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Speaker 1: Hey, guys, Saga and Crystal here.

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

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

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Speaker 2: the future of the show.

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Speaker 1: This is the only place where you can find honest

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Speaker 1: perspectives from the left and the right that simply does

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

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Speaker 2: all put together for you every morning in your inbox.

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

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

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Speaker 1: dot com. Good morning, everybody, Happy Thursday. We have an

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Speaker 1: amazing show for everybody today, Bro Show. Good to see you,

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Speaker 1: Ryan Sager, all right, Dad's show. Bro Show. That's what

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Speaker 1: people live for.

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Speaker 3: The pound.

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Speaker 1: I gotta get all my god.

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Speaker 3: Shit, the two shirts.

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Speaker 1: Yeah yeah, that's we gotta get the T shirts. All right.

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Speaker 1: So we've got a great show for everybody today. Let's

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Speaker 1: do this the hardest part of the job. What do

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Speaker 1: we have. We're going to start with the shutdown. We

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Speaker 1: are officially some twenty four four forty eight hours something

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Speaker 1: like thirty six hours. All right, we'll go with that.

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Speaker 1: Time is a blur when you know, nobody knows the

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Speaker 1: government infant of home. Yeah, exactly. We have a shutdown

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Speaker 1: that's going on. We're going to break down all the

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Speaker 1: politics for everybody, some of the developments from the Trump administration.

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Speaker 1: We're going to get then to some of the democratic

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Speaker 1: response and some of the internacing warfare about whether the

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Speaker 1: shutdown was a good idea or not. We have a

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Speaker 1: lot of economic news actually to break down. In fact,

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Speaker 1: because the government shut down, some of the key government

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Speaker 1: indicators maybe not be released by the Trump administration, as

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Speaker 1: well as some news on the BLS nominee. That's one

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Speaker 1: of those key data points that the Trump administration had

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Speaker 1: been at war with. They nominated this new guy, and

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Speaker 1: now all of a sudden, with his nomination has been pulled.

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Speaker 1: We are going to talk about Sora. Sora is this

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Speaker 1: new Ryan open AI video generator, deeply dystopian AI.

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Speaker 3: This show is produced by that.

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Speaker 1: Yeah, yeah, I wish it was produced by Story. It'd

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Speaker 1: save us a lot of money, wouldn't it. Although the

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Speaker 1: whole point may be, you know, in terms of what

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Speaker 1: we're giving up, what are we getting for all of this,

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Speaker 1: and in particular the amount of money and power that

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Speaker 1: these data centers which power this AI are consuming. It's astronomical.

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Speaker 1: I know that's high, and even I did not know

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Speaker 1: what the actual numbers were, including in the state where

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Speaker 1: I live. We're also going to talk about Qatar, and

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Speaker 1: it's funny, Ryan, we're very often accused of being Katari

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Speaker 1: assets for being critical of Israel. So I do hope

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Speaker 1: that this block will set the record straight. Donald Trump,

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Speaker 1: out of thin air, created Article five style protections for Qatar,

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Speaker 1: why exactly because Israel attacked them. Seems better to just

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Speaker 1: constrain Israel than just unilaterally grant Article five protection. And also,

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Speaker 1: Steve Wikoff, you know, you and I have been joking

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Speaker 1: in the last twenty four hours. I always kind of

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Speaker 1: thought it was a Zionist talking point that Steve Wikoff

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Speaker 1: is bought by Qatar A little bit point, all right,

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Speaker 1: It's like, you know, listen, if he actually had followed

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Speaker 1: through the ceasefire and a dealer in Gaza, maybe we could.

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Speaker 1: You know, It's like, what's a few billion here between friends.

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Speaker 1: But if we're going to be where we are now

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Speaker 1: and you're going to be straight, you know, in some

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Speaker 1: sketchy dealings. It needs to be called out.

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Speaker 4: And he speaking, you can imagine being guitar, like, we

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Speaker 4: gave this guy billion.

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Speaker 1: Yeah, yeah, we're still getting We're still getting more.

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Speaker 3: It's ridiculous by good assets anymore. Yeah, it's so good.

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Speaker 1: And then finally we're going to talk about TikTok, some

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Speaker 1: of the new pro Israel censorship rolling out across TikTok.

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Speaker 1: And Ryan, you have a TikTok creator who you are

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Speaker 1: friends with, who has been massively surprised in the algorithm.

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Speaker 3: Tell us about him. Yeah, he goes by your favorite guy.

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Speaker 4: He's kind of tutored us over it, drops out a

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Speaker 4: little bit about how to do TikTok because this is

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Speaker 4: a foreign well not only a foreign company, but he

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Speaker 4: kind of used to be foreign in that colloquial sense

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Speaker 4: to old people like me and Sagar, and so he

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Speaker 4: since this new rollout, I think it was September thirteenth

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Speaker 4: or twenty third, we'll get into it with him. These

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Speaker 4: new community guidelines are are presaging the extraordinary amount of

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Speaker 4: censorship that we're going to see interesting on TikTok going forward.

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Speaker 3: So like his politics, don't like his poblics.

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Speaker 4: Whatever he's going to talk to us about out what

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Speaker 4: it's doing for his ability to.

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Speaker 1: Express those totally on this Platfor eah, I don't care

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Speaker 1: what is politics on right, so you know, for me,

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Speaker 1: it's just more interesting about the you know, censorship guidelines

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Speaker 1: and the things that have come into place in some place. Previously,

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Speaker 1: there was a lot of discussion around Israel and particularly

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Speaker 1: really had an effect on youth culture and it's been

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Speaker 1: hit like that at night. So we're very curious to

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Speaker 1: see how that goes. Thank you everybody who's been supporting

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Speaker 1: the show Breakingpoints dot com. If you are able to,

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Speaker 1: If you're not no worries to become a full subscriber,

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Speaker 1: episode to a friend and or rates five stars. It

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Speaker 1: really helps other people find the show. So let's go

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Speaker 1: ahead and start with the shutdown. As you said, the

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Speaker 1: most consequential news is that the White House is telegraphing

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Speaker 1: riffs or reduction in forces of US government employees given

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Speaker 1: their unilateral authority on how to run the government when

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Speaker 1: there is a shutdown. Here is the press structory of

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Speaker 1: Caroline Levitt speak yesterday at a press conference. Let's take

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Speaker 1: a listen.

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Speaker 4: I'm clarify the timing of these potential layoffs to federal workers.

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Speaker 1: You said imminent, the Vice President seemed to.

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Speaker 3: Say in a couple of days.

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Speaker 1: It looks like russ both maybe said in two days.

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Speaker 1: What is when would these layoffs begin two days? Imminent?

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Speaker 1: Very soon?

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Speaker 3: You will expect more announcements.

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Speaker 1: All right, now, is it just not clear or are

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Speaker 1: you waiting?

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Speaker 3: Is it? No, it's not unclear.

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Speaker 5: All of those things are very synonymous with one another.

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Speaker 5: These riffs are unfortunately going to have to happen very soon.

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Speaker 1: Let's fix our policy after the shutdown? Where have I

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Speaker 1: heard that before?

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Speaker 3: Where have I heard that on the other side?

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Speaker 1: Nothing, there's nothing. There's something so beautiful about everybody just

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Speaker 1: switching sides on the shutdown. Republicans shut down the government

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Speaker 1: multiple times. People just tore their hair out over the norms.

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Speaker 1: Now that Democrats are shutting the shutdown, I love it personally,

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Speaker 1: you know, I like to see people be responsive to

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Speaker 1: their partisan bases. But Ryan tell us tell us a

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Speaker 1: little bit your thoughts here in terms of the messaging

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Speaker 1: wars on the shutdown before we get to Schumer.

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Speaker 4: I mean, I think there's there might be something.

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Speaker 3: To that regarding Schumer.

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Speaker 4: I don't know, it's just just AOC threatening to challenge

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Speaker 4: him in a primary. It's it's just generally this sense

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Speaker 4: among Democrats that he is failing at his job and

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Speaker 4: he's not being tough enough.

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Speaker 3: I've heard of him going into.

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Speaker 4: Spaces here in d C where it's all establishment elite

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Speaker 4: type figures and just getting absolute like cold shoulder, yeah,

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Speaker 4: just like oh right, this guy interesting. Like so even

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Speaker 4: like the brass, it's like this, there's a there's a

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Speaker 4: sense that going from Harry Reid and Nancy Pelosi some

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Speaker 4: some real ballers to Chuck Schumer and Hakeem Jeffries is

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Speaker 4: a is a massive step down.

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Speaker 3: And like talent and stress.

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Speaker 4: That's subjectively, it's objectively, but even the establishment like understands that.

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Speaker 1: Yeah, but I'll save some of my commentary. But isn't

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Speaker 1: that kind of their fault? Like they're the ones who

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Speaker 1: wanted people who were more agreeable and more old tested.

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Speaker 3: I mean, they voted for right, they voted for these guys.

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Speaker 1: They supported their cannon.

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Speaker 4: Read, you know, and read helped the Usher and Schumer

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Speaker 4: and Pelosi helped up.

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Speaker 3: That's in Jefferys.

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Speaker 4: Yeah, he's really AOC's fault for knocking Joe Crowley out

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Speaker 4: that he'd be the House speaker right now.

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Speaker 1: So it's actually deeply funny to you consider all of that.

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Speaker 1: All right, let's get to Chuck Schumer his own response

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Speaker 1: from the framing coming out of the House leadership or

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Speaker 1: the House and Senate leadership from the Democrats.

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Speaker 6: Let's take a listen what happens on Friday night when

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Speaker 6: the family sits around the kitchen table and says, how

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Speaker 6: are we going to pay the bills? When they see

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Speaker 6: that their insurance could be one thousand dollars more a month,

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Speaker 6: health insurance vital to the parents, the children.

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Speaker 3: Of the family.

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Speaker 6: What are they going to do? The average American can't

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Speaker 6: afford one thousand dollars a month, or even four hundred

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Speaker 6: dollars a month.

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Speaker 3: The average Americans could.

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Speaker 6: Say, what the heck happened here? And we Democrats are

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Speaker 6: going to be there every day every Senate House groups

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Speaker 6: that care about healthcare, hospital groups, healthcare groups, research groups,

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Speaker 6: and letting them know this didn't have to happen. It

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Speaker 6: happened because our Republican colleagues wanted to give tax breaks

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Speaker 6: to billionaires and cut their healthcare.

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Speaker 1: So Ryan, they are going all in on the healthcare message.

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Speaker 1: We've talked about it here quite a bit with Crystal.

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Speaker 1: It does obviously, it's the most poll tested. I mean,

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Speaker 1: it'sture not even legitimate is a deeply important issue. Obamacare subscribers,

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Speaker 1: you too, You're like, I'm just way yeah, I'm like yeah,

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Speaker 1: you know, maybe it's like a sly thing where I'm like, yeah,

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Speaker 1: it wouldn't be so bad. You know, they got what

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Speaker 1: they wanted to be nice, especially you know with the

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Speaker 1: with the new addition here into our family Plan. The

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Speaker 1: question around it is is this going to satisfy the

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Speaker 1: Democratic base for some of the stuff that they want

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Speaker 1: to stop Trump on. It's not really about healthcare, let's

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Speaker 1: be honest. They just want, you know, kind of throw

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Speaker 1: wrench in the government. And then the secondary question is

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Speaker 1: can the Democrats withstand what the Trump administration is going

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Speaker 1: to do. So, for example, let's put a four up

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Speaker 1: here on the screen. I'll get your reaction. Russ vote,

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Speaker 1: who is the OMB director says quote, roughly eighteen billion

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Speaker 1: in New York City infrastructure projects that have now been

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Speaker 1: put on hold to ensure funding is not flowing based

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Speaker 1: on quote unconstitutional DEI principles more infos who come from

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Speaker 1: the US dot he specifically there was talking about New

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Speaker 1: York City, what is it, the Second Avenue subway line,

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Speaker 1: as well as another infrastructure project that is currently being

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Speaker 1: funded by the government. And so you see the direct

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Speaker 1: targeting here of New York City, and I can combine

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Speaker 1: it here, yeah with a five just so you can

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Speaker 1: tell us a little bit about some of the states

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Speaker 1: nearly eight billion in green quote green new scam funding

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Speaker 1: to feel the left crimeate agenda is being canceled. Projects

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Speaker 1: are in the following state California, Colorado, Connecticut, Delaware, Hawaii, Illinois, Maryland, Massachusetts, Minnesota,

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Speaker 1: New Hampshire, New Jersey, New Mexico, New York, Oregon, Vermont, Washington.

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Speaker 1: For the life of me, Ryan.

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Speaker 3: Pop Quiz, I love class. What connects all of those states?

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Speaker 1: You know, For the life of me, I cannot figure

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Speaker 1: out what is in common with all these states.

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Speaker 3: They have capitals that have three syllables.

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Speaker 1: There, you go, right, that's got to be it, right,

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Speaker 1: Not that they all voted for Democrats and oh yeah, that's.

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Speaker 3: So yeah.

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Speaker 1: I mean, what do you think about the way that

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Speaker 1: these establishment Dems are going to handle this, right, because

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Speaker 1: they already lost a couple in terms of the vote,

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Speaker 1: So how many do they actually need?

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Speaker 3: Many?

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Speaker 1: Like seven de.

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Speaker 3: Votment they need three more, sorry.

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Speaker 1: Three more, they need three more to come along with them.

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Speaker 1: You've got the government New York City obviously being targeted

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Speaker 1: because of Chuck Schumer the rest of the Democratic States

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Speaker 1: to put a lot of pressure there on the senators

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Speaker 1: of course, reduction and force. You got Democrats have a

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Speaker 1: lot of veterans for the government like itself, for the bureaucrats.

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Speaker 1: Are they really going to sit by and allow, you know,

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Speaker 1: tens of thousands, hundreds of thousands to be fired and

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Speaker 1: eventually cave I don't know. I mean that almost seems

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Speaker 1: worse to me from a Democratic base perspective. So what's

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Speaker 1: your read currently on the situation?

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Speaker 3: Right?

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Speaker 4: And I think we can put up a six as well,

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Speaker 4: because this goes to its reporting from Capitol Hill saying

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Speaker 4: that a gang of moderates in both parties they're starting.

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Speaker 3: The old old, the age old gang process in search

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Speaker 3: of a deal. Center on ACA subodies.

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Speaker 4: What this means basically is that you'll get enough Democrats

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Speaker 4: sitting down in a room with enough Republicans that if

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Speaker 4: they all agree, they can no matter what the leaderships

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Speaker 4: want to do, they can they can break the log jam.

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Speaker 4: And so I think this is where it heads because

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Speaker 4: from Democrats perspective, the base and Schumer, they just want

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Speaker 4: to show that they put up a fight, and now

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Speaker 4: they've kind of showed that, and if they can get something,

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Speaker 4: then they can move on and say we're going to

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Speaker 4: fight fight on this another day. Schumer's strategy here is

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Speaker 4: very clear, and I get it like he's in January,

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Speaker 4: you and I'm talking about all of you, particularly Sager,

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Speaker 4: are going to you know, get hit with the if

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Speaker 4: you're on the exchanges, which is about twenty million people, Yes,

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Speaker 4: the subsets go away and boom, all of a sudden,

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Speaker 4: your affordable payment for the Affordable Care Act is now

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Speaker 4: deeply affordable, by the way, but it's more affordable, yes,

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Speaker 4: than when they strip the subsidies away. And Democrats want

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Speaker 4: the public to know why that happened. And they're hoping

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Speaker 4: that this big storm that they're creating now will then

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Speaker 4: remind people. Okay, so they're hoping I think that they

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Speaker 4: may make enough of a storm. And then once you've

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Speaker 4: done that, you've kind of scratched all the different itches.

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Speaker 4: You still have this fundamental philosophical question that actually speaking

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Speaker 4: of AOC goes back to her debate with Joe Crowley,

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Speaker 4: where she had gotten Crowley to say that ICE is fascist,

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Speaker 4: and then she'd be like, but then why would you

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Speaker 4: vote to fund a fascist agency? Which you it's like

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Speaker 4: when that's why a lot of politicians don't want to

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Speaker 4: call what's happening in Gaza genocide because once you call

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Speaker 4: it a genocide, fund on what planet can you fund

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Speaker 4: a gend And what planet can you fund a fascist agency?

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Speaker 4: So Democrats have said, this is an authoritarian crackdown. You know,

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Speaker 4: this is the end of the American Republic. Oh, and

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Speaker 4: here we're going to fund it.

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Speaker 3: That is just it.

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Speaker 1: That's what they did earlier, right, So I get killed,

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Speaker 1: So they have to do something right. But then doesn't

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Speaker 1: it seem as if shutting it down for messaging purposes

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Speaker 1: only to cave in a couple of days, isn't that worse? Right?

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Speaker 1: And how would Schumer and Jeffries and them handle it?

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Speaker 1: So again, to explain just a little bit to people,

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Speaker 1: the House bills already passed, right, you only need a

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Speaker 1: couple of Senators to buckle and to just vote for

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Speaker 1: the quote clean CR whatever to go through, and then

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Speaker 1: you're done. And so the majority of the Democrats could

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Speaker 1: stand against the bill, but if a couple of the

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Speaker 1: quote moderates due, well you still lost. And that's going

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Speaker 1: to affect the national Party at a make level.

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Speaker 4: And maybe they get it, and it'll be interesting to

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Speaker 4: see how they work the details out, because yeah, you

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Speaker 4: can make a deal around the subsidies, pass the clean

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Speaker 4: CR and then try to implement it in the next thing.

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Speaker 4: Then you're at the whim of Republicans again, right, and

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Speaker 4: really you have to get it passed, But then then

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Speaker 4: Johnson and Republicans in the House would have to then

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Speaker 4: agree to it, which goes back to a question I've

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Speaker 4: been wondering from the GOP perspective, why fight this? Actually, well,

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Speaker 4: like they don't care about deficits anymore, but why not

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Speaker 4: just say, okay, fine, you know what, this subsidies going

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Speaker 4: away would suck for us in an election here anyway, Fine,

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Speaker 4: keep them?

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Speaker 1: Yeah, you know, because I wonder how much of this

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Speaker 1: is about healthcare and how much is it about the

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Speaker 1: executive just basically doing backflips on Hey, we've been wanting this.

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Speaker 1: They're like, we want the O and B director, for example.

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Speaker 1: I can read this just this morning. There's a new

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Speaker 1: Trump truth quote. I have a meeting today with RUSS

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Speaker 1: vote of Project twenty twenty five fame to determine which which.

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Speaker 1: By the way, hilarious because now now project plainting.

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Speaker 3: Because he said, yeah, nothing to do with productly doing five.

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Speaker 1: I will fire anybody who has anything to do with

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Speaker 1: Project twenty five anyway, whatever. Project to determine which of

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Speaker 1: the many democratic agencies, most of which are a political

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Speaker 1: scam he recommends to be cut, and whether or not

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Speaker 1: those cuts will be temporary or permanent. I can't believe

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Speaker 1: the radical left Democrats gave me this unprecedented opportunity. They

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Speaker 1: are not stupid people, so maybe this is their way

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Speaker 1: of wanting to quietly quickly make America great again. I mean,

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Speaker 1: he's kind of correct, right in terms of they knew

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Speaker 1: that this was the likely outcome. The Democratic response I

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Speaker 1: have seen is if you look at russ votes tweet

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Speaker 1: on New York City, it has nothing to do with

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Speaker 1: the shutdown. He said it was about DEI so The

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Speaker 1: point that I've seen the base and them make is guys,

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Speaker 1: they're going to cut funding whether they whether there's a

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Speaker 1: shutdown or not, So who cares? Why should we buckle

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Speaker 1: to this? I just personally think that they can't sit

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Speaker 1: by for that long and let the government just cut

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Speaker 1: whatever agency or whatever people put entirely on furlough. In particular,

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Speaker 1: if you see a straight up targeting of all democratic

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Speaker 1: states and of their funding, how long are they really

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Speaker 1: going to go with it before some mealy mouth you know,

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Speaker 1: New Nevada Democrat is going to becoming in voting for

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Speaker 1: the CR. I could I just I could see that

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Speaker 1: happening very quickly.

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Speaker 3: It could, Yeah, it could for sure.

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Speaker 4: But yes, like Democrats also do have that point that

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Speaker 4: like Russ votes to do this stuff anyway, right, so

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Speaker 4: the threats and that he's probably gonna do more.

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Speaker 3: Was it shutdown?

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Speaker 4: But yeah, Democrats was what you know, when you lose power,

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Speaker 4: you're left with like that and even worse.

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Speaker 1: Elections consequences as Obama. As Obama famously said, I do

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Speaker 1: wonder here with the shutdown again, you know how the

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Speaker 1: Democratic base is feeling is because something that is mystifying

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Speaker 1: to me is if you recall in twenty thirteen, the

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Speaker 1: shutdown was the biggest story in the world. It was everywhere,

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Speaker 1: especially I was living. I was going to college here

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Speaker 1: in Washington. But the Obama administration made sure that you

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Speaker 1: knew about the shutdown, like they had some I remember,

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Speaker 1: you know, even in the place that I would walk sometimes,

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Speaker 1: which is near my university was technically National Park Grounds,

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Speaker 1: and there was a big sign over and it was like,

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Speaker 1: this place is shut You could still walk there, but

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Speaker 1: it's like it's shut down because of the shutdown. The

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Speaker 1: Trump administration is doing some of that, but the Republicans

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Speaker 1: also their full media, you know, Fox News, the radio stations,

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Speaker 1: everybody was mobilized. This seems weirdly like a low key shutdown,

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Speaker 1: almost like do the Democratic base feel the responsiveness here,

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Speaker 1: because I haven't seen that quite yet in terms of

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Speaker 1: their media, in terms of maybe like their feeling as

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Speaker 1: if they're being responded to, and that that feels relevant

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Speaker 1: as we transition to the next part about how the

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Speaker 1: Democrats themselves are kind of handling the shutdown.

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Speaker 4: Yeah, and while you were in college, I was actually

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Speaker 4: on pool duty with Obama.

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Speaker 3: Oh wow, that was going on.

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Speaker 4: I remember sprinting up the Lincoln Memorial Steps. Because he

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Speaker 4: went up and did an event at the very top

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Speaker 4: of the Lincoln Memorial Steps, I beat all the rest

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Speaker 4: of the poll reporters totally out of shape.

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Speaker 1: That's a good feeling.

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Speaker 4: Yes, and Obama was in much better shape than all

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Speaker 4: of us, yes combined.

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Speaker 3: And yeah, it was a huge deal.

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Speaker 4: I think that there's a boredom with twenty years at

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Speaker 4: this point almost of Washington doing shut down drama, fiscal

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Speaker 4: cliff drama, the debt sealing drama, super committees like.

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Speaker 3: And it all adds up to just blips for people, Like.

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Speaker 4: There's a there's you know, some for hundreds of thousands

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Speaker 4: of like individuals who work for the federal government, certainly

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Speaker 4: it's impactful. But for the three hundred plus million people

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Speaker 4: in the country, like, we're just kind of kind of

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Speaker 4: bored of like all of this. But that is a

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Speaker 4: recipe oftentimes for catastrophe, because eventually.

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Speaker 3: The wolf does show up.

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Speaker 4: Yeah, even if you have been crying wolf right a while,

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Speaker 4: people kind of learn the wrong lesson from that fairy

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Speaker 4: tale sometimes like or whatever you would call it. It's like, yes,

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Speaker 4: you shouldn't cry wolf. But also there are wolves.

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Speaker 1: This is again kind of to the messaging battle is again, look,

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Speaker 1: I'm biased, so it's my own person, but I mean,

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Speaker 1: you have to be honest. Like the way that the

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Speaker 1: Trump administration has been handling this, even if you hate

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Speaker 1: the way they're doing it, it's effective. Like every government

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Speaker 1: agency if you go to their website, has a thing

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Speaker 1: at the top. It's like the Democrats, the radical left

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Speaker 1: Democrats shut down the government.

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Speaker 3: They figured out they don't have to follow the law.

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Speaker 3: Who cares righttically, what are they going to do?

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Speaker 1: You're gonna assume over the hat Hatch Act violation or whatever?

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Speaker 1: Good luck? Right? You know, it seems like quaint in

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Speaker 1: our current politics, and from the Democratic side, like we

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Speaker 1: have Hakim Jefferys, we have Chuck Schumer, it just to

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Speaker 1: me is lame, like the way that it just doesn't

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Speaker 1: seem legitimate. It doesn't seem as if they really believe

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Speaker 1: in the fight. And especially when you have multiple Democratic

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Speaker 1: senators who already kind of voted for it, You're like, Okay,

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Speaker 1: what are we really doing here? And so our team

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Speaker 1: helped me decipher this new TikTok democratic meme that was

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Speaker 1: posted by the Democratic Party of a kitty explaining the

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Speaker 1: government shutdown. Let's take a Listenpublican.

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Speaker 7: And Democrat kitties cannot agree on what should be funded.

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Speaker 7: Democrat kitties want you to have health care. Republican kitties

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Speaker 7: do not. Republican kitties control the Senate, House and the

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Speaker 7: White House, so they're using the had to cut your

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Speaker 7: health care.

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Speaker 3: And give money to billionaires.

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Speaker 7: Democrat kitty tries to negotiate, but Republican kitty keeps running away.

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Speaker 1: He has a vacation to get to.

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Speaker 7: Uh oh, suddenly the money you pay for your health

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Speaker 7: insurance has tripled, thanks Republicans.

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Speaker 1: Our Our gen Z Staffer tells us that usually this

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Speaker 1: meme is about kitty explains boyfriend to girlfriend and not

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Speaker 1: technically about the government shutdown. I don't know about this.

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Speaker 1: I mean, look, maybe the point about unified government is

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Speaker 1: always one that does hit with the American people, right

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Speaker 1: is they're like, hey, you have the House, the Senate

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Speaker 1: and the White House, and so you guys still can't

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Speaker 1: fund the government. It's like, well, you know, there is

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Speaker 1: the filibuster, which you know, the Republicans still, I guess

436
00:20:39,720 --> 00:20:42,639
Speaker 1: do believe in both kind of bases. Probably would be fine.

437
00:20:42,760 --> 00:20:44,879
Speaker 1: With nuking the filibuster. So technically, you know, if they

438
00:20:44,920 --> 00:20:47,360
Speaker 1: really wanted to, they could nuke the philibuster and then

439
00:20:47,400 --> 00:20:50,080
Speaker 1: they could just fund the government. But that doesn't seem

440
00:20:50,160 --> 00:20:52,840
Speaker 1: like something that they want to do. But more broadly,

441
00:20:52,920 --> 00:20:55,920
Speaker 1: Ryan this kind of gets to the shutdown wars and

442
00:20:55,960 --> 00:21:00,200
Speaker 1: some more establishment voices in DC voicing against Democrat to

443
00:21:00,240 --> 00:21:02,880
Speaker 1: embrace of the shutdown. Let's put a eight please up

444
00:21:02,880 --> 00:21:05,320
Speaker 1: on the screen. I'm very curious for what you think.

445
00:21:05,359 --> 00:21:08,000
Speaker 1: So Washington Post editorial board, you know, one of the

446
00:21:08,000 --> 00:21:11,800
Speaker 1: classic people used to care but nobody really cares a

447
00:21:11,800 --> 00:21:14,840
Speaker 1: lot more still has some voice in Washington quote the

448
00:21:14,880 --> 00:21:19,360
Speaker 1: Democrats marched into a shutdown trap, they say, Progressive Democrats

449
00:21:19,600 --> 00:21:22,600
Speaker 1: like the Freedom Caucus are urging their party in a

450
00:21:22,680 --> 00:21:25,840
Speaker 1: dangerous direction. And so what they say is that the

451
00:21:25,840 --> 00:21:29,080
Speaker 1: Democratic Party shut off any potential escape valve to avoid

452
00:21:29,119 --> 00:21:33,160
Speaker 1: a shutdown. In doing so, progressives embrace the same disastrous

453
00:21:33,160 --> 00:21:36,240
Speaker 1: mentality that led the House Freedom Caucus to believe it

454
00:21:36,240 --> 00:21:39,240
Speaker 1: could come out ahead in previous government funding shutdowns. They

455
00:21:39,440 --> 00:21:42,880
Speaker 1: strongly assumed, they wrongly assume their political leverage would withstand

456
00:21:42,920 --> 00:21:46,159
Speaker 1: the ensuing fallout. Left wing democrats like the Freedom Caucus

457
00:21:46,240 --> 00:21:48,879
Speaker 1: before them enter the shutdown in a position of weakness,

458
00:21:48,960 --> 00:21:50,919
Speaker 1: they point to the Trump administration saying that they're going

459
00:21:51,000 --> 00:21:54,480
Speaker 1: to do whatever they want. And they also point specifically

460
00:21:54,520 --> 00:21:58,439
Speaker 1: to how, in their telling, the previous Republican shutdowns quote

461
00:21:58,480 --> 00:22:02,240
Speaker 1: failed to achieve Republican goals every time. Do you think

462
00:22:02,280 --> 00:22:04,080
Speaker 1: that that's true or not? Because I don't think it's

463
00:22:04,119 --> 00:22:06,720
Speaker 1: necessarily true that the Freedom cack Is Act didn't achieve

464
00:22:06,720 --> 00:22:09,520
Speaker 1: they didn't achieve their goals. I think they vastly achieved

465
00:22:09,520 --> 00:22:10,520
Speaker 1: their goals in.

466
00:22:10,440 --> 00:22:11,960
Speaker 3: A significant way. They achieved their goals.

467
00:22:12,400 --> 00:22:16,320
Speaker 4: Yeah, particularly when it comes to leveling off government spending

468
00:22:16,359 --> 00:22:23,720
Speaker 4: starting in like after twenty eleven, which actually slowed the recovery.

469
00:22:24,080 --> 00:22:26,840
Speaker 4: They had sequestration, it got sequestration out of it. And

470
00:22:26,880 --> 00:22:31,760
Speaker 4: I think without that, they don't win the Senate in

471
00:22:31,800 --> 00:22:34,520
Speaker 4: twenty fourteen. And if you don't win the Senate in

472
00:22:34,560 --> 00:22:38,000
Speaker 4: twenty fourteen, Merret Garland is a Supreme Court justice, and

473
00:22:38,080 --> 00:22:42,080
Speaker 4: our entire world looks different than it does now. So

474
00:22:42,320 --> 00:22:45,080
Speaker 4: and I think without actually without what the Freedom cauc

475
00:22:45,200 --> 00:22:48,320
Speaker 4: Is accomplished in slowing the economy and then slowing the

476
00:22:48,320 --> 00:22:51,080
Speaker 4: recovery in those four or five years, you don't even

477
00:22:51,080 --> 00:22:53,840
Speaker 4: get Trump winning in twenty sixteen because it was such

478
00:22:53,840 --> 00:22:56,760
Speaker 4: a close election and people were frustrated at the very

479
00:22:56,800 --> 00:23:00,720
Speaker 4: slow recovery from the financial crisis. So you know, they

480
00:23:00,800 --> 00:23:02,800
Speaker 4: actually got there. They got they didn't get everything they

481
00:23:02,800 --> 00:23:05,080
Speaker 4: wanted by any remote stretch of the imagination, and we

482
00:23:05,160 --> 00:23:07,320
Speaker 4: now have what thirty plus trillion dollars in debt, So

483
00:23:07,440 --> 00:23:10,160
Speaker 4: like from their perspective, they were like, well, we totally failed,

484
00:23:10,160 --> 00:23:15,920
Speaker 4: but you know it's marginally. They actually did bring about

485
00:23:16,040 --> 00:23:19,199
Speaker 4: four or five years of austerity with a Democrat in

486
00:23:19,240 --> 00:23:21,320
Speaker 4: the White House, which was to their political benefit.

487
00:23:21,359 --> 00:23:22,879
Speaker 1: And I would flip it too and say, did they

488
00:23:22,880 --> 00:23:25,919
Speaker 1: really care about austerity? Obviously not. What they cared about

489
00:23:26,000 --> 00:23:28,640
Speaker 1: was the exercise of power in and of itself, right,

490
00:23:28,680 --> 00:23:30,960
Speaker 1: And what they showed is that some fifteen to thirty

491
00:23:31,000 --> 00:23:35,000
Speaker 1: people actually could wield immense amounts of power relative to

492
00:23:35,160 --> 00:23:37,399
Speaker 1: everybody else in the government. It's almost like a tyranny

493
00:23:37,440 --> 00:23:39,719
Speaker 1: of the minority part where as long as you're together

494
00:23:40,040 --> 00:23:41,959
Speaker 1: in lockstep, that the rest of the group is going

495
00:23:42,000 --> 00:23:45,240
Speaker 1: to have to adapt itself to whoever you are. This

496
00:23:45,359 --> 00:23:48,000
Speaker 1: is part of the problem though with the Democratic Party. Again,

497
00:23:48,040 --> 00:23:50,520
Speaker 1: I think, in my opinion, is that by kind of

498
00:23:50,680 --> 00:23:54,120
Speaker 1: lamely talking about ACA. And again, I don't even think

499
00:23:54,160 --> 00:23:57,280
Speaker 1: really authentically, because the truth is is that the Democrats

500
00:23:57,359 --> 00:23:58,080
Speaker 1: just wanted to shut down.

501
00:23:58,119 --> 00:23:58,439
Speaker 3: Period.

502
00:23:58,480 --> 00:24:01,200
Speaker 1: Like if you listen and they cite from Greg Sasar

503
00:24:01,320 --> 00:24:03,639
Speaker 1: and others, they're like, it's not about ACA. Okay. They

504
00:24:03,680 --> 00:24:05,280
Speaker 1: were like, we hate Trump. They're like, well, we think

505
00:24:05,320 --> 00:24:08,000
Speaker 1: what Trump is so horrible. We're not going to fund it, period, Right,

506
00:24:08,000 --> 00:24:10,680
Speaker 1: We're going to make his life hell. It's a question

507
00:24:10,760 --> 00:24:12,480
Speaker 1: mark of whether they are making their life hell, but

508
00:24:12,720 --> 00:24:14,320
Speaker 1: it's the only thing that we have, so we might

509
00:24:14,359 --> 00:24:16,399
Speaker 1: as well do it. And I think that that has

510
00:24:16,440 --> 00:24:20,000
Speaker 1: a lot of currency. But without any uptick and constant

511
00:24:20,000 --> 00:24:21,879
Speaker 1: browbie of a lot of the people who are the

512
00:24:21,920 --> 00:24:25,400
Speaker 1: Democratic Party faithful accepting that message, then you do kind

513
00:24:25,400 --> 00:24:28,159
Speaker 1: of find yourself in a weird position where if you

514
00:24:28,160 --> 00:24:31,480
Speaker 1: look at Chuck Schumer, he's not taking what I originally

515
00:24:31,560 --> 00:24:33,800
Speaker 1: said the smartest thing Mitch McConnell ever said in two

516
00:24:33,800 --> 00:24:35,880
Speaker 1: thousand and nine was our job is just make sure

517
00:24:35,880 --> 00:24:38,119
Speaker 1: the president doesn't get reelected no period. All right. I

518
00:24:38,200 --> 00:24:39,719
Speaker 1: was like, they were like, oh, we are you going

519
00:24:39,760 --> 00:24:41,520
Speaker 1: to work with Obama? He's like no, He's like that's

520
00:24:41,600 --> 00:24:44,480
Speaker 1: we have one job make sure that he does not succeed,

521
00:24:44,680 --> 00:24:48,000
Speaker 1: period and everyone was shocked by that. It was actually

522
00:24:48,000 --> 00:24:50,840
Speaker 1: the most honest thing a politician has said in years,

523
00:24:50,920 --> 00:24:53,240
Speaker 1: because he's like, yoh, you think we're going to negotiating

524
00:24:53,280 --> 00:24:55,960
Speaker 1: good faith. Absolutely not. He's like, we're here to make

525
00:24:56,119 --> 00:24:59,479
Speaker 1: to make shit miserable for Obama. And he succeeded one

526
00:24:59,560 --> 00:25:02,840
Speaker 1: hundred percent. So the point is, though on the Democratic side,

527
00:25:02,920 --> 00:25:05,000
Speaker 1: you don't see that level of fight and of energy.

528
00:25:05,200 --> 00:25:08,760
Speaker 1: And look, McConnell became hated many years later, but he

529
00:25:08,880 --> 00:25:12,440
Speaker 1: was a hero, right, He was a absolute Tea Party

530
00:25:12,680 --> 00:25:15,919
Speaker 1: Freedom Caucus hero there for some time. Obviously there were

531
00:25:15,960 --> 00:25:18,560
Speaker 1: a lot of fights in particular, but Paul Ryan became

532
00:25:18,760 --> 00:25:20,959
Speaker 1: the House Speaker as a result of this, and he

533
00:25:21,000 --> 00:25:23,639
Speaker 1: was seen as a credible person who could replace Bayner.

534
00:25:23,720 --> 00:25:26,320
Speaker 1: So like to me, that's where no, the shutdown politics

535
00:25:26,320 --> 00:25:29,760
Speaker 1: actually did work in terms of look at the Republican

536
00:25:29,840 --> 00:25:32,800
Speaker 1: stars of that period. Every single one of them remains

537
00:25:32,800 --> 00:25:35,720
Speaker 1: prominent to today. Ted Cruz, you could say a lot. Yes,

538
00:25:35,720 --> 00:25:39,119
Speaker 1: he failed to achieve the Republican nomination. He came in second. Okay,

539
00:25:39,400 --> 00:25:41,639
Speaker 1: you know he got second in the Republican primary in

540
00:25:41,640 --> 00:25:44,119
Speaker 1: twenty sixteen. That's nothing to sneeze at, like he had

541
00:25:44,119 --> 00:25:47,560
Speaker 1: a real popular currency for If you're a Democrat and

542
00:25:47,600 --> 00:25:49,879
Speaker 1: you want to be taken seriously, you do need to

543
00:25:49,920 --> 00:25:52,040
Speaker 1: mount like a credible fight against Trump if that's where

544
00:25:52,040 --> 00:25:54,320
Speaker 1: your party base is. So that's where I feel like

545
00:25:54,320 --> 00:25:57,280
Speaker 1: the Washington Post is almost being too cute by saying

546
00:25:57,359 --> 00:25:59,640
Speaker 1: their actual political ends. Their political ends are not about

547
00:25:59,640 --> 00:26:01,840
Speaker 1: the ACA. That's probably not going to I mean, maybe

548
00:26:01,840 --> 00:26:03,760
Speaker 1: it will be. You know, it'd be great for me

549
00:26:03,800 --> 00:26:06,840
Speaker 1: if it did, and for everybody else, But I don't

550
00:26:06,840 --> 00:26:09,000
Speaker 1: think that that's the ultimate point of the shutdown itself.

551
00:26:09,320 --> 00:26:13,080
Speaker 1: And that's why I've seen some more establishment liberals and

552
00:26:13,160 --> 00:26:15,200
Speaker 1: others being like, Guys, this is a bad idea. Trump

553
00:26:15,240 --> 00:26:16,879
Speaker 1: is just going to use it as an excuse, And

554
00:26:16,880 --> 00:26:18,760
Speaker 1: it's like, yeah, but you're doing that anyway, right, so

555
00:26:19,000 --> 00:26:21,040
Speaker 1: why not? It just seems like a hail Mary approach

556
00:26:21,280 --> 00:26:23,280
Speaker 1: to government. But I know you have some more mixed

557
00:26:23,280 --> 00:26:23,880
Speaker 1: thoughts on show.

558
00:26:23,920 --> 00:26:25,640
Speaker 3: No, No, I think that's I think that's about right.

559
00:26:26,119 --> 00:26:28,040
Speaker 4: The one final point I would have on this is

560
00:26:28,040 --> 00:26:31,000
Speaker 4: that I was talking to somebody last night who spends

561
00:26:31,040 --> 00:26:32,440
Speaker 4: a lot of time in China and they were telling

562
00:26:32,440 --> 00:26:36,439
Speaker 4: me about all the different projects that they've got going on,

563
00:26:36,560 --> 00:26:37,600
Speaker 4: trying to figure out.

564
00:26:38,400 --> 00:26:40,600
Speaker 3: Ways to like repurpose like waste.

565
00:26:40,280 --> 00:26:43,720
Speaker 4: Removal and all that, like confronting all of the difficult

566
00:26:43,960 --> 00:26:49,119
Speaker 4: challenges of contemporary life and trying to like move forward

567
00:26:49,160 --> 00:26:52,399
Speaker 4: in ways that can like make everybody's life better. And

568
00:26:52,440 --> 00:26:55,200
Speaker 4: it just reminded me of like just how existentially kind

569
00:26:55,200 --> 00:26:57,919
Speaker 4: of dead and boring our own politics is.

570
00:26:59,160 --> 00:27:02,280
Speaker 3: What do we do? Like are we going to keep

571
00:27:02,280 --> 00:27:03,080
Speaker 3: the government open or out?

572
00:27:03,400 --> 00:27:07,320
Speaker 4: And why is there any effort by any party to

573
00:27:07,520 --> 00:27:12,600
Speaker 4: actually grapple with the problems that are confronting contemporary society.

574
00:27:13,680 --> 00:27:14,399
Speaker 3: I don't see it.

575
00:27:14,520 --> 00:27:15,400
Speaker 1: No, I don't see it either.

576
00:27:15,720 --> 00:27:16,919
Speaker 3: I mean, we're going to talk what do we do?

577
00:27:17,040 --> 00:27:18,560
Speaker 1: Like what we're gonna talk in our store block about

578
00:27:18,560 --> 00:27:21,639
Speaker 1: these data centers, rising electricity prices. Everyone's like, oh, I

579
00:27:21,880 --> 00:27:23,440
Speaker 1: just got to take it.

580
00:27:23,440 --> 00:27:27,120
Speaker 4: It just feels it just feels like a hollow death

581
00:27:27,160 --> 00:27:30,639
Speaker 4: spiral and here we are just like riding it on

582
00:27:30,720 --> 00:27:31,280
Speaker 4: the way down.

583
00:27:31,720 --> 00:27:33,440
Speaker 1: It's like inspiring.

584
00:27:33,960 --> 00:27:36,000
Speaker 3: Is it good that they do as bad as? I

585
00:27:36,040 --> 00:27:37,680
Speaker 3: don't know, we're all just circling the drain.

586
00:27:38,000 --> 00:27:40,639
Speaker 1: Uh, I'm with you, right? If Chinese century it is,

587
00:27:41,400 --> 00:27:46,119
Speaker 1: you might as well embrace it. Okay, let's go ahead

588
00:27:46,119 --> 00:27:49,280
Speaker 1: to the next part here on the economy. As you

589
00:27:49,359 --> 00:27:51,480
Speaker 1: were saying about death spirals and all that, we may

590
00:27:51,520 --> 00:27:53,760
Speaker 1: not even know if we're in a death spiral apparently,

591
00:27:53,800 --> 00:27:55,600
Speaker 1: So let's go and put this up here on the

592
00:27:55,600 --> 00:27:58,720
Speaker 1: screen about some of the key economic data that will

593
00:27:58,720 --> 00:28:02,120
Speaker 1: be suspended during a government cut down. The jobless claims

594
00:28:02,160 --> 00:28:05,359
Speaker 1: from the Labor Department will likely not be released. Non

595
00:28:05,440 --> 00:28:08,040
Speaker 1: farm payrolls by the BLS will not be released. The

596
00:28:08,080 --> 00:28:10,639
Speaker 1: CPI and the PPI, the consumer Price Index and the

597
00:28:11,080 --> 00:28:14,520
Speaker 1: pursuit of producer price intexs key inflation indicators from the

598
00:28:14,520 --> 00:28:17,800
Speaker 1: BLS will likely not be released. Retail sales, factory orders,

599
00:28:17,920 --> 00:28:20,679
Speaker 1: housing starts, trade data from the Census and the Bureau

600
00:28:20,680 --> 00:28:24,560
Speaker 1: of Economic Affairs, the Employment Trends Index from the Conference Board,

601
00:28:24,760 --> 00:28:28,239
Speaker 1: the GDP data, new home sales and construction permits from

602
00:28:28,280 --> 00:28:31,560
Speaker 1: the Census Bureau, export and import trade data from Census

603
00:28:31,560 --> 00:28:34,760
Speaker 1: and Commerce. And they say, quote, the next FED meeting

604
00:28:34,840 --> 00:28:37,600
Speaker 1: is four weeks away. We're entering at data freeze. So

605
00:28:37,720 --> 00:28:40,840
Speaker 1: historically the FED would shift more dubvish on average during

606
00:28:41,000 --> 00:28:43,880
Speaker 1: US government shutdown, which maybe that might be a blessing

607
00:28:43,920 --> 00:28:47,040
Speaker 1: in disguise, right, the FED would become a little bit

608
00:28:47,120 --> 00:28:47,880
Speaker 1: more dubbish.

609
00:28:47,920 --> 00:28:50,760
Speaker 4: But a source of mine at BLS said that one

610
00:28:51,320 --> 00:28:53,800
Speaker 4: BLS official is listed as essential.

611
00:28:54,040 --> 00:28:57,320
Speaker 3: Wow, so what it? Yes, that's out of about two thousand.

612
00:28:57,480 --> 00:28:59,440
Speaker 1: Should we explain the essential thing for people?

613
00:28:59,440 --> 00:29:01,840
Speaker 4: For non wan So if you're if you're deemed to

614
00:29:01,840 --> 00:29:05,000
Speaker 4: be an essential employee, then you have to keep working.

615
00:29:05,240 --> 00:29:08,120
Speaker 3: Doesn't mean you get paid, right, ye, paid, but you

616
00:29:08,120 --> 00:29:09,720
Speaker 3: do have to keep working. But you have to keep working.

617
00:29:10,000 --> 00:29:12,720
Speaker 4: So there's one dude and it's not apparently I guess

618
00:29:12,720 --> 00:29:14,920
Speaker 4: the guy who just will talk about him in a second.

619
00:29:15,760 --> 00:29:19,080
Speaker 4: One dude or woman who is deemed to be essential.

620
00:29:19,840 --> 00:29:22,600
Speaker 4: Somebody's got to make sure you run that coffee maker

621
00:29:22,600 --> 00:29:23,880
Speaker 4: so it doesn't get moldy or whatever.

622
00:29:24,360 --> 00:29:25,080
Speaker 3: That's essential.

623
00:29:25,720 --> 00:29:30,000
Speaker 4: And so the BLS every day, it's thousands of employees

624
00:29:30,120 --> 00:29:38,520
Speaker 4: are collecting and analyzing data from businesses and other entities

625
00:29:38,560 --> 00:29:41,680
Speaker 4: around the country like this. This data does not just

626
00:29:42,080 --> 00:29:45,080
Speaker 4: appear out of nowhere, like it has to be produced,

627
00:29:45,120 --> 00:29:48,320
Speaker 4: it has to be found. So you're like, these employees

628
00:29:48,320 --> 00:29:50,840
Speaker 4: are on the phone calling businesses because if you're a business,

629
00:29:50,880 --> 00:29:53,880
Speaker 4: you think your top priority is calling bls back now

630
00:29:53,960 --> 00:29:55,960
Speaker 4: and telling them like, how many employees do.

631
00:29:55,920 --> 00:29:56,200
Speaker 3: You have this?

632
00:29:56,320 --> 00:29:59,120
Speaker 1: No, I've shared this before. Breaking Points was recently selected

633
00:29:59,120 --> 00:30:02,560
Speaker 1: for like the whatever survey, and it was so annoying

634
00:30:02,640 --> 00:30:05,120
Speaker 1: to fill out right. The only reason that we did

635
00:30:05,160 --> 00:30:08,040
Speaker 1: it is because they were like, you will be punished

636
00:30:08,120 --> 00:30:09,640
Speaker 1: if you do not fill out this or I was like,

637
00:30:09,680 --> 00:30:12,000
Speaker 1: all right, I guess it goes two hours of my life,

638
00:30:12,280 --> 00:30:12,960
Speaker 1: you know, going.

639
00:30:12,840 --> 00:30:16,160
Speaker 4: Right, And so it's it's a bunch of bureaucrats job

640
00:30:16,280 --> 00:30:18,160
Speaker 4: to make sure Sager fills that paperworkout.

641
00:30:18,240 --> 00:30:20,040
Speaker 3: And Sager does not want to fill out that. No.

642
00:30:20,120 --> 00:30:22,120
Speaker 1: I didn't want to. I even ask the accounts, I go,

643
00:30:22,200 --> 00:30:22,960
Speaker 1: do I have to do this?

644
00:30:23,000 --> 00:30:25,400
Speaker 4: They're like yeah, yeah. I was like okay, And so

645
00:30:25,520 --> 00:30:27,960
Speaker 4: now they're not going to be harassing. You're like, you

646
00:30:28,000 --> 00:30:31,880
Speaker 4: know what, I'm not filling that paperworkout, and so our

647
00:30:32,080 --> 00:30:35,240
Speaker 4: will be flying blind, yeah, into the FED meeting and elsewhere,

648
00:30:35,880 --> 00:30:39,720
Speaker 4: because once they come back right then then recollecting getting

649
00:30:39,760 --> 00:30:41,520
Speaker 4: it getting it started is a lot harder.

650
00:30:42,920 --> 00:30:44,080
Speaker 3: And the accuracy.

651
00:30:44,120 --> 00:30:44,160
Speaker 1: No.

652
00:30:44,240 --> 00:30:47,720
Speaker 4: Trump was very frustrated abou all the revisions. Can you

653
00:30:47,760 --> 00:30:49,680
Speaker 4: imagine what kind of revisions we're going to be looking at?

654
00:30:49,720 --> 00:30:50,920
Speaker 4: Good point of these coming months.

655
00:30:51,000 --> 00:30:54,600
Speaker 1: Yeah, government shutdowns always cost just kind of crazy disruptions

656
00:30:54,600 --> 00:30:58,239
Speaker 1: in service, and you know exactly anyways, and also, by

657
00:30:58,280 --> 00:31:00,640
Speaker 1: the way, that's why the market usually re acts negatively.

658
00:31:00,680 --> 00:31:02,800
Speaker 1: Although yesterday for some reason the stock still went green.

659
00:31:03,040 --> 00:31:05,920
Speaker 1: We'll talk about that with the AI block as to

660
00:31:05,960 --> 00:31:08,720
Speaker 1: what's actually driving the economy. But we had some very

661
00:31:08,800 --> 00:31:11,280
Speaker 1: limited data before the government shutdown we can share with you.

662
00:31:11,400 --> 00:31:13,520
Speaker 1: Let's put this up here on the screen. This was

663
00:31:13,560 --> 00:31:16,719
Speaker 1: from ADP. They say, quote that the US lost some

664
00:31:16,840 --> 00:31:21,040
Speaker 1: thirty two thousand jobs in September, says ADP Payroll Processor.

665
00:31:21,120 --> 00:31:23,520
Speaker 1: That is down from a revised loss of three thousand

666
00:31:23,560 --> 00:31:27,760
Speaker 1: in August. Economists had expected an increase of forty five thousand.

667
00:31:28,000 --> 00:31:30,680
Speaker 1: So the ADP does not include government workers. But they

668
00:31:30,680 --> 00:31:32,640
Speaker 1: say that they have to give it a closer look

669
00:31:32,680 --> 00:31:35,120
Speaker 1: this month because the BLS data is going to be

670
00:31:35,160 --> 00:31:37,320
Speaker 1: delayed because of the government shutdowns. So we are kind

671
00:31:37,320 --> 00:31:40,240
Speaker 1: of flying blind, as you just said. They say, quote,

672
00:31:40,320 --> 00:31:43,000
Speaker 1: the surprise job loss in September is the latest sign

673
00:31:43,040 --> 00:31:45,600
Speaker 1: that the labor market is weakening. Job growth has slowed

674
00:31:45,600 --> 00:31:47,760
Speaker 1: to a trickle this year, even as the unemployment rate

675
00:31:47,800 --> 00:31:51,640
Speaker 1: has mostly held steady. Federal reserve last month lowered short

676
00:31:51,720 --> 00:31:54,080
Speaker 1: term interest rates by quarter point and signal more cuts

677
00:31:54,120 --> 00:31:58,200
Speaker 1: are likely citing weak hiring specifically like this, and they

678
00:31:58,240 --> 00:32:01,560
Speaker 1: say that the leisure and hospitalitiestor shed some nineteen thousand

679
00:32:01,640 --> 00:32:05,960
Speaker 1: jobs last month, which was the largest decline among major sectors.

680
00:32:06,120 --> 00:32:09,200
Speaker 1: Education health services were still bright spots, with a collective

681
00:32:09,240 --> 00:32:11,360
Speaker 1: gain of thirty three thousand. So I think think the

682
00:32:11,440 --> 00:32:14,680
Speaker 1: fact that the leisure in hospitality industry is the one

683
00:32:14,680 --> 00:32:17,360
Speaker 1: that's getting the most hit that reminds me a lot

684
00:32:17,400 --> 00:32:20,200
Speaker 1: of COVID and of oh nine. Now it's not in

685
00:32:20,240 --> 00:32:22,760
Speaker 1: any way comparable to thirty two thousand, but the point is,

686
00:32:23,200 --> 00:32:25,959
Speaker 1: when consumer spending starts to soften, what's the first thing

687
00:32:26,000 --> 00:32:29,800
Speaker 1: that goes? Flights, hotels, travel, things like that. And if

688
00:32:29,800 --> 00:32:32,320
Speaker 1: you have that on top of a government shutdown, why

689
00:32:32,320 --> 00:32:34,680
Speaker 1: does the shutdown matter? Well, remember, the federal government is

690
00:32:34,720 --> 00:32:36,720
Speaker 1: the largest employer in the United States. You know, two

691
00:32:36,760 --> 00:32:39,600
Speaker 1: million people work for the federal government. So let's say

692
00:32:39,640 --> 00:32:41,880
Speaker 1: that this thing, the last one dragged thirty five months.

693
00:32:41,960 --> 00:32:44,360
Speaker 1: We were doing it for thirty five days, sorry, thirty

694
00:32:44,360 --> 00:32:47,800
Speaker 1: five minus. Can you imagine thirty five days? We were

695
00:32:47,840 --> 00:32:49,760
Speaker 1: trying to do the math on a number of mispay periods.

696
00:32:49,800 --> 00:32:51,760
Speaker 1: But that's a lot of money. I mean, the average

697
00:32:51,800 --> 00:32:55,000
Speaker 1: margin for the median household income is somewhere between five

698
00:32:55,080 --> 00:32:58,640
Speaker 1: hundred to one thousand dollars for an emergency, So to

699
00:32:58,800 --> 00:33:02,280
Speaker 1: mispaid periods, you're really starting to cut into credit card

700
00:33:02,360 --> 00:33:04,840
Speaker 1: debt and to some other issues. I mean, we could

701
00:33:04,840 --> 00:33:07,000
Speaker 1: put the morality or whatever of that aside and say

702
00:33:07,080 --> 00:33:09,840
Speaker 1: economically that's usually not good. That means it's like, Okay,

703
00:33:09,880 --> 00:33:12,280
Speaker 1: we're not eating out, we're not buying gas, we're making

704
00:33:12,320 --> 00:33:14,760
Speaker 1: like app putting most stuff on a credit card, hoping

705
00:33:14,800 --> 00:33:18,360
Speaker 1: that stuff eventually we do get paid. We can backpay

706
00:33:18,400 --> 00:33:21,080
Speaker 1: our mortgage, our rent, et cetera. So that's a that's

707
00:33:21,120 --> 00:33:22,720
Speaker 1: a difficult situation.

708
00:33:22,680 --> 00:33:24,520
Speaker 3: Right, Right, We're not going to fly anywhere in the fall.

709
00:33:24,600 --> 00:33:27,280
Speaker 1: Yeah, we're definitely not going We're not going anywhere for Thanksgiving, right,

710
00:33:27,320 --> 00:33:29,920
Speaker 1: you know, things like Thanksgiving. I mean, isn't I believe

711
00:33:30,320 --> 00:33:32,840
Speaker 1: Thanksgiving Sunday is like the biggest travel day of the

712
00:33:33,000 --> 00:33:35,440
Speaker 1: entire year, so tens of millions of people take to them.

713
00:33:35,480 --> 00:33:36,960
Speaker 4: We might not be making that and a lot of

714
00:33:36,960 --> 00:33:38,920
Speaker 4: those people had miserable flights last time.

715
00:33:39,000 --> 00:33:40,560
Speaker 3: Yeah, it was you know, what maybe we're just not

716
00:33:40,560 --> 00:33:41,160
Speaker 3: gonna slode us.

717
00:33:41,200 --> 00:33:41,680
Speaker 1: We're there too.

718
00:33:41,720 --> 00:33:43,560
Speaker 3: Ye, they were going to fly this year. We'll just.

719
00:33:45,120 --> 00:33:48,640
Speaker 4: Whoever lives close enough to drive together, we'll celebrate with that.

720
00:33:48,880 --> 00:33:52,520
Speaker 4: And this is come, this difficult time is coming as

721
00:33:52,560 --> 00:33:56,480
Speaker 4: people are stretched ever tighter because of the increase in

722
00:33:57,520 --> 00:34:01,200
Speaker 4: energy costs and grocery bills and uh, you know, interest

723
00:34:01,280 --> 00:34:04,760
Speaker 4: rates and housing prices. Like it's it's just tougher out

724
00:34:04,760 --> 00:34:07,360
Speaker 4: there than it was five years ago. Uh, and so

725
00:34:08,280 --> 00:34:10,480
Speaker 4: people have I think a little bit less breathing room

726
00:34:10,920 --> 00:34:11,520
Speaker 4: going this time.

727
00:34:11,520 --> 00:34:14,320
Speaker 3: But also Trump's.

728
00:34:15,760 --> 00:34:19,080
Speaker 4: Global whatever you would call it, a global trade war

729
00:34:19,239 --> 00:34:24,440
Speaker 4: and like attack on Canada in particular, has has really

730
00:34:25,080 --> 00:34:29,560
Speaker 4: dragged down, uh, tourism from Canada and tourism from everywhere

731
00:34:29,600 --> 00:34:30,080
Speaker 4: around the world.

732
00:34:30,120 --> 00:34:32,640
Speaker 1: Yeah, I heard this is screwing Vegas.

733
00:34:32,760 --> 00:34:34,680
Speaker 3: So first of all, now l a too.

734
00:34:34,840 --> 00:34:37,240
Speaker 1: Really, what's some of those Canadians.

735
00:34:37,440 --> 00:34:41,600
Speaker 4: Canadians love they love Vegas and they love they love Canada.

736
00:34:41,640 --> 00:34:43,640
Speaker 4: By the way, you've been to Canada, right, Yeah, you

737
00:34:43,640 --> 00:34:46,640
Speaker 4: want to stay in Canada all the time? No, Okay, exactly,

738
00:34:46,719 --> 00:34:50,759
Speaker 4: I'm not Canadian. Closest closest country the United States. And

739
00:34:50,800 --> 00:34:53,759
Speaker 4: so they come down here in droves. Yeah, they go

740
00:34:53,840 --> 00:34:56,520
Speaker 4: to Florida, they go to outer banks.

741
00:34:56,239 --> 00:35:00,480
Speaker 1: You know, they go to there's snowbirds. Yeah, okay, that

742
00:35:00,840 --> 00:35:01,320
Speaker 1: makes sense.

743
00:35:01,520 --> 00:35:04,080
Speaker 4: Yeah, and so if you're in canad wouldn't you rather

744
00:35:04,080 --> 00:35:05,320
Speaker 4: be in La Sure?

745
00:35:05,600 --> 00:35:06,600
Speaker 3: Yeah, definitely.

746
00:35:06,640 --> 00:35:08,359
Speaker 4: Instead the Canadians like, you know what, screw it, We're

747
00:35:08,360 --> 00:35:08,920
Speaker 4: not going to La.

748
00:35:10,040 --> 00:35:10,759
Speaker 1: So where are they going?

749
00:35:11,400 --> 00:35:13,600
Speaker 4: A lot of me staying home, And then I think

750
00:35:13,680 --> 00:35:15,799
Speaker 4: they're going to Europe. I don't know what they're doing.

751
00:35:15,800 --> 00:35:17,399
Speaker 4: It's good, that is, Actually that's a good question. Maybe

752
00:35:17,400 --> 00:35:22,040
Speaker 4: they're going to Mexico. That would actually be lying right over. Well,

753
00:35:22,120 --> 00:35:25,320
Speaker 4: I'll actually make some call to like the Canadian tourism places.

754
00:35:25,560 --> 00:35:27,400
Speaker 4: I would love where the Canadians is because they're not

755
00:35:27,480 --> 00:35:31,800
Speaker 4: coming here and it's killing, you know, our tourism industry.

756
00:35:32,040 --> 00:35:34,520
Speaker 1: I knew that about Vega because I've seen some Vegas

757
00:35:34,600 --> 00:35:35,920
Speaker 1: stuff coming out and be like, oh my.

758
00:35:35,880 --> 00:35:38,800
Speaker 3: God, Vega screw just one after another.

759
00:35:38,880 --> 00:35:42,040
Speaker 1: I was like, really like Canada that relying on Vegas. Interesting.

760
00:35:42,440 --> 00:35:45,440
Speaker 1: All right, let's continue to on this, you know, on

761
00:35:45,520 --> 00:35:48,600
Speaker 1: this train with the BLS news that we could share

762
00:35:48,640 --> 00:35:49,799
Speaker 1: with all of you. Let's put it up here on

763
00:35:49,840 --> 00:35:52,840
Speaker 1: the screen so you'll all recall the BLS commissioner was

764
00:35:52,880 --> 00:35:57,520
Speaker 1: fired after our revision happened because Trump didn't like the revision,

765
00:35:57,560 --> 00:36:01,239
Speaker 1: and so Trump nominated E. J. Antone me, previously of

766
00:36:01,239 --> 00:36:04,960
Speaker 1: the Heritage Foundation, to lead the Bureau of Labor Statistics. Well,

767
00:36:05,040 --> 00:36:08,440
Speaker 1: it turns out that his nomination has now been pulled

768
00:36:08,760 --> 00:36:12,640
Speaker 1: from the BLS before the United States Senate to be confirmed.

769
00:36:12,800 --> 00:36:15,440
Speaker 1: The quote White House official declined to say the reasons

770
00:36:15,440 --> 00:36:17,880
Speaker 1: for withdrawing the nomination, only to say that he was

771
00:36:17,920 --> 00:36:21,120
Speaker 1: a talented economist and President Trump plans to announce a

772
00:36:21,160 --> 00:36:23,680
Speaker 1: new nominee soon. So Ryan, as you and I know

773
00:36:23,920 --> 00:36:27,960
Speaker 1: here in Washington, what this means is that not one senator,

774
00:36:28,160 --> 00:36:32,000
Speaker 1: not two, but four Republicans came to the White House

775
00:36:32,040 --> 00:36:35,120
Speaker 1: and they're like, hey, this is not happening, period. And

776
00:36:35,160 --> 00:36:37,799
Speaker 1: so usually what happens then is the White House gets

777
00:36:37,840 --> 00:36:41,680
Speaker 1: to save face and withdraw and no Republican senator has

778
00:36:41,719 --> 00:36:44,359
Speaker 1: to come out publicly and say I was not going

779
00:36:44,360 --> 00:36:46,360
Speaker 1: to vote for this person. But they were willing to

780
00:36:46,360 --> 00:36:48,440
Speaker 1: do it. They called the bluff, They called the Office

781
00:36:48,440 --> 00:36:51,680
Speaker 1: of White House Legislative Affairs and they're like, look, he's

782
00:36:51,680 --> 00:36:53,560
Speaker 1: not getting he's not even going to go through committee.

783
00:36:53,600 --> 00:36:56,040
Speaker 1: He's not going through the floor. Pull his nomination and

784
00:36:56,160 --> 00:36:58,440
Speaker 1: let's move on because this is not happening right now.

785
00:36:58,440 --> 00:36:59,960
Speaker 3: So Larry Summers went down.

786
00:37:00,120 --> 00:37:03,439
Speaker 4: Yeah, maybe five Democrats from the Banking Committee just called

787
00:37:03,440 --> 00:37:06,200
Speaker 4: the Obama administration and said, we're not making him fed shair. Yep,

788
00:37:06,320 --> 00:37:08,719
Speaker 4: you can put him up, but he's going down. Yeah,

789
00:37:08,760 --> 00:37:09,959
Speaker 4: and you're like, you know what, then we're not putting

790
00:37:10,000 --> 00:37:13,320
Speaker 4: him up. There was these he had, he lacked support

791
00:37:13,400 --> 00:37:20,040
Speaker 4: within within the right wing. Incredible quote, uh do you

792
00:37:20,080 --> 00:37:22,919
Speaker 4: know uh Kyle Palmerlow, I don't know him, no tax

793
00:37:22,960 --> 00:37:29,359
Speaker 4: expert for the for American Enterprise Institute. He wrote on

794
00:37:29,400 --> 00:37:32,600
Speaker 4: Twitter after after his nomination. He wrote, quote, there are

795
00:37:32,600 --> 00:37:35,920
Speaker 4: a lot of competent conservative economists that could do this job.

796
00:37:36,239 --> 00:37:37,520
Speaker 3: E J is not one of them.

797
00:37:38,280 --> 00:37:41,120
Speaker 1: It's just such a very bitchy.

798
00:37:41,120 --> 00:37:44,040
Speaker 4: I just once and that's a baseline. He's just saying

799
00:37:44,360 --> 00:37:49,400
Speaker 4: he's just not competent. So it wasn't a ideological problem.

800
00:37:49,640 --> 00:37:51,680
Speaker 4: And BLS had a bunch of problems after he was named,

801
00:37:51,680 --> 00:37:53,759
Speaker 4: Like remember they were like, oh, by the way, we're

802
00:37:53,800 --> 00:37:57,520
Speaker 4: not releasing our data. Yes that's right, No, no explanation,

803
00:37:58,400 --> 00:38:00,000
Speaker 4: this is this is like last week or the week before.

804
00:38:00,960 --> 00:38:03,680
Speaker 4: Data is late, and Wall Street is just not used

805
00:38:03,719 --> 00:38:08,000
Speaker 4: to BLS having that data late. Like Wall Street trusts

806
00:38:08,040 --> 00:38:10,520
Speaker 4: BLS data, and they trust that when they say it's

807
00:38:10,520 --> 00:38:12,600
Speaker 4: going to come post at eight thirty, it posts it

808
00:38:12,680 --> 00:38:13,799
Speaker 4: eight thirty precisely.

809
00:38:14,160 --> 00:38:16,720
Speaker 3: And they're sitting there with their trigger fingers ready to

810
00:38:16,920 --> 00:38:17,440
Speaker 3: trade on it.

811
00:38:17,640 --> 00:38:17,920
Speaker 1: Yeah.

812
00:38:17,960 --> 00:38:19,799
Speaker 4: Oh no, they're not even their trigger fingers, but they're

813
00:38:19,840 --> 00:38:23,360
Speaker 4: like fake algorithmic trading models are ready to ready to

814
00:38:23,400 --> 00:38:26,560
Speaker 4: start trading. And to have a guy who's like, wait,

815
00:38:27,160 --> 00:38:28,680
Speaker 4: we're not putting the data out on.

816
00:38:28,680 --> 00:38:32,400
Speaker 1: Time, right, it's out here inconceivable right to Wall Street

817
00:38:32,440 --> 00:38:34,080
Speaker 1: and two others. That's a good point. I hadn't thought

818
00:38:34,120 --> 00:38:36,880
Speaker 1: about that, But you're right. Last thing here in terms

819
00:38:36,920 --> 00:38:39,359
Speaker 1: of the White House and the economy. Who can put

820
00:38:39,360 --> 00:38:42,040
Speaker 1: this up here on the screen. The Supreme Court has

821
00:38:42,080 --> 00:38:46,200
Speaker 1: allowed Lisa Cook to keep her job for now. For

822
00:38:46,320 --> 00:38:49,279
Speaker 1: those who were not tracking, Lisa Cook was one of

823
00:38:49,280 --> 00:38:52,319
Speaker 1: the members of the Federal Reserve Board. Is a member

824
00:38:52,400 --> 00:38:55,760
Speaker 1: or is a member of the Federal Reserve Board who

825
00:38:56,360 --> 00:38:59,400
Speaker 1: was not going along with the Trump administration's desire to

826
00:38:59,400 --> 00:39:03,480
Speaker 1: cut rates sooner than as soon as possible. So Trump

827
00:39:03,760 --> 00:39:08,080
Speaker 1: and the administration accused her of mortgage fraud based on

828
00:39:08,280 --> 00:39:11,000
Speaker 1: what is it? Within the executive they're technically allowed to

829
00:39:11,000 --> 00:39:14,560
Speaker 1: file people fire people, quote for cause. And so basically

830
00:39:14,680 --> 00:39:16,680
Speaker 1: one of their what is it, the Federal Housing Administrator,

831
00:39:16,840 --> 00:39:19,960
Speaker 1: Bill Pult went out and found this thing which she

832
00:39:20,040 --> 00:39:22,719
Speaker 1: allegedly purchased a home or as a vacation hope, something

833
00:39:22,760 --> 00:39:24,800
Speaker 1: like that, some sort of vacation of some sort of

834
00:39:24,840 --> 00:39:28,759
Speaker 1: mortgage fraud technicality. Based on that, Trump said that she

835
00:39:28,920 --> 00:39:31,640
Speaker 1: was fired. This led to a showdown with the Supreme

836
00:39:31,680 --> 00:39:35,160
Speaker 1: Court over whether a whether the charges are legitimate, and

837
00:39:35,200 --> 00:39:38,319
Speaker 1: b whether that qualifies as being fired four cause. So

838
00:39:38,360 --> 00:39:41,200
Speaker 1: the court, in a brief order quote deferred a decision

839
00:39:41,440 --> 00:39:44,920
Speaker 1: on the Trump administration's emergency request to remove Cook from

840
00:39:45,000 --> 00:39:49,320
Speaker 1: the bank's independent board while the lawsuit challenged her dismissal proceeds.

841
00:39:49,320 --> 00:39:50,680
Speaker 1: So this is going to take a while, at the

842
00:39:50,800 --> 00:39:53,040
Speaker 1: very least till January. I think that all of this

843
00:39:53,120 --> 00:39:55,719
Speaker 1: goes forward, it's going to center on the legitimacy of

844
00:39:55,760 --> 00:39:58,960
Speaker 1: the charges over Trump's own executive power. But at the

845
00:39:59,080 --> 00:40:01,920
Speaker 1: very least, four Trump is not getting the total control

846
00:40:02,120 --> 00:40:04,480
Speaker 1: of the Federal Reserve Board that he wanted the.

847
00:40:04,840 --> 00:40:06,680
Speaker 3: Right, but he did get his little rate cut.

848
00:40:06,719 --> 00:40:10,200
Speaker 1: Quarter point right, Well, he wants a lot more, right,

849
00:40:10,239 --> 00:40:12,160
Speaker 1: And I mean I want a lot more. To be honest,

850
00:40:12,360 --> 00:40:16,800
Speaker 1: I still think it's crushing a lot of our economy.

851
00:40:17,600 --> 00:40:19,600
Speaker 1: All right, we're turning now to Sora. Some of you

852
00:40:19,680 --> 00:40:24,520
Speaker 1: may have seen this open AI released a new video generator,

853
00:40:24,600 --> 00:40:28,320
Speaker 1: and while it's cool, I guess you know a little

854
00:40:28,320 --> 00:40:31,279
Speaker 1: bit dystopian. What a lot of people are missing are

855
00:40:31,320 --> 00:40:34,560
Speaker 1: some of the backbones of the US power industry and

856
00:40:34,640 --> 00:40:38,040
Speaker 1: economy that are behind all of this, which are actually

857
00:40:38,120 --> 00:40:40,400
Speaker 1: wreaking havoc on all of our lives in a hidden

858
00:40:40,440 --> 00:40:42,480
Speaker 1: way that a lot of people don't appreciate. So let's

859
00:40:42,480 --> 00:40:44,520
Speaker 1: ahead and put this up here on the screen. This

860
00:40:44,560 --> 00:40:47,680
Speaker 1: is new data that has been released and compiled by

861
00:40:47,719 --> 00:40:51,799
Speaker 1: Bloomberg over consuming the growing share of electricity. The data

862
00:40:51,800 --> 00:40:54,600
Speaker 1: centers are in individual US states. So stick with me,

863
00:40:54,640 --> 00:40:56,520
Speaker 1: and let's keep this up so I can read to

864
00:40:56,520 --> 00:41:00,319
Speaker 1: everybody what the overall total electricity consumption is on a

865
00:41:00,360 --> 00:41:03,439
Speaker 1: state by state basis, Virginia, the state where I live,

866
00:41:03,840 --> 00:41:08,279
Speaker 1: thirty nine percent of all power consumption is going to

867
00:41:08,360 --> 00:41:11,440
Speaker 1: data centers. Ryan thirty nine percent. Probably all of that

868
00:41:11,560 --> 00:41:14,719
Speaker 1: is federal government. If I had to guess Amazon and

869
00:41:14,880 --> 00:41:18,520
Speaker 1: as well that are all together, but that's an absolutely

870
00:41:18,560 --> 00:41:22,480
Speaker 1: insane amount of power consumption. The state of Oregon thirty

871
00:41:22,560 --> 00:41:28,120
Speaker 1: three percent, Iowa eighteen, Nevada fifteen, Utah fifteen, Nebraska fourteen,

872
00:41:28,239 --> 00:41:34,080
Speaker 1: Arizona eleven, Wyoming ten, Ohio nine, Illinois seven, Georgia six,

873
00:41:34,360 --> 00:41:39,040
Speaker 1: New Jersey six, Washington six, Texas five, North Dakota five.

874
00:41:39,280 --> 00:41:46,439
Speaker 1: I find it incredibly consequential that smaller states like Oregon, Iowa, Nevada, Utah, Nebraska,

875
00:41:46,920 --> 00:41:50,719
Speaker 1: traditional more flyover states, especially Iowa through Nebraska, are being

876
00:41:50,840 --> 00:41:52,799
Speaker 1: used by a lot of these data centers because it

877
00:41:52,840 --> 00:41:55,879
Speaker 1: shows that they're picking those more rural areas and they're

878
00:41:55,880 --> 00:41:59,359
Speaker 1: getting their state legislators and their municipalities to actually give

879
00:41:59,400 --> 00:42:03,000
Speaker 1: them tax breaks to only because their promises, who create

880
00:42:03,040 --> 00:42:05,080
Speaker 1: a bunch of jobs, et cetera. Oh, you know, we're

881
00:42:05,080 --> 00:42:07,520
Speaker 1: going to pump all this money into the economy. But

882
00:42:07,560 --> 00:42:09,759
Speaker 1: the way that our power grid works, which is not

883
00:42:09,800 --> 00:42:12,960
Speaker 1: a horrible idea, is that, hey, we have regulated public

884
00:42:13,000 --> 00:42:16,439
Speaker 1: power based on that it's a platform through which all

885
00:42:16,480 --> 00:42:20,080
Speaker 1: of us get to build upon our houses, our businesses,

886
00:42:20,239 --> 00:42:23,560
Speaker 1: and the costs and the benefits are widely distributed. Across.

887
00:42:23,600 --> 00:42:26,200
Speaker 1: It's a floor that the government in our power industry

888
00:42:26,400 --> 00:42:29,080
Speaker 1: sets so that we can build upon it. And yet

889
00:42:29,160 --> 00:42:32,120
Speaker 1: in a scarce power in a place where we are

890
00:42:32,200 --> 00:42:34,520
Speaker 1: right now because we have not we don't have any

891
00:42:34,600 --> 00:42:38,080
Speaker 1: proper investment or building of nuclear energy. I know you're

892
00:42:38,160 --> 00:42:40,640
Speaker 1: more of a solarble guy. I'm not personally a solar guy.

893
00:42:40,680 --> 00:42:44,440
Speaker 1: I'm pretty much all of these, but yeah, I'm all regardless.

894
00:42:44,480 --> 00:42:47,160
Speaker 1: The point is that we don't have a preponderance of

895
00:42:47,200 --> 00:42:49,440
Speaker 1: power the way that they do in China and in

896
00:42:49,480 --> 00:42:51,560
Speaker 1: a lot of other places. Even if we were to

897
00:42:51,600 --> 00:42:54,319
Speaker 1: go all in on oil, we still don't have new

898
00:42:54,360 --> 00:42:56,840
Speaker 1: oil refineries, we don't have new natural gas ricks. We

899
00:42:56,920 --> 00:43:00,719
Speaker 1: are in stasis effectively in every state in the So

900
00:43:00,920 --> 00:43:04,840
Speaker 1: in a scarce power world and in which AI data

901
00:43:04,880 --> 00:43:08,920
Speaker 1: center usage, power and investment is a huge chunk of

902
00:43:09,000 --> 00:43:12,840
Speaker 1: GDP spending. What does that mean? It means that these industries,

903
00:43:12,880 --> 00:43:16,000
Speaker 1: which have endless amounts of money behind them, come in,

904
00:43:16,320 --> 00:43:20,040
Speaker 1: build your data center, use an insane amount of electricity.

905
00:43:20,280 --> 00:43:21,960
Speaker 1: They don't care if the power bill goes up. It

906
00:43:21,960 --> 00:43:24,160
Speaker 1: does nothing to their bottom line. Because all of this

907
00:43:24,280 --> 00:43:25,960
Speaker 1: is fake. None of us even making money in the

908
00:43:26,000 --> 00:43:28,480
Speaker 1: first place, they'll just pay it no matter what. Who's

909
00:43:28,520 --> 00:43:30,919
Speaker 1: the person for whom a power bill increase is going

910
00:43:30,960 --> 00:43:33,960
Speaker 1: to affect you, especially in the more rural areas, the

911
00:43:34,000 --> 00:43:38,560
Speaker 1: fixed income household, and just general suburban residents. That's why

912
00:43:38,640 --> 00:43:41,160
Speaker 1: I think it's outrageous to have some thirty nine thirty

913
00:43:41,200 --> 00:43:44,439
Speaker 1: three percent in places like Virginia and Oregon, one third

914
00:43:44,480 --> 00:43:47,560
Speaker 1: to almost forty percent of power being consumed by a

915
00:43:47,640 --> 00:43:50,600
Speaker 1: single industry. We can't be living in the world where

916
00:43:50,680 --> 00:43:54,120
Speaker 1: everybody else has to absorb all of those increased costs.

917
00:43:54,200 --> 00:43:58,640
Speaker 1: And it's again begs the question for what. So if

918
00:43:58,680 --> 00:44:02,319
Speaker 1: this was the Manhattan Project, you know, the Tennessee Valley

919
00:44:02,360 --> 00:44:05,120
Speaker 1: of thor like any of the maybe right, maybe we

920
00:44:05,160 --> 00:44:07,320
Speaker 1: could all set okay, okay, we can all pay a

921
00:44:07,360 --> 00:44:10,320
Speaker 1: little bit more because this is so important to the country.

922
00:44:10,360 --> 00:44:11,880
Speaker 3: The hollow electric program.

923
00:44:11,920 --> 00:44:14,560
Speaker 1: Yeah we are electrified. There you go. One of my

924
00:44:14,600 --> 00:44:18,000
Speaker 1: favorite sections of the Robert Carroll books. He I think

925
00:44:18,000 --> 00:44:19,960
Speaker 1: he won a Politicer Prize for it. It's in the

926
00:44:20,000 --> 00:44:24,120
Speaker 1: first book called pat to Power is a chapter specifically

927
00:44:24,320 --> 00:44:28,399
Speaker 1: on rural electrification and what it meant to more rural

928
00:44:28,440 --> 00:44:30,399
Speaker 1: areas in the nineteen thirties. It was a New Deal

929
00:44:30,440 --> 00:44:33,520
Speaker 1: style program designed by Fdr Johnson used it as a

930
00:44:33,520 --> 00:44:36,160
Speaker 1: new congressman that was able to bring power to the

931
00:44:36,239 --> 00:44:38,840
Speaker 1: Hill Country of Texas. I highly recommend going, at the

932
00:44:38,880 --> 00:44:41,439
Speaker 1: very least just read that chapter to understand what that means.

933
00:44:41,480 --> 00:44:43,279
Speaker 1: That's the level of where yeah, okay, I think we

934
00:44:43,320 --> 00:44:46,440
Speaker 1: could be okay, socializing some of that costs this. No,

935
00:44:46,600 --> 00:44:50,280
Speaker 1: all right, and say that's the issue story for AI

936
00:44:50,440 --> 00:44:53,840
Speaker 1: generated slop. No, no, no, no, no, We're not doing that.

937
00:44:54,160 --> 00:44:57,200
Speaker 1: And yet what we see instead is instead of thinking

938
00:44:57,200 --> 00:44:59,960
Speaker 1: about the data centers, what people are starting to think about,

939
00:45:00,440 --> 00:45:02,680
Speaker 1: and there's a new bill of introducing the state of Ohio,

940
00:45:03,040 --> 00:45:06,840
Speaker 1: is that the utility companies can automatically adjust a customer

941
00:45:06,880 --> 00:45:10,720
Speaker 1: thermostat to quote reduce the load on the power grid

942
00:45:11,000 --> 00:45:13,719
Speaker 1: during periods of high demand for the data center. So

943
00:45:13,920 --> 00:45:16,560
Speaker 1: your house has to be hotter, so the data center

944
00:45:16,920 --> 00:45:20,440
Speaker 1: can crunch. Sam Altman, slop. Okay, let's take a listen

945
00:45:20,480 --> 00:45:21,320
Speaker 1: from local news.

946
00:45:21,600 --> 00:45:25,120
Speaker 8: The Republican lawmaker at the Ohio State House introduced to

947
00:45:25,160 --> 00:45:30,040
Speaker 8: bill this week that would allow utility companies to automatically

948
00:45:30,080 --> 00:45:35,080
Speaker 8: adjust your thermostat at your house. House Built four twenty

949
00:45:35,120 --> 00:45:40,120
Speaker 8: seven would create a voluntary Demand Response Program, Customers would

950
00:45:40,160 --> 00:45:43,160
Speaker 8: be allowed to sign up to let their utility company

951
00:45:43,280 --> 00:45:49,600
Speaker 8: temporarily adjust energy use, including raising thermostat settings or cycling

952
00:45:49,719 --> 00:45:53,920
Speaker 8: water heaters during periods of high demand. The bill sponsor,

953
00:45:54,080 --> 00:45:59,279
Speaker 8: Representative Roy Kloppenstein, said it's meant to help homeowners and

954
00:45:59,400 --> 00:46:02,320
Speaker 8: small business. This is save money while reducing the load

955
00:46:02,400 --> 00:46:06,200
Speaker 8: on the power grid, and analysis from the Ohio Environmental

956
00:46:06,200 --> 00:46:09,920
Speaker 8: Council estimates the program would generate between thirty four and

957
00:46:10,000 --> 00:46:14,040
Speaker 8: one hundred million dollars in savings for the utility system,

958
00:46:14,080 --> 00:46:17,280
Speaker 8: depending on how many customers sign up for it.

959
00:46:18,080 --> 00:46:20,839
Speaker 1: Temporarily adjust home power use in small business. I don't

960
00:46:20,880 --> 00:46:23,640
Speaker 1: hear any data center being mentioned there, right, And that's

961
00:46:23,640 --> 00:46:25,799
Speaker 1: my issue is like these we don't have had any

962
00:46:25,840 --> 00:46:28,520
Speaker 1: power demands or anything on these folks, and they get

963
00:46:28,560 --> 00:46:31,000
Speaker 1: to just, you know, unlimitedly suck from the grid and

964
00:46:31,080 --> 00:46:33,960
Speaker 1: make sure that everybody else power bills get to go up. No, no,

965
00:46:34,719 --> 00:46:37,680
Speaker 1: we can't be having that right And instead, like I said,

966
00:46:38,000 --> 00:46:40,320
Speaker 1: I tweeted something in reaction to those data powers, and

967
00:46:40,360 --> 00:46:43,040
Speaker 1: I said, hey, state legislators, wake up, you guys have

968
00:46:43,760 --> 00:46:46,600
Speaker 1: huge amounts of authority, dominion power. You know where I

969
00:46:46,640 --> 00:46:50,359
Speaker 1: live Virginia legislators can come in and change the way.

970
00:46:50,360 --> 00:46:52,319
Speaker 1: If you're going to consume forty percent of power, I'm sorry,

971
00:46:52,360 --> 00:46:53,440
Speaker 1: you got to be paying a hell of a lot

972
00:46:53,520 --> 00:46:56,080
Speaker 1: more and making sure that there's some offset or whatever

973
00:46:56,120 --> 00:47:00,879
Speaker 1: for consumers. And instead, what Virginia political expert was telling

974
00:47:00,920 --> 00:47:04,600
Speaker 1: me was it's the inverse where what's happening is that

975
00:47:04,680 --> 00:47:07,280
Speaker 1: the legislators are all bought and paid for by Amazon,

976
00:47:07,560 --> 00:47:10,319
Speaker 1: by Meta, Google all these other people, And instead they're

977
00:47:10,360 --> 00:47:13,080
Speaker 1: throwing incentives at the data centers because they're like, oh,

978
00:47:13,120 --> 00:47:16,279
Speaker 1: we create all of these amazing jobs for all the

979
00:47:16,320 --> 00:47:20,000
Speaker 1: people who said, okay, yeah, it's great for you know,

980
00:47:20,080 --> 00:47:22,440
Speaker 1: the thousand people or whatever that work there, But what

981
00:47:22,480 --> 00:47:24,520
Speaker 1: about the millions or still people that have to pay

982
00:47:24,680 --> 00:47:26,920
Speaker 1: a higher power bell in a lot of these other places.

983
00:47:26,960 --> 00:47:30,160
Speaker 1: So I think this is a major populist issue which

984
00:47:30,160 --> 00:47:33,719
Speaker 1: everybody is sleeping on. And again, if this were the

985
00:47:33,840 --> 00:47:38,040
Speaker 1: railroads of the eighteen hundreds, it transformed America, right, you know,

986
00:47:38,120 --> 00:47:40,800
Speaker 1: undeniab I get it. They were the villains of the time,

987
00:47:41,160 --> 00:47:45,320
Speaker 1: et cetera. But fundamentally they had a good value proposition.

988
00:47:45,560 --> 00:47:47,839
Speaker 1: Is you used to have to take a wagon, Now

989
00:47:47,880 --> 00:47:50,240
Speaker 1: you can go to California in a week. All right,

990
00:47:50,320 --> 00:47:55,000
Speaker 1: that was a real thing. Telecom in the nineties, same thing.

991
00:47:55,600 --> 00:47:58,080
Speaker 1: We could say a lot about how much of it

992
00:47:58,160 --> 00:48:01,840
Speaker 1: was a bust. They overspent on fiber optics. They massively

993
00:48:01,840 --> 00:48:05,239
Speaker 1: consumed amount of GDP to invest because they got a

994
00:48:05,280 --> 00:48:07,040
Speaker 1: little too high on their own supply from the dot

995
00:48:07,080 --> 00:48:09,520
Speaker 1: com bubble. But that was a real thing. Fiber optic

996
00:48:09,640 --> 00:48:10,520
Speaker 1: was a real thing.

997
00:48:10,560 --> 00:48:11,040
Speaker 3: The Internet.

998
00:48:11,280 --> 00:48:14,160
Speaker 1: What is being built here? Right? You know we have

999
00:48:14,360 --> 00:48:17,000
Speaker 1: all these billions of billions and billions and billions of dollars.

1000
00:48:17,080 --> 00:48:21,720
Speaker 1: They're being spent all for what. And that's the point

1001
00:48:21,880 --> 00:48:25,360
Speaker 1: where when you see what they're actually releasing, I'm sorry

1002
00:48:25,680 --> 00:48:28,799
Speaker 1: who asked for this? And here's the new trailer from

1003
00:48:28,800 --> 00:48:32,880
Speaker 1: open Ai about Sora to the video generator. This is

1004
00:48:32,880 --> 00:48:35,000
Speaker 1: what you're all paying for. Let's take a listen.

1005
00:48:36,200 --> 00:48:38,840
Speaker 5: One year ago, Sora one redefined what was possible with

1006
00:48:38,920 --> 00:48:42,560
Speaker 5: moving images. Today we're announcing the Sora app, powered by

1007
00:48:42,600 --> 00:48:50,319
Speaker 5: the all new Sora two. That's the most powerful imagination

1008
00:48:50,520 --> 00:48:51,760
Speaker 5: engine ever built.

1009
00:48:52,600 --> 00:48:56,000
Speaker 3: Sure, and it's packed with new features.

1010
00:48:56,840 --> 00:49:03,840
Speaker 5: I'll pass it a bill for more details.

1011
00:49:03,840 --> 00:49:06,080
Speaker 3: Every video comes with sound.

1012
00:49:15,719 --> 00:49:18,680
Speaker 1: Wow, so cool. New images and by the way, you

1013
00:49:18,719 --> 00:49:21,160
Speaker 1: know what the funny thing is one of the very

1014
00:49:21,160 --> 00:49:25,000
Speaker 1: first images ryan and videos that was released on Sora

1015
00:49:25,480 --> 00:49:28,799
Speaker 1: was this. Let's just play this. What we saw was

1016
00:49:28,960 --> 00:49:34,040
Speaker 1: immediately Sora being used to create a surveillance style video

1017
00:49:34,600 --> 00:49:40,120
Speaker 1: showing Sam Altman himself stealing GPUs at Target and being

1018
00:49:40,160 --> 00:49:43,400
Speaker 1: accosted by a security officer. I mean, I don't know,

1019
00:49:43,400 --> 00:49:46,120
Speaker 1: what do you think It looks real ish like I

1020
00:49:46,120 --> 00:49:49,800
Speaker 1: could probably tell it was AI. So you basically created

1021
00:49:50,160 --> 00:49:54,319
Speaker 1: slop video which will be used for YouTube shorts and

1022
00:49:54,480 --> 00:50:00,080
Speaker 1: Instagram and all this other nonsense to do for scrolling purposes.

1023
00:50:00,280 --> 00:50:04,320
Speaker 1: And also you created a technology which makes it unronically

1024
00:50:04,400 --> 00:50:07,799
Speaker 1: possible so that a surveillance video and deep fakes and

1025
00:50:07,840 --> 00:50:10,319
Speaker 1: all that other stuff could be immediately employed. Let's say,

1026
00:50:10,320 --> 00:50:12,719
Speaker 1: in a matter of crisis, think about the Charlie Kirk thing.

1027
00:50:12,719 --> 00:50:14,680
Speaker 1: If this was around at that time and you say

1028
00:50:14,719 --> 00:50:18,239
Speaker 1: I have surveillance video showing Tyler Robinson doing X, Y

1029
00:50:18,280 --> 00:50:20,600
Speaker 1: and Z, it would go massively viral. You and I

1030
00:50:20,680 --> 00:50:23,439
Speaker 1: know that, so thank you for creating that. By the way,

1031
00:50:23,440 --> 00:50:25,840
Speaker 1: the amount of power you know, if you have chat EAPT,

1032
00:50:25,920 --> 00:50:28,319
Speaker 1: I pay for chat EPT, and even if you want

1033
00:50:28,360 --> 00:50:30,600
Speaker 1: to use it to create an image. It takes forever,

1034
00:50:30,800 --> 00:50:33,200
Speaker 1: you know why, because it's a shit ton of you know,

1035
00:50:33,320 --> 00:50:36,440
Speaker 1: cpu use and electricity and all it has to crunch

1036
00:50:36,480 --> 00:50:39,440
Speaker 1: through that. So what is the purpose of what we're

1037
00:50:39,480 --> 00:50:41,520
Speaker 1: being created here? The bowl case is, you have no

1038
00:50:41,640 --> 00:50:44,880
Speaker 1: idea all of the endless possibilities. It's like, what the

1039
00:50:44,880 --> 00:50:49,440
Speaker 1: destruction of Hollywood and creative industry to create, like, you

1040
00:50:49,480 --> 00:50:52,840
Speaker 1: know again, slot video because that's where things are mostly

1041
00:50:52,840 --> 00:50:53,479
Speaker 1: trending right.

1042
00:50:53,400 --> 00:50:55,600
Speaker 4: Now, right, we don't need a video of an elephant

1043
00:50:55,840 --> 00:50:58,359
Speaker 4: going through a like a jazz switch.

1044
00:50:58,400 --> 00:50:59,960
Speaker 1: Yeah, we don't need that, we don't, I agree with you.

1045
00:51:00,239 --> 00:51:01,960
Speaker 3: Yeah, yeah.

1046
00:51:02,200 --> 00:51:05,839
Speaker 4: So the big tech platforms spent the nineties and two

1047
00:51:05,840 --> 00:51:10,520
Speaker 4: thousands in early twenty tens basically destroying the news media

1048
00:51:11,560 --> 00:51:18,840
Speaker 4: and creating this new media where people just create stuff

1049
00:51:18,880 --> 00:51:22,120
Speaker 4: and share it with each other and don't trust any

1050
00:51:22,520 --> 00:51:23,960
Speaker 4: traditional sources.

1051
00:51:23,520 --> 00:51:25,040
Speaker 1: Of some benefits of that information.

1052
00:51:25,080 --> 00:51:27,440
Speaker 4: Some benefits, we're going to find out it might be

1053
00:51:27,480 --> 00:51:32,200
Speaker 4: some downside, some downsides as well. Yeah, And now that

1054
00:51:32,280 --> 00:51:35,200
Speaker 4: nobody trusts anything and there's no real traditional news media left,

1055
00:51:36,840 --> 00:51:39,880
Speaker 4: they're going to make it so that everybody can just

1056
00:51:40,480 --> 00:51:47,600
Speaker 4: make you know, authentic looking fake videos. And in order

1057
00:51:47,640 --> 00:51:50,440
Speaker 4: to do that, they're going to destroy as much of

1058
00:51:50,480 --> 00:51:55,240
Speaker 4: the Amazon as again to like and build data centers

1059
00:51:55,280 --> 00:51:58,719
Speaker 4: all over the United States triple or quadruple your electric bill,

1060
00:52:00,239 --> 00:52:04,640
Speaker 4: and yeah, like for that. The question for what is

1061
00:52:04,680 --> 00:52:07,560
Speaker 4: a key one Chris and I had on an author yesterday.

1062
00:52:07,560 --> 00:52:11,040
Speaker 4: It was like, well, the purpose of this, whether it's

1063
00:52:11,239 --> 00:52:14,520
Speaker 4: intended or not, is it's gonna kill everybody. So there's

1064
00:52:14,600 --> 00:52:16,880
Speaker 4: like that, and it is true that a lot of

1065
00:52:16,920 --> 00:52:18,600
Speaker 4: people in the AI world are like, yeah, there's a

1066
00:52:18,680 --> 00:52:21,080
Speaker 4: twenty percent chance of an existential event as a result

1067
00:52:21,080 --> 00:52:21,279
Speaker 4: of this.

1068
00:52:21,680 --> 00:52:24,080
Speaker 1: I don't really but even yeah, I don't believe.

1069
00:52:24,200 --> 00:52:26,120
Speaker 3: I hope it's just slop.

1070
00:52:26,320 --> 00:52:29,080
Speaker 4: Yeah, and that it plateaus out it slop.

1071
00:52:29,239 --> 00:52:30,319
Speaker 3: That's my that's my hope.

1072
00:52:30,400 --> 00:52:31,920
Speaker 1: That's what I think. I mean, I think this is

1073
00:52:31,960 --> 00:52:34,319
Speaker 1: the end state, Like this is the reality is if

1074
00:52:34,320 --> 00:52:36,719
Speaker 1: you look at the way that how by the way,

1075
00:52:36,719 --> 00:52:39,000
Speaker 1: how are they even paying for all of this? You know,

1076
00:52:39,800 --> 00:52:43,600
Speaker 1: AI data center? Where does it come to scroll algorithm?

1077
00:52:43,760 --> 00:52:48,280
Speaker 1: That's it? You know, massive amounts of screen time, addiction period, Twitter, Facebook,

1078
00:52:48,320 --> 00:52:50,400
Speaker 1: they all have the same business model. It's just spend

1079
00:52:50,400 --> 00:52:53,520
Speaker 1: as much time on platform as possible, sell as many

1080
00:52:53,560 --> 00:52:56,319
Speaker 1: ads as possible. That's it. And so that's how they're

1081
00:52:56,320 --> 00:52:59,080
Speaker 1: paying for this, for for the AI data centers, for

1082
00:52:59,120 --> 00:53:03,160
Speaker 1: the project with the hope that you get artificial general intelligence.

1083
00:53:03,320 --> 00:53:06,759
Speaker 1: But the end state seems pretty simple. AI to the

1084
00:53:06,800 --> 00:53:09,319
Speaker 1: extent that it's used in the workplace is for shit

1085
00:53:09,560 --> 00:53:14,680
Speaker 1: that nobody thought is game changing. Oh it's summarized my emails. Awesome,

1086
00:53:14,920 --> 00:53:18,239
Speaker 1: summarize my note taking. You know. I've talked previously because

1087
00:53:18,280 --> 00:53:21,000
Speaker 1: I actually know people who work in like really big corporations,

1088
00:53:21,000 --> 00:53:23,200
Speaker 1: and I would like, tell me about how you use AI.

1089
00:53:23,239 --> 00:53:24,920
Speaker 1: They're like, oh, it's great. We cut out the entry

1090
00:53:25,000 --> 00:53:27,799
Speaker 1: level workers. I was like, so that's it, and they're like, yeah,

1091
00:53:27,800 --> 00:53:30,959
Speaker 1: that's it, you know it. We use Microsoft teams. Lets

1092
00:53:30,960 --> 00:53:33,279
Speaker 1: me summarize my notes and then we send that for

1093
00:53:33,360 --> 00:53:35,759
Speaker 1: an agenda. Somebody who is entry level used to have

1094
00:53:35,760 --> 00:53:37,319
Speaker 1: to do that before. And I was like, but you're

1095
00:53:37,320 --> 00:53:39,160
Speaker 1: still having the meetings. You're still doing like, oh, yeah,

1096
00:53:39,200 --> 00:53:41,440
Speaker 1: it hasn't changed any actual decision making.

1097
00:53:41,840 --> 00:53:42,839
Speaker 3: A bunch of twenty four year old.

1098
00:53:42,920 --> 00:53:46,040
Speaker 1: To be fair, let's say, in coding and in technology

1099
00:53:46,400 --> 00:53:48,600
Speaker 1: is a little bit different, right, you can actually have AI.

1100
00:53:48,680 --> 00:53:51,120
Speaker 1: I think AI is quite good at coding up to

1101
00:53:51,160 --> 00:53:53,439
Speaker 1: like ninety four ninety five percent and doing a lot

1102
00:53:53,480 --> 00:53:58,080
Speaker 1: of the previously more difficult or like the time consuming work,

1103
00:53:58,320 --> 00:54:01,000
Speaker 1: leaving time for creative Great. Okay, but I don't yet

1104
00:54:01,040 --> 00:54:04,680
Speaker 1: see evidence of like a massive game changing thing which

1105
00:54:04,760 --> 00:54:07,759
Speaker 1: doesn't just lead to the tech power law distribution which

1106
00:54:07,800 --> 00:54:09,919
Speaker 1: makes a bunch of people in Silicon Valley a lot richer,

1107
00:54:10,120 --> 00:54:12,680
Speaker 1: because instead, what's happened is that AI has led to

1108
00:54:12,920 --> 00:54:16,600
Speaker 1: mostly job loss or not really real job growth while

1109
00:54:16,920 --> 00:54:20,359
Speaker 1: they're still pumping all this money into the industry. Plus

1110
00:54:20,440 --> 00:54:22,759
Speaker 1: the data center question, it just leads to this thing

1111
00:54:22,760 --> 00:54:24,799
Speaker 1: where're like, what are we all doing here? You know,

1112
00:54:24,840 --> 00:54:28,680
Speaker 1: for what? And I don't think people understand. If it

1113
00:54:28,719 --> 00:54:34,080
Speaker 1: were not for AI data center spend, GDP would be contracting, right,

1114
00:54:34,160 --> 00:54:39,120
Speaker 1: the only reason that we have increasing the recession otherwise

1115
00:54:39,280 --> 00:54:41,759
Speaker 1: you're exactly right is and the data bears all of

1116
00:54:41,800 --> 00:54:43,560
Speaker 1: this out. We've played it here on the show many

1117
00:54:43,560 --> 00:54:47,799
Speaker 1: times before. Is without the data center capital expenditure from

1118
00:54:47,800 --> 00:54:51,640
Speaker 1: the technology industry, there is no GDP growth. And in fact,

1119
00:54:51,680 --> 00:54:54,560
Speaker 1: I was just reading this morning one of the consequences

1120
00:54:54,880 --> 00:54:59,640
Speaker 1: of the nineteen nineties telecom boom, like the amount of

1121
00:54:59,640 --> 00:55:03,280
Speaker 1: money that went into that, is that what private capital

1122
00:55:03,400 --> 00:55:05,960
Speaker 1: all understood in the nineties, there's only one way to

1123
00:55:06,000 --> 00:55:08,200
Speaker 1: return money in the middle of a mania or a

1124
00:55:08,239 --> 00:55:10,600
Speaker 1: craze is to invest in the mania or the cruise

1125
00:55:11,000 --> 00:55:13,719
Speaker 1: that has a huge opportunity costs. Because what it meant

1126
00:55:13,760 --> 00:55:16,560
Speaker 1: in the nineties was that small businesses that are doing

1127
00:55:16,640 --> 00:55:21,279
Speaker 1: traditional manufacturing were not going to get capital expenditure and

1128
00:55:21,480 --> 00:55:24,839
Speaker 1: or any investment. All private investment was chasing the same thing.

1129
00:55:25,200 --> 00:55:28,000
Speaker 1: At the same time of the nineteen nineties, what happened

1130
00:55:28,120 --> 00:55:31,160
Speaker 1: the end of the Cold War NAFTA, PNTR with China,

1131
00:55:31,320 --> 00:55:34,000
Speaker 1: which means not only do they get the reduced amount

1132
00:55:34,000 --> 00:55:36,600
Speaker 1: of money that they should have been owed absent the

1133
00:55:36,640 --> 00:55:41,799
Speaker 1: AI or the telecom boom, they also face growing international competition. Well,

1134
00:55:41,840 --> 00:55:44,319
Speaker 1: I think we're in a very similar thing right now.

1135
00:55:45,080 --> 00:55:48,480
Speaker 1: You have all of this money, stock, the whole s

1136
00:55:48,520 --> 00:55:50,360
Speaker 1: and P five hundred the government shuts down on the

1137
00:55:50,440 --> 00:55:53,719
Speaker 1: SP five hundred goes up. Why because of ANVIDIA, Right

1138
00:55:53,920 --> 00:55:56,360
Speaker 1: you know, you're looking at these stock valuations and everything.

1139
00:55:57,280 --> 00:55:59,040
Speaker 1: None of it makes any sense. And then at the

1140
00:55:59,080 --> 00:56:02,400
Speaker 1: same time, with Trump administration's trade policy, what you have

1141
00:56:02,920 --> 00:56:06,799
Speaker 1: is a chilling on domestic investment and manufacture, which means

1142
00:56:06,840 --> 00:56:09,560
Speaker 1: again any money in the economy that people have to

1143
00:56:09,600 --> 00:56:11,920
Speaker 1: spare is just going towards a SAA So I know

1144
00:56:11,960 --> 00:56:15,239
Speaker 1: this is kind of tedious, but there are serious implications

1145
00:56:15,239 --> 00:56:17,560
Speaker 1: for all of for this for all of us, not

1146
00:56:17,600 --> 00:56:19,560
Speaker 1: just in terms of let's say you own a small business.

1147
00:56:19,560 --> 00:56:21,319
Speaker 1: You wanted to buy a new tractor or whatever, and

1148
00:56:21,360 --> 00:56:24,080
Speaker 1: you're you're owned by private equity. Well, private equity doesn't

1149
00:56:24,080 --> 00:56:25,640
Speaker 1: have a lot of incentive to make sure that you're

1150
00:56:25,640 --> 00:56:27,960
Speaker 1: buying a bunch of new construction equipment. They would much

1151
00:56:28,040 --> 00:56:31,040
Speaker 1: rather go in and invest in some AI startup or

1152
00:56:31,080 --> 00:56:33,400
Speaker 1: something like that. That's a real effect. And then add

1153
00:56:33,400 --> 00:56:35,600
Speaker 1: the Trump trade stuff on top of that, it's a

1154
00:56:35,600 --> 00:56:36,280
Speaker 1: real problem.

1155
00:56:36,360 --> 00:56:38,879
Speaker 3: Yeah, yeah, yeah, And when that bubble.

1156
00:56:38,560 --> 00:56:42,799
Speaker 4: Pops, because even the like Zuckerberg's of the world think

1157
00:56:42,840 --> 00:56:44,839
Speaker 4: that the bubble will pop. Their argument is that it'll

1158
00:56:44,840 --> 00:56:47,640
Speaker 4: pop and it will be like the railroads, it will

1159
00:56:47,640 --> 00:56:49,760
Speaker 4: be like the telecoms that it will have left behind.

1160
00:56:49,880 --> 00:56:52,200
Speaker 1: Yes, the infrastructure, built instructure.

1161
00:56:52,239 --> 00:56:55,319
Speaker 4: So bubble pops, you bunch a bunch of people get

1162
00:56:55,440 --> 00:56:57,960
Speaker 4: washed out. Zuckerberg, as he said, that'll create a lot

1163
00:56:57,960 --> 00:57:01,880
Speaker 4: of opportunity to buy assets cost So he continues to

1164
00:57:01,920 --> 00:57:07,360
Speaker 4: then concentrate his market power and then and then builds

1165
00:57:07,360 --> 00:57:12,200
Speaker 4: it up from there. But that's a So that's Zuckerberg

1166
00:57:12,239 --> 00:57:15,920
Speaker 4: and others are baking in financial crisis as like an

1167
00:57:15,920 --> 00:57:19,360
Speaker 4: inevitable result. Just a when not if.

1168
00:57:19,400 --> 00:57:21,479
Speaker 1: Financial crash just means nothing to somebody worth one hundred

1169
00:57:21,480 --> 00:57:23,520
Speaker 1: and fifty billion, right, one hundred and fifteen means.

1170
00:57:23,720 --> 00:57:25,400
Speaker 3: It means cheaper assets to buy.

1171
00:57:25,680 --> 00:57:28,520
Speaker 1: Yeah, yeah, a great point. If you're worth one hundred

1172
00:57:28,520 --> 00:57:30,880
Speaker 1: fifty billion, even if you go in half to seventy five,

1173
00:57:30,920 --> 00:57:33,200
Speaker 1: that means nothing to you. If you are one hundred

1174
00:57:33,240 --> 00:57:35,520
Speaker 1: thousand and you go to seventy five thousand, that means

1175
00:57:35,560 --> 00:57:38,160
Speaker 1: a lot to you, right, Okay, So like that's the

1176
00:57:38,200 --> 00:57:40,880
Speaker 1: point that these people never seem to quite understand, is

1177
00:57:40,880 --> 00:57:44,080
Speaker 1: that the people who suffer from these financial bubbles are

1178
00:57:44,120 --> 00:57:46,920
Speaker 1: not the people who cause them in the first place.

1179
00:57:47,040 --> 00:57:49,560
Speaker 1: By the way, our producer Griffin has been flagging some

1180
00:57:49,640 --> 00:57:52,600
Speaker 1: of this weird Hollywood stuff to us. Let's go and

1181
00:57:52,600 --> 00:57:55,080
Speaker 1: put these up here on the screen. So there is

1182
00:57:55,200 --> 00:58:03,000
Speaker 1: now a new AI director. The Italian producer Andrea Ervolino

1183
00:58:03,480 --> 00:58:07,640
Speaker 1: has unveiled a feature helmed by a virtual auteur, and

1184
00:58:07,880 --> 00:58:11,600
Speaker 1: what it does is that the Fellini AI would be

1185
00:58:11,680 --> 00:58:15,280
Speaker 1: housed inside of his company, which would act as a

1186
00:58:15,320 --> 00:58:19,320
Speaker 1: quote human in the loop supervisor and producer who guides

1187
00:58:19,400 --> 00:58:23,040
Speaker 1: and monitors the technology, and quote, you can imagine a

1188
00:58:23,080 --> 00:58:25,800
Speaker 1: future in which only one percent of humanity still works,

1189
00:58:26,240 --> 00:58:29,720
Speaker 1: transforming labor into a symbolic ritual, while the rest of

1190
00:58:29,720 --> 00:58:33,640
Speaker 1: the population lives in the freedom and leisure produced by machines.

1191
00:58:33,760 --> 00:58:36,280
Speaker 1: The log line states for this new AI produced movie

1192
00:58:36,400 --> 00:58:38,880
Speaker 1: that the last workers become the final masks of a

1193
00:58:38,960 --> 00:58:43,280
Speaker 1: humanity that resists the insolence of labor. I don't know, Ryan,

1194
00:58:44,560 --> 00:58:48,400
Speaker 1: I'm not so bought into some sort of Matrix style fantasy.

1195
00:58:48,480 --> 00:58:50,520
Speaker 1: And then on the right there you see that they

1196
00:58:50,560 --> 00:58:54,240
Speaker 1: talk about the Hollywood AI is ready to crush Hollywood

1197
00:58:54,400 --> 00:58:56,920
Speaker 1: as we have known it with these AI actors.

1198
00:58:57,960 --> 00:58:59,800
Speaker 3: Fake actress is going to get an agent.

1199
00:59:00,120 --> 00:59:03,520
Speaker 1: And that's where I just don't even you know, I

1200
00:59:03,520 --> 00:59:06,160
Speaker 1: can't even really understand, you know, what it all means,

1201
00:59:06,200 --> 00:59:09,360
Speaker 1: because they say, we may not even have real movie

1202
00:59:09,400 --> 00:59:14,200
Speaker 1: stars anymore. We'll soon have computer generated actors aspirational celebrities.

1203
00:59:14,480 --> 00:59:16,800
Speaker 1: That is the future currently imagined by the founder of

1204
00:59:16,880 --> 00:59:19,640
Speaker 1: this AI actor. And what they said is that in

1205
00:59:19,680 --> 00:59:24,200
Speaker 1: this new lab, they're hyper real digital stars. The actresses

1206
00:59:24,240 --> 00:59:28,640
Speaker 1: said that they would produce sketch video and maybe signing

1207
00:59:28,800 --> 00:59:33,240
Speaker 1: to a future talent agency. Basically, their likenesses would be

1208
00:59:33,280 --> 00:59:36,760
Speaker 1: controlled by some sort of corporate conglomerate and that they

1209
00:59:36,800 --> 00:59:41,520
Speaker 1: would then be featured in movies and licensed to different

1210
00:59:41,520 --> 00:59:45,880
Speaker 1: commercials and stars. This is basically an a rature of

1211
00:59:45,960 --> 00:59:48,680
Speaker 1: humanity as we know it, and it's one of those

1212
00:59:48,760 --> 00:59:52,240
Speaker 1: where the matrix was I guess the documentary. And also

1213
00:59:52,360 --> 00:59:57,440
Speaker 1: though the government and the level of skepticism that is

1214
00:59:57,520 --> 01:00:00,560
Speaker 1: required is not happening, because I said, on this state level,

1215
01:00:00,800 --> 01:00:04,680
Speaker 1: it seems by my immediate perusal that moststate legislators think

1216
01:00:04,720 --> 01:00:06,640
Speaker 1: data centers are a good thing because of money, right,

1217
01:00:06,640 --> 01:00:08,880
Speaker 1: because they're getting donated to and because they've given these

1218
01:00:08,880 --> 01:00:11,440
Speaker 1: fake statistics. But I think the people at the very

1219
01:00:11,560 --> 01:00:15,040
Speaker 1: least are deeply skeptical of whatever the hell all of

1220
01:00:15,080 --> 01:00:17,280
Speaker 1: this is. So I just wonder if there can ever

1221
01:00:17,320 --> 01:00:21,200
Speaker 1: be any sort of democratic pushback. The technology companies are

1222
01:00:21,280 --> 01:00:24,560
Speaker 1: betting that they can go, they can leap so forward

1223
01:00:24,920 --> 01:00:28,720
Speaker 1: before any skepticism happens, that they can just get there

1224
01:00:29,080 --> 01:00:31,400
Speaker 1: before anybody really wakes up to what's going on.

1225
01:00:31,480 --> 01:00:35,320
Speaker 4: Yeah, and when you think about the arc of all

1226
01:00:35,360 --> 01:00:40,240
Speaker 4: of kind of earth history. And you you know, people

1227
01:00:40,320 --> 01:00:42,760
Speaker 4: say that we're now in the midst of the sixth

1228
01:00:42,920 --> 01:00:46,720
Speaker 4: Great Extinction, like you know, sixth mass. I've seen people

1229
01:00:46,760 --> 01:00:50,560
Speaker 4: say that, yeah, and statistically like it's accurate, like so

1230
01:00:50,720 --> 01:00:55,480
Speaker 4: many different species, both plant and animal are dying off,

1231
01:00:55,520 --> 01:01:01,800
Speaker 4: and they scientists can demonstrate that it is because of humanity,

1232
01:01:01,880 --> 01:01:03,760
Speaker 4: like we just we gobble everything up.

1233
01:01:05,560 --> 01:01:09,280
Speaker 3: And so when you think about that in a moral.

1234
01:01:08,960 --> 01:01:11,520
Speaker 4: Sense, which is difficult to do because it's like species

1235
01:01:11,800 --> 01:01:14,080
Speaker 4: are often a moral you think you have to think

1236
01:01:14,080 --> 01:01:16,360
Speaker 4: about it in a moral sense because humans are the

1237
01:01:16,400 --> 01:01:18,560
Speaker 4: first ones that have to invent morality. And so you

1238
01:01:18,600 --> 01:01:21,760
Speaker 4: think about, Okay, the costs to the Earth have been

1239
01:01:23,240 --> 01:01:24,120
Speaker 4: existential to.

1240
01:01:26,120 --> 01:01:27,600
Speaker 3: Thousands upon thousands.

1241
01:01:27,240 --> 01:01:31,720
Speaker 4: Of species, but it has produced what humanity can produce,

1242
01:01:32,560 --> 01:01:36,560
Speaker 4: which is love, which is art. Shakespeare as a stand in,

1243
01:01:36,840 --> 01:01:43,040
Speaker 4: like those developments represent a break from what existed before

1244
01:01:43,120 --> 01:01:48,560
Speaker 4: the other five extinctions. Now we're not even gonna have that, Like,

1245
01:01:48,800 --> 01:01:52,400
Speaker 4: what is humanity bringing to the earth other than misery

1246
01:01:52,440 --> 01:01:56,640
Speaker 4: and despair? If we're not producing more Shakespeare's I agree with.

1247
01:01:56,560 --> 01:01:59,600
Speaker 1: You, I'm with you. This is what the fundamental like

1248
01:01:59,640 --> 01:02:03,040
Speaker 1: anti humanness of it is something that's very concerning to me.

1249
01:02:03,360 --> 01:02:06,960
Speaker 1: I also am just concerned at the lack of interest

1250
01:02:07,240 --> 01:02:11,439
Speaker 1: that legislators and others have in any of what's going

1251
01:02:11,480 --> 01:02:15,400
Speaker 1: on right now, and in particular they seem instead to

1252
01:02:15,440 --> 01:02:17,880
Speaker 1: just be bought and paid for and just waiting for

1253
01:02:17,920 --> 01:02:20,640
Speaker 1: something to happen before we all have to grapple with it.

1254
01:02:20,720 --> 01:02:23,760
Speaker 1: So anyway, yeah, we're all paying higher electricity bills so

1255
01:02:23,800 --> 01:02:27,640
Speaker 1: that Sora can generate slop videos for kids to be

1256
01:02:27,680 --> 01:02:31,000
Speaker 1: addicted on TikTok and YouTube shorts in the future. What

1257
01:02:31,040 --> 01:02:32,560
Speaker 1: a great investment for US alves