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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 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.

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Speaker 2: Good morning, everybody, Happy Monday. Welcome to Breaking Points.

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Speaker 3: Emily. Great to see you.

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Speaker 4: It's great to be here. Happy Monday, everyone. We have

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Speaker 4: a big show. The New York City mayoral election is

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Speaker 4: coming up, and we have some pictures video from a

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Speaker 4: giant rally that happened last night, actually on the year

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Speaker 4: anniversary of Trump's Madison Square Garden rally.

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Speaker 3: I didn't know that.

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Speaker 4: I think today is the anniversary of the Madison Square

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Speaker 4: Garden rally.

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Speaker 3: And have to think about what that means.

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Speaker 2: I think Zoranda that I'm purpose with the astrology of

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Speaker 2: that means, Yeah, a bunch of news in the show.

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Speaker 3: So we've got potential trade deal with China we're going

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Speaker 3: to get to.

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Speaker 2: We've got trade tensions with Canada over some Ronald Reagan

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Speaker 2: at I have a lot of thoughts about that one.

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Speaker 2: We're tracking the government shutdown troops on the verge of

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Speaker 2: not getting paid. A weird anonymous donor who we just

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Speaker 2: learned who they are, came in to pay like a

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Speaker 2: small portion. Anyway, weird stuff going on there. Candas Zones

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Speaker 2: apparently thanks Peter Chiel is not human and Elon Musk

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Speaker 2: and Sam Oltman I think we're the three that she

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Speaker 2: named checked in particular, So.

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Speaker 4: That may weigh on your mind as you determined whether

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Speaker 4: Brigitte Macron is or is not a woman because Candace Batting,

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Speaker 4: I don't know, maybe five hundred on some of these

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Speaker 4: some of these diagnoses.

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Speaker 2: Yeah, I guess I'm becoming more persuaded of Candace fun

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Speaker 2: a variety of things with this new tape. So anyway,

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Speaker 2: a lot that's going on there. Binance CEO pardoned in

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Speaker 2: a corrupt deal, the aforementioned zoron rally plus and being

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Speaker 2: attacked aggressively by any number of corners from Democrats and

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Speaker 2: Republicans for his musliming and cream. Jean Pierre is out

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Speaker 2: with a new book and it is really something, and

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Speaker 2: the wash Int Post review of it gathing, did you

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Speaker 2: read this whole thing? Oh my gosh, I sort of

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Speaker 2: want to read all it's a little too long to

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Speaker 2: just read the whole thing out. But whoever wrote this

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Speaker 2: is not a person I was like really familiar with.

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Speaker 2: She had took a phenomenal job just taking apart not

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Speaker 2: just creing John Pierre, but this particular style of like

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Speaker 2: self congratulatory, decorum liberalism.

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Speaker 4: Yeah, the review is about so much more than KJP.

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Speaker 4: It's about this era in our politics. And reading the

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Speaker 4: review and we'll get into this, of course, it's sort

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Speaker 4: of like a window into the last decade, and you

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Speaker 4: can kind of feel like this is an era that

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Speaker 4: is over, like a chapter that's over. So it's actually

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Speaker 4: a good block to do after the Zorn block.

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Speaker 2: Maybe yeah, oh yeah, that's a good point. Good point

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Speaker 2: that works well. So we've got a lot in the show.

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Speaker 2: We're going to try to get to all of it,

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Speaker 2: especially because I only really wants to talk about the

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Speaker 2: kjppiece that we're going to try to keep these blocks

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Speaker 2: from meandering too long, you know, as the ladies like.

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Speaker 4: To just ladyship are low, and then we'll have only

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Speaker 4: our selves to blame.

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Speaker 2: Yes, indeed, all right, so let's go ahead and get

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Speaker 2: to this potential Chinese trade deal. Our negotiators have been

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Speaker 2: talking to their negotiators. Scott Bessen is saying that it's

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Speaker 2: looking good. Trump is supposed to meet with she later

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Speaker 2: this week, and so he was making the rounds of

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Speaker 2: the Sunday shows.

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Speaker 3: He got asked specifically.

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Speaker 2: About soybeans because this has been a huge sore, sore spot,

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Speaker 2: that's the words. I'm looking for, a sore spot for

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Speaker 2: American farmers, you know, major problem. The Argentina thing ties

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Speaker 2: into that as well. And so in any case, he

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Speaker 2: gets asked about this and reveals something I was not

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Speaker 2: aware of, which is he too, is actually a soybean farmer.

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Speaker 3: Let's take a listen.

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Speaker 4: China has been boycotting American soybeans, and American farmers have

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Speaker 4: really suffered.

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Speaker 5: Do you see a.

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Speaker 6: Real light at the end of the tunnel there that

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Speaker 6: may allow soybeans again?

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Speaker 7: Well, Martha, in case you don't know what. I'm actually

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Speaker 7: a soybean farmer, so I have felt this pain too.

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Speaker 7: And there are a couple of things happening here. One,

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Speaker 7: the Chinese have substantially dropped their purchases to almost zero,

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Speaker 7: so they unfortunately have been using American farmers, who are

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Speaker 7: amongst President Trump's biggest supporters. I think he had more

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Speaker 7: than ninety percent support, and then this was one of

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Speaker 7: the biggest crops in twenty or thirty years, so it

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Speaker 7: was a perfect storm. But I think we have addressed

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Speaker 7: the farmer's concerns. And I'm not going to get ahead

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Speaker 7: of the president, but I believe when the announcement of

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Speaker 7: the deal with China is made public that our soybean

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Speaker 7: farmers will feel very good about what's going on.

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Speaker 2: So never fear American farmers. Treasury Secretary billionaire Scott Besant

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Speaker 2: is a bit of a soybean farmer himself and is

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Speaker 2: feeling the pain here too.

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Speaker 5: Is he worth a billionaires? Who liked five hundred million?

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Speaker 3: He is thought he was a billionaire, but maybe I'll

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Speaker 3: double check.

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Speaker 5: Exorbitantly wealthy, You're.

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Speaker 3: A multi hundred millionaire potentially, right.

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Speaker 4: And so actually, what's kind of interesting about that clipp

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Speaker 4: is first of all, this is why people should divest

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Speaker 4: their financial interests so that you are quote feeling the pain,

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Speaker 4: because that obviously creates different interests that could be influencing

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Speaker 4: the way you do policy. I'm actually not saying that's

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Speaker 4: the case in Scott Vessens position here, although the Argentinian

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Speaker 4: beef saga, which we're going to get into, seems like

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Speaker 4: the Argentinian soybean situation had a little bit to do

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Speaker 4: with maybe Scott Besson's interest is Ryan and I covered

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Speaker 4: and we interviewed in Argentinian.

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Speaker 5: Journalists about all of that.

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Speaker 4: But the other thing is a lot of these like

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Speaker 4: quote soybean farmers are just exorbitantly also exorbitantly wealthy, big

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Speaker 4: agg people, and so that's another important part of this,

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Speaker 4: and I suspect we'll get to it with our guests

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Speaker 4: as well.

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Speaker 2: Yeah, that's a great point. Let's go and put a

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Speaker 2: two up on the screen. Just we don't know a

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Speaker 2: lot about this potential deal. I mean, it's not even

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Speaker 2: been inked yet, but they're describing this as a positive

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Speaker 2: framework which has been agreed to prior to this Trump

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Speaker 2: g summit. Some of the pieces obviously that are being

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Speaker 2: watched with close interest are the soybean piece, some sort

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Speaker 2: of agreement with regard to Sentinel and the Sentinel precursors

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Speaker 2: that come from China.

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Speaker 3: And then in addition, the.

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Speaker 2: Rare earth export controls which China had been you know, threatening,

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Speaker 2: which could just like completely tank or entire economy which

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Speaker 2: is just one giant bet on Ai. So the rare

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Speaker 2: earth mineral situation very critical. I think, you know, some

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Speaker 2: of the leverage that was applied there from China is

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Speaker 2: probably part of what is helping to potentially bring this

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Speaker 2: deal together at this point.

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Speaker 4: Yeah, and I mean, the importance of China to the

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Speaker 4: soybean market can't possibly understate it. It's so crucial and significant.

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Speaker 4: And so Trump is also in Japan today. He just

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Speaker 4: he already touched on in Japan, and he'll be going

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Speaker 4: to South Korea. He's already trying to meet with Kim

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Speaker 4: Jong un, which has nothing to do with soybeans, of course,

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Speaker 4: But this entire swing is to shore up deals that

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Speaker 4: since Liberation Day on that was a April second, April first,

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Speaker 4: April second.

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Speaker 5: They didn't want to do it in April Fool's Day.

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Speaker 5: This is how many months? Six months? And here's the tour.

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Speaker 5: I try to shore up some.

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Speaker 4: Of these deals and get specifics down and make it

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Speaker 4: work for Americans.

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Speaker 2: Yeah, indeed, And at the same time there's a new

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Speaker 2: blow up with regard to Canada. I mean, this is

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Speaker 2: just like typical trumpy and the dumbest thing possible.

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Speaker 3: The whole thing is extremely annoying to me.

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Speaker 2: So Ontario launched this ad buy that featured snippets from

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Speaker 2: a Ronald Reagan's speech where he's talking about how tariffs

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Speaker 2: are bad.

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Speaker 3: Right, Reagan being you.

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Speaker 2: Know, the like neoliberal, you know, the trickle down economics

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Speaker 2: guy whatever, not my economic cup of tea. And part

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Speaker 2: of why me and Sager and I think you and

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Speaker 2: Brian have been pissed off at the incredibly stupid way

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Speaker 2: that Trump has gone about doing terror US because it

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Speaker 2: has created this reaction of just like, oh, the tariffs

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Speaker 2: in general must be bad, and it's like, well, no,

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Speaker 2: they're a tool that can be used with industrial policy,

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Speaker 2: that can be effective. But anyway you get from Canada

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Speaker 2: this Ronald Reagan speech ad where he's talking about tariffs,

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Speaker 2: and this apparently deeply upset President Trump.

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Speaker 3: So let's take a listen first to the ad.

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Speaker 8: When someone says let's impose tariffs on foreign imports. It

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Speaker 8: looks like they're doing the patriotic thing by protecting American

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Speaker 8: products and jobs. And sometimes for a short while it works,

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Speaker 8: but only for a short time.

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Speaker 9: But over the long.

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Speaker 8: Run, such trade barriers hurt every American worker and consumer.

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Speaker 8: High tariffs inevitably lead the retaliation by foreign countries and

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Speaker 8: the triggering of fierce trade wards. Then the worst happens.

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Speaker 8: Marcus shrink can collapse, businesses and industry shutdown, and millions

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Speaker 8: of people lose their jobs. Throughout the world, there's a

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Speaker 8: growing realization that the weight of prosperity for oral nations

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Speaker 8: is rejecting protectionist legislation and promoting fair and free competition.

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Speaker 8: America's jobs and growth are at stake.

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Speaker 2: This was very upsetting to Trump a four up on

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Speaker 2: the screen, and we should say too by the way,

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Speaker 2: I mean what Reagan is articulating. There was like the

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Speaker 2: standard free trade orthodoxy that reigned in this town up

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Speaker 2: until quite recently, and you know, really starts to break

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Speaker 2: under Trump.

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Speaker 3: Biden moves in.

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Speaker 2: That direction as well, and then we've had you know,

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Speaker 2: Trump two point zero where they've just done all kinds

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Speaker 2: of wild things. But in any case Trump on true

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Speaker 2: social size. The Ronald Reagan Foundation has just announced that

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Speaker 2: Canada has fraudulently used an advertisement which is fake featuring

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Speaker 2: Ronald Reagan speaking negatively about Tariff's to add U was

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Speaker 2: for seventy five million dollars. They only did this to

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Speaker 2: interfere with the decision of the US Supreme Court in

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Speaker 2: other courts, tariffs are very important to the national security

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Speaker 2: and economy of the USA. Based on their egregious behavior,

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Speaker 2: all trade negotiations with Canada are hereby terminated. Thank you

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Speaker 2: for your attention to this matter, President DJT and Emily.

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Speaker 2: He went on from there to announce that they were

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Speaker 2: going to levy an additional across the board ten percent

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Speaker 2: tariff on all Canadian goods, and.

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Speaker 4: He said he doesn't think he's going to be meeting

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Speaker 4: with Mark Carney again anytime soon now. Reagan is such

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Speaker 4: an interesting case study because Reagan was criticized relentlessly by

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Speaker 4: the hyper neoliberals at the time for putting Tariff's very

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Speaker 4: protectionist tariffs on Japan, and so Reagan is the worst

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Speaker 4: possible case study for the Doug Fords of the world.

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Speaker 4: He's in charge of Ontario, Rob Ford the Great, Rob

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Speaker 4: Ford's brother to embrace, because again, like there's a lot

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Speaker 4: of daylight between Trump's tariff policy and Raygan's the tariff policy.

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Speaker 4: But the particular example of Canada actually is instructive because

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Speaker 4: the rebalancing of the trade relationship with Canada is something

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Speaker 4: that almost everyone except for the most like libertarian minded

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Speaker 4: person would tell you was completely necessary.

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Speaker 5: And so for.

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Speaker 4: Canada to deploy Reagan in that way, it's just it's

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Speaker 4: like insulting on a million different levels. But it's especially

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Speaker 4: stupid when you think about what the relationship with what

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Speaker 4: the what the US trade relationship with Canada looked like,

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Speaker 4: Like what.

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Speaker 5: Do they want?

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Speaker 4: They want just like completely they want what they were

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Speaker 4: used to, like what you were saying.

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Speaker 2: Well, and Rob Ford is an interesting character because he's

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Speaker 2: a very kind of like Trumpian figure.

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Speaker 5: Doug Ford. Rob is the brother. They look exactly like.

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Speaker 3: They look a similar character.

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Speaker 2: I mean Rob was wilder, for sure, but but Doug

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Speaker 2: Ford is uh, you know, Trumpian type of character, very bombastic,

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Speaker 2: very nationalist in his way. And so it's also worth

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Speaker 2: remembering like this wasn't this actually wasn't Mark Carney, you know,

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Speaker 2: this wasn't the whole of Canada, right, this is this

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Speaker 2: one province that decided to spend this this money. And

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Speaker 2: by the way, again, the idea is this for this

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Speaker 2: to play in American markets, which is what pissed Trump.

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Speaker 2: But then you know you have Trump using like the

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Speaker 2: powers of a king to just like he's pissed off,

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Speaker 2: so separate and apart from any economic pretext even he's

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Speaker 2: just like, I don't like your ad. So now the

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Speaker 2: entire country is going to be tear of ten percent,

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Speaker 2: which those costs Guess what? Guess who pays those consumers

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Speaker 2: and disproportionately working class consumers in the US who will

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Speaker 2: now bear the cost of Trump just being like annoyed

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Speaker 2: over this stupid Ronald Reagan ad. Scott Bessett was of

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Speaker 2: course asked about this on the Sunday shows as well,

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Speaker 2: and didn't have a lot of answers about, Okay, well,

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Speaker 2: what are we talking about? Is a ten percent truly

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Speaker 2: across the border? They're going to be any exceptions, etc.

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Speaker 2: Let's go ahead and take a listen to what he

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Speaker 2: had to say.

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Speaker 10: Why is the president setting trade policy based on a

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Speaker 10: television ad he doesn't like?

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Speaker 7: Well, Kristen, let's think about this, This is a kind

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Speaker 7: of propaganda against US citizens. It's psyops. Why would the

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Speaker 7: government of Ontario, I'm told that they've spent they have

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Speaker 7: spent or we're planning to spend up to seventy five

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Speaker 7: million dollars on these ads to come across the US order.

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Speaker 7: So what was the purpose of that other than to

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Speaker 7: sway public opinion? And you know, it's some kind of

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Speaker 7: propaganda that the Premiere of Ontario unilaterally launched.

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Speaker 10: Will the ten percent tariffs apply to all Canadian goods?

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Speaker 5: Mister Secretary.

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Speaker 7: Christina, I've been traveling since this unfortunate event happened. I

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Speaker 7: know that the AD's been taken down, So you know,

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Speaker 7: we'll have to see.

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Speaker 10: Does the President know if the tariffs will apply to

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Speaker 10: ten percent tariffs will apply to all Canadian goods? Has

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Speaker 10: he made a determination about that?

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Speaker 7: Well, well, I'm sure he. I'm sure he knows, and

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Speaker 7: I'm sure the Ambassador of Greer knows.

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Speaker 2: I'm sure he knows, but I don't really know, so

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Speaker 2: can as your quest.

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Speaker 5: That says it all? That says it all. I'm sure

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Speaker 5: he knows, and.

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Speaker 2: But I'm not sure that he is sure that he knows,

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Speaker 2: you know, like he's probably go oh, maybe now, but

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Speaker 2: he's probably didn't really think it through.

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Speaker 3: He's just like, yeah, turn percent, I'm pissed off.

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Speaker 2: And like that's as much as the that's as much

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Speaker 2: of the thinking as goes into this.

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Speaker 4: I mean, the billions of dollars that are on the

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Speaker 4: line with these whims is it's truly I mean use

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Speaker 4: the word king, but like that's why tariffs are supposed

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Speaker 4: to go through Congress right the most part, or they

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Speaker 4: were originally supposed to go through Congress for the most part,

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Speaker 4: because there's just i mean, you're your entire this is

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Speaker 4: this is planning of the economy. And obviously there's more

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Speaker 4: to the economy than tariffs. But in a lot of cases,

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Speaker 4: some of the downstream stuff that we talk about taxes

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Speaker 4: and the like actually are coming like the tariffs. So

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Speaker 4: the first part of this, it's like how much business

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Speaker 4: can you do in the United States? What kind of

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Speaker 4: business can you do at what cost in the United States?

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Speaker 4: So other stuff when it comes bacon out of planning

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Speaker 4: in many cases a downstream of the tariffs, and so

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Speaker 4: you have the you got the executive on a whim.

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Speaker 4: The ad is the best example of this because we

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Speaker 4: know that it's happened before, like even with Doug Ford.

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Speaker 4: There's been back and forth with Trump and sort of

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Speaker 4: these these capricious teriffs.

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Speaker 5: But that's Trump's point, is that.

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Speaker 4: And I think for the first month, like post April

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Speaker 4: second whatever, it was this uncertainty that Trump was using

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Speaker 4: it as his leverage kind of made sense because people

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Speaker 4: were like, whoa, we have no idea what's coming.

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Speaker 5: Let's like they were forced to the table.

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Speaker 4: But the longer the uncertainty goes on, people don't have

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Speaker 4: to necessarily come to the table because they say it's

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Speaker 4: not a good bet, like that, I'm betting on what

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Speaker 4: I don't know. And it's Trump never made it clear

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Speaker 4: what he's actually looking for, in particular from these other countries.

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Speaker 4: So yeah, it's it's it's either one side of the

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Speaker 4: spectrum or the other. Like Canada either wants their fantasy

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Speaker 4: of Reagan era free trade or they want they want

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Speaker 4: some certainty from Trump as to what he's looking for

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Speaker 4: on that.

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Speaker 2: Yeah, good and good luck with that. And that's why

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Speaker 2: you end up betting. Secretary doesn't have that, yeah.

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Speaker 4: Right, which is where people end up betting in the

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Speaker 4: other direction, because you don't have the certainty.

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Speaker 2: Yeah, well, Bessen and his hedge fund buddies should be

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Speaker 2: happy with the results.

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Speaker 3: In Argentina last night. I don't know if you tried,

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Speaker 3: Malay's party secured.

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Speaker 2: I think forty percent of the vote pretty easy one so,

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Speaker 2: and I mean basically what happened here is Malay's party

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Speaker 2: suffered some losses in local elections, and it looked like

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Speaker 2: the public was turning against you know, I hesitate to

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Speaker 2: call libertarian at this point when you get bailouts from

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Speaker 2: all kinds of including our country around the world. But

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Speaker 2: you know, it was looking like the argent the Argentine

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Speaker 2: Tenian public was turning on this project. And then the

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Speaker 2: Trump administration comes in and says basically like, Okay, we're

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Speaker 2: going to bail you out, but if you don't vote

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Speaker 2: the way that we want you to, we're going to.

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Speaker 3: Screw you over.

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Speaker 2: I mean, there's an overt threat that was made, and

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Speaker 2: it appears that the public responded to that. So Malay's

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Speaker 2: party performed well. Obviously, this ties into the soybee market

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Speaker 2: as one piece of the other piece of this that

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Speaker 2: we've been covering as well is the cattle ranching industry,

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Speaker 2: the beef industry, beef prices in this country have been

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Speaker 2: extremely high and rising. You would think that cattle ranchers,

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Speaker 2: who have been struggling and screwed in a lot of

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Speaker 2: ways that we've also been covering over the years, you

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Speaker 2: would think that would be a good thing, you know,

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Speaker 2: for them. Maybe they're getting more on their end. But

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Speaker 2: because of monopoly and consolidation, that has really not come

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Speaker 2: together for cattle ranchers here in the US. Than Trump

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Speaker 2: came in and said that to depress the prices, to

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Speaker 2: further screw the ranchers here, he's going to buy beef

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Speaker 2: from Argentina. So to talk about all of these things,

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Speaker 2: we actually have a rancher who also is a journalist

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Speaker 2: who covers the industry extensively. Mike Cali Crate is going

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Speaker 2: to join us now. Joining us now to talk about

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Speaker 2: the president's decision to purchase beef from Argentina is Mike

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Speaker 2: Cali Crate. He is himself a rancher, he's a journalist,

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Speaker 2: he's a family farm advocate, and he is also a

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Speaker 2: founder of Ranch Foods Directly. It's great to have you, Mike.

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Speaker 11: Thanks for having me, Crystal.

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Speaker 3: Yeah, of course, So.

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Speaker 2: Let's go and put a tear sheet up on the screen.

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Speaker 2: This is some of your writing about this deal. You say,

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Speaker 2: Colorado Springs rancher, that would be you, says importing Argentinian

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Speaker 2: beef could hurt us ranchers.

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Speaker 3: I'd actually like you, though, to back up a little.

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Speaker 2: Bit from this present moment and give us a bit

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Speaker 2: of a lay of the land of the cattle ranching industry.

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Speaker 2: And also, you know, beef prices have gone up a lot,

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Speaker 2: certainly American consumers are very concerned about that. Have ranchers

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Speaker 2: been benefiting from that price increase? What is kind of

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Speaker 2: the state of the industry right now.

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Speaker 11: No, ranchers have not benefited from consumer price increases. There's

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Speaker 11: a disconnect between consumer prices and what ranchers receive for cattle.

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Speaker 11: And it's a middleman problem, a monopoly problem, essentially, a

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Speaker 11: cartail sort of partnership between the biggest meat packers who

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Speaker 11: now control eighty five percent the big four control eighty

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Speaker 11: five percent of the slaughter market, in partnership with big

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Speaker 11: retailers who control a very similar share of the retail market.

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Speaker 11: And I'm talking about Walmart, Kroger, Amazon, Whole Foods, Safeway, Albertson's,

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Speaker 11: and so the rancher has really been shut out of

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Speaker 11: his fair share of the consumer dollar. Really going back

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Speaker 11: clear to the late seventies when when the book Vicious

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Speaker 11: Circles the Mafia in the Marketplace detailed how the big

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Speaker 11: meat packers were cooperating rather than competing and stealing really

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Speaker 11: the producer's share of the consumer dollars. So we've lost

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Speaker 11: half our ranchers during this period of time when when

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Speaker 11: this cartel has been really depressing the price for livestock

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Speaker 11: at the same time as they're raising prices for consumers.

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Speaker 11: And we've liquidated ten million cows. So now we've come

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Speaker 11: to a very very critical time when we just don't

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Speaker 11: have enough livestock to feed our own people. And that's

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Speaker 11: been made up for. It's been a it's been a

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Speaker 11: gradual progression, but it's been made up for with imports.

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Speaker 11: So we're importing up to twenty percent of the meat

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Speaker 11: that we eat today, and it's from wherever the cartel

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Speaker 11: can find it the cheapest to import into this country.

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Speaker 11: And it's a sad state when producers everywhere, it doesn't

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Speaker 11: matter whether you're in the United States or whether you're

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Speaker 11: in Argentina, you're being paid below your cost of production

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Speaker 11: because of this abusive market power that lies in the

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Speaker 11: hands of these very powerful multinational corporations.

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Speaker 4: And President Trump is obviously concerning about just bringing down

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Speaker 4: the price of beef overall. Could you speak a bit

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Speaker 4: to what's happened in the last I don't know year,

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Speaker 4: couple years, just recent history that's behind this price spike

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Speaker 4: that consumers are experiencing now. Is it still deeply connected

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Speaker 4: to those overall trends concentration? Are there micro factors that

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Speaker 4: have influenced it just in recent history? What's going on now?

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Speaker 11: Well, right now, because of the real serious lack of

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Speaker 11: cattle here in the United States and the fact that

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Speaker 11: we've shut down the the import of feeder cattle out

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Speaker 11: of Mexico along with additional tariffs on Brazilian beef, it's

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Speaker 11: it's inflated that that cost to the retailer, and and

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Speaker 11: the retailer is absolutely not willing to give up any

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Speaker 11: of their unfair margins that they've that they've been able

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Speaker 11: to achieve because of their abusive market power, and and

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Speaker 11: so retailers are charging all they can uh They're they're

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Speaker 11: always going to test with the consumers willing to pay

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Speaker 11: and and so the problem is from that point back,

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Speaker 11: the producer isn't getting his fair share. Nor is the worker,

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Speaker 11: the worker in the meat in the meat system, whether

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Speaker 11: it's a slaughterhouse worker or or a processing worker. Uh,

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Speaker 11: they're not They're not getting their fair share either, and

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Speaker 11: so so the and so what we've seen is with

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Speaker 11: this reduction in imports is retailers saying, oh, this is

440
00:21:58,760 --> 00:22:01,679
Speaker 11: a great time to raise prices. But the thing you

441
00:22:01,720 --> 00:22:04,239
Speaker 11: need to look at as far as the price of

442
00:22:04,280 --> 00:22:07,480
Speaker 11: beef to the consumer, it's about the same. It takes

443
00:22:07,520 --> 00:22:10,800
Speaker 11: about the same amount of minutes within an hour to

444
00:22:11,480 --> 00:22:13,840
Speaker 11: eat to buy a pound of ground beef as it did,

445
00:22:14,080 --> 00:22:17,200
Speaker 11: you know, twenty years ago. And so our beef price

446
00:22:17,280 --> 00:22:23,040
Speaker 11: is really too high? Probably not, probably not. But is

447
00:22:23,119 --> 00:22:26,240
Speaker 11: the income to the normal family that's trying to buy

448
00:22:26,280 --> 00:22:30,040
Speaker 11: beef too low? Absolutely, When you're working two and three

449
00:22:30,200 --> 00:22:33,720
Speaker 11: jobs to pay your mortgage, to pay for your technology,

450
00:22:33,760 --> 00:22:38,199
Speaker 11: to pay for food, of course it's going to hit

451
00:22:38,240 --> 00:22:41,560
Speaker 11: you hard. But right now at Ranch Foods Direct, we've

452
00:22:41,560 --> 00:22:44,840
Speaker 11: got six dollars a pound ground beef that is thirty

453
00:22:44,920 --> 00:22:48,560
Speaker 11: some cents below the national average. Plus it's local and

454
00:22:48,600 --> 00:22:53,359
Speaker 11: it's really good. But the industry has sold America on

455
00:22:53,480 --> 00:22:55,840
Speaker 11: the fact that you've got to get big to be

456
00:22:55,920 --> 00:22:59,159
Speaker 11: efficient and have economies of scale. All of that was

457
00:22:59,240 --> 00:23:04,120
Speaker 11: proven fall during COVID when we had empty shelves all

458
00:23:04,160 --> 00:23:07,960
Speaker 11: across to America while our company, the local regional company

459
00:23:08,000 --> 00:23:11,400
Speaker 11: in Colorado Springs that has a supply chain that goes

460
00:23:11,400 --> 00:23:15,200
Speaker 11: to Saint Francis, Kansas on the Colorado border, we never

461
00:23:15,280 --> 00:23:19,800
Speaker 11: ran out, but we have a local regional model that

462
00:23:19,880 --> 00:23:21,720
Speaker 11: I think has got to get replicated if we're going

463
00:23:21,760 --> 00:23:24,480
Speaker 11: to actually feed ourselves going forward. We have to address

464
00:23:24,720 --> 00:23:28,520
Speaker 11: the abusive market power, the monopoly power of big food.

465
00:23:29,000 --> 00:23:32,640
Speaker 11: And I know this maybe doesn't matter much when you're

466
00:23:32,640 --> 00:23:37,679
Speaker 11: talking about AI and you're talking about Venezuelan regime changes

467
00:23:38,000 --> 00:23:41,000
Speaker 11: and you're talking about all of this crazy stuff in

468
00:23:41,040 --> 00:23:44,679
Speaker 11: the news. But this is food. This is what we

469
00:23:44,720 --> 00:23:47,160
Speaker 11: put on our plates every day to nourish our families.

470
00:23:47,160 --> 00:23:50,240
Speaker 11: And it's not just beef. It's everything that we eat

471
00:23:50,359 --> 00:23:53,400
Speaker 11: is under the power of a handful of global corporations.

472
00:23:53,560 --> 00:23:55,720
Speaker 2: Yeah, it's such a great point I would love for

473
00:23:55,760 --> 00:23:58,840
Speaker 2: you to dig into. You mentioned that you've the industry

474
00:23:58,920 --> 00:24:03,479
Speaker 2: is liquidated million cows, and that that lack of supply

475
00:24:04,200 --> 00:24:08,120
Speaker 2: is part of why we're seeing these skyrocketing prices. Now,

476
00:24:09,280 --> 00:24:13,199
Speaker 2: what led to that liquidation, What was the math of

477
00:24:13,240 --> 00:24:15,320
Speaker 2: the business logic that led to that outcome?

478
00:24:16,480 --> 00:24:20,000
Speaker 11: Decades of being paid below the cost of production is

479
00:24:20,040 --> 00:24:23,520
Speaker 11: what led to that liquidation. I've been at this about

480
00:24:23,560 --> 00:24:26,520
Speaker 11: fifty years, and I just remember my in laws at

481
00:24:26,560 --> 00:24:30,680
Speaker 11: the dinner table with my sons reminding them, don't do

482
00:24:30,800 --> 00:24:34,920
Speaker 11: what we've done. Do not be ranchers, Do not raise cattle.

483
00:24:35,040 --> 00:24:37,760
Speaker 11: It is not a great lifestyle. You can't get paid

484
00:24:37,880 --> 00:24:42,640
Speaker 11: enough to pay the mortgage and live a reasonable quality

485
00:24:42,680 --> 00:24:46,440
Speaker 11: of life there. You know, farmers and ranchers their basic

486
00:24:46,560 --> 00:24:49,359
Speaker 11: net income is coming from off farm income. And so

487
00:24:49,400 --> 00:24:53,320
Speaker 11: the big food companies have reduced the prices paid to

488
00:24:53,400 --> 00:24:56,080
Speaker 11: producers because they have the power to do so, and

489
00:24:56,359 --> 00:25:00,600
Speaker 11: so we have. Then in the last few decades, ranching

490
00:25:00,600 --> 00:25:03,320
Speaker 11: has not been an attractive business, and so we've not

491
00:25:03,560 --> 00:25:07,120
Speaker 11: replaced the cows that they've as they've gotten older with

492
00:25:07,119 --> 00:25:12,119
Speaker 11: with heifer's and the bankers are clamoring for for note

493
00:25:12,119 --> 00:25:16,520
Speaker 11: payments and mortgage reductions, and we just simply haven't maintained

494
00:25:16,520 --> 00:25:19,000
Speaker 11: our cow herd because there has not been a fair,

495
00:25:19,119 --> 00:25:21,560
Speaker 11: open and competitive marketplace, and.

496
00:25:21,640 --> 00:25:25,000
Speaker 4: So Trump is saying it's not we don't totally understand

497
00:25:25,000 --> 00:25:27,359
Speaker 4: what he's going to do with Argentina yet, but he said,

498
00:25:27,440 --> 00:25:28,679
Speaker 4: you know, not a lot of beef.

499
00:25:28,960 --> 00:25:29,760
Speaker 5: You know, it's.

500
00:25:29,640 --> 00:25:32,440
Speaker 4: It's you know, it's not going to be a ton.

501
00:25:33,240 --> 00:25:35,960
Speaker 4: But based on all of that, based on what we

502
00:25:36,040 --> 00:25:40,840
Speaker 4: know so far, what influence would a modest amount of

503
00:25:40,880 --> 00:25:43,959
Speaker 4: imports from Argentina, a modest amount of beef imports from

504
00:25:44,040 --> 00:25:46,480
Speaker 4: Argentina have on the industry as you see it?

505
00:25:47,359 --> 00:25:49,040
Speaker 11: Well right now, I don't know that it would have

506
00:25:49,480 --> 00:25:52,200
Speaker 11: a lot if you really had a supply and demand market,

507
00:25:52,240 --> 00:25:55,399
Speaker 11: which we have not had for probably since the eighties.

508
00:25:55,480 --> 00:25:59,280
Speaker 11: We haven't had that. And but but the thing is

509
00:25:59,640 --> 00:26:03,359
Speaker 11: thenouncement of it. Let's those cattle futures, you know, the

510
00:26:03,440 --> 00:26:08,720
Speaker 11: Chicago MRK just totally crater the price on the futures market,

511
00:26:08,920 --> 00:26:12,800
Speaker 11: which then reduces those prices for calves and feeder cattle

512
00:26:13,320 --> 00:26:18,399
Speaker 11: and live cattle to the rancher. Right now, but I

513
00:26:18,440 --> 00:26:23,879
Speaker 11: don't think Trump understands just how much disconnect there is

514
00:26:24,040 --> 00:26:27,399
Speaker 11: between retail prices and ranch gate prices. You know, a

515
00:26:27,520 --> 00:26:30,719
Speaker 11: rancher is in the business of turning grass into cattle

516
00:26:31,400 --> 00:26:33,760
Speaker 11: and they hope for a competitive market that will give

517
00:26:33,760 --> 00:26:35,840
Speaker 11: them a fair share of that consumer dollar. Back in

518
00:26:35,920 --> 00:26:39,240
Speaker 11: nineteen seventy when I first started, the rancher got about

519
00:26:39,280 --> 00:26:42,200
Speaker 11: seventy percent, The producer of livestock got about seventy percent

520
00:26:42,240 --> 00:26:44,560
Speaker 11: of the consumer dollar. That dropped to as low as

521
00:26:44,600 --> 00:26:48,000
Speaker 11: twenty seven percent during COVID to now it's around fifty

522
00:26:48,040 --> 00:26:51,000
Speaker 11: four to fifty five percent. So we still are not

523
00:26:51,200 --> 00:26:54,520
Speaker 11: getting our fair share of what consumers spend, and that

524
00:26:54,680 --> 00:26:57,960
Speaker 11: is again a result of the market power of the middlemen.

525
00:26:58,880 --> 00:27:00,800
Speaker 2: Mike, I wonder if you could talk a little bit

526
00:27:00,840 --> 00:27:03,119
Speaker 2: of politics here with us. You know, you had in

527
00:27:03,160 --> 00:27:06,080
Speaker 2: the Biden administration, with Lena Khan, you had a real

528
00:27:06,240 --> 00:27:08,399
Speaker 2: renewed interest in an anti trust.

529
00:27:08,520 --> 00:27:09,400
Speaker 3: I remember there was.

530
00:27:09,320 --> 00:27:15,040
Speaker 2: Some at least at least rhetorical emphasis on, hey, we

531
00:27:15,080 --> 00:27:17,680
Speaker 2: got to break up some of these meat packers and

532
00:27:17,760 --> 00:27:21,240
Speaker 2: you know, the cartels that you're talking about. But none

533
00:27:21,280 --> 00:27:23,760
Speaker 2: of that seems to have really been rewarded, certainly by

534
00:27:23,960 --> 00:27:27,400
Speaker 2: rural America, and you know, your you know, your your

535
00:27:27,440 --> 00:27:32,960
Speaker 2: business competitors in the industry overwhelmingly went for Trump. So,

536
00:27:33,640 --> 00:27:35,440
Speaker 2: you know, how do you think about the way that

537
00:27:35,760 --> 00:27:39,159
Speaker 2: Democrats have over years you know, completely lost this constituenc

538
00:27:39,200 --> 00:27:40,879
Speaker 2: You used to have a John Tester or someone like that.

539
00:27:40,960 --> 00:27:43,040
Speaker 2: It was you know, very sort of like populist, anti

540
00:27:43,040 --> 00:27:44,879
Speaker 2: trust it was able to win in these states, and

541
00:27:44,920 --> 00:27:47,000
Speaker 2: I just don't think that it's it's possible anymore.

542
00:27:47,000 --> 00:27:47,920
Speaker 3: How do you think about that?

543
00:27:48,680 --> 00:27:52,280
Speaker 11: Well, I am I'm really disappointed that that no one

544
00:27:52,400 --> 00:27:57,080
Speaker 11: politically Democrat or Republican has delivered on antitrust law enforcement.

545
00:27:57,520 --> 00:28:00,399
Speaker 11: And I think that the last election would have had

546
00:28:00,440 --> 00:28:03,119
Speaker 11: a far different outcome if they would not have kept

547
00:28:03,440 --> 00:28:06,119
Speaker 11: Lena Khan with the Federal Trade Commission in the closet.

548
00:28:06,359 --> 00:28:10,600
Speaker 11: I mean, she was working to improve competitive markets and

549
00:28:10,800 --> 00:28:17,120
Speaker 11: fairness all the way around around consumer welfare and corporate

550
00:28:17,200 --> 00:28:20,280
Speaker 11: power and all of that, and we just didn't we

551
00:28:20,320 --> 00:28:24,159
Speaker 11: didn't even know about it. Kamala Harris need even mentioned it.

552
00:28:24,440 --> 00:28:27,199
Speaker 11: So we've never had support. In fact, going back to

553
00:28:27,240 --> 00:28:30,919
Speaker 11: the Obama years when they had the concentration hearings across

554
00:28:30,960 --> 00:28:35,000
Speaker 11: the country, we thought full well, with all of that

555
00:28:35,280 --> 00:28:38,360
Speaker 11: proof and all of that information about the abusive market

556
00:28:38,360 --> 00:28:41,240
Speaker 11: power of big meat packers, that there would be some relief.

557
00:28:41,680 --> 00:28:45,120
Speaker 11: And Lena Khan wrote the article Obama's Game of Chicken.

558
00:28:45,240 --> 00:28:48,480
Speaker 11: It was in the Atlantic. It was amazing piece of writing.

559
00:28:48,800 --> 00:28:51,360
Speaker 11: And then eventually she made her way into the chair

560
00:28:51,400 --> 00:28:54,720
Speaker 11: of the Federal Trade Commission and was doing absolutely the

561
00:28:54,760 --> 00:28:57,880
Speaker 11: best work we've seen in one hundred years. Trump comes

562
00:28:57,880 --> 00:29:03,000
Speaker 11: in and fires her. That is just how how unbelievably

563
00:29:03,160 --> 00:29:07,960
Speaker 11: ignorant the the current administration is about the real needs

564
00:29:08,280 --> 00:29:12,480
Speaker 11: of consumers and producers around our food system in particular,

565
00:29:12,720 --> 00:29:15,320
Speaker 11: although Lena Khan looked at a lot of other things,

566
00:29:15,360 --> 00:29:19,360
Speaker 11: but she's the one that blocked the Kroger Safeway merger.

567
00:29:19,560 --> 00:29:25,959
Speaker 11: So Safeway Albertson's merger that was absolutely required, and prior

568
00:29:26,000 --> 00:29:29,360
Speaker 11: to that, we we blocked the Safe or the Cisco

569
00:29:29,920 --> 00:29:33,240
Speaker 11: US Foods merger. But the problem we're seeing now is

570
00:29:33,520 --> 00:29:36,240
Speaker 11: these companies that try to merge get to know each other,

571
00:29:36,280 --> 00:29:38,520
Speaker 11: and whether it's approved or not, they still cooperate and

572
00:29:38,520 --> 00:29:41,520
Speaker 11: work together to maximize their profits. I mean, how is

573
00:29:41,560 --> 00:29:46,720
Speaker 11: it that Cisco earns or makes a hundred percent return

574
00:29:46,800 --> 00:29:50,400
Speaker 11: on equity ro O Roe right now, if you look

575
00:29:50,440 --> 00:29:53,880
Speaker 11: it up on Google, Cisco's rite out one hundred percent

576
00:29:53,920 --> 00:29:56,680
Speaker 11: return on equity. That's not a competitive market, and that

577
00:29:56,760 --> 00:30:00,240
Speaker 11: comes at the expense of producers and consumers and all

578
00:30:00,280 --> 00:30:01,560
Speaker 11: the workers that are in between.

579
00:30:02,040 --> 00:30:05,520
Speaker 4: And your case actually is that that goes straight to

580
00:30:05,600 --> 00:30:09,520
Speaker 4: those beef prices that if you have it's essentially like

581
00:30:09,560 --> 00:30:12,960
Speaker 4: the greed inflation argument that the Biden administration made a

582
00:30:12,360 --> 00:30:16,719
Speaker 4: half hearted attempt attempt to sell to the public, that

583
00:30:16,760 --> 00:30:19,920
Speaker 4: when you have consolidation, you're able to just ratch it up.

584
00:30:19,920 --> 00:30:22,520
Speaker 4: The retailers themselves are able to just ratch it up

585
00:30:22,520 --> 00:30:24,600
Speaker 4: the prices. That is that, Am I getting that right?

586
00:30:24,640 --> 00:30:25,760
Speaker 4: Based on what you were expecting?

587
00:30:25,760 --> 00:30:30,200
Speaker 11: One hundred percent? That is exactly exactly right. You give

588
00:30:30,240 --> 00:30:32,920
Speaker 11: them the ability to extract wealth and they will do

589
00:30:33,080 --> 00:30:37,640
Speaker 11: it to the maximum amount allowable that they're able to.

590
00:30:38,200 --> 00:30:40,240
Speaker 11: And you know, that's all goes back to the corporate

591
00:30:40,280 --> 00:30:45,640
Speaker 11: responsibility of providing maximum returns to shareholders. But it's honestly

592
00:30:45,720 --> 00:30:48,360
Speaker 11: maximum returns to executive level pay.

593
00:30:48,440 --> 00:30:51,120
Speaker 2: Yeah, my last question to you, you know, what would

594
00:30:51,160 --> 00:30:53,560
Speaker 2: your pitch be to Americans who are listening to this

595
00:30:53,720 --> 00:30:55,840
Speaker 2: or are like, well, that's all well and good, but

596
00:30:56,000 --> 00:30:58,200
Speaker 2: like prices are too high, and if it's going to

597
00:30:58,240 --> 00:31:02,720
Speaker 2: help to import beef from Argentina or wherever, why don't

598
00:31:02,760 --> 00:31:05,080
Speaker 2: we just why don't we just go for that? Because

599
00:31:05,160 --> 00:31:07,120
Speaker 2: my pocketbook is hurting right now. What would you tell

600
00:31:07,120 --> 00:31:08,800
Speaker 2: Americans about why they should care.

601
00:31:09,560 --> 00:31:12,400
Speaker 11: Well, I tell Americans they should care because importing Argentine

602
00:31:12,440 --> 00:31:14,760
Speaker 11: beef is not going to lower your prices. It might

603
00:31:14,800 --> 00:31:18,800
Speaker 11: lower the prices to ranchers, which guarantees that the herd

604
00:31:18,800 --> 00:31:21,120
Speaker 11: won't be rebuilt and won't be feeding us in the future,

605
00:31:21,120 --> 00:31:24,560
Speaker 11: but it will not lower prices, not with the cartel,

606
00:31:24,760 --> 00:31:27,440
Speaker 11: the monopoly power of the middlemen. And think about it

607
00:31:27,440 --> 00:31:30,640
Speaker 11: in a minute, from the Argentine perspective, I mean, their

608
00:31:30,640 --> 00:31:35,560
Speaker 11: economy is not doing great, their consumers are not doing great.

609
00:31:35,640 --> 00:31:37,480
Speaker 11: So we go down there and we're going to take

610
00:31:37,720 --> 00:31:43,120
Speaker 11: meat off the plates of Argentine consumers, raise their prices,

611
00:31:43,600 --> 00:31:46,400
Speaker 11: only to use it as a lever to lower prices

612
00:31:46,400 --> 00:31:49,920
Speaker 11: to ranchers and not lower prices to American consumers. And

613
00:31:49,960 --> 00:31:52,720
Speaker 11: the other point that no one is making is when

614
00:31:53,200 --> 00:31:57,840
Speaker 11: Argentina gets favorable trade conditions with the United States, the

615
00:31:57,920 --> 00:32:00,920
Speaker 11: highest and best consuming market in the world world, how

616
00:32:00,960 --> 00:32:06,520
Speaker 11: many animals transship cross those borders into Argentina that then

617
00:32:06,600 --> 00:32:09,640
Speaker 11: are able to go into the United States at the

618
00:32:09,680 --> 00:32:14,000
Speaker 11: best prices on the globe. Mike cal create and only

619
00:32:14,040 --> 00:32:17,400
Speaker 11: the middleman making the money. Yeah, So the Argentine producers

620
00:32:17,480 --> 00:32:22,920
Speaker 11: under the same pressure, same big companies JBS marfrigg. You know,

621
00:32:22,960 --> 00:32:25,960
Speaker 11: the biggest companies in the world are transacting the deal

622
00:32:26,160 --> 00:32:26,760
Speaker 11: and they'll.

623
00:32:26,560 --> 00:32:30,280
Speaker 2: Be subject to the same nightmare you've been living here. Mike,

624
00:32:30,320 --> 00:32:33,360
Speaker 2: thank you so much for for helping us understand. Tell

625
00:32:33,360 --> 00:32:35,000
Speaker 2: people you know where they can find you, where they

626
00:32:35,000 --> 00:32:36,600
Speaker 2: can buy your products, all of that good stuff.

627
00:32:37,040 --> 00:32:39,040
Speaker 11: Well, if you go to Mike cal Create dot com,

628
00:32:39,080 --> 00:32:40,920
Speaker 11: you'll see what we're up to, and I've got a

629
00:32:40,920 --> 00:32:43,360
Speaker 11: blog there. But if as far as the ranch Foods

630
00:32:43,360 --> 00:32:46,200
Speaker 11: Direct model, which I would hope others might replicate around

631
00:32:46,280 --> 00:32:49,600
Speaker 11: the country to connect producers more closely to consumers, go

632
00:32:49,640 --> 00:32:52,120
Speaker 11: to ranch Foodsdirect dot com and you'll be able to

633
00:32:52,160 --> 00:32:53,040
Speaker 11: see what we do there.

634
00:32:53,280 --> 00:32:56,200
Speaker 3: Just put in my order yesterday. So thank you so much.

635
00:32:56,480 --> 00:32:57,800
Speaker 3: See Mike, thank you.

636
00:32:57,840 --> 00:32:58,480
Speaker 11: I appreciate it.

637
00:32:58,520 --> 00:32:59,040
Speaker 3: Great to have you.

638
00:32:59,080 --> 00:33:00,920
Speaker 11: Okay, all right bye.

639
00:33:03,120 --> 00:33:06,880
Speaker 4: We learned not long ago that a mysterious private donor

640
00:33:07,080 --> 00:33:10,280
Speaker 4: was jumping in to bail out the government during the

641
00:33:10,320 --> 00:33:14,680
Speaker 4: shutdown so that some US troops could continue to get paid.

642
00:33:15,080 --> 00:33:18,440
Speaker 4: As Congress continues to take no action, tries to take action,

643
00:33:18,560 --> 00:33:21,320
Speaker 4: but hasn't taken any action. To at least make sure

644
00:33:21,360 --> 00:33:23,440
Speaker 4: that the troops are paid during the shutdown.

645
00:33:23,920 --> 00:33:25,360
Speaker 5: Here is a little bit of a back and.

646
00:33:25,400 --> 00:33:28,120
Speaker 4: Forth between Donald Trump and a reporter about who might

647
00:33:28,160 --> 00:33:31,080
Speaker 4: have stepped in with this one hundred and thirty million

648
00:33:31,160 --> 00:33:33,400
Speaker 4: dollars donation straight to the government.

649
00:33:33,760 --> 00:33:34,960
Speaker 5: We can roll the clip, so.

650
00:33:35,120 --> 00:33:38,800
Speaker 4: Find somebody to pay for our troops during the shutdown.

651
00:33:40,880 --> 00:33:44,280
Speaker 12: He's a great gentleman. He's a great page. He's obviously

652
00:33:44,320 --> 00:33:48,800
Speaker 12: a very substantial man. And he contributed one hundred and

653
00:33:48,880 --> 00:33:52,160
Speaker 12: thirty million dollars toward the military in order to make

654
00:33:52,280 --> 00:33:55,280
Speaker 12: up any different So he wanted to see the military

655
00:33:55,320 --> 00:33:58,440
Speaker 12: get paid. So did I. And he's a wonderful man,

656
00:33:58,480 --> 00:34:01,440
Speaker 12: and he does in what publicity. He doesn't you know,

657
00:34:01,480 --> 00:34:03,840
Speaker 12: he'd prefer I think that his name not be mentioned,

658
00:34:03,840 --> 00:34:07,040
Speaker 12: which is pretty unusual that the world they come from.

659
00:34:07,080 --> 00:34:10,279
Speaker 12: And he's a big supporter of an American It is

660
00:34:10,360 --> 00:34:12,000
Speaker 12: a great American citizen.

661
00:34:12,480 --> 00:34:15,000
Speaker 4: We now know who that donor is. We can put

662
00:34:15,040 --> 00:34:18,000
Speaker 4: b two up on the screen. Timothy Melon of the

663
00:34:18,120 --> 00:34:20,440
Speaker 4: Mellon family. You actually may remember his name from the

664
00:34:20,440 --> 00:34:24,800
Speaker 4: twenty twenty four election cycle when he just was giving

665
00:34:24,800 --> 00:34:26,720
Speaker 4: all pumping money into the Trump campaign.

666
00:34:27,040 --> 00:34:31,600
Speaker 2: Essentially made a fifty million dollar donation to Trump.

667
00:34:31,480 --> 00:34:35,320
Speaker 3: Super Pack fifty million dollars. So he's one of Trump's

668
00:34:35,440 --> 00:34:36,240
Speaker 3: largest donors.

669
00:34:36,520 --> 00:34:39,880
Speaker 4: Incredible. He's somewhat of a recluse. He lives in Wyoming.

670
00:34:39,960 --> 00:34:43,000
Speaker 4: He's a big supporter of Robert F. Kennedy Junior in

671
00:34:43,040 --> 00:34:45,200
Speaker 4: his group. The Children's Health Defense Fund, I think is

672
00:34:45,239 --> 00:34:47,399
Speaker 4: the name of it. And so according to two people

673
00:34:47,400 --> 00:34:49,720
Speaker 4: familiar with the matter, according to the New York Times,

674
00:34:49,719 --> 00:34:51,720
Speaker 4: these are the New York Times sources to people familiar

675
00:34:51,760 --> 00:34:54,560
Speaker 4: with the matter, it was Timothy Mellon who came in

676
00:34:54,840 --> 00:34:58,760
Speaker 4: and ended up giving one hundred and thirty million dollars.

677
00:34:58,880 --> 00:35:02,520
Speaker 4: Let's roll this clip of true Secretary Scott Besant on

678
00:35:02,560 --> 00:35:04,000
Speaker 4: whether or not the troops were getting paid.

679
00:35:04,280 --> 00:35:08,720
Speaker 7: We were able to pay the military employees from excess

680
00:35:08,760 --> 00:35:11,279
Speaker 7: funds at the Pentagon Medal of this month. I think

681
00:35:11,320 --> 00:35:14,000
Speaker 7: we'll be able to pay them beginning in November. But

682
00:35:14,200 --> 00:35:18,319
Speaker 7: by November fifteenth, our troops and service members who are

683
00:35:18,360 --> 00:35:21,160
Speaker 7: willing to risk their lives aren't going to be able

684
00:35:21,160 --> 00:35:21,680
Speaker 7: to get paid.

685
00:35:21,760 --> 00:35:26,319
Speaker 3: What it embarrassing, Yes, embarrassed, that's right now. It is.

686
00:35:26,800 --> 00:35:28,919
Speaker 4: And so now you have Timothy Mellon jumping in which

687
00:35:28,960 --> 00:35:32,520
Speaker 4: Crystal is actually kind of interesting because Republicans have used

688
00:35:32,560 --> 00:35:34,960
Speaker 4: I mean, it's interesting a lot of ways, but Republicans.

689
00:35:34,440 --> 00:35:37,560
Speaker 5: Have used particularly the troops, just.

690
00:35:37,560 --> 00:35:40,800
Speaker 4: As Democrats did during previous government shutdowns to say, quote,

691
00:35:40,800 --> 00:35:42,440
Speaker 4: what an embarrassment.

692
00:35:42,000 --> 00:35:44,800
Speaker 5: Like, get to the table, give us the votes.

693
00:35:45,040 --> 00:35:47,520
Speaker 4: Republicans are typically the ones in the position of withholding

694
00:35:47,600 --> 00:35:50,800
Speaker 4: votes on a cr to fund the government. Now it's Democrats,

695
00:35:50,800 --> 00:35:53,600
Speaker 4: and Republicans thought this was their leverage. So it's actually

696
00:35:53,640 --> 00:35:56,040
Speaker 4: kind of interesting that you have someone in a way

697
00:35:56,200 --> 00:35:59,799
Speaker 4: taking away the leverage that a Republican donors is under

698
00:36:00,280 --> 00:36:02,560
Speaker 4: their argument that Democrats need to get to the table

699
00:36:03,120 --> 00:36:06,319
Speaker 4: to negotiate so the troops can get paid. Obviously, there's

700
00:36:06,400 --> 00:36:09,040
Speaker 4: questions over whether the one hundred and thirty million is

701
00:36:09,200 --> 00:36:11,000
Speaker 4: enough to really, yeah, make a difference.

702
00:36:11,040 --> 00:36:13,640
Speaker 2: Apparently that would be like one hundred dollars to each

703
00:36:13,880 --> 00:36:14,480
Speaker 2: service member.

704
00:36:14,600 --> 00:36:15,759
Speaker 5: That's what the time you do it.

705
00:36:16,040 --> 00:36:19,680
Speaker 2: It is one of the weird this is it's weird

706
00:36:19,719 --> 00:36:22,279
Speaker 2: and troubling, and it's worth thinking about the principle of it,

707
00:36:22,640 --> 00:36:25,640
Speaker 2: even though it's not nearly sufficient to even come close

708
00:36:25,680 --> 00:36:29,239
Speaker 2: to actually paying the entire military. What now we've got

709
00:36:29,239 --> 00:36:32,719
Speaker 2: like random private oligarchs funding the military. Is this really

710
00:36:32,719 --> 00:36:34,359
Speaker 2: the direction we want to go in at a time

711
00:36:34,400 --> 00:36:37,000
Speaker 2: when Trump is increasingly using the military as like his

712
00:36:37,120 --> 00:36:41,160
Speaker 2: own personal force against whatever people in cities and causes

713
00:36:41,160 --> 00:36:44,520
Speaker 2: that he doesn't particularly like. So the principle of it

714
00:36:44,600 --> 00:36:51,160
Speaker 2: is disturbing. Potentially illegal by the way, you know, unclear,

715
00:36:51,239 --> 00:36:53,320
Speaker 2: completely legally, but potentially illegal.

716
00:36:53,640 --> 00:36:55,320
Speaker 3: So it's like, what is this guy.

717
00:36:55,200 --> 00:36:58,920
Speaker 2: Doing when you're not even coming close to solving the problem.

718
00:36:59,080 --> 00:37:00,719
Speaker 3: I don't know, it's.

719
00:37:00,200 --> 00:37:03,520
Speaker 2: To me, the whole thing is very strange and troubling

720
00:37:03,760 --> 00:37:07,440
Speaker 2: in you know, a way that often Trump Trump regime

721
00:37:07,480 --> 00:37:08,240
Speaker 2: actions are.

722
00:37:08,600 --> 00:37:11,440
Speaker 4: Well, let's put this before on the screen. You can

723
00:37:11,520 --> 00:37:15,839
Speaker 4: see already for federal workers. There are some lines outside

724
00:37:16,000 --> 00:37:18,840
Speaker 4: of food pantry. So this load federal workers.

725
00:37:19,120 --> 00:37:21,920
Speaker 2: This is Landover, Maryland, which is you know, just outside

726
00:37:22,000 --> 00:37:25,400
Speaker 2: the Beltway here in the Beltway area here. And so

727
00:37:26,040 --> 00:37:29,080
Speaker 2: I saw some restaurants around town. I was walking around

728
00:37:29,120 --> 00:37:32,160
Speaker 2: DC last night, who had, you know, fifty percent off

729
00:37:32,160 --> 00:37:35,120
Speaker 2: for federal workers. You know, this thing is really starting

730
00:37:35,160 --> 00:37:38,959
Speaker 2: to to bite. It's people are really starting to feel

731
00:37:38,960 --> 00:37:42,520
Speaker 2: the pain. You know, paychecks are starting to be missed. Obviously,

732
00:37:42,560 --> 00:37:44,759
Speaker 2: workers are for a load you're going to have even

733
00:37:44,800 --> 00:37:47,239
Speaker 2: more workers for a load after the end of the month.

734
00:37:47,800 --> 00:37:50,960
Speaker 2: As best said, there, you know, come November fifteenth, troops

735
00:37:50,960 --> 00:37:53,719
Speaker 2: are no longer going to be paid. Doesn't look like

736
00:37:53,800 --> 00:37:56,080
Speaker 2: they've been sort of like moving different pots of money

737
00:37:56,160 --> 00:37:58,960
Speaker 2: around again in a way that's not really entirely clear

738
00:37:59,000 --> 00:38:01,959
Speaker 2: as legal, but they're moving different pats of money around

739
00:38:02,000 --> 00:38:04,120
Speaker 2: to try to make sure the troops are paid. A

740
00:38:04,120 --> 00:38:06,640
Speaker 2: lot of times, what happens in these shutdowns is that

741
00:38:06,960 --> 00:38:10,239
Speaker 2: Congress will pass a separate bill saying just like, okay, well,

742
00:38:10,239 --> 00:38:11,879
Speaker 2: we are going to pay the troops no matter how

743
00:38:11,920 --> 00:38:14,799
Speaker 2: long this thing goes. But they have not done that,

744
00:38:15,160 --> 00:38:18,040
Speaker 2: so they're really in the same camp as basically everyone

745
00:38:18,080 --> 00:38:19,640
Speaker 2: else as this thing stretches out.

746
00:38:19,840 --> 00:38:23,480
Speaker 4: Median average saving for an American is six hundred dollars.

747
00:38:24,000 --> 00:38:26,320
Speaker 4: And so you know, it's true that a lot of

748
00:38:26,360 --> 00:38:28,719
Speaker 4: these workers end up getting back pay, but that's not

749
00:38:28,760 --> 00:38:31,799
Speaker 4: helpful if your paycheck to paycheck or even a little

750
00:38:31,800 --> 00:38:34,040
Speaker 4: bit more comfortable than paycheck to paycheck. Because we are

751
00:38:34,080 --> 00:38:36,279
Speaker 4: now going into what could end up being one of

752
00:38:36,280 --> 00:38:38,719
Speaker 4: the longest government actually it might end up being the

753
00:38:38,760 --> 00:38:41,960
Speaker 4: longest government shutdown in history, because there is no end

754
00:38:42,000 --> 00:38:42,399
Speaker 4: in sight.

755
00:38:42,640 --> 00:38:43,239
Speaker 5: Whatsoever.

756
00:38:43,600 --> 00:38:49,200
Speaker 4: Yeah, and Jake Sherman loath as I am to invoke

757
00:38:49,280 --> 00:38:51,520
Speaker 4: any of his wisdom here of punch bawle. He says,

758
00:38:51,840 --> 00:38:54,120
Speaker 4: the flaw in this is Democrats have sold their base

759
00:38:54,160 --> 00:38:55,919
Speaker 4: in membership that they aren't trying to make a point,

760
00:38:55,960 --> 00:38:58,920
Speaker 4: they're trying to enact change. That's actually kind of an

761
00:38:58,920 --> 00:39:02,719
Speaker 4: interesting way to put it, because the leverage that Democrats have,

762
00:39:04,040 --> 00:39:06,680
Speaker 4: not the leverage, but the sort of the reason that

763
00:39:06,760 --> 00:39:10,360
Speaker 4: Democrats did the shutdown was to show the base that

764
00:39:10,400 --> 00:39:13,759
Speaker 4: they're fighting. And so what have they gotten at this point?

765
00:39:13,800 --> 00:39:15,799
Speaker 4: What can they get at this point out of it?

766
00:39:15,840 --> 00:39:20,160
Speaker 4: They make it Republicans to negotiate on premiums as possible,

767
00:39:20,239 --> 00:39:22,440
Speaker 4: on something for that, but nobody's even talking right now.

768
00:39:22,600 --> 00:39:24,960
Speaker 2: Yeah, No, it's I mean, there's really at this point

769
00:39:25,080 --> 00:39:27,120
Speaker 2: is no end insight. We did get that report last

770
00:39:27,160 --> 00:39:29,960
Speaker 2: week that we talked about that maybe Republicans were open

771
00:39:30,040 --> 00:39:33,400
Speaker 2: to something on the ACA subsidies. You know, I do

772
00:39:33,440 --> 00:39:35,640
Speaker 2: think Democrats would take if they could get any kind

773
00:39:35,680 --> 00:39:37,480
Speaker 2: of a win. I think they would probably take it.

774
00:39:37,760 --> 00:39:39,880
Speaker 2: You know, Schumer and co. Were really forced into this

775
00:39:39,920 --> 00:39:42,360
Speaker 2: by the base. It was not the politics they wanted

776
00:39:42,400 --> 00:39:45,640
Speaker 2: to pursue, and their persistence in it too, is really

777
00:39:45,760 --> 00:39:47,920
Speaker 2: forced on them by the base, which is really interesting.

778
00:39:48,000 --> 00:39:49,399
Speaker 2: I mean think there's kind of a tie in here

779
00:39:49,440 --> 00:39:51,239
Speaker 2: with some of the Zoron clip that will show of

780
00:39:51,320 --> 00:39:54,239
Speaker 2: Kathy Hochel and the crowd channing at her like tax

781
00:39:54,320 --> 00:39:58,359
Speaker 2: the rich. You have now leadership and establishment Democrats really

782
00:39:58,400 --> 00:40:01,799
Speaker 2: feeling the pressure from just an normally liberal base that

783
00:40:02,080 --> 00:40:05,600
Speaker 2: is increasingly disgusted with them and wants a more hardline

784
00:40:05,600 --> 00:40:08,480
Speaker 2: and more radical direction for the party. And so the

785
00:40:08,480 --> 00:40:10,400
Speaker 2: fact that Democrats, you know, I mean Sager and I

786
00:40:10,440 --> 00:40:11,320
Speaker 2: both early on were.

787
00:40:11,160 --> 00:40:12,719
Speaker 3: Like, yeah, they're probably going to fold, because that's just

788
00:40:12,800 --> 00:40:13,319
Speaker 3: what they do.

789
00:40:13,840 --> 00:40:15,800
Speaker 2: The reason we were wrong is because they are feeling

790
00:40:15,880 --> 00:40:19,600
Speaker 2: much more pressure from their own voters than we expected.

791
00:40:20,000 --> 00:40:23,160
Speaker 2: And you know, I think the Trump administration has taken

792
00:40:23,320 --> 00:40:26,600
Speaker 2: a lot of the staying out of the you know,

793
00:40:26,680 --> 00:40:29,799
Speaker 2: the mass destruction of the federalgarment workforce. They've been doing

794
00:40:29,840 --> 00:40:32,080
Speaker 2: that all along. So when you're like, oh, we're going

795
00:40:32,160 --> 00:40:34,120
Speaker 2: to hurt them more, it's like, well, you were already

796
00:40:34,120 --> 00:40:38,200
Speaker 2: doing that anyway. And when I think they've also been

797
00:40:38,200 --> 00:40:40,080
Speaker 2: buoyed by a lot of polls that show the public

798
00:40:40,120 --> 00:40:44,000
Speaker 2: are predominantly blaming Republicans, and it makes sense because they

799
00:40:44,040 --> 00:40:46,080
Speaker 2: are in control of everything. So people just look at

800
00:40:46,080 --> 00:40:47,520
Speaker 2: this and they're like, you guys run the show, so

801
00:40:47,640 --> 00:40:48,240
Speaker 2: get it together.

802
00:40:48,280 --> 00:40:49,239
Speaker 3: You got to negotiate with.

803
00:40:49,200 --> 00:40:53,239
Speaker 2: Them, figure something out, and so they feel like Republicans

804
00:40:53,280 --> 00:40:55,560
Speaker 2: are taking on water would think this thing as well,

805
00:40:55,600 --> 00:40:57,839
Speaker 2: which I think has strengthened some backbones.

806
00:40:58,400 --> 00:40:59,879
Speaker 3: Another test, though, is going to come.

807
00:41:00,000 --> 00:41:02,799
Speaker 2: I mean, this is really honestly, really terrible and really

808
00:41:02,840 --> 00:41:04,760
Speaker 2: die or it could put B five up on the screen.

809
00:41:06,040 --> 00:41:09,080
Speaker 2: Food stamp benefits SNAP benefits are going to run out

810
00:41:09,400 --> 00:41:11,359
Speaker 2: at the end of this month. You know, you've got

811
00:41:11,400 --> 00:41:16,759
Speaker 2: tens of millions of Americans who rely on SNAP benefits. Originally,

812
00:41:17,120 --> 00:41:19,759
Speaker 2: it had looked like the administration was going to use

813
00:41:19,800 --> 00:41:22,960
Speaker 2: some emergency funds to keep those benefits flowing. Now the

814
00:41:23,080 --> 00:41:25,839
Speaker 2: USDA is saying, nope, we're not going to do that. So,

815
00:41:25,960 --> 00:41:28,879
Speaker 2: you know, heading into November, heading into the month of Thanksgiving,

816
00:41:29,280 --> 00:41:32,840
Speaker 2: with the potential loss of those benefits, you've got Americans

817
00:41:32,880 --> 00:41:35,960
Speaker 2: who are going to go hungry if something is not

818
00:41:36,080 --> 00:41:38,760
Speaker 2: done to extend this funding or to get the government

819
00:41:38,760 --> 00:41:39,520
Speaker 2: fully back open.

820
00:41:39,760 --> 00:41:41,120
Speaker 5: And I'm just thinking about this now.

821
00:41:41,200 --> 00:41:46,040
Speaker 4: One of the sort of designs behind Doge is that

822
00:41:46,120 --> 00:41:48,919
Speaker 4: you kind of can do things right, like Republicans are like, hey,

823
00:41:48,920 --> 00:41:53,120
Speaker 4: you can do things. And so I'm wondering if the

824
00:41:53,239 --> 00:41:58,839
Speaker 4: USDA snap funds run out, if that becomes a sort

825
00:41:58,840 --> 00:42:02,040
Speaker 4: of predicate for some type of permanent reduction. I don't know,

826
00:42:02,640 --> 00:42:06,160
Speaker 4: but there may be legal avenues that a RUSS vote

827
00:42:06,360 --> 00:42:09,839
Speaker 4: or someone else the administration tries to pursue to make

828
00:42:09,840 --> 00:42:11,840
Speaker 4: permanent cuts, like they are with their trying to do

829
00:42:11,880 --> 00:42:14,120
Speaker 4: with federal workers. So I'm not sure about that, but

830
00:42:14,160 --> 00:42:16,160
Speaker 4: I do wonder if that's part of this. We can

831
00:42:16,200 --> 00:42:18,439
Speaker 4: put the next element on the screen. How Democrats are

832
00:42:18,440 --> 00:42:23,359
Speaker 4: calling back their members to DC. According to punch Bowl

833
00:42:23,440 --> 00:42:27,720
Speaker 4: Laura Weiss, they're holding in person caucus meetings tomorrow so Tuesday,

834
00:42:27,800 --> 00:42:31,640
Speaker 4: and events on Wednesday. It's possible we see an end

835
00:42:31,680 --> 00:42:35,720
Speaker 4: to this by the I mean it's possible by the weekend.

836
00:42:36,320 --> 00:42:38,960
Speaker 4: I don't know that anybody is particularly optimistic, though, if

837
00:42:38,960 --> 00:42:40,960
Speaker 4: we put the next element up on the screen. Over

838
00:42:41,000 --> 00:42:44,239
Speaker 4: the weekend, there was a ground stop at Lax.

839
00:42:45,280 --> 00:42:48,800
Speaker 5: It disrupted flights from Lax to airport.

840
00:42:49,160 --> 00:42:54,279
Speaker 4: Yeah, and so yeah, the longer this goes on with

841
00:42:54,440 --> 00:42:59,360
Speaker 4: people blaming Republicans' I think that's probably stable. Those numbers

842
00:42:59,400 --> 00:43:02,000
Speaker 4: of America blaming Republicans. I would probably put some of

843
00:43:02,000 --> 00:43:04,080
Speaker 4: the blame on the media for that. I think it's

844
00:43:04,320 --> 00:43:06,600
Speaker 4: a contrast and how the media is covered it. When

845
00:43:06,640 --> 00:43:10,120
Speaker 4: Republicans literally were the ones withholding their votes. That doesn't

846
00:43:10,160 --> 00:43:12,319
Speaker 4: mean there's no blame to go around. There's definitely blame

847
00:43:12,360 --> 00:43:16,239
Speaker 4: to go around in this government shutdown. But maybe that's

848
00:43:16,280 --> 00:43:20,319
Speaker 4: weighing on Democrats' minds that they're sort of technically, if

849
00:43:20,360 --> 00:43:23,600
Speaker 4: the public is blaming Republicans, they have an upper hand

850
00:43:23,760 --> 00:43:27,480
Speaker 4: of some sort when they go to negotiation presumably this week.

851
00:43:27,560 --> 00:43:30,640
Speaker 4: But the positions are hardened when you look at Republican leadership.

852
00:43:30,640 --> 00:43:33,319
Speaker 4: They really are not projecting that they're willing to come

853
00:43:33,320 --> 00:43:36,200
Speaker 4: to the table on premiums in the ACA subsidies.

854
00:43:36,239 --> 00:43:38,080
Speaker 5: So we'll see, yeah, we will.

855
00:43:38,239 --> 00:43:41,640
Speaker 2: And you know, I think there's also concern you were

856
00:43:41,640 --> 00:43:45,600
Speaker 2: saying that vote might use the you know, the funding

857
00:43:45,640 --> 00:43:49,720
Speaker 2: shortage on food stamps to make some sort of permanent cuts,

858
00:43:49,760 --> 00:43:52,040
Speaker 2: even though again it should be illegal, that should be

859
00:43:52,040 --> 00:43:54,000
Speaker 2: something that has to go through Congress, but you know,

860
00:43:54,080 --> 00:43:59,040
Speaker 2: whatever laws don't exist anymore. Apparently, there's also concern that

861
00:43:59,080 --> 00:44:02,200
Speaker 2: those federal workers actually who you know, some of them

862
00:44:02,200 --> 00:44:03,319
Speaker 2: are working for free right now.

863
00:44:03,320 --> 00:44:05,600
Speaker 3: By the way, don't get back pay a lot.

864
00:44:06,040 --> 00:44:08,200
Speaker 2: Because he put on a memo saying we're probably not

865
00:44:08,239 --> 00:44:10,879
Speaker 2: going to pay Actually, and again, there is a law

866
00:44:10,920 --> 00:44:13,840
Speaker 2: that was passed that mandates during a shutdown, federal government

867
00:44:13,880 --> 00:44:17,279
Speaker 2: workers will get their back pay. But this administration just

868
00:44:17,320 --> 00:44:19,400
Speaker 2: does whatever the hell they want. So I don't think

869
00:44:19,400 --> 00:44:23,000
Speaker 2: that federal government workers feel particularly secure that they're ever

870
00:44:23,080 --> 00:44:26,240
Speaker 2: going to see the paychecks that they're missing right now.

871
00:44:26,719 --> 00:44:28,279
Speaker 2: You know, this is the guy who said that he

872
00:44:28,320 --> 00:44:29,680
Speaker 2: wants to cause them what he say, he wants to

873
00:44:29,680 --> 00:44:32,040
Speaker 2: cause them trauma or something like that. Yeah, So, I

874
00:44:32,080 --> 00:44:34,160
Speaker 2: mean that is part of his goal, that's his m

875
00:44:34,400 --> 00:44:38,399
Speaker 2: he's true ideologue in this regard. And so I don't

876
00:44:38,400 --> 00:44:42,480
Speaker 2: think anyone should be surprised that he, in particular would

877
00:44:42,520 --> 00:44:44,799
Speaker 2: who is one of the more powerful members of the administration,

878
00:44:44,920 --> 00:44:47,680
Speaker 2: certainly one of the more you know, ideological architects of

879
00:44:47,719 --> 00:44:50,600
Speaker 2: the direction of this administration, that he would use this

880
00:44:50,640 --> 00:44:53,960
Speaker 2: as an excuse to create more pain and suffering among

881
00:44:54,320 --> 00:44:57,720
Speaker 2: the federal government workforce and to shrink the federal government

882
00:44:57,800 --> 00:45:00,360
Speaker 2: more than they've been able to successfully do.

883
00:45:00,360 --> 00:45:02,960
Speaker 3: Doge and already they ran into you know, a doge.

884
00:45:03,000 --> 00:45:04,799
Speaker 2: They ran into things where they'd fire a bunch of

885
00:45:04,800 --> 00:45:06,640
Speaker 2: people from the CDC or whatever and be like, oh,

886
00:45:06,680 --> 00:45:08,120
Speaker 2: you know what, actually we do want to track at

887
00:45:08,120 --> 00:45:11,279
Speaker 2: Bola it turns out, or you know, they fire a

888
00:45:11,280 --> 00:45:12,960
Speaker 2: bunch of people from that vein and be oh, you know,

889
00:45:13,000 --> 00:45:15,239
Speaker 2: with this whole like error plane scrashing to each other,

890
00:45:15,400 --> 00:45:17,399
Speaker 2: situation is not really great. Let's bring some of those

891
00:45:17,400 --> 00:45:20,200
Speaker 2: people back. They've already had to do some of that.

892
00:45:20,880 --> 00:45:22,480
Speaker 2: You know, we had the situation in Texas with the

893
00:45:22,480 --> 00:45:24,480
Speaker 2: floods and a lot of questions over whether or not

894
00:45:24,760 --> 00:45:26,760
Speaker 2: some of the cuts that have been made to relevant

895
00:45:26,800 --> 00:45:30,560
Speaker 2: agencies there impacted the ability to respond to those absolutely

896
00:45:30,560 --> 00:45:34,440
Speaker 2: devastating floods. So they've already run into like hitting the

897
00:45:34,480 --> 00:45:36,960
Speaker 2: bone in some of the cuts that they've made. But

898
00:45:37,440 --> 00:45:40,200
Speaker 2: there's no sign that individuals like him in particular are

899
00:45:40,239 --> 00:45:41,279
Speaker 2: interested in slowing down.

900
00:45:41,680 --> 00:45:44,400
Speaker 4: Well. And also, listen, I'm someone who thinks Snap needs

901
00:45:44,520 --> 00:45:47,600
Speaker 4: significant reforms and somebody who thinks Obamacare needs significant reforms.

902
00:45:47,600 --> 00:45:49,480
Speaker 4: And Stoler has a good post on that over at

903
00:45:49,480 --> 00:45:50,200
Speaker 4: Big This Morning.

904
00:45:50,280 --> 00:45:51,239
Speaker 3: Yeah frustrating that too.

905
00:45:51,320 --> 00:45:52,359
Speaker 5: Yeah, it's super good.

906
00:45:52,400 --> 00:45:56,399
Speaker 4: But the there's a lot of tramp voters who are

907
00:45:56,520 --> 00:46:00,560
Speaker 4: on snaff So that's another As Democrats people turn to

908
00:46:00,680 --> 00:46:03,439
Speaker 4: Washington this week, that's another thing, that's another big piece

909
00:46:03,440 --> 00:46:06,520
Speaker 4: of leverage. It's another arrow in their quiver as they

910
00:46:06,600 --> 00:46:09,080
Speaker 4: try to bring Republicans to the table on something. In

911
00:46:09,080 --> 00:46:11,560
Speaker 4: addition to the subsidies, which Marjorie Taylor Green has been

912
00:46:11,600 --> 00:46:15,520
Speaker 4: outspoken about the Obamacare subsidies. Snap is that I mean,

913
00:46:15,560 --> 00:46:18,200
Speaker 4: if you have most of the country blaming Republicans for

914
00:46:18,239 --> 00:46:22,360
Speaker 4: the shutdown, and then you have troops going unpaid lines

915
00:46:22,360 --> 00:46:28,360
Speaker 4: at food pantries, snap benefits lapsing, and like potentially increases

916
00:46:28,360 --> 00:46:32,239
Speaker 4: in premiums, that's starting to look pretty dire for Republicans

917
00:46:32,239 --> 00:46:34,840
Speaker 4: if they don't come to the table. It's again, I

918
00:46:34,880 --> 00:46:37,239
Speaker 4: think it's a different situation than another shutdowns. Democrats are

919
00:46:37,280 --> 00:46:41,000
Speaker 4: the ones technically withholding the votes, but Republicans, if they're

920
00:46:41,040 --> 00:46:43,320
Speaker 4: taking the blame with the public, it's a that's a

921
00:46:43,400 --> 00:46:46,520
Speaker 4: recipe for a political disaster heading into a midterm year.

922
00:46:46,560 --> 00:46:48,759
Speaker 4: I don't think people vote on shutdowns, you know, a

923
00:46:48,840 --> 00:46:50,680
Speaker 4: year from now, I'm not sure that'll be in the

924
00:46:50,719 --> 00:46:53,759
Speaker 4: front of anybody's mind. But obviously it's one of those

925
00:46:53,760 --> 00:46:56,919
Speaker 4: moments that can make you feel whether this party cares

926
00:46:56,960 --> 00:46:59,360
Speaker 4: about you or not, this the MAGA movement, whether it

927
00:46:59,480 --> 00:47:02,560
Speaker 4: really true has your best interest at hand. That's something

928
00:47:02,640 --> 00:47:04,280
Speaker 4: that can kind of sink into people's psyche.

929
00:47:04,440 --> 00:47:06,279
Speaker 2: They may not vote on the shutdown, but they may

930
00:47:06,320 --> 00:47:08,480
Speaker 2: well vote on, Hey, my premiums just went up one

931
00:47:08,520 --> 00:47:12,040
Speaker 2: hundred percent, you know. And that's to your point about

932
00:47:12,440 --> 00:47:16,320
Speaker 2: this really disproportioning hitting the MAGA base. Seventy three percent

933
00:47:16,400 --> 00:47:20,319
Speaker 2: of those subsidies go to Red states because it's it's

934
00:47:20,400 --> 00:47:24,400
Speaker 2: overwhelmingly the states that didn't expand Medicaid. That's where these

935
00:47:24,440 --> 00:47:26,640
Speaker 2: subsidies are really filling the gap, and those are all

936
00:47:26,680 --> 00:47:29,080
Speaker 2: red states. The poor states in the country are all

937
00:47:29,280 --> 00:47:31,719
Speaker 2: Red states, so you'll have a disproportionate number of the

938
00:47:31,719 --> 00:47:35,319
Speaker 2: stat benefits going to those states as well. So, yeah,

939
00:47:35,400 --> 00:47:38,360
Speaker 2: you're you're talking about a lot of pain, specifically for

940
00:47:38,560 --> 00:47:41,440
Speaker 2: oftentimes Republican voters and oftentimes some of the most you know,

941
00:47:41,480 --> 00:47:43,680
Speaker 2: diehard supporters of Trump himself.

942
00:47:44,600 --> 00:47:46,600
Speaker 4: I mean, yeah, it's one of those It could potentially

943
00:47:46,640 --> 00:47:48,960
Speaker 4: be one of those moments actually, sort of like the Epstein,

944
00:47:49,760 --> 00:47:52,880
Speaker 4: particularly when when Pambondi said we're closing the case basically

945
00:47:52,920 --> 00:47:54,960
Speaker 4: like wipe our hands were done. It's one of those

946
00:47:55,040 --> 00:47:58,560
Speaker 4: moments that can make people who who thought, you know,

947
00:47:58,560 --> 00:48:00,759
Speaker 4: as Donald Trump was campaigning saying everybody is going to

948
00:48:00,800 --> 00:48:03,439
Speaker 4: have healthcare, you know, I think at the Madison Square

949
00:48:03,480 --> 00:48:05,360
Speaker 4: Garden rally, he said he was going to cut energy

950
00:48:05,360 --> 00:48:09,520
Speaker 4: prices in half and inflation was going to significantly decrease.

951
00:48:09,800 --> 00:48:11,920
Speaker 4: And that's why he's so concerned about the beef, as

952
00:48:11,960 --> 00:48:14,760
Speaker 4: we talked about earlier in the show, because beef prices

953
00:48:14,760 --> 00:48:17,040
Speaker 4: are the things that are going high, and he knows

954
00:48:16,840 --> 00:48:19,480
Speaker 4: he's shrewd enough politically to know that that really matters

955
00:48:19,480 --> 00:48:21,799
Speaker 4: to voters, because he talked about it on the campaign trail.

956
00:48:22,080 --> 00:48:24,760
Speaker 4: So it could potentially be one of those moments where

957
00:48:25,160 --> 00:48:28,920
Speaker 4: the working class section of the magabase starts to question

958
00:48:29,520 --> 00:48:31,960
Speaker 4: whether or not MAGA really does care about them. You

959
00:48:32,000 --> 00:48:35,000
Speaker 4: could see that happening and Epstein was a big moment

960
00:48:35,080 --> 00:48:37,719
Speaker 4: where they said, is this.

961
00:48:37,680 --> 00:48:40,480
Speaker 5: Really about what we thought it was about? Does he

962
00:48:40,680 --> 00:48:42,600
Speaker 5: really care like he said he did?

963
00:48:43,280 --> 00:48:46,160
Speaker 4: And you know that not everybody in who voted for

964
00:48:46,200 --> 00:48:49,479
Speaker 4: Trump loves Trump, but there's a level of he told

965
00:48:49,480 --> 00:48:51,360
Speaker 4: you everybody else, he was right to tell you everybody

966
00:48:51,400 --> 00:48:52,000
Speaker 4: else was wrong.

967
00:48:52,880 --> 00:48:54,560
Speaker 5: Does that mean that he's right, that.

968
00:48:54,520 --> 00:48:57,680
Speaker 2: He's right right, yeah, and that's really making things better exactly. Well,

969
00:48:57,760 --> 00:49:00,760
Speaker 2: I will say I think Epstein landed much more clearly,

970
00:49:00,800 --> 00:49:03,560
Speaker 2: squarely at his feet, because it's like cash, it's his

971
00:49:03,719 --> 00:49:06,480
Speaker 2: people right right. With this, I could see a lot

972
00:49:06,480 --> 00:49:10,080
Speaker 2: of people blaming. I mean, the thing in the Trump

973
00:49:10,280 --> 00:49:13,920
Speaker 2: era that we've seen is similar to how Obama had

974
00:49:13,920 --> 00:49:18,560
Speaker 2: this particular hold you on a certain population. Trump has

975
00:49:18,560 --> 00:49:21,040
Speaker 2: a certain hold and it doesn't translate to the rest

976
00:49:21,040 --> 00:49:21,960
Speaker 2: of the Republican Party.

977
00:49:22,000 --> 00:49:22,920
Speaker 3: You know, the midterms.

978
00:49:22,719 --> 00:49:26,680
Speaker 2: He hasn't done well in midterms in particular, and so

979
00:49:27,000 --> 00:49:28,799
Speaker 2: the other thing is maybe.

980
00:49:28,520 --> 00:49:29,399
Speaker 3: People still are low.

981
00:49:29,400 --> 00:49:31,919
Speaker 2: It's not Trump's fault, this Congress can't get their act

982
00:49:31,920 --> 00:49:35,400
Speaker 2: together or whatever. But that doesn't exactly make them excited

983
00:49:35,440 --> 00:49:38,600
Speaker 2: to come out and vote for Republicans in midterm elections upcoming.

984
00:49:38,680 --> 00:49:41,399
Speaker 4: Well, it doesn't also necessarily give you the faith in

985
00:49:41,560 --> 00:49:44,960
Speaker 4: a mega candidate that you might have otherwise. Right, they're saying,

986
00:49:45,000 --> 00:49:47,000
Speaker 4: you know, because there was the working class at this

987
00:49:47,040 --> 00:49:49,080
Speaker 4: idea that the Republicans worked for them for a long time.

988
00:49:49,239 --> 00:49:51,520
Speaker 5: And you know, we've all talked about why that might be.

989
00:49:51,719 --> 00:49:55,719
Speaker 4: But that's always been a problem for Republicans. And it's

990
00:49:55,760 --> 00:49:57,799
Speaker 4: especially a problem if you've already traded a lot of

991
00:49:57,840 --> 00:50:01,319
Speaker 4: suburban voters for more working class voters, especially in the

992
00:50:01,360 --> 00:50:05,040
Speaker 4: Roust belt place like Wisconsin, Pennsylvania, Ohio. So does the

993
00:50:05,120 --> 00:50:08,759
Speaker 4: MAGA candidate lose some credibility if there's still you know,

994
00:50:08,760 --> 00:50:13,360
Speaker 4: your typical Republican and they're like Brooks Brothers suit but

995
00:50:13,400 --> 00:50:17,080
Speaker 4: they claim to be maga. The trust gap is significant

996
00:50:17,239 --> 00:50:20,759
Speaker 4: when voters who vote for Donald Trump A have to

997
00:50:21,040 --> 00:50:21,759
Speaker 4: go vote for you?

998
00:50:21,920 --> 00:50:23,440
Speaker 5: Do they even vote? Let alone?

999
00:50:23,480 --> 00:50:25,600
Speaker 4: If they do vote, do they vote for you when

1000
00:50:25,920 --> 00:50:28,440
Speaker 4: they see their snap benefits lapsing and their premium is

1001
00:50:28,440 --> 00:50:29,480
Speaker 4: about to explode.

1002
00:50:29,719 --> 00:50:32,919
Speaker 2: Yeah, it feels like a lot of like twenty ten

1003
00:50:33,040 --> 00:50:37,399
Speaker 2: level kind of like disillusionment is what I've Potentially we'll

1004
00:50:37,400 --> 00:50:38,040
Speaker 2: see interesting.

1005
00:50:38,120 --> 00:50:41,200
Speaker 4: Yeah, you should interview somebody who maybe ran for Congress

1006
00:50:41,200 --> 00:50:41,759
Speaker 4: in twenty ten.

1007
00:50:42,360 --> 00:50:45,160
Speaker 3: I think I have an en see what we could do.

1008
00:50:45,520 --> 00:50:47,000
Speaker 4: I actually always love it when you talk about it

1009
00:50:47,040 --> 00:50:49,160
Speaker 4: because it was such an important year and there's so

1010
00:50:49,160 --> 00:50:53,040
Speaker 4: many different trends that came to like blossom six years later.

1011
00:50:53,200 --> 00:50:55,279
Speaker 2: Yeah, I had a front rosie because I went to

1012
00:50:55,360 --> 00:50:58,360
Speaker 2: every I went to so many tea party meetings because

1013
00:50:58,360 --> 00:51:00,600
Speaker 2: my policy was, like anyone in the strict invites me

1014
00:51:00,680 --> 00:51:02,680
Speaker 2: to come talk, I will come talk to you. So

1015
00:51:02,760 --> 00:51:04,879
Speaker 2: I got berated by a lot of angry people who

1016
00:51:04,920 --> 00:51:07,040
Speaker 2: thought that I was ushering in sodom and gomorrah.

1017
00:51:08,120 --> 00:51:12,200
Speaker 4: To be fair, to be fair, you were here, we

1018
00:51:12,239 --> 00:51:14,560
Speaker 4: are here, we are Have you heard wop?

1019
00:51:14,680 --> 00:51:16,040
Speaker 5: I blame it. I blame you for that.

1020
00:51:16,880 --> 00:51:20,080
Speaker 2: I blame you for you should do your Ben Shapiro

1021
00:51:20,239 --> 00:51:22,759
Speaker 2: esque rendition, your own rendition of four.

1022
00:51:27,200 --> 00:51:28,280
Speaker 3: All right, moving along.

1023
00:51:28,120 --> 00:51:30,799
Speaker 4: Speaking of Ben Shapiro, let's move on to Candas there

1024
00:51:30,840 --> 00:51:31,160
Speaker 4: we go.

1025
00:51:31,800 --> 00:51:35,080
Speaker 2: Candice has some very interesting thoughts about some of the

1026
00:51:35,160 --> 00:51:39,560
Speaker 2: tech oligarchs who are, like, you know, completely taking all

1027
00:51:39,600 --> 00:51:42,480
Speaker 2: of our fates into their hands with no input from

1028
00:51:42,600 --> 00:51:46,080
Speaker 2: us whatsoever. So glad to see that she's focusing her

1029
00:51:46,560 --> 00:51:47,719
Speaker 2: mental energy on them.

1030
00:51:47,760 --> 00:51:49,600
Speaker 3: Her take is very interesting, though. Let's take a lism.

1031
00:51:49,840 --> 00:51:51,560
Speaker 13: I don't even think people are human, Like I look

1032
00:51:51,640 --> 00:51:55,480
Speaker 13: at Emon Mosku and Sam Altman and Peter Teel, and

1033
00:51:55,520 --> 00:51:57,719
Speaker 13: I'm pretty sure they're hybrid, you know what I mean,

1034
00:51:58,080 --> 00:52:01,080
Speaker 13: Like they just look like a Apple software that I

1035
00:52:01,120 --> 00:52:03,480
Speaker 13: should be able to download at night, you know, like

1036
00:52:03,600 --> 00:52:05,160
Speaker 13: my phone's getting an update or something.

1037
00:52:05,160 --> 00:52:06,920
Speaker 14: It's something in the eyes, like I don't know. I'm like,

1038
00:52:06,960 --> 00:52:10,200
Speaker 14: I don't know. I don't I don't know if I stabbed.

1039
00:52:09,800 --> 00:52:11,120
Speaker 13: You, if you bleed, you know, I'm not going to

1040
00:52:11,160 --> 00:52:13,960
Speaker 13: stab them, But I don't know. If they bleed all

1041
00:52:14,040 --> 00:52:16,080
Speaker 13: the way, I think a battery would fall out, you

1042
00:52:16,080 --> 00:52:16,520
Speaker 13: know what I mean.

1043
00:52:17,040 --> 00:52:18,680
Speaker 14: And I just get that sense.

1044
00:52:18,719 --> 00:52:21,799
Speaker 13: I've always known it was demonic, and people just get

1045
00:52:21,840 --> 00:52:24,400
Speaker 13: on board because, as we talk about in this book,

1046
00:52:25,160 --> 00:52:29,360
Speaker 13: they are using science and this idea of technology and

1047
00:52:29,360 --> 00:52:33,319
Speaker 13: this idea of transforming society for the better to indoctoring us.

1048
00:52:33,200 --> 00:52:34,240
Speaker 14: Into accepting this.

1049
00:52:34,800 --> 00:52:37,680
Speaker 13: And it's wrong and it's backwards, and they weigh they're

1050
00:52:37,840 --> 00:52:39,040
Speaker 13: the main component of.

1051
00:52:38,920 --> 00:52:40,879
Speaker 14: All of this is psychology, right.

1052
00:52:40,920 --> 00:52:42,920
Speaker 13: They're able to do it because of psychology, making you

1053
00:52:42,960 --> 00:52:45,680
Speaker 13: think that society has gotten better. Our kids have objectively

1054
00:52:45,719 --> 00:52:49,919
Speaker 13: gotten dumber, we've become fatter, we've become less healthy, we've

1055
00:52:49,920 --> 00:52:55,080
Speaker 13: become less emotionally sound, and yet they are convincing us

1056
00:52:55,080 --> 00:52:58,280
Speaker 13: that this is like human humanity is great leap forward.

1057
00:52:58,760 --> 00:53:00,400
Speaker 14: We put a man of the mood. He just like

1058
00:53:00,480 --> 00:53:02,880
Speaker 14: called them up and was like, hey, Press, what's up,

1059
00:53:02,920 --> 00:53:04,759
Speaker 14: I'm up here. Yeah, it's so cool. It's really great,

1060
00:53:04,800 --> 00:53:08,719
Speaker 14: it's nice starry night up here. Caminet text you.

1061
00:53:08,760 --> 00:53:11,799
Speaker 13: I go by in sixty nine and they get these people,

1062
00:53:12,000 --> 00:53:12,640
Speaker 13: they tell you, look.

1063
00:53:12,520 --> 00:53:15,200
Speaker 14: He's a genius. Real, Oh, they're all right away, he's

1064
00:53:15,200 --> 00:53:15,560
Speaker 14: a genius.

1065
00:53:15,560 --> 00:53:17,000
Speaker 13: So we should just accept that you a Muscus is

1066
00:53:17,000 --> 00:53:19,440
Speaker 13: a genius because like all the writers who are obviously

1067
00:53:19,680 --> 00:53:22,200
Speaker 13: in doctrine into the occult, are telling us that this

1068
00:53:22,280 --> 00:53:24,960
Speaker 13: is the next person that we should worship. The establishment

1069
00:53:25,000 --> 00:53:28,120
Speaker 13: of Hollywood, it was all cults. They were all Alistair

1070
00:53:28,160 --> 00:53:31,880
Speaker 13: Crowley proteges who were just raping kids and summoning demons,

1071
00:53:31,880 --> 00:53:34,000
Speaker 13: and demons are real. So at the same time that

1072
00:53:34,080 --> 00:53:37,920
Speaker 13: they're summoning demons, they are making us all believe.

1073
00:53:38,120 --> 00:53:39,239
Speaker 14: That faith is not real.

1074
00:53:39,760 --> 00:53:44,120
Speaker 13: And that has been I think the greatest, the greatest

1075
00:53:44,120 --> 00:53:45,880
Speaker 13: trick that the devil ever.

1076
00:53:45,719 --> 00:53:48,280
Speaker 14: Played, right is making people think they didn't exist.

1077
00:53:48,920 --> 00:53:52,840
Speaker 2: Emily agree and disagree.

1078
00:53:53,160 --> 00:53:56,560
Speaker 5: Uh, she's certainly cooking crystals. She's certainly cooking.

1079
00:53:56,600 --> 00:53:58,799
Speaker 3: She also is cooking. Everyone can agree on that.

1080
00:53:58,920 --> 00:53:59,520
Speaker 5: She was also a.

1081
00:53:59,560 --> 00:54:03,400
Speaker 4: Potentially i mean Trump for her friend Charlie Kirk's assassination.

1082
00:54:04,719 --> 00:54:07,440
Speaker 4: There's a lot of speculation which we do not mean

1083
00:54:07,480 --> 00:54:11,120
Speaker 4: to get into because we're not professional medical professionals that

1084
00:54:11,160 --> 00:54:14,640
Speaker 4: she may be having some type of episode because she

1085
00:54:14,840 --> 00:54:19,560
Speaker 4: is sort of starting to sound like the person who

1086
00:54:19,840 --> 00:54:22,160
Speaker 4: has like a like literal tinfoil on their head on

1087
00:54:22,200 --> 00:54:22,960
Speaker 4: the street corner.

1088
00:54:23,560 --> 00:54:25,799
Speaker 2: Okay, but I mean she has been doing the whole

1089
00:54:25,800 --> 00:54:27,520
Speaker 2: Bridget Macron thing for a while now.

1090
00:54:27,640 --> 00:54:32,399
Speaker 4: Yeah, it's true entirely when you're here, although I will

1091
00:54:32,440 --> 00:54:36,560
Speaker 4: say that I think that particular I imagine people sense

1092
00:54:36,600 --> 00:54:40,920
Speaker 4: it in that particular clip, there's a certain usually you

1093
00:54:40,960 --> 00:54:43,400
Speaker 4: can follow her logic when it's crazy, you know what

1094
00:54:43,440 --> 00:54:46,320
Speaker 4: I mean, You're you're like, this is wild and wacky,

1095
00:54:46,360 --> 00:54:49,800
Speaker 4: but I can sort of follow along. There's a sense

1096
00:54:49,840 --> 00:54:52,160
Speaker 4: of like just listening to her there. I don't know,

1097
00:54:52,360 --> 00:54:53,959
Speaker 4: it seems different to me. It seems like a little

1098
00:54:53,960 --> 00:54:56,920
Speaker 4: bit more, a little bit less rational, like we're just.

1099
00:54:57,200 --> 00:54:58,840
Speaker 3: We're just her logic on this perfectly.

1100
00:54:59,040 --> 00:55:02,640
Speaker 2: Crystal is bull myself, I followed this logic personally perfectly.

1101
00:55:02,719 --> 00:55:08,480
Speaker 2: But I mean, like, let's say it lets humanity off

1102
00:55:08,520 --> 00:55:11,080
Speaker 2: the hook too much to say that these characters are

1103
00:55:11,120 --> 00:55:11,839
Speaker 2: not actually human.

1104
00:55:12,200 --> 00:55:14,040
Speaker 3: That would be a very yeah.

1105
00:55:14,040 --> 00:55:16,800
Speaker 2: I would love to think that these are not fully humans,

1106
00:55:16,800 --> 00:55:19,240
Speaker 2: that these are some sort of weird hybrid alien beings

1107
00:55:19,600 --> 00:55:21,759
Speaker 2: who are you know, and that's why they are doing

1108
00:55:21,840 --> 00:55:25,560
Speaker 2: all of these terrible things. But in reality they are human,

1109
00:55:25,600 --> 00:55:28,879
Speaker 2: and humans are capable of, you know, terrible destruction and

1110
00:55:29,360 --> 00:55:31,480
Speaker 2: you know, and the weird thing is that all three

1111
00:55:31,560 --> 00:55:34,160
Speaker 2: of them, I think, see themselves as like heroes actually,

1112
00:55:34,360 --> 00:55:39,640
Speaker 2: and this is uh, it's it's also who sort of

1113
00:55:39,880 --> 00:55:42,200
Speaker 2: has a somewhat directional truth to it though, because they

1114
00:55:42,239 --> 00:55:47,120
Speaker 2: also are transhumans. They want into the hybrids that she's

1115
00:55:47,160 --> 00:55:51,080
Speaker 2: talking about. They actually do want to go in that direction,

1116
00:55:51,200 --> 00:55:54,600
Speaker 2: the merging of the human and the machine and uh,

1117
00:55:54,640 --> 00:55:57,880
Speaker 2: and are deeply interested, of course, in consolidating all of

1118
00:55:57,880 --> 00:56:00,600
Speaker 2: his power wealth in their own hands at the expense

1119
00:56:00,760 --> 00:56:03,439
Speaker 2: of actual humanity. Which is why when Peter Thiale gets

1120
00:56:03,440 --> 00:56:05,719
Speaker 2: asked you think by ross out that do you think

1121
00:56:05,760 --> 00:56:09,319
Speaker 2: the human race should survive? He has to sputter and

1122
00:56:09,600 --> 00:56:14,239
Speaker 2: stumble and mumble and think before he can answer what

1123
00:56:14,400 --> 00:56:17,000
Speaker 2: should be the easiest question of all time.

1124
00:56:18,000 --> 00:56:19,719
Speaker 4: You know, what actually they're doing is turning all of

1125
00:56:19,840 --> 00:56:22,640
Speaker 4: us into candis OANs like that's actually what's happening is

1126
00:56:22,680 --> 00:56:27,080
Speaker 4: they're turning all of us into people who are driven by.

1127
00:56:26,960 --> 00:56:28,920
Speaker 5: The algorithm into madness.

1128
00:56:29,200 --> 00:56:32,400
Speaker 4: And I think she's a glimpse and producers Mac and

1129
00:56:32,440 --> 00:56:35,000
Speaker 4: Griffin are just saying only crime is being right too

1130
00:56:35,040 --> 00:56:38,839
Speaker 4: early about bandits, and Mac is like Kandas is onto

1131
00:56:38,880 --> 00:56:43,479
Speaker 4: something here, Yeah, because like that's what happens is there's

1132
00:56:43,760 --> 00:56:47,600
Speaker 4: truth to the fact that they want to make us

1133
00:56:47,719 --> 00:56:51,040
Speaker 4: less human. And there's something very human about wanting to

1134
00:56:51,040 --> 00:56:54,759
Speaker 4: make us less human because it's driven by greed and

1135
00:56:55,200 --> 00:56:59,240
Speaker 4: lust for power and utopianism, which has been with us

1136
00:56:59,320 --> 00:57:03,400
Speaker 4: since the human race has existed. And so this drive

1137
00:57:03,440 --> 00:57:07,600
Speaker 4: for transhumanism is deeply human. And actually Candice was getting

1138
00:57:07,600 --> 00:57:09,399
Speaker 4: to that when she was talking about the Devil's best

1139
00:57:09,400 --> 00:57:13,720
Speaker 4: trick is making people think that the devil doesn't exist.

1140
00:57:13,760 --> 00:57:16,200
Speaker 4: Like that's what she was getting at with that point.

1141
00:57:16,560 --> 00:57:20,160
Speaker 4: There's something deeply, deeply human about the pursuit of power

1142
00:57:20,400 --> 00:57:25,160
Speaker 4: and money that tricks people into buying utopian fantasies, and

1143
00:57:25,520 --> 00:57:28,320
Speaker 4: even like the rich and powerful people themselves will be

1144
00:57:28,680 --> 00:57:31,240
Speaker 4: seduced by this idea that there it's not actually about

1145
00:57:31,240 --> 00:57:33,240
Speaker 4: the money, it's not actually about the power. It's about

1146
00:57:33,640 --> 00:57:37,600
Speaker 4: the idea that we're creating a better life, a better world,

1147
00:57:37,840 --> 00:57:40,600
Speaker 4: which I think everybody can see over the last like

1148
00:57:40,640 --> 00:57:45,080
Speaker 4: what twenty year experiment since Peter Teel's technologies and just

1149
00:57:45,120 --> 00:57:47,760
Speaker 4: in the last couple of years of Sam Altman's technologies,

1150
00:57:48,120 --> 00:57:49,800
Speaker 4: and what Elon Musk has done.

1151
00:57:49,760 --> 00:57:53,360
Speaker 5: To acts, which I mean, I just look at it.

1152
00:57:54,640 --> 00:57:56,480
Speaker 5: What that does is it makes us.

1153
00:57:56,560 --> 00:58:00,000
Speaker 4: It turns us all into crazy people because the Algori

1154
00:58:00,080 --> 00:58:04,640
Speaker 4: rhythm has bad incentives, and we communicate, we export all

1155
00:58:04,640 --> 00:58:05,440
Speaker 4: of our communication.

1156
00:58:05,960 --> 00:58:07,360
Speaker 5: This is just a preview of what's to come.

1157
00:58:07,480 --> 00:58:10,760
Speaker 4: We've exported so much of our communication onto platforms that

1158
00:58:11,000 --> 00:58:13,440
Speaker 4: can be the flip of a switch by one person

1159
00:58:13,480 --> 00:58:16,560
Speaker 4: like Elon Musk can change the direction of.

1160
00:58:16,480 --> 00:58:18,880
Speaker 5: The entire political discourse. Yeah, we've seen it. We know

1161
00:58:18,920 --> 00:58:20,240
Speaker 5: that that's what can be done.

1162
00:58:20,320 --> 00:58:24,240
Speaker 4: Yeah, and that controls not just what we say, uh,

1163
00:58:24,440 --> 00:58:27,880
Speaker 4: but it controls the incentive system of what we decide

1164
00:58:28,040 --> 00:58:29,360
Speaker 4: we're going to say.

1165
00:58:29,480 --> 00:58:33,080
Speaker 2: They're colonizing our minds. I mean, that's what they're doing

1166
00:58:33,440 --> 00:58:37,080
Speaker 2: and successfully, by the way. And so I mean that's

1167
00:58:37,160 --> 00:58:40,120
Speaker 2: why listen, as you know, wild is what she said

1168
00:58:40,120 --> 00:58:44,440
Speaker 2: there is. I am glad to see her taking an

1169
00:58:44,440 --> 00:58:48,560
Speaker 2: interest in this subject because, as we've discussed before, like

1170
00:58:48,680 --> 00:58:52,240
Speaker 2: this is this is a dire situation we're facing. Yes,

1171
00:58:52,360 --> 00:58:56,479
Speaker 2: it's dire from a job loss perspective. It's dire from

1172
00:58:56,560 --> 00:58:59,959
Speaker 2: a resources and energy perspective. It's dire from a cost

1173
00:59:00,080 --> 00:59:03,560
Speaker 2: perspective in terms of our electricity bills. It's dire from

1174
00:59:03,600 --> 00:59:06,320
Speaker 2: a controlling our thoughts and minds and being able to

1175
00:59:06,360 --> 00:59:10,560
Speaker 2: tell truth from fiction and I live in reality together perspective.

1176
00:59:11,240 --> 00:59:14,720
Speaker 2: It's potentially dire from like an actual, true existential threat,

1177
00:59:14,760 --> 00:59:16,720
Speaker 2: which I think is a real and genuine risk that

1178
00:59:16,760 --> 00:59:19,400
Speaker 2: I do not put off the table. It's dire from

1179
00:59:19,480 --> 00:59:22,800
Speaker 2: a mass consolidation of wealth and power perspective. Like you

1180
00:59:22,840 --> 00:59:25,040
Speaker 2: want to talk about a democracy crisis, There's no way

1181
00:59:25,080 --> 00:59:28,840
Speaker 2: a democracy survives if you have someone one of these

1182
00:59:28,920 --> 00:59:32,560
Speaker 2: characters able to achieve AGI and all of the incredible

1183
00:59:32,600 --> 00:59:35,880
Speaker 2: economic power, power and benefits that come along with that.

1184
00:59:36,560 --> 00:59:40,360
Speaker 2: So you know, which is why someone like Elon Musk,

1185
00:59:40,440 --> 00:59:44,000
Speaker 2: who was very concerned about the things we're talking about,

1186
00:59:44,680 --> 00:59:48,160
Speaker 2: and that's why he started open AI with Sam Altmithie, Okay,

1187
00:59:48,160 --> 00:59:49,800
Speaker 2: we can develop this, but we'll do it in this

1188
00:59:49,920 --> 00:59:50,640
Speaker 2: nonprofit way.

1189
00:59:50,680 --> 00:59:52,280
Speaker 3: No, I'm not saying that the conception was.

1190
00:59:52,520 --> 00:59:55,680
Speaker 2: Like was like great from the start, but he had

1191
00:59:55,760 --> 00:59:57,240
Speaker 2: some mind of we have to do this in a

1192
00:59:57,280 --> 01:00:00,040
Speaker 2: safe way. It can't be for profit. It needs to

1193
01:00:00,080 --> 01:00:02,640
Speaker 2: be in the public interest. And then once he sees

1194
01:00:02,680 --> 01:00:04,880
Speaker 2: everyone x by the way, yep, and once he sees

1195
01:00:04,880 --> 01:00:06,800
Speaker 2: everyone else is off to the races, then he's off

1196
01:00:06,800 --> 01:00:10,760
Speaker 2: to the races too. So it's it is an actually

1197
01:00:10,800 --> 01:00:14,720
Speaker 2: existential conversation, in my opinion, And if you listen to that,

1198
01:00:14,800 --> 01:00:17,120
Speaker 2: it's an existential conversation because they'll tell you we're trying

1199
01:00:17,120 --> 01:00:19,880
Speaker 2: to eliminate human labor, we're trying to rewrite the social contract.

1200
01:00:20,160 --> 01:00:23,360
Speaker 2: We want to completely upend society as it exists today.

1201
01:00:23,880 --> 01:00:26,720
Speaker 2: So I am glad to see figures on the right

1202
01:00:26,800 --> 01:00:30,640
Speaker 2: late Candice occasionally see Bannon, you know, certainly like figures

1203
01:00:30,640 --> 01:00:33,600
Speaker 2: like you, Sager, who are looking at this with clear

1204
01:00:33,640 --> 01:00:36,160
Speaker 2: eyes and going this is this is horrific, and we

1205
01:00:36,360 --> 01:00:38,439
Speaker 2: have to come together and take control in some way

1206
01:00:38,480 --> 01:00:42,800
Speaker 2: because otherwise, you know, we are barreling towards an incredibly

1207
01:00:43,520 --> 01:00:44,760
Speaker 2: risky and dire future.

1208
01:00:44,880 --> 01:00:47,560
Speaker 4: Well and again, like it gives rocket fuel to those

1209
01:00:47,600 --> 01:00:50,880
Speaker 4: conspiracy theories that people aren't like actually human, and it

1210
01:00:50,920 --> 01:00:53,680
Speaker 4: makes those things much more believable as you break down

1211
01:00:53,680 --> 01:00:56,160
Speaker 4: the law, break down the wall between fact and fiction

1212
01:00:56,520 --> 01:00:59,280
Speaker 4: with your technologies and your algorithms, and so again, they're

1213
01:00:59,560 --> 01:01:02,600
Speaker 4: they're turning us all into cana zons. And for a

1214
01:01:02,680 --> 01:01:06,600
Speaker 4: bit more cogent, I would say argument along the lines

1215
01:01:06,640 --> 01:01:10,200
Speaker 4: of what she is making about, Like, if you want

1216
01:01:10,200 --> 01:01:12,880
Speaker 4: a faith based argument, I recommend Living in Wonder by Roderer,

1217
01:01:12,920 --> 01:01:15,280
Speaker 4: which came out recently. It does a really good job

1218
01:01:15,320 --> 01:01:19,960
Speaker 4: with this. But it's all happening so quickly. In fact,

1219
01:01:20,080 --> 01:01:22,480
Speaker 4: we should get to the clip of THEO Vaughn who

1220
01:01:22,560 --> 01:01:26,480
Speaker 4: asked Sam Altman if he feels fully human along the

1221
01:01:26,480 --> 01:01:28,640
Speaker 4: lines of the ros Daltha interview of Peter Teel that

1222
01:01:28,680 --> 01:01:32,680
Speaker 4: Crystal reference. These guys are having conversations in public because

1223
01:01:32,680 --> 01:01:34,280
Speaker 4: they think they're untouchable, and to.

1224
01:01:34,240 --> 01:01:35,000
Speaker 5: Some extent they are.

1225
01:01:35,040 --> 01:01:38,360
Speaker 4: I mean, think about the Amazon Web servers outage last week,

1226
01:01:38,480 --> 01:01:41,880
Speaker 4: the consolidation of power combined with AI. So when you

1227
01:01:41,880 --> 01:01:46,200
Speaker 4: have consolidated, consolidated power that's running on AI, they have.

1228
01:01:46,240 --> 01:01:49,520
Speaker 5: Lost control of their AI. Are ready, Yeah, they and

1229
01:01:49,560 --> 01:01:50,200
Speaker 5: they admit it.

1230
01:01:50,600 --> 01:01:54,480
Speaker 4: So think of how consequential the AWS outage was last week,

1231
01:01:54,720 --> 01:01:57,480
Speaker 4: and then think of what happens when you have massive

1232
01:01:57,480 --> 01:02:00,240
Speaker 4: consolidation and AI together all at the same time, and

1233
01:02:00,280 --> 01:02:03,480
Speaker 4: people like Sam Altman running the show.

1234
01:02:03,560 --> 01:02:04,200
Speaker 5: Here's c two.

1235
01:02:04,600 --> 01:02:06,480
Speaker 6: Yeah, I'm just always oh my god. Yeah, these people

1236
01:02:06,520 --> 01:02:09,200
Speaker 6: are able to see things differently and quantify things differently.

1237
01:02:09,520 --> 01:02:14,120
Speaker 6: Do you always feel because some tech guys they just

1238
01:02:14,160 --> 01:02:18,000
Speaker 6: have a different understanding of possibility, right, a different understanding

1239
01:02:18,040 --> 01:02:21,000
Speaker 6: of feeling and things. Do you feel human all the time?

1240
01:02:21,240 --> 01:02:22,720
Speaker 15: I do feel human all the time. But I feel

1241
01:02:22,760 --> 01:02:27,320
Speaker 15: like I I have noticed that I think extremely differently

1242
01:02:27,400 --> 01:02:32,200
Speaker 15: about the future, about exponential change, about compounding technology than

1243
01:02:32,280 --> 01:02:34,320
Speaker 15: almost anybody else that I kind of come across in

1244
01:02:34,360 --> 01:02:38,680
Speaker 15: regular life. So that's cool. I feel extremely human. I

1245
01:02:38,760 --> 01:02:41,120
Speaker 15: feel like, you know, driven by crazy emotions as much

1246
01:02:41,120 --> 01:02:43,760
Speaker 15: as anybody, but I am like very aware that I'll

1247
01:02:43,800 --> 01:02:46,520
Speaker 15: have a different lens than a lot of people.

1248
01:02:46,920 --> 01:02:48,880
Speaker 6: Have you met some people in tech space You're like, whoa,

1249
01:02:48,920 --> 01:02:51,240
Speaker 6: that guy is only six or seven percent, he's low,

1250
01:02:51,360 --> 01:02:57,000
Speaker 6: he has not a lot of human in him. Yes, yeah, okay, I.

1251
01:02:56,960 --> 01:02:59,200
Speaker 2: Love how Sam's like, yes, I've met people who are

1252
01:02:59,280 --> 01:03:02,840
Speaker 2: not human, but me and myself, I'm totally Even.

1253
01:03:03,320 --> 01:03:06,320
Speaker 4: His interview with Tucker Carlson came out like I think

1254
01:03:06,360 --> 01:03:08,760
Speaker 4: it was a couple of days before Charlie Kirk was assassinating,

1255
01:03:08,800 --> 01:03:09,680
Speaker 4: so it kind of got buried.

1256
01:03:09,760 --> 01:03:11,440
Speaker 3: Yeah, I never got actually got around to watching it.

1257
01:03:11,560 --> 01:03:12,320
Speaker 5: You have to watch it.

1258
01:03:12,360 --> 01:03:14,600
Speaker 4: So Tucker asked him how he sleeps at night, and

1259
01:03:14,720 --> 01:03:18,760
Speaker 4: Allman's just like, not, well, it's so wild that he

1260
01:03:18,840 --> 01:03:23,120
Speaker 4: goes out and says these things in public, not doing

1261
01:03:23,160 --> 01:03:26,960
Speaker 4: a great job in installing confidence in the population.

1262
01:03:27,440 --> 01:03:33,640
Speaker 5: Meanwhile, Crystal, who is working on behalf of these oligarchs.

1263
01:03:33,760 --> 01:03:38,400
Speaker 4: But Kristensen, of course, I had to let the pause

1264
01:03:38,480 --> 01:03:41,040
Speaker 4: hang because I know it's surprising to people.

1265
01:03:41,160 --> 01:03:44,919
Speaker 2: Oh yeah, that she's doing the most evil thing imaginable

1266
01:03:45,160 --> 01:03:48,360
Speaker 2: in the wake of her senatorial career. You know, I

1267
01:03:48,440 --> 01:03:51,840
Speaker 2: might be open to the hybrid hypothesis when it comes

1268
01:03:51,920 --> 01:03:57,160
Speaker 2: to Carson Cinema. So here she is testifying at a

1269
01:03:57,200 --> 01:04:02,000
Speaker 2: local town hall, basically saying to that listen, I'm working

1270
01:04:02,040 --> 01:04:04,920
Speaker 2: to push these data centers into communities, and you can

1271
01:04:04,960 --> 01:04:07,400
Speaker 2: either cooperate with us, or the federal government is just

1272
01:04:07,440 --> 01:04:09,200
Speaker 2: going to come in and force you to accept this

1273
01:04:09,240 --> 01:04:11,200
Speaker 2: and then you're not going to have any say over

1274
01:04:11,240 --> 01:04:14,160
Speaker 2: how it goes for you or you know or like

1275
01:04:14,240 --> 01:04:16,240
Speaker 2: it's coming. So you can either work with us. We

1276
01:04:16,240 --> 01:04:17,760
Speaker 2: can do this the easy way or the hard way

1277
01:04:17,880 --> 01:04:19,520
Speaker 2: is the subtext of what she says here.

1278
01:04:19,680 --> 01:04:20,760
Speaker 3: Let's go ahead and take a listen.

1279
01:04:21,120 --> 01:04:24,120
Speaker 16: I'm here tonight on behalf of ACT in Infrastructure. I

1280
01:04:24,200 --> 01:04:27,560
Speaker 16: also am the founder and co chair of a national

1281
01:04:27,600 --> 01:04:32,680
Speaker 16: coalition called the AI Infrastructure Coalition. We are a national

1282
01:04:32,720 --> 01:04:35,720
Speaker 16: coalition formed earlier this year, and we're cand in glove

1283
01:04:35,760 --> 01:04:42,640
Speaker 16: with the Trump administration as we prepare for AI American dominance,

1284
01:04:43,520 --> 01:04:46,680
Speaker 16: to prepare against a competing PEP from China, but also

1285
01:04:46,800 --> 01:04:49,880
Speaker 16: to ensure that domestically that we are prepared for the

1286
01:04:49,880 --> 01:04:52,640
Speaker 16: AI revolution that is coming here. The AI Action Plan

1287
01:04:53,120 --> 01:04:56,560
Speaker 16: set out by the Trump administration says very clearly that

1288
01:04:56,680 --> 01:05:01,000
Speaker 16: we must continue to proliferate AI and AI data centers

1289
01:05:01,040 --> 01:05:01,800
Speaker 16: throughout the country.

1290
01:05:02,440 --> 01:05:04,640
Speaker 2: So there she goes hand in glove with the Trump

1291
01:05:04,640 --> 01:05:09,800
Speaker 2: administration to make sure that AI data centers proliferate throughout

1292
01:05:09,840 --> 01:05:11,960
Speaker 2: the country. And I'll tell you, you know, I live

1293
01:05:11,960 --> 01:05:14,320
Speaker 2: in a town where one of these data centers may

1294
01:05:14,360 --> 01:05:17,320
Speaker 2: be coming. There are it's and it's a very conservatives

1295
01:05:17,400 --> 01:05:19,760
Speaker 2: rural areas, very conservative, you know, about like sixty five

1296
01:05:19,760 --> 01:05:22,600
Speaker 2: percent for Trump or something, and you see tons of

1297
01:05:22,600 --> 01:05:24,080
Speaker 2: signs like stop the data center.

1298
01:05:24,120 --> 01:05:26,200
Speaker 3: I mean, this is it really is something.

1299
01:05:25,880 --> 01:05:31,320
Speaker 2: That there are a wide variety of cross partisan concerns

1300
01:05:32,000 --> 01:05:35,400
Speaker 2: here including about local autonomy, you know, as cinema is

1301
01:05:35,440 --> 01:05:37,600
Speaker 2: basically threatening them, like it's coming whether you want it

1302
01:05:37,680 --> 01:05:40,920
Speaker 2: or not. Local autonomy is one of them. You know,

1303
01:05:40,960 --> 01:05:43,520
Speaker 2: there's the water usage. You've had wells that have gone

1304
01:05:43,600 --> 01:05:46,120
Speaker 2: dry near these places, you know, especially in rural areas.

1305
01:05:46,160 --> 01:05:47,720
Speaker 2: I'm personally on well water. A lot of people in

1306
01:05:47,720 --> 01:05:50,120
Speaker 2: my county and in the area are. You have the

1307
01:05:50,480 --> 01:05:53,480
Speaker 2: noise concern, the light pollution concern. You have the skyrocketing

1308
01:05:53,520 --> 01:05:57,919
Speaker 2: electricity energy costs, so you have you know a lot

1309
01:05:57,960 --> 01:06:03,720
Speaker 2: of just like immediate concerns about these massive construction projects

1310
01:06:03,720 --> 01:06:06,720
Speaker 2: that are just like proliferating across the country and that

1311
01:06:06,840 --> 01:06:09,000
Speaker 2: you know, people like her are pushing onto communities that

1312
01:06:09,040 --> 01:06:09,720
Speaker 2: really don't want them.

1313
01:06:09,800 --> 01:06:11,640
Speaker 4: Well, And there was a great semaph report, I think

1314
01:06:11,640 --> 01:06:13,840
Speaker 4: it was a Dave Wigel report from a couple of

1315
01:06:13,920 --> 01:06:16,520
Speaker 4: weeks ago about how this is like the sneaky issue

1316
01:06:16,600 --> 01:06:20,840
Speaker 4: in the midterm cycle that because so many communities are

1317
01:06:21,080 --> 01:06:26,040
Speaker 4: experiencing problems related to the data centers, that anybody who's

1318
01:06:26,080 --> 01:06:29,440
Speaker 4: actually able to do the anti cinema here is probably

1319
01:06:29,520 --> 01:06:31,720
Speaker 4: whichever party is able to do in some of these

1320
01:06:31,760 --> 01:06:36,520
Speaker 4: like congressional races, the anti cinema approach that'll behoove them

1321
01:06:36,640 --> 01:06:39,760
Speaker 4: because in many, many communities this is becoming a significant problem.

1322
01:06:39,960 --> 01:06:44,000
Speaker 4: And on that note, guess who is on this Bernie Sanders,

1323
01:06:44,160 --> 01:06:45,000
Speaker 4: Let's roll see four.

1324
01:06:45,320 --> 01:06:47,920
Speaker 3: Do you think open AI and CHATCHPT should be broken up?

1325
01:06:48,320 --> 01:06:50,280
Speaker 9: I do, But it's a deeper issue than that. We

1326
01:06:50,360 --> 01:06:53,400
Speaker 9: need to take a deep breath and understand that. It's

1327
01:06:53,440 --> 01:06:56,959
Speaker 9: like you know, media are coming to it. We got

1328
01:06:56,960 --> 01:07:02,000
Speaker 9: to be prepared to deal with in all of its complexity. Economically,

1329
01:07:02,080 --> 01:07:05,600
Speaker 9: I worry about massive loss of jobs. In terms of

1330
01:07:05,640 --> 01:07:08,240
Speaker 9: what it does to us as human beings, there are

1331
01:07:08,280 --> 01:07:10,800
Speaker 9: products not being sold. Is you don't need to relate

1332
01:07:10,840 --> 01:07:13,720
Speaker 9: to a human being anymore. You will have somebody hanging

1333
01:07:13,720 --> 01:07:17,360
Speaker 9: around your neck is your AI buddy. And in a

1334
01:07:17,400 --> 01:07:21,840
Speaker 9: country where there's a lot of emotional distress, what do

1335
01:07:21,920 --> 01:07:25,320
Speaker 9: you worry about that? How we continue community, how we

1336
01:07:25,360 --> 01:07:29,000
Speaker 9: relate to each other as human beings. And then, of course,

1337
01:07:29,040 --> 01:07:34,760
Speaker 9: in terms of AI, we worry about the super intelligent AI,

1338
01:07:35,000 --> 01:07:40,720
Speaker 9: which supersedes human intelligence. And one day the AI says

1339
01:07:40,720 --> 01:07:44,680
Speaker 9: to the human being, sorry, but actually no, you worry

1340
01:07:44,720 --> 01:07:46,920
Speaker 9: about a terminator like scenario something like that.

1341
01:07:47,640 --> 01:07:50,440
Speaker 4: So that was Senator standards in an interview with Alex

1342
01:07:50,480 --> 01:07:54,240
Speaker 4: Thompson of Access Crystal, showing a path forward not just

1343
01:07:54,280 --> 01:07:57,520
Speaker 4: for Democrats but for Republicans if anyone is smart enough

1344
01:07:57,560 --> 01:07:58,360
Speaker 4: to take it.

1345
01:07:58,400 --> 01:07:59,880
Speaker 5: And that's where the question.

1346
01:07:59,720 --> 01:08:02,360
Speaker 2: Is, right, Yeah, Well, at the federal level, certainly, the

1347
01:08:02,400 --> 01:08:06,080
Speaker 2: Trump administration has decided that they're all in, you know.

1348
01:08:06,160 --> 01:08:09,360
Speaker 2: And obviously jade Vance is very much back by Peter Thiel,

1349
01:08:09,440 --> 01:08:11,160
Speaker 2: has been throughout his career.

1350
01:08:11,240 --> 01:08:12,959
Speaker 3: They're thinking he's their guy.

1351
01:08:13,840 --> 01:08:16,400
Speaker 2: They've decided we're going to take any breaks that were

1352
01:08:16,439 --> 01:08:18,800
Speaker 2: on the car, we're going to take them off, right.

1353
01:08:18,880 --> 01:08:21,720
Speaker 2: We are going to make sure in terms of regulatory

1354
01:08:21,760 --> 01:08:24,160
Speaker 2: breaks or to make sure the funding is there. We're

1355
01:08:24,200 --> 01:08:26,479
Speaker 2: going to make sure there's no sort of like, you know,

1356
01:08:26,520 --> 01:08:30,120
Speaker 2: any sort of sec enforcement actions coming your way. We're

1357
01:08:30,320 --> 01:08:33,679
Speaker 2: going to go all in in the most reckless manner

1358
01:08:33,760 --> 01:08:37,280
Speaker 2: possible because we've got to win this, you know, war

1359
01:08:37,320 --> 01:08:40,240
Speaker 2: against China. We've got to win the race to Agi

1360
01:08:40,439 --> 01:08:43,559
Speaker 2: before China gets there. And so that is the full

1361
01:08:43,600 --> 01:08:46,640
Speaker 2: thrust from the national level of the UH, you know,

1362
01:08:46,680 --> 01:08:49,280
Speaker 2: the Trump administration certainly right now, and if jade Vance

1363
01:08:49,400 --> 01:08:52,360
Speaker 2: is the predecessor to Trump, then I fully expect him

1364
01:08:52,400 --> 01:08:54,519
Speaker 2: to continue in that direction, and of course Trump is

1365
01:08:54,560 --> 01:08:56,720
Speaker 2: out there. Steve Bannon is zaygo. Trump is going to

1366
01:08:56,760 --> 01:08:58,840
Speaker 2: be the guy again in twenty twenty eight. I don't

1367
01:08:58,840 --> 01:09:00,880
Speaker 2: think we can put that off the tape either, And

1368
01:09:00,920 --> 01:09:04,840
Speaker 2: he's clearly decided that, you know, being fully in bed

1369
01:09:05,120 --> 01:09:07,920
Speaker 2: with these tech oligarchs was the best thing for him

1370
01:09:08,000 --> 01:09:10,519
Speaker 2: politically in the direction that he wanted to go in.

1371
01:09:10,640 --> 01:09:14,200
Speaker 2: So it does leave a massive opening for someone to

1372
01:09:14,320 --> 01:09:17,200
Speaker 2: articulate all of these fears. And as I said, the

1373
01:09:17,240 --> 01:09:20,400
Speaker 2: fears are both immediate and medium term in terms of

1374
01:09:20,880 --> 01:09:24,200
Speaker 2: job loss and long term as Bernie articulates there as well,

1375
01:09:24,200 --> 01:09:27,320
Speaker 2: in terms of these more existential concerns about what it

1376
01:09:27,360 --> 01:09:32,040
Speaker 2: would mean to have a superior intelligence on the planet, Like,

1377
01:09:32,439 --> 01:09:34,600
Speaker 2: has anyone thought about that? There are people who have

1378
01:09:34,640 --> 01:09:36,519
Speaker 2: thought about it, most of them have concluded that it's

1379
01:09:36,520 --> 01:09:39,120
Speaker 2: going to be really bad for human beings. Yet we

1380
01:09:39,200 --> 01:09:42,800
Speaker 2: continue a pace anyway. So if you know, eighty something

1381
01:09:42,880 --> 01:09:45,519
Speaker 2: year old Bernie Sanders can figure all of that out,

1382
01:09:45,640 --> 01:09:48,759
Speaker 2: I think a lot of Americans are thinking the same direction.

1383
01:09:49,280 --> 01:09:52,519
Speaker 2: And it seems to me like we're at an inflection

1384
01:09:52,680 --> 01:09:56,680
Speaker 2: point as these data centers increasingly crop up, especially in

1385
01:09:56,800 --> 01:10:00,800
Speaker 2: rural areas where there's more and more awareness of what

1386
01:10:00,880 --> 01:10:03,479
Speaker 2: is happening and the speed and pace of you know,

1387
01:10:03,520 --> 01:10:07,000
Speaker 2: at which it is occurring, and the massive impact that

1388
01:10:07,040 --> 01:10:09,120
Speaker 2: it could have on all of our lives in the future.

1389
01:10:10,280 --> 01:10:15,679
Speaker 4: And most conservative Catholic intellectuals are deeply suspicious of AI,

1390
01:10:15,920 --> 01:10:19,840
Speaker 4: which puts JD Vance in a fascinating position. And we

1391
01:10:19,880 --> 01:10:23,360
Speaker 4: did a long segment on why Peter Thiel is talking

1392
01:10:23,479 --> 01:10:27,400
Speaker 4: so much about AI, the Apocalypse, the catacon recently, and

1393
01:10:27,439 --> 01:10:30,479
Speaker 4: I think the conclusion that we landed on is he's

1394
01:10:30,760 --> 01:10:35,360
Speaker 4: trying to seduce, especially religious conservatives, in the midst of

1395
01:10:35,400 --> 01:10:39,960
Speaker 4: this nationwide religious revival that everyone'saw on display at the

1396
01:10:40,080 --> 01:10:43,599
Speaker 4: Kirk Memorial. He's trying to convince those people, which are

1397
01:10:43,720 --> 01:10:48,439
Speaker 4: such an important part of the Republican coalition, to put

1398
01:10:48,479 --> 01:10:51,600
Speaker 4: their faith in AI and to put their faith in

1399
01:10:51,880 --> 01:10:54,920
Speaker 4: big tech. And if he's able to do that, if

1400
01:10:54,960 --> 01:10:57,439
Speaker 4: you bring the Jdvances on board and start making this

1401
01:10:57,640 --> 01:11:02,760
Speaker 4: argument a faith based argument, a faith based argument for accelerationism,

1402
01:11:03,520 --> 01:11:06,320
Speaker 4: that's a huge win because you can see the argument

1403
01:11:06,360 --> 01:11:11,639
Speaker 4: that Bernie just made their being appealing to people around

1404
01:11:11,640 --> 01:11:16,040
Speaker 4: the country who are are honestly like conservative Trump types

1405
01:11:17,040 --> 01:11:20,479
Speaker 4: or just normal you know, suburban parents who are freaked

1406
01:11:20,479 --> 01:11:23,720
Speaker 4: out about what's happening to their children. So that's a

1407
01:11:23,960 --> 01:11:27,639
Speaker 4: huge reason why we're starting to see Teal. I think

1408
01:11:27,680 --> 01:11:31,320
Speaker 4: Teal is smarter, honestly, and he's more politically savvy, much

1409
01:11:31,360 --> 01:11:34,360
Speaker 4: more politically experienced than Elon or Sam Altman. I mean,

1410
01:11:34,400 --> 01:11:37,640
Speaker 4: his political involvement goes back a long time, and so

1411
01:11:37,720 --> 01:11:40,000
Speaker 4: I think that's where you're trying to see, where you're

1412
01:11:40,000 --> 01:11:42,280
Speaker 4: seeing him try to get out ahead of some of

1413
01:11:42,320 --> 01:11:46,000
Speaker 4: these arguments to bring so like Candicetone's Conservative Catholic actually

1414
01:11:46,160 --> 01:11:50,080
Speaker 4: interesting point, big audience among conservative Catholics, trying to make

1415
01:11:50,120 --> 01:11:51,680
Speaker 4: the point that hey, we don't know where any of

1416
01:11:51,720 --> 01:11:53,760
Speaker 4: this is going, but we have to put our faith

1417
01:11:53,760 --> 01:11:58,200
Speaker 4: in this accelerationist because otherwise the de Growthers sure look

1418
01:11:58,240 --> 01:12:03,639
Speaker 4: a lot like some biblical prophecies about the dark forces.

1419
01:12:04,160 --> 01:12:06,720
Speaker 4: So that's that's I think all of this, I think

1420
01:12:06,800 --> 01:12:09,880
Speaker 4: lends credence to the conversation that we had the other day.

1421
01:12:10,400 --> 01:12:13,960
Speaker 4: And on top of that, where does I mean the

1422
01:12:14,000 --> 01:12:16,240
Speaker 4: Trump administration. We heard a lot in the lead up.

1423
01:12:16,240 --> 01:12:17,920
Speaker 4: You probably remember this last year this time last year

1424
01:12:17,920 --> 01:12:22,439
Speaker 4: about little tech right like accelerationism, little tech. We have

1425
01:12:22,520 --> 01:12:28,920
Speaker 4: to open up everything, make a much more liberal, lowercase

1426
01:12:29,040 --> 01:12:32,120
Speaker 4: L regulatory environment for all of these little tech companies

1427
01:12:32,160 --> 01:12:33,559
Speaker 4: to thrive and to innovate.

1428
01:12:34,200 --> 01:12:34,559
Speaker 5: Crystal.

1429
01:12:34,560 --> 01:12:37,519
Speaker 4: I feel like the regulatory environment right now, since Donald

1430
01:12:37,520 --> 01:12:42,600
Speaker 4: Trumpery took office is pretty much designed to favor big tech, right, Like,

1431
01:12:42,880 --> 01:12:44,240
Speaker 4: are we seeing this flourishing?

1432
01:12:44,520 --> 01:12:47,759
Speaker 2: The tech itself is designed to favor big exactly because

1433
01:12:48,000 --> 01:12:51,680
Speaker 2: at least the theory of all the American companies, you know,

1434
01:12:51,800 --> 01:12:54,479
Speaker 2: Deep seek Proof potentially a different direction as possible, but

1435
01:12:54,560 --> 01:12:56,920
Speaker 2: the theory of all the American companies is basically, you

1436
01:12:56,960 --> 01:13:00,000
Speaker 2: just throw as much money at this thing as possib

1437
01:13:00,600 --> 01:13:03,479
Speaker 2: You build out as many data centers, as much compute

1438
01:13:03,560 --> 01:13:07,360
Speaker 2: as possible to the tune them hundreds of billions of dollars,

1439
01:13:07,880 --> 01:13:11,760
Speaker 2: and that's the way to win the race. And so

1440
01:13:12,160 --> 01:13:15,040
Speaker 2: of course, like you're not going to have some plucky

1441
01:13:15,080 --> 01:13:17,120
Speaker 2: startup that's able to pull that off.

1442
01:13:17,479 --> 01:13:19,559
Speaker 5: Especially with all the lobbying here that's going on.

1443
01:13:19,920 --> 01:13:23,800
Speaker 2: Yeah, I mean, it's gonna be the giant players. And

1444
01:13:24,240 --> 01:13:26,000
Speaker 2: which is why I always thought the little tech thing

1445
01:13:26,080 --> 01:13:28,080
Speaker 2: was complete nutter bullshit. And I think it was complete

1446
01:13:28,160 --> 01:13:30,200
Speaker 2: nutter bullshit. I don't think that Mark Andrees and these

1447
01:13:30,200 --> 01:13:32,719
Speaker 2: other people that are pushing it are so like out

1448
01:13:32,720 --> 01:13:36,280
Speaker 2: of touch with the nature of the tech to not

1449
01:13:36,400 --> 01:13:38,839
Speaker 2: understand that it was going to be the big players

1450
01:13:39,200 --> 01:13:40,639
Speaker 2: that dominate the space.

1451
01:13:40,920 --> 01:13:41,840
Speaker 3: Now are there going to be.

1452
01:13:41,880 --> 01:13:44,600
Speaker 2: You know, startups that are using the tech and you know,

1453
01:13:44,720 --> 01:13:48,599
Speaker 2: ancillary pressure, But in terms of who is developing the

1454
01:13:48,640 --> 01:13:52,759
Speaker 2: core technology, it's going to be one of the giants.

1455
01:13:53,200 --> 01:13:56,519
Speaker 2: And that's why all of these guys have thrown in

1456
01:13:56,880 --> 01:13:59,760
Speaker 2: so hard for it, because they want to be the guy.

1457
01:14:00,160 --> 01:14:02,679
Speaker 2: They want to be the master of the universe. That's

1458
01:14:02,720 --> 01:14:05,479
Speaker 2: the way that they see it. And Emily, your points

1459
01:14:05,520 --> 01:14:08,360
Speaker 2: on the on what Teal is doing and your insights

1460
01:14:08,360 --> 01:14:11,280
Speaker 2: into that, I think are really important for people to understand.

1461
01:14:11,320 --> 01:14:13,000
Speaker 2: Whether or not he believes what he's saying or not,

1462
01:14:13,080 --> 01:14:15,519
Speaker 2: who the hell knows, It doesn't really matter, but he's

1463
01:14:15,560 --> 01:14:20,160
Speaker 2: trying to square the circle of convincing religious people that

1464
01:14:20,880 --> 01:14:24,519
Speaker 2: this technology, which on his face looks anti creation and

1465
01:14:24,600 --> 01:14:28,960
Speaker 2: anti human is actually actually it's fine, and actually we

1466
01:14:29,080 --> 01:14:32,439
Speaker 2: have to do this, like the proper religious course to take,

1467
01:14:33,000 --> 01:14:36,400
Speaker 2: you know, with if you're in the Christian faith, is

1468
01:14:36,479 --> 01:14:39,920
Speaker 2: to pursue this at all costs. And take all the

1469
01:14:39,960 --> 01:14:42,599
Speaker 2: breaks off the car and just trust that it's going

1470
01:14:42,640 --> 01:14:45,280
Speaker 2: to work out, that that is the like, the proper

1471
01:14:45,320 --> 01:14:46,760
Speaker 2: thing to do, and just turn your mind off all

1472
01:14:46,760 --> 01:14:49,200
Speaker 2: your concern don't worry about it, right, We've just got

1473
01:14:49,240 --> 01:14:50,800
Speaker 2: to We just got to go drive this car a

1474
01:14:50,800 --> 01:14:51,720
Speaker 2: one hundred miles an hour.

1475
01:14:51,840 --> 01:14:55,040
Speaker 4: Yeah, yeah, And you know it's it's It's interesting because

1476
01:14:55,040 --> 01:14:56,559
Speaker 4: I think a lot of people are engaging with the

1477
01:14:56,640 --> 01:15:02,200
Speaker 4: teal argument as it's in entirely sincere, and I think

1478
01:15:02,200 --> 01:15:05,559
Speaker 4: it's probably both sincere. He does seem entirely sincere about it,

1479
01:15:05,600 --> 01:15:09,000
Speaker 4: but it's not just sincere. It's sincere in a very

1480
01:15:09,160 --> 01:15:14,240
Speaker 4: particular direction. And there's an audience that he would have

1481
01:15:14,280 --> 01:15:16,960
Speaker 4: a motivation to try and persuade right now, And so

1482
01:15:17,120 --> 01:15:19,000
Speaker 4: I think that's an important les to look at what

1483
01:15:19,040 --> 01:15:23,320
Speaker 4: he's doing through. Man, what a time to be alive, Crystal,

1484
01:15:23,320 --> 01:15:24,639
Speaker 4: What a time to be alive.

1485
01:15:25,120 --> 01:15:25,599
Speaker 3: Indeed,