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Speaker 1: This is Wall Street Week. I'm David Weston bringing you

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Speaker 1: stories of capitalism. The AI race isn't just among companies

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Speaker 1: and countries to get there first. It's also a contest

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Speaker 1: between scientific discovery and making a whole lot of money,

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Speaker 1: and Demessavas is trying to win at both. Plus, if

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Speaker 1: we don't watch out, China will end up beating the

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Speaker 1: US in AI by winning the race to bring new

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Speaker 1: power online, including through a dramatic increase in renewables. And

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Speaker 1: even as some governments are trying to attract new business

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Speaker 1: and well through favorable taxes, others are going the other way,

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Speaker 1: which has led to a nasty public spat between Ken

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Speaker 1: Griffin and New York's Mayor Memdani. But we begin with

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Speaker 1: the war in Iran, which seems far from over despite

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Speaker 1: President Trump's wishes. But so far the war hasn't really

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Speaker 1: bothered the debt and equity markets all that much. Bridgewater

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Speaker 1: founder Ray Daalio has spent a career making long term

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Speaker 1: investments based on his understanding of the geopolitics and the

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Speaker 1: politics of great economic powers like the US being challenged

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Speaker 1: by others.

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Speaker 2: Follow the cash, Follow the money.

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Speaker 3: Okay, there's a reaction like wars are bad and wars

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Speaker 3: are bad. But the reality is markets trade as the

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Speaker 3: present value of future cash flows by and large, and

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Speaker 3: so if you've got the cash, followed the cash. So

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Speaker 3: what's happening in the way of changes, what it means

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Speaker 3: for energy in Asia or what it means here and

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Speaker 3: for our cash flows. But the markets are trading on

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Speaker 3: the basis of the cash flow. So when we came

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Speaker 3: into this period of time, there was a reaction before

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Speaker 3: we had the earnings reports where there was a reaction

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Speaker 3: that this is a scary thing.

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Speaker 2: Quite often markets will sell off.

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Speaker 3: At that time, they did sell off, and then we

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Speaker 3: had great earnings estimates and the reported earnings were much

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Speaker 3: greater than.

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Speaker 2: The actual earnings.

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Speaker 3: So follow the money, Okay, At the end of the day,

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Speaker 3: you're exchanging alumsum payment for a future cash flow, and

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Speaker 3: that's what matters.

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Speaker 1: What about those longer term treads, I mean tectonic plates

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Speaker 1: as they were shifting, whether it's monetary, where there's financial,

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Speaker 1: whether it's geopolitical. How does the Warner run fit into

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Speaker 1: those sort of long term shifts.

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Speaker 3: Yeah, it's interesting if you look at the markets, Pearl

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Speaker 3: Harbor comes imagine that and you see not much effects

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Speaker 3: initial effect, and then you see the cash flow as

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Speaker 3: a mattering.

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Speaker 2: But over the period of time it depends.

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Speaker 3: There are there are the winners, there are losers, and

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Speaker 3: they're in the neutral countries. Okay, economically, the winners still

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Speaker 3: experience the cost of the war, the debt, like the

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Speaker 3: British Empire had the debt and had its consequences.

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Speaker 2: The losers of the war get wiped out.

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Speaker 3: You change all orders, you change the domestic political order,

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Speaker 3: the international order, the monetary order, and almost everything. The

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Speaker 3: winners are the neutral countries because they profit during the war.

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Speaker 2: The United States made a.

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Speaker 3: Lot of money in both World War One and World

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Speaker 3: War Two in the time when that wasn't in the wars,

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Speaker 3: and then it accumulated a lot of gold and so on.

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Speaker 2: Many it entered the period late.

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Speaker 3: So the neutral countries are the ones that end up

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Speaker 3: not being disrupted and end up doing the best.

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Speaker 1: I'm not even sure what it means for the US

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Speaker 1: to win the war in Iran right now, but I

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Speaker 1: think it's clear. Tell me, Okay, the world is looking

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Speaker 1: at will Iran have this control of the Strait of Homos,

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Speaker 1: Will it retain the.

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Speaker 2: Uranium, the nuclear and Will.

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Speaker 3: It also have the power through the missiles and others

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Speaker 3: to inflict harm. Will the United States have the power

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Speaker 3: to fight the war? In other words, with politics and

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Speaker 3: Americans with gas prices and cost of living, we now

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Speaker 3: have a situation where the world is looking at this.

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Speaker 2: And defining it.

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Speaker 3: Does the United States have the capacity to win the war?

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Speaker 3: And this has huge implications because.

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Speaker 2: It means.

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Speaker 3: For countries, it means alliances. Why do they have the

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Speaker 3: bases there? The United States has about seven hundred and

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Speaker 3: fifty bases in about eighty countries, and those bases are

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Speaker 3: largely there under the assumption that the United States will

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Speaker 3: turn up and defend them. Right now that perception is changing,

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Speaker 3: So I think winning the war is clear. Iran is

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Speaker 3: perceived as a middle power, not a great power, and

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Speaker 3: can the United States win it or not? And this

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Speaker 3: is now having a big effect in when I go

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Speaker 3: around the world, like in Asia. You know, the United

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Speaker 3: States has been viewed as a countervailing force relative to China.

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Speaker 3: Now it's believed that that the United States cannot be

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Speaker 3: relied on to fight that war, will not be there

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Speaker 3: with those bases, and this is changing relationships with China too.

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Speaker 3: You're seeing a number of leaders go up to China

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Speaker 3: and essentially essentially have relations. But it's like the tribute system.

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Speaker 3: But also in the region, there's the recognition in their

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Speaker 3: view that there is an environment where the countries in

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Speaker 3: the region I have to recognize and respect that power.

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Speaker 3: And so now you're seeing that happen. That tribute system

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Speaker 3: is not a oppressive controlling system. It's much more like

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Speaker 3: there's the person the more powerful have an obligation to

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Speaker 3: behave well with the less powerful, and the less powerful

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Speaker 3: have an obligation to recognize the more powerful, and they

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Speaker 3: should operate in a harmonious way.

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Speaker 2: You say that as.

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Speaker 1: Far as we can tell, you can tell the Chinese

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Speaker 1: Binelarges think they're doing pretty well in the rivalry with

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Speaker 1: the United States.

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Speaker 3: Right now, China Inc. Is making a ton of money.

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Speaker 3: In other words, if you look at the amount of

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Speaker 3: money that they are making through their export earnings and

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Speaker 3: the amount of financial assets that they've accumulated and are accumulated,

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Speaker 3: it's huge. So one talks a lot about trade, but

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Speaker 3: you have to look about money and the quantity of

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Speaker 3: money and their earnings and their raising of living standards,

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Speaker 3: and how they're competing in various areas, certainly AI, but

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Speaker 3: robotics and a number of areas.

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Speaker 2: You would have to say that they are doing very well.

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Speaker 1: We say the post World War two order imposed LEGI

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Speaker 1: with US is breaking down. Would you say China has

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Speaker 1: a substantial say, if not dictating the next world order.

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Speaker 3: Yes, of course, but that doesn't mean I think you

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Speaker 3: said it well and not dictating. I think that there

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Speaker 3: will be an evolution, and I think that China's rise

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Speaker 3: in relative power that we're talking about is creating a

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Speaker 3: situation that they will create a tribute system type of system.

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Speaker 3: And what's important and actually practical about that is it

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Speaker 3: recognizes that there are differences in power. Okay, the system

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Speaker 3: that we win through a tiny country in the United

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Speaker 3: Nations could have the same boat as a huge country

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Speaker 3: and it wasn't the practical system. So I think you're

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Speaker 3: going to see it evolve in that region as being

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Speaker 3: a attribute system type of system. I think increasingly we're

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Speaker 3: going to see that in the world. I don't expect

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Speaker 3: China to be an aggressive military power.

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Speaker 2: I think that they.

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Speaker 3: You will see economically Chinese companies competing in the world.

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Speaker 3: You're going to see an acceleration of that the use

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Speaker 3: of the REMMB as a world currency, you're going to

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Speaker 3: see in an acceleration of that. It won't replace the

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Speaker 3: dollar quickly, but it's going to grow quickly for transactions.

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Speaker 3: So you're going to see that kind of operation. You're

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Speaker 3: going to see in negotiations. You're not going to see

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Speaker 3: that you will not be able to.

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Speaker 2: Push around China that there will it will be a force.

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Speaker 1: What does this mean for investors such as you? I mean,

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Speaker 1: investments are made against an order of some sort, there's

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Speaker 1: a predictability. You have contracts, you can enforce them if

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Speaker 1: in fact there's a breakdown in the world order. What

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Speaker 1: does that say to investors?

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Speaker 2: Think?

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Speaker 3: I think, first of all, when we think of investing,

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Speaker 3: we have to think of what is investing for and

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Speaker 3: it's our total life, not just making the most money.

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Speaker 3: So they have to think about diversification very well, right,

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Speaker 3: In other words, they have to think about we're now

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Speaker 3: in a turbulent time and that means, for example, the

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Speaker 3: value of money could be a risk. What currency is

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Speaker 3: it going to be in so, and how do you diversify.

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Speaker 3: So for example, now as we have AI have a

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Speaker 3: big effect. It's a fantastic technology that's like going to

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Speaker 3: have big revolutionary effects. If we look in history of

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Speaker 3: such cases, what we can see is then it also

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Speaker 3: can create bubbles. Also, liquidity is very valuable in a

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Speaker 3: very rapidly changing world because uncertainty is so great. Look

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Speaker 3: at the difference in stocks by way of example, right,

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Speaker 3: so who would guess? Who could know? And so liquidity

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Speaker 3: is very valuable. That's right. Diversification is very valuable. And

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Speaker 3: when I say diversification, I do include gold in that

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Speaker 3: in terms of money, because we do have a question

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Speaker 3: mark in terms of money, and this isn't These are

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Speaker 3: not tactical moves. In other words, I don't think that

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Speaker 3: the average man should be able should be moving in

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Speaker 3: an out based on what I say or what others say.

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Speaker 3: They should have a strategic gacid allocation next that they

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Speaker 3: buy and large stick to that has the best reward

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Speaker 3: to risk ratio.

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Speaker 1: Coming up, what happens when the world of scientific discovery

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Speaker 1: runs up against the need for hundreds of billions of dollars.

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Speaker 1: The story of demisisabus of deep mind. Next, this is

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Speaker 1: a story about passion and profits. The quest for scientific

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Speaker 1: discovery often begins with curiosity, but money and power can

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Speaker 1: follow closely behind. We saw it with the printing press,

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Speaker 1: the nuclear bomb, and now we're seeing it with artificial intelligence.

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Speaker 1: When a technology becomes powerful enough to change the course

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Speaker 1: of humanity, who should benefit most from it and who

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Speaker 1: has the power to control it?

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Speaker 4: Maybe Sa Sabis turns out to be the Robert Oppenheimer

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Speaker 4: of the twenty first century. Somebody who leads a project

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Speaker 4: like the Manhattan Project brings into the world an incredible technology.

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Speaker 4: It's a massive scientific achievement and is dangerous. And I

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Speaker 4: think the builders of the technology, including Demis as I

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Speaker 4: got to know him, had that same thought.

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Speaker 1: Sebastian Mallaby is a senior fellow at the Council on

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Speaker 1: Foreign Relations and the author, most recently, of The Infinity Machine.

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Speaker 1: His book chronicles the rise of artificial intelligence through the

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Speaker 1: lens of one of its key players, Demis Hassabas, a

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Speaker 1: Nobel laureate and the co founder of Google's AI lab

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Speaker 1: deep Mind.

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Speaker 4: Right from the start, they were thinking, you know, the

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Speaker 4: Manhattan Project was both good and bad, and probably going

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Speaker 4: to be the same with AI, and we have to

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Speaker 4: be careful and so Right at the beginning of DeepMind's story,

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Speaker 4: Demis Asabis meets his scientific co founder Shane Legg at

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Speaker 4: an AI safety lecture in London, and this is, you know,

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Speaker 4: seventeen years ago. You know again, the nuclear analogy is instructive.

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Speaker 4: We have a nuclear non proliferation treaty for nuclear weapons.

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Speaker 4: It's not completely air tight, but it's better than nothing.

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Speaker 4: And that's what we're going to need to have with

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Speaker 4: artificial intelligence.

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Speaker 1: To get there. Some believe that we might need a

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Speaker 1: wake up call. That's what Nobel Laureate Jeffrey Hinton told

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Speaker 1: us late last year here on Wall Street Week.

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Speaker 5: Some people say that our best hope is to have

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Speaker 5: AI try to take over and fail. We need something

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Speaker 5: to really scare the out of us, something like Chernobyl

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Speaker 5: for AI. I'm not sure I agree with that, but

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Speaker 5: that's certainly a possibility. We need something to make people

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Speaker 5: pay more attention, to put more resources. So at present,

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Speaker 5: the big companies aren't going to put like a third

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Speaker 5: of their resources into figuring out how to make it safe.

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Speaker 5: But if it tried to take over and only just failed,

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Speaker 5: maybe they would.

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Speaker 1: Even without an AI uprising. Malobi thinks policymakers have become

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Speaker 1: more aware of the technology's risks, especially in the wake

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Speaker 1: of anthropics.

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Speaker 4: Mythos rollout mythos is a dangerous point because already you know,

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Speaker 4: the US Treasury Secretary, the feedchamm and have told the

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Speaker 4: banks listen, your bank accounts are going to be emptied

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Speaker 4: if you don't protect yourself against these system So we've

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Speaker 4: had hints of Cuban missile crisis already. I would point

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Speaker 4: out to Jeff Hinton, who I like very much, that

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Speaker 4: you know, before the Nuclear and Non Proliferation Treaty in

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Speaker 4: the sixties, there was the nineteen fifties, and in the

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Speaker 4: nineteen fifties that's when the IAEA to track all the

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Speaker 4: nuclear material was created. In nineteen fifty six it was negotiated,

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Speaker 4: so you know that was actually ahead of the Cuban

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Speaker 4: missile crisis.

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Speaker 1: Whatever the outcome is for Ai Malobi thinks it will

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Speaker 1: be shaped by the people who create and control it

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Speaker 1: and their individual personalities and motivations.

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Speaker 4: And in Demesisabas's case, you know he's building something which

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Speaker 4: he himself says is dangerous, Right, why do you do that?

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Speaker 4: What makes you want to do it? And the answer

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Speaker 4: in his case is scientific curiosity. He is so burningly

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Speaker 4: determined to understand what he calls the fabric of reality

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Speaker 4: that he expresses that ambition and spiritual language that to

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Speaker 4: understand nature is to become closer to God.

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Speaker 1: For others, Meloby says, it's the ambition for money or power.

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Speaker 4: I think if you look at the other end of

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Speaker 4: the spectrum, you look at Mark Zackerberg. For him, it's

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Speaker 4: always been really commercial, right. He wants AI because it

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Speaker 4: will make Instagram and Facebook be more compelling, maybe more addictive.

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Speaker 4: That's what he's motivated by. I think Elil Mass just

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Speaker 4: wants to be the greatest industrialist of all time, so

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Speaker 4: he wants to do it for that reason. Sam Altmann

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Speaker 4: is kind of opportunistically riding again something will make him powerful.

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Speaker 4: This is a man who thought of running for governor

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Speaker 4: of California, is rumoured to have thought of a presidential run.

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Speaker 4: So he wants power.

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Speaker 1: But whether it's power or money or scientific achievement that

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Speaker 1: motivates the world's AI titans, they all have at least

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Speaker 1: one thing in common, the drive to be number one.

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Speaker 4: I remember going to see Demis right after the launch

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Speaker 4: of chat Ept at the end of twenty twenty two,

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Speaker 4: and of course this was the moment when deep Mind

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Speaker 4: and Demosis Services had been the leaders in global AI

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Speaker 4: without dispute for a decade, and all of a sudden,

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Speaker 4: this upstart in California. Simultman drops this model. It goes

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Speaker 4: viral and Demis is no longer the leader. So I

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Speaker 4: go see him and I say, well, how do you

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Speaker 4: feel about this? And he says, Sebastian, they've parked their

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Speaker 4: tanks on the lawn.

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Speaker 2: This is war.

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Speaker 4: You could see that competitive fury in his eyes. And yes,

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Speaker 4: I think most complicated human beings have more than one

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Speaker 4: personality inside them, And in Dems's case, there is the scientist.

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Speaker 4: There is also the furious competitor.

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Speaker 1: There's also the enormous need for money, for capital to

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Speaker 1: compete for compute, but also for the talent that comes

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Speaker 1: across in your book about how much it costs to

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Speaker 1: really get some of these scientists to come work with you.

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Speaker 1: Does that necessary sssarily take it out of the science

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Speaker 1: and make it fundamentally a commercial phenomena.

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Speaker 4: Well, it's definitely a commercial phenomenon. And we just saw

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Speaker 4: in the results this week from all the big tech

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Speaker 4: firms that they've expanded what they say they're going to

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Speaker 4: spend on the computing chips, the infrastructure that they need.

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Speaker 4: This is just going from extremely big to crazy big.

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Speaker 4: So you're totally right, it's commercial and we can't escape that,

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Speaker 4: but it could also be scientific, right that you could

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Speaker 4: have both at the same time and for what it's worth.

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Speaker 4: You know. Demis's view is that the future path to

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Speaker 4: you know, the kind of AI that can unlock all

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Speaker 4: of science is through these large language models. There's no

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Speaker 4: alternative path where you go in some totally parallel route.

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Speaker 4: So we're going to build these large language models. They're

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Speaker 4: going to get better and better. They're going to become

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Speaker 4: more agentic where they actually take actions. They're going to

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Speaker 4: understand the physical world that's spatial intelligence, and then from

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Speaker 4: there it will get into you know, the ultimate test,

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Speaker 4: which is supposing you trained an AI and you told

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Speaker 4: that everything that people knew in eleven, could it then

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Speaker 4: invent by itself general relativity.

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Speaker 1: The tension between the science and the business of AI

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Speaker 1: has come to a head in the ongoing trial between

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Speaker 1: Elon Musk and Open Ai. At the center of the

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Speaker 1: trial is a debate over who should control the chat

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Speaker 1: GPT creator, and the outcome could shake up the corporate

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Speaker 1: models that have underpinned the tech industry's explosive AI growth

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Speaker 1: as of right now as we speak, as over the

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Speaker 1: next seve hundred and twenty five billion dollars this year

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Speaker 1: from the big investors, how does that pencil out?

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Speaker 4: I mean, fundamentally, what we've got at the moment is

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Speaker 4: an A plus technology with a C minus business model.

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Speaker 4: And the purpose of capital markets is to bridge from

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Speaker 4: today when the technology is great but you're not making money,

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Speaker 4: to some beautiful future when finally you figure out the

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Speaker 4: business model and you do make money. But I think

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Speaker 4: we're running an experiment in the limits of that capital

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Speaker 4: market function because the capital markets are not infinitely deep.

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Speaker 4: So when you have open ai, which was spending money

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Speaker 4: like completely crazy and was not attached to one hyperscala

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Speaker 4: deep pocketed balance sheet that was extremely precarious, is extremely precarious.

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Speaker 4: I said three months ago that I thought there was

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Speaker 4: a fifty to fifty chance that open ai would go

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Speaker 4: bust basically, I mean it would be absorbed by another company.

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Speaker 4: And I still believe that that by the summer of

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Speaker 4: next year there's a half chance that it just runs

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Speaker 4: out of its ability to raise money, has to sell itself.

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Speaker 1: And that's where the hyperscalers are all created equal because

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Speaker 1: in a Google they can say we're making up more

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Speaker 1: money on search and maybe genius as well, we've got

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Speaker 1: some revenue coming in for this, and Amazon can say

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Speaker 1: we certainly have the cloud, the television a lot. Then

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Speaker 1: you get to a meta. It's not quite so clear

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Speaker 1: what they have to support this investment.

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Speaker 4: Right right, And they just seem to be quite clumsy

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Speaker 4: about translating all the money they spend on AI into

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Speaker 4: actual AI results. And we'll see how this plays out.

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Speaker 4: But there was this moment last year in twenty twenty

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Speaker 4: five when they were doing record expenditures on the signing

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Speaker 4: bonuses of AI scientists because basically they didn't have much

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Speaker 4: of a team and the only way they could get

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Speaker 4: a team coming from behind was to just ten x

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Speaker 4: people's salary, and so, you know, all the other labs

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Speaker 4: were going nuts. Actually witnessed the head of one of

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Speaker 4: the other companies, you know, pretty much yelling at the

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Speaker 4: metaperson saying, you know, you're draining all our talent. You

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Speaker 4: guys are you know, completely useless. You're never going to

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Speaker 4: build a system that's really powerful because you're hopeless. But

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Speaker 4: you're taking our good people away, and then the Chinese

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Speaker 4: will overtake us, and then they'll kill us. It's pretty extreme.

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Speaker 1: If throwing money at a problem is the clumsy solution

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Speaker 1: and often not the right one. What business model both

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Speaker 1: contains ambition and allows science to flourish. Malaby says some

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Speaker 1: of the big players have tried through their corporate structures,

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Speaker 1: though none has yet proven effective.

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Speaker 4: You know, all of the top three labs have experimented

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Speaker 4: with these governance ideas, and in fact, in my research

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Speaker 4: for this book, I found out about I think called

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Speaker 4: Project Mario, which was secret hitherto, but Project Marrier was

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Speaker 4: essentially Demesisabis saying, I need safety governance. I need a

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Speaker 4: kind of nonprofit board which will oversee the powerful AI

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Speaker 4: when I get it. And we can't just have the

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Speaker 4: corporate board of Google deciding how it gets ruled rolled out.

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Speaker 4: That's not democratically legitimate, that's not good for humanity. We

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Speaker 4: need that nonprofit structure to be grafted onto Google. So

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Speaker 4: he spent three years fighting about that. As we know

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Speaker 4: in open AI more in the public domain, they began

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Speaker 4: as a nonprofit and then they grafted on a for

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Speaker 4: profit later. Anthropic has its own version of this kind

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Speaker 4: of hybrid for profit nonprofit. But the harsh reality is,

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Speaker 4: as you said earlier, you know, this is an extremely

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Speaker 4: expensive technology to build, and so the for profit capital

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Speaker 4: raising kind of redd in tooth and claw capitalist thing

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Speaker 4: is going to dominate because you need money all the time.

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Speaker 1: Is there anything the government can and should be doing

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Speaker 1: now on the safety front.

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Speaker 4: So there are three things. The first thing is we

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Speaker 4: already have a national AI sort of security monitoring body,

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Speaker 4: but it doesn't have enough resources, it doesn't have the

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Speaker 4: power to veto a model before it's released. We should

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Speaker 4: have one which is like the Food and Drug Administration,

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Speaker 4: which is properly resourced. It has expert staff, and if

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Speaker 4: the drug is not safe or efficacious, you can ban

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Speaker 4: the release.

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Speaker 2: Right.

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Speaker 4: AI is just as dangerous as drugs, so we should

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Speaker 4: have an FDA for AI. Second thing we should do

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Speaker 4: is we should divert more money from just building the

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Speaker 4: model stronger to alignment research, where you align the model

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Speaker 4: with human priorities. That's a whole field of engineering. It's

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Speaker 4: getting some resources at the moment, but you know, obviously

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Speaker 4: it's not in the commercial interest of the companies to

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Speaker 4: invest too much in that so public policy needs to

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Speaker 4: support the public good of AI alignment. And the third

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Speaker 4: thing is on the international front, because like it or not,

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Speaker 4: the Chinese have very good AI models. So unless we

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Speaker 4: bind in China and other countries like France which has

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Speaker 4: the AI lab mistrial and other places, we need everybody

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Speaker 4: to acknowledge, just like we did in the nuclear age,

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Speaker 4: that this is dangerous if it proliferates into the hands

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Speaker 4: of terrorists and so forth, and so we should all

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Speaker 4: come together with agreed joint common safety standards. Otherwise, if

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Speaker 4: just one country is safe and the other ones aren't,

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Speaker 4: we haven't made humanity any safer.

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Speaker 1: The invention of the atomic bomb gave humanity a stark warning.

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Speaker 1: It's up to humans to safeguard against technology of immense

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Speaker 1: power endangering us all. And as the AI battle rages

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Speaker 1: all around us, maybe we can take some lessons from

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Speaker 1: that earlier arms race to limit the potential damage from

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Speaker 1: the next one up next, the US is in a

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Speaker 1: race with China to develop AI, but who wins may

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Speaker 1: depend less on the models and chips than it does

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Speaker 1: on how we go about finding the power for all

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Speaker 1: that AI needs. This is a story about taking your

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Speaker 1: eye off the ball. Since President Trump came to office,

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Speaker 1: the first time, he's been focused on the economic and

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Speaker 1: national security risks posed by one country. In particular, would you.

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Speaker 6: Say China, China?

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Speaker 7: China.

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Speaker 6: We were losing to China. We want to be China.

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Speaker 2: We're leading China.

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Speaker 1: In his second term, President Trump has focused on AI

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Speaker 1: as a key area of competition between the two countries,

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Speaker 1: and specifically the chips needed to drive all those large

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Speaker 1: language models.

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Speaker 6: China and other countries are racing to catch up to

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Speaker 6: America having to do with AI, and we're not going

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Speaker 6: to let him do it. We have the great chips,

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Speaker 6: we have the great everything, and we're going to be

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Speaker 6: fighting them in a very friendly fashion.

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Speaker 1: But while the US is doing what it can to

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Speaker 1: protect its lead in the computer race, there's another contest

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Speaker 1: that it may be losing the battle to make sure

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Speaker 1: we have the power we need to drive all that

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Speaker 1: AI we're developing.

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Speaker 7: It's fascinating because when you look at AI, there's a

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Speaker 7: huge energy need for the data centers.

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Speaker 1: We all know Hank Paulson from his time running Goldman

441
00:25:18,600 --> 00:25:21,880
Speaker 1: Sacks and then leading us through the Great Financial Crisis

442
00:25:21,920 --> 00:25:25,439
Speaker 1: as Treasury Secretary, but he's also devoted much of his

443
00:25:25,520 --> 00:25:29,280
Speaker 1: career to climate issues and helped lead Goldman Sachs to

444
00:25:29,400 --> 00:25:31,480
Speaker 1: China over thirty years ago.

445
00:25:31,760 --> 00:25:35,600
Speaker 7: We have one big advantage on China and that we

446
00:25:35,800 --> 00:25:40,880
Speaker 7: have were energy independent, right and they aren't. But we

447
00:25:40,960 --> 00:25:45,440
Speaker 7: have a shortage of electricity in this country. The demand

448
00:25:45,840 --> 00:25:50,200
Speaker 7: is much greater than the supply and it's growing, and

449
00:25:50,320 --> 00:25:55,359
Speaker 7: so we have a shortage of electricity to power data centers. China,

450
00:25:55,480 --> 00:25:59,359
Speaker 7: on the other hand, they're investing massively in coal and

451
00:25:59,400 --> 00:26:00,879
Speaker 7: a lot of things I wouldn't like them to be

452
00:26:00,920 --> 00:26:05,560
Speaker 7: investing in. But they are investing big time in renewables,

453
00:26:05,640 --> 00:26:10,720
Speaker 7: solar and wind. They have more renewables than Europe, the UK,

454
00:26:11,080 --> 00:26:13,879
Speaker 7: the US combined. They're going to have half their energy

455
00:26:13,880 --> 00:26:20,440
Speaker 7: from renewables. So they've got plenty of electricity. Meanwhile, in

456
00:26:20,480 --> 00:26:24,719
Speaker 7: our country, utilities can't meet the demand. Electricity prices are

457
00:26:24,760 --> 00:26:28,640
Speaker 7: spiking up, so right payers are putting up their hands

458
00:26:28,720 --> 00:26:31,479
Speaker 7: and say no more. At the same time, we need

459
00:26:31,760 --> 00:26:36,000
Speaker 7: the electricity. And so the interesting thing is if you

460
00:26:36,080 --> 00:26:39,440
Speaker 7: look at the US, all of our electricity, essentially new

461
00:26:39,480 --> 00:26:43,119
Speaker 7: electricity the last couple of years has come from solar

462
00:26:43,160 --> 00:26:47,400
Speaker 7: and wind. At the same time, the administration is frustrating it.

463
00:26:47,960 --> 00:26:52,280
Speaker 7: So again, I would say that we are ahead of

464
00:26:52,359 --> 00:26:57,000
Speaker 7: China when it comes to AI. They're investing massively. But

465
00:26:57,119 --> 00:27:00,399
Speaker 7: I got to tell you, the biggest potential drag we

466
00:27:00,520 --> 00:27:05,800
Speaker 7: have is not having enough electricity to power our our

467
00:27:05,880 --> 00:27:06,520
Speaker 7: data centers.

468
00:27:07,160 --> 00:27:08,920
Speaker 1: Are we disadvantaging ourselves?

469
00:27:09,000 --> 00:27:09,640
Speaker 8: I think we are.

470
00:27:10,800 --> 00:27:14,879
Speaker 1: Former US Ambassador to China, Nick Burns saw the unprecedented

471
00:27:14,920 --> 00:27:17,520
Speaker 1: scale of China's energy investment firsthand.

472
00:27:18,160 --> 00:27:20,159
Speaker 8: I used to travel a lot by train in China

473
00:27:20,520 --> 00:27:22,520
Speaker 8: because you can see a lot more of the country,

474
00:27:22,520 --> 00:27:24,880
Speaker 8: you can talk to people. The degree to which China

475
00:27:25,000 --> 00:27:28,000
Speaker 8: is building transmission lines all across the country, and I

476
00:27:28,080 --> 00:27:31,439
Speaker 8: visited twenty six of the provinces, even out to the west.

477
00:27:31,720 --> 00:27:35,359
Speaker 8: It's staggering. The degree to which they're now controlling the

478
00:27:35,400 --> 00:27:40,560
Speaker 8: global supply chain in electric vehicles, in lithium batteries, in

479
00:27:40,760 --> 00:27:44,560
Speaker 8: solar panels, and wind power. They are the world leaders

480
00:27:44,600 --> 00:27:46,480
Speaker 8: in this, and I think that the United States should

481
00:27:46,480 --> 00:27:48,679
Speaker 8: be making a similar effort. You know, maybe it's not

482
00:27:48,720 --> 00:27:51,399
Speaker 8: as cost effective now, but we have to think out

483
00:27:51,800 --> 00:27:54,280
Speaker 8: to the twenty thirties and twenty forties, and I do

484
00:27:54,359 --> 00:27:58,280
Speaker 8: think as we consider this big challenge of how do

485
00:27:58,320 --> 00:28:01,399
Speaker 8: we compete with China and yet not get into a

486
00:28:01,480 --> 00:28:04,680
Speaker 8: war with China. We have to start planning more long

487
00:28:04,800 --> 00:28:06,080
Speaker 8: term as they are doing.

488
00:28:07,400 --> 00:28:10,520
Speaker 1: The numbers bear out what Hank Paulson and Nick Burns

489
00:28:10,520 --> 00:28:14,160
Speaker 1: have seen on the ground in China since twenty twenty one,

490
00:28:14,560 --> 00:28:18,119
Speaker 1: In just five short years, it has added more power

491
00:28:18,160 --> 00:28:22,080
Speaker 1: capacity across all energy technologies than the United States has

492
00:28:22,119 --> 00:28:26,240
Speaker 1: built in its entire history, and that gap is only growing.

493
00:28:26,840 --> 00:28:29,440
Speaker 1: Over the next five years, China plans to add more

494
00:28:29,440 --> 00:28:33,720
Speaker 1: than three point four terawatts of energy generation capacity, nearly

495
00:28:33,840 --> 00:28:35,960
Speaker 1: six times as much as the US.

496
00:28:36,520 --> 00:28:39,400
Speaker 9: They've been developing their electric grid at a rate that

497
00:28:39,560 --> 00:28:40,880
Speaker 9: is extraordinary.

498
00:28:41,400 --> 00:28:45,080
Speaker 1: Elizabeth Economy, a China policy expert and senior fellow at

499
00:28:45,080 --> 00:28:48,040
Speaker 1: the Hoover Institution, says there will be a high cost

500
00:28:48,240 --> 00:28:49,600
Speaker 1: to falling farther behind.

501
00:28:50,880 --> 00:28:54,120
Speaker 9: China has made a big bet on renewables and clean

502
00:28:54,240 --> 00:28:57,840
Speaker 9: energy more broadly. This past year, for the very first time,

503
00:28:58,640 --> 00:29:02,520
Speaker 9: it has more power generation capacity in clean energy than

504
00:29:02,520 --> 00:29:04,760
Speaker 9: it does in fossil fuel energy. Now that they're not

505
00:29:04,800 --> 00:29:07,720
Speaker 9: the only ones. Europeans are following suit, but we clearly

506
00:29:07,720 --> 00:29:10,400
Speaker 9: are moving in the opposite direction, sort of all in

507
00:29:10,440 --> 00:29:13,400
Speaker 9: on fossil fuels. I think It's important to understand that

508
00:29:13,440 --> 00:29:16,120
Speaker 9: the bet from the Chinese side is not necessarily just

509
00:29:16,160 --> 00:29:19,360
Speaker 9: about the health of the Chinese people or the Chinese environment.

510
00:29:19,520 --> 00:29:22,239
Speaker 9: This is a real economic play for them. You know,

511
00:29:22,280 --> 00:29:25,360
Speaker 9: they are cognizant of the fact that by twenty thirty five,

512
00:29:25,720 --> 00:29:29,080
Speaker 9: the clean energy market is estimated to be globally as

513
00:29:29,160 --> 00:29:32,040
Speaker 9: big as seven trillion dollars, and they want to command

514
00:29:32,040 --> 00:29:34,800
Speaker 9: that market. So they have spent a lot of time

515
00:29:34,840 --> 00:29:38,440
Speaker 9: over the past several years investing very heavily in renewables.

516
00:29:38,520 --> 00:29:42,240
Speaker 9: You know, last year trillion dollars in renewable investments. And

517
00:29:42,280 --> 00:29:45,800
Speaker 9: as a result, they've seen their exports at evs skyrocket

518
00:29:45,840 --> 00:29:49,120
Speaker 9: eighty percent increase in twenty twenty five, forty percent for

519
00:29:49,200 --> 00:29:51,680
Speaker 9: battery exports, twenty percent for solar panels.

520
00:29:51,880 --> 00:29:53,040
Speaker 10: This is a real money maker.

521
00:29:53,600 --> 00:29:56,760
Speaker 9: So I think for the Chinese as they look out,

522
00:29:56,920 --> 00:29:59,719
Speaker 9: clean energy is green, right, It's green for the environment,

523
00:29:59,760 --> 00:30:02,200
Speaker 9: and you know, it's green for money.

524
00:30:02,360 --> 00:30:04,280
Speaker 1: You make a really interesting point that this has been

525
00:30:04,280 --> 00:30:07,120
Speaker 1: going on for several years. President She did not just

526
00:30:07,160 --> 00:30:08,680
Speaker 1: wake up yesterday and say let's have a lot of

527
00:30:08,720 --> 00:30:12,240
Speaker 1: renewables for AI. It started before really there was the

528
00:30:12,240 --> 00:30:14,520
Speaker 1: big push for AI. How much of this is pure

529
00:30:14,600 --> 00:30:17,560
Speaker 1: commerce rather than development of AI and competition and.

530
00:30:17,600 --> 00:30:20,240
Speaker 9: AI, I mean on the energy side of it. I

531
00:30:20,280 --> 00:30:22,280
Speaker 9: don't think that. I think the AI is very late

532
00:30:22,280 --> 00:30:25,240
Speaker 9: to the game. I mean the Chinese have been beginning

533
00:30:25,280 --> 00:30:28,000
Speaker 9: with renewables, and beginning of the late nineteen eighties early

534
00:30:28,080 --> 00:30:31,760
Speaker 9: nineteen nineties, they were already inviting Western firms in for

535
00:30:31,840 --> 00:30:35,000
Speaker 9: wind turbines and solar panels and saying, sure, we'll give

536
00:30:35,040 --> 00:30:37,200
Speaker 9: you access to the Chinese market. Now you just give

537
00:30:37,280 --> 00:30:39,560
Speaker 9: us some of your advanced technology or set up an

538
00:30:39,640 --> 00:30:42,440
Speaker 9: R and D center. Sometimes they might just illegally appropriate

539
00:30:42,440 --> 00:30:46,560
Speaker 9: the technology. But you know, one five year plan after another,

540
00:30:46,920 --> 00:30:50,480
Speaker 9: renewables have been part of the Chinese plan. And you're

541
00:30:50,560 --> 00:30:53,120
Speaker 9: right exactly. She Jinpin did not wake up, you know,

542
00:30:53,240 --> 00:30:55,200
Speaker 9: one day and say, oh, this really matters.

543
00:30:56,160 --> 00:30:59,440
Speaker 1: So China's push into renewables may not have been intended

544
00:30:59,440 --> 00:31:03,560
Speaker 1: for AI. That's where it could matter most. In the US,

545
00:31:03,600 --> 00:31:07,400
Speaker 1: power demand is exploding, with consumption from data centers alone

546
00:31:07,560 --> 00:31:11,200
Speaker 1: expected to triple by twenty thirty five, putting even more

547
00:31:11,240 --> 00:31:14,800
Speaker 1: pressure on a grid already under strain. But instead of

548
00:31:14,880 --> 00:31:18,440
Speaker 1: racing to close the gap with renewable alternatives, the US

549
00:31:18,520 --> 00:31:22,640
Speaker 1: is pulling back from a sector China increasingly dominates, accounting

550
00:31:22,680 --> 00:31:25,920
Speaker 1: for roughly eighty percent of global technology production in solar

551
00:31:25,960 --> 00:31:29,800
Speaker 1: and battery tech and more than seventy percent in wind.

552
00:31:30,080 --> 00:31:34,160
Speaker 1: This enormous development of renewables in China didn't come free.

553
00:31:34,640 --> 00:31:36,239
Speaker 1: They had to spend some money to do it. If

554
00:31:36,240 --> 00:31:38,400
Speaker 1: the United States wanted to get back in this game

555
00:31:38,440 --> 00:31:41,920
Speaker 1: and compete on the renewable part, does it have the capacity?

556
00:31:41,920 --> 00:31:44,040
Speaker 1: How much money is involved? How much money has the

557
00:31:44,080 --> 00:31:45,480
Speaker 1: Chinese government really put into this?

558
00:31:46,160 --> 00:31:49,160
Speaker 9: I mean, at this point, it's easily over a trillion dollars.

559
00:31:49,200 --> 00:31:52,080
Speaker 9: It's been billions of dollars every year, and as I mentioned,

560
00:31:52,120 --> 00:31:55,360
Speaker 9: a trillion dollars you know, just last year in clean

561
00:31:55,480 --> 00:31:58,600
Speaker 9: energy investments. So there's not a way that we're going

562
00:31:58,720 --> 00:32:03,200
Speaker 9: to compete across this spectrum of technologies, you know, sol

563
00:32:03,280 --> 00:32:06,560
Speaker 9: or wind, nuclear, We're just not going to be able

564
00:32:06,600 --> 00:32:08,920
Speaker 9: to do that at this point. Even in evse Right,

565
00:32:09,000 --> 00:32:13,280
Speaker 9: China's exports were worth about seventy six billion dollars last year.

566
00:32:13,400 --> 00:32:16,520
Speaker 9: Ours somewhere around three to four billion dollars. I mean,

567
00:32:16,720 --> 00:32:18,880
Speaker 9: don't forget they're also a country of one point four

568
00:32:19,040 --> 00:32:22,600
Speaker 9: billion people, so roughly three and a half four times

569
00:32:22,640 --> 00:32:25,240
Speaker 9: as large as we are, so that capacity is much

570
00:32:25,280 --> 00:32:28,200
Speaker 9: greater as well. But could we get back in the game.

571
00:32:28,280 --> 00:32:30,720
Speaker 9: I think that was the point of the Biden Administration's

572
00:32:30,720 --> 00:32:33,680
Speaker 9: Inflation Reduction Act, right, It was a mix of subsidies

573
00:32:33,720 --> 00:32:37,640
Speaker 9: and tax incentives. It attracted an enormous amount of foreign investment,

574
00:32:38,040 --> 00:32:40,240
Speaker 9: so it had I think a lot of potential to

575
00:32:40,680 --> 00:32:45,000
Speaker 9: reboot the clean energy sector in the United States. But

576
00:32:45,120 --> 00:32:48,600
Speaker 9: you know, the Trump administration is not that interested in

577
00:32:48,640 --> 00:32:51,760
Speaker 9: the clean energy in the renewable sector, and so you know,

578
00:32:51,800 --> 00:32:55,000
Speaker 9: we saw that they rolled back probably ninety five percent

579
00:32:55,400 --> 00:32:56,880
Speaker 9: of the Inflation Reduction Act.

580
00:32:57,880 --> 00:33:00,000
Speaker 1: Can the markets make up a good part of the difference?

581
00:33:00,200 --> 00:33:02,880
Speaker 1: By that, I mean this instead of the government giving

582
00:33:02,920 --> 00:33:07,080
Speaker 1: subsidies or tax breaks, incentives and renewables, is it possible

583
00:33:07,160 --> 00:33:09,040
Speaker 1: the market will take over and say it's just cheaper

584
00:33:09,400 --> 00:33:11,280
Speaker 1: to get energy from some of the renewables.

585
00:33:11,640 --> 00:33:14,240
Speaker 9: Well, I think there's always a hurdle, right when you're

586
00:33:14,280 --> 00:33:17,600
Speaker 9: introducing a new technology that you have to it has

587
00:33:17,640 --> 00:33:19,160
Speaker 9: to you have to get over and that is where

588
00:33:19,160 --> 00:33:21,920
Speaker 9: the government subsidies or incentives, you know, can play an

589
00:33:21,960 --> 00:33:24,320
Speaker 9: important role. I mean we see that now with rare earths,

590
00:33:24,520 --> 00:33:28,400
Speaker 9: and I think the Trump administration has come around to appreciate. Right, then,

591
00:33:28,440 --> 00:33:30,560
Speaker 9: if you're going to compete with China, you're going to

592
00:33:30,640 --> 00:33:33,080
Speaker 9: have to adopt some elements of their playbook.

593
00:33:33,360 --> 00:33:33,520
Speaker 7: Right.

594
00:33:33,520 --> 00:33:35,440
Speaker 9: You're going to have to invest, You're going to have

595
00:33:35,520 --> 00:33:38,800
Speaker 9: to have a secure market, you know, for the new

596
00:33:38,840 --> 00:33:42,640
Speaker 9: investment for the new technology that you're developing, right because

597
00:33:42,680 --> 00:33:44,240
Speaker 9: you have to get it over the hurdle from the

598
00:33:44,240 --> 00:33:48,480
Speaker 9: innovation to the manufacturing to the you know, deployment and export.

599
00:33:48,720 --> 00:33:51,400
Speaker 9: And I think that's the that's the full life cycle

600
00:33:51,480 --> 00:33:55,600
Speaker 9: of new technologies that China has created its playbook, and

601
00:33:55,640 --> 00:33:58,640
Speaker 9: we don't really have a playbook that can compete without

602
00:33:59,000 --> 00:34:01,640
Speaker 9: a little more government in prevention than we've typically been

603
00:34:01,640 --> 00:34:02,240
Speaker 9: comfortable with.

604
00:34:04,280 --> 00:34:07,080
Speaker 1: The US and China may be competing hard on AI,

605
00:34:07,440 --> 00:34:09,560
Speaker 1: and the US may have taken its eye off the

606
00:34:09,560 --> 00:34:13,040
Speaker 1: ball on energy that's critical in that competition, but there's

607
00:34:13,040 --> 00:34:16,120
Speaker 1: at least one area where they may find common ground,

608
00:34:16,840 --> 00:34:19,680
Speaker 1: agreeing on rules to make sure that all this AI

609
00:34:19,800 --> 00:34:24,440
Speaker 1: being built and powered is as safe as possible. Do

610
00:34:24,520 --> 00:34:27,880
Speaker 1: we need to work with China on safety for AI?

611
00:34:29,239 --> 00:34:34,919
Speaker 7: Yeah, obviously we do it at some time, but right

612
00:34:34,960 --> 00:34:40,360
Speaker 7: now they're an adversary when it comes to military and security.

613
00:34:41,040 --> 00:34:45,239
Speaker 7: So I think we're going to be forced to do

614
00:34:45,280 --> 00:34:47,960
Speaker 7: it when we start seeing accents and bad things happen.

615
00:34:48,480 --> 00:34:50,080
Speaker 7: And I just want to make sure we're in the

616
00:34:50,160 --> 00:34:53,960
Speaker 7: lead when we get to that point. I really do.

617
00:34:54,239 --> 00:34:57,320
Speaker 7: And I take a step further and say, when President

618
00:34:57,600 --> 00:35:00,360
Speaker 7: Trump and Shay meet, it's going to be the first

619
00:35:00,719 --> 00:35:05,520
Speaker 7: of I hope, you know, for summit meetings, and I'm

620
00:35:05,600 --> 00:35:08,920
Speaker 7: hoping right now there is. You know, we got a

621
00:35:08,960 --> 00:35:12,480
Speaker 7: trade deficit, but we've got a trust deficit big, and

622
00:35:12,560 --> 00:35:15,640
Speaker 7: I want to close that trust deficit because we need

623
00:35:15,680 --> 00:35:19,480
Speaker 7: to figure out how we can compete and work together

624
00:35:19,840 --> 00:35:22,399
Speaker 7: at the same time. And if we don't, the world

625
00:35:22,520 --> 00:35:24,439
Speaker 7: is going to be a much more dangerous and less

626
00:35:24,440 --> 00:35:29,279
Speaker 7: prosperous place. So again I view and I think a

627
00:35:29,360 --> 00:35:34,640
Speaker 7: positive is I really do believe President Trump wants to

628
00:35:34,640 --> 00:35:39,560
Speaker 7: find a way to work with China, and I hope

629
00:35:40,000 --> 00:35:42,719
Speaker 7: that the Chinese feel the same way.

630
00:35:45,000 --> 00:35:48,160
Speaker 1: Coming up, don't text you, don't text me, text that

631
00:35:48,280 --> 00:35:51,520
Speaker 1: guy behind the tree. But what if that guy is

632
00:35:51,640 --> 00:36:08,840
Speaker 1: Ken Griffin. This is a story about balancing the books,

633
00:36:09,280 --> 00:36:12,320
Speaker 1: faced with putting together his first budget. New York City's

634
00:36:12,320 --> 00:36:15,520
Speaker 1: mayor Mamdanie managed to pick a nasty and very public

635
00:36:15,560 --> 00:36:18,280
Speaker 1: fight with one of the biggest names on Wall Street,

636
00:36:18,760 --> 00:36:27,799
Speaker 1: Ken Griffin. New York City has long been known as

637
00:36:27,840 --> 00:36:30,840
Speaker 1: the city of Opportunity, home of the Statue of Liberty,

638
00:36:31,160 --> 00:36:36,720
Speaker 1: Broadway and Wall Street. It's also home to the highest

639
00:36:36,800 --> 00:36:40,120
Speaker 1: number of billionaires anywhere in the world. The city's new

640
00:36:40,120 --> 00:36:42,680
Speaker 1: mayor thinks they might be able to help him with

641
00:36:42,800 --> 00:36:43,920
Speaker 1: his budget problem.

642
00:36:44,400 --> 00:36:46,279
Speaker 6: When I ran for mayor, I said I was going

643
00:36:46,360 --> 00:36:47,000
Speaker 6: to tax the rich.

644
00:36:49,440 --> 00:36:50,920
Speaker 10: Well, today we're taxing.

645
00:36:51,719 --> 00:36:55,200
Speaker 1: In April, New York City Mayor Zoran Mamdani stood in

646
00:36:55,200 --> 00:36:58,480
Speaker 1: front of a penthouse on Billionaire's Row, a penthouse owned

647
00:36:58,480 --> 00:37:03,000
Speaker 1: by Citadel CEO Griffin, and made him the poster child

648
00:37:03,040 --> 00:37:06,320
Speaker 1: for a proposed so called peda tear tax on second

649
00:37:06,320 --> 00:37:08,959
Speaker 1: homes in the city with an assessed value of five

650
00:37:09,000 --> 00:37:10,040
Speaker 1: million dollars or more.

651
00:37:11,000 --> 00:37:13,720
Speaker 6: This tax will raise at least five hundred million dollars

652
00:37:13,800 --> 00:37:15,080
Speaker 6: directly for the city.

653
00:37:15,280 --> 00:37:17,800
Speaker 1: The move triggered some of the other Wall Street leaders

654
00:37:17,880 --> 00:37:19,200
Speaker 1: to come to Griffin's defense.

655
00:37:20,000 --> 00:37:23,399
Speaker 11: If your goal is to make New York City kind

656
00:37:23,440 --> 00:37:26,520
Speaker 11: of financially solvent, what you don't want to do is

657
00:37:26,600 --> 00:37:28,800
Speaker 11: drive out the Ken Griffins of the world. Wall Street

658
00:37:29,280 --> 00:37:32,080
Speaker 11: and the tax revenues from Wall Street are what enable

659
00:37:32,120 --> 00:37:34,120
Speaker 11: New York City, all the people in New York City

660
00:37:34,280 --> 00:37:35,280
Speaker 11: to have a better life.

661
00:37:35,880 --> 00:37:40,000
Speaker 1: Mam Donnie originally proposed increasing real estate taxes overall, but

662
00:37:40,040 --> 00:37:42,680
Speaker 1: thought better of the idea after Governor Hokel came up

663
00:37:42,680 --> 00:37:45,600
Speaker 1: with some help from the state budget. So far, however,

664
00:37:45,719 --> 00:37:48,760
Speaker 1: he's sticking with trying to tax the most valuable second

665
00:37:48,800 --> 00:37:49,760
Speaker 1: homes in the city.

666
00:37:50,040 --> 00:37:52,160
Speaker 12: I think Mam Donnie made a mistake, you know, going

667
00:37:52,200 --> 00:37:56,240
Speaker 12: after Ken Griffin by name, as he trumpeted his success

668
00:37:56,280 --> 00:37:59,080
Speaker 12: in raising taxes even though he only got a tiny morsel.

669
00:38:00,000 --> 00:38:02,600
Speaker 1: All Street veteran Whitney Tilson ran for mayor of New

670
00:38:02,680 --> 00:38:05,240
Speaker 1: York City against mister Memdanie last year.

671
00:38:05,840 --> 00:38:08,719
Speaker 12: What we're talking about is, you know those pencil towers

672
00:38:08,960 --> 00:38:12,600
Speaker 12: overlooking Central Park that are dark at night because nobody

673
00:38:12,600 --> 00:38:16,719
Speaker 12: actually lives there. I do think tone matters, and just

674
00:38:16,880 --> 00:38:22,680
Speaker 12: out there painting billionaires as evil is really dumb, given

675
00:38:22,760 --> 00:38:25,280
Speaker 12: the one percent of New York City tax payers account

676
00:38:25,360 --> 00:38:28,600
Speaker 12: for forty seven percent of the personal income tax paid

677
00:38:29,000 --> 00:38:33,000
Speaker 12: in New York City. A bunch of billionaires went down

678
00:38:33,000 --> 00:38:36,760
Speaker 12: to Florida during COVID, and that has real budgetary impacts

679
00:38:37,120 --> 00:38:40,600
Speaker 12: on New York. We should be rolling out a welcome

680
00:38:40,640 --> 00:38:44,080
Speaker 12: matt for every rich person who wants to live invest here.

681
00:38:44,239 --> 00:38:47,520
Speaker 12: And we're already a very high tax city, depending on

682
00:38:47,520 --> 00:38:49,759
Speaker 12: how you measure it, probably the highest tax burden of

683
00:38:49,760 --> 00:38:53,120
Speaker 12: any city in the country. But there's something unique about

684
00:38:53,200 --> 00:38:55,640
Speaker 12: New York. I tell my rich friends who are thinking

685
00:38:55,680 --> 00:38:57,560
Speaker 12: of moving, the whole point of being rich is you

686
00:38:57,560 --> 00:38:58,719
Speaker 12: can live where you want to live.

687
00:38:59,320 --> 00:39:02,080
Speaker 1: Imposing new taxes on their property may not be the

688
00:39:02,120 --> 00:39:05,400
Speaker 1: best way to attract wealthy residents. But Steve Pullip, the

689
00:39:05,440 --> 00:39:07,960
Speaker 1: head of Partnership for New York City and the former

690
00:39:08,000 --> 00:39:11,000
Speaker 1: mayor of Jersey City, has even deeper concerns.

691
00:39:11,520 --> 00:39:15,840
Speaker 13: I think that there is a bigger message with regards

692
00:39:15,880 --> 00:39:20,040
Speaker 13: to the Ken Griffin conversation. Okay, yeah, it's not great

693
00:39:20,120 --> 00:39:23,520
Speaker 13: that he was highlighted in that way, and in this

694
00:39:23,719 --> 00:39:27,880
Speaker 13: environment where you have people being the targets of political violence,

695
00:39:28,080 --> 00:39:33,160
Speaker 13: CEOs being assassinated, it's inappropriate and that's been covered fairly extensively.

696
00:39:33,880 --> 00:39:36,760
Speaker 1: Whether it was smart to target a specific Wall Street

697
00:39:36,760 --> 00:39:40,000
Speaker 1: CEO like Ken Griffin or not, the fact remains that

698
00:39:40,040 --> 00:39:43,440
Speaker 1: New York City has struggled with years of budget shortfalls.

699
00:39:43,800 --> 00:39:47,360
Speaker 1: Mam Donnie's new proposal promises to balance the city's budget

700
00:39:47,600 --> 00:39:50,880
Speaker 1: at least in the short term, despite inheriting a twelve

701
00:39:50,960 --> 00:39:55,960
Speaker 1: billion dollar deficit, but only with that peda tare tax included.

702
00:39:56,239 --> 00:39:58,399
Speaker 12: It's about the size of the budget New York if

703
00:39:58,400 --> 00:39:59,960
Speaker 12: it were a state, it would be the third ti

704
00:40:00,000 --> 00:40:02,960
Speaker 12: tenth largest state by population. It would be the third

705
00:40:03,040 --> 00:40:06,759
Speaker 12: largest state by budget. So he's looking at some real

706
00:40:06,800 --> 00:40:10,080
Speaker 12: budget cuts, and that of course affects the unions that

707
00:40:10,120 --> 00:40:12,440
Speaker 12: were among his biggest supporters. He wants to spend more

708
00:40:12,480 --> 00:40:14,799
Speaker 12: money as a democratic socialist, so he's sort of caught

709
00:40:14,840 --> 00:40:16,000
Speaker 12: between a rock and a hard place.

710
00:40:17,320 --> 00:40:20,440
Speaker 1: The challenge facing them Dani is made more complicated by

711
00:40:20,480 --> 00:40:24,040
Speaker 1: the structure of the tax system. Property taxes are the

712
00:40:24,080 --> 00:40:27,160
Speaker 1: single biggest source of revenue for New York City, accounting

713
00:40:27,160 --> 00:40:29,800
Speaker 1: for more than thirty percent of its budget, but those

714
00:40:29,840 --> 00:40:33,480
Speaker 1: taxes hit residents in very different ways. As an example,

715
00:40:33,760 --> 00:40:37,399
Speaker 1: even though single family homes have the highest nominal tax rate,

716
00:40:37,680 --> 00:40:40,799
Speaker 1: caps on assessment mean they pay the lowest effective rate,

717
00:40:41,080 --> 00:40:44,480
Speaker 1: putting most of the burden on apartment buildings, condos, and

718
00:40:44,520 --> 00:40:46,120
Speaker 1: commercial property owners.

719
00:40:46,560 --> 00:40:52,560
Speaker 12: They're weird anomalies in which someone who is grandfathered into

720
00:40:52,600 --> 00:40:56,760
Speaker 12: an older building but very expensive apartment on Park Avenue

721
00:40:57,160 --> 00:40:59,279
Speaker 12: is paying a much lower tax rate than a blue

722
00:40:59,280 --> 00:41:02,040
Speaker 12: collar person out in one of the outer boroughs.

723
00:41:02,120 --> 00:41:06,080
Speaker 10: Right, It's a very different burden on those owners, the

724
00:41:06,080 --> 00:41:09,600
Speaker 10: middle class family in Queens versus the billionaire on Central

725
00:41:09,640 --> 00:41:12,680
Speaker 10: Park South. So you have to come up with some

726
00:41:12,800 --> 00:41:16,760
Speaker 10: type of other structure. I think the Pieta Tere tax

727
00:41:16,840 --> 00:41:19,000
Speaker 10: is a fair idea at Ruth.

728
00:41:18,840 --> 00:41:21,959
Speaker 1: Culp Haaber is a partner at commercial real estate firm

729
00:41:22,160 --> 00:41:26,040
Speaker 1: Wharton Property Advisors. For her, the issue isn't so much

730
00:41:26,080 --> 00:41:28,839
Speaker 1: the idea of a new real estate tax. It's more

731
00:41:28,880 --> 00:41:32,279
Speaker 1: a matter of how mayor Mam Donnie is going about it.

732
00:41:32,320 --> 00:41:36,520
Speaker 10: To take for granted, an owner such as Ken Griffin,

733
00:41:37,760 --> 00:41:42,759
Speaker 10: who has contributed in the form of his company, it's

734
00:41:42,840 --> 00:41:46,040
Speaker 10: going to be twenty five thousand jobs before he's done,

735
00:41:46,120 --> 00:41:52,040
Speaker 10: and hundreds of millions to hospitals and museums. I mean,

736
00:41:52,120 --> 00:41:55,120
Speaker 10: this is a guy we want here, you know, and

737
00:41:55,160 --> 00:41:58,400
Speaker 10: we don't want to antagonize him in any way. Citadel

738
00:41:58,440 --> 00:42:03,480
Speaker 10: alone has paid tens of millions in taxis. Yes, their

739
00:42:03,480 --> 00:42:06,320
Speaker 10: employees make a lot of money, and I can understand

740
00:42:06,360 --> 00:42:08,480
Speaker 10: how some people have a problem with that.

741
00:42:09,680 --> 00:42:13,000
Speaker 1: Citadel has about thirteen hundred employees in the city, and

742
00:42:13,040 --> 00:42:15,200
Speaker 1: Griffin is now saying he'll move at least some of

743
00:42:15,239 --> 00:42:18,160
Speaker 1: them to Miami and take another look at a huge

744
00:42:18,200 --> 00:42:20,240
Speaker 1: new office tower on Park Avenue.

745
00:42:20,719 --> 00:42:24,480
Speaker 10: Not only has he committed to a sixty percent ownership

746
00:42:24,560 --> 00:42:27,760
Speaker 10: of this development, but he's committed to being the anchor tenant,

747
00:42:27,960 --> 00:42:30,239
Speaker 10: meaning he's going to take like half the space in

748
00:42:30,280 --> 00:42:34,400
Speaker 10: the building. This is a major commitment. If he pulls

749
00:42:34,440 --> 00:42:37,239
Speaker 10: out from that, the message that is going to go

750
00:42:37,400 --> 00:42:41,840
Speaker 10: out literally to the world is New York is not

751
00:42:41,920 --> 00:42:45,520
Speaker 10: a good place to do business. It would be a disaster.

752
00:42:46,200 --> 00:42:48,480
Speaker 1: This wouldn't be the first time Griffin made good on

753
00:42:48,520 --> 00:42:51,440
Speaker 1: a promise like that. Citadel once employed more than one

754
00:42:51,480 --> 00:42:54,600
Speaker 1: thousand employees in its fifty thousand square foot office building

755
00:42:54,680 --> 00:42:55,360
Speaker 1: in Chicago.

756
00:42:55,760 --> 00:42:58,480
Speaker 10: We need to look to history and what happened in

757
00:42:58,520 --> 00:43:02,520
Speaker 10: twenty twenty two with Ken Griffin in Chicago with Governor

758
00:43:02,600 --> 00:43:06,840
Speaker 10: Pritzker and Ken Griffin was building his business in Chicago.

759
00:43:07,680 --> 00:43:12,920
Speaker 10: There was politics, goun involved. Ken Griffin wasn't happy about

760
00:43:13,000 --> 00:43:17,360
Speaker 10: the crime situation in Chicago and he left.

761
00:43:17,960 --> 00:43:20,520
Speaker 1: Thus far, most of what we've heard about to address

762
00:43:20,560 --> 00:43:23,560
Speaker 1: the budget gap has been about raising more revenue. But

763
00:43:23,680 --> 00:43:26,799
Speaker 1: Fullip thinks it's not fundamentally a question of how much

764
00:43:26,920 --> 00:43:28,160
Speaker 1: the city is taking in.

765
00:43:28,840 --> 00:43:31,640
Speaker 13: I think at the core of the problem is that

766
00:43:32,239 --> 00:43:35,360
Speaker 13: you have a spending problem and less of a revenue problem.

767
00:43:35,360 --> 00:43:37,759
Speaker 13: And that's what we try to kind of hammer home repeatedly.

768
00:43:38,040 --> 00:43:40,840
Speaker 1: Where did New York City go in the wrong direction

769
00:43:40,920 --> 00:43:42,520
Speaker 1: of their budget? There was a time not too long

770
00:43:42,560 --> 00:43:45,800
Speaker 1: ago that they had balanced budgets. They were doing okay.

771
00:43:46,120 --> 00:43:48,560
Speaker 1: Is it because the spending just grew too much or

772
00:43:48,719 --> 00:43:51,759
Speaker 1: the growth of the overall economy slowed down?

773
00:43:52,400 --> 00:43:55,560
Speaker 13: I mean, look, it's complicated because you have a lot

774
00:43:55,560 --> 00:44:00,640
Speaker 13: of things simultaneously happening. So you had costs COVID go

775
00:44:00,719 --> 00:44:04,520
Speaker 13: through the roof, you have tariffs, you have wages and

776
00:44:04,640 --> 00:44:08,839
Speaker 13: union contracts that have increased fairly significantly. You've had very

777
00:44:08,880 --> 00:44:11,960
Speaker 13: progressive mayors that have layered on additional social service. So

778
00:44:11,960 --> 00:44:13,960
Speaker 13: all those things kind of come together. But a pragmatic

779
00:44:13,960 --> 00:44:16,800
Speaker 13: person would look at it and say, the city budget

780
00:44:16,800 --> 00:44:20,000
Speaker 13: has grown significantly faster than the rate of inflation, and

781
00:44:20,000 --> 00:44:22,600
Speaker 13: that is a question mark on why. But putting that

782
00:44:22,680 --> 00:44:25,560
Speaker 13: aside for a second, what We've tried to say, is

783
00:44:25,960 --> 00:44:29,640
Speaker 13: we should be thoughtful about the program overall and whether

784
00:44:29,840 --> 00:44:32,120
Speaker 13: it achieves the outcome that you want to achieve.

785
00:44:32,320 --> 00:44:35,319
Speaker 1: If the PEDA tair tax goes forward, and if it's

786
00:44:35,360 --> 00:44:38,640
Speaker 1: five hundred million dollars, that's the way short of where

787
00:44:38,640 --> 00:44:40,759
Speaker 1: we need to be. I mean, the eskmens are over

788
00:44:40,840 --> 00:44:44,000
Speaker 1: five billion dollars. So if you'd won, if you've got

789
00:44:44,000 --> 00:44:46,080
Speaker 1: to be mayor, where would you look for the other

790
00:44:46,120 --> 00:44:47,880
Speaker 1: four and a half plus billion dollars.

791
00:44:48,239 --> 00:44:52,240
Speaker 12: I found it very difficult, and I tried to really

792
00:44:52,760 --> 00:44:54,880
Speaker 12: get down into the weeds. I mean, you can see

793
00:44:54,960 --> 00:44:57,400
Speaker 12: five million dollars to build a public restroom in a

794
00:44:57,440 --> 00:45:01,160
Speaker 12: park is ten times too much. Pay six times as

795
00:45:01,239 --> 00:45:03,640
Speaker 12: much as any city in the world to construct one

796
00:45:03,719 --> 00:45:07,799
Speaker 12: mile of subway. So you can see those examples. Just

797
00:45:07,840 --> 00:45:10,080
Speaker 12: the school budgets thirty seven percent of our hundred and

798
00:45:10,080 --> 00:45:13,200
Speaker 12: eighteen billion dollar budget. I have been very involved in

799
00:45:13,280 --> 00:45:15,960
Speaker 12: charter schools and educational form over the years, and I

800
00:45:16,000 --> 00:45:17,640
Speaker 12: know there's a lot of fat in there, you know,

801
00:45:17,719 --> 00:45:19,640
Speaker 12: dead people on the payroll and that kind of thing.

802
00:45:20,160 --> 00:45:22,120
Speaker 12: So I think I might start with just sort of

803
00:45:22,120 --> 00:45:25,600
Speaker 12: a one or two percent across the board cut and

804
00:45:25,640 --> 00:45:27,680
Speaker 12: then that sort of gets you in one hundred and

805
00:45:27,680 --> 00:45:29,840
Speaker 12: eighteen billion dollar budget. That gets you a bunch of

806
00:45:29,880 --> 00:45:32,919
Speaker 12: the way there, and then negotiate from there.

807
00:45:33,920 --> 00:45:36,239
Speaker 1: Balancing the books on a New York City budget is

808
00:45:36,440 --> 00:45:39,720
Speaker 1: never easy, and it's not surprising that there's a range

809
00:45:39,719 --> 00:45:41,640
Speaker 1: of ideas about how to come up with a few

810
00:45:41,719 --> 00:45:45,200
Speaker 1: billion dollars to make it work with or without calling

811
00:45:45,239 --> 00:45:50,200
Speaker 1: out specific CEOs and their penthouse apartments. But the one

812
00:45:50,239 --> 00:45:53,040
Speaker 1: thing most everyone agrees on is that we need to

813
00:45:53,080 --> 00:45:56,440
Speaker 1: get the balance right to ensure that New York City

814
00:45:56,560 --> 00:46:00,400
Speaker 1: remains a magnet for talented young workers and the companies

815
00:46:00,520 --> 00:46:01,359
Speaker 1: that employ them.

816
00:46:01,840 --> 00:46:04,960
Speaker 13: The best asset here, which is very hard to replicate

817
00:46:05,480 --> 00:46:08,959
Speaker 13: in New York City, brand is very very special, and two,

818
00:46:09,440 --> 00:46:12,000
Speaker 13: it is the most desirable place for young people.

819
00:46:11,800 --> 00:46:12,560
Speaker 9: To want to be.

820
00:46:13,040 --> 00:46:15,840
Speaker 13: That is a very very special thing. Now you have

821
00:46:16,280 --> 00:46:19,800
Speaker 13: ai that uncertainty around jobs and the affordability on housing,

822
00:46:19,840 --> 00:46:22,120
Speaker 13: so those are two things that go directly at that

823
00:46:22,239 --> 00:46:24,120
Speaker 13: young person who wants to live here, so that is

824
00:46:24,160 --> 00:46:26,600
Speaker 13: a challenge. And then you also have places like use

825
00:46:26,680 --> 00:46:31,319
Speaker 13: Texas as an example, so JP Morgan today has more

826
00:46:31,480 --> 00:46:34,040
Speaker 13: jobs in Texas than they do in New York. It's

827
00:46:34,080 --> 00:46:35,799
Speaker 13: a crazy thing to think about. Ten years ago that

828
00:46:35,840 --> 00:46:38,080
Speaker 13: wasn't the case. So the trend is moving in a

829
00:46:38,120 --> 00:46:41,840
Speaker 13: bad direction. Goldman Sachs trend in the bad direction. Why

830
00:46:42,440 --> 00:46:46,400
Speaker 13: it's bigger than taxes, it's Texas has been very deliberate

831
00:46:46,440 --> 00:46:48,399
Speaker 13: with their strategy on how they're going to attract jobs.

832
00:46:48,440 --> 00:46:52,160
Speaker 13: So they change their court systems entirely to replicate Delaware,

833
00:46:52,200 --> 00:46:55,560
Speaker 13: to make it more corporate friendly. They're starting as stock

834
00:46:55,719 --> 00:46:59,960
Speaker 13: Texas Stock Exchange to have better access to the capital markets.

835
00:47:00,280 --> 00:47:03,520
Speaker 13: Then they have incentives and they have leadership that talks

836
00:47:03,560 --> 00:47:07,040
Speaker 13: about embracing their big corporate communities.

837
00:47:07,239 --> 00:47:09,279
Speaker 12: You need to build a lot more housing, not just

838
00:47:09,400 --> 00:47:13,439
Speaker 12: low income or affordable housing, but it all trickles through.

839
00:47:13,640 --> 00:47:16,319
Speaker 12: We need to build more housing for you know, young

840
00:47:16,360 --> 00:47:19,080
Speaker 12: professionals who can afford to pay more. You know, look

841
00:47:19,120 --> 00:47:21,439
Speaker 12: when Amazon came and wanted to put their headquarters here,

842
00:47:21,719 --> 00:47:24,600
Speaker 12: you know, you want a mayor who invites Jeff Bezos

843
00:47:24,600 --> 00:47:28,359
Speaker 12: and the Amazon executives to Gracie Mansions, sits down with

844
00:47:28,400 --> 00:47:32,000
Speaker 12: all the key people from the city, and you know,

845
00:47:32,120 --> 00:47:34,000
Speaker 12: rolls out to welcome Matt. So some of it's just

846
00:47:34,040 --> 00:47:36,680
Speaker 12: sort of messaging and signaling and being a champion for

847
00:47:36,719 --> 00:47:37,840
Speaker 12: business in the city.

848
00:47:39,560 --> 00:47:41,279
Speaker 1: That does it for us. Here at Wall Street Week,

849
00:47:41,440 --> 00:47:44,320
Speaker 1: I'm David Weston. See you next week for more stories

850
00:47:44,520 --> 00:47:59,640
Speaker 1: of capitalism.