring, no whining, show to strength. I mean, yeah,

832
00:41:03,160 --> 00:41:07,319
Speaker 1: like this is literally like I don't know, it's like

833
00:41:07,440 --> 00:41:10,680
Speaker 1: teenage behavior, which weird even at that point. But these

834
00:41:10,719 --> 00:41:13,479
Speaker 1: are sixty year old men who are the ultra rich,

835
00:41:13,600 --> 00:41:16,520
Speaker 1: who are also in Larry Summers case, literally married. I mean,

836
00:41:16,760 --> 00:41:18,400
Speaker 1: I have no idea how he can ever show his

837
00:41:18,440 --> 00:41:22,040
Speaker 1: face in public. Ever. Again, let's go to the next one, Shawe.

838
00:41:22,080 --> 00:41:23,919
Speaker 1: In terms of the emails, same thing.

839
00:41:23,960 --> 00:41:24,120
Speaker 4: You know.

840
00:41:24,200 --> 00:41:27,879
Speaker 1: This was from Larry Summers to this woman who he

841
00:41:27,920 --> 00:41:30,000
Speaker 1: was wooing. He said, I wanted to show how grateful

842
00:41:30,040 --> 00:41:31,799
Speaker 1: I am and have been for your support, also for

843
00:41:31,800 --> 00:41:33,920
Speaker 1: the support of my father's work. This is what she's saying.

844
00:41:34,040 --> 00:41:35,880
Speaker 1: I don't say these things often by hope, he implies.

845
00:41:36,160 --> 00:41:40,000
Speaker 1: You know, it's one of those where he is exploiting

846
00:41:40,320 --> 00:41:43,920
Speaker 1: this relationship and his own past relationship with her father

847
00:41:44,440 --> 00:41:47,480
Speaker 1: to like try to woo this girl. I mean, are

848
00:41:47,520 --> 00:41:49,600
Speaker 1: this woman right at the time? I just think it's

849
00:41:49,640 --> 00:41:50,160
Speaker 1: really sick.

850
00:41:50,280 --> 00:41:53,080
Speaker 2: So this is the woman that it appears the messages

851
00:41:53,200 --> 00:41:57,919
Speaker 2: were about, and so he had this mentee relationship with her.

852
00:41:58,280 --> 00:42:03,040
Speaker 2: But in addition, her dad is a CCP official, So

853
00:42:03,480 --> 00:42:06,239
Speaker 2: you know, I mean, there's just all sorts of layers

854
00:42:06,280 --> 00:42:09,920
Speaker 2: of morally professionally inappropriate.

855
00:42:11,040 --> 00:42:13,080
Speaker 3: I mean, it's it's gross.

856
00:42:13,160 --> 00:42:15,360
Speaker 2: And then the fact that this man is still was

857
00:42:15,440 --> 00:42:18,520
Speaker 2: up until this moment so trusted by so many people

858
00:42:18,560 --> 00:42:21,880
Speaker 2: in power here in DC is extraordinary. Caput B six

859
00:42:22,200 --> 00:42:25,040
Speaker 2: up on the screen here from ze Jalani.

860
00:42:25,120 --> 00:42:26,000
Speaker 3: This was the original.

861
00:42:26,080 --> 00:42:29,160
Speaker 2: He's deeply shamed after new Epstein emails and will pause

862
00:42:29,200 --> 00:42:33,080
Speaker 2: public engagements. So there you go. That's the tale of

863
00:42:33,160 --> 00:42:37,040
Speaker 2: Larry Summers here. But you know, he's just emblematic of

864
00:42:37,239 --> 00:42:40,160
Speaker 2: so many and you know the fact that Epstein had

865
00:42:40,160 --> 00:42:43,520
Speaker 2: these close relationships with people like him who are held

866
00:42:43,560 --> 00:42:46,480
Speaker 2: in such high esteem by so many elites and look

867
00:42:46,520 --> 00:42:49,839
Speaker 2: to for guidance and wisdom and serious person blah blah

868
00:42:49,880 --> 00:42:53,720
Speaker 2: blah is part of how he was able to maintain

869
00:42:54,200 --> 00:42:57,359
Speaker 2: all of his you know, his wealth and his connections

870
00:42:57,400 --> 00:43:01,960
Speaker 2: and his banking relationships. This is one one piece because

871
00:43:02,000 --> 00:43:04,440
Speaker 2: he would people would he would use the fact that like, oh, well,

872
00:43:04,520 --> 00:43:06,440
Speaker 2: Larry Summers truss me, will Bill Gates trust me? Well,

873
00:43:06,440 --> 00:43:09,960
Speaker 2: Elon must trust me, so why wouldn't you? And the

874
00:43:10,000 --> 00:43:12,200
Speaker 2: fact that they all had this cone of silence around

875
00:43:12,239 --> 00:43:14,040
Speaker 2: it is how it perpetuated for.

876
00:43:14,360 --> 00:43:17,000
Speaker 1: So so, and they had no moral standards. I mean again,

877
00:43:17,080 --> 00:43:19,360
Speaker 1: even if somebody was like, hey man, you know so

878
00:43:19,480 --> 00:43:22,080
Speaker 1: and so he's a good guy, I'm like, yeah, maybe,

879
00:43:22,520 --> 00:43:25,640
Speaker 1: and then you do Google search and you see conviction

880
00:43:25,719 --> 00:43:27,640
Speaker 1: for him, like yeah, I'm good. You know, It's like

881
00:43:27,960 --> 00:43:29,400
Speaker 1: it'd be one of those where I'd be like, hey,

882
00:43:29,719 --> 00:43:31,759
Speaker 1: do you know about this? And if they're like, oh, yeah,

883
00:43:31,840 --> 00:43:35,239
Speaker 1: but you know he said she actually was you know,

884
00:43:35,440 --> 00:43:37,920
Speaker 1: she looked eighteen or something, I'd be like, oh, bro,

885
00:43:38,200 --> 00:43:39,520
Speaker 1: like this is not happening.

886
00:43:39,560 --> 00:43:42,279
Speaker 2: And even if so yeah, they led to downplay Alan

887
00:43:42,320 --> 00:43:44,880
Speaker 2: Dershowood still out there downplaying it like oh, you know

888
00:43:44,960 --> 00:43:47,520
Speaker 2: the girl was, she was seventeen, It's just one. They

889
00:43:47,560 --> 00:43:50,480
Speaker 2: were so harsh on him, blah blah blah. But this

890
00:43:50,640 --> 00:43:54,200
Speaker 2: these emails again leading up until literally he's arrested. Day

891
00:43:54,239 --> 00:43:59,040
Speaker 2: before he's arrested and put in prison. They this was

892
00:43:59,080 --> 00:44:02,040
Speaker 2: after Julie Capeer. Yeah, I had done all of her

893
00:44:02,080 --> 00:44:04,440
Speaker 2: reporting for the Miami Herald about how no, there were

894
00:44:04,560 --> 00:44:07,000
Speaker 2: dozens of girls, We're talking down to what the youngest

895
00:44:07,080 --> 00:44:11,160
Speaker 2: was like thirteen. So he got this slap on the wrist.

896
00:44:11,719 --> 00:44:17,759
Speaker 2: Totally rigged and inappropriate, literally illegal sweetheart deal. All of

897
00:44:17,800 --> 00:44:20,600
Speaker 2: that is in the public domain. So even if Larry

898
00:44:20,640 --> 00:44:23,200
Speaker 2: Summers wanted to be tricked by Epstein's you know, oh

899
00:44:23,239 --> 00:44:25,080
Speaker 2: well it was just you know, I hired a prostitute

900
00:44:25,080 --> 00:44:27,320
Speaker 2: once that I didn't know that she wasn't any whatever,

901
00:44:27,360 --> 00:44:30,359
Speaker 2: which is still disgusting, right, But even if you you know,

902
00:44:30,400 --> 00:44:33,120
Speaker 2: wanted to buy that at this point in time, all

903
00:44:33,280 --> 00:44:36,360
Speaker 2: every it's all out there. I mean, we have learned

904
00:44:36,360 --> 00:44:39,640
Speaker 2: more over the years, but the general shape and the

905
00:44:40,120 --> 00:44:43,200
Speaker 2: web of how disgusting this was was out in the

906
00:44:43,200 --> 00:44:46,759
Speaker 2: public record, and he was still seeking relationship advice for

907
00:44:46,840 --> 00:44:48,879
Speaker 2: his affair from this man.

908
00:44:49,040 --> 00:44:52,920
Speaker 1: Yeah, just grotesque again, I mean, they live in a

909
00:44:52,960 --> 00:44:55,040
Speaker 1: different world than the rest of us. I guess I

910
00:44:55,080 --> 00:44:56,399
Speaker 1: don't really have another word for it.

911
00:44:59,280 --> 00:45:01,360
Speaker 2: So we have a bunch updates for you with regard

912
00:45:01,440 --> 00:45:04,920
Speaker 2: to Trump's ice deployments across the country, but wanted to

913
00:45:04,920 --> 00:45:07,239
Speaker 2: start actually with a polling update. Of course, Trump and

914
00:45:07,239 --> 00:45:09,640
Speaker 2: the Republicans took a lot of pride in the gains

915
00:45:09,680 --> 00:45:13,160
Speaker 2: that they made with Latino voters, particularly in this election cycle,

916
00:45:13,160 --> 00:45:15,560
Speaker 2: have really pinned a lot, actually staked a lot on

917
00:45:15,680 --> 00:45:17,879
Speaker 2: this realignment of working class Latino.

918
00:45:17,600 --> 00:45:19,000
Speaker 3: Voters towards Republicans.

919
00:45:19,239 --> 00:45:21,960
Speaker 6: Let's check in on how that's going Latinos on Trump

920
00:45:21,960 --> 00:45:24,080
Speaker 6: and immigration. You know, back a year ago, what do

921
00:45:24,160 --> 00:45:27,440
Speaker 6: we see on the issue of immigration. Latino voters trusted

922
00:45:27,520 --> 00:45:30,319
Speaker 6: Kamala Harris more than Donald Trump, but by just two

923
00:45:30,360 --> 00:45:33,960
Speaker 6: points one two. Look now at Donald Trump's then approvating

924
00:45:34,280 --> 00:45:38,320
Speaker 6: on immigration among Latinos. He is thirty eight points underwater.

925
00:45:38,440 --> 00:45:41,840
Speaker 6: That is a thirty six point shift essentially from where

926
00:45:41,880 --> 00:45:44,480
Speaker 6: we were a year ago. On immigration, Kamala Harris and

927
00:45:44,480 --> 00:45:46,960
Speaker 6: Donald Trump are basically tied on the issue of immigration,

928
00:45:47,239 --> 00:45:51,640
Speaker 6: and now on the issue of immigration, Latinos despise hate

929
00:45:51,680 --> 00:45:55,760
Speaker 6: Donald Trump. Trump's not approparating among Latinos. In early February, again,

930
00:45:55,960 --> 00:45:58,359
Speaker 6: he was just two points underwater. Look at where he

931
00:45:58,440 --> 00:46:03,560
Speaker 6: is now late October minus thirty four points. Thirty four

932
00:46:03,640 --> 00:46:06,799
Speaker 6: points underwater, a shift to thirty two points over the

933
00:46:06,800 --> 00:46:08,359
Speaker 6: course of this year. I should point out this as

934
00:46:08,360 --> 00:46:10,440
Speaker 6: the CBS new Juga pole, but I was looking at

935
00:46:10,480 --> 00:46:12,759
Speaker 6: the Averager polls. I was looking at our own poll

936
00:46:13,320 --> 00:46:17,560
Speaker 6: very similar shift twenty twenty five thirty point shifts on

937
00:46:17,600 --> 00:46:21,520
Speaker 6: the net approval rating away from Donald Trump among Latino's

938
00:46:21,560 --> 00:46:23,839
Speaker 6: overall and what did we learn from the twenty twenty

939
00:46:23,880 --> 00:46:27,200
Speaker 6: five elections. I took the highest Latino percentage area in

940
00:46:27,239 --> 00:46:30,359
Speaker 6: both New Jersey and Virginia. New Jersey, it was Union City.

941
00:46:30,560 --> 00:46:32,560
Speaker 6: Look at this twenty twenty four president of the twenty

942
00:46:32,600 --> 00:46:36,239
Speaker 6: twenty five governor shift. There was a fifty two I'm

943
00:46:36,320 --> 00:46:38,680
Speaker 6: laughing because you never see any numbers like this, A

944
00:46:38,760 --> 00:46:42,120
Speaker 6: fifty two point shift towards Mikey Show from how Kamala

945
00:46:42,160 --> 00:46:45,120
Speaker 6: Harris did on the margin. Mikey Show ran away with this.

946
00:46:45,400 --> 00:46:47,760
Speaker 6: Kamala Harris did win that vote, but by a small margin.

947
00:46:48,520 --> 00:46:50,759
Speaker 6: Mikey Show did fifty two points better. How about in

948
00:46:50,840 --> 00:46:53,920
Speaker 6: Virginia Manasa's Park. Look at that, a twenty two point

949
00:46:53,960 --> 00:46:57,279
Speaker 6: shift towards Abigail Spamberger from how Kamala Harris did.

950
00:46:57,560 --> 00:46:58,680
Speaker 1: Back in twenty twenty four.

951
00:46:58,800 --> 00:47:01,800
Speaker 6: We saw a huge Latino shift in both New Jersey

952
00:47:02,040 --> 00:47:03,000
Speaker 6: and Virginia.

953
00:47:03,120 --> 00:47:04,920
Speaker 2: And I think sagar that Latinos are one of the

954
00:47:04,920 --> 00:47:08,960
Speaker 2: biggest swing blocks in America. Democrats really took for granted that,

955
00:47:09,040 --> 00:47:12,400
Speaker 2: you know, Latino support and also had this very caricaturish

956
00:47:12,520 --> 00:47:15,279
Speaker 2: view of what they wanted in terms of, you know,

957
00:47:15,360 --> 00:47:18,000
Speaker 2: super serving a soft on immigration message and that that

958
00:47:18,000 --> 00:47:20,200
Speaker 2: would be enough to hold them in the coalition forever.

959
00:47:20,560 --> 00:47:22,560
Speaker 2: And you and I have been tracking, you know, especially

960
00:47:22,600 --> 00:47:25,560
Speaker 2: in twenty twenty you saw these significant shifts down in

961
00:47:25,600 --> 00:47:28,759
Speaker 2: Texas and Rio Grand Valley. Then you saw in twenty

962
00:47:28,840 --> 00:47:31,320
Speaker 2: twenty four even more shifts towards Trump, and then I

963
00:47:31,360 --> 00:47:34,160
Speaker 2: think Republicans have somewhat made the mistake of just assuming

964
00:47:34,200 --> 00:47:36,319
Speaker 2: that like, oh, now they're in our coalition and that's

965
00:47:36,320 --> 00:47:37,560
Speaker 2: it and nothing is going to change.

966
00:47:37,560 --> 00:47:39,640
Speaker 1: It's just especially true in Texas where a lot of

967
00:47:39,640 --> 00:47:43,800
Speaker 1: the jerrymandering relies on the Latino swinge. That's the biggest mistake.

968
00:47:44,160 --> 00:47:47,400
Speaker 1: I mean, look, no constituency should be taken for granted.

969
00:47:47,520 --> 00:47:49,839
Speaker 1: I do also think it's caricaturist to say that it's

970
00:47:49,880 --> 00:47:52,000
Speaker 1: only about immigration. One of the things that we always

971
00:47:52,000 --> 00:47:54,200
Speaker 1: said is, yeah, it turns out Latinos are like everybody

972
00:47:54,200 --> 00:47:57,239
Speaker 1: else and in terms of we care about the economy,

973
00:47:57,400 --> 00:48:00,600
Speaker 1: actually we're not all the same. Actually, a Puerto Rican

974
00:48:00,680 --> 00:48:02,800
Speaker 1: in New York is not the same as a fifth

975
00:48:02,840 --> 00:48:07,319
Speaker 1: generation Mexican Ish guy in South Texas. Turns out, yes

976
00:48:07,360 --> 00:48:10,200
Speaker 1: we may understand each other's language, we're totally different. We

977
00:48:10,239 --> 00:48:13,560
Speaker 1: have totally doing a wants, dreams whatever. Our entire daily

978
00:48:13,600 --> 00:48:17,319
Speaker 1: life is distinctly different than also a Cuban or Paraguayan

979
00:48:17,640 --> 00:48:22,319
Speaker 1: in South Florida and then also a Chicano in Los Angeles.

980
00:48:22,320 --> 00:48:24,839
Speaker 1: Like we're all the same, okay, actually in that we're

981
00:48:24,880 --> 00:48:29,319
Speaker 1: all different, that's it, and mostly we're basically yeah we are. Yeah,

982
00:48:29,600 --> 00:48:32,439
Speaker 1: it's a tutology, but it's true. It's one of those where, yes,

983
00:48:32,560 --> 00:48:35,480
Speaker 1: we are in a massive country, we all individually live

984
00:48:35,760 --> 00:48:38,400
Speaker 1: in our areas where our wants needs can be like

985
00:48:38,600 --> 00:48:41,279
Speaker 1: ish the same, but the circumstances of our life are

986
00:48:41,360 --> 00:48:44,120
Speaker 1: very different. So we generally vote in terms of our

987
00:48:44,120 --> 00:48:47,359
Speaker 1: own interests. And this is why remember the Tony Hinchcliffe thing.

988
00:48:47,360 --> 00:48:49,920
Speaker 1: They're like, oh, Puerto Rican, so they're not going to

989
00:48:49,960 --> 00:48:52,720
Speaker 1: take that. It's like, yeah, actually they voted overwhelmingly for Trump,

990
00:48:52,760 --> 00:48:56,040
Speaker 1: and especially down in South Florida, and it's like, yeah, why, well,

991
00:48:56,080 --> 00:48:58,440
Speaker 1: because it turns out like they're not like little sissies

992
00:48:58,480 --> 00:49:01,920
Speaker 1: that can't take a joke again, just like everyone else.

993
00:49:02,000 --> 00:49:05,320
Speaker 1: So in this case, I think their net on immigration

994
00:49:05,920 --> 00:49:09,520
Speaker 1: in the same way other people are net negative on immigration.

995
00:49:09,560 --> 00:49:12,000
Speaker 1: They're like, this feels chaotic, That's what it's right.

996
00:49:12,040 --> 00:49:14,320
Speaker 2: I mean, I would say that they're may just given

997
00:49:14,360 --> 00:49:17,799
Speaker 2: the racial character of the way the immigration push has

998
00:49:17,880 --> 00:49:22,120
Speaker 2: been executed with the Kavanaugh stops, the number of US

999
00:49:22,160 --> 00:49:25,200
Speaker 2: citizens who happen to look Latino or have Latino surnames

1000
00:49:25,280 --> 00:49:27,640
Speaker 2: or whatever, who have been stopped, who have been arrested,

1001
00:49:27,640 --> 00:49:30,160
Speaker 2: who haven't been believed even when they pull out their

1002
00:49:30,200 --> 00:49:32,799
Speaker 2: driver's license, Like, I think it probably does hit a

1003
00:49:32,800 --> 00:49:35,720
Speaker 2: little extra if you're Latino and you see the way

1004
00:49:36,160 --> 00:49:38,319
Speaker 2: that people who look like you and you know, have

1005
00:49:38,400 --> 00:49:41,800
Speaker 2: similar names come have similar ethnic backgrounds or being targeted.

1006
00:49:41,840 --> 00:49:43,799
Speaker 2: Your communities are the ones that are being you know,

1007
00:49:43,880 --> 00:49:45,960
Speaker 2: most targeted by ICE. Like I do think that that

1008
00:49:46,120 --> 00:49:49,719
Speaker 2: is is certainly a significant factor here as well. But

1009
00:49:49,880 --> 00:49:53,880
Speaker 2: in terms of the latest so you know, Baveno's crew

1010
00:49:54,239 --> 00:49:56,600
Speaker 2: of Customs and Border Patrol, which are the you know,

1011
00:49:56,640 --> 00:49:58,359
Speaker 2: we talk about ICE as kind of a catch hall

1012
00:49:58,440 --> 00:50:01,439
Speaker 2: CBP is actually the most across and Bovino has been

1013
00:50:01,600 --> 00:50:04,480
Speaker 2: He's the one who did the big apartment raid in Chicago, Like,

1014
00:50:04,560 --> 00:50:08,239
Speaker 2: he's been sort of the most wild and and has

1015
00:50:08,280 --> 00:50:12,000
Speaker 2: the most like militarized sort of forces behind him. He

1016
00:50:12,120 --> 00:50:14,800
Speaker 2: also in Chicago, And I think this is part probably

1017
00:50:14,840 --> 00:50:15,920
Speaker 2: of why they're leaving.

1018
00:50:15,680 --> 00:50:16,560
Speaker 3: The city of Chicago.

1019
00:50:16,640 --> 00:50:18,839
Speaker 2: At this point, there were a bunch of court orders

1020
00:50:18,880 --> 00:50:22,240
Speaker 2: that came down to really constrain their use of force,

1021
00:50:22,320 --> 00:50:24,799
Speaker 2: in particular their use of tear gas, which had been

1022
00:50:25,040 --> 00:50:29,560
Speaker 2: totally just wild and indiscriminate. We showed you the video

1023
00:50:29,640 --> 00:50:32,200
Speaker 2: here of them like spraying tear gas into a car

1024
00:50:32,280 --> 00:50:34,359
Speaker 2: that was passing by that had a one year old

1025
00:50:34,600 --> 00:50:37,319
Speaker 2: strapped into the seat. American citizens, by the way, one

1026
00:50:37,400 --> 00:50:39,080
Speaker 2: year old strapped into the seat and they just pepper

1027
00:50:39,080 --> 00:50:41,440
Speaker 2: spray them as they're driving by. So in any case,

1028
00:50:41,440 --> 00:50:42,920
Speaker 2: there had been a bunch of court orders against him.

1029
00:50:42,920 --> 00:50:44,720
Speaker 2: He had to admit in court that he had lied

1030
00:50:44,800 --> 00:50:48,040
Speaker 2: about a number of incidents as well. So they've left Chicago.

1031
00:50:48,440 --> 00:50:50,799
Speaker 2: Now they're in Charlotte. We can put see two up

1032
00:50:50,800 --> 00:50:52,320
Speaker 2: on the screen. This is from a day ago. I

1033
00:50:52,360 --> 00:50:54,320
Speaker 2: don't know what the update is, but US Border Patrol

1034
00:50:54,320 --> 00:50:58,279
Speaker 2: over US eighty one on first date of Charlotte immigration crackdown.

1035
00:50:58,480 --> 00:51:01,000
Speaker 2: We've seen backlash in the community. There's you know, video,

1036
00:51:01,040 --> 00:51:04,280
Speaker 2: similar videos of Chicago coming out as Charlotte, and apparently

1037
00:51:04,320 --> 00:51:06,640
Speaker 2: the idea is to stay there for a relatively short

1038
00:51:06,680 --> 00:51:10,400
Speaker 2: period before heading down to New Orleans. We also have

1039
00:51:10,480 --> 00:51:12,920
Speaker 2: some numbers here about Okay, so, you know, do they

1040
00:51:13,160 --> 00:51:14,640
Speaker 2: get the bad guys in Chicago?

1041
00:51:14,840 --> 00:51:15,600
Speaker 3: Was it all worth it?

1042
00:51:15,680 --> 00:51:18,920
Speaker 2: All the you know, black Hawk helicopters zip tying children

1043
00:51:19,000 --> 00:51:22,880
Speaker 2: pepper spray near Halloween parades, shooting an American citizen it

1044
00:51:22,960 --> 00:51:25,719
Speaker 2: was an activist five times? Was this all worth it?

1045
00:51:25,880 --> 00:51:28,799
Speaker 2: Put C three up on the screen. Two point six

1046
00:51:28,880 --> 00:51:33,880
Speaker 2: percent sixteen people on the list of six hundred and

1047
00:51:33,880 --> 00:51:36,960
Speaker 2: fourteen that had to be provided to the court in

1048
00:51:37,160 --> 00:51:40,319
Speaker 2: one of these cases, two point six percent of them

1049
00:51:40,520 --> 00:51:44,239
Speaker 2: had any criminal history at all. I mean, that is

1050
00:51:44,760 --> 00:51:48,680
Speaker 2: so pathetic, is they said? I think in this article

1051
00:51:48,760 --> 00:51:50,400
Speaker 2: or one of the other ones that I read about this,

1052
00:51:50,560 --> 00:51:53,680
Speaker 2: that you know, normal Chicago PD would in a single

1053
00:51:53,719 --> 00:51:57,080
Speaker 2: weekend come into contact and have dealings with more than

1054
00:51:57,200 --> 00:52:01,759
Speaker 2: sixteen people with criminal records. So when they use all

1055
00:52:01,760 --> 00:52:04,440
Speaker 2: this rhetoric about the worst of the worst, and you know,

1056
00:52:04,520 --> 00:52:07,840
Speaker 2: these are the worst people on the planet, this is

1057
00:52:07,880 --> 00:52:10,640
Speaker 2: what we're actually talking about here. Barely any of these

1058
00:52:10,680 --> 00:52:15,359
Speaker 2: people had criminal histories. In the big apartment breed that

1059
00:52:15,440 --> 00:52:18,080
Speaker 2: they broadcast on social media were so proud of they

1060
00:52:18,080 --> 00:52:22,360
Speaker 2: put out all this propaganda about used the Blackhawk military helicopters, swooping,

1061
00:52:23,160 --> 00:52:26,319
Speaker 2: knockdown doors, dragging out shoulder in the middle of the night,

1062
00:52:26,400 --> 00:52:30,080
Speaker 2: American citizens all the rest. Guess how many people they

1063
00:52:30,160 --> 00:52:34,799
Speaker 2: ended up charging from that zero zero. Again, we were

1064
00:52:34,800 --> 00:52:37,799
Speaker 2: told this building was infested with trender rag trender Raga

1065
00:52:37,800 --> 00:52:40,520
Speaker 2: had taken over this building. It was lawless gang violence.

1066
00:52:40,560 --> 00:52:42,560
Speaker 2: I'm not going to say that there weren't any sort

1067
00:52:42,600 --> 00:52:44,960
Speaker 2: of crimes being committed in the building because people had

1068
00:52:45,000 --> 00:52:47,120
Speaker 2: complained about, you know, drug use and this sorts of

1069
00:52:47,160 --> 00:52:49,360
Speaker 2: thing that was going on. You had a total slum

1070
00:52:49,440 --> 00:52:51,600
Speaker 2: lord who owns the building, who's probably the one who,

1071
00:52:51,600 --> 00:52:53,759
Speaker 2: by the way, who called in ice. What they were

1072
00:52:53,760 --> 00:52:57,960
Speaker 2: able to actually charge though, zero people out of this

1073
00:52:58,160 --> 00:53:01,360
Speaker 2: whole thing. So it's very important for people to understand

1074
00:53:01,680 --> 00:53:05,400
Speaker 2: the way that they will routinely lie and misrepresent what

1075
00:53:05,400 --> 00:53:07,359
Speaker 2: they're doing. And there was also soccer just a big

1076
00:53:07,400 --> 00:53:09,760
Speaker 2: New York Times piece backing up other reporting as well

1077
00:53:09,960 --> 00:53:14,000
Speaker 2: that because DHS has shifted their priorities, the actual you know,

1078
00:53:14,080 --> 00:53:19,120
Speaker 2: investigations into sex trafficking or human trafficking or drug dealing,

1079
00:53:19,280 --> 00:53:22,359
Speaker 2: those sorts of things have fallen by the wayside so

1080
00:53:22,400 --> 00:53:25,120
Speaker 2: that they can pick up Jose at the home depot.

1081
00:53:25,360 --> 00:53:28,239
Speaker 1: I mean, administration doesn't have credibility on this. They haven't

1082
00:53:28,239 --> 00:53:30,759
Speaker 1: a lot of credibility since Seacott, in my opinion, as

1083
00:53:30,800 --> 00:53:32,560
Speaker 1: painful for me you to say, all right, I mean,

1084
00:53:32,719 --> 00:53:35,719
Speaker 1: you know, I like I want deportation, I want law

1085
00:53:35,760 --> 00:53:37,839
Speaker 1: and order. I still think, you know, broadly, I think

1086
00:53:37,880 --> 00:53:41,200
Speaker 1: criminals and all that should be prioritized deported. And I mean, yes,

1087
00:53:41,239 --> 00:53:43,320
Speaker 1: it's great. I know the left is now now a

1088
00:53:43,400 --> 00:53:46,040
Speaker 1: refound love of deporting criminals and illegals, not that they

1089
00:53:46,080 --> 00:53:49,160
Speaker 1: ever actually wanted to under the Biden administration, but okay,

1090
00:53:49,200 --> 00:53:51,839
Speaker 1: you know, cool that we're now accepting that. It's very

1091
00:53:51,840 --> 00:53:55,760
Speaker 1: frustrating to be honest, because you're watching the entire credibility

1092
00:53:55,840 --> 00:54:00,000
Speaker 1: of the ideas behind mass deportation or deportation itself be eroded.

1093
00:54:00,200 --> 00:54:04,239
Speaker 1: This is like an abolished ice activist dream, to be honest, like,

1094
00:54:04,320 --> 00:54:07,840
Speaker 1: you know, you have more political credibility than ever before,

1095
00:54:07,880 --> 00:54:11,160
Speaker 1: and the case of immigration restriction will probably be damaged

1096
00:54:11,200 --> 00:54:14,320
Speaker 1: now for generations to come. I think that's very damaging.

1097
00:54:14,600 --> 00:54:16,440
Speaker 1: And I do blame the administration because they are the

1098
00:54:16,440 --> 00:54:20,399
Speaker 1: people who ultimately have to enact as policy. I think

1099
00:54:20,400 --> 00:54:25,560
Speaker 1: that they've cartoonishly behaved and they're creating more chaos, and

1100
00:54:25,640 --> 00:54:28,160
Speaker 1: so yeah, I mean I've just resigned. I'm like, look,

1101
00:54:28,239 --> 00:54:30,359
Speaker 1: it's I think it's over. Like, I think we've got

1102
00:54:30,360 --> 00:54:33,759
Speaker 1: three and a half years. They'll clownishly, you know, continue

1103
00:54:34,160 --> 00:54:37,160
Speaker 1: this type and then you know, do we have the

1104
00:54:37,239 --> 00:54:38,120
Speaker 1: Cernovich tweet?

1105
00:54:38,400 --> 00:54:38,560
Speaker 5: Yeah?

1106
00:54:39,320 --> 00:54:41,120
Speaker 1: Can we put C five up here on the screen.

1107
00:54:41,840 --> 00:54:44,120
Speaker 1: This has been sticking in my head only I mean

1108
00:54:44,160 --> 00:54:46,799
Speaker 1: I've also been saying it, but what he said. Mike

1109
00:54:47,040 --> 00:54:50,000
Speaker 1: is a prominent conservative activist. He says during a recent

1110
00:54:50,280 --> 00:54:52,840
Speaker 1: visit in DC, the talk of everyone was how overt

1111
00:54:52,880 --> 00:54:54,880
Speaker 1: the corruption was. It's at levels you read about in

1112
00:54:54,920 --> 00:54:58,080
Speaker 1: history books in nearly every department. Lots of do people

1113
00:54:58,120 --> 00:55:01,000
Speaker 1: just think Democrats will never win, they'll all get away

1114
00:55:01,040 --> 00:55:03,120
Speaker 1: with this. And I mean, I think this not just

1115
00:55:03,160 --> 00:55:06,439
Speaker 1: about immigration. I think about this broadly with a lot

1116
00:55:06,520 --> 00:55:08,640
Speaker 1: of the administration. And you can make fun of ask

1117
00:55:09,040 --> 00:55:12,240
Speaker 1: you can make fun all you want. There were lots

1118
00:55:12,360 --> 00:55:16,040
Speaker 1: of well meaning people in the election who voted for

1119
00:55:16,360 --> 00:55:21,719
Speaker 1: legitimate immigration concerns, and ultimately, you know, the crime for

1120
00:55:21,880 --> 00:55:25,160
Speaker 1: people who use those, you know, to then not only

1121
00:55:25,239 --> 00:55:28,640
Speaker 1: enrich themselves but do damage to the cause. It's devastating.

1122
00:55:28,680 --> 00:55:30,920
Speaker 1: I mean, it's one of those where like, look, you know,

1123
00:55:30,960 --> 00:55:33,719
Speaker 1: if you think back for I don't know, let's say

1124
00:55:33,719 --> 00:55:37,319
Speaker 1: Biden any you know, if you believed in those types

1125
00:55:37,360 --> 00:55:39,319
Speaker 1: of politics and then you have a bad leader and

1126
00:55:39,360 --> 00:55:42,440
Speaker 1: a bad administration who does tremendous justice, Like that's a

1127
00:55:42,840 --> 00:55:45,120
Speaker 1: you know, like that's criminal, right actually, because it's really

1128
00:55:45,160 --> 00:55:48,000
Speaker 1: a lot of voters and others, And we talked yesterday

1129
00:55:48,040 --> 00:55:51,479
Speaker 1: about the whole fuenttes like racialism thing. I mean, they're

1130
00:55:51,480 --> 00:55:54,799
Speaker 1: doing everything in their power to try and basically like

1131
00:55:55,120 --> 00:55:59,120
Speaker 1: basically empower this like racialist view of the world. Basically

1132
00:55:59,120 --> 00:56:02,080
Speaker 1: at this point, yeah, I mean, it's honestly, like it's

1133
00:56:02,120 --> 00:56:05,279
Speaker 1: really depressing because what it does show you is how

1134
00:56:05,360 --> 00:56:08,279
Speaker 1: cartoonish like the behavior here is. And look, I'm not

1135
00:56:08,280 --> 00:56:10,200
Speaker 1: going to deny they're real people's lives who are also

1136
00:56:10,280 --> 00:56:12,800
Speaker 1: at stake here. Yeah, I mean, I you know, maintain

1137
00:56:13,440 --> 00:56:15,719
Speaker 1: even if you're quote not a criminal and you became

1138
00:56:15,719 --> 00:56:18,120
Speaker 1: here illegally, I still think you should be deported. But

1139
00:56:18,400 --> 00:56:20,520
Speaker 1: you know, good luck making that argument in the future.

1140
00:56:20,560 --> 00:56:23,680
Speaker 1: If people look at Blackhawk helicopters and all this other stuff,

1141
00:56:23,680 --> 00:56:24,839
Speaker 1: they're going to say at the end of the day,

1142
00:56:24,840 --> 00:56:27,040
Speaker 1: I'm not willing to make that trade off. I'll continue

1143
00:56:27,040 --> 00:56:29,040
Speaker 1: to make the case. I still believe it. But if

1144
00:56:29,040 --> 00:56:31,080
Speaker 1: this is the way that it actually, it's kind of

1145
00:56:31,120 --> 00:56:33,920
Speaker 1: like when people try to defend socialism or whatever, and

1146
00:56:33,960 --> 00:56:36,080
Speaker 1: everyone's always like, well, if you know, look at has

1147
00:56:36,120 --> 00:56:39,239
Speaker 1: it ever worked before? Right? If the practical example that

1148
00:56:39,360 --> 00:56:41,680
Speaker 1: anyone in modern memory can have of this, they're going

1149
00:56:41,719 --> 00:56:45,440
Speaker 1: to be deeply skeptical for generations to come. And I

1150
00:56:45,480 --> 00:56:48,720
Speaker 1: think that, you know, I think my friend Raihan Salam

1151
00:56:48,840 --> 00:56:51,759
Speaker 1: wrote this years ago about Trump and maybe he was right.

1152
00:56:51,920 --> 00:56:54,040
Speaker 1: He wrote it back in twenty fifteen. He's like an

1153
00:56:54,120 --> 00:56:56,960
Speaker 1: og immigration restrictionist and he was like, I think Trump

1154
00:56:57,000 --> 00:56:58,960
Speaker 1: will do damage to the cause for you. I actually

1155
00:56:59,040 --> 00:57:00,799
Speaker 1: ridiculed him at the time. I'm like, well, he's the

1156
00:57:00,800 --> 00:57:02,560
Speaker 1: only one who won, and you know now he won

1157
00:57:02,640 --> 00:57:05,600
Speaker 1: again in twenty twenty four. But perhaps he's been vindicated

1158
00:57:05,719 --> 00:57:06,359
Speaker 1: in the long run.

1159
00:57:06,760 --> 00:57:10,120
Speaker 3: Interesting, speaking of that corruption piece, puts C four up

1160
00:57:10,120 --> 00:57:10,560
Speaker 3: on the screen.

1161
00:57:10,600 --> 00:57:12,320
Speaker 1: It's just kind shit, like, I mean, it's.

1162
00:57:12,200 --> 00:57:14,799
Speaker 2: Just crazy Christy Noam, who loves to do these friaking

1163
00:57:14,840 --> 00:57:18,800
Speaker 2: photo shoots and is just an embarrassing person in general alone.

1164
00:57:18,880 --> 00:57:21,200
Speaker 2: Behold pro Publica. By the way, it's been doing some

1165
00:57:21,320 --> 00:57:24,200
Speaker 2: very good reporting. Firm tied to Christy Nooms. Secretly it

1166
00:57:24,240 --> 00:57:30,040
Speaker 2: got money from two hundred twenty million dollar dhs AD contracts.

1167
00:57:30,400 --> 00:57:33,040
Speaker 2: What I mean, what do we even need dhs ads for?

1168
00:57:33,240 --> 00:57:33,920
Speaker 3: To begin with?

1169
00:57:34,280 --> 00:57:36,400
Speaker 2: You guys want to see what these ads look like,

1170
00:57:36,480 --> 00:57:38,320
Speaker 2: and then I can tell you more about the details

1171
00:57:38,360 --> 00:57:40,360
Speaker 2: of this firm and who all is involved with it.

1172
00:57:40,560 --> 00:57:42,120
Speaker 3: Let's go and play CE six.

1173
00:57:42,320 --> 00:57:44,640
Speaker 2: This is one of the ads that this firm was

1174
00:57:44,640 --> 00:57:48,040
Speaker 2: involved with creating.

1175
00:57:48,360 --> 00:57:51,600
Speaker 7: Why do I love these wide open spaces? They remind

1176
00:57:51,600 --> 00:57:54,320
Speaker 7: me of why our forefathers came here, not just for

1177
00:57:54,360 --> 00:57:57,520
Speaker 7: its beauty, but for the freedom only America provides.

1178
00:57:57,960 --> 00:57:58,919
Speaker 1: I'm Christy Noman.

1179
00:57:59,800 --> 00:58:02,760
Speaker 7: The cowboys who tame the West, to the Titans who

1180
00:58:02,760 --> 00:58:06,440
Speaker 7: built our cities, to the dreamers who chase the impossible.

1181
00:58:07,480 --> 00:58:12,600
Speaker 7: America has always rewarded vision and grit. Our greatness calls

1182
00:58:12,640 --> 00:58:15,840
Speaker 7: people to us for a chance to prosper, to live

1183
00:58:15,920 --> 00:58:20,200
Speaker 7: how they choose, to become part of something special. Anyone

1184
00:58:20,200 --> 00:58:22,680
Speaker 7: who searches for freedom can always find a home here.

1185
00:58:23,080 --> 00:58:26,680
Speaker 7: But that freedom's a precious thing and we defend it vigorously.

1186
00:58:27,600 --> 00:58:31,000
Speaker 7: You cross the border illegally, we'll find you break our

1187
00:58:31,080 --> 00:58:34,520
Speaker 7: laws will punish you harm American citizens.

1188
00:58:35,040 --> 00:58:38,120
Speaker 1: There will be consequences. But if you come here.

1189
00:58:38,000 --> 00:58:41,040
Speaker 7: The right way, your American dream can be as big

1190
00:58:41,280 --> 00:58:44,080
Speaker 7: as these endless guys from President Trump.

1191
00:58:43,840 --> 00:58:45,240
Speaker 1: And me, welcome home.

1192
00:58:46,160 --> 00:58:48,440
Speaker 3: Okay, So I had noticed up deal.

1193
00:58:48,480 --> 00:58:50,960
Speaker 1: I'd noticed some of these ads. This is a little weird,

1194
00:58:51,040 --> 00:58:53,920
Speaker 1: A little weird. Yeah, Well, because on Fox News in particular,

1195
00:58:54,040 --> 00:58:55,880
Speaker 1: they'd be like, you need to leave, and I was like,

1196
00:58:55,880 --> 00:58:58,120
Speaker 1: how many illegals are watching Fox News? I mean, I'm

1197
00:58:58,120 --> 00:59:00,560
Speaker 1: only watching Fox News because I have to for work.

1198
00:59:00,840 --> 00:59:03,160
Speaker 2: I really think that some ad of Christina I'm and

1199
00:59:03,200 --> 00:59:05,480
Speaker 2: a horse is like going to change your.

1200
00:59:05,240 --> 00:59:06,520
Speaker 3: Decision about where I mean.

1201
00:59:06,440 --> 00:59:10,000
Speaker 2: It's just it's a total vanity project. She, like probably

1202
00:59:10,160 --> 00:59:12,960
Speaker 2: many others, wants to run for president, I assume. And

1203
00:59:13,000 --> 00:59:15,640
Speaker 2: so this is a way they've flooded the big beautiful bill,

1204
00:59:15,920 --> 00:59:21,919
Speaker 2: flooded DHS and ICE with just insane amounts of cash.

1205
00:59:21,960 --> 00:59:23,439
Speaker 2: And so this is the type of shit that they're

1206
00:59:23,440 --> 00:59:26,280
Speaker 2: doing with it, this little ad campaign, which, by the way,

1207
00:59:26,840 --> 00:59:30,920
Speaker 2: so to again, two hundred twenty million dollars. They kept

1208
00:59:31,240 --> 00:59:34,600
Speaker 2: one beneficiary of the nine figure ad deal a secret,

1209
00:59:34,640 --> 00:59:38,800
Speaker 2: according to Pro Publica records, and interviews show a Republican

1210
00:59:38,800 --> 00:59:42,440
Speaker 2: consulting firm with long standing personal and business ties to

1211
00:59:42,560 --> 00:59:45,320
Speaker 2: know them, and her senior aids at DHS. The company

1212
00:59:45,400 --> 00:59:48,320
Speaker 2: running the Mount Rushmore shoot, called the Strategy Group, does

1213
00:59:48,360 --> 00:59:51,120
Speaker 2: not appear on public documents about the contract. The main

1214
00:59:51,160 --> 00:59:54,440
Speaker 2: recipient listed on the contracts is a mysterious Delaware company

1215
00:59:54,440 --> 00:59:57,680
Speaker 2: which was created days before the deal was finalized. No

1216
00:59:57,880 --> 01:00:01,240
Speaker 2: firm has closer ties to nomes. Political operation in the

1217
01:00:01,320 --> 01:00:03,919
Speaker 2: Strategy Group played a central role in her twenty twenty

1218
01:00:03,920 --> 01:00:08,600
Speaker 2: two South Dakota gubernatorial campaign. Corey Lewandowski, who is not

1219
01:00:08,640 --> 01:00:10,920
Speaker 2: only her top advisor at DHS, which is the part

1220
01:00:10,920 --> 01:00:13,600
Speaker 2: they put in here, is also her rumored boyfriend, has

1221
01:00:13,640 --> 01:00:16,360
Speaker 2: worked extensively with the firm, and the company's CEO is

1222
01:00:16,560 --> 01:00:20,440
Speaker 2: married to noam's chief spokesperson, Tricia McLaughlin.

1223
01:00:20,640 --> 01:00:23,120
Speaker 3: So there you go. Strategy Group's ad work is.

1224
01:00:23,040 --> 01:00:25,400
Speaker 2: The first known example of money flowing from Nome's agency

1225
01:00:25,440 --> 01:00:29,320
Speaker 2: to businesses controlled by her allies and friends. And you know,

1226
01:00:29,440 --> 01:00:33,720
Speaker 2: there's there's this now secret why they decided to hide

1227
01:00:33,720 --> 01:00:38,360
Speaker 2: this because it is blatantly and clearly, disgustingly corrupt and

1228
01:00:38,960 --> 01:00:41,160
Speaker 2: just you know, total cash grab at every level.

1229
01:00:41,160 --> 01:00:42,880
Speaker 3: Of this administration. And it's true.

1230
01:00:42,880 --> 01:00:45,440
Speaker 2: You know, I keep thinking about Steve Bannon telling I

1231
01:00:45,480 --> 01:00:47,400
Speaker 2: don't remember what conference he was at. He was like,

1232
01:00:47,480 --> 01:00:49,720
Speaker 2: you know, if the Democrats get back in power, some

1233
01:00:49,800 --> 01:00:51,680
Speaker 2: of us are going to prison. Now I don't think

1234
01:00:51,880 --> 01:00:54,040
Speaker 2: you know, Bannon's already been in prison. I'm not aware

1235
01:00:54,040 --> 01:00:55,960
Speaker 2: of him committing any new crimes, so he's not at

1236
01:00:55,960 --> 01:00:58,520
Speaker 2: the top of my list. But like, yes, this level

1237
01:00:58,520 --> 01:01:02,280
Speaker 2: of corrupt dealing, it should be punished, the level of lawlessness,

1238
01:01:02,280 --> 01:01:04,480
Speaker 2: like when crimes are broken. I do think that some

1239
01:01:04,520 --> 01:01:08,560
Speaker 2: of these officials should fear for their freedom after this

1240
01:01:08,680 --> 01:01:11,760
Speaker 2: administration is through, because I can tell you the Democratic

1241
01:01:11,800 --> 01:01:13,880
Speaker 2: base is going to be looking for a candidate in

1242
01:01:13,920 --> 01:01:16,680
Speaker 2: twenty twenty eight who is willing to say Steven Miller

1243
01:01:16,720 --> 01:01:18,040
Speaker 2: and Christy nom should be in jail.

1244
01:01:18,440 --> 01:01:20,920
Speaker 1: I mean, you know, I can't say you weren't warned.

1245
01:01:21,120 --> 01:01:24,080
Speaker 1: And yes, if you cartoonishly disregard the law, I mean

1246
01:01:24,120 --> 01:01:28,160
Speaker 1: in Kirsty Nomes case or Stephen Miller, even if my

1247
01:01:28,280 --> 01:01:30,720
Speaker 1: opinion is what's going to happen is Trump on his

1248
01:01:30,760 --> 01:01:33,640
Speaker 1: way out will do the Hunter Biden thing, the preemptive

1249
01:01:33,640 --> 01:01:36,040
Speaker 1: pardon for any and all whatever, and so no I

1250
01:01:36,040 --> 01:01:39,560
Speaker 1: don't think anybody's going to prison, but whenever it comes

1251
01:01:39,600 --> 01:01:43,440
Speaker 1: to investigations in the interim. What a lot of people

1252
01:01:43,440 --> 01:01:46,160
Speaker 1: don't know is that the government doesn't pay, let's say,

1253
01:01:46,160 --> 01:01:49,320
Speaker 1: for your legal fees, like when you get called before Congress,

1254
01:01:49,440 --> 01:01:53,560
Speaker 1: especially if it's on a private matter, and so many officials.

1255
01:01:53,640 --> 01:01:55,680
Speaker 1: This happened in the Clinton administration, this happened in the

1256
01:01:55,720 --> 01:01:58,880
Speaker 1: first Trump administration. You'll remember I said this during Doge.

1257
01:01:58,920 --> 01:02:01,040
Speaker 1: I was like, man, I hope you got or you know,

1258
01:02:01,120 --> 01:02:03,680
Speaker 1: Elon will be fine, he's rich. Everybody else I'm like,

1259
01:02:03,840 --> 01:02:07,200
Speaker 1: you better lawyer up, because when the Dems come calling

1260
01:02:07,320 --> 01:02:10,760
Speaker 1: in the House Oversight Committee with subpoenas, these guys charge

1261
01:02:10,800 --> 01:02:13,400
Speaker 1: like one thousand dollars an hour, and sometimes they can

1262
01:02:13,440 --> 01:02:16,880
Speaker 1: take a twelve to fifteen hours for transcripts and for interviews,

1263
01:02:16,880 --> 01:02:19,800
Speaker 1: and you need a council in the room that entire time,

1264
01:02:20,000 --> 01:02:23,120
Speaker 1: or when you're calling before like the level. Look, it's

1265
01:02:23,520 --> 01:02:26,160
Speaker 1: that's what That's how government has worked now basically since

1266
01:02:26,360 --> 01:02:29,160
Speaker 1: the Kenneth Star affair. Like every time the opposition party,

1267
01:02:29,320 --> 01:02:31,480
Speaker 1: no matter who it is, is in power, they try

1268
01:02:31,520 --> 01:02:34,840
Speaker 1: to do investigations and subpoena power and all that and yes,

1269
01:02:34,920 --> 01:02:38,840
Speaker 1: there's a huge political incentive. So if you're see Christy Nome,

1270
01:02:39,040 --> 01:02:41,040
Speaker 1: I think she'll probably figure it out. Donors, if you're

1271
01:02:41,120 --> 01:02:44,040
Speaker 1: Trisia McLaughlin or like one of the junior people, those

1272
01:02:44,040 --> 01:02:45,400
Speaker 1: are the ones where I'm like, I would be very

1273
01:02:45,480 --> 01:02:46,560
Speaker 1: worried if I were.

1274
01:02:46,480 --> 01:02:48,520
Speaker 2: You, or you know some of these ICE guys who

1275
01:02:48,520 --> 01:02:52,240
Speaker 2: are out on the street, like, just because Steve Miller

1276
01:02:52,320 --> 01:02:54,000
Speaker 2: or Greg Bavin or whatever told you to do it

1277
01:02:54,000 --> 01:02:56,600
Speaker 2: doesn't mean that you're totally protective. And this actually duvetails

1278
01:02:56,600 --> 01:02:59,000
Speaker 2: into the Venezuela segment we're about to do. Or some

1279
01:02:59,080 --> 01:03:01,680
Speaker 2: of these militaries are VIS members who are being tasked

1280
01:03:01,680 --> 01:03:04,120
Speaker 2: with like murdering random people in the Caribbean or in

1281
01:03:04,160 --> 01:03:07,960
Speaker 2: the Pacific. Are seeking outside legal councils because they are

1282
01:03:08,000 --> 01:03:10,760
Speaker 2: concerned about their own legal liability and they do not

1283
01:03:10,880 --> 01:03:13,160
Speaker 2: trust the guidance that they're getting within the administration.