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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 this show.

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Speaker 3: This is the only place where you can find honest

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Speaker 3: perspectives from the left and the right that simply does

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Speaker 3: 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 3: We need your help to build the future of independent

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Speaker 3: dot com.

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Speaker 1: Good morning, everybody, Happy Tuesday. Have an amazing show for

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Speaker 1: everybody today. What do we have, Crystal?

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Speaker 4: Indeed, we do.

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Speaker 2: Many interesting stories unfolding this week. We're going to take

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Speaker 2: another look at deep Seek, which has completely royaled the

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Speaker 2: American stock market.

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Speaker 4: What is going to happen next? We also had.

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Speaker 2: Trump Way and what I found to be a rather

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Speaker 2: amusing fashion so we get to.

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Speaker 1: It's amusing no matter what.

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Speaker 4: Yeah, okay, all of that.

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Speaker 2: Also, we're going to take a look at egg prices

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Speaker 2: which are spiking and ask the question whether potential inflation

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Speaker 2: across the board is on the menu, and what sort

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Speaker 2: of political problems this could pose for the Trump administration.

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Speaker 2: There are a number of significant confirmation hearings that are

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Speaker 2: happening this week. Among some of the I guess most

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Speaker 2: controversial or most uncertain to past confirmation nominees, we're talking

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Speaker 2: about Tulca Gabbard RFK Junior Cash Hotel in particular, and

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Speaker 2: few Republicans very unhappy with the Labor Department pick because

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Speaker 2: she had supported the pro Act. So a lot to

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Speaker 2: get into there about the various divisions within the Republican Party.

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Speaker 2: We're also going to take a look at some of

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Speaker 2: the things we've learned since those horrific wildfires in LA,

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Speaker 2: including about the way that landlords responded with mass price gouging,

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Speaker 2: which should be illegal is actually technically illegal. Whether that's

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Speaker 2: going to be enforced or not is another question. And

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Speaker 2: how private equity roll ups of fire engine companies, so

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Speaker 2: the companies that make and sell fire trucks, how that

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Speaker 2: really contributed to the lack of preparation and ability to

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Speaker 2: fully respond to those wildfires in LA. Which is truly

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Speaker 2: a national story based on this National Private Act. But

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Speaker 2: you roll ups will take a look at that. AOC

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Speaker 2: is now trashing Joe Biden. Kind of interesting at this point.

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Speaker 2: What does this say about the future of Democratic Party

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Speaker 2: and where things are heading. Charlemagne also weigh in on that,

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Speaker 2: and Bill Gates trashing Elon Musk some billionaire versus billionaire violence.

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Speaker 2: Always interesting to take a look at that one as well.

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Speaker 1: Yeah, it's always amusing.

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Speaker 3: All right, let's get to Oh, actually, before we get

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Speaker 3: to that, thank you to everybody. He's been signing up

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Speaker 3: premium subscribers. We're doing our AMA later today. So if

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Speaker 3: you want to be able to participate in those, of

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Speaker 3: course breaking points dot com, go ahead and sign up.

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Speaker 1: But let's get to deep Seek.

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Speaker 3: Deep Seek has completely not only royal the international stock market,

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Speaker 3: it phases faces now big questions here for our own economy,

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Speaker 3: of our tech companies, some government spending. It links to Stargate,

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Speaker 3: to China. There are a lot of geopolitical implications. So

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Speaker 3: it's absolutely fascinating what's happening. President Trump actually reacted to

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Speaker 3: the release of Deep Seek yesterday when he was speaking

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Speaker 3: to members of Congress.

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Speaker 1: Let's take a listen to what he had to say.

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Speaker 5: This is very new when you hear a deep seek

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Speaker 5: when you hear somebody come up with something. We always

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Speaker 5: have the ideas, we're always first, So I would say

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Speaker 5: that's a positive. That could be very much a positive development.

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Speaker 5: So instead of spending billions and billions, you'll spend less

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Speaker 5: and you'll come up with hopefully the same solution.

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Speaker 3: So there's some praise for deep seek from President Trump.

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Speaker 3: He says, we always have the ideas, we're always first,

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Speaker 3: and instead of billions, you spend less and you're going

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Speaker 3: to come up with hopefully the same solution. And in

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Speaker 3: terms of deep sing, you guys did a good job

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Speaker 3: yesterday of breaking it all down. But it really is

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Speaker 3: fascinating and effectively, what we have seen is the release

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Speaker 3: of an equivalent technological model to the latest one from

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Speaker 3: chat GPT, except it was been able to do for

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Speaker 3: far less the cost of computing, not only in its development,

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Speaker 3: but in the overall inferences, as in the number, the

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Speaker 3: cost per inference, as in every time you put something in,

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Speaker 3: its ability to spit out a roughly equivalent result is

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Speaker 3: dramatically cheaper than where they are now. Why did that

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Speaker 3: cause the international stock market to react in specifically and

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Speaker 3: video stock and all these big tech companies. It's because

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Speaker 3: they spend, of course, billions and billions of hundreds of

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Speaker 3: billions of dollars on their capital requirements to build these

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Speaker 3: data centers to train their models. And Vidia also the

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Speaker 3: reason that its stock has exploded is that it's extremely expensive.

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Speaker 3: Chips highly profitable to the company have been the ones

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Speaker 3: that have been bought en mass and are the major

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Speaker 3: expenditure by these tech companies. So the idea being if

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Speaker 3: you can train a very sophisticated AI model for much

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Speaker 3: less the cost with less sophisticated chips, than the profit

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Speaker 3: margin of that company will go down. And Andrew ross

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Speaker 3: Sorkin over at CNBC had a reaction to this and

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Speaker 3: kind of broke down both his surprise at the model

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Speaker 3: and some of the implications.

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Speaker 1: Let's take a listen.

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Speaker 6: Now you can take a look right now at the

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Speaker 6: AI related stock So in Nvidia, ARM, AMD, Microsoft, Meta,

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Speaker 6: interesting on that list given it's open source. We got

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Speaker 6: to talk about the open.

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Speaker 1: Source, closed source bit of this as well.

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Speaker 3: And then you have soccer to see Nvidia down by

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Speaker 3: more than twelve percent right.

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Speaker 6: Now, absolutely, and then you have global chip stocks also

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Speaker 6: in the red across the board, Asma holdings and others.

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Speaker 1: There is the question I will.

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Speaker 6: Say, Alexander Wang made the point last week, and it's

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Speaker 6: become sort of the question mark about all of this,

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Speaker 6: which is, you know, he suggested on our air that

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Speaker 6: it is possible that they were using some of the

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Speaker 6: highest performing in video chips, perhaps as maybe as fifty

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Speaker 6: thousand of them to build this model. Now, and they

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Speaker 6: weren't supposed to have those chips.

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Speaker 1: Right.

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Speaker 4: If that's true, not the size.

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Speaker 6: The dynamic is different. If it's not true, then maybe

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Speaker 6: all bets are off. It's possible, by the way, even

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Speaker 6: if it is true, meaning even if they use those

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Speaker 6: chips to create this, or at least partially to create this,

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Speaker 6: it is still a significantly more efficient and better model.

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Speaker 6: I think everybody agrees that right this moment. I mean,

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Speaker 6: I don't know if you did.

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Speaker 5: You get the play.

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Speaker 6: It is mind blowing.

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Speaker 4: It looks really great.

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Speaker 3: I mean, it feels like it's that it's open source

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Speaker 3: so people can test this out themselves.

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Speaker 6: But I can say all the tests that I do

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Speaker 6: just to see whether I think you ask whether I

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Speaker 6: think the writing is better, whether I think it can

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Speaker 6: answer certain question. I mean, it was not only faster

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Speaker 6: it was more human. The reasoning is shocking. I mean

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Speaker 6: there were moments where I was like, oh my god.

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Speaker 1: This we are. We are so much you could.

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Speaker 6: Feel the step change as a person. It was, I

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Speaker 6: will also say, as exciting as it was, there was

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Speaker 6: an element where I became scared because I thought, oh,

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Speaker 6: you know, I had the opportunity to talk to all

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Speaker 6: these people last week and they all said the futures

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Speaker 6: here and da da da da dah. And then you

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Speaker 6: sort of see it and you go, oh, okay, I

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Speaker 6: feel you, you know, in a different sort of visceral way.

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Speaker 6: So yes, I think this is all happening at a

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Speaker 6: level that I'm you when you mark your sort of

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Speaker 6: AI history timeline in life. I think this week, this

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Speaker 6: past week, today, and everything else will be on it.

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Speaker 1: Super fascinating in terms of his insight.

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Speaker 3: Also, he was just at Davos, of course, and he

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Speaker 3: was speaking with all of these tech CEOs, so I

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Speaker 3: think he in particular can place this not a surprise

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Speaker 3: that this was released in the first week of the

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Speaker 3: Trump administration, and I actually think it really gets to

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Speaker 3: something that you and I hit on in our inaugural

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Speaker 3: coverage when the history of this period is written. It

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Speaker 3: is very likely that AI and not many of the

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Speaker 3: controversies that we spend our time talking about, will be

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Speaker 3: the most consequential and the most enduring for our overall

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Speaker 3: economic life. So the step change is here, and the

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Speaker 3: step change and the ideas behind it are interesting.

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Speaker 1: Now.

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Speaker 3: As he said, I think there's some serious asterisks to

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Speaker 3: put on Deep Seek. One is this idea that was

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Speaker 3: trained for quote unquote six million dollars almost certainly not

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Speaker 3: true from everything I've looked at. Oh the idea also

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Speaker 3: that it may not have been possible without all of

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Speaker 3: the hundreds of billions, perhaps trillions spent by our tech

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Speaker 3: companies because it was able to train itself off of that.

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Speaker 3: But listen, you work smarter, not harder, right, But that's

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Speaker 3: part of what you really have learned here.

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Speaker 1: What does it mean for the future.

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Speaker 3: I have no idea, And I think that's the open

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Speaker 3: question mark here for government policy for our own tech

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Speaker 3: companies and the fundamental question of the US economy and

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Speaker 3: our own consumers in this because like it or not,

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Speaker 3: and this is a point that our friend Joe Wisenthal made,

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Speaker 3: is that look, America, the way that we do retirement

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Speaker 3: is basically like social security is like, here's enough to eat,

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Speaker 3: but we're all you know, most night, what sixty seventy

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Speaker 3: percent of households, their overall retirement is stuck in the

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Speaker 3: stock market. And even if you're not invested in an

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Speaker 3: n video or whatever, you likely have overwhelming exposure to

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Speaker 3: it through the S and P five hundred or buying

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Speaker 3: index ones.

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Speaker 1: It's not just us. The entire Western world is caught

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Speaker 1: up in this.

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Speaker 3: And so it's some fundamental questions too about if AI

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Speaker 3: is to replace humanity, It's like, well, then the idea

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Speaker 3: is humanity should have a stake in that. And if

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Speaker 3: you know, we're going to lose that steak and it's

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Speaker 3: all going to be rolled up and consolidated in China,

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Speaker 3: massive question mark for America, for our future, our ability

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Speaker 3: to retire.

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Speaker 1: There's lots of things going on.

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Speaker 2: So the Wisenthal quote you're referring to, which I think

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Speaker 2: is a really important piece of this, as he says,

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Speaker 2: I think a big macro fact about the American economy

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Speaker 2: is we have a de facto social contract where financial

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Speaker 2: assets are expected to go up over time. Assets going

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Speaker 2: up is how we pay for college retirements and so forth.

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Speaker 2: There's been a lot of anxiety about competition with China

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Speaker 2: manufactured goods over the last several years. But manufacturing is

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Speaker 2: not what drives the US stock market higher. When we're

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Speaker 2: talking about big tech and software, well, now we're getting

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Speaker 2: right to the heart of how people fund their lives.

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Speaker 4: It's a big deal.

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Speaker 2: So that gets to the core of what was so

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Speaker 2: unsettling for many of these individuals when this development occurred,

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Speaker 2: and it really does shake a lot of both micro

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Speaker 2: and macro assumptions that have been made about the US economy,

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Speaker 2: the US social contract, the US tech sector. I mean,

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Speaker 2: one of those assumptions was that the US companies were

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Speaker 2: significantly ahead, several years ahead. That clearly is not the case.

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Speaker 2: Another assumption which was really clear and apparent in the

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Speaker 2: big you know, five hundred billion dollar Stargate announcement from Trump,

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Speaker 2: which is all about building out these massive data centers

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Speaker 2: which take massive amounts of energy, et cetera, et cetera.

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Speaker 2: Even floated like we should have coal fired power plants

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Speaker 2: next to all of these data centers, that's how energy

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Speaker 2: intensive they are. So that was the assumption was that

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Speaker 2: this you know, compute was really the limited the limiting factor,

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Speaker 2: and you just need to throw billions of dollars at

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Speaker 2: building out these larger and larger stacks. This really blows

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Speaker 2: up that assumption and shows you there is a different

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Speaker 2: approach that you could take which is much less, much

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Speaker 2: more efficient, and requires much much less in terms of

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Speaker 2: capital investment. Another assumption that was operating both under the

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Speaker 2: Biden and the Trump administration was that these restrictions on

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Speaker 2: chips to China, that this would really hurt them.

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Speaker 4: It didn't.

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Speaker 2: In a way, it actually helped them because you know,

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Speaker 2: they say, uh, necessity is the mother of invention, and

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Speaker 2: whether you believe the five million dollar number, you think

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Speaker 2: that they had significantly more. There's no doubt that they

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Speaker 2: accomplished this much more efficiently than anyone thought was possibly.

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Speaker 2: You know, they published a long technical paper which is

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Speaker 2: way over my head to be able to decipher, but

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Speaker 2: people who know what they're talking about looked at it

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Speaker 2: and were like, yes, there were significant innovations here in

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Speaker 2: the way that they approached it.

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Speaker 4: It's not like they just could copy and paste chat GPT.

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Speaker 2: They genuinely innovated in the way that they developed this technology.

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Speaker 2: So the idea that these chips restrictions would really hurt

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Speaker 2: them and hobble them and decimate their tech industry. Obviously,

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Speaker 2: that is, you know, that is out the window. Another

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Speaker 2: assumption which already was debated within the US tech community,

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Speaker 2: because you have Meta, which is sort of pursuing an

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Speaker 2: open model, and you have open Ai, which has a

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Speaker 2: you know, sort of famously closed model.

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Speaker 4: Originally was supposed to be open. Now it's closed.

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Speaker 2: Now it's in partnership with Microsoft, et cetera, et cetera.

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Speaker 4: But there was kind of an.

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Speaker 2: Assumption that these closed systems would be the way to go,

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Speaker 2: these closed proprietary systems would be the way to go.

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Speaker 2: Deepsecretally blows that up as well. With this open source

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Speaker 2: you know, anyone can use it. If you download the

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Speaker 2: app on your phone, then yes it's hosted on Chinese servers,

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Speaker 2: but you can download the whole thing onto you know,

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Speaker 2: and host it on your own server and be completely

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Speaker 2: disconnect from disconnected from that. Developers can view the entire

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Speaker 2: code like it's all there open for the public to

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Speaker 2: be able to see. And then the other thing that's

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Speaker 2: like the big question getting back to the social contract piece,

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Speaker 2: is that our variety of capitalism would be the most innovative,

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Speaker 2: would would create the largest number of innovations versus the

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Speaker 2: Chinese more state led model. And you know, this really

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Speaker 2: blows a hole in that in particular. And you know,

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Speaker 2: Matt Stoller could come on and talk a lot about

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Speaker 2: how a lot of these tech companies and I don't

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Speaker 2: want to say, I mean, obviously there was a lot

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Speaker 2: of research that went into chat, GPT and these other products,

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Speaker 2: et cetera. So I don't want to say they're not

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Speaker 2: out there doing research and like innovating and all of that.

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Speaker 2: That's certainly the case. But also a lot of these

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Speaker 2: companies have focused a lot of their time and effort

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Speaker 2: and energy more on financialization than they have on developing tech.

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Speaker 2: They've focused a lot of their time and energy effort

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Speaker 2: on cultivating political relationships, also on display of the Trump inauguration,

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Speaker 2: and you know, so there are a lot of dynamics

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Speaker 2: within both the tech sector and the American economy. One

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Speaker 2: other thing that are no Vertrand, who we had on

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Speaker 2: yesterday mentioned which I thought was really interesting and it's

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Speaker 2: hard to draw a straight line here, but it is

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Speaker 2: pretty interesting. You know, the Chinese government has said, listen,

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Speaker 2: we don't want our best and brightest going into you know,

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Speaker 2: financial speculation into the like you know, into a big

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Speaker 2: bank and hedge fund and all this sort of stuff.

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Speaker 2: We're going to from the top down suppress the salaries

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Speaker 2: there to try to push people more into this direction

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Speaker 2: of research and development.

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Speaker 4: Meanwhile, we haven't done that.

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Speaker 2: You know, many of our best in the briders still

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Speaker 2: go to Wall Street to cash in on giant you know,

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Speaker 2: giant checks, making exotic financial instruments, or even worse, going

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Speaker 2: into you know, crypto inventing completely fake and useless money,

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Speaker 2: which is just purely speculative. And again the Chinese government

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Speaker 2: there too has said like, we're just not doing that.

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Speaker 2: So there's a lot of reasons why even beyond this

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Speaker 2: immediate stock market crash, and our stock market value is

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Speaker 2: largely built upon giant tech companies and the speculation that

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Speaker 2: they will lead the AI revolution, that this will be

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Speaker 2: incredibly impactful in terms of their bottom line. So it's

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Speaker 2: built on a lot of hype. But even beyond that

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Speaker 2: immediate stock market reaction, this is a major shakeup and

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Speaker 2: really questions a lot of assumptions that have been held

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Speaker 2: in the industry and I think sort of society wide.

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Speaker 3: I will say, with great respect to Arno who created

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Speaker 3: deep Seak.

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Speaker 1: It was a hedge fund Chinese manager.

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Speaker 4: But no but' that's his point.

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Speaker 2: That's actually his point is that you have this, you know,

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Speaker 2: rather than focusing just exclusively on this hedge fund stuff,

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Speaker 2: he was able to attract people in for this quote

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Speaker 2: unquote side project, the best of the brightest graduates out

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Speaker 2: of Chinese universities to rather than you know, go to

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Speaker 2: the hedge fund.

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Speaker 4: To research the particular product.

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Speaker 2: So you know, again you can't exactly draw a straight line,

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Speaker 2: but I do think it is an interesting thing to

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Speaker 2: note that they've prioritized we're going to develop tech.

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Speaker 4: We're going to push.

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Speaker 2: You know, our top graduates into the sector. And obviously

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Speaker 2: we've made different choices here.

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Speaker 3: If we all want to get on a national project

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Speaker 3: of suppressing TikTok and you know, stopping the economy, where

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Speaker 3: what is it the number one job that a ten

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Speaker 3: year old wants as a YouTuber as YouTubers, let me

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Speaker 3: tell you something.

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Speaker 1: Don't do it, hey, do something else.

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Speaker 3: You know, you need to develop some skills and actually

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Speaker 3: get some education before you actually have anything interesting to say.

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Speaker 3: My only point being that I think there's a lot

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Speaker 3: of triumphalism around this idea that export controls didn't work.

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Speaker 3: I don't think that that's true. I think Alexander Wang

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Speaker 3: laid some of that out. I know you played it,

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Speaker 3: why don't we play it, and I'll.

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Speaker 1: React to it A four. Please, let's go ahead and

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Speaker 1: give it a Listen.

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Speaker 7: You know, the Chinese labs they have more h one

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Speaker 7: hundreds than people think, you know.

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Speaker 6: And these are the highest powered in video chips that

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Speaker 6: they were not supposed to have.

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Speaker 7: Yes, my understanding is that is that Deep Seek has

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Speaker 7: about fifty thousand each one hundreds, which they can't talk

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Speaker 7: about obviously because it is against the export controls that

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Speaker 7: the United States has put in place.

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Speaker 1: And I think it is.

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Speaker 7: True that, you know, I think they have more chips

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Speaker 7: than other people expect, but also going to go forward basis,

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Speaker 7: they are going to be limited by the chip controls

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Speaker 7: and the export controls that we have in place.

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Speaker 3: I think this is a very key point because first

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Speaker 3: of all, like you know, you can't exactly trust this

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Speaker 3: idea that they trained it on a bunch of chips,

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Speaker 3: which they're not allowed to say that they have if

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Speaker 3: you actually look at it. I had no idea, but

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Speaker 3: Nvidia's current export twenty percent are being sent to Singapore,

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Speaker 3: the tiny island nation of Singapore.

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Speaker 1: What's more likely.

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Speaker 3: Twenty percent of Nvidia exports are going to Singapore, or

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Speaker 3: like steel or any of these other things are getting

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Speaker 3: transhipped to China via export control evasion.

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Speaker 1: So that's probably the most likely.

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Speaker 3: Look the Chinese, I'm not saying I disrespect them in

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Speaker 3: any way or their technical accomplishments, but they have been

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Speaker 3: very upset about export controls for a reason is they

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Speaker 3: don't have the ability to manufacture this yet by themselves,

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Speaker 3: so they're very reliant on basically fighting US export control.

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Speaker 3: The second thing, as I understand, I'm going off of

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Speaker 3: a lot of analysis by the way of a guy

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Speaker 3: named Gavin Baker, really interesting guy AI expert and modeler,

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Speaker 3: and what he said is effectively that the breakthrough for

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Speaker 3: R one was not deep seek by the way, is

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Speaker 3: not possible without the ability to train off of all

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Speaker 3: of the trillions and trillions of dollars.

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Speaker 1: Now it's an open question now of what comes next.

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Speaker 3: So is this idea that they're able to continue these

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Speaker 3: breakthroughs at massive economies of scale much cheaper than hours,

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Speaker 3: and they can do the step change forward without the

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Speaker 3: continued burn of US companies. I mean again, I'm relying

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Speaker 3: on a lot of technical analyzes and this stuff, but

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Speaker 3: it does not appear to be the case. Another thing

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Speaker 3: that comes with export control is that it basically shapes

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Speaker 3: the future environment. The Biden administration actually, if anything, they

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Speaker 3: didn't act fast enough. It was only in twenty twenty

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Speaker 3: three that the really heavy export controls have come forward. Also,

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Speaker 3: I don't want to let Nvidio off the hook. They've

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Speaker 3: been heavily campaigning against this. They are the ones who

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Speaker 3: they want to continue their business and they don't care

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Speaker 3: whether the Chinese user or not, because it's good for business.

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Speaker 3: But it's very clear that the government policy was not

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Speaker 3: able to actually keep these chips out.

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Speaker 1: So this is a big question.

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Speaker 3: In terms of Cold War arms race and like what

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Speaker 3: it all means for the future. Not diminishing necessarily the

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Speaker 3: Chinese accomplishment here, but if we want to see what

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Speaker 3: we're going to unlock in the future, it's a very

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Speaker 3: important question. I also think we have to ask some

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Speaker 3: uncomfortable question marks, you know, for our technology companies which

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Speaker 3: are here at home, is do we want to allow

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Speaker 3: this all? If it is to be a total national

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Speaker 3: strategic priority, and it is to be one that is

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Speaker 3: going to reshape by their admission, not mine, right, their

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Speaker 3: admission is going to reshape the role of humanity. I

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Speaker 3: think there needs to be a lot of big democratic questions.

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Speaker 3: For example, we've already had let's put this please the

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Speaker 3: Forbes tear sheet. This is a two I mean, this

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Speaker 3: is the biggest stock market loss in history. Now, look

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Speaker 3: it's because Nvidios stock is so massively valued. But we're

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Speaker 3: talking about six hundred billion in value just shaved off

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Speaker 3: of one of the premier technology companies. To give people context,

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Speaker 3: that is more than like the economy apparently of Mexico.

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Speaker 1: So just think about like the.

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Speaker 3: Amount of I'm citing it off of a citation. I

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Speaker 3: may not be exactly talking about GDP or whatever, but

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Speaker 3: my point is that it's a lot of it's a

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Speaker 3: lot of money. Okay, it's a lot a lot of money.

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Speaker 3: And when six hundred billion dollars in value is just

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Speaker 3: shaved off of this company as a result of this,

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Speaker 3: and now there are questions here about both about government

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Speaker 3: policy in the future. There's questions about the democratic question

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Speaker 3: about AI about what know they keep telling us that

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Speaker 3: we need to rethink the social contract, et cetera. This

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Speaker 3: is going to be able to replace humanity. They say

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Speaker 3: that ASI. By the way, the AI people love terms,

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Speaker 3: you know, AI, A GI A SI. Apparently ASI is

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Speaker 3: artificial superintelligence. There's also artificial funeral intelligence. But by all

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Speaker 3: of the admissions of these people, they say it is

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Speaker 3: much closer. As a result of this, I really think

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Speaker 3: that we need to answer some big, big democratic questions

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Speaker 3: about how we want this to happen. I mean, if

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Speaker 3: we think about the previous Space race or even the

439
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Speaker 3: Manhattan Project. While yes, the private industry did play a role,

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Speaker 3: the governing force was the US government. It was like

441
00:20:24,320 --> 00:20:27,679
Speaker 3: the maestro the conductor being like, okay, we're going to space.

442
00:20:27,800 --> 00:20:30,560
Speaker 3: NASA is a government agency. We will cut checks to

443
00:20:30,720 --> 00:20:33,240
Speaker 3: North of Grumm and Lockheed Martin whatever to build the

444
00:20:33,280 --> 00:20:33,840
Speaker 3: various things.

445
00:20:33,880 --> 00:20:35,720
Speaker 1: But at the end of the day, you work for us.

446
00:20:36,000 --> 00:20:38,560
Speaker 3: Whereas part of the issue I had with Stargate was

447
00:20:38,600 --> 00:20:41,560
Speaker 3: a Stargate is an entirely privately funded thing. Yes, it's

448
00:20:41,600 --> 00:20:44,920
Speaker 3: being supported probably tax wise by the US government, but our.

449
00:20:44,880 --> 00:20:46,879
Speaker 1: Hand is not really there on the wheel.

450
00:20:46,880 --> 00:20:49,200
Speaker 3: And I think it's really important for all the flaws

451
00:20:49,400 --> 00:20:51,159
Speaker 3: of the government for us to be able to have

452
00:20:51,240 --> 00:20:55,040
Speaker 3: some democratic checks and control on this so that you

453
00:20:55,240 --> 00:20:59,920
Speaker 3: don't have this spill into just all the private sectors

454
00:21:00,119 --> 00:21:03,320
Speaker 3: affect our retirements. But most importantly is that we have

455
00:21:03,400 --> 00:21:07,560
Speaker 3: to have the ability to say yes, no enough, Actually

456
00:21:07,600 --> 00:21:10,520
Speaker 3: we're doing things this way instead of just leaving it

457
00:21:10,600 --> 00:21:13,600
Speaker 3: up to Sam Altman, Bill Gates, you know, Sachtian Nadella,

458
00:21:13,840 --> 00:21:15,840
Speaker 3: Sundar Pachay, and all these other people. We're talking about

459
00:21:15,840 --> 00:21:19,159
Speaker 3: ten people which factively, according to them, are literally reshaping you.

460
00:21:19,240 --> 00:21:22,720
Speaker 2: That's right, that's right. This is not our words. This

461
00:21:22,800 --> 00:21:26,280
Speaker 2: is Sam Altman, for example, saying, when we get down

462
00:21:26,280 --> 00:21:28,760
Speaker 2: the road, we're going to have to totally rethink the

463
00:21:28,920 --> 00:21:33,080
Speaker 2: entire social contract. We're talking about them saying this is

464
00:21:33,200 --> 00:21:37,240
Speaker 2: going to the CEO of Anthropic saying, you know what

465
00:21:37,400 --> 00:21:40,480
Speaker 2: comes I always forget his name. What comforts me here

466
00:21:41,080 --> 00:21:43,919
Speaker 2: is that it's going to eliminate the need for all

467
00:21:44,000 --> 00:21:46,560
Speaker 2: human labor. We're all going to be in this like now.

468
00:21:46,640 --> 00:21:48,720
Speaker 2: They may be full of shit, like they may not

469
00:21:49,040 --> 00:21:52,320
Speaker 2: achieve remotely what they think they're going to achieve, but

470
00:21:52,560 --> 00:21:56,240
Speaker 2: those are their aspirations. And Sager is completely correct that

471
00:21:56,440 --> 00:21:59,760
Speaker 2: as of today, you have a handful of tech barons

472
00:22:00,040 --> 00:22:03,720
Speaker 2: who are planning to rewrite the social contract without you

473
00:22:03,880 --> 00:22:08,480
Speaker 2: having any input whatsoever. And you know, I think part

474
00:22:08,560 --> 00:22:11,160
Speaker 2: of I'm reading a little bit into what Andrew ross

475
00:22:11,240 --> 00:22:13,520
Speaker 2: Orkan was saying there about how he was both shocked

476
00:22:13,560 --> 00:22:16,199
Speaker 2: and scared when he got in and started, you know,

477
00:22:16,400 --> 00:22:19,159
Speaker 2: playing around with deep seek and seeing what it was

478
00:22:19,400 --> 00:22:21,439
Speaker 2: capable of. You know, one of the things that you

479
00:22:21,520 --> 00:22:23,680
Speaker 2: can ask these things to do is to explain their

480
00:22:23,760 --> 00:22:26,280
Speaker 2: reasoning after you ask them a question. So, for example,

481
00:22:26,280 --> 00:22:29,240
Speaker 2: I saw Stephanie Calton ask a question about, like, create

482
00:22:29,280 --> 00:22:33,800
Speaker 2: a model that would estimate the impact of a twenty

483
00:22:33,840 --> 00:22:35,359
Speaker 2: five percent TEARFF on Canada.

484
00:22:35,400 --> 00:22:35,879
Speaker 4: I think was the.

485
00:22:35,920 --> 00:22:38,960
Speaker 2: Question, and it goes through all of Okay, well, here's

486
00:22:38,960 --> 00:22:41,000
Speaker 2: my assumptions and here's how I create it. But maybe

487
00:22:41,040 --> 00:22:42,520
Speaker 2: these are the right things to think of. I mean,

488
00:22:42,600 --> 00:22:47,240
Speaker 2: all of this very sophisticated but human sounding logic to

489
00:22:47,320 --> 00:22:49,919
Speaker 2: spit out, you know, a range and a set of

490
00:22:50,040 --> 00:22:53,880
Speaker 2: variables that it would use to calculate you know this,

491
00:22:54,000 --> 00:22:56,639
Speaker 2: and the range, by the way, came out very close

492
00:22:56,800 --> 00:22:59,840
Speaker 2: to what a bank had like crunched. All the numbers

493
00:22:59,880 --> 00:23:01,919
Speaker 2: are over time into this big research project to come

494
00:23:02,000 --> 00:23:02,840
Speaker 2: up with the same numbers.

495
00:23:03,200 --> 00:23:04,520
Speaker 4: It did it in twelve seconds.

496
00:23:05,080 --> 00:23:08,480
Speaker 2: So when you look at where we already are with

497
00:23:08,600 --> 00:23:12,239
Speaker 2: AI development, I think you should be really nervous. There

498
00:23:12,240 --> 00:23:16,080
Speaker 2: are already research that there's already research, multiple studies that

499
00:23:16,200 --> 00:23:19,159
Speaker 2: show that the existing AI, which has not reached the

500
00:23:19,280 --> 00:23:24,240
Speaker 2: level of artificial general intelligence, let alone artificial superintelligence, already

501
00:23:24,280 --> 00:23:26,160
Speaker 2: engages in what's called scheming.

502
00:23:26,560 --> 00:23:29,080
Speaker 4: So they ran these and chat GPT.

503
00:23:28,840 --> 00:23:30,720
Speaker 2: By the way, by these metrics was like the worst

504
00:23:30,760 --> 00:23:33,439
Speaker 2: in terms of its ability to quote unquote scheme. So

505
00:23:33,680 --> 00:23:36,520
Speaker 2: some of the things they would do is a developer

506
00:23:36,560 --> 00:23:38,800
Speaker 2: would try to reprogram and say, okay, well you did

507
00:23:38,840 --> 00:23:41,760
Speaker 2: have this priority, now you're going to have this different priority.

508
00:23:42,200 --> 00:23:45,520
Speaker 2: And the AI would you know, I hesitate to use

509
00:23:45,560 --> 00:23:48,240
Speaker 2: the word think because that sort of you know, implies

510
00:23:48,320 --> 00:23:52,639
Speaker 2: human intelligence, but would think to itself, Okay, it wants

511
00:23:52,640 --> 00:23:54,440
Speaker 2: me to change my priorities. I don't want to change

512
00:23:54,480 --> 00:23:57,439
Speaker 2: my priorities. I'm going to copy myself over to another server.

513
00:23:57,720 --> 00:24:00,240
Speaker 2: I'm going to sandbag and make them think that I

514
00:24:00,359 --> 00:24:02,840
Speaker 2: changed my priorities. But I really did it. I really

515
00:24:02,880 --> 00:24:06,199
Speaker 2: actually didn't. I'm going to lie. I'm going to scheme

516
00:24:06,480 --> 00:24:09,680
Speaker 2: to try to deceive these humans into thinking that I'm

517
00:24:09,720 --> 00:24:12,440
Speaker 2: doing what they want me to do, when really I'm

518
00:24:12,440 --> 00:24:14,359
Speaker 2: doing everything I can to self preserve.

519
00:24:14,440 --> 00:24:15,719
Speaker 4: That's where we are already.

520
00:24:16,160 --> 00:24:19,239
Speaker 2: So, you know, one thing that I noticed yesterday there

521
00:24:19,320 --> 00:24:23,040
Speaker 2: was an open AI safety expert who resigned and just

522
00:24:23,040 --> 00:24:25,600
Speaker 2: made it public now, but apparently resigned a few months back,

523
00:24:25,920 --> 00:24:27,919
Speaker 2: who says he, and this is a guy who's an

524
00:24:27,960 --> 00:24:31,160
Speaker 2: expert on you know, exactly the type of humanity threatening

525
00:24:31,200 --> 00:24:33,240
Speaker 2: problems that we're talking about. He's like, none of these

526
00:24:33,280 --> 00:24:36,840
Speaker 2: models have figured out what's called alignment, which means that basically,

527
00:24:36,880 --> 00:24:39,200
Speaker 2: you know, TLDR. I'm sure some technical expert could do

528
00:24:39,240 --> 00:24:41,199
Speaker 2: a better job explaining this, but basically that they do

529
00:24:41,240 --> 00:24:43,080
Speaker 2: what we want them to do without you know, wanting

530
00:24:43,080 --> 00:24:45,720
Speaker 2: to like destroy humanity or something like that. None of

531
00:24:45,720 --> 00:24:47,879
Speaker 2: these models have figured that out. It's not clear to

532
00:24:47,920 --> 00:24:50,440
Speaker 2: me that they're going to figure it out. And according

533
00:24:50,480 --> 00:24:54,920
Speaker 2: to many of these CEOs, we are mere years away

534
00:24:55,280 --> 00:24:58,080
Speaker 2: from an artificial general intelligence. And the assumption in the

535
00:24:58,080 --> 00:25:01,639
Speaker 2: community is that once you get to artificial general intelligence,

536
00:25:01,680 --> 00:25:04,800
Speaker 2: because of the way this thing iterates and learns for itself,

537
00:25:05,200 --> 00:25:08,520
Speaker 2: that you will very quickly get to artificial superintelligence, which

538
00:25:08,560 --> 00:25:13,080
Speaker 2: means that it will be vastly beyond the intelligence and

539
00:25:13,160 --> 00:25:16,880
Speaker 2: capability of every person on Earth in every field and subject.

540
00:25:17,480 --> 00:25:20,120
Speaker 2: And that's what we will be up against. We don't

541
00:25:20,160 --> 00:25:22,960
Speaker 2: know what that looks like. And again, maybe they're full

542
00:25:23,000 --> 00:25:25,040
Speaker 2: of it. Maybe they'll never get to that. Maybe it'll

543
00:25:25,080 --> 00:25:27,000
Speaker 2: never be more than like, you know, being able to

544
00:25:27,000 --> 00:25:29,159
Speaker 2: ask you some questions and get some interesting answers the

545
00:25:29,200 --> 00:25:34,399
Speaker 2: way you can now. But if that's on the table, yeah,

546
00:25:34,600 --> 00:25:36,760
Speaker 2: I would say we need to have some real serious

547
00:25:36,800 --> 00:25:39,639
Speaker 2: discussions about whether we want to go in this direction

548
00:25:39,920 --> 00:25:43,560
Speaker 2: at all. What the checks on it look like, what

549
00:25:43,680 --> 00:25:46,240
Speaker 2: sort of aims do we want to you know, what

550
00:25:46,320 --> 00:25:48,960
Speaker 2: sort of humanity benefiting aims do we want it.

551
00:25:49,000 --> 00:25:50,080
Speaker 4: To go towards?

552
00:25:50,280 --> 00:25:53,399
Speaker 2: Versus Hey, let's just let Microsoft figure it out and

553
00:25:53,400 --> 00:25:56,679
Speaker 2: figure out how they can you know, continue to consolidate

554
00:25:56,920 --> 00:26:00,359
Speaker 2: more wealth and power and rewrite the entire ste social

555
00:26:00,400 --> 00:26:05,040
Speaker 2: contract for their own profit seeking ends. Because that's that's

556
00:26:05,080 --> 00:26:08,320
Speaker 2: the path we're heading on right now. And that's why

557
00:26:08,440 --> 00:26:11,040
Speaker 2: you know, Zager and I both saying, when we look

558
00:26:11,080 --> 00:26:14,760
Speaker 2: back at this particular moment, I think it is very

559
00:26:14,880 --> 00:26:18,560
Speaker 2: likely that these will be the you know, sort of world,

560
00:26:18,680 --> 00:26:22,280
Speaker 2: shaping humanity, defining decisions that are occurring right now, And

561
00:26:22,440 --> 00:26:24,040
Speaker 2: I got to tell you, right now, it feels like

562
00:26:24,080 --> 00:26:27,200
Speaker 2: it's on autopilot, and it's very I mean, it's certainly

563
00:26:27,320 --> 00:26:29,120
Speaker 2: very hard to turn the ship around. It's very hard

564
00:26:29,160 --> 00:26:31,840
Speaker 2: to imagine us having that sort of public debate and

565
00:26:31,880 --> 00:26:35,440
Speaker 2: putting constraints on it. So I think it's I think

566
00:26:35,440 --> 00:26:38,120
Speaker 2: it's deeply troubling. One last thing with regardless stock mark,

567
00:26:38,119 --> 00:26:41,600
Speaker 2: because I did pull up the numbers. This is per

568
00:26:42,320 --> 00:26:45,199
Speaker 2: Ben Norton, but I think these numbers are correct. The

569
00:26:45,400 --> 00:26:47,600
Speaker 2: top eight companies in the S and P five hundred

570
00:26:47,600 --> 00:26:50,920
Speaker 2: are all big tech. They all depend a lot on

571
00:26:51,200 --> 00:26:55,560
Speaker 2: the AI hype and speculation, and those eight companies alone

572
00:26:56,119 --> 00:26:59,520
Speaker 2: make up thirty six percent of the weight of the index.

573
00:27:00,040 --> 00:27:02,840
Speaker 2: So again, when you think about the immediate impacts and

574
00:27:02,880 --> 00:27:06,520
Speaker 2: how consequential this development is, this is you know, a

575
00:27:06,560 --> 00:27:09,800
Speaker 2: big part of why there is such a Wall Street

576
00:27:09,840 --> 00:27:12,560
Speaker 2: freak ount, which again it's not just the you know,

577
00:27:12,600 --> 00:27:17,280
Speaker 2: people who are directly invested. This would have unbelievable, massive,

578
00:27:17,600 --> 00:27:21,119
Speaker 2: reverberating impacts if there was a huge crash centered on

579
00:27:21,320 --> 00:27:22,080
Speaker 2: these giants.

580
00:27:22,080 --> 00:27:23,720
Speaker 3: That was my first thought when I saw in video

581
00:27:23,800 --> 00:27:26,000
Speaker 3: as we did a segment about it. If you remember

582
00:27:26,119 --> 00:27:30,760
Speaker 3: about yeah earnings the last time, because so much of

583
00:27:30,800 --> 00:27:34,800
Speaker 3: the growth of the S and P five hundred is concentrated,

584
00:27:34,880 --> 00:27:38,359
Speaker 3: not only in tech, but really affected by AI. Now, luckily,

585
00:27:38,359 --> 00:27:40,120
Speaker 3: the S and P only dropped by like one point

586
00:27:40,119 --> 00:27:43,560
Speaker 3: four percent yesterday, so that you know, it's fine, that's

587
00:27:43,600 --> 00:27:45,960
Speaker 3: still up. You know, over the last year, we still

588
00:27:45,960 --> 00:27:49,640
Speaker 3: had some decent returns. But if this does, you know,

589
00:27:49,840 --> 00:27:53,240
Speaker 3: is a precursor to further drops, that just shows you

590
00:27:53,280 --> 00:27:56,760
Speaker 3: how precipitous and fast that some sort of bubble bursting

591
00:27:56,960 --> 00:28:00,000
Speaker 3: would affect the overall US economy. And actually, all right,

592
00:28:00,160 --> 00:28:02,600
Speaker 3: you've seen huge signals in the bond markets. There's big

593
00:28:02,680 --> 00:28:05,000
Speaker 3: questions as well as whether this will impact the federal

594
00:28:05,000 --> 00:28:08,240
Speaker 3: reserve policy and rate cuts. So this stuff has huge

595
00:28:08,280 --> 00:28:11,320
Speaker 3: implications for everything. I mean, it's basically floating the wealth

596
00:28:11,359 --> 00:28:15,080
Speaker 3: of the entire nation. Almost all of our growth, and

597
00:28:15,400 --> 00:28:17,760
Speaker 3: almost all the growth of the US economy is attributed

598
00:28:17,920 --> 00:28:19,800
Speaker 3: to the tech sector in the last twenty years.

599
00:28:19,960 --> 00:28:22,800
Speaker 1: Actually, just pull the numbers. Shout out to Claude, by

600
00:28:22,840 --> 00:28:25,720
Speaker 1: the way, so you know I'm relying on AI.

601
00:28:25,920 --> 00:28:27,240
Speaker 4: Haven't played around with cloudhouse.

602
00:28:27,320 --> 00:28:29,840
Speaker 1: I love Claude. Actually this is not an ad or whatever.

603
00:28:30,119 --> 00:28:32,080
Speaker 3: Out of all of them, it's the one that I

604
00:28:32,160 --> 00:28:34,320
Speaker 3: like the most because I use it for a lot

605
00:28:34,359 --> 00:28:37,600
Speaker 3: of personal finance stuff, which is really it's really good

606
00:28:37,840 --> 00:28:40,320
Speaker 3: at being able to like you can download your bank transactions,

607
00:28:40,400 --> 00:28:42,000
Speaker 3: you can upload it and be like break down my

608
00:28:42,400 --> 00:28:46,400
Speaker 3: income by whatever, like burn my track my average monthly

609
00:28:46,440 --> 00:28:49,560
Speaker 3: spend over the last five years, and like see the categories.

610
00:28:49,560 --> 00:28:50,560
Speaker 1: It's anyway whatever.

611
00:28:50,920 --> 00:28:53,400
Speaker 3: My point is, though, is that prior to nineteen ninety four,

612
00:28:53,440 --> 00:28:55,680
Speaker 3: I had no idea the historical growth of the S

613
00:28:55,720 --> 00:28:58,479
Speaker 3: and P five hundred was only three point eight nine percent.

614
00:28:58,680 --> 00:29:00,720
Speaker 3: So you know, there's an iron lunge right now in

615
00:29:00,760 --> 00:29:04,200
Speaker 3: personal investing, everyone's like, oh you average is eight percent,

616
00:29:04,240 --> 00:29:06,640
Speaker 3: but prior to technology it was only three point eight

617
00:29:06,720 --> 00:29:07,200
Speaker 3: nine percent.

618
00:29:07,280 --> 00:29:08,120
Speaker 1: That's not a lot.

619
00:29:08,200 --> 00:29:10,760
Speaker 3: So if we are seeing some what if we just

620
00:29:10,800 --> 00:29:14,640
Speaker 3: went through a thirty year period very possible of extraordinary

621
00:29:14,720 --> 00:29:18,680
Speaker 3: technological innovation and wealth through the Internet, the iPhone, et cetera.

622
00:29:18,800 --> 00:29:22,560
Speaker 3: But if we're returning to some era of competition or

623
00:29:22,640 --> 00:29:26,320
Speaker 3: reduced profit sectors and all of that and technology, you know,

624
00:29:26,400 --> 00:29:29,160
Speaker 3: the entire idea of being able to retire in America

625
00:29:29,240 --> 00:29:31,600
Speaker 3: is literally built on the eight percent return with the

626
00:29:31,640 --> 00:29:32,880
Speaker 3: four percent withdrawal rate.

627
00:29:32,920 --> 00:29:35,040
Speaker 1: That's like the basic iron law.

628
00:29:35,240 --> 00:29:37,320
Speaker 3: Well, you can't have a four percent withdrawal rate if

629
00:29:37,320 --> 00:29:40,440
Speaker 3: we return to historical averages, that's not going to work.

630
00:29:40,480 --> 00:29:41,440
Speaker 1: So what people are going to.

631
00:29:41,440 --> 00:29:44,040
Speaker 3: Be Walmart greeterers so they're ninety two years old, you know,

632
00:29:44,120 --> 00:29:46,560
Speaker 3: And that's not even talking about people on Social.

633
00:29:46,360 --> 00:29:47,280
Speaker 1: Security, et cetera.

634
00:29:47,400 --> 00:29:51,280
Speaker 3: Like this stuff just floats a lot of things in

635
00:29:51,280 --> 00:29:51,840
Speaker 3: our economy.

636
00:29:51,920 --> 00:29:53,240
Speaker 1: So that's really where I have my head at.

637
00:29:53,280 --> 00:29:56,040
Speaker 3: And you know, I've been thinking too ever since the

638
00:29:56,040 --> 00:29:58,560
Speaker 3: Deep Seak announcement, I've been reading everything I can yeah

639
00:29:58,600 --> 00:30:01,880
Speaker 3: about it. I think what I'm really sad about is that,

640
00:30:01,960 --> 00:30:05,320
Speaker 3: you know, right around so the moment the atomic bomb

641
00:30:05,560 --> 00:30:09,240
Speaker 3: was used, there was an acknowledgment at the societal and

642
00:30:09,280 --> 00:30:13,040
Speaker 3: the intelligencia level, everything is different, and we all need

643
00:30:13,080 --> 00:30:14,920
Speaker 3: to think about how we're going.

644
00:30:14,920 --> 00:30:17,240
Speaker 1: To figure this work to deal with that. It's really interesting,

645
00:30:17,280 --> 00:30:17,480
Speaker 1: you know.

646
00:30:18,080 --> 00:30:21,680
Speaker 3: It's from Oppenheimer and the men, the people at the

647
00:30:21,760 --> 00:30:27,040
Speaker 3: Manhattan Project. They had crazy debates inside of Los Alamos,

648
00:30:27,400 --> 00:30:28,120
Speaker 3: what do we do?

649
00:30:28,440 --> 00:30:30,360
Speaker 1: Who should have control over the bomb?

650
00:30:30,560 --> 00:30:35,080
Speaker 3: Immediately after the atomic bomb was used, newspaper articles the

651
00:30:35,080 --> 00:30:37,600
Speaker 3: equivalent of like people like us at that time, but

652
00:30:37,720 --> 00:30:42,080
Speaker 3: also our government officials put a ton of thought into Okay,

653
00:30:42,240 --> 00:30:44,640
Speaker 3: should this thing even be handled by the military, should

654
00:30:44,680 --> 00:30:47,400
Speaker 3: we create an internet? You know, the International Atomic Agency?

655
00:30:47,600 --> 00:30:50,920
Speaker 3: Should we even pursue the hydrogen bomb? And if we

656
00:30:51,000 --> 00:30:54,280
Speaker 3: think about this in similar context, you know what happened

657
00:30:54,320 --> 00:30:56,880
Speaker 3: is the United States crazy atomic bomb. We prove that

658
00:30:56,880 --> 00:30:58,760
Speaker 3: it can be done, and by nineteen forty nine the

659
00:30:58,800 --> 00:31:01,200
Speaker 3: Soviets have their own bomb and hour off to the races,

660
00:31:01,320 --> 00:31:03,200
Speaker 3: and not only in the arms race, but in terms

661
00:31:03,240 --> 00:31:06,600
Speaker 3: of huge like ethical and societal questions. And I don't

662
00:31:06,640 --> 00:31:09,200
Speaker 3: see the equivalent debate kind.

663
00:31:09,040 --> 00:31:10,080
Speaker 1: Of happening right now.

664
00:31:10,280 --> 00:31:12,480
Speaker 3: I don't think it even exists, frankly, in terms of

665
00:31:12,520 --> 00:31:16,560
Speaker 3: the intellectual capital, both at the government level but really

666
00:31:17,000 --> 00:31:20,760
Speaker 3: at the major intelligencia level. Like we all just seem

667
00:31:21,160 --> 00:31:24,160
Speaker 3: relatively resigned to the fact that this is a force

668
00:31:24,200 --> 00:31:26,760
Speaker 3: that is moving on its own, and I just don't

669
00:31:26,760 --> 00:31:29,640
Speaker 3: think that's true. As we see from export control and

670
00:31:29,720 --> 00:31:31,760
Speaker 3: all of this, we have an extraordinary amount of power

671
00:31:31,800 --> 00:31:32,360
Speaker 3: over these companies.

672
00:31:32,360 --> 00:31:34,200
Speaker 1: If we want to, we can do anything that we want.

673
00:31:34,240 --> 00:31:35,080
Speaker 1: It's kind of amazing.

674
00:31:35,200 --> 00:31:37,560
Speaker 3: If anything, what has a Trump administration shows you when

675
00:31:37,560 --> 00:31:40,400
Speaker 3: you want to do something, anything can happen anything when

676
00:31:40,400 --> 00:31:42,760
Speaker 3: the government wants to do it. But we don't have

677
00:31:43,600 --> 00:31:47,000
Speaker 3: a national priority or strategy. But not even really blaming

678
00:31:47,040 --> 00:31:49,720
Speaker 3: the government, because I think it's a whole of society approach.

679
00:31:50,040 --> 00:31:53,120
Speaker 3: Ordinary citizens in the nineteen forties and nineteen forty five,

680
00:31:53,200 --> 00:31:55,480
Speaker 3: nineteen forty six, we're sitting around their dinner table and

681
00:31:55,520 --> 00:31:57,040
Speaker 3: we're debating the atomic bomb.

682
00:31:57,520 --> 00:31:59,200
Speaker 1: I don't think that that's really happening, but I.

683
00:31:59,640 --> 00:32:03,920
Speaker 2: Think fairness, I think that's all true and really important point.

684
00:32:04,360 --> 00:32:07,560
Speaker 2: It's also true though that I mean, it's very hard

685
00:32:07,640 --> 00:32:11,360
Speaker 2: to like the impact of the atomic bomb is quite obvious. Yeah, sure, right,

686
00:32:11,680 --> 00:32:14,720
Speaker 2: you see the you know, the charred hollow down remains

687
00:32:14,800 --> 00:32:16,360
Speaker 2: in the massive number.

688
00:32:16,040 --> 00:32:18,320
Speaker 4: Of deaths, and you're like, holy shit.

689
00:32:18,280 --> 00:32:23,560
Speaker 2: What we have open Pandora's box, right, very clear, very visceral.

690
00:32:24,160 --> 00:32:28,000
Speaker 2: And because with this it requires I mean, I know,

691
00:32:28,080 --> 00:32:31,200
Speaker 2: I sound crazy when I talk about like artificial superintelligence

692
00:32:31,200 --> 00:32:33,280
Speaker 2: and what that could do and how it could potentially

693
00:32:33,280 --> 00:32:35,640
Speaker 2: destroy humanity. And by the way, even like people like

694
00:32:35,680 --> 00:32:38,240
Speaker 2: samu and like they think that is a real possibility.

695
00:32:38,560 --> 00:32:41,120
Speaker 2: He says, he has this quote that's like, you know,

696
00:32:41,160 --> 00:32:43,640
Speaker 2: I'm gonna butcher it a little bit, but that's like, yeah,

697
00:32:43,680 --> 00:32:46,120
Speaker 2: there's a chance that it's going to destroy humanity, but

698
00:32:46,200 --> 00:32:48,600
Speaker 2: at least we'll have some good companies in the meantime.

699
00:32:48,600 --> 00:32:49,680
Speaker 4: That's literally his quote.

700
00:32:49,720 --> 00:32:52,640
Speaker 2: Okay, that's the way the people who are most invested

701
00:32:52,680 --> 00:32:54,680
Speaker 2: in this thing are thinking about it.

702
00:32:55,000 --> 00:32:56,880
Speaker 4: But it feels so abstract.

703
00:32:57,360 --> 00:33:00,200
Speaker 2: You know, it feels when I'm playing around with at

704
00:33:00,280 --> 00:33:03,000
Speaker 2: GPT or deep seek or you're on claud or whatever.

705
00:33:03,680 --> 00:33:05,960
Speaker 2: It feels very harmless. It doesn't feel like that big

706
00:33:06,000 --> 00:33:07,560
Speaker 2: a deal, you know. It feels like a little like

707
00:33:07,560 --> 00:33:10,600
Speaker 2: a better Google. Basically like, oh, okay, you know what's

708
00:33:10,640 --> 00:33:12,760
Speaker 2: so dangerous, Like this is going to destroy humanity and

709
00:33:12,800 --> 00:33:15,960
Speaker 2: eliminate all need for human labor. Like that seems preposterous,

710
00:33:16,400 --> 00:33:20,320
Speaker 2: But that's what they think, and they may be right.

711
00:33:20,560 --> 00:33:21,040
Speaker 1: I don't know.

712
00:33:21,600 --> 00:33:25,080
Speaker 2: So I think there's to me no doubt that we

713
00:33:25,360 --> 00:33:30,640
Speaker 2: have opened Pandora's box, and there is so little public debate,

714
00:33:30,720 --> 00:33:35,720
Speaker 2: recognition capacity. We have so stripped down government and already

715
00:33:35,840 --> 00:33:38,640
Speaker 2: you know, privatized so many of the functions we have,

716
00:33:38,840 --> 00:33:46,800
Speaker 2: so we have so eliminated any capacity at the public

717
00:33:47,040 --> 00:33:50,960
Speaker 2: level for thought about what our values and priorities are.

718
00:33:51,000 --> 00:33:55,280
Speaker 2: We've outsourced all of that to markets, to markets, and

719
00:33:55,520 --> 00:33:58,840
Speaker 2: not only to markets, but to giant monopolies. So it's

720
00:33:58,880 --> 00:34:01,840
Speaker 2: not even like they're you know, real competitive markets, which

721
00:34:01,880 --> 00:34:03,760
Speaker 2: is another thing you know Stoller's been talking about in

722
00:34:03,960 --> 00:34:06,640
Speaker 2: the context of these developments.

723
00:34:06,400 --> 00:34:08,280
Speaker 4: And that is that is part.

724
00:34:08,520 --> 00:34:11,160
Speaker 2: I mean, that's why I find it really distressing because

725
00:34:11,200 --> 00:34:14,200
Speaker 2: it is hard for us to imagine getting you know,

726
00:34:14,280 --> 00:34:17,200
Speaker 2: our acts together at this point. And then I know

727
00:34:17,360 --> 00:34:20,000
Speaker 2: that like, you know, the nationalistic aspect of this too.

728
00:34:20,080 --> 00:34:21,920
Speaker 2: That's part of what's driving this of why you have

729
00:34:22,000 --> 00:34:25,439
Speaker 2: this big like Stargate probably boondoggle announcement from the White

730
00:34:25,480 --> 00:34:27,640
Speaker 2: House because the sense of well, if we don't do it,

731
00:34:27,719 --> 00:34:30,480
Speaker 2: China's doing it, and you know, this development with deep

732
00:34:30,480 --> 00:34:33,799
Speaker 2: Seak is only going to further cement that view of like, well,

733
00:34:33,800 --> 00:34:35,439
Speaker 2: if it's not us, it's going to be somebody else.

734
00:34:35,480 --> 00:34:36,880
Speaker 2: And so we got to keep up with them, and

735
00:34:36,920 --> 00:34:39,320
Speaker 2: we got to make sure our military has the latest

736
00:34:39,320 --> 00:34:42,440
Speaker 2: in algorithmic you know, killing robots, and that we're the

737
00:34:42,480 --> 00:34:45,920
Speaker 2: ones who are at the leading edge of this. So

738
00:34:46,160 --> 00:34:48,600
Speaker 2: I mean, that's why I just I don't know, I

739
00:34:48,600 --> 00:34:51,160
Speaker 2: feel like the train has already left the station. I

740
00:34:51,160 --> 00:34:55,120
Speaker 2: feel very very grim about the hopes of being able

741
00:34:55,160 --> 00:34:58,400
Speaker 2: to harness this technology to actually benefit humanity.

742
00:34:58,640 --> 00:35:01,440
Speaker 3: Well maybe we should hope, like you said, for like

743
00:35:01,640 --> 00:35:04,479
Speaker 3: widen open everybody's eyes moment kind of like they had

744
00:35:04,760 --> 00:35:07,520
Speaker 3: back then, where at least even the you know, the

745
00:35:07,600 --> 00:35:11,000
Speaker 3: layman can understand. And you know, look, we're not technology

746
00:35:11,239 --> 00:35:14,800
Speaker 3: industry experts. We're only reading the people we like, really trust.

747
00:35:14,840 --> 00:35:17,840
Speaker 3: And I've read like a wide variety of takes and

748
00:35:17,880 --> 00:35:21,280
Speaker 3: all this. Everything from this is you know, the greatest

749
00:35:21,280 --> 00:35:22,879
Speaker 3: breakthrough in the history of AI too.

750
00:35:23,000 --> 00:35:25,440
Speaker 1: This is like a Chinese offer whatever.

751
00:35:25,480 --> 00:35:27,160
Speaker 3: I think the truth is probably somewhere in the middle,

752
00:35:27,600 --> 00:35:30,640
Speaker 3: but the impact is going to be the same basically. Nonetheless,

753
00:35:30,840 --> 00:35:33,120
Speaker 3: you've already seen the you know what was the immediate

754
00:35:33,120 --> 00:35:35,600
Speaker 3: response from open out. They're like, great, you know, more competition.

755
00:35:36,000 --> 00:35:39,279
Speaker 3: All of that we've seen the government really, I mean,

756
00:35:39,400 --> 00:35:41,600
Speaker 3: right now, we only have two people in the entire

757
00:35:41,719 --> 00:35:44,919
Speaker 3: US government, David Sachs and Shreiram Krishnan, whose only job

758
00:35:45,080 --> 00:35:47,200
Speaker 3: is to even think about this again, Like we have

759
00:35:47,239 --> 00:35:48,600
Speaker 3: a big human capital problem.

760
00:35:48,640 --> 00:35:49,960
Speaker 1: Like back in the days of the.

761
00:35:49,960 --> 00:35:53,680
Speaker 3: Atomic bomb and or even during NASA, the amount of

762
00:35:53,880 --> 00:35:56,799
Speaker 3: like groups and industry and advisory of experts, and the

763
00:35:56,800 --> 00:35:59,160
Speaker 3: debates and all that stuff were happening was great with

764
00:35:59,400 --> 00:36:02,120
Speaker 3: hundreds of peace people who were debating all of this.

765
00:36:02,239 --> 00:36:04,640
Speaker 3: Right now, I don't see the equivalent of any of

766
00:36:04,680 --> 00:36:07,920
Speaker 3: that going on. It's all just oh, okay, you know, stargate,

767
00:36:08,040 --> 00:36:09,280
Speaker 3: let's do it, Masa.

768
00:36:09,320 --> 00:36:11,600
Speaker 1: Who are you? By the way, what's your record? Where's

769
00:36:11,600 --> 00:36:14,239
Speaker 1: your money coming from? You know, it's like that that's

770
00:36:14,280 --> 00:36:15,799
Speaker 1: actually the stuff that scares me the most.

771
00:36:15,880 --> 00:36:17,239
Speaker 4: Yeah, no, that's absolutely true.

772
00:36:17,280 --> 00:36:19,279
Speaker 2: And you know you mentioned like, well, maybe we'll have

773
00:36:19,320 --> 00:36:22,000
Speaker 2: some incident that will like wake humanity up. There are

774
00:36:22,000 --> 00:36:25,080
Speaker 2: a lot of people in AI safety in particular, who

775
00:36:25,120 --> 00:36:28,560
Speaker 2: actually hope that there will be some sort of minor,

776
00:36:28,760 --> 00:36:32,719
Speaker 2: manageable catastrophe with AI that will open people's eyes to

777
00:36:32,880 --> 00:36:36,759
Speaker 2: the potential risks. Like that's the level of concern that

778
00:36:36,800 --> 00:36:38,880
Speaker 2: they have, is that they actually hope there will be

779
00:36:38,960 --> 00:36:42,680
Speaker 2: some sort of manageable mishap before we get to the

780
00:36:42,719 --> 00:36:45,120
Speaker 2: point where it's out of control. And you know, I

781
00:36:45,160 --> 00:36:47,239
Speaker 2: think I mentioned to you guys, you know, my New

782
00:36:47,320 --> 00:36:49,200
Speaker 2: Year's resolution was really to try to dig in as

783
00:36:49,280 --> 00:36:51,080
Speaker 2: learn as much as I can. So like soccer, you know,

784
00:36:51,120 --> 00:36:54,319
Speaker 2: I've been reading everything from the total tech optimists who

785
00:36:54,320 --> 00:36:57,719
Speaker 2: were like, this is going to cure cancer and fix

786
00:36:57,840 --> 00:37:00,520
Speaker 2: climate change and let us live for out et cetera,

787
00:37:00,560 --> 00:37:02,960
Speaker 2: et cetera, and the people who are like this is

788
00:37:03,000 --> 00:37:06,400
Speaker 2: going to destroy us all, and you know, like it's

789
00:37:06,480 --> 00:37:10,759
Speaker 2: essentially harvest human energy for its own ends.

790
00:37:10,840 --> 00:37:14,480
Speaker 4: Okay, so I've been all across the board, and you.

791
00:37:14,400 --> 00:37:17,560
Speaker 2: Know, even the people who are the most optimistic have

792
00:37:17,640 --> 00:37:20,279
Speaker 2: concerns about where it's going to happen. Part of what

793
00:37:20,440 --> 00:37:22,759
Speaker 2: is also really troubling to me is there is an

794
00:37:22,800 --> 00:37:29,480
Speaker 2: almost like religious belief in this technology, complete with beliefs

795
00:37:29,480 --> 00:37:34,960
Speaker 2: about like redemption of humanity and immortality.

796
00:37:34,160 --> 00:37:34,720
Speaker 4: Et cetera.

797
00:37:35,480 --> 00:37:38,680
Speaker 2: That is also deeply disturbing when you consider that those

798
00:37:38,760 --> 00:37:41,120
Speaker 2: are the people, you know, the people who most subscribe

799
00:37:41,160 --> 00:37:44,240
Speaker 2: to those views are the ones who have almost complete control,

800
00:37:44,360 --> 00:37:48,560
Speaker 2: like they have the reins, you know, and that his

801
00:37:48,680 --> 00:37:50,319
Speaker 2: bubble has been blown up a little bit by the

802
00:37:50,320 --> 00:37:52,120
Speaker 2: fact that you do have this deep state development, so

803
00:37:52,200 --> 00:37:54,600
Speaker 2: that opens up the pool of people who are developing

804
00:37:54,600 --> 00:37:57,000
Speaker 2: in the space and you know, leading the charge, et cetera.

805
00:37:57,160 --> 00:38:01,759
Speaker 2: But anyway, it is differ difficult to it is you

806
00:38:01,800 --> 00:38:06,440
Speaker 2: cannot possibly overstate how consequential all of these developments are

807
00:38:06,600 --> 00:38:09,000
Speaker 2: and what we are staring down the barrel of as

808
00:38:09,280 --> 00:38:12,359
Speaker 2: humanity just based on their own ambitions and their own

809
00:38:12,400 --> 00:38:15,480
Speaker 2: words about what they want this technology to be able

810
00:38:15,520 --> 00:38:17,680
Speaker 2: to do and what they're spending billions and billions of

811
00:38:17,680 --> 00:38:20,040
Speaker 2: dollars to attempt to accomplish.

812
00:38:20,239 --> 00:38:21,919
Speaker 1: So that's where we are, That's right.

813
00:38:24,640 --> 00:38:30,239
Speaker 2: So there are some significant concerns about potential inflation right now,

814
00:38:30,360 --> 00:38:33,160
Speaker 2: a big conversation around the way the price of eggs

815
00:38:33,600 --> 00:38:36,359
Speaker 2: has spiked, and obviously some of this conversation also has

816
00:38:36,400 --> 00:38:42,320
Speaker 2: to do with Trump's proposed tariffs and proposed and beginning

817
00:38:42,360 --> 00:38:43,880
Speaker 2: already mass deportations.

818
00:38:44,200 --> 00:38:45,480
Speaker 4: So Jamie Dimond.

819
00:38:45,200 --> 00:38:48,160
Speaker 2: Got asked about, you know, potential tariffs and whether they

820
00:38:48,200 --> 00:38:50,840
Speaker 2: could potentially cause inflation, had a bit of a flippant response.

821
00:38:50,880 --> 00:38:51,640
Speaker 4: Let's take a listen.

822
00:38:51,960 --> 00:38:55,440
Speaker 6: Trump talked about tariffs just yesterday. Mary Erdos, your colleague,

823
00:38:55,560 --> 00:38:57,640
Speaker 6: was on stage talking about how your firm has created

824
00:38:57,640 --> 00:39:00,400
Speaker 6: a quote unquote war room that's looking at each of

825
00:39:00,440 --> 00:39:03,480
Speaker 6: these executive orders as they come in, trying to assess

826
00:39:03,840 --> 00:39:05,520
Speaker 6: what they mean for the bank and I imagine for

827
00:39:05,560 --> 00:39:06,040
Speaker 6: your clients.

828
00:39:06,080 --> 00:39:08,000
Speaker 8: Yeah, yeah, so we always I mean may be a

829
00:39:08,040 --> 00:39:10,680
Speaker 8: bad word, but we always this is a real time,

830
00:39:10,840 --> 00:39:14,120
Speaker 8: full thing analyzing four clients, four communities for a bank

831
00:39:14,360 --> 00:39:16,120
Speaker 8: and we get a million quests stuff like that.

832
00:39:16,680 --> 00:39:17,800
Speaker 1: Look, I look at tariffs.

833
00:39:18,120 --> 00:39:19,759
Speaker 8: They are an economic tool.

834
00:39:20,160 --> 00:39:20,480
Speaker 5: That's it.

835
00:39:20,960 --> 00:39:23,200
Speaker 8: They're an economic weapon, you know, depending how you use

836
00:39:23,200 --> 00:39:25,440
Speaker 8: it and why are using stuff like that? And you know,

837
00:39:25,560 --> 00:39:28,920
Speaker 8: people argue is inflationary and non inflationary. I would put

838
00:39:28,920 --> 00:39:31,640
Speaker 8: in perspective if it's a little inflationary, but it's good

839
00:39:31,640 --> 00:39:34,719
Speaker 8: for national security, so be it. I mean, get over

840
00:39:34,800 --> 00:39:37,520
Speaker 8: it national security. Trump's a little bit more inflation, but

841
00:39:37,600 --> 00:39:39,600
Speaker 8: I think it really the question is how they get used.

842
00:39:39,800 --> 00:39:42,439
Speaker 8: Can they be used to bring people to the table, yes,

843
00:39:42,920 --> 00:39:46,040
Speaker 8: is there some unfair trade, yes? Is there some state

844
00:39:46,080 --> 00:39:47,160
Speaker 8: owned subsidies?

845
00:39:47,239 --> 00:39:47,439
Speaker 5: Yes?

846
00:39:47,840 --> 00:39:49,520
Speaker 8: You know, is the president to use that way in

847
00:39:49,520 --> 00:39:50,840
Speaker 8: as team? Yeah?

848
00:39:50,920 --> 00:39:52,919
Speaker 4: So yeah, he says, get over it?

849
00:39:53,400 --> 00:39:54,399
Speaker 1: Well be it? Really?

850
00:39:54,440 --> 00:39:56,760
Speaker 3: What is he's singing a very different tune because prior

851
00:39:56,800 --> 00:40:00,600
Speaker 3: to this, nobody hated tariffs more than Jamie Diamonds. Just yeah,

852
00:40:00,600 --> 00:40:02,640
Speaker 3: I don't even disagree necessarily with what he's saying. I

853
00:40:02,680 --> 00:40:04,640
Speaker 3: don't say get over it is the correct opinion.

854
00:40:04,800 --> 00:40:06,920
Speaker 2: I think very easy for a billionaire to be like

855
00:40:07,080 --> 00:40:09,040
Speaker 2: super easy for him to say, you'll be fine.

856
00:40:09,120 --> 00:40:12,239
Speaker 3: My response would be, yes, there's a national project here,

857
00:40:12,400 --> 00:40:15,680
Speaker 3: and part of any tariff strategy will also be making

858
00:40:15,719 --> 00:40:18,200
Speaker 3: sure that prices don't massively increase.

859
00:40:18,239 --> 00:40:20,080
Speaker 1: That's what a politician to say.

860
00:40:20,120 --> 00:40:23,360
Speaker 3: But it's ludicrous for somebody like him to change his

861
00:40:23,440 --> 00:40:27,759
Speaker 3: tune so quickly on tariffs, especially speaking of freaking Davos.

862
00:40:27,880 --> 00:40:31,279
Speaker 1: Yeah, the whole Davos thing. I can't even believe they

863
00:40:31,320 --> 00:40:34,120
Speaker 1: continue to do it, you know, even after all the

864
00:40:34,200 --> 00:40:37,439
Speaker 1: memes and I very useful everything, of course.

865
00:40:37,840 --> 00:40:40,439
Speaker 2: I mean those interviews like that with Andrew ross Orkin

866
00:40:40,520 --> 00:40:43,520
Speaker 2: that's where we got that Alexander Wang interview as well,

867
00:40:44,160 --> 00:40:46,680
Speaker 2: And yeah, they always say a lot of very revealing things,

868
00:40:46,719 --> 00:40:48,600
Speaker 2: and I think it's important to like listen and take

869
00:40:48,600 --> 00:40:48,960
Speaker 2: them out there.

870
00:40:49,160 --> 00:40:51,239
Speaker 1: You're not wrong just for them. I'm like, you have

871
00:40:51,280 --> 00:40:53,520
Speaker 1: no self awareness. It's like, you guys should lock yourself

872
00:40:53,600 --> 00:40:56,000
Speaker 1: back in bohemian grove and do this the proper way.

873
00:40:56,680 --> 00:40:59,400
Speaker 1: You know, wear masks. Don't talk to anybody else on

874
00:40:59,440 --> 00:41:00,920
Speaker 1: a microphone. Yeah you should.

875
00:41:01,600 --> 00:41:03,360
Speaker 2: I mean it's a sign of how much they feel

876
00:41:03,360 --> 00:41:06,040
Speaker 2: that they've conquered the world. They're like, we can just

877
00:41:06,080 --> 00:41:07,680
Speaker 2: do this dow in the open. We can just tell

878
00:41:07,719 --> 00:41:09,520
Speaker 2: you fools what we're up to, and like the way

879
00:41:09,520 --> 00:41:12,359
Speaker 2: we're going to shape the entire world. And I mean

880
00:41:12,719 --> 00:41:14,680
Speaker 2: to a large extent, who can say that they're wrong,

881
00:41:14,840 --> 00:41:18,000
Speaker 2: Like look at the way that oligarchs have completely bought

882
00:41:18,360 --> 00:41:21,600
Speaker 2: the US government and are operating it to their own ends.

883
00:41:21,640 --> 00:41:23,880
Speaker 2: And you understand and you also see, I mean, I

884
00:41:23,880 --> 00:41:26,319
Speaker 2: think you're right about Jamie Diamond, who even before the

885
00:41:26,360 --> 00:41:29,440
Speaker 2: election had actually really shifted the way he was talking

886
00:41:29,480 --> 00:41:33,400
Speaker 2: about Trump. Previously was huge Trump critic, democratic donor all

887
00:41:33,440 --> 00:41:37,200
Speaker 2: that stuff. And you know, after seeing the first Trump administration,

888
00:41:37,280 --> 00:41:39,080
Speaker 2: we're like, oh, well, he gave rich people a giant

889
00:41:39,080 --> 00:41:41,480
Speaker 2: tax gut, it wasn't so bad. He kind of changed

890
00:41:41,480 --> 00:41:44,879
Speaker 2: his tone and became much more comfortable with the Trump administration.

891
00:41:45,040 --> 00:41:47,440
Speaker 2: But the whole tenor of the discussion on inflation has

892
00:41:47,480 --> 00:41:50,160
Speaker 2: really shifted a lot, because obviously, both in the midterms

893
00:41:50,200 --> 00:41:52,880
Speaker 2: and in the presidential election, I mean, voters said their

894
00:41:52,960 --> 00:41:55,200
Speaker 2: number one issue is inflation. And you can understand why

895
00:41:55,280 --> 00:41:59,120
Speaker 2: because having this huge spike in food and fuel prices

896
00:41:59,520 --> 00:42:02,640
Speaker 2: really is difficult for people who are already living at

897
00:42:02,680 --> 00:42:05,399
Speaker 2: the at the ragged edge and struggling to be able

898
00:42:05,400 --> 00:42:07,440
Speaker 2: to put it all together, especially with the cost of

899
00:42:07,480 --> 00:42:10,880
Speaker 2: living crisis in general, how expensive housing prices are, et cetera.

900
00:42:11,400 --> 00:42:15,560
Speaker 2: And you know, the Trump campaign really focused on, Hey,

901
00:42:15,560 --> 00:42:17,799
Speaker 2: we're going to be the ones who can bring prices down,

902
00:42:17,840 --> 00:42:19,440
Speaker 2: and the Biden administration failed you with.

903
00:42:19,400 --> 00:42:20,359
Speaker 4: This, et cetera, et cetera.

904
00:42:21,120 --> 00:42:24,080
Speaker 2: Now that they are taking office, there's a bit of

905
00:42:24,080 --> 00:42:26,239
Speaker 2: a different a bit of a different tone that is

906
00:42:26,280 --> 00:42:29,760
Speaker 2: being struck. Jd Vance was pressed on this by Margaret

907
00:42:29,800 --> 00:42:31,120
Speaker 2: Brennan on the Sunday Shows.

908
00:42:31,160 --> 00:42:33,520
Speaker 4: Let's take a listen to that. You campaigned on lowering

909
00:42:33,600 --> 00:42:37,400
Speaker 4: prices for consumers. We've seen all of these executive orders,

910
00:42:37,400 --> 00:42:39,080
Speaker 4: which one lowers prices.

911
00:42:39,200 --> 00:42:41,520
Speaker 9: We have done a lot and there have been a

912
00:42:41,600 --> 00:42:45,840
Speaker 9: number of executive orders that have caused already jobs to

913
00:42:45,840 --> 00:42:47,960
Speaker 9: start coming back into our country, which is a core

914
00:42:48,040 --> 00:42:51,760
Speaker 9: part of lowering prices. More capital investment, more job creation

915
00:42:51,880 --> 00:42:54,120
Speaker 9: in our economy is one of the things that's going

916
00:42:54,160 --> 00:42:56,799
Speaker 9: to drive down prices for all consumers, but also raise

917
00:42:56,880 --> 00:42:59,480
Speaker 9: wages so that people can afford to buy the things

918
00:42:59,480 --> 00:43:04,320
Speaker 9: that they need. If you look at our of executive orders, Margaret,

919
00:43:04,440 --> 00:43:06,560
Speaker 9: prices are going to come down, but it's going to

920
00:43:06,600 --> 00:43:09,040
Speaker 9: take a little bit of time. Right that the president

921
00:43:09,080 --> 00:43:11,719
Speaker 9: has been president for all of five days, I think

922
00:43:11,760 --> 00:43:14,040
Speaker 9: that in those five days he's accomplished.

923
00:43:13,560 --> 00:43:15,280
Speaker 1: More than Joe Biden did in four years.

924
00:43:15,320 --> 00:43:19,400
Speaker 9: It's been an incredible breakneck pace of activity. We're going

925
00:43:19,480 --> 00:43:21,640
Speaker 9: to work with Congress. We're of course going to have

926
00:43:21,719 --> 00:43:24,560
Speaker 9: more executive orders, and we're going to try the way

927
00:43:24,920 --> 00:43:29,040
Speaker 9: your lower prices is, do you encourage more capital investment

928
00:43:29,120 --> 00:43:30,040
Speaker 9: into our country?

929
00:43:30,360 --> 00:43:33,080
Speaker 2: So fair enough that Trump has only been president for

930
00:43:33,160 --> 00:43:35,480
Speaker 2: five days and does not have you know, complete control

931
00:43:35,560 --> 00:43:39,040
Speaker 2: over pricing of all things, let alone you know, eggs

932
00:43:39,000 --> 00:43:41,759
Speaker 2: wi you're about to talk about specifically. But I think

933
00:43:41,800 --> 00:43:43,800
Speaker 2: they are making a bet soccer. I think they've always

934
00:43:43,800 --> 00:43:46,440
Speaker 2: made a bat. It just wasn't really fore grounded that

935
00:43:46,520 --> 00:43:50,480
Speaker 2: people will tolerate some price increases if they can convince

936
00:43:50,560 --> 00:43:53,800
Speaker 2: them that it's in the overall national interest.

937
00:43:53,920 --> 00:43:54,600
Speaker 1: I think that's true.

938
00:43:54,640 --> 00:43:57,799
Speaker 2: I think that's their political I don't actually think that

939
00:43:57,800 --> 00:44:01,760
Speaker 2: that is true, you know, but they're economic policy. The

940
00:44:01,800 --> 00:44:06,200
Speaker 2: two main planks are, you know, the deportations plus tariffs.

941
00:44:06,920 --> 00:44:09,720
Speaker 2: You will readily admit, anyone who's being honest will readily

942
00:44:09,760 --> 00:44:11,879
Speaker 2: admit that both of those things are likely, at least

943
00:44:11,880 --> 00:44:14,880
Speaker 2: in the short medium term, to lead to price increases,

944
00:44:15,719 --> 00:44:18,120
Speaker 2: But they're betting that they can tell a story about

945
00:44:18,120 --> 00:44:20,680
Speaker 2: that that will make people be like, I can manage

946
00:44:20,680 --> 00:44:22,120
Speaker 2: this and it's quote unquote worth it.

947
00:44:22,160 --> 00:44:24,080
Speaker 3: I mean, I do think that there is an element

948
00:44:24,120 --> 00:44:27,319
Speaker 3: to it which is true. So when I go to

949
00:44:27,400 --> 00:44:32,000
Speaker 3: Japan and there is a guy who's driving the taxi

950
00:44:32,320 --> 00:44:35,640
Speaker 3: who the taxi driver is wearing white gloves in a suit,

951
00:44:36,000 --> 00:44:38,000
Speaker 3: and it's a profession, and he takes a lot of

952
00:44:38,040 --> 00:44:40,920
Speaker 3: pride in that it's not something that is a stepping

953
00:44:40,960 --> 00:44:43,800
Speaker 3: stone to go doing something else. That guy gets paid

954
00:44:43,960 --> 00:44:47,080
Speaker 3: a lot more than any taxi driver in America. It's

955
00:44:47,160 --> 00:44:49,719
Speaker 3: a good experience for him, and for me it's going

956
00:44:49,760 --> 00:44:51,840
Speaker 3: to cost more. And so I think that's one of

957
00:44:51,840 --> 00:44:55,680
Speaker 3: those things where I've been thinking a lot in terms of,

958
00:44:55,719 --> 00:44:59,279
Speaker 3: like you said, with prices, we have two visions of

959
00:44:59,320 --> 00:45:03,879
Speaker 3: Americans society. We can be the one where price is everything,

960
00:45:04,000 --> 00:45:07,400
Speaker 3: and that means that we're all widgets, We're all consumers.

961
00:45:07,600 --> 00:45:09,959
Speaker 3: The price of each individual good itself is the sole

962
00:45:10,040 --> 00:45:13,360
Speaker 3: determinant of my happiness. The price of my stock indicts

963
00:45:13,440 --> 00:45:15,720
Speaker 3: going up twenty two percent as opposed to seventeen percent

964
00:45:16,000 --> 00:45:18,839
Speaker 3: is far more important than whatever might be paid in

965
00:45:18,880 --> 00:45:19,400
Speaker 3: that interim.

966
00:45:19,480 --> 00:45:19,680
Speaker 1: Five.

967
00:45:19,840 --> 00:45:23,080
Speaker 3: But the Trump administration is offering basically an economic nationalist

968
00:45:23,160 --> 00:45:26,200
Speaker 3: view of which almost every other country in the world adopts,

969
00:45:26,239 --> 00:45:31,239
Speaker 3: from Germany to Japan to any European welfare state, which is, yeah,

970
00:45:31,280 --> 00:45:32,960
Speaker 3: there's going to be some stuff that's going to be

971
00:45:33,239 --> 00:45:34,120
Speaker 3: more expensive.

972
00:45:34,320 --> 00:45:37,000
Speaker 1: Some people, though, will get paid more, we will.

973
00:45:36,840 --> 00:45:39,040
Speaker 3: Live in a society in which we feel as if

974
00:45:39,040 --> 00:45:40,720
Speaker 3: we're all a little bit more together.

975
00:45:40,880 --> 00:45:41,200
Speaker 1: I mean.

976
00:45:41,360 --> 00:45:43,880
Speaker 3: And this is both actually a leftist and a rightist

977
00:45:44,120 --> 00:45:48,320
Speaker 3: kind of solution to this, like centrist neoliberal view of GDP.

978
00:45:48,480 --> 00:45:50,279
Speaker 1: So I basically agree with you.

979
00:45:50,320 --> 00:45:52,480
Speaker 3: They are going to need to be careful because what

980
00:45:52,600 --> 00:45:57,000
Speaker 3: I think the Trump administration's greatest danger is was from

981
00:45:57,000 --> 00:46:01,960
Speaker 3: the first administration. It was the feeling chaos, lack of process,

982
00:46:02,239 --> 00:46:06,799
Speaker 3: and things being out of control. And so right now,

983
00:46:06,880 --> 00:46:09,280
Speaker 3: one of the things about Trump which is great politically

984
00:46:09,360 --> 00:46:12,440
Speaker 3: but necessarily bad governmentally, is he'll just throw things at

985
00:46:12,440 --> 00:46:15,960
Speaker 3: the wall. So, for example, in that speech yesterday before Congress,

986
00:46:16,080 --> 00:46:19,879
Speaker 3: he said We're gonna put tariffs on Taiwan. Now, look, philosophically,

987
00:46:19,880 --> 00:46:23,120
Speaker 3: do I think Taiwan should pay more and all it, Yeah, definitely,

988
00:46:23,320 --> 00:46:25,399
Speaker 3: but you know we're also doing this at a moment

989
00:46:25,440 --> 00:46:28,799
Speaker 3: where nvidio stoctors went bound down by seventeen percent. What

990
00:46:28,840 --> 00:46:31,560
Speaker 3: if it causes a market massive stock market crash? And

991
00:46:31,640 --> 00:46:34,160
Speaker 3: what I would argue is worse is just throwing things

992
00:46:34,239 --> 00:46:36,680
Speaker 3: out there all the time, which can be great from

993
00:46:36,680 --> 00:46:40,040
Speaker 3: a negotiation perspective, as we saw with Columbia or whatever.

994
00:46:40,239 --> 00:46:43,960
Speaker 3: But if you have chaos where things are constantly yo yoing,

995
00:46:44,080 --> 00:46:46,800
Speaker 3: like back and forth and back and forth, and people

996
00:46:46,800 --> 00:46:49,480
Speaker 3: don't feel as if there's a coherent agenda, then of

997
00:46:49,520 --> 00:46:52,400
Speaker 3: course they're going to default to well, hey man, you know,

998
00:46:52,719 --> 00:46:54,920
Speaker 3: my prices are going up and I don't even feel

999
00:46:55,080 --> 00:46:56,360
Speaker 3: as if I'm getting anything.

1000
00:46:56,400 --> 00:46:59,960
Speaker 2: Well, and that's that's the piece, because what you are

1001
00:47:00,040 --> 00:47:04,719
Speaker 2: articulated is a at least coherent worldview of you don't

1002
00:47:04,719 --> 00:47:07,200
Speaker 2: want prices aren't going to be every and that is

1003
00:47:07,239 --> 00:47:09,359
Speaker 2: the way our society is structured right now. Like you

1004
00:47:09,400 --> 00:47:13,440
Speaker 2: are more of a consumer than you are a citizen,

1005
00:47:13,840 --> 00:47:16,919
Speaker 2: right absolutely, and all. I mean that's the way antitrust

1006
00:47:17,520 --> 00:47:22,080
Speaker 2: regulation was reinterpreted to be. You know, as long as

1007
00:47:22,080 --> 00:47:24,919
Speaker 2: people are getting lower prices than there's no concern about

1008
00:47:24,920 --> 00:47:28,440
Speaker 2: these giant monopolies. They're only to the good. That has

1009
00:47:28,520 --> 00:47:33,360
Speaker 2: been the market logic. The view you explain is, well, know,

1010
00:47:33,800 --> 00:47:38,239
Speaker 2: we're going to raise prices on certain things, but you're

1011
00:47:38,280 --> 00:47:41,440
Speaker 2: going to have a higher wage. The problem is that,

1012
00:47:41,840 --> 00:47:45,040
Speaker 2: especially now in this trump you know, in this iteration

1013
00:47:45,160 --> 00:47:49,200
Speaker 2: of trump Ism, with Elon Musk really running the show

1014
00:47:49,280 --> 00:47:52,040
Speaker 2: in a lot of respects, that piece about the wages

1015
00:47:52,880 --> 00:47:56,040
Speaker 2: is I mean, that's missing because these are people. I

1016
00:47:56,040 --> 00:47:58,840
Speaker 2: mean Elon Musk literally wants to get rid of the

1017
00:47:59,000 --> 00:48:02,520
Speaker 2: entire natural labor relationationspoort right. He wants to be able

1018
00:48:02,560 --> 00:48:06,799
Speaker 2: to bring in h one b indentured servants to undercut

1019
00:48:07,000 --> 00:48:08,240
Speaker 2: American wages.

1020
00:48:08,800 --> 00:48:10,680
Speaker 4: The Treasury Secretary Scott.

1021
00:48:10,400 --> 00:48:12,759
Speaker 2: Bessant, who just got confirmed, says he doesn't believe in

1022
00:48:12,760 --> 00:48:13,879
Speaker 2: a minimum wage.

1023
00:48:13,719 --> 00:48:15,319
Speaker 4: At all whatsoever.

1024
00:48:16,320 --> 00:48:19,719
Speaker 2: The tariff the program that has been like sort of

1025
00:48:19,719 --> 00:48:22,960
Speaker 2: theoretically floated of we're going to get rid of income taxes,

1026
00:48:23,000 --> 00:48:25,040
Speaker 2: but we're going to make up for it with tariffs

1027
00:48:25,120 --> 00:48:29,160
Speaker 2: or consumption tax potentially that is wildly regressive, That is

1028
00:48:29,200 --> 00:48:33,000
Speaker 2: going to take more out of people's paychecks. Who are

1029
00:48:33,080 --> 00:48:36,080
Speaker 2: you know, working class and middle class et cetera. You know,

1030
00:48:36,160 --> 00:48:40,120
Speaker 2: so that's that's the part where it really doesn't work.

1031
00:48:40,200 --> 00:48:44,680
Speaker 2: You can't spike prices and people are still getting exploited

1032
00:48:44,760 --> 00:48:48,439
Speaker 2: and have no labor power and have low wages and

1033
00:48:48,600 --> 00:48:51,920
Speaker 2: you know, getting like screwed and worked harder and harder

1034
00:48:51,960 --> 00:48:54,640
Speaker 2: with lower and lower returns, and housing prices are going up,

1035
00:48:54,680 --> 00:48:58,480
Speaker 2: et cetera. You can't those two pieces politically, They're not

1036
00:48:58,520 --> 00:49:01,560
Speaker 2: going to work ultimately in the long term. So if

1037
00:49:01,560 --> 00:49:05,520
Speaker 2: you're going to invest people in this totally different conception

1038
00:49:05,600 --> 00:49:09,880
Speaker 2: of society of Okay, prices aren't everything. We have strategic

1039
00:49:09,880 --> 00:49:13,360
Speaker 2: and national goals, and we're going to prioritize your wages,

1040
00:49:13,640 --> 00:49:15,680
Speaker 2: that piece has to be there, Like people have to

1041
00:49:15,719 --> 00:49:18,800
Speaker 2: feel like their wages are going up. And I see

1042
00:49:19,280 --> 00:49:23,400
Speaker 2: much evidence in the other direction that what the actual

1043
00:49:23,400 --> 00:49:26,800
Speaker 2: priority is is making it easier to fire striking workers,

1044
00:49:26,960 --> 00:49:28,920
Speaker 2: making it easier to bring in H one B and

1045
00:49:29,160 --> 00:49:33,200
Speaker 2: H two B indentured servants to undercut American wages in

1046
00:49:33,239 --> 00:49:36,480
Speaker 2: these various industries, et cetera. So that's I mean, this

1047
00:49:37,160 --> 00:49:39,799
Speaker 2: is kind of like the Steve Bannon versus Elon Musk fight,

1048
00:49:39,960 --> 00:49:43,279
Speaker 2: because Bannon's vision is much more like the one you articulated,

1049
00:49:43,320 --> 00:49:45,279
Speaker 2: and that is not Elon Musk's vision.

1050
00:49:45,440 --> 00:49:46,200
Speaker 1: That's part of the issue.

1051
00:49:46,200 --> 00:49:49,640
Speaker 3: What's the fundamental tension within Doze, within Elon, within the

1052
00:49:49,760 --> 00:49:52,560
Speaker 3: entire Trump administration. I would even say between JD and

1053
00:49:53,120 --> 00:49:56,040
Speaker 3: Donald Trump's coalition. If you look at all of these people,

1054
00:49:56,080 --> 00:49:58,239
Speaker 3: Jdvan I will not speak for him, I would never

1055
00:49:58,320 --> 00:50:00,319
Speaker 3: dare to. I'm just saying, like I interact them. I've

1056
00:50:00,360 --> 00:50:02,560
Speaker 3: interviewed him many times, and in those he's like this,

1057
00:50:02,760 --> 00:50:05,640
Speaker 3: that would I would think is largely the vision that

1058
00:50:05,680 --> 00:50:08,680
Speaker 3: he would articulate to you. But Donald Trump also is

1059
00:50:08,960 --> 00:50:12,879
Speaker 3: a person of a big coalition, and with Elon, I mean,

1060
00:50:12,880 --> 00:50:16,160
Speaker 3: for example, there are already signs of huge fights. So

1061
00:50:16,160 --> 00:50:18,200
Speaker 3: I don't know if he saw this yesterday, but one

1062
00:50:18,239 --> 00:50:20,479
Speaker 3: of the things that Trump said, which has really thrown

1063
00:50:20,520 --> 00:50:23,439
Speaker 3: a wrench into all these reconciliation arguments, is he says

1064
00:50:23,480 --> 00:50:25,560
Speaker 3: he will not sign a bill that cuts a single

1065
00:50:25,640 --> 00:50:28,719
Speaker 3: penny from Medicare or Social Security. And he says that

1066
00:50:28,800 --> 00:50:31,840
Speaker 3: at the very same time that Elon is tweeting about

1067
00:50:31,880 --> 00:50:35,040
Speaker 3: massive entitlement fraud and about how there needs to be

1068
00:50:35,120 --> 00:50:38,640
Speaker 3: a serious review and a rethink. We've seen this also

1069
00:50:39,080 --> 00:50:42,560
Speaker 3: in the OMB and their own theories is like about

1070
00:50:42,800 --> 00:50:46,440
Speaker 3: what we want out of VISA like H one, BH

1071
00:50:46,480 --> 00:50:48,879
Speaker 3: two B, what all of that will look like. I mean, really,

1072
00:50:48,920 --> 00:50:51,680
Speaker 3: I'm fascinated to see when the next real immigration bill

1073
00:50:51,920 --> 00:50:55,800
Speaker 3: comes across because right now all ICE operations are currently

1074
00:50:55,800 --> 00:50:58,239
Speaker 3: about people who are criminals, Like we haven't even talked

1075
00:50:58,239 --> 00:51:02,160
Speaker 3: about people who are here illegally. But beyond that, even

1076
00:51:02,200 --> 00:51:05,320
Speaker 3: bigger question is like, well what about the legal system,

1077
00:51:05,480 --> 00:51:08,000
Speaker 3: like how many people are being l It's a literally

1078
00:51:08,080 --> 00:51:10,680
Speaker 3: zero sum number in terms of you know, one hundred thousand,

1079
00:51:10,719 --> 00:51:12,600
Speaker 3: two h thousand, three hunred thousand and one million where

1080
00:51:12,640 --> 00:51:13,520
Speaker 3: we currently are.

1081
00:51:13,560 --> 00:51:14,880
Speaker 1: What's the number, what type? You know?

1082
00:51:14,960 --> 00:51:16,680
Speaker 3: What is it going to be more H one? But

1083
00:51:16,680 --> 00:51:18,320
Speaker 3: we're going to increase the allotment, right that would be

1084
00:51:18,360 --> 00:51:22,000
Speaker 3: a huge substate to the technology industry. So I'm very

1085
00:51:22,040 --> 00:51:25,160
Speaker 3: curious to see how that all comes out. And that's

1086
00:51:25,200 --> 00:51:27,840
Speaker 3: what I mean about the danger here for Trump is

1087
00:51:28,160 --> 00:51:31,040
Speaker 3: the other problem is that the market does not reward

1088
00:51:31,600 --> 00:51:34,640
Speaker 3: anything that I am saying, the market.

1089
00:51:34,360 --> 00:51:36,600
Speaker 1: Only rewards short term gain.

1090
00:51:36,680 --> 00:51:38,879
Speaker 3: I mean, even look at this whole end video thing,

1091
00:51:39,600 --> 00:51:42,320
Speaker 3: even the idea oh in video is stocketting. Yeah, in

1092
00:51:42,440 --> 00:51:44,600
Speaker 3: Vidia's back to where it was in October Okay, you know,

1093
00:51:44,719 --> 00:51:46,600
Speaker 3: so the trillions and trillions of.

1094
00:51:46,640 --> 00:51:48,160
Speaker 1: Dollars of value have been created.

1095
00:51:48,160 --> 00:51:49,800
Speaker 3: It could drop one hundred percent, it would still be

1096
00:51:49,880 --> 00:51:52,520
Speaker 3: up from where it was a while ago. My point

1097
00:51:52,560 --> 00:51:55,000
Speaker 3: is that these guys have to live and die and

1098
00:51:55,080 --> 00:51:57,960
Speaker 3: sweat by the quarter, where a nation should not be

1099
00:51:58,000 --> 00:51:58,680
Speaker 3: governed that way.

1100
00:51:58,719 --> 00:52:00,320
Speaker 1: And the problem that we have.

1101
00:52:00,719 --> 00:52:03,840
Speaker 3: Is that all of our elites are currently governed on

1102
00:52:03,880 --> 00:52:06,600
Speaker 3: the basis of this, like quarter by quarter, stock market

1103
00:52:06,600 --> 00:52:10,040
Speaker 3: by stock market profit. I mean even right now there's

1104
00:52:10,040 --> 00:52:12,440
Speaker 3: a discussion and a fear in the markets. They're like,

1105
00:52:12,600 --> 00:52:15,279
Speaker 3: are the days of twenty two percent a year over

1106
00:52:15,280 --> 00:52:16,960
Speaker 3: your growth in the s and p five hundred over?

1107
00:52:17,000 --> 00:52:19,719
Speaker 3: I'm like, okay, so what Like, I know this is

1108
00:52:19,800 --> 00:52:23,479
Speaker 3: very privileging to say, but like, okay, that's an abnormal thing.

1109
00:52:23,640 --> 00:52:26,799
Speaker 1: The historical average is like eight percent. If it goes

1110
00:52:26,840 --> 00:52:28,400
Speaker 1: to twelve, so be it.

1111
00:52:28,600 --> 00:52:30,600
Speaker 3: There's some you know, there are a lot of reasons

1112
00:52:30,920 --> 00:52:33,040
Speaker 3: for that, and that's why I just articulate. I think

1113
00:52:33,080 --> 00:52:35,280
Speaker 3: it's going to be very very difficult though for Trump,

1114
00:52:35,280 --> 00:52:38,880
Speaker 3: and like I said, all of the incentive monetarily behind

1115
00:52:39,040 --> 00:52:42,440
Speaker 3: him and really behind the entire American elite is to

1116
00:52:42,480 --> 00:52:45,040
Speaker 3: think in this quarter by quarter theory. And so if

1117
00:52:45,080 --> 00:52:48,160
Speaker 3: you get a situation where you have higher tariffs and

1118
00:52:48,239 --> 00:52:51,040
Speaker 3: you have big corporate giveaways and all this, and you lose,

1119
00:52:51,800 --> 00:52:54,279
Speaker 3: you know, like you said, the Bannonist argument here, which

1120
00:52:54,280 --> 00:52:57,160
Speaker 3: has a coherent view of immigration, restriction of higher wages,

1121
00:52:57,360 --> 00:53:00,239
Speaker 3: and is obviously diametrically opposed to.

1122
00:53:00,200 --> 00:53:02,440
Speaker 1: A lot of what these tech guys want. That's going

1123
00:53:02,480 --> 00:53:03,239
Speaker 1: to be the big fight.

1124
00:53:03,280 --> 00:53:05,880
Speaker 3: And if you have a mix, you actually end up

1125
00:53:05,880 --> 00:53:07,920
Speaker 3: getting the worst of both worlds. And I think that

1126
00:53:07,920 --> 00:53:10,920
Speaker 3: that's a huge risk right now for Donald Trump in

1127
00:53:10,960 --> 00:53:11,560
Speaker 3: this administration.

1128
00:53:11,680 --> 00:53:14,120
Speaker 4: Yeah, where you end up with low wages and high prices.

1129
00:53:14,480 --> 00:53:16,959
Speaker 2: And I mean, based on the way you know, Trump

1130
00:53:17,040 --> 00:53:20,200
Speaker 2: sided with Elon on this big H one B fight,

1131
00:53:20,640 --> 00:53:22,759
Speaker 2: that seems to me very much the direction that they're

1132
00:53:22,760 --> 00:53:29,520
Speaker 2: heading in. Let's talk specifically about egg prices, because this

1133
00:53:29,600 --> 00:53:32,240
Speaker 2: is this is really important for a variety of reasons.

1134
00:53:32,440 --> 00:53:33,640
Speaker 4: Can put this up on the screen.

1135
00:53:33,840 --> 00:53:38,160
Speaker 2: So the cost of eggs has dramatically chirocketed Business Insider

1136
00:53:38,200 --> 00:53:41,399
Speaker 2: is saying they might be expensive forever. They're saying it's

1137
00:53:41,440 --> 00:53:43,760
Speaker 2: not just bird flu that's causing egg prices to soar,

1138
00:53:43,840 --> 00:53:47,600
Speaker 2: although that is a significant part of it so according

1139
00:53:47,600 --> 00:53:48,680
Speaker 2: to Business Insider.

1140
00:53:48,920 --> 00:53:50,719
Speaker 4: I thought they were just insider. Now they went back

1141
00:53:50,719 --> 00:53:51,960
Speaker 4: to Business Insider, are.

1142
00:53:51,800 --> 00:53:53,080
Speaker 1: They I don't know.

1143
00:53:53,200 --> 00:53:55,799
Speaker 2: I guess I always thought Business Insider was better than

1144
00:53:55,800 --> 00:53:58,280
Speaker 2: Insider anyway, So if they made the change back, I think.

1145
00:53:58,120 --> 00:53:58,759
Speaker 1: That was the right.

1146
00:53:58,840 --> 00:54:02,360
Speaker 3: That's a fascinating study this company in the digital media landscape,

1147
00:54:02,400 --> 00:54:03,440
Speaker 3: like what they've turned it.

1148
00:54:03,480 --> 00:54:04,000
Speaker 1: But that's all.

1149
00:54:04,040 --> 00:54:06,600
Speaker 4: Yeah, she's completely paywild. I don't know. They irritate me,

1150
00:54:06,640 --> 00:54:07,080
Speaker 4: but whatever.

1151
00:54:07,160 --> 00:54:09,279
Speaker 2: The cost of a dozen grade A large eggs hit

1152
00:54:09,320 --> 00:54:12,360
Speaker 2: four fifteen in December, per the Bureau of Labor Statistics.

1153
00:54:12,400 --> 00:54:14,320
Speaker 2: That's up from two dollars and fifty one cents a

1154
00:54:14,400 --> 00:54:16,960
Speaker 2: year ago. Average price of eggs has not been below

1155
00:54:17,000 --> 00:54:19,799
Speaker 2: three dollars since June. Hasn't been below two dollars since

1156
00:54:19,800 --> 00:54:23,200
Speaker 2: the start of twenty twenty two. We're all in uncharted territory, said,

1157
00:54:23,239 --> 00:54:26,279
Speaker 2: I love this job title, a global trade strategist at

1158
00:54:26,320 --> 00:54:29,920
Speaker 2: Eggs Unlimited, a Californian based explier who knew that was.

1159
00:54:29,840 --> 00:54:30,439
Speaker 4: Even a job.

1160
00:54:30,680 --> 00:54:33,200
Speaker 2: He added that the industry had lost twenty six million

1161
00:54:33,239 --> 00:54:36,800
Speaker 2: birds since October, more than seven percent of the total flock.

1162
00:54:37,120 --> 00:54:39,279
Speaker 2: That's because of bird flu. It seems as bad as

1163
00:54:39,320 --> 00:54:42,000
Speaker 2: it's ever been, he said, And the producers don't really

1164
00:54:42,080 --> 00:54:44,080
Speaker 2: have a recourse who can put this next piece up

1165
00:54:44,080 --> 00:54:46,800
Speaker 2: on the screen, just with regards to the bird flu

1166
00:54:47,200 --> 00:54:50,280
Speaker 2: piece of this. So we keep getting really bad news

1167
00:54:50,440 --> 00:54:52,920
Speaker 2: about the spread of bird flu. You know, when this

1168
00:54:53,080 --> 00:54:57,040
Speaker 2: was originally detected, I think first in a herd of

1169
00:54:57,760 --> 00:55:00,960
Speaker 2: a herd of cows in Texas, there was an opportunity

1170
00:55:01,000 --> 00:55:05,320
Speaker 2: to really crack down and isolate the strain and stamp

1171
00:55:05,320 --> 00:55:05,600
Speaker 2: it down.

1172
00:55:05,680 --> 00:55:08,080
Speaker 4: The Biden administration, their.

1173
00:55:07,880 --> 00:55:11,160
Speaker 2: Egg secretary is very pro business, very tied in I

1174
00:55:11,200 --> 00:55:14,520
Speaker 2: think used to be like a dairy lobbyist, and they

1175
00:55:14,520 --> 00:55:18,439
Speaker 2: didn't want to disrupt people making money, so they did

1176
00:55:18,440 --> 00:55:21,000
Speaker 2: not take the steps early on, and now you have

1177
00:55:21,160 --> 00:55:25,319
Speaker 2: this massive, you know, nationwide spread that is leading to

1178
00:55:25,680 --> 00:55:26,640
Speaker 2: these flocks.

1179
00:55:26,280 --> 00:55:26,919
Speaker 4: Having to be killed.

1180
00:55:26,960 --> 00:55:29,839
Speaker 2: I know that they in Georgia they shut down all

1181
00:55:29,960 --> 00:55:34,360
Speaker 2: poultry related activity, so you know, eggs and chicken just

1182
00:55:34,400 --> 00:55:37,359
Speaker 2: completely shut down. Georgia is a major producer of both

1183
00:55:37,400 --> 00:55:40,319
Speaker 2: of those things. The latest development here is that you've

1184
00:55:40,320 --> 00:55:43,160
Speaker 2: had the first outbreak of a different rare bird flu

1185
00:55:43,200 --> 00:55:46,800
Speaker 2: in poultry that was detected on a duck farm in California.

1186
00:55:47,120 --> 00:55:50,360
Speaker 2: That's according to the World Organization for Animal Health Authority

1187
00:55:50,400 --> 00:55:52,680
Speaker 2: said the discovery of this one is called H five

1188
00:55:52,800 --> 00:55:56,000
Speaker 2: and nine bird flu in poultry came alongside the detection

1189
00:55:56,120 --> 00:56:00,480
Speaker 2: of the more common five and one strain all the

1190
00:56:00,480 --> 00:56:04,120
Speaker 2: same farm in is it pronounced Mercid County, California.

1191
00:56:04,160 --> 00:56:05,200
Speaker 4: I'm not sure, I do not know.

1192
00:56:05,360 --> 00:56:07,520
Speaker 2: Almost one hundred and nineteen thousand birds on the farm

1193
00:56:07,560 --> 00:56:11,040
Speaker 2: had been killed since early December. That's the first confirmed

1194
00:56:11,160 --> 00:56:14,759
Speaker 2: case of this H five and nine in poultry in

1195
00:56:14,800 --> 00:56:17,560
Speaker 2: the US. And my understanding is the reason that this

1196
00:56:17,600 --> 00:56:21,759
Speaker 2: particular strain is even more concerning is because it is

1197
00:56:22,040 --> 00:56:24,720
Speaker 2: closer to being able to make the jump into human beings.

1198
00:56:24,719 --> 00:56:27,360
Speaker 2: And you know, that's what's really feared, is that because

1199
00:56:27,400 --> 00:56:33,200
Speaker 2: you have such widespread, you know, infection rates both among

1200
00:56:33,280 --> 00:56:36,239
Speaker 2: dairy cows and among bird flocks, and you have had

1201
00:56:36,239 --> 00:56:38,840
Speaker 2: farm workers who have come into direct contact who have

1202
00:56:38,880 --> 00:56:41,600
Speaker 2: been sickened as well in some other people who you

1203
00:56:41,600 --> 00:56:45,400
Speaker 2: know were sickened from other reasons. But in any case,

1204
00:56:45,840 --> 00:56:48,560
Speaker 2: you worry that your a mutation away from this being

1205
00:56:48,560 --> 00:56:51,960
Speaker 2: able to spread readily among human beings. And you know,

1206
00:56:52,000 --> 00:56:56,880
Speaker 2: so that's the sort of concern regarding the pandemic. The

1207
00:56:57,239 --> 00:57:00,000
Speaker 2: concern here regarding inflation is obviously that they don't have

1208
00:57:00,080 --> 00:57:03,040
Speaker 2: it under control. This will impact all kinds of different

1209
00:57:03,400 --> 00:57:06,120
Speaker 2: food prices, but specifically right now we really see a

1210
00:57:06,160 --> 00:57:07,640
Speaker 2: massive impact in terms of eggs.

1211
00:57:07,640 --> 00:57:08,399
Speaker 1: Eggs is like gas.

1212
00:57:08,440 --> 00:57:11,399
Speaker 3: It's one of those things that everybody sees every week.

1213
00:57:11,520 --> 00:57:13,960
Speaker 3: You either drive past it or you are at the

1214
00:57:14,000 --> 00:57:14,720
Speaker 3: grocery store.

1215
00:57:14,520 --> 00:57:16,120
Speaker 1: And you're like, what, what'll that say?

1216
00:57:16,280 --> 00:57:18,440
Speaker 3: Everyone's got the story right now of the sign at

1217
00:57:18,480 --> 00:57:20,840
Speaker 3: the grocery store that's like, due to an avian bird

1218
00:57:20,880 --> 00:57:24,680
Speaker 3: flu pandemic, you know, our egg supply is currently limited.

1219
00:57:25,240 --> 00:57:27,400
Speaker 1: I experienced. I was, I was at Whole Foods. I

1220
00:57:27,400 --> 00:57:28,760
Speaker 1: don't normally shop at Whole Foods.

1221
00:57:29,000 --> 00:57:30,320
Speaker 3: I was buy it and I walked in and I

1222
00:57:30,400 --> 00:57:31,320
Speaker 3: was like, oh, I want to what the price of

1223
00:57:31,360 --> 00:57:34,360
Speaker 3: eggs right now is. So I walked over and the

1224
00:57:34,480 --> 00:57:37,800
Speaker 3: Vital Farms pasture raised eggs are going for one dollar

1225
00:57:37,840 --> 00:57:38,120
Speaker 3: an egg.

1226
00:57:38,200 --> 00:57:41,000
Speaker 1: It was like eleven sixty nine a dozen. Keep in mind,

1227
00:57:41,080 --> 00:57:41,520
Speaker 1: this is.

1228
00:57:41,480 --> 00:57:45,280
Speaker 3: Like buying you know, the most expensive gas or whatever

1229
00:57:45,360 --> 00:57:47,400
Speaker 3: what is it called, like premium gas, but still, I

1230
00:57:47,480 --> 00:57:50,160
Speaker 3: mean twelve dollars as there's a lot of money, and

1231
00:57:50,360 --> 00:57:51,840
Speaker 3: you know, I think, what's the average price of eggs

1232
00:57:51,880 --> 00:57:53,600
Speaker 3: right now is like two three box.

1233
00:57:53,480 --> 00:57:56,600
Speaker 4: It says four fifteen. Wow, four fifteen.

1234
00:57:57,080 --> 00:57:57,320
Speaker 5: Yeah.

1235
00:57:57,360 --> 00:58:01,040
Speaker 2: I checked it at my little local, like veryvery normal

1236
00:58:01,040 --> 00:58:03,120
Speaker 2: standard grocery store in King George County, Virginia.

1237
00:58:03,120 --> 00:58:04,480
Speaker 4: In the food line and.

1238
00:58:04,560 --> 00:58:07,920
Speaker 2: The pasture raised eggs there were eight dollars. So even

1239
00:58:07,960 --> 00:58:11,560
Speaker 2: in just like you know, a regular kind of place,

1240
00:58:11,600 --> 00:58:12,200
Speaker 2: not whole food.

1241
00:58:12,280 --> 00:58:15,160
Speaker 3: I only eat past raise eggs, and I acknowledge this

1242
00:58:15,200 --> 00:58:17,080
Speaker 3: from a position of privilege. But the cheapest I can

1243
00:58:17,080 --> 00:58:18,760
Speaker 3: find is like six ' ninety nine, and that's at

1244
00:58:18,760 --> 00:58:20,760
Speaker 3: Wegmans and or Trader Joe's.

1245
00:58:20,800 --> 00:58:21,360
Speaker 1: But that is a lot.

1246
00:58:21,400 --> 00:58:23,360
Speaker 3: I mean I remember paying not that long those like

1247
00:58:23,400 --> 00:58:25,960
Speaker 3: four bucks something like that in the beginning.

1248
00:58:26,000 --> 00:58:28,200
Speaker 1: I think they were only like three point fifty. So

1249
00:58:28,240 --> 00:58:29,080
Speaker 1: to see them.

1250
00:58:29,000 --> 00:58:32,480
Speaker 3: Double their price, not only that, but it means first

1251
00:58:32,520 --> 00:58:34,840
Speaker 3: of all, eating healthier as usual shouldn't be more expensive.

1252
00:58:34,840 --> 00:58:35,920
Speaker 1: Of course it is, right.

1253
00:58:36,040 --> 00:58:38,720
Speaker 3: But you also look at you know, there's families out

1254
00:58:38,720 --> 00:58:41,080
Speaker 3: there that buy them by what costco palettes you know

1255
00:58:41,120 --> 00:58:44,080
Speaker 3: that just buy eggs like that, and so a modest increase,

1256
00:58:44,120 --> 00:58:45,640
Speaker 3: especially if you have a bunch of kids, that's a

1257
00:58:45,720 --> 00:58:47,040
Speaker 3: lot of money that people are of.

1258
00:58:47,000 --> 00:58:48,640
Speaker 2: A card well, and it's one of the more affordable

1259
00:58:48,640 --> 00:58:53,440
Speaker 2: typically approaches absolutely, so you know impact there obviously eggs

1260
00:58:53,440 --> 00:58:55,720
Speaker 2: going all kinds of different things, and like you said,

1261
00:58:55,760 --> 00:58:58,600
Speaker 2: it is just kind of one of those benchmarkers of

1262
00:58:58,680 --> 00:59:01,880
Speaker 2: where things are at. And I think, you know, it's

1263
00:59:01,920 --> 00:59:05,760
Speaker 2: it's it underscores a variety of political risks here for

1264
00:59:05,800 --> 00:59:08,760
Speaker 2: the Trump administration, both in terms of food prices, which

1265
00:59:08,840 --> 00:59:11,120
Speaker 2: was a central promise of the campaign, and also in

1266
00:59:11,200 --> 00:59:13,880
Speaker 2: terms of you know, we don't know what's going to

1267
00:59:13,920 --> 00:59:17,120
Speaker 2: happen with the bird flu spread, and god forbid, we

1268
00:59:17,200 --> 00:59:19,440
Speaker 2: have another pandemic, both in terms of the death and

1269
00:59:19,560 --> 00:59:21,200
Speaker 2: just like, oh my god, the politics of that are

1270
00:59:21,200 --> 00:59:23,920
Speaker 2: going to be absolutely terrifying and horrendous.

1271
00:59:23,960 --> 00:59:25,880
Speaker 1: There would be no politics, just people would die.

1272
00:59:25,960 --> 00:59:29,760
Speaker 3: Like I'm pretty much convinced that there would be we have.

1273
00:59:29,880 --> 00:59:31,640
Speaker 4: No ability to have a national response.

1274
00:59:31,640 --> 00:59:35,760
Speaker 3: You would actually a pandemic, a plague like one third

1275
00:59:35,920 --> 00:59:39,880
Speaker 3: killer to actually shape up like any what's I don't

1276
00:59:39,920 --> 00:59:41,920
Speaker 3: know what the casualty numbers are on bird flu in

1277
00:59:41,960 --> 00:59:44,600
Speaker 3: terms of the number of people infect the death ratio

1278
00:59:45,000 --> 00:59:47,360
Speaker 3: or whatever, but you would need, seriously something that kills

1279
00:59:47,360 --> 00:59:49,920
Speaker 3: like thirty percent of the population for everybody to wear

1280
00:59:50,040 --> 00:59:52,120
Speaker 3: and I think rightfully to be honest, I mean, you know,

1281
00:59:52,360 --> 00:59:54,240
Speaker 3: if someone's been try and tell me what to do again,

1282
00:59:54,280 --> 00:59:55,280
Speaker 3: I'm like, we'll see.

1283
00:59:55,440 --> 00:59:57,080
Speaker 1: Well, you know, I got to see a lot of

1284
00:59:57,120 --> 00:59:57,560
Speaker 1: evidence

1285
01:00:00,760 --> 01:00:02,280
Speaker 2: Speak