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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: not exist anywhere else.

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Speaker 2: So if that is something that's important to you, please

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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. There's a lot going on in the world.

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Speaker 1: You might have missed this. The Trump administration is currently

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Speaker 1: going to bat for the prediction markets masquerading as sports

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Speaker 1: gambling companies to nationalize sports gambling to dramatically enrich not

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Speaker 1: only the Trump family themselves, but also all of the

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Speaker 1: most degenerate executives in the United States. So I want

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Speaker 1: to go ahead and give a major shout out here

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Speaker 1: to the chairman of the CFTC, the Commodities Future Trading Commission,

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Speaker 1: which is responsible for regulating prediction markets, wo by the

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Speaker 1: way is actually a former crypto executive and is now

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Speaker 1: actually trying to preempt any state efforts to rein in

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Speaker 1: prediction markets backdoor sports gambling across the nation, violating state

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Speaker 1: sovereignty and their ability to regulate sports gambling internally. Here's

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Speaker 1: the chairman of the CFDC, Mike Sellig. Let's take a

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Speaker 1: listen to what he had to say.

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Speaker 3: CFDC Chairman Mike saliing here. Over the past year, American

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Speaker 3: prediction markets have been hit with an onslaught of state

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Speaker 3: led litigation. In response, the CFDC has today filed a

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Speaker 3: Friend of the Court brief to defend its exclusive jurisdiction

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Speaker 3: over these derivative markets. Today, the CFDC is taking an

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Speaker 3: important step to ensure that these markets have a place

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Speaker 3: here in America and have the integrity and resilience and

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Speaker 3: vibrancy that our derivatives' markets deserve. To those who seek

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Speaker 3: to challenge our authority in this space, let me be clear,

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Speaker 3: we will see you in court.

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Speaker 1: So what he is saying there is that states do

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Speaker 1: not have the right to regulate sports gambling, which goes

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Speaker 1: directly against the Supreme Court decision. Now, let me also explain,

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Speaker 1: because if you listen to that. You're like, oh, well,

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Speaker 1: he's talking about derivative markets and financial work. No, that's

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Speaker 1: not what this is about, literally at all. And don't

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Speaker 1: get to that here in a second. Let's put up

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Speaker 1: here Governor Spencer Cox of Utah's response. He says, Mike,

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Speaker 1: I appreciate you attempting this with a straight face, but

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Speaker 1: I don't remember the CFTC having authority over the derivative

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Speaker 1: market of Lebron James rebounds. These prediction markets you are

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Speaker 1: breathlessly defending are gambling, pure and simple. They are destroying

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Speaker 1: the lives of families and countless Americans, especially young men.

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Speaker 1: They have no place in Utah. Let me be clear,

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Speaker 1: I will use every resource within my disposal as governor

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Speaker 1: of the sovereign state of Utah and under the Constitution

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Speaker 1: of the United States, to beat you in court. So

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Speaker 1: that is a Republican governor. And this very much, Chrystal

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Speaker 1: resembles what happened with AI. You have these companies, you

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Speaker 1: have Calshi, you have Polymarket, you have DraftKings, FanDuel, all

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Speaker 1: of the gambling companies rushing to get into the prediction

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Speaker 1: market space. And let me explain this very clearly sports gambling,

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Speaker 1: as you all know, which I am massively against the

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Speaker 1: Fanduels and the DraftKings. They are more tightly regulated than

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Speaker 1: these prediction markets. What the prediction markets are arguing is

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Speaker 1: that because they are explicitly not gambling, that they are

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Speaker 1: legalized in all fifty states. And as we have also seen,

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Speaker 1: if go take a look at DraftKings stock and FanDuel stock,

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Speaker 1: they're down forty to fifty percent. The reason why is

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Speaker 1: they're bleeding money to these prediction markets. Vegas actually handled

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Speaker 1: way less money for the Super Bowl this year than

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Speaker 1: they did the year before. Why gambling is a loser

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Speaker 1: take all market. And what I mean by that is

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Speaker 1: whichever person is willing to offer the most degenerate bets,

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Speaker 1: that's the person who wins. And even as bad as

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Speaker 1: much as I hate DraftKings and FanDuel, you're not betting

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Speaker 1: on dildo colors on the floors on the basketball courts

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Speaker 1: of WNBA. Even they have a standard because they have

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Speaker 1: state regulators that they have to deal with, right they have.

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Speaker 1: I mean, we're talking about the different colors of gatorade.

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Speaker 1: Like it's quoint to think about people in Vegas. Well,

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Speaker 1: every year betting on heads and tails. That used to

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Speaker 1: be the most the worst example of degenerous. No, like,

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Speaker 1: we are in a ten to fifteen to twenty thirty

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Speaker 1: times worse situation with the type of bets that are

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Speaker 1: being offered on this rife for insider trading. Remember the

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Speaker 1: Streaker one I told you about that literally happened. Somebody

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Speaker 1: actually did bet on Streaker and then did it. It

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Speaker 1: was an offshore book, to be clear, however, and his

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Speaker 1: bet was avoided. But I'm giving you an example of

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Speaker 1: exactly the type of things can happen. This is not

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Speaker 1: even to mention all the insider trading possibilities from that.

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Speaker 1: We saw the state of Israel just indicted multiple people

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Speaker 1: who were in the military and arrested them for betting

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Speaker 1: on operations that they knew was going to happen. You

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Speaker 1: cannot allow bets life and death. Very recently, there was

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Speaker 1: a market on whether a space booster was going to fail,

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Speaker 1: and they were like, wow, it's really cool to bet

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Speaker 1: on stuff which could literally result in the deaths of

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Speaker 1: the crew are involved. And they're like, well, to be clear,

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Speaker 1: it's just about a mechanical failure. It's like, yeah, mechanical

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Speaker 1: failure that could literally lead to it.

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Speaker 4: Yeah, what do you think is going to happen that

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Speaker 4: mechanical Right, So.

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Speaker 1: I'm just betting on whether Apollo thirteen is going to

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Speaker 1: take off or not. Guys, Right, it's a come on.

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Speaker 1: This is the nonsense, yeah, which has been This is

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Speaker 1: this is literally like the clearest example of total free

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Speaker 1: market capitalism, which is except as always in the American context,

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Speaker 1: completely backed now by the power of the state. The

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Speaker 1: United States federal government going to bat not just for

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Speaker 1: betting markets, but for betting markets that offer the worst,

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Speaker 1: most degenerate products that milk these people. You know, the

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Speaker 1: advertising of these companies. They're telling children out there, eighteen

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Speaker 1: nineteen year olds, guys, this is how you can make

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Speaker 1: your life savings. This is how you can pay your tuition.

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Speaker 1: I mean, I'm getting reels of guys who are betting

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Speaker 1: on whether Trump is going to say the word low

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Speaker 1: IQ and they're watching, you know, an entire weeks worth

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Speaker 1: of news and then cheering and popping champagne whenever he

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Speaker 1: finally says it for a five hundred to one payout work.

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Speaker 1: This is insanity, like absolute insanity, and it's being backed

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Speaker 1: by the government because these people are making money hand

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Speaker 1: over fist. It's disgusting. This is gambling, pure and simple.

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Speaker 2: Yeah, well the gas lighting put D four up on

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Speaker 2: the screen of like this is a derivatives market where

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Speaker 2: Americans can hedge their risk against changing weather or no,

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Speaker 2: this is sports betting, okay, I mean the estimate here

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Speaker 2: is that ninety percent of Calshi's bets are on our sports.

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Speaker 2: Like that's that's primarily what these things are used for,

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Speaker 2: and not that it really would make it better if

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Speaker 2: it wasn't primarily sports. But you know, their dodge is factively, Oh,

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Speaker 2: this isn't really sports gambling. It's the sophisticated derivatives and

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Speaker 2: we're just democratizing the access to this technology. Blah blah blah.

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Speaker 2: Like the whole thing is just complete gas lighting. And

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Speaker 2: you know, I think to me, zooming out the two

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Speaker 2: major underlying stories here, the two things that are really

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Speaker 2: going on is number one, the corruption obviously, like you know,

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Speaker 2: I mean Don Junior's on the COUCHI board, like it's

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Speaker 2: you know, they're making tons of money, They're throughout the

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Speaker 2: whole government, So they want this gravy train to the

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Speaker 2: people in power are profiting off of this direct exploitation

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Speaker 2: of you know, ordinary Americans, and they want that gravy

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Speaker 2: train to keep going. We are at the stage in

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Speaker 2: capitalism where like the level of just predatory behavior is

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Speaker 2: completely brazen and completely overt. But I think the other

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Speaker 2: thing that is going on here is, you know, we've

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Speaker 2: always are Our national story has always had a bit

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Speaker 2: of like a casino lottery element to it, of like

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Speaker 2: you may not be rich today, but hey, here in America,

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Speaker 2: anything's possible. The previous story was about if you work

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Speaker 2: hard and you know, we have this grand meritocracy, and

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Speaker 2: there was some level of truth to that, right, not completely,

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Speaker 2: but there was some level, and people bought into it.

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Speaker 4: So it was like, okay, if.

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Speaker 2: We do the right and we go to school, we

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Speaker 2: work hard, and we start a great busines. Since we

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Speaker 2: make a great product, we too can join like the

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Speaker 2: class of the millionaires, We too can become one of

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Speaker 2: society's elites. Now that story has unraveled, So now the

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Speaker 2: story is just complete casino capitalism.

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Speaker 4: It's just complete. You know.

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Speaker 2: We use the example before. Maybe you too can get

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Speaker 2: cast as a plant in the Bad Bunny halftime show

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Speaker 2: and have insider knowledge of whether Lady Gaga and Ricky

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Speaker 2: Martin are going to be performing.

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Speaker 4: And be able to cash in.

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Speaker 2: That is, in the absence of, you know, a broader

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Speaker 2: redistribution of wealth. They are wrapping this explicitly predatory scheme

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Speaker 2: in a like promise of riches and wealth for ordinary

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Speaker 2: people who have lost all hope that there is any

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Speaker 2: other path to success, not even riches in wealth, but

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Speaker 2: just to like escape an entirely precarious existence. So I

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Speaker 2: think when you look at when you look at this

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Speaker 2: in a certain ways, when you look at the AI development,

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Speaker 2: certainly in the crypto space and the betting space, I

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Speaker 2: think part of what is going on here is not

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Speaker 2: just about the corruption. It's about selling a narrative to

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Speaker 2: people that this is going to be the new way

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Speaker 2: that you're able to make it big and.

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Speaker 1: Let me, you know, bring it out even deeper, just

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Speaker 1: show you how deep the rabbit hole goes. I wanted

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Speaker 1: to cover this a few weeks ago, but we weren't

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Speaker 1: able to put it in the show. Let's put C

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Speaker 1: three or D three up there on the screen. The

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Speaker 1: CFTC before this announcement, literally just a week before announced

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Speaker 1: the Innovation Advisory Committee. Let me name you some of

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Speaker 1: the people who are on there. The CEO of Coinbase,

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Speaker 1: the CEO of Polymarket, the CEO of Ripple, the CEO

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Speaker 1: of FanDuel, the CEO of Calshi, the CEO crypto dot Com,

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Speaker 1: the CEO of DraftKings, the CEO of Blockchain, the CEO

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Speaker 1: of Kraken, Gemini, Solana Labs, Robin Hood. I mean I

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Speaker 1: just named some of the worst companies in the United States.

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Speaker 1: Like these are the people who are getting phenomenally rich

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Speaker 1: basically making gambling as widely available to the American public

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Speaker 1: as they can using an buying In some cases the

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Speaker 1: power now of the power of the federal government to

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Speaker 1: basically enable their ability to legalize gambling across the nation.

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Speaker 1: I never even thought I would be in the business

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Speaker 1: of defending the DraftKings and the fan duels. But really

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Speaker 1: this is about state sovereignty. I massively opposed sports gambling.

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Speaker 1: I think we should make it completely illegal at the

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Speaker 1: online level. If people want to have gambling in their states,

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Speaker 1: they should have to go to a casino, and it

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Speaker 1: should be very tightly regulated in terms of the number

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Speaker 1: of bets to make sure that you know you can't

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Speaker 1: do prop bets for insider trading. And all of that,

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Speaker 1: et cetera. But at a sovereign level. From what the

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Speaker 1: Supreme Court said, it's up to the states. You cannot

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Speaker 1: allow the CFTC and the federal government to just say, hey, California,

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Speaker 1: you know they had a whole referendum on this. They

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Speaker 1: rejected it. They said, Nope, we're not going to do it.

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Speaker 1: We're going to keep it in the whatever in the

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Speaker 1: tribal casinos. Texas, same thing the gambling companies have taken

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Speaker 1: l after l in Texas. Texas legislature is like, nope,

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Speaker 1: we're not doing it, which cost Miriam Madlson all these

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Speaker 1: people a hell of a lot of money. But this

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Speaker 1: is how you get around it. It's literally making the

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Speaker 1: worst possible types of bets with zero regulation or at

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Speaker 1: least the least amount of regulation, taking it out of

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Speaker 1: the hands of the state and saying no, we're going

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Speaker 1: to make it widely available for all and none of

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Speaker 1: the proper safeguards that are currently in place for insider trading.

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Speaker 1: And these people are printing money. Remember the CALCI founder

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Speaker 1: who's like, I'm one of the youngest female billionaires in

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Speaker 1: the world. We should be ashamed of this. This is

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Speaker 1: shameful to become a billionaire by propping up gambling, and

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Speaker 1: you know everybody is like in the tech industry, everybody's

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Speaker 1: getting bought off. I recently saw a story of a guy,

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Speaker 1: a sports podcaster who criticized cal sheet. They reached out

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Speaker 1: to him the next week for They reach out to

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Speaker 1: him literally the week after to offer him a sponsorship.

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Speaker 1: And you know, nobody wants to talk about this because

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Speaker 1: they're all taking money from the same thing. And you

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Speaker 1: would think DraftKings and Fantool would be trying to do

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Speaker 1: something about No DraftKings is now, Oh, we're going to

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Speaker 1: get into the prediction business. This is a race to

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Speaker 1: the bottom to make it as completely unregulated, open for

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Speaker 1: insider trading, open for corruption as possible. But because they're

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Speaker 1: all making so much money milking all of these people,

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Speaker 1: regular sports fans, people who are losing hope, the bottom

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Speaker 1: level of society, like we are turning everyday Americans, especially

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Speaker 1: young men, into the same guys that you see at

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Speaker 1: the gas station doing scratch off tickets. That's what we're

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Speaker 1: doing for a whole nation, and it's like nobody wants

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Speaker 1: to stand up for it. Luckily, at least some are

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Speaker 1: let me put D five up here on the screen.

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Speaker 1: I want to give credit to Elizabeth Warren. She says

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Speaker 1: Trump's CFTC is trying to strip state authority to regulate

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Speaker 1: gambling within their borders, protect Americans from getting ripped off.

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Speaker 1: The CFTC should focus on ensuring our derivatives markets don't

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Speaker 1: blow up the economy again, not helping corrupt political insiders

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Speaker 1: cash in. Excellent, well said. And then finally D six,

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Speaker 1: Just if you're wondering where this is all coming from,

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Speaker 1: don't forget the Donald Trump's own truth Social company was

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Speaker 1: supposed to launch a polymarket competitor, and Donald Trump Junior

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Speaker 1: himself is literally a strategic advisor to both CALCI and

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Speaker 1: to Polymarket. We're currently on the CFTC Advisory committee and

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Speaker 1: who the new CFTC chairman is working on their behalf.

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Speaker 1: And by the way, even before this, the CFTC advisor

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Speaker 1: or the CFTC committee, he wasn't necessarily supposed to have

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Speaker 1: all this authority. There were a lot of shenanigans in

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Speaker 1: terms of making sure that nobody else was on the board,

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Speaker 1: similar to what they did here with the FTC. So

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Speaker 1: here we go. This is going to be a multi

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Speaker 1: billion dollar bonanza. The amount of people who are going

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Speaker 1: to lose money, it's astronomical, Like the amount of sports

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Speaker 1: betters and other people were going to be lured in.

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Speaker 1: There's no regulation for advertising, no regulation at the federal level.

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Speaker 1: It's going to be I mean, this is going to

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Speaker 1: be as close to a Rip and Roar eighteen ninety silver,

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Speaker 1: you know, pedaling, what were the snake oil We're going back.

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Speaker 1: This is what it's going to look like. And think

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Speaker 1: about how comulated, how many people suffered from that. But

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Speaker 1: I'm just glad that this tech executives are going to

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Speaker 1: get filthy.

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Speaker 2: Rich on steroids in the algorithm era too, where it's

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Speaker 2: like all super supercharged. I wanted to shout out Pedro Gonzalez.

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Speaker 2: I thought he had a good take on this, and

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Speaker 2: shout out to you as well for being like principled

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Speaker 2: and consistent in your position series. It's very funny that

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Speaker 2: the New Right does this save the West LARP and

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Speaker 2: then you look at its policy preferences and it's all

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Speaker 2: just legalizing crime, crypto scams, normalizing gambling, et cetera. It's

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Speaker 2: the movement of decline and profiting from decline. And I

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Speaker 2: mean You've been making this point about, like, you know,

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Speaker 2: the all of the quote unquote degenerate behavior is now

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Speaker 2: just like embraced and fully deregulated, and no one bothers

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Speaker 2: to pause and say, this seems a little inconsistent with

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Speaker 2: some of the other things a lot of political project

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Speaker 2: has been.

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Speaker 1: A lot of right wingers were so mad at me

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Speaker 1: yesterday for tweeting this, and I said that Trump is

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Speaker 1: now the most pro vice president in American history. He

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Speaker 1: in a single year, he is trying to deregulate and

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Speaker 1: legalize gambling in all fifty states. He is rescheduling marijuana

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Speaker 1: to enrich hit rich drug pedaling donors, and is now

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Speaker 1: pressuring banks to maintain access for only fans models. So

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Speaker 1: I mean, there you go. I mean, what else you have?

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Speaker 1: The most pro porn, pro wed, pro gambling president in

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Speaker 1: American history. Congratulations for many of us who you know,

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Speaker 1: at the very least you know thought, Look, I knew

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Speaker 1: the crypto thing was going to be a bonanza and whatever,

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Speaker 1: like that's bad, but it's kind of separate to gambling,

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Speaker 1: Like this is the most predatory industry with the highest

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Speaker 1: suicide rate. I mean, they're one third of American young

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Speaker 1: men have an open gambling account. The amount of addiction,

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Speaker 1: it's if you talk to the gambling hotlines and others,

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Speaker 1: it is horrible. And for those of you who think like, oh,

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Speaker 1: I don't gamble, so it doesn't affect me. When a

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Speaker 1: state legalizes online, a state legalizes gambling, the aggregate like

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Speaker 1: amount of credit goes down. It actually affects everybody. The

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Speaker 1: amount of domestic violence it goes up. The public resources

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Speaker 1: are going to have to be dedicated to dealing with this.

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Speaker 1: It's going to be like the cocaine crisis in the

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Speaker 1: eighteen nineties, when all of a sudden, we just said

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Speaker 1: junkies everywhere, and we didn't know what to do. It's

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Speaker 1: going to be very similar. Go to Vegas and you

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Speaker 1: see the bums that are on the street begging for

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Speaker 1: a dollar so they can get some food. That's going

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Speaker 1: to be the whole nation, you know.

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Speaker 4: And it's the adaption to pretend you're pro family.

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Speaker 2: Well you know, yeah, yeah, nothing will blow up in regularly.

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Speaker 1: Nothing will blow your life up like a gambling addiction.

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Speaker 1: I can tell you a story after story, lawsuit after

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Speaker 1: lawsuit after lawsuit, people who never placed a bet to

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Speaker 1: fully bankrupt divorce and on the verge of suicide in

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Speaker 1: the span of two or three years, gambling with their

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Speaker 1: kids Christmas presents, life savings, five twenty nine accounts, and

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Speaker 1: these people will take your money all day long. And

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Speaker 1: now it's going to be even less regularly, and it's.

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Speaker 4: Young men who will suffer the most.

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Speaker 2: Your most you know, easily is sort of like have

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Speaker 2: the psychology that's the most easily exploited by this stuff

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Speaker 2: that are overwhelmingly the largest percentage.

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Speaker 1: Of the bad. So bad, All right, let's get to

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Speaker 1: the next one.

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Speaker 2: So the New York Times had a very interesting focus

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Speaker 2: group of Democratic voters, which I feel like we don't

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Speaker 2: see that much. I feel like there's always because the

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Speaker 2: liberal media is kind of like more in tune with Democrats.

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Speaker 2: There's less curiosity about what's going on with the Democratic base.

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Speaker 2: So it's usually either like swing voters or Trump voters.

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Speaker 2: Let's go on safari and see what these strange creatures

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Speaker 2: think about the world. So they decided to do that

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Speaker 2: with the Democratic base, and you know, now, I think

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Speaker 2: liberal media has become more disconnected from where the Democratic bases,

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Speaker 2: and the Democratic party leadership certainly has become more disconnected

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Speaker 2: from where the Democratic bases. So anyway we can put

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Speaker 2: this F one up on the screen. This was the

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Speaker 2: headline for their focus group. They said, show up for

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Speaker 2: us thirteen Democratic voters on Trump Ice and their frustrations

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Speaker 2: with the Democratic Party and the thing they sees on

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Speaker 2: here at the top with these three voters is their

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Speaker 2: description of the Democratic Party. One says paralyzed and the

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Speaker 2: other says sold out, another says afraid. These are three

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Speaker 2: very different people, very different you know, backgrounds. So and

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Speaker 2: this was the conclusion across the board, let's go and

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Speaker 2: put F two up on the screen. This is probably

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Speaker 2: the slide that got the single most attention. Ryan, Emily

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Speaker 2: and Emily mentioned this in their show yesterday, but we

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Speaker 2: wanted to dig in a little bit more. They asked

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Speaker 2: their thirteen focused group participants what type of candidates they're

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Speaker 2: looking for, and they ask them, you know, would you

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Speaker 2: prefer someone who's young or you don't really care? And overwhelmingly,

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Speaker 2: of course, people say we like someone who's younger. What

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Speaker 2: sort of class background there is major preference for, you know,

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Speaker 2: middle or working class? They asked them, do you prefer

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Speaker 2: a candidate who identifies as progressive or a candidate who

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Speaker 2: identifies as moderate. Every single person said they prefer a

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Speaker 2: progressive candidate for a moderate candidate. Literally, no one raised

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Speaker 2: a hand. Okay, let me go ahead and put the

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Speaker 2: next piece up on the screen of data here. That

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Speaker 2: was also interesting. So this is where they're asking them. Okay, well,

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Speaker 2: tell me what you think about the Democratic Party if

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Speaker 2: you had to use one or two words to describe it,

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Speaker 2: what words would you pick?

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Speaker 4: Now?

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Speaker 2: I remind you, these are all Democrats, okay, these are

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Speaker 2: Democratic Party voters. Number one spineless, Number two, more complacent

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Speaker 2: than I thought they would be. Number three paralyzed, afraid, incompetent.

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Speaker 2: I guess suffocated or given up, sold out? Next one

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Speaker 2: sellouts and suckers immobilized. Can I say no balls, no kahonas,

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Speaker 2: I will say, there are a large number of young

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Speaker 2: Democrats that are really starting to climb the ranks in

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Speaker 2: the party, that are motivated. I'm hoping that that will

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Speaker 2: start to take over a little bit more so when

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Speaker 2: you see those numbers overall, of like the Democratic Party

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Speaker 2: being at its lowest approval rating in history. These type

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Speaker 2: of people are a big part of that story because

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Speaker 2: obviously Republicans are going to hate Democrats. There's a significant

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Speaker 2: number of independents who are obviously discussed with Democrats, but

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Speaker 2: it's their own voters being so disgusted and frustrated with

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Speaker 2: them that has really sent them to the lowest lows

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Speaker 2: and then last one. Then we can get, you know,

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Speaker 2: into our reaction to all of this. This is there

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Speaker 2: was a question about, Okay, well, is there anyone out

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Speaker 2: there that you think is you know, doing something good.

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Speaker 2: Has anybody seen anything from Democrat, any candidate or public

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Speaker 2: figure or someone locally that's made you say, oh.

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Speaker 4: Yeah, we need more of this. This is what we

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Speaker 4: should be doing.

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Speaker 2: More of this, guy, says Mike thirty three, white Democrat,

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Speaker 2: says Zoron Montani. Clear concise messaging. It's exactly what everybody wants.

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Speaker 2: It helps everybody. It's the perfect messaging because it's clear

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Speaker 2: and concise. Unlike Democrats, just like Bernie. Bernie has said

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Speaker 2: the same thing since the eighties. You've got a tax

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Speaker 2: of billionaires, you've got a tax upperclass. He's never changed.

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Speaker 2: That's the messaging. You've just got to drill it into them.

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Speaker 2: And Zoron did it. Man, it's beautiful. Diane seventy two

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Speaker 2: said Mike said it pretty clearly, and I can't really

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Speaker 2: think of anything to add to that. And there was

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Speaker 2: another person further down the list who also was like, yeah,

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Speaker 2: Mike said what I was going to say.

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Speaker 4: Now, I will temper that.

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Speaker 2: Zager with the fact that the other two names that

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Speaker 2: came up organically in the course of the conversation as

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Speaker 2: like democratic candidates that they were excited about were Jasmine

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Speaker 2: Crockett and Pete Booter.

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Speaker 1: I wanted everyone to know very careful because.

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Speaker 4: So what a progressive is is very.

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Speaker 1: Contested, as we have all discovered over the years of

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Speaker 1: the show. And I have no hate for the average American,

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Speaker 1: but it's not like people are very good at self identifying.

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Speaker 1: Somebody will be like, I'm a conservative, but that means

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Speaker 1: I want to tax billionaires and you're like, wait what

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Speaker 1: You're like, what are you talking about? Right? And then somebody, Look,

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Speaker 1: people are complicated. They don't think much about terms when

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Speaker 1: they hear the I mean, when I say the word progressive,

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Speaker 1: what do they think I want to move forward?

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Speaker 3: Right?

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Speaker 1: I mean can mean a lot of different things. Do

431
00:21:22,440 --> 00:21:25,879
Speaker 1: the activist class to the leftist base, that's an actual identity.

432
00:21:25,960 --> 00:21:28,880
Speaker 1: So like when I say I am a rightist. That's

433
00:21:28,920 --> 00:21:32,359
Speaker 1: because I've read a lot about politics. I don't identify

434
00:21:32,480 --> 00:21:35,639
Speaker 1: as a small C conservative. That's really not something that

435
00:21:35,800 --> 00:21:38,399
Speaker 1: is like that doesn't encompass like a belief right like

436
00:21:38,600 --> 00:21:41,119
Speaker 1: I would put myself much more in the vein of

437
00:21:41,160 --> 00:21:43,920
Speaker 1: like a European rightist. But most people don't think about

438
00:21:43,960 --> 00:21:46,640
Speaker 1: politics like. They don't read a lot about definitions. To them,

439
00:21:46,680 --> 00:21:49,280
Speaker 1: progressive means going forward, great, awesome right.

440
00:21:50,000 --> 00:21:52,120
Speaker 2: Just to add to that, at least one of them,

441
00:21:52,119 --> 00:21:54,639
Speaker 2: but maybe a number of them, brought up Joe Manchin

442
00:21:54,840 --> 00:21:57,520
Speaker 2: as why they do not want to moderate. And so

443
00:21:57,680 --> 00:22:00,840
Speaker 2: I think the combination of him, Kirson cinem and maybe

444
00:22:00,840 --> 00:22:03,240
Speaker 2: a handful of others, but those two being the primary villains,

445
00:22:03,520 --> 00:22:07,200
Speaker 2: they really destroyed the moderate label within the Democratic Party

446
00:22:07,400 --> 00:22:10,200
Speaker 2: because now moderate just seems like, oh, you're just gonna

447
00:22:10,200 --> 00:22:13,080
Speaker 2: obstruct anything good happening. You're just going to sell out

448
00:22:13,160 --> 00:22:15,000
Speaker 2: to like various corporate interests.

449
00:22:15,040 --> 00:22:16,679
Speaker 4: So no, of course we don't want that.

450
00:22:17,000 --> 00:22:18,919
Speaker 2: And then the other thing, and this is where you

451
00:22:18,960 --> 00:22:23,600
Speaker 2: know where it's dangerous, is there is a the Democratic

452
00:22:23,600 --> 00:22:26,840
Speaker 2: base is united in wanting to fight harder against Trump right.

453
00:22:26,880 --> 00:22:30,160
Speaker 2: They want someone who's pushing back effectively and is out

454
00:22:30,200 --> 00:22:33,240
Speaker 2: there and taking risks and is meeting the moment in

455
00:22:33,320 --> 00:22:36,040
Speaker 2: terms of the threat that they perceive to the country.

456
00:22:36,760 --> 00:22:39,159
Speaker 2: Sometimes though, that can be very amorphous. That's how you

457
00:22:39,280 --> 00:22:41,439
Speaker 2: end up with someone like Jasmine Crockett being named as

458
00:22:41,480 --> 00:22:44,560
Speaker 2: like she's a fighter will She is very rhetorically gifted,

459
00:22:44,880 --> 00:22:47,600
Speaker 2: she's very sassy. You know, she gets out there, she's

460
00:22:47,640 --> 00:22:50,919
Speaker 2: like quick with the quip, undeniably like talented and charismatic.

461
00:22:51,240 --> 00:22:53,360
Speaker 2: But if you dig underneath the surface, there's some real

462
00:22:53,359 --> 00:22:55,520
Speaker 2: problems there in terms of who she's taking money from

463
00:22:55,640 --> 00:22:58,000
Speaker 2: and the positions, how far she's willing to go, and she's.

464
00:22:57,880 --> 00:23:02,200
Speaker 1: Procrypt, she's identity pauled, like she's calling James Tallerico racist.

465
00:23:02,280 --> 00:23:04,119
Speaker 1: You know, she's the worst if you ask me. But

466
00:23:04,480 --> 00:23:05,200
Speaker 1: that's the issue.

467
00:23:05,200 --> 00:23:06,600
Speaker 4: But that's that's the challenge.

468
00:23:06,600 --> 00:23:09,400
Speaker 2: That's the question mark to me is not do Democrats

469
00:23:09,440 --> 00:23:11,400
Speaker 2: want to f They do, There's no doubt about it.

470
00:23:11,480 --> 00:23:14,080
Speaker 2: You know that that argument has been one and I

471
00:23:14,119 --> 00:23:16,440
Speaker 2: think the argument also has been one about like we're

472
00:23:16,480 --> 00:23:19,440
Speaker 2: not listening to these establishment boys like Chuck Shumeranha King, Jeffries,

473
00:23:19,600 --> 00:23:21,680
Speaker 2: go fuck yourself. We don't care what you have to say.

474
00:23:22,000 --> 00:23:24,840
Speaker 2: Even liberal you know, media institutions. I think there's been

475
00:23:24,880 --> 00:23:27,719
Speaker 2: a really breaking of the trust. But what it means

476
00:23:27,880 --> 00:23:31,240
Speaker 2: is being a progressive. Is that Gavin Newsome being on

477
00:23:31,280 --> 00:23:34,400
Speaker 2: Twitter and doing his like trolling routine, or is that,

478
00:23:34,760 --> 00:23:38,760
Speaker 2: you know, a Zoran mom Donnie type of politician where

479
00:23:38,800 --> 00:23:40,920
Speaker 2: not only do you have I mean Zora actually doesn't

480
00:23:40,960 --> 00:23:42,840
Speaker 2: do a lot of the like trope clapback or whatever,

481
00:23:43,040 --> 00:23:45,359
Speaker 2: but where you have an aggressive social media posture, but

482
00:23:45,440 --> 00:23:49,000
Speaker 2: it's backed up by specific policies as well. And so

483
00:23:49,320 --> 00:23:51,000
Speaker 2: that's the piece that you know, I think sort of

484
00:23:51,000 --> 00:23:54,080
Speaker 2: remains to be determined, and we're going to see. I

485
00:23:54,080 --> 00:23:56,520
Speaker 2: think we'll get a lot of indication of that from

486
00:23:56,840 --> 00:23:58,600
Speaker 2: some of the primaries that are going to play out

487
00:23:59,320 --> 00:24:01,760
Speaker 2: going to play out right now, and then certainly obviously

488
00:24:01,800 --> 00:24:04,280
Speaker 2: the biggest test of that will be in twenty twenty

489
00:24:04,320 --> 00:24:07,280
Speaker 2: eight whether someone like Gavin Newsom is going to be

490
00:24:07,359 --> 00:24:10,600
Speaker 2: able to position themselves as a quote unquote progressive even

491
00:24:10,640 --> 00:24:14,680
Speaker 2: as he is out there standing with billionaires to oppose

492
00:24:14,720 --> 00:24:17,800
Speaker 2: a wealth tax in his state. I am personally actually

493
00:24:18,040 --> 00:24:20,280
Speaker 2: hopeful that some of those things will be a problem,

494
00:24:20,520 --> 00:24:22,720
Speaker 2: Like you can see them mention in you know, a

495
00:24:22,760 --> 00:24:25,320
Speaker 2: bunch of the responses throughout this they talk about taxing

496
00:24:25,320 --> 00:24:27,760
Speaker 2: the rich as it's kind of like a litmus test issue,

497
00:24:27,920 --> 00:24:30,320
Speaker 2: and that would be a very hard one for a

498
00:24:30,400 --> 00:24:33,919
Speaker 2: Gavin Newsom's style candidate to you know, obviously he's like

499
00:24:33,960 --> 00:24:37,119
Speaker 2: already on the wrong side of that issue. So I

500
00:24:37,160 --> 00:24:41,480
Speaker 2: am hopeful that there actually will be a substantive policy

501
00:24:41,920 --> 00:24:44,959
Speaker 2: lens that the term progressive will be viewed for, But

502
00:24:45,040 --> 00:24:47,480
Speaker 2: I fully acknowledge that that is still a question mark

503
00:24:47,520 --> 00:24:47,960
Speaker 2: for sure.

504
00:24:48,320 --> 00:24:50,960
Speaker 1: As I have learned over the years, and I've watched

505
00:24:51,160 --> 00:24:54,639
Speaker 1: the words working class came to mean very different things.

506
00:24:54,920 --> 00:24:57,159
Speaker 1: To remember, Ted Cruz used to say that we're a

507
00:24:57,200 --> 00:25:00,479
Speaker 1: working class part. Ted Cruz called up a working class politician, okay,

508
00:25:00,680 --> 00:25:02,080
Speaker 1: And if you were to ask people, some of the

509
00:25:02,119 --> 00:25:03,960
Speaker 1: people who voted for him, they might even say, oh, yeah,

510
00:25:04,000 --> 00:25:06,480
Speaker 1: you sports the work, like be honest, like is there

511
00:25:06,520 --> 00:25:08,879
Speaker 1: a huge disconnect for all of it. I've seen the

512
00:25:08,960 --> 00:25:13,000
Speaker 1: term bastardized about populism or working class now in the

513
00:25:13,040 --> 00:25:15,880
Speaker 1: Republican Party, and it can be true at a rhetorical level,

514
00:25:15,960 --> 00:25:18,119
Speaker 1: wrong at a policy level. Turns out, a lot of

515
00:25:18,160 --> 00:25:20,640
Speaker 1: people don't care about the policy level. At the middle

516
00:25:20,760 --> 00:25:23,320
Speaker 1: of an election, you could very easily see how it

517
00:25:23,359 --> 00:25:25,560
Speaker 1: could be bastardized. And I mean for the people who

518
00:25:25,560 --> 00:25:27,399
Speaker 1: watch our show, it's going to be tough because you know,

519
00:25:27,480 --> 00:25:29,680
Speaker 1: you guys, if you're watching this, you're in the top

520
00:25:29,760 --> 00:25:33,159
Speaker 1: two five percent of people consume politics. You got to

521
00:25:33,160 --> 00:25:35,800
Speaker 1: think about your uncle or somebody who really doesn't pay

522
00:25:36,040 --> 00:25:38,439
Speaker 1: that much attention is pissed off about Trump because of

523
00:25:38,720 --> 00:25:40,840
Speaker 1: the White House lawn or something like that. You know

524
00:25:41,000 --> 00:25:44,200
Speaker 1: somebody who's cranky about decorum. What does the term progressive

525
00:25:44,280 --> 00:25:47,200
Speaker 1: mean to them? Probably nothing. And so when a Pete

526
00:25:47,200 --> 00:25:50,119
Speaker 1: boodhaj Edge can say that famous Hillary line, I'm a

527
00:25:50,160 --> 00:25:53,119
Speaker 1: progressive who likes to get things done, it might land

528
00:25:53,359 --> 00:25:56,280
Speaker 1: same with Gavin Newsom. I nobody's done more on climate

529
00:25:56,400 --> 00:26:00,440
Speaker 1: than me. The billionaire question. He's a very savvy political operator.

530
00:26:00,600 --> 00:26:04,480
Speaker 1: Times I'll give you some hope. I'll give you some hope,

531
00:26:04,520 --> 00:26:08,119
Speaker 1: which is for the Democratic base. Because the Democratic base

532
00:26:08,520 --> 00:26:13,159
Speaker 1: is now more overwhelmingly college educated than everyone else. They

533
00:26:13,200 --> 00:26:16,000
Speaker 1: are going to be a lot more well read and

534
00:26:16,240 --> 00:26:20,560
Speaker 1: grammatic literally grammatically, uh, let's think about the best way

535
00:26:20,560 --> 00:26:22,400
Speaker 1: to phrases. They're going to be a lot more educated

536
00:26:22,600 --> 00:26:25,280
Speaker 1: and a lot more have much more of an ability

537
00:26:25,400 --> 00:26:29,560
Speaker 1: to parse language and actually think about what these terms mean.

538
00:26:29,880 --> 00:26:32,800
Speaker 1: As opposed to what the current existing Republican base is

539
00:26:32,840 --> 00:26:36,040
Speaker 1: going to be, They're going to be way more heavier

540
00:26:36,119 --> 00:26:39,600
Speaker 1: news consumers, much more well read whenever it comes to politics,

541
00:26:40,119 --> 00:26:43,679
Speaker 1: probably care much more about policy. Richard Henania has the

542
00:26:43,720 --> 00:26:47,040
Speaker 1: famous thing about how conservatives watch TV and liberals read

543
00:26:47,200 --> 00:26:49,880
Speaker 1: that actually does matter whenever it comes to policy, prescription

544
00:26:50,080 --> 00:26:52,080
Speaker 1: and other things. Is if you're going to read a

545
00:26:52,119 --> 00:26:55,280
Speaker 1: policy position that already puts you pretty dramatically out of

546
00:26:55,280 --> 00:26:57,760
Speaker 1: step with some of the other base that is voting,

547
00:26:57,800 --> 00:26:59,560
Speaker 1: I mean, I'm just being real here in terms of

548
00:26:59,640 --> 00:27:01,919
Speaker 1: how that will look. So I think it will actually

549
00:27:01,920 --> 00:27:04,560
Speaker 1: look quite different. But the other thing that I'm not

550
00:27:05,080 --> 00:27:06,760
Speaker 1: I don't want to underestimate for a lot of the

551
00:27:06,760 --> 00:27:10,080
Speaker 1: people who are also Democrats is you should forget don't forget.

552
00:27:10,200 --> 00:27:12,439
Speaker 1: South Carolina could be the first state and that's a

553
00:27:12,760 --> 00:27:16,560
Speaker 1: very different Democratic primary. And then if you have lower

554
00:27:16,600 --> 00:27:20,040
Speaker 1: propensity voters who are upset at Trump who come out

555
00:27:20,080 --> 00:27:20,440
Speaker 1: to vote.

556
00:27:20,480 --> 00:27:22,680
Speaker 2: Although those people in South Carolina did not mess with

557
00:27:22,720 --> 00:27:25,600
Speaker 2: Pete Boodage, so I'm not worried about him doing well there, they.

558
00:27:25,520 --> 00:27:27,719
Speaker 1: Could mess with Crockett right, I could see that.

559
00:27:27,800 --> 00:27:29,320
Speaker 4: I mean, you think, don't you think she's going to

560
00:27:29,400 --> 00:27:29,960
Speaker 4: run for president?

561
00:27:30,119 --> 00:27:30,720
Speaker 3: Maybe? Why not?

562
00:27:30,840 --> 00:27:32,480
Speaker 4: I think he's not to win.

563
00:27:33,119 --> 00:27:36,240
Speaker 2: You know Texas, like the war senator from Texas.

564
00:27:35,880 --> 00:27:37,280
Speaker 1: Bato failed he ran for president.

565
00:27:37,400 --> 00:27:38,520
Speaker 4: Yeah, but how did that work out?

566
00:27:38,640 --> 00:27:39,560
Speaker 1: Sure he got two percent?

567
00:27:39,600 --> 00:27:40,479
Speaker 4: But yeah, I don't know.

568
00:27:40,760 --> 00:27:42,520
Speaker 1: What I need is Jim Clyburn to come in and

569
00:27:42,920 --> 00:27:45,359
Speaker 1: make you a king. Remember there's no Iowa, there's no

570
00:27:45,440 --> 00:27:46,960
Speaker 1: New Hampshire Clearinghouse this time.

571
00:27:47,000 --> 00:27:47,479
Speaker 4: Well it's not.

572
00:27:47,560 --> 00:27:49,600
Speaker 2: It's actually not clear what the order of the states

573
00:27:49,680 --> 00:27:51,040
Speaker 2: is going to be. Some of that is still up

574
00:27:51,040 --> 00:27:53,680
Speaker 2: for grounds. South Carolina will certainly be early and important

575
00:27:53,680 --> 00:27:54,360
Speaker 2: in the process.

576
00:27:54,400 --> 00:27:56,359
Speaker 4: But I mean, here's here's what I would say.

577
00:27:56,480 --> 00:27:58,600
Speaker 2: My own prediction is that there are going to be

578
00:27:58,640 --> 00:28:00,720
Speaker 2: a few issues that are Lippus test issues. I think

579
00:28:00,760 --> 00:28:03,920
Speaker 2: their money for maypack, I think they're taxing the rich,

580
00:28:04,560 --> 00:28:07,000
Speaker 2: and I think it's abolishing nice. I think those three

581
00:28:07,000 --> 00:28:10,199
Speaker 2: things are going to be actual litmus test issues, and

582
00:28:10,320 --> 00:28:12,880
Speaker 2: candidates who can't give clear cut answers on that are

583
00:28:12,880 --> 00:28:15,199
Speaker 2: going to struggle. And I think the testing ground for

584
00:28:15,240 --> 00:28:16,880
Speaker 2: that has been that I've had at podcast where you've

585
00:28:16,920 --> 00:28:20,760
Speaker 2: got you know, you've got lady, I mean, Jennifer and

586
00:28:20,840 --> 00:28:23,159
Speaker 2: Pumps at this point have really shifted a lot to

587
00:28:23,200 --> 00:28:25,480
Speaker 2: the left right. These were Hillary supporters who are now like,

588
00:28:25,520 --> 00:28:26,960
Speaker 2: you know what, Bernie was right and we should have

589
00:28:26,960 --> 00:28:29,600
Speaker 2: been there a lot. So they have shifted significantly. But

590
00:28:29,680 --> 00:28:32,119
Speaker 2: you know, their audience is very reflective of kind of

591
00:28:32,119 --> 00:28:35,480
Speaker 2: like the core liberal base of the Democratic Party. And

592
00:28:35,600 --> 00:28:38,440
Speaker 2: they are not speak not having it. They have not

593
00:28:38,640 --> 00:28:41,360
Speaker 2: having it with Corey Booker coming on and doing his

594
00:28:41,440 --> 00:28:43,520
Speaker 2: little tap dance or Ram Emmanuel whoever.

595
00:28:43,800 --> 00:28:45,720
Speaker 4: They are not having it with these people.

596
00:28:45,800 --> 00:28:48,200
Speaker 2: And so you know, that tells me there is kind

597
00:28:48,200 --> 00:28:50,520
Speaker 2: of a hard line and an expectation of we want

598
00:28:50,520 --> 00:28:53,480
Speaker 2: to hear not just you, you know, with a bunch

599
00:28:53,520 --> 00:28:56,200
Speaker 2: of word salad trying to massage an answer. We want

600
00:28:56,240 --> 00:28:58,560
Speaker 2: to hear yes or no answers to these few questions.

601
00:28:58,600 --> 00:29:00,560
Speaker 2: The other thing that gives me some hope, especially on

602
00:29:00,560 --> 00:29:02,040
Speaker 2: the identity politics front.

603
00:29:02,160 --> 00:29:06,480
Speaker 4: Is there is also the level of trickery that Hillary.

604
00:29:06,200 --> 00:29:09,240
Speaker 2: Clinton was able to engage in in her campaign against Bernie,

605
00:29:09,360 --> 00:29:13,640
Speaker 2: where she was positioning herself like using identity politics to

606
00:29:13,720 --> 00:29:16,600
Speaker 2: pretend like she was the more progressive candidate. I think

607
00:29:16,640 --> 00:29:20,440
Speaker 2: people see through that garbage entirely at this point, as

608
00:29:20,520 --> 00:29:23,360
Speaker 2: evidenced by the fact that Hailey Stevens, who is a

609
00:29:23,760 --> 00:29:26,320
Speaker 2: Michigan member of Congress, she's in the House right now

610
00:29:26,320 --> 00:29:29,000
Speaker 2: and is running for Senate. It's like the conservative or

611
00:29:29,040 --> 00:29:32,040
Speaker 2: moderate candidate in that race back by Tuck, Shoomer, etc.

612
00:29:32,720 --> 00:29:35,520
Speaker 2: She went and toured an ICE facility and she tro

613
00:29:35,640 --> 00:29:37,880
Speaker 2: When she came out, she was like, Oh, I felt

614
00:29:37,960 --> 00:29:40,880
Speaker 2: better because we've got female ICE agents who are running

615
00:29:40,880 --> 00:29:43,200
Speaker 2: the place, trying to do like a girl boss ice

616
00:29:43,240 --> 00:29:46,320
Speaker 2: agent situation. And people were not buying this whatsoever.

617
00:29:46,480 --> 00:29:49,120
Speaker 4: This is f five. Let's take aalism of noe.

618
00:29:49,160 --> 00:29:52,320
Speaker 1: There are female female leadership.

619
00:29:52,360 --> 00:29:55,280
Speaker 4: Here your female leadership, and there are women.

620
00:29:55,600 --> 00:30:00,320
Speaker 5: Who who walked with us today and explained on the

621
00:30:00,400 --> 00:30:04,440
Speaker 5: intake process how important it is to dream people with humanity,

622
00:30:04,520 --> 00:30:07,680
Speaker 5: and that obviously really stuck out to me because some

623
00:30:07,760 --> 00:30:10,320
Speaker 5: of the things that we are witnessing before our eyes

624
00:30:10,440 --> 00:30:13,320
Speaker 5: in our neighborhoods, in our streets is really a lack

625
00:30:13,360 --> 00:30:14,080
Speaker 5: of humanity.

626
00:30:14,680 --> 00:30:17,800
Speaker 2: So people were you know, this one did not land.

627
00:30:18,000 --> 00:30:22,640
Speaker 2: This did not land with the Democratic base whatsoever. I mean,

628
00:30:22,680 --> 00:30:25,160
Speaker 2: it's the name, right, It's like you know they're bombing.

629
00:30:24,800 --> 00:30:26,960
Speaker 1: But they're they're at least their female.

630
00:30:27,280 --> 00:30:30,400
Speaker 2: Right, they're female, and they're flying the gay pride flags. No, no, no,

631
00:30:30,440 --> 00:30:32,880
Speaker 2: where we see through that. Now, we're not doing this anymore.

632
00:30:33,120 --> 00:30:36,240
Speaker 1: Listen, I would I would welcome nothing more. More. Recently,

633
00:30:36,240 --> 00:30:39,000
Speaker 1: there's been a gay there's been a sassy gay ice

634
00:30:39,040 --> 00:30:41,520
Speaker 1: agent who's gone viral on the road. Oh, I thought

635
00:30:41,560 --> 00:30:46,080
Speaker 1: I saw that. I loved the same thing. If we

636
00:30:46,080 --> 00:30:49,520
Speaker 1: could turn them against we can turn against identity politics,

637
00:30:50,160 --> 00:30:52,680
Speaker 1: no one will be happier than me. Oh that was great.

638
00:30:55,840 --> 00:30:56,760
Speaker 1: Let's get to the next one.

639
00:30:56,880 --> 00:30:58,400
Speaker 4: Yeah. So this is an interesting story.

640
00:30:58,400 --> 00:31:00,280
Speaker 2: It kind of dovetails with some of the you know,

641
00:31:00,760 --> 00:31:03,800
Speaker 2: it's a cross coalitional I think backlash against the push

642
00:31:03,880 --> 00:31:06,520
Speaker 2: towards gambling. But the most clear place where we've had

643
00:31:06,520 --> 00:31:10,680
Speaker 2: this cross partisan backlash is in the fight against AI

644
00:31:10,760 --> 00:31:13,160
Speaker 2: more broadly, but specifically on the front lines with regards

645
00:31:13,160 --> 00:31:14,520
Speaker 2: to data centers. And we could put this up on

646
00:31:14,520 --> 00:31:17,920
Speaker 2: the screen. This is a scene from Claremore, Oklahoma. This

647
00:31:18,080 --> 00:31:23,920
Speaker 2: is like a local Oklahoma town meeting where this person

648
00:31:23,960 --> 00:31:26,040
Speaker 2: who was in Oklahoma says people are being arrested for

649
00:31:26,080 --> 00:31:28,719
Speaker 2: speaking out against AI data centers. Please keep standing up

650
00:31:28,720 --> 00:31:32,240
Speaker 2: for your community. There's another video that's gone viral this

651
00:31:32,320 --> 00:31:34,040
Speaker 2: morning that I saw you guys could take this down.

652
00:31:34,680 --> 00:31:37,200
Speaker 2: That I saw of another place I'm not sure if

653
00:31:37,200 --> 00:31:38,880
Speaker 2: it was a red state or not, but where there

654
00:31:38,880 --> 00:31:41,680
Speaker 2: had been significant protests against the data center and ultimately

655
00:31:41,720 --> 00:31:45,000
Speaker 2: the town backs down. The backlash against these places is

656
00:31:45,080 --> 00:31:47,480
Speaker 2: really building. And I was just listening to The New

657
00:31:47,560 --> 00:31:50,120
Speaker 2: York Times actually did a deep dive into a town

658
00:31:50,160 --> 00:31:52,760
Speaker 2: in Indiana that has become a hot spot for a

659
00:31:52,760 --> 00:31:54,000
Speaker 2: bunch of these data centers.

660
00:31:54,200 --> 00:31:56,320
Speaker 4: And the first ones kind of got built and.

661
00:31:56,320 --> 00:31:59,440
Speaker 2: People just like accepted it, and there wasn't they didn't

662
00:31:59,440 --> 00:32:01,840
Speaker 2: need any zone owing approval, so the town council like

663
00:32:01,880 --> 00:32:04,239
Speaker 2: it just kind of sailed through. And now people are

664
00:32:04,280 --> 00:32:07,720
Speaker 2: experiencing all of this increased traffic and noise, and they're

665
00:32:07,720 --> 00:32:10,280
Speaker 2: starting to research, Okay, what even is AI and what

666
00:32:10,360 --> 00:32:11,600
Speaker 2: is this going to mean, and what's it going to

667
00:32:11,880 --> 00:32:14,320
Speaker 2: mean long term? And how many jobs are even really created?

668
00:32:14,440 --> 00:32:16,400
Speaker 2: What is this going to mean for our community? And

669
00:32:16,480 --> 00:32:20,320
Speaker 2: now there was a huge backlash to this new data

670
00:32:20,320 --> 00:32:22,440
Speaker 2: center that they were trying to place there that did

671
00:32:22,520 --> 00:32:25,400
Speaker 2: require a zoning change, which meant that the town had

672
00:32:25,400 --> 00:32:29,240
Speaker 2: a chance to weigh in, so they held meetings overnight

673
00:32:29,400 --> 00:32:32,480
Speaker 2: and they first called for okay, who's in support of this?

674
00:32:32,920 --> 00:32:35,600
Speaker 2: And people got up and they spoke for there were like,

675
00:32:35,680 --> 00:32:38,080
Speaker 2: you know, enough to fill about twenty five minutes. Then

676
00:32:38,280 --> 00:32:41,280
Speaker 2: they opened it up for the opponents. The opponents there

677
00:32:41,280 --> 00:32:43,440
Speaker 2: were so many of them that the meeting went on

678
00:32:43,520 --> 00:32:47,120
Speaker 2: into four am assult ultimately, and this is a small town,

679
00:32:47,240 --> 00:32:49,600
Speaker 2: right and ultimately the town council is like, okay, yeah,

680
00:32:49,600 --> 00:32:51,680
Speaker 2: we're not going to do this. And so you are

681
00:32:51,720 --> 00:32:55,120
Speaker 2: seeing this huge backlash and a lot of these data

682
00:32:55,120 --> 00:32:58,400
Speaker 2: centers are being located in red states and red areas

683
00:32:58,400 --> 00:33:01,480
Speaker 2: because rural areas have more and rural areas tend to

684
00:33:01,560 --> 00:33:04,479
Speaker 2: be more Republican. Let's go and put G two up

685
00:33:04,480 --> 00:33:07,239
Speaker 2: on the screen. This was a fantastic report from the

686
00:33:07,240 --> 00:33:10,560
Speaker 2: Financial Times. They say Donald Trump's AI push fuel's revolt

687
00:33:10,920 --> 00:33:13,479
Speaker 2: in MAGA heartlands. On a cold Tuesday evening last week,

688
00:33:13,520 --> 00:33:17,520
Speaker 2: about two hundred Missourians, Missouri being another hotbed of AI

689
00:33:17,640 --> 00:33:20,760
Speaker 2: development and also backlash, crammed into a Methodist church to

690
00:33:20,800 --> 00:33:23,880
Speaker 2: share a message. The AI revolution embraced by Trump's White

691
00:33:23,880 --> 00:33:26,040
Speaker 2: House did not have their unqualified support.

692
00:33:26,360 --> 00:33:26,840
Speaker 1: Quote.

693
00:33:26,960 --> 00:33:29,800
Speaker 2: I voted for this administration and didn't really think about

694
00:33:29,800 --> 00:33:32,680
Speaker 2: AI until it started to affect me, said Lisa Garrett,

695
00:33:32,680 --> 00:33:35,360
Speaker 2: who lives beside the site of a rapidly greenlit six

696
00:33:35,440 --> 00:33:39,400
Speaker 2: point six billion dollars four hundred acre data center development

697
00:33:39,440 --> 00:33:42,440
Speaker 2: in the satellite city of Independence, just east of Kansas City.

698
00:33:42,680 --> 00:33:45,680
Speaker 2: A worker for a local ministry, Garrett's Onneyes extends beyond

699
00:33:45,680 --> 00:33:48,600
Speaker 2: the project's demand on local water and electricity supplies, to

700
00:33:48,640 --> 00:33:51,200
Speaker 2: the broader social impact of the industry it is being

701
00:33:51,200 --> 00:33:54,720
Speaker 2: built to support. I have grandchildren. It does concern me

702
00:33:54,840 --> 00:33:57,400
Speaker 2: that they're being drawn into a world that isn't real,

703
00:33:57,480 --> 00:33:59,880
Speaker 2: she said. Her concerns, which pull after poll has shown

704
00:33:59,880 --> 00:34:02,239
Speaker 2: her shared by much of Trump's space, are increasingly at

705
00:34:02,240 --> 00:34:06,160
Speaker 2: odds with the posture and policies of his administration. And actually, Sager,

706
00:34:06,240 --> 00:34:09,200
Speaker 2: I mean it is very like cross partisan the concerns

707
00:34:09,200 --> 00:34:12,480
Speaker 2: here about data centers in particular. But the recent pulling

708
00:34:12,480 --> 00:34:14,600
Speaker 2: that I saw show showed that the concerns were actually

709
00:34:14,680 --> 00:34:17,520
Speaker 2: higher on the right for reasons that you can understand,

710
00:34:17,520 --> 00:34:19,919
Speaker 2: because there tends to be more you know, more of

711
00:34:20,000 --> 00:34:22,680
Speaker 2: a rural base, more concern about, okay, what is this

712
00:34:22,680 --> 00:34:25,040
Speaker 2: community going to be, and more like sort of like

713
00:34:25,080 --> 00:34:28,719
Speaker 2: this rootedness in a certain place and so and more

714
00:34:28,800 --> 00:34:31,680
Speaker 2: quote unquote conservative views of like we aren't we are

715
00:34:31,719 --> 00:34:33,920
Speaker 2: a little wary of change. We don't necessarily want the

716
00:34:33,920 --> 00:34:35,719
Speaker 2: world to be turned upside down, not just in our

717
00:34:35,719 --> 00:34:38,920
Speaker 2: local community, but by whatever this means. So, you know,

718
00:34:39,000 --> 00:34:41,640
Speaker 2: I think this is one of the important fights as

719
00:34:41,680 --> 00:34:45,520
Speaker 2: we contemplate what AI is going to mean for our

720
00:34:45,560 --> 00:34:48,480
Speaker 2: social contract, and one of the places where you can

721
00:34:48,520 --> 00:34:50,920
Speaker 2: sort of like you know, throw sand in the gears

722
00:34:51,000 --> 00:34:53,680
Speaker 2: and at least slow the process down so that there

723
00:34:53,760 --> 00:34:56,200
Speaker 2: is more of a chance for democracy to be able.

724
00:34:56,080 --> 00:34:56,520
Speaker 1: To catch up.

725
00:34:56,600 --> 00:34:56,759
Speaker 4: Yeah.

726
00:34:56,800 --> 00:34:59,920
Speaker 1: I just think it's amazing, Like they're literally organic movements,

727
00:35:00,040 --> 00:35:03,440
Speaker 1: people with their children, no data center, because again, everyone

728
00:35:03,520 --> 00:35:06,719
Speaker 1: can feel this encroachment in their lives, especially if you

729
00:35:06,760 --> 00:35:08,960
Speaker 1: have a child. So there's all these viral threads that

730
00:35:09,000 --> 00:35:12,520
Speaker 1: are going around now about Spotify. For example, someone was like,

731
00:35:12,560 --> 00:35:15,920
Speaker 1: you know, I'm so careful I don't allow video, and

732
00:35:15,960 --> 00:35:18,280
Speaker 1: then what ended up happening is I gave my kids

733
00:35:18,280 --> 00:35:21,240
Speaker 1: access to my Spotify account, but now Spotify is including

734
00:35:21,360 --> 00:35:23,920
Speaker 1: music videos and it was like a workaround, and he's like,

735
00:35:23,960 --> 00:35:26,359
Speaker 1: now I have to take Spotify away from it. It's

736
00:35:26,400 --> 00:35:30,239
Speaker 1: like at every level you have parents who are bombarded

737
00:35:30,360 --> 00:35:33,360
Speaker 1: doing everything they possibly can, having to pay attention to

738
00:35:33,480 --> 00:35:36,799
Speaker 1: like every facet of modern life. More recently, you know

739
00:35:36,840 --> 00:35:39,600
Speaker 1: how they would give out chromebooks or computers. You have

740
00:35:39,680 --> 00:35:41,759
Speaker 1: teachers or you have parents who are turning them in.

741
00:35:41,800 --> 00:35:43,640
Speaker 1: They're like, I can't have my children on this. They're

742
00:35:43,719 --> 00:35:46,279
Speaker 1: using it as a workaround their screen time and all this.

743
00:35:46,560 --> 00:35:49,799
Speaker 1: They're demanding that schools go back to paper because they're like,

744
00:35:49,840 --> 00:35:52,600
Speaker 1: we have to just get rid of all this technology.

745
00:35:52,680 --> 00:35:55,520
Speaker 1: Nothing's good coming from this is rotting my child's brain.

746
00:35:55,760 --> 00:35:58,799
Speaker 1: And then you put the AI data center stuff into this,

747
00:35:59,200 --> 00:36:00,879
Speaker 1: and then you have to look at the promise. What

748
00:36:00,920 --> 00:36:05,000
Speaker 1: are we getting more claud agents that might like automate

749
00:36:05,120 --> 00:36:08,960
Speaker 1: all the jobs, or more slop that children can watch

750
00:36:08,960 --> 00:36:13,080
Speaker 1: on YouTube or YouTube shorts more. You know, now there's

751
00:36:13,080 --> 00:36:16,279
Speaker 1: all these new AI movies that people are competing for.

752
00:36:16,360 --> 00:36:19,160
Speaker 1: Everyone's like the bargain is not worth it. Higher electricity

753
00:36:19,200 --> 00:36:21,680
Speaker 1: price and trying to take my job, which you increasingly

754
00:36:22,040 --> 00:36:24,640
Speaker 1: brag about, and then general also just like propping up

755
00:36:24,680 --> 00:36:27,239
Speaker 1: a sham stock market all at the same time, it's

756
00:36:27,280 --> 00:36:30,640
Speaker 1: just is ridiculous. On top of corrupting a local community

757
00:36:31,200 --> 00:36:34,919
Speaker 1: energy usage power bills it's all about control. And yeah,

758
00:36:34,960 --> 00:36:37,279
Speaker 1: the most conservative impulse of all time is to like

759
00:36:37,600 --> 00:36:40,320
Speaker 1: the famous line is like stand thwart history and yell stop,

760
00:36:40,480 --> 00:36:42,120
Speaker 1: and like that's how a lot of people feel right now.

761
00:36:42,120 --> 00:36:43,320
Speaker 4: I feel like the way right now.

762
00:36:43,480 --> 00:36:46,319
Speaker 2: I feel that way because listen, you know, I think

763
00:36:46,360 --> 00:36:47,680
Speaker 2: the technology is cool.

764
00:36:47,880 --> 00:36:49,720
Speaker 4: Like I've been playing around with Claude.

765
00:36:50,120 --> 00:36:54,279
Speaker 2: I think the advances over the past year, the more

766
00:36:54,320 --> 00:36:57,600
Speaker 2: I dig into it, the more I realize is genuinely extraordinary.

767
00:36:57,719 --> 00:36:59,360
Speaker 2: You know, the things you're able to feed in the

768
00:36:59,360 --> 00:37:03,520
Speaker 2: hallucination have been diminished, the level the ability this part

769
00:37:03,560 --> 00:37:06,160
Speaker 2: I haven't been able to figure out yet. But you know,

770
00:37:07,000 --> 00:37:09,399
Speaker 2: you hear people who are not technical people or able

771
00:37:09,440 --> 00:37:11,279
Speaker 2: to just go and like create an app and it

772
00:37:11,280 --> 00:37:13,480
Speaker 2: doesn't even take very long and Claude spins it out

773
00:37:13,520 --> 00:37:14,080
Speaker 2: in a few minutes.

774
00:37:14,280 --> 00:37:16,319
Speaker 4: This is something. This is astonishing.

775
00:37:16,800 --> 00:37:20,440
Speaker 2: And if it was, if the ownership was done correctly

776
00:37:20,480 --> 00:37:23,600
Speaker 2: and the democratic control was done correctly, you can't imagine,

777
00:37:23,640 --> 00:37:26,000
Speaker 2: you know, a society that was not structured like ours,

778
00:37:26,200 --> 00:37:28,920
Speaker 2: where this would just be beneficial, where it would just

779
00:37:28,960 --> 00:37:30,960
Speaker 2: be exciting and we would figure out how to manage

780
00:37:30,960 --> 00:37:34,000
Speaker 2: the resources. I mean, the other risk that some of

781
00:37:34,000 --> 00:37:37,080
Speaker 2: the community members in Indiana we're talking about is they're like,

782
00:37:37,440 --> 00:37:39,960
Speaker 2: they're like, we looked into this and there are a

783
00:37:39,960 --> 00:37:42,919
Speaker 2: lot of models coming out of China that are much

784
00:37:43,000 --> 00:37:45,920
Speaker 2: less resource intensive. So you're going to build all of

785
00:37:45,960 --> 00:37:48,040
Speaker 2: these data centers out are they even going to be

786
00:37:48,080 --> 00:37:50,040
Speaker 2: needed in the future as these things become more and

787
00:37:50,080 --> 00:37:50,800
Speaker 2: more efficient?

788
00:37:51,080 --> 00:37:52,040
Speaker 4: So even that, you.

789
00:37:52,040 --> 00:37:54,480
Speaker 2: Know, and then we're left with this big hulking, you know,

790
00:37:54,680 --> 00:37:56,920
Speaker 2: decaying husk in our community.

791
00:37:56,960 --> 00:37:58,400
Speaker 4: And what does that ultimately look like?

792
00:37:58,440 --> 00:38:00,879
Speaker 2: So in any case, you know, we we would need

793
00:38:00,920 --> 00:38:04,319
Speaker 2: to have massive democratic input on the resource usage, on

794
00:38:04,480 --> 00:38:07,760
Speaker 2: the you know, capital expenditure, on how this is deployed,

795
00:38:07,840 --> 00:38:10,480
Speaker 2: on how it is used, all on you know, how

796
00:38:10,520 --> 00:38:15,600
Speaker 2: the how the fruits of this alleged productivity gains are

797
00:38:15,640 --> 00:38:18,040
Speaker 2: going to be distributed. I mean, that's like the essential

798
00:38:18,120 --> 00:38:21,240
Speaker 2: question in my view. But obviously we don't have any

799
00:38:21,280 --> 00:38:23,480
Speaker 2: of that, which is why again I think these fights

800
00:38:23,520 --> 00:38:26,440
Speaker 2: against data centers on a local basis, like that is

801
00:38:26,480 --> 00:38:29,600
Speaker 2: the most likely place where you can have any sort

802
00:38:29,880 --> 00:38:33,480
Speaker 2: of pushback, any sort of slow down in terms of

803
00:38:33,480 --> 00:38:35,440
Speaker 2: this development, because in terms of you know, from this

804
00:38:35,480 --> 00:38:38,239
Speaker 2: administration's perspective, it's just off to the races, and you know,

805
00:38:38,320 --> 00:38:43,399
Speaker 2: the dystopian parts of this are becoming are increasingly here.

806
00:38:43,719 --> 00:38:45,560
Speaker 4: Let's put G three up on the screen. We covered

807
00:38:45,560 --> 00:38:46,120
Speaker 4: this before.

808
00:38:46,160 --> 00:38:49,759
Speaker 2: There's this fight between Anthropic and the Pentagon where they're

809
00:38:49,800 --> 00:38:52,880
Speaker 2: threatening to cut off Anthropic in what is being described

810
00:38:52,920 --> 00:38:56,560
Speaker 2: here as an AI safeguards dispute, and the TLDR is

811
00:38:56,760 --> 00:39:00,600
Speaker 2: that the Anthropic people got concerned about the way that

812
00:39:00,719 --> 00:39:04,080
Speaker 2: Claude was used in the Venezuela rate. Now they have

813
00:39:04,320 --> 00:39:07,960
Speaker 2: some sort of partnership with Palenteer and Claude and Anthropics

814
00:39:08,000 --> 00:39:12,320
Speaker 2: products are generally more advanced in terms of government application,

815
00:39:12,440 --> 00:39:15,200
Speaker 2: so they have a big contract with the Pentagon, and

816
00:39:15,600 --> 00:39:18,440
Speaker 2: they're saying to the Pentagon, look, we have two red lines.

817
00:39:18,520 --> 00:39:20,640
Speaker 2: Number one, we don't want Claude to be used in

818
00:39:20,680 --> 00:39:24,799
Speaker 2: any sort of like autonomous killer robots, and number two,

819
00:39:24,840 --> 00:39:27,240
Speaker 2: we don't want to be used for mass surveillance against

820
00:39:27,280 --> 00:39:29,040
Speaker 2: American people. Now, I'm not sure why you have this

821
00:39:29,120 --> 00:39:31,880
Speaker 2: tie up with Palenteer if you have these concerns, but

822
00:39:32,239 --> 00:39:35,040
Speaker 2: that's where they're trying to draw a line. The other

823
00:39:35,080 --> 00:39:38,839
Speaker 2: AI companies do not have such moral red lines, and

824
00:39:38,920 --> 00:39:40,839
Speaker 2: I don't want to give Anthropic too much credit here.

825
00:39:40,880 --> 00:39:44,600
Speaker 2: Because I think it's incredibly, incredibly naive to think that

826
00:39:44,640 --> 00:39:46,680
Speaker 2: you would be able to hold the line on these

827
00:39:46,719 --> 00:39:50,960
Speaker 2: things and you as individual like business owner or capitalists,

828
00:39:51,000 --> 00:39:53,080
Speaker 2: are going to be able to tell the Department of

829
00:39:53,120 --> 00:39:57,719
Speaker 2: War and the United States government how your technology gets deployed. Like,

830
00:39:57,760 --> 00:40:00,759
Speaker 2: I think that was a very fanciful notion, but you

831
00:40:00,800 --> 00:40:03,680
Speaker 2: can see how already the Pentagon's like, no, we're not

832
00:40:03,719 --> 00:40:05,640
Speaker 2: going to listen to you. Not only are we not

833
00:40:05,680 --> 00:40:08,600
Speaker 2: going to abide by your little, your little moral red

834
00:40:08,640 --> 00:40:12,120
Speaker 2: lines against killer robots and mass surveillance, but we are

835
00:40:12,160 --> 00:40:14,799
Speaker 2: going to punish any company that does work with you

836
00:40:15,120 --> 00:40:18,000
Speaker 2: because you have the audacity to even try to put

837
00:40:18,040 --> 00:40:21,440
Speaker 2: any sort of red line on how your technology can

838
00:40:21,480 --> 00:40:25,960
Speaker 2: be deployed. So you know, there was Eric Schmidt, former

839
00:40:26,000 --> 00:40:29,440
Speaker 2: CEO of Google. He was talking about a year ago

840
00:40:29,680 --> 00:40:32,560
Speaker 2: saying that, you know, one of the things that all

841
00:40:32,600 --> 00:40:35,399
Speaker 2: the AI CEOs were basically in agreement with is if

842
00:40:35,400 --> 00:40:38,160
Speaker 2: this starts getting deployed and killer robots, they would pull

843
00:40:38,160 --> 00:40:40,759
Speaker 2: the plug. But what you realize is like you don't

844
00:40:40,760 --> 00:40:42,759
Speaker 2: actually have the ability to pull the plug even if

845
00:40:42,800 --> 00:40:45,360
Speaker 2: you wanted to then, and already they've all abandoned that

846
00:40:45,400 --> 00:40:47,640
Speaker 2: and like eh, well maybe killer Robert robots or okay,

847
00:40:47,680 --> 00:40:49,960
Speaker 2: maybe it's fine, no big deal, we could work around it.

848
00:40:50,440 --> 00:40:53,440
Speaker 2: But even if they did hold to their moral standards,

849
00:40:54,160 --> 00:40:57,320
Speaker 2: once that technology gets out, once the Pentagon has access

850
00:40:57,400 --> 00:40:59,640
Speaker 2: to it, like you're so cute to think that you're

851
00:40:59,680 --> 00:41:01,480
Speaker 2: going to be the one in charge to be able

852
00:41:01,520 --> 00:41:02,160
Speaker 2: to pull the plug on.

853
00:41:02,320 --> 00:41:04,000
Speaker 1: Yeah, it's always been like that. Is that once you

854
00:41:04,120 --> 00:41:06,719
Speaker 1: unleash the technology, once people get normalized, so we can

855
00:41:06,760 --> 00:41:08,880
Speaker 1: get open source, they can work from it, the government

856
00:41:08,960 --> 00:41:12,080
Speaker 1: can use however they want. This is the big danger

857
00:41:12,640 --> 00:41:16,120
Speaker 1: in all of this for defense technology. And ultimately, like

858
00:41:16,360 --> 00:41:19,080
Speaker 1: maybe you know, it's never really solvable, Like once the

859
00:41:19,160 --> 00:41:21,640
Speaker 1: tech exists, it will always be used for the lowest

860
00:41:21,640 --> 00:41:24,480
Speaker 1: common denominator, Like there's just no really way around it.

861
00:41:24,560 --> 00:41:27,360
Speaker 1: It's basically always been that way war often like blood,

862
00:41:27,480 --> 00:41:30,160
Speaker 1: is that the only thing that moves the wheels of history.

863
00:41:30,560 --> 00:41:33,040
Speaker 1: Let's put G four up there on the screen just

864
00:41:33,080 --> 00:41:36,000
Speaker 1: to give an example here. SpaceX is now going to

865
00:41:36,080 --> 00:41:41,320
Speaker 1: compete in the contest for autonomous drone technology and this

866
00:41:41,840 --> 00:41:46,640
Speaker 1: is the next frontier, you know, drone swarms and competition

867
00:41:46,840 --> 00:41:51,320
Speaker 1: for AI targeting and then who will build the targeting software,

868
00:41:51,320 --> 00:41:53,080
Speaker 1: and there's always one company that's going to be willing

869
00:41:53,120 --> 00:41:55,319
Speaker 1: to play ball and to make money. So there's really

870
00:41:55,360 --> 00:41:58,080
Speaker 1: no way around this. And also there's a competitor aspect.

871
00:41:58,200 --> 00:42:01,720
Speaker 1: China has been heavily invested in drones and drone swarms,

872
00:42:01,760 --> 00:42:04,320
Speaker 1: and it's often been like one of the dangers you know,

873
00:42:04,400 --> 00:42:07,399
Speaker 1: for some of these bigger US carriers and US Navy

874
00:42:07,480 --> 00:42:13,200
Speaker 1: destroyers or US Navy, US Navy vessels, that one of

875
00:42:13,239 --> 00:42:15,239
Speaker 1: the pain points that they see. And so then the

876
00:42:15,400 --> 00:42:17,440
Speaker 1: US says, well, well, now we need to create our

877
00:42:17,520 --> 00:42:20,960
Speaker 1: own drone technology, our own counter drone technology. This is

878
00:42:21,040 --> 00:42:24,520
Speaker 1: the danger, this in this entire thing, and we know this.

879
00:42:24,800 --> 00:42:27,279
Speaker 1: It will be used to some effect. They already used

880
00:42:27,280 --> 00:42:30,040
Speaker 1: Claude with Venezuela. We may be going to a major

881
00:42:30,080 --> 00:42:31,880
Speaker 1: war with Iran. There's going to be a ton of

882
00:42:31,920 --> 00:42:33,120
Speaker 1: AI whenever it comes in.

883
00:42:33,200 --> 00:42:35,960
Speaker 2: And we know how it was deployed in Gaza in

884
00:42:36,120 --> 00:42:38,560
Speaker 2: Palestine and the way it is deployed, you know, also

885
00:42:38,640 --> 00:42:41,680
Speaker 2: in the West Bank and a lot of ways. Gaza

886
00:42:41,880 --> 00:42:46,040
Speaker 2: is the testing ground for mass surveillance. You Palenteer, Microsoft,

887
00:42:46,120 --> 00:42:48,360
Speaker 2: like a bunch of these companies been caught involved in

888
00:42:48,400 --> 00:42:52,000
Speaker 2: the Gaza genocide. And so that has been the testing ground.

889
00:42:52,040 --> 00:42:55,160
Speaker 2: I think that helped you accelerate the incredibly dystopian place

890
00:42:55,239 --> 00:42:56,960
Speaker 2: that we're in. The last thing I'll say I was

891
00:42:57,280 --> 00:42:59,560
Speaker 2: Novar Media had a good, a good piece on this,

892
00:42:59,640 --> 00:43:01,839
Speaker 2: and they were saying, you know, when when scientists were

893
00:43:01,960 --> 00:43:05,160
Speaker 2: building the you know, we're developing nuclear weapons, like you

894
00:43:05,239 --> 00:43:08,799
Speaker 2: know Oppenheimer, they were not so foolish as to think

895
00:43:09,120 --> 00:43:12,719
Speaker 2: that they, as the developers and creators of this technology,

896
00:43:13,000 --> 00:43:14,680
Speaker 2: we're then going to get to tell the government how

897
00:43:14,719 --> 00:43:15,400
Speaker 2: it gets deployed.

898
00:43:15,400 --> 00:43:17,280
Speaker 1: Well, actually Oppenheimer was foolish enough.

899
00:43:17,160 --> 00:43:19,040
Speaker 4: To think that, but a lot of the well take

900
00:43:19,080 --> 00:43:19,279
Speaker 4: it out.

901
00:43:19,400 --> 00:43:20,960
Speaker 2: But I mean he I think he knew at the

902
00:43:21,040 --> 00:43:22,480
Speaker 2: end of the day, the President of the United States

903
00:43:22,560 --> 00:43:24,640
Speaker 2: is going to say how this is used, not me, right,

904
00:43:24,680 --> 00:43:27,279
Speaker 2: and so he made his case. But you know, I

905
00:43:27,320 --> 00:43:29,759
Speaker 2: don't think they they thought that, like, oh, we're going

906
00:43:29,840 --> 00:43:31,839
Speaker 2: to get to control how this is, how and when

907
00:43:31,960 --> 00:43:35,600
Speaker 2: and wherever. Now, many of them organized afterwards to try

908
00:43:35,719 --> 00:43:38,960
Speaker 2: to you know, check nuclear proliferation and try to check

909
00:43:39,000 --> 00:43:41,600
Speaker 2: the use and spread in advance of this technology, but

910
00:43:41,719 --> 00:43:44,120
Speaker 2: there was a much clearer understanding of like, no, we're

911
00:43:44,200 --> 00:43:47,320
Speaker 2: developing this for the US government, and they're going to

912
00:43:47,440 --> 00:43:50,880
Speaker 2: get to have to say over what comes. And I

913
00:43:51,440 --> 00:43:55,160
Speaker 2: you know, because we've lived in this like free market

914
00:43:55,320 --> 00:43:59,120
Speaker 2: capitalists sort of like delusion where government just cedes control

915
00:43:59,640 --> 00:44:02,640
Speaker 2: to listen too markets. I think these guys did delude

916
00:44:02,640 --> 00:44:06,360
Speaker 2: themselves into thinking like we're going to get to figure

917
00:44:06,400 --> 00:44:08,720
Speaker 2: out how this is deployed, and it's like it doesn't

918
00:44:08,800 --> 00:44:11,359
Speaker 2: work that way. So you know, when you did your

919
00:44:11,520 --> 00:44:14,239
Speaker 2: tie up with the Pentagon, and now you want to

920
00:44:14,280 --> 00:44:16,359
Speaker 2: set a moral red line, and I think they did

921
00:44:16,440 --> 00:44:18,799
Speaker 2: have that red line from the beginning. You know, you're

922
00:44:18,840 --> 00:44:20,960
Speaker 2: a fool if you think that they're going to abide

923
00:44:21,200 --> 00:44:23,360
Speaker 2: by what you want. They see themselves as in this

924
00:44:23,560 --> 00:44:25,680
Speaker 2: race with China and they're going to win at all costs,

925
00:44:25,840 --> 00:44:26,960
Speaker 2: at all costs.

926
00:44:27,160 --> 00:44:29,839
Speaker 1: And I'm look, war with Iran. Who knows how it's

927
00:44:29,880 --> 00:44:31,680
Speaker 1: going to go con spiral. It could go into this,

928
00:44:32,280 --> 00:44:33,799
Speaker 1: go into that next thing. You know, these things are

929
00:44:33,800 --> 00:44:36,520
Speaker 1: going to get nationalized, the Defense Production Act, your data

930
00:44:36,560 --> 00:44:38,680
Speaker 1: centers and all that will be seized and be put

931
00:44:38,719 --> 00:44:40,800
Speaker 1: to ford. I mean that can happen like this. You

932
00:44:40,880 --> 00:44:43,799
Speaker 1: know in wartime, go read a book about World War two.

933
00:44:43,920 --> 00:44:47,120
Speaker 1: Look how quickly you went from private industry to literally

934
00:44:47,200 --> 00:44:50,279
Speaker 1: the War production board managing with the Ford Factory is

935
00:44:50,320 --> 00:44:51,600
Speaker 1: plumbing out what you think? They're not going to do

936
00:44:51,680 --> 00:44:54,239
Speaker 1: that with AI and with everything else. If things get

937
00:44:54,280 --> 00:44:57,120
Speaker 1: truly existential, the laws already on the books. They have

938
00:44:57,239 --> 00:45:00,279
Speaker 1: monarchical powers if they want to. You're right, this is

939
00:45:00,320 --> 00:45:03,440
Speaker 1: deeply naive. All right, Thank you guys so much for watching.

940
00:45:03,760 --> 00:45:06,680
Speaker 1: We appreciate it. Please support us if you can. If not,

941
00:45:06,880 --> 00:45:08,480
Speaker 1: Friday show tomorrow. See you all then,