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Speaker 1: Bloomberg Audio Studios, podcasts, radio news.

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Speaker 2: This is Wall Street Week. I'm David Weston bringing you

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Speaker 2: stories of capitalism. The race to an AI future takes

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Speaker 2: us through the obscure land of open source code, and

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Speaker 2: one of those leading the charge, Lisa Sue of AMD,

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Speaker 2: explains what is at stake plus, however we get there,

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Speaker 2: that AI future will require a whole lot more electricity,

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Speaker 2: which we'll have to include a whole lot more nuclear

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Speaker 2: power than we have ever seen before. And as the

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Speaker 2: holiday season approaches, we take you on a trip down

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Speaker 2: memory lane to the department stores of yesterday and the

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Speaker 2: efforts of one of the remaining icons, Macy's, to transform

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Speaker 2: itself for the future. But we start with the FED

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Speaker 2: decision this week. What we learned about where the FED

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Speaker 2: is going if it knows with Glenn Hubbard of the

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Speaker 2: Columbia Business School, who headed the Council of Economic Advisors

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Speaker 2: under President George W.

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Speaker 3: Bush Well, the decision itself isn't a surprise. David, Why though,

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Speaker 3: is a good question. I don't see really an argument

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Speaker 3: for cutting the fund's rate, particularly given the Fed's own

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Speaker 3: macroeconomic forecasts that would have real GDP growth now higher.

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Speaker 3: Next year, not lower. There are reasonable minds on both

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Speaker 3: sides who are debating the employment tradeoff and the inflation

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Speaker 3: tradeoff were interestingly going forward, what could the Fed do?

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Speaker 3: I don't see rate cuts. If you look at the

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Speaker 3: FED funds rate now, it's roughly in the range of

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Speaker 3: where it should be given views about what the real

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Speaker 3: Federal funds rate is and the inflation forecast the Fed

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Speaker 3: itself has put out. So I don't see much more

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Speaker 3: room to cut.

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Speaker 2: If you believe the Fed's projections next year. In twenty

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Speaker 2: twenty six, they took up the GDP growth by half

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Speaker 2: a percent.

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Speaker 4: That's big.

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Speaker 2: How do you cut rates into a growing economy?

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Speaker 3: Well, I think they would have to argue that it's

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Speaker 3: about employment, not just output, but that seems very tortured

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Speaker 3: as an argument. They still have time to react to

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Speaker 3: labor pressures should they worsen. Remember, the Fed also lowered

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Speaker 3: the unemployment rate for next year as well. That doesn't

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Speaker 3: look like an economy heading toward recession. I'm not saying

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Speaker 3: that will come to pass, but that is the Fed's view.

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Speaker 2: Artificial intelligence is all the talk of the town, including

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Speaker 2: with the chair Pale in his decision this week. How

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Speaker 2: can the FED understand AI well enough to know what

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Speaker 2: that will do, for example, productivity, which the chair talked about.

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Speaker 3: Well, I don't think any of us, if we're honest, No,

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Speaker 3: and I talk to business people in California. They're extremely optimistic.

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Speaker 3: Every CEO is optimistic. Some others are more dour among economists, honestly,

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Speaker 3: I think there's every reason to believe generative AI could

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Speaker 3: be a big productivity boom. But there lies the rub

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Speaker 3: for the FED. If you think AI is the future

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Speaker 3: of productivity, that's a story for higher, not lower interest rates.

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Speaker 3: The real interest rate will go up and inflation is

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Speaker 3: still stuck at a higher level. If we're wrong about AI,

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Speaker 3: then we've got many things to worry about because we

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Speaker 3: have a lot of cap X going into AI data

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Speaker 3: centers and things like that. But I don't think the

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Speaker 3: AI productivity story gets the FED to low rates. This

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Speaker 3: is not a replay of green Span in the nineteen nineties.

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Speaker 2: What sorts of pressures could AI in success with increased

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Speaker 2: productivity increase investment, as you say, put on the dual mandate,

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Speaker 2: because you could have on the one said growth economic

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Speaker 2: growth increased productivity radically with lower employment, so you could

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Speaker 2: be on both sides of that mandate.

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Speaker 5: You well could.

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Speaker 3: At the moment, I'm not so sure. So we have

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Speaker 3: seen obviously a weakening labor market, but I'm not sure

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Speaker 3: AI is associated with it. When you look at all

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Speaker 3: of the sectors that are weakening, to me, it looks

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Speaker 3: more like an unwind of excess hiring during COVID. So

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Speaker 3: we don't yet know, and we don't know going forward.

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Speaker 3: Is AI going to be more of a compliment to you,

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Speaker 3: me and everybody else in terms of the skills we

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Speaker 3: have or a substitute. But if it were the case

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Speaker 3: that AI displaced a lot of jobs, to me, that's

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Speaker 3: less of a federal reserve challenge and more of a

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Speaker 3: government challenge that the government needs to do something, have

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Speaker 3: a policy to prepare people better than we did in

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Speaker 3: previous waves of technological change.

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Speaker 2: One of the things that Cherpeal addressed was tariff's When

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Speaker 2: he was asked about the elevated well above the two

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Speaker 2: percent number and inflation, he said, well, that's really a

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Speaker 2: tariff thing, and we think that will dissipate. Is he

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Speaker 2: right about that?

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Speaker 3: In principle, yes, a tariff is if you had a

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Speaker 3: once in four all tariff that should raise prices, not inflation.

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Speaker 3: It only raises inflation for a period of time. The

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Speaker 3: problem is we've seen tariffs come, tariffs go, rates go up,

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Speaker 3: rates go down, so it becomes a little harder. My

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Speaker 3: worry about the tariffs is less about inflation somewhat for

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Speaker 3: the reasons Chair Powell has suggested, but more for their

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Speaker 3: long run corrosive effect on the economy in productivity, in

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Speaker 3: supply chains. You know again, America's imports are more than

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Speaker 3: half of them, or intermediate goods. We're shooting ourselves in

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Speaker 3: the foot whenever we do large across the board tariffs.

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Speaker 2: What do you make of the fact we're now up

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Speaker 2: to three descents, two going one way, one going the

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Speaker 2: other way. We went for a long time actually with

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Speaker 2: essentially no dessence in the FED. Is this a good thing,

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Speaker 2: a bad thing, or something in between?

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Speaker 3: I think it's It could be any of you bobs.

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Speaker 3: So it's a good thing in the sense that in

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Speaker 3: a healthy organization, if you and I don't have the

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Speaker 3: same view, we should speak it. If we're not going

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Speaker 3: to be reconciled. That said, you've got to ultimately govern

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Speaker 3: the FED. We're about to have a new FED chair.

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Speaker 3: The President will tell us who it is sometime in

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Speaker 3: the near future, and that gentleman or lady is going

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Speaker 3: to have to bring together a group of people with

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Speaker 3: disparate opinions. That's where the challenge seems to hold. Your

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Speaker 3: Powell has done a very good job, I think, in

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Speaker 3: managing through a situation where people could reasonably hold different

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Speaker 3: views about the economy and obvious political cross currents. He's

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Speaker 3: been able to get through that. The new FED chair,

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Speaker 3: whoever it is, will face that challenge.

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Speaker 2: It's one thing to have disagreements over policy, over theory,

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Speaker 2: even over what the data are telling. You don't think

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Speaker 2: they have political disagreements. We tend to think that the

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Speaker 2: FED should stay away from political disagreements and disagree over

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Speaker 2: the merits.

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Speaker 3: As it Well, that's absolutely right. You can make a

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Speaker 3: case right now in the economy for different points of

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Speaker 3: view about the path of interest rates. The fact that

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Speaker 3: I have one point of view does not mean, for example,

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Speaker 3: that Governor Waller's wrong because he is a different point

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Speaker 3: of view. This is a different way of looking at

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Speaker 3: the world. I respect that if your argument is based

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Speaker 3: on politics, then that's not a technocratic argument for the FED.

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Speaker 3: Political arguments are fine when you're talking about fiscal policy

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Speaker 3: or things that the Congress does. But the FED was

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Speaker 3: set up to provide independent judgment about monetary policy, and

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Speaker 3: that's what it should do.

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Speaker 2: To provide independent judgments and to be perceived as providing

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Speaker 2: independent judgments.

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Speaker 3: It's critical, David, because if people don't believe that you're independent,

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Speaker 3: even if you yourself think you are, that doesn't work,

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Speaker 3: and you have to ask yourself why does it not work.

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Speaker 3: The bond market and capital markets depend on the perception

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Speaker 3: that the FED is an independent agency.

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Speaker 2: One of the things that came up more than once

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Speaker 2: in the news conference, although Cherpal really refused to address it,

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Speaker 2: is the question in Governor Cook's case depending before the

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Speaker 2: Supreme Court, if you had to choose which is more

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Speaker 2: important who the FED chair is or how the Supreme

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Speaker 2: Court rules.

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Speaker 3: Well, I'm going to give you a non lawyer's answer

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Speaker 3: because I honestly I don't know. But to me, the

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Speaker 3: Cook case is very important, and not just because it's

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Speaker 3: about Governor Cook. Per sees call it about X. Whoever

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Speaker 3: X is if the President can fire a member of

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Speaker 3: the Federal Reserve Board for what doesn't appear to be caused,

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Speaker 3: at least as an outsider. Then that speaks volumes about

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Speaker 3: the Fed's independent So I think that case is one

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Speaker 3: to watch. You know, I'm not a lawyer. I don't

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Speaker 3: know what the outcome will be, but I wish the

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Speaker 3: Supreme more well in deciding.

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Speaker 2: It looking forward into twenty twenty six, which is very,

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Speaker 2: very difficult obviously. Do you think there's more risks to

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Speaker 2: the upside or the downside in the economy?

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Speaker 3: You know, I see risks in both directions. The AI

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Speaker 3: boom that we spoke about is clearly an upside risk

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Speaker 3: to me. The resilience of the economy is also an

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Speaker 3: upside risk. If we were having this conversation a year

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Speaker 3: ago and you had told me about Liberation Day, I

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Speaker 3: alone got to know that. I would have then thought

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Speaker 3: the macroeconomy would do worse than it did. I would

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Speaker 3: have predicted market effects, which did happen, but not the

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Speaker 3: mac for economic effects. And I think part of that

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Speaker 3: is the overwhelming resilience of the American economy combined with

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Speaker 3: the productivity book. I think those are real upsides. The

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Speaker 3: downsides I would worry about is that the labor market

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Speaker 3: could weaken gradually and suddenly, and we already have a

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Speaker 3: credit cycle that looks relatively mature to me, and so

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Speaker 3: I would start to worry about credit accidents which could

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Speaker 3: affect the bod market, So that would worry me as

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Speaker 3: a downside. And then of course there are always geopolitical

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Speaker 3: risks that I'm certainly not an expert in and are

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Speaker 3: hard to predict. So I think there are risks on

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Speaker 3: both sides. It's going to be a very interesting year

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Speaker 3: for the Fed for fiscal policy, and obviously because it's

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Speaker 3: an election year, a highly charged.

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Speaker 4: Year coming up.

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Speaker 2: Getting to an AI future, it's not just a matter

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Speaker 2: of how much money is spent, it's also what the

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Speaker 2: basic structure of the system looks like. AMD Lisa Sue

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Speaker 2: on the critical bets being made on open source versus

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Speaker 2: proprietary code. This is a story about frontemies, when to

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Speaker 2: try and beat your competition, and when to share with

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Speaker 2: those competitors to build a bigger overall business and compete

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Speaker 2: in other ways. The competition to develop AI models could

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Speaker 2: not be more fierce, with big tech companies investing record

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Speaker 2: amounts of money on chips and data centers.

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Speaker 6: These companies investing trillions of dollars in CAPEX.

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Speaker 7: Trillions of dollars in the raise to build artificial intelligence

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Speaker 7: support systems.

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Speaker 3: Trillions of dollars of our tech companies investing in building

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Speaker 3: data centers in America.

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Speaker 2: How far AI will take us and how fast may

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Speaker 2: depend in part on a basic choice about the overall

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Speaker 2: approach to sharing for withholding information, a choice often mentioned

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Speaker 2: in passing, but one that investors may not have identified

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Speaker 2: as key.

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Speaker 7: I want to see AI everywhere. You know we were

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Speaker 7: such so early in the real usage of the technology.

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Speaker 2: Lisa Sue is chair and CEO of a m D,

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Speaker 2: the chip maker with hundreds of billions of dollars at

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Speaker 2: stake in the development of AI. When it comes to

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Speaker 2: the software that runs on their products, she and her

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Speaker 2: company have made their choice in favor of open source

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Speaker 2: technology sharing where they can.

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Speaker 7: The difference with an open source or open standards is

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Speaker 7: the idea that you set out a set of standards

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Speaker 7: that people can follow, and then different companies can choose

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Speaker 7: to implement in a different way. And you know, the

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Speaker 7: whole idea is to provide platforms that the entire ecosystem,

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Speaker 7: lots and lots of developers can develop, and that that

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Speaker 7: you can be able to interchange sort of the best

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Speaker 7: of breed from different sources.

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Speaker 2: Why is there so much passion around open I mean,

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Speaker 2: is it a matter of business or is there a

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Speaker 2: matter of philosophy?

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Speaker 7: The philosophy is, you know, do you believe that there's

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Speaker 7: any one company or any one group that will have

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Speaker 7: all of the best ideas in the world, or do

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Speaker 7: you believe that if you have an open ecosystem where

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Speaker 7: different researchers and different groups can contribute, that you will

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Speaker 7: end up with a better product overall? And philosophically, I think,

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Speaker 7: you know, from an am D standpoint. You know, actually,

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Speaker 7: if I think about throughout my career, I look at,

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Speaker 7: you know, sort of the different inflection points on technology.

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Speaker 7: Things often start new ideas often start in a closed environment.

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Speaker 7: But when you actually think about when they get big

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Speaker 7: and when you know a lot of people adopt, you

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Speaker 7: like to be an open environment. And you know that's philosophically. Now,

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Speaker 7: let's talk about the business aspects of it. You know,

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Speaker 7: the business aspects of it are you know, we all

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Speaker 7: have to make choices of where we invest and do

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Speaker 7: you want to trust you know, all of your crown

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Speaker 7: jewels and all of your data in a closed ecosystem

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Speaker 7: that you know, may or may not be the most

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Speaker 7: competitive at any given time, or you know, may have

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Speaker 7: you know, a flaw or any of those things. Whereas

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Speaker 7: you know, in an open ecosystem, you have choices. You

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Speaker 7: can decide who is the best at any given time.

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Speaker 7: You can decide if I have my data in a

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Speaker 7: cloud environment, I can easily move it to another environment.

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Speaker 7: If I have my applications that are built on one chip,

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Speaker 7: if there's a better chip, you know, a few years later,

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Speaker 7: you can move you know, quickly. That's that's kind of

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Speaker 7: the idea of both.

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Speaker 2: What broadly speaking of the advantages of open and let

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Speaker 2: me throw all out For example, in a new technology,

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Speaker 2: is it more likely, all of the things being equal,

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Speaker 2: that the technology will develop more quickly if it's open.

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Speaker 7: I would say that the main advantage of an open

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Speaker 7: ecosystem is that you can get many, many more developers

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Speaker 7: on that ecosystem, and they will contribute, you know, sort

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Speaker 7: of in their you know, special way. So you know,

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Speaker 7: an example I can give you is, you know, when

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Speaker 7: we think about supercomputing, like the largest supercomputers in the world,

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Speaker 7: we usually like to develop them on open software stacks,

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Speaker 7: so that researchers from all different labs can actually contribute

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Speaker 7: to those applications and those learnings. We see that a

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Speaker 7: lot in open ecosystems, which is the notion that we

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Speaker 7: want more developers. Like Linux is a great example, right.

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Speaker 7: Linux is one of the examples where with an open

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Speaker 7: operating system, you can see that it's now really become

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Speaker 7: the standard for a lot of computing going forward.

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Speaker 2: For all the advantages of the open source approach to AI,

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Speaker 2: many of the most important players, including most recently Meta

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Speaker 2: with a new model expected to debut next year, have

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Speaker 2: gone the other way, keeping much of their generative AI

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Speaker 2: tech proprietary. And there are some advantages to that approach,

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Speaker 2: including preventing bad actors from having access to source code

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Speaker 2: that they can manipulate. That's something Sue believes can be

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Speaker 2: remedied by community.

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Speaker 7: I think there is a definite view that there's a

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Speaker 7: place for open and then there's a place for proprietary.

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Speaker 7: And when I say that, I mean, look, there are

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Speaker 7: amazing groups of researchers that are working on the largest

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Speaker 7: foundational models. When you think about you know, what's happening

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Speaker 7: at open AI and what's happening at Google and what's

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Speaker 7: happening at Anthropic, what's happening at Meta. These are phenomenal

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Speaker 7: labs that are doing a tremendous research in AI. There

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Speaker 7: are also a number of open models. You know open

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Speaker 7: Ai has an open model, you know Meta, their Lama

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Speaker 7: series as have had open models. And what you find

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Speaker 7: when those models are open is there are more researchers

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Speaker 7: that are able to build on top of that, and

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Speaker 7: I think there's significant advantages there. So you know, our

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Speaker 7: thought process in how this evolves over time is you're

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Speaker 7: going to have both in the ecosystem And just like

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Speaker 7: my very early example of sort of the Apple iOS

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Speaker 7: ecosystem and the Google Android ecosystem, it's not like you're

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Speaker 7: going to have all of one takeover all of the

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Speaker 7: other takeover. But what you do see is there's value

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Speaker 7: in richness in having let's call it a little bit

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Speaker 7: of competition between the ecosystems. And most importantly, what we

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Speaker 7: want is what's best for the consumer is to get

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Speaker 7: the best overall product experience and the best overall capabilities.

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Speaker 8: And you do that when you.

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Speaker 7: Allow a playing field that allows good competition across the board.

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Speaker 2: The debate between open source and proprietary is not a

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Speaker 2: new one. This IBM seven oh five. The computer industry

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Speaker 2: had to confront a similar choice long before the current

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Speaker 2: rush to artificial intelligence models. Sam Palmasana was the CEO

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Speaker 2: of IBM from two thousand and three through twenty eleven.

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Speaker 9: How this whole thing began was basically in the late

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Speaker 9: nineties and there were two different model There were proprietary

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Speaker 9: models that exist at IVM and the main framed Microsoft

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Speaker 9: Client Server, et cetera. They're all proprietary, and we believed

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Speaker 9: that IBM that a better model was one that would

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Speaker 9: drive more innovation work growth if it was open source

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Speaker 9: so everybody could participate. So that led to this Linux Initiative,

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Speaker 9: which was the open source in this institute that was

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Speaker 9: created by the industry, which we were part of. And

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Speaker 9: obviously what happened over time.

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Speaker 4: Now we put a lot behind it.

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Speaker 9: We made a billion dollar bet that Linux would become

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Speaker 9: commercial and that in the future Linux in the patche

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Speaker 9: would be kind of the operating the.

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Speaker 4: Environment of the Internet.

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Speaker 9: It worked out, but it could have been a mistake,

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Speaker 9: but it worked out, so that gave it a lot

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Speaker 9: of momentum. But the whole point was open innovation is

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Speaker 9: going to win over single company proprietary approaches because they

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Speaker 9: have a limited amount of resource and unlimited market. Even

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Speaker 9: if they have a large share position, it's still a

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Speaker 9: smaller market than the entire industry.

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Speaker 2: When you made the decision to go open source with Linux,

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Speaker 2: was there controversy about it? The pluses and the minuses

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Speaker 2: of that decision.

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Speaker 9: Huge internal debate. Think about this stuff, IBM inventative. With

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Speaker 9: the history of the industry, it was all proprietary, whether

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Speaker 9: that was not just in mainframe or storage and database

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Speaker 9: and all those things were all invented by IBM. So

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Speaker 9: there's the camp that said, hey, you guys, this is crazy.

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Speaker 9: We have this proprietary model. It's very profitable. Slower growth,

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Speaker 9: but it's very profitable, and it's from a business perspective.

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Speaker 9: The alternative was that, no, if we can open up

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Speaker 9: the opportunity and then participate in a bigger opportunity than

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Speaker 9: the one we're participated in, IBM will be better off

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Speaker 9: long term, and that was the decision.

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Speaker 2: The IBM moved to open source for operating systems twenty

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Speaker 2: five years ago helped spur what became a software revolution

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Speaker 2: as firms adopted the system and built their own proprietary

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Speaker 2: applications on top of it. Looking back on it now,

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Speaker 2: it's hard not to conclude that it was good for

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Speaker 2: the business overall and ultimately good for companies like IBM.

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Speaker 2: But is history likely to repeat itself this time as

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Speaker 2: the world experien ements with various generative AI approaches said, the.

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Speaker 7: Chip is actually quite small. What you really we want

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Speaker 7: to present a framework where we're going to get the

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Speaker 7: best ideas coming out of this, and from an AMD standpoint,

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Speaker 7: we'd love you to run on our chips, but more importantly,

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Speaker 7: we want you to run on an open ecosystem so

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Speaker 7: you can decide, you know, two years from now or

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Speaker 7: four years from now, if you made a choice of AMD,

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Speaker 7: that doesn't mean you're locked into our chips for the

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Speaker 7: next five years. It means that you have an open

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Speaker 7: ecosystem where you can benefit from all of the competitive

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Speaker 7: capabilities that come on board over the next five to ten.

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Speaker 2: Years, which sounds like it should be good for the

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Speaker 2: business long term overall the business. Is it also good

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Speaker 2: for AMD in the sense that in that world where

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Speaker 2: you can switch and you don't have to be committed,

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Speaker 2: you'll sell more chips over the long term.

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Speaker 7: I believe we will because we are giving people the

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Speaker 7: opportunity to choose, and look, we always have to be

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Speaker 7: best in class, right, there's no question that it's there's

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Speaker 7: so many innovations to come on board. But the idea

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Speaker 7: that if you develop on AMD, you have choice and

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Speaker 7: you also have the ability to work closely with us

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Speaker 7: in terms of, you know, how we develop this ecosystem together,

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Speaker 7: that this is a case where one plus one is

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Speaker 7: going to be greater than three because you know, we're

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Speaker 7: getting the smartest people from all of the ecosystem versus

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Speaker 7: just you know, we're going to figure out everything on

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Speaker 7: our own.

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Speaker 2: And it's not just the big US tech companies making

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Speaker 2: their bets on open versus a proprietary. China is casting

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Speaker 2: its vote as well and perhaps ironically siding with the

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Speaker 2: open approach.

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Speaker 9: Where we started, it was mostly proprietary, and the winners

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Speaker 9: at that point in time were Meta, Google, Open Ai, Microsoft,

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Speaker 9: you know, et cetera.

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Speaker 4: They were the winners.

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Speaker 9: And we're growing like crazy with these large language models.

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Speaker 9: Then all of a sudden, this thing happens in China.

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Speaker 9: And there's two things that happen in China that are

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Speaker 9: open sourced and they're based on this view that innovation

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Speaker 9: will scale faster if we have an open source approach.

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Speaker 9: Deep Seek it's got a lot of press, a lot

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Speaker 9: of coverage. The other one's called huggy Face, which you

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Speaker 9: hardly hear about. But if you look at the numbers

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Speaker 9: compared to the growth before twenty twenty four, it was

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Speaker 9: heavily dominated by the three companies, the hyperscalers I talked about,

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Speaker 9: and then since then it's been these other companies and

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Speaker 9: the China approach. So since twenty twenty four, China actually

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Speaker 9: is out growing the proprietary models, but it's the open

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Speaker 9: source innovation and they've gone from nothing to millions of

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Speaker 9: people now using these capabilities.

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Speaker 10: To your point, Sam, there's this chart that we were

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Speaker 10: provided actually by you're folks out out at Stanford, which

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Speaker 10: actually illustrates the competitive nature of the large amount languge

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Speaker 10: models in China for the United States over time.

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Speaker 9: Correct you look at at the point I was making

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Speaker 9: up until twenty twenty four, it was clearly a blue

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Speaker 9: curve led by the United States, the companies, but led

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Speaker 9: by the United States. It flipped in twenty twenty four.

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Speaker 9: I went vertical, and it's almost caught up to the

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Speaker 9: United states now this thing is rocketing.

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Speaker 2: As happens so often, it ultimately comes down to business,

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Speaker 2: albeit business with profound ramifications well beyond the specific companies involved.

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Speaker 2: Amd Su has little doubt that what works best for

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Speaker 2: AI development overall will also be the best way forward

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Speaker 2: for her company.

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Speaker 7: The ability to collaborate actually helps us go faster because

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Speaker 7: you only have to differentiate on the things that are

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Speaker 7: let's call it the most secret sauce. And if we

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Speaker 7: can come up with standards so that we're not doing

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Speaker 7: the same work multiple times at different companies, you know,

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Speaker 7: that's actually a good thing.

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Speaker 2: And the secret sauce for you is in the chip.

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Speaker 7: Yes, the secret sauce is in the chip. It's in

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Speaker 7: how we marry the chip to what will eventually be

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Speaker 7: the application. And in our world, David, what I find

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Speaker 7: the most interesting is the idea that every application that

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Speaker 7: we see going forward, every device that you see, is

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Speaker 7: going to have AI as part of its essential element,

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Speaker 7: and we want to be as much as we can

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Speaker 7: the provider of that essential AI capability. From the hardware side,

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Speaker 7: we've seen, you know, sort of the advent of chat

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Speaker 7: GPT now turn into you know, is there a AI

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Speaker 7: bubble and I say that we're just starting to see

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Speaker 7: the real utility of AI. Yes, the investments are high,

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Speaker 7: but why are we all so so confident that there's

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Speaker 7: a payoff at the end. The way AI has been

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Speaker 7: improving over the last you know, let's call it a

441
00:23:34,000 --> 00:23:37,800
Speaker 7: couple of years, has been faster than any other technology

442
00:23:37,920 --> 00:23:40,199
Speaker 7: that I've seen. The adoption rates have been faster than

443
00:23:40,200 --> 00:23:44,800
Speaker 7: any other technology. The potential is faster than any other technology.

444
00:23:45,160 --> 00:23:47,200
Speaker 7: But what I'm here to tell you is that it's

445
00:23:47,240 --> 00:23:51,080
Speaker 7: nowhere near its peak capability.

446
00:23:53,240 --> 00:23:57,280
Speaker 2: Up next going nuclear. However, we build the AI systems,

447
00:23:57,320 --> 00:24:01,120
Speaker 2: can we run them without nuclear power? Nuclear power than

448
00:24:01,160 --> 00:24:13,840
Speaker 2: we have ever seen before. This is a story about

449
00:24:13,960 --> 00:24:16,639
Speaker 2: betting on the come when we have a lot on

450
00:24:16,680 --> 00:24:19,159
Speaker 2: the line and really need it to work, But the

451
00:24:19,200 --> 00:24:22,720
Speaker 2: outcome is far from certain. The United States and the

452
00:24:22,760 --> 00:24:26,199
Speaker 2: world are facing an impending power shortage.

453
00:24:27,240 --> 00:24:30,560
Speaker 11: What we know now is that the nation, the country

454
00:24:30,880 --> 00:24:33,840
Speaker 11: is short of electrons and we need to build more generation.

455
00:24:34,080 --> 00:24:37,280
Speaker 7: We do have an incredible demand increasing demand for energy.

456
00:24:37,400 --> 00:24:41,920
Speaker 2: We are seeing fundamental growth in the demand for electricity.

457
00:24:42,720 --> 00:24:46,480
Speaker 2: Why do we suddenly need so much more electricity? Well,

458
00:24:46,520 --> 00:24:49,639
Speaker 2: we've all heard about AI data centers, hungry for energy

459
00:24:49,680 --> 00:24:52,920
Speaker 2: that would satisfy medium sized cities. But it turns out

460
00:24:53,040 --> 00:24:54,720
Speaker 2: that's only part of the story.

461
00:24:55,640 --> 00:24:58,480
Speaker 5: AI data centers appear to be the sort of fastest

462
00:24:58,480 --> 00:25:01,359
Speaker 5: coming and largest new source. Over the long term, reshoring

463
00:25:01,480 --> 00:25:04,920
Speaker 5: of manufacturing will be incredibly important as well.

464
00:25:05,119 --> 00:25:08,240
Speaker 2: Joseph Mikett is director of the Energy Security and Climate

465
00:25:08,359 --> 00:25:12,359
Speaker 2: Change Program at CSIS and author of paper on Energy

466
00:25:12,359 --> 00:25:15,040
Speaker 2: strategy for the Aspen Economic Strategy Group.

467
00:25:15,800 --> 00:25:18,639
Speaker 5: When we look at the onshuring of manufacturing, there's a

468
00:25:18,640 --> 00:25:23,280
Speaker 5: couple different sources of new demand that are going to

469
00:25:23,720 --> 00:25:26,440
Speaker 5: really come to bear in the next few years. One

470
00:25:26,560 --> 00:25:29,919
Speaker 5: is semiconductor manufacturing. As the US has tried to secure

471
00:25:29,960 --> 00:25:34,040
Speaker 5: that supply chain. The government is making investments in public

472
00:25:34,080 --> 00:25:38,240
Speaker 5: private partnerships in building leading fabrication facilities here in the US.

473
00:25:38,880 --> 00:25:41,520
Speaker 5: The US for the previous decades had had very little

474
00:25:41,560 --> 00:25:45,240
Speaker 5: growth in its use of electricity. We now foresee growth

475
00:25:45,440 --> 00:25:49,320
Speaker 5: between twenty and one hundred percent over the next fifteen years.

476
00:25:50,520 --> 00:25:53,520
Speaker 2: So where are all these electrons going to come from?

477
00:25:53,960 --> 00:25:56,680
Speaker 2: If we're going to double our energy supply we're even

478
00:25:56,720 --> 00:25:59,480
Speaker 2: just lifted by twenty percent over the next fifteen years.

479
00:26:00,000 --> 00:26:02,240
Speaker 2: One of the sources will have to be nuclear.

480
00:26:03,400 --> 00:26:05,800
Speaker 12: Nuclear is going to be a contributing factor for sure.

481
00:26:05,960 --> 00:26:09,600
Speaker 12: I think we need to continually apply the right technologies

482
00:26:09,760 --> 00:26:11,480
Speaker 12: where the right resources exist.

483
00:26:12,040 --> 00:26:16,240
Speaker 2: Scott Strazik is president and CEO of ge Vernova, whose

484
00:26:16,320 --> 00:26:20,880
Speaker 2: business includes power solutions from nuclear, natural gas, and wind.

485
00:26:21,480 --> 00:26:23,239
Speaker 12: In the US, as an example, we do have very

486
00:26:23,240 --> 00:26:26,560
Speaker 12: inexpensive gas. Because of that, we do want to leverage

487
00:26:26,600 --> 00:26:29,240
Speaker 12: that resource. At the same time, we have a lot

488
00:26:29,280 --> 00:26:32,800
Speaker 12: of good land that has good fuel in the form

489
00:26:32,840 --> 00:26:36,399
Speaker 12: of wind and solar. Where those resources exist, we should

490
00:26:36,480 --> 00:26:39,600
Speaker 12: use them. Where nuclear plays a really important role is

491
00:26:39,640 --> 00:26:44,480
Speaker 12: where those natural resources aren't readily available, and it's especially

492
00:26:44,520 --> 00:26:47,200
Speaker 12: important in places where we need what we call power

493
00:26:47,359 --> 00:26:50,520
Speaker 12: dense solutions. And what I mean by that is places

494
00:26:50,560 --> 00:26:53,000
Speaker 12: that need electrons that don't have a lot of space,

495
00:26:53,560 --> 00:26:56,600
Speaker 12: because we can build nuclear in a fairly small amount

496
00:26:56,640 --> 00:26:59,560
Speaker 12: of space, yet it creates a lot of electrons.

497
00:27:00,840 --> 00:27:03,199
Speaker 2: If nuclear is going to be an important part of

498
00:27:03,240 --> 00:27:06,360
Speaker 2: meeting our energy demands, it has a long way to go.

499
00:27:06,600 --> 00:27:09,679
Speaker 2: The US has had commercial nuclear power plants since the

500
00:27:09,760 --> 00:27:13,159
Speaker 2: late nineteen fifties, but only two have come online in

501
00:27:13,200 --> 00:27:16,879
Speaker 2: the last thirty years. Today, only about twenty percent of

502
00:27:16,880 --> 00:27:21,120
Speaker 2: electricity comes from nuclear generation, a number that hasn't increased for.

503
00:27:21,160 --> 00:27:26,080
Speaker 12: Decades historically when we've been building nuclear plants, because they

504
00:27:26,119 --> 00:27:28,919
Speaker 12: require a lot of infrastructure, they require a lot of

505
00:27:28,960 --> 00:27:33,080
Speaker 12: security apparatus. We would build one plant that would be

506
00:27:33,359 --> 00:27:36,400
Speaker 12: directionally a gigawot in size, and that's a lot, that's

507
00:27:36,480 --> 00:27:40,840
Speaker 12: a million homes that it's powering directionally. Today, what we're

508
00:27:40,840 --> 00:27:43,359
Speaker 12: working on is a small modular reactor, which is a

509
00:27:43,400 --> 00:27:45,119
Speaker 12: three hundred megawa application.

510
00:27:46,080 --> 00:27:49,639
Speaker 5: Historically, the US has built very large light water nuclear reactors,

511
00:27:49,880 --> 00:27:53,440
Speaker 5: and while that supply chain has atrophied, we have partners

512
00:27:53,440 --> 00:27:57,159
Speaker 5: who can supply that technology. It is licensed and ready

513
00:27:57,160 --> 00:27:59,680
Speaker 5: to be built when it can achieve financing. Those are

514
00:27:59,760 --> 00:28:03,639
Speaker 5: law large grid scale reactors. Reactors of another size of

515
00:28:03,720 --> 00:28:06,920
Speaker 5: other designs still have to make it through the regulatory process,

516
00:28:06,920 --> 00:28:10,240
Speaker 5: but they hold great promise both as grid serving entities,

517
00:28:10,400 --> 00:28:14,760
Speaker 5: maybe running smaller microgrids, working for industrial facilities. I don't

518
00:28:14,800 --> 00:28:17,680
Speaker 5: think the right question is to say which of these

519
00:28:17,760 --> 00:28:20,000
Speaker 5: is going to win, but rather how do we build

520
00:28:20,040 --> 00:28:23,560
Speaker 5: an ecosystem that can support both, because both will provide

521
00:28:23,840 --> 00:28:27,800
Speaker 5: solid services to US consumers as well as export opportunities

522
00:28:27,840 --> 00:28:28,719
Speaker 5: for the United States.

523
00:28:29,160 --> 00:28:31,800
Speaker 12: One of the challenges in the nuclear industry is when

524
00:28:31,840 --> 00:28:34,440
Speaker 12: we were building them at a gigwat size, each one

525
00:28:34,480 --> 00:28:36,800
Speaker 12: was a little different, and with each one being a

526
00:28:36,800 --> 00:28:40,440
Speaker 12: little bit bespoke and unique, the cost was always higher

527
00:28:40,480 --> 00:28:45,360
Speaker 12: than desirable. By scaling to a smaller product that we

528
00:28:45,440 --> 00:28:48,320
Speaker 12: can fit into many more applications, we have a much

529
00:28:48,400 --> 00:28:50,520
Speaker 12: higher degree confidence that we can come down the cost

530
00:28:50,560 --> 00:28:55,200
Speaker 12: curve because ultimately affordability matters, and nuclear is very attractive

531
00:28:55,240 --> 00:28:59,680
Speaker 12: because it's a zero carbon electron, but early it's going

532
00:28:59,720 --> 00:29:01,680
Speaker 12: to be more expensive, and we need to give the

533
00:29:01,760 --> 00:29:04,680
Speaker 12: industry and our end customers confidence that we can come

534
00:29:04,720 --> 00:29:08,200
Speaker 12: down the cost curve as we gain more volume, which

535
00:29:08,240 --> 00:29:09,520
Speaker 12: I'm highly confident we can do.

536
00:29:09,640 --> 00:29:12,520
Speaker 2: What about the fuel source? Is the fuel the same

537
00:29:12,600 --> 00:29:14,560
Speaker 2: for the big gigawatt as it is for the three

538
00:29:14,640 --> 00:29:15,720
Speaker 2: hundred megaway.

539
00:29:15,440 --> 00:29:18,360
Speaker 12: It is, and we'll create the fuel in the same location,

540
00:29:18,480 --> 00:29:21,000
Speaker 12: and we'll meet to North Carolina for our small modular

541
00:29:21,000 --> 00:29:25,520
Speaker 12: reactors that continues to feed the sixty gigawatts of existing

542
00:29:25,600 --> 00:29:27,200
Speaker 12: install base we have in the country.

543
00:29:27,640 --> 00:29:30,920
Speaker 2: Is fuel supply a potential limiting factor as we build

544
00:29:30,960 --> 00:29:31,520
Speaker 2: out nuclear?

545
00:29:31,840 --> 00:29:34,920
Speaker 12: As nuclear grows, for sure, we're going to need more

546
00:29:35,200 --> 00:29:38,440
Speaker 12: uranium supply. I think this is an area for growth

547
00:29:38,480 --> 00:29:41,520
Speaker 12: in the US. We certainly are dependent on other countries

548
00:29:41,560 --> 00:29:44,440
Speaker 12: today for more of our uranium than we are as

549
00:29:44,440 --> 00:29:47,640
Speaker 12: an example with things like gas, where we can extract

550
00:29:47,680 --> 00:29:49,800
Speaker 12: all of it out of the ground ourselves here. So

551
00:29:50,280 --> 00:29:52,160
Speaker 12: that is going to be priority, and I think that's

552
00:29:52,160 --> 00:29:54,640
Speaker 12: something that you're seeing a lot of companies lean into today.

553
00:29:55,720 --> 00:29:59,120
Speaker 2: As promising as small modular reactors may be, the need

554
00:29:59,160 --> 00:30:02,880
Speaker 2: for energy won't peak. US power demand is expected to

555
00:30:02,920 --> 00:30:06,320
Speaker 2: outstrip peak supply by twenty twenty eight, and the fact

556
00:30:06,400 --> 00:30:10,040
Speaker 2: remains that as of today, there are no small modular

557
00:30:10,080 --> 00:30:13,360
Speaker 2: reactors actually up and working in the United States or

558
00:30:13,400 --> 00:30:17,560
Speaker 2: anywhere outside of China and Russia, though ge Vernova hopes

559
00:30:17,600 --> 00:30:20,760
Speaker 2: to change that by twenty thirty. Nicole Holmes is the

560
00:30:20,800 --> 00:30:24,040
Speaker 2: company's chief commercial officer and the nuclear engineer.

561
00:30:24,680 --> 00:30:25,760
Speaker 12: This is very important.

562
00:30:26,000 --> 00:30:28,240
Speaker 13: If you don't remember anything else, it's that this is

563
00:30:28,320 --> 00:30:31,479
Speaker 13: real and it's happening right now. A lot of people

564
00:30:31,560 --> 00:30:34,440
Speaker 13: ask me when will nuclear happen? When will there be

565
00:30:34,560 --> 00:30:37,560
Speaker 13: new nuclear And the answer is going on today in

566
00:30:37,600 --> 00:30:40,880
Speaker 13: the Ontario province in Canada, we are building the BWX

567
00:30:40,920 --> 00:30:44,440
Speaker 13: three hundred and with our partner OPG, the small modular

568
00:30:44,480 --> 00:30:46,840
Speaker 13: reactor will be online by the end of this decade.

569
00:30:47,120 --> 00:30:50,560
Speaker 13: So if you start today in the US, for example,

570
00:30:50,600 --> 00:30:53,440
Speaker 13: we have a construction permit application with our partner, the

571
00:30:53,480 --> 00:30:56,320
Speaker 13: Tennessee Valley Authority, the utility that would own and operate

572
00:30:56,360 --> 00:30:59,720
Speaker 13: that reactor, in front of the Nuclear Regulatory Commission, with

573
00:31:00,120 --> 00:31:03,080
Speaker 13: the timeline to get that construction permit at the end

574
00:31:03,120 --> 00:31:06,760
Speaker 13: of twenty twenty six and potentially began construction as early

575
00:31:06,800 --> 00:31:10,040
Speaker 13: as twenty twenty seven. In this kind of timeframe, we

576
00:31:10,080 --> 00:31:13,320
Speaker 13: could have small modular reactors operating in the early twenty

577
00:31:13,360 --> 00:31:14,719
Speaker 13: thirties in the United States.

578
00:31:15,800 --> 00:31:19,160
Speaker 12: The time is now. The reality is after Fukushima in

579
00:31:19,240 --> 00:31:22,440
Speaker 12: most of the western world, there has not been new

580
00:31:22,480 --> 00:31:25,040
Speaker 12: build now. We also were living during a period of

581
00:31:25,040 --> 00:31:28,960
Speaker 12: time in which electric demand growth was reasonably flat.

582
00:31:29,800 --> 00:31:30,520
Speaker 14: We're past that.

583
00:31:30,600 --> 00:31:33,360
Speaker 12: We're at an inflection point where we need a lot

584
00:31:33,440 --> 00:31:37,960
Speaker 12: more incremental electrons for national security, for economic growth, to

585
00:31:38,120 --> 00:31:41,200
Speaker 12: frankly keep the lights on, as many parts of many

586
00:31:41,280 --> 00:31:46,560
Speaker 12: industries are electrifying, so when you don't have an ultimate demand,

587
00:31:46,760 --> 00:31:49,720
Speaker 12: it's hard to innovate. We're now into a phase where

588
00:31:49,720 --> 00:31:52,160
Speaker 12: we have a substantial amount of growth, so it's the

589
00:31:52,320 --> 00:31:55,760
Speaker 12: right time for nuclear to re emerge. It's also a

590
00:31:55,800 --> 00:31:59,160
Speaker 12: time where it can play an incrementally important role in

591
00:31:59,200 --> 00:32:02,640
Speaker 12: the decarbon is ation the existing system in the US.

592
00:32:02,680 --> 00:32:05,200
Speaker 12: A lot of the decarbonization that has happened in the

593
00:32:05,320 --> 00:32:08,520
Speaker 12: US to date was really coal to gas switching because

594
00:32:08,640 --> 00:32:12,200
Speaker 12: gas is two thirds less carbon intense than coal, but

595
00:32:12,280 --> 00:32:15,680
Speaker 12: there's still a carbon element. The beauty of nuclear is

596
00:32:15,720 --> 00:32:19,480
Speaker 12: at zero carbon, and as customers want to lower the

597
00:32:19,520 --> 00:32:23,760
Speaker 12: carbon intensity of their total solutions think hyperscalers as an example,

598
00:32:24,280 --> 00:32:28,760
Speaker 12: they'll pay to add nuclear into their power generation mix

599
00:32:29,120 --> 00:32:31,040
Speaker 12: to meet their sustainability commitments.

600
00:32:32,200 --> 00:32:34,960
Speaker 2: The increased demand for electricity is one reason the move

601
00:32:35,040 --> 00:32:38,880
Speaker 2: to nuclear may accelerate. Another is government support.

602
00:32:39,840 --> 00:32:42,880
Speaker 12: US government plays an incredibly important role. It starts with

603
00:32:43,120 --> 00:32:47,440
Speaker 12: the Nuclear Regulatory Commission approving our ability to start construction

604
00:32:47,520 --> 00:32:50,360
Speaker 12: on projects. We do expect that by the summer of

605
00:32:50,400 --> 00:32:54,720
Speaker 12: twenty six. Beyond that, funding certainly is a relevant dynamic.

606
00:32:54,800 --> 00:32:58,360
Speaker 12: We have a project with TVA Tennessee Valley Authority that

607
00:32:58,480 --> 00:33:01,240
Speaker 12: just received four hundred million dollars dollars of funding support

608
00:33:01,240 --> 00:33:04,400
Speaker 12: from the Department of Energy. We also signed one hundred

609
00:33:04,400 --> 00:33:08,360
Speaker 12: billion dollar MoU with the US government earlier this quarter

610
00:33:08,560 --> 00:33:13,080
Speaker 12: in October to industrialize small modular actors in the US.

611
00:33:13,240 --> 00:33:16,120
Speaker 12: When President Trump and a number of business leaders were

612
00:33:16,120 --> 00:33:19,520
Speaker 12: in Japan earlier in the year. That could materially move

613
00:33:19,600 --> 00:33:23,520
Speaker 12: the nuclear industry sooner if we gain access to a

614
00:33:23,520 --> 00:33:27,160
Speaker 12: lot of that funding right now, it's a MoU. We're

615
00:33:27,200 --> 00:33:30,400
Speaker 12: working really hard right now on site selection, on terms

616
00:33:30,400 --> 00:33:34,640
Speaker 12: and conditions to translate that MoU into a definitive agreement.

617
00:33:35,120 --> 00:33:37,000
Speaker 12: And if we can get something done with the US

618
00:33:37,080 --> 00:33:39,840
Speaker 12: government in that regard at scale, that could be a

619
00:33:39,880 --> 00:33:43,680
Speaker 12: real catalyst. So Secretary Rights Secretary Lutnik are both playing

620
00:33:44,280 --> 00:33:47,240
Speaker 12: very visionary leadership roles as I see it, to try

621
00:33:47,280 --> 00:33:50,320
Speaker 12: to move this nuclear industry, and we're working with them

622
00:33:50,320 --> 00:33:52,320
Speaker 12: every day and every week to make that a reality.

623
00:33:52,760 --> 00:33:56,800
Speaker 2: Business has all sorts of uncertainties. International relations go to

624
00:33:56,880 --> 00:34:00,400
Speaker 2: a degree beyond that. Yes, how confident are you in

625
00:34:00,440 --> 00:34:03,239
Speaker 2: that money from Japan specifically that was talked about in

626
00:34:03,280 --> 00:34:05,760
Speaker 2: the commitment for investment in the United States for Nuclear

627
00:34:06,080 --> 00:34:07,120
Speaker 2: Vernova specifically.

628
00:34:07,200 --> 00:34:09,480
Speaker 12: Well, in our case, one of the benefits we have

629
00:34:09,719 --> 00:34:12,920
Speaker 12: is we do have a Japanese partner in our nuclear business.

630
00:34:13,040 --> 00:34:17,120
Speaker 12: So it's g E Vernova Hitachi together. I mean, Hatachi

631
00:34:17,160 --> 00:34:19,960
Speaker 12: is a minority partner, but a very important partner for US.

632
00:34:20,000 --> 00:34:23,719
Speaker 12: So if the Japanese government is going to fund projects

633
00:34:23,760 --> 00:34:27,080
Speaker 12: in the US associated of that trade deal, it certainly

634
00:34:27,120 --> 00:34:30,560
Speaker 12: makes sense for it to be in arrangements where there's

635
00:34:30,680 --> 00:34:33,920
Speaker 12: Japanese companies also involved, and that's one of the benefits

636
00:34:33,960 --> 00:34:38,680
Speaker 12: we have. Ultimately, opining on whether the transaction happens or

637
00:34:38,719 --> 00:34:42,040
Speaker 12: not with the Japanese government is probably beyond my pay grade.

638
00:34:42,200 --> 00:34:44,320
Speaker 12: I'll tell you though, that when I was in Japan

639
00:34:44,440 --> 00:34:47,320
Speaker 12: with the US government and many of my business peers,

640
00:34:47,840 --> 00:34:49,840
Speaker 12: I found the interactions highly motivating.

641
00:34:51,400 --> 00:34:54,240
Speaker 2: Nuclear energy has had a long and not always smooth

642
00:34:54,360 --> 00:34:57,279
Speaker 2: path in the United States, but the coming together of

643
00:34:57,400 --> 00:35:00,720
Speaker 2: much higher demand for electricity, not least because of AI

644
00:35:00,840 --> 00:35:04,880
Speaker 2: data centers with bipartisan support in Washington, may mean that

645
00:35:05,000 --> 00:35:09,160
Speaker 2: this time truly is different, that nuclear power will provide

646
00:35:09,160 --> 00:35:12,560
Speaker 2: the card that completes that inside straight we need to

647
00:35:12,600 --> 00:35:14,000
Speaker 2: pay off for us.

648
00:35:13,800 --> 00:35:15,440
Speaker 13: All you know.

649
00:35:15,640 --> 00:35:18,200
Speaker 12: On the topic of nuclear I think the good news

650
00:35:18,280 --> 00:35:21,239
Speaker 12: right now is that's generally a topic that's agreed to

651
00:35:21,400 --> 00:35:24,920
Speaker 12: on both sides of the aisle, So there's some consensus there,

652
00:35:25,000 --> 00:35:28,120
Speaker 12: maybe more so than some other power generation sources. So

653
00:35:28,800 --> 00:35:32,640
Speaker 12: I'm not concerned about future administrations per se when it

654
00:35:32,640 --> 00:35:36,279
Speaker 12: comes to nuclear, So we needed a kickstart, and with

655
00:35:36,400 --> 00:35:39,800
Speaker 12: President Trump's vision, the country has it right now on nuclear.

656
00:35:39,920 --> 00:35:43,200
Speaker 12: So we do inside the company every day talk to

657
00:35:43,239 --> 00:35:47,000
Speaker 12: ourselves about meeting this moment in serving that vision. Twenty

658
00:35:47,040 --> 00:35:49,840
Speaker 12: twenty six is an incredibly important year for nuclear in

659
00:35:49,840 --> 00:35:51,960
Speaker 12: the US, but I think we're going to get a lot.

660
00:35:51,840 --> 00:35:56,840
Speaker 2: Done coming up shopping for the holidays, we look at

661
00:35:56,880 --> 00:35:59,480
Speaker 2: the future of department stores and what they need to

662
00:35:59,480 --> 00:36:14,879
Speaker 2: figure out to have a future. This is a story

663
00:36:14,920 --> 00:36:18,000
Speaker 2: about holding on to the past. There was a day

664
00:36:18,040 --> 00:36:20,560
Speaker 2: when department stores were at the very center of the

665
00:36:20,600 --> 00:36:24,799
Speaker 2: American middle class experience, from the elaborate display windows to

666
00:36:24,840 --> 00:36:27,920
Speaker 2: the main four cosmetics counters, all the way up the escalators,

667
00:36:27,960 --> 00:36:30,920
Speaker 2: through floor after floor of everything you needed for your

668
00:36:30,960 --> 00:36:35,080
Speaker 2: wardrobe and for your home. Our colleague Romaine Bostik reports

669
00:36:35,080 --> 00:36:38,399
Speaker 2: on one iconic retailer with ambitious plans to make its

670
00:36:38,440 --> 00:36:41,760
Speaker 2: department stores fit the new age of the American shopper.

671
00:36:43,160 --> 00:36:49,680
Speaker 15: The holiday season, that time of year when the city

672
00:36:49,680 --> 00:36:53,080
Speaker 15: that Never sleeps takes a moment to reflect lights twinkle

673
00:36:53,160 --> 00:36:55,640
Speaker 15: up and down to avenues of New York City from

674
00:36:55,640 --> 00:36:58,920
Speaker 15: the posh storefronts down and soho to the ornate window

675
00:36:58,960 --> 00:37:02,360
Speaker 15: displays up along fith Avenue to the epicenter in between

676
00:37:02,680 --> 00:37:05,880
Speaker 15: the miracle and magic of Macy's on thirty fourth Street.

677
00:37:06,400 --> 00:37:08,839
Speaker 4: Christmas is in just today. It's a frame of.

678
00:37:08,880 --> 00:37:13,080
Speaker 15: Mind American retailer sees on the season, hoping to capitalize

679
00:37:13,080 --> 00:37:16,600
Speaker 15: on that frame of mind, creating something that lasts beyond

680
00:37:16,800 --> 00:37:19,759
Speaker 15: just the holidays. A reflection of that effort can be

681
00:37:19,800 --> 00:37:22,440
Speaker 15: found about an hour's drive away from Manhattan in the

682
00:37:22,440 --> 00:37:25,600
Speaker 15: Long Island suburb of Garden City, New York, where Macy's

683
00:37:25,640 --> 00:37:27,759
Speaker 15: and spearheading a broader corporate transformation.

684
00:37:28,400 --> 00:37:30,880
Speaker 6: We're looking to be that neighborhood store, the place that

685
00:37:30,920 --> 00:37:33,359
Speaker 6: you think of that is it really convenient, but also

686
00:37:33,400 --> 00:37:35,280
Speaker 6: has special things that you can buy for the people

687
00:37:35,320 --> 00:37:35,680
Speaker 6: you love.

688
00:37:36,400 --> 00:37:38,759
Speaker 15: Tony Spring took over a CEO of Macy's Inc. In

689
00:37:38,800 --> 00:37:41,400
Speaker 15: twenty twenty four after more than nine years of helping

690
00:37:41,400 --> 00:37:45,480
Speaker 15: to refresh the company's luxury retail arm, Bloomingdale's. Now the

691
00:37:45,520 --> 00:37:48,320
Speaker 15: focus is on the Macy's brand itself, a middle market

692
00:37:48,360 --> 00:37:51,239
Speaker 15: department store that has been plagued by slowing sales and

693
00:37:51,320 --> 00:37:54,839
Speaker 15: waning cultural relevancy. In his first month on the job

694
00:37:54,960 --> 00:37:58,239
Speaker 15: Spring announced plans to close the third of US Macy's locations,

695
00:37:58,440 --> 00:38:00,520
Speaker 15: a move that would free up seven one hundred and

696
00:38:00,560 --> 00:38:03,840
Speaker 15: fifty million dollars of assets, money to be reinvested in

697
00:38:03,880 --> 00:38:08,040
Speaker 15: the best performing stores, including here at the Roosevelt Field Mall.

698
00:38:08,719 --> 00:38:11,840
Speaker 15: When it opened in the nineteen fifties, the Impai design

699
00:38:11,960 --> 00:38:15,239
Speaker 15: Roosevelt Field Mall was the largest in North America and

700
00:38:15,320 --> 00:38:18,520
Speaker 15: today is situated in a county whose median income is

701
00:38:18,560 --> 00:38:20,960
Speaker 15: significantly higher than the US average.

702
00:38:21,360 --> 00:38:25,120
Speaker 6: This is a storied retailer with incredible, rich history that

703
00:38:25,200 --> 00:38:27,480
Speaker 6: we're very proud of. But we never want our rich

704
00:38:27,600 --> 00:38:29,760
Speaker 6: history to get in a way of our brighter future.

705
00:38:29,800 --> 00:38:32,560
Speaker 6: The optionality that the customer has that they may want

706
00:38:32,560 --> 00:38:34,520
Speaker 6: to shop on their phone, they want to shop in

707
00:38:34,560 --> 00:38:36,680
Speaker 6: their car, they may want to shop in the store,

708
00:38:36,800 --> 00:38:39,600
Speaker 6: and we have to be able to adjust the way

709
00:38:39,680 --> 00:38:42,080
Speaker 6: we work to be able to provide that convenience for

710
00:38:42,120 --> 00:38:42,640
Speaker 6: the customer.

711
00:38:43,120 --> 00:38:46,040
Speaker 15: But that link between department stores and the customers they target,

712
00:38:46,160 --> 00:38:49,120
Speaker 15: it's largely broken down. Department stores account for less than

713
00:38:49,160 --> 00:38:52,520
Speaker 15: one percent of total US retail sales, down from about

714
00:38:52,560 --> 00:38:56,480
Speaker 15: sixteen percent in the early nineteen nineties. Retail historian Michael

715
00:38:56,520 --> 00:38:59,839
Speaker 15: Lisicki suggests the decline stems from losing sight of the cork.

716
00:39:00,880 --> 00:39:04,759
Speaker 14: These stores really excels when they were able to directly

717
00:39:04,880 --> 00:39:09,359
Speaker 14: serve their immediate communities. They weren't just commercial destinations, they

718
00:39:09,400 --> 00:39:13,239
Speaker 14: were social destinations, and that was so important in their

719
00:39:13,400 --> 00:39:14,360
Speaker 14: general success.

720
00:39:15,160 --> 00:39:18,160
Speaker 15: Department stores have long been a mirror of the American consumer,

721
00:39:18,360 --> 00:39:21,320
Speaker 15: but their roots they go back centuries to the Tokyo

722
00:39:21,400 --> 00:39:24,200
Speaker 15: fabric shops of the sixteen hundreds, to the more modern

723
00:39:24,239 --> 00:39:27,720
Speaker 15: template established in the eighteen fifties when a French husband

724
00:39:27,719 --> 00:39:31,160
Speaker 15: and wife duo transformed a small Parisian novelty shop into

725
00:39:31,239 --> 00:39:34,480
Speaker 15: La beau Mache, offering at the time the widest variety

726
00:39:34,520 --> 00:39:35,840
Speaker 15: of goods under one roof.

727
00:39:36,200 --> 00:39:39,720
Speaker 14: They started out very modest, usually as dry goods stores,

728
00:39:40,080 --> 00:39:43,080
Speaker 14: and then slowly graduated and became bigger.

729
00:39:43,280 --> 00:39:46,759
Speaker 16: It really was the focal center of so many communities.

730
00:39:46,800 --> 00:39:50,520
Speaker 17: What happened America race to the suburbs, and new families

731
00:39:50,560 --> 00:39:54,560
Speaker 17: were not necessarily drawn to department stores. They wanted price,

732
00:39:55,080 --> 00:39:58,319
Speaker 17: they wanted convenience, they wanted late hours, and though the

733
00:39:58,400 --> 00:40:02,440
Speaker 17: department stores tried to chase their traditional shopper to the suburbs,

734
00:40:03,320 --> 00:40:06,760
Speaker 17: the customer had changed who is the customer today?

735
00:40:06,840 --> 00:40:09,960
Speaker 14: I think that's a question that these remaining department stores

736
00:40:10,080 --> 00:40:11,720
Speaker 14: need to ask themselves.

737
00:40:12,080 --> 00:40:15,200
Speaker 15: The middle is exactly where macy still sees promise.

738
00:40:15,640 --> 00:40:18,080
Speaker 6: Let's think of the middle as the center, the center

739
00:40:18,120 --> 00:40:21,080
Speaker 6: of it all, which the center gives you the opportunity

740
00:40:21,120 --> 00:40:24,040
Speaker 6: to serve up and to serve down. And I think

741
00:40:24,080 --> 00:40:28,279
Speaker 6: from backstage to luxury, we have the opportunity across this

742
00:40:28,360 --> 00:40:32,600
Speaker 6: retail portfolio to satisfy what customers are looking for today.

743
00:40:32,760 --> 00:40:34,240
Speaker 4: The customer has choices.

744
00:40:35,000 --> 00:40:38,440
Speaker 11: They're not handcuffed to any mall or any downtown.

745
00:40:38,640 --> 00:40:40,200
Speaker 4: They can shop literally.

746
00:40:40,440 --> 00:40:44,640
Speaker 11: Anywhere, literally anywhere, and they love the freedom that they

747
00:40:44,719 --> 00:40:45,160
Speaker 11: can give it.

748
00:40:45,760 --> 00:40:48,080
Speaker 15: Mark Cohen is a retail veteran who worked as an

749
00:40:48,120 --> 00:40:50,880
Speaker 15: executive for some of the most iconic and now defunct

750
00:40:50,920 --> 00:40:54,400
Speaker 15: department stores at the golden era, Bradley's, Lord and Taylor

751
00:40:54,719 --> 00:40:55,320
Speaker 15: and Sears.

752
00:40:55,719 --> 00:41:00,319
Speaker 11: A store has to be neat, clean and friendly. That's

753
00:41:00,320 --> 00:41:04,680
Speaker 11: sort of step one. That's old style store management, and

754
00:41:05,000 --> 00:41:07,919
Speaker 11: it got lost at Macy's twenty five thirty years ago.

755
00:41:08,080 --> 00:41:09,560
Speaker 16: It seems like it would be a lot easier to

756
00:41:09,600 --> 00:41:12,040
Speaker 16: do that if you were a single brand store or

757
00:41:12,040 --> 00:41:14,120
Speaker 16: a more curated, smaller footprint.

758
00:41:14,120 --> 00:41:15,960
Speaker 11: It's easy if your Apple and you only have a

759
00:41:16,000 --> 00:41:18,600
Speaker 11: handful of products to sell, and your devotion is to

760
00:41:18,640 --> 00:41:23,600
Speaker 11: those products, and your store presentation is deliberately, completely simple

761
00:41:23,640 --> 00:41:24,480
Speaker 11: and straightforward.

762
00:41:24,520 --> 00:41:26,359
Speaker 4: It's all about the merchandise.

763
00:41:27,120 --> 00:41:30,240
Speaker 15: To make matters more complicated, the divide between the haves

764
00:41:30,239 --> 00:41:34,520
Speaker 15: and have nots is widening economic uncertainty, forcing middle income

765
00:41:34,560 --> 00:41:35,919
Speaker 15: households to pull back.

766
00:41:36,320 --> 00:41:38,120
Speaker 16: When you look at where we are in twenty twenty

767
00:41:38,120 --> 00:41:42,120
Speaker 16: five heading into twenty twenty six, is there a middle

768
00:41:42,160 --> 00:41:45,160
Speaker 16: market retail business model?

769
00:41:45,640 --> 00:41:48,880
Speaker 11: There's a market. It's not the market that there once was.

770
00:41:49,880 --> 00:41:54,319
Speaker 11: It's a market that's under tremendous pressure and challenge, but

771
00:41:54,600 --> 00:42:00,600
Speaker 11: it's viable if it represents things customers really want to buy,

772
00:42:01,360 --> 00:42:05,600
Speaker 11: and it treats customers well enough for customers to remain loyal.

773
00:42:06,000 --> 00:42:08,480
Speaker 15: One of the ways Macy's attempted to capture the shrinking

774
00:42:08,520 --> 00:42:12,920
Speaker 15: middle was through deep discounts. Tony Spring is changing that precedent.

775
00:42:13,400 --> 00:42:17,640
Speaker 6: I think closing a sale with value is compelling. People

776
00:42:17,719 --> 00:42:20,360
Speaker 6: do it in many walks of life, whether it's the hotel,

777
00:42:20,400 --> 00:42:23,000
Speaker 6: life stay at, or the restaurant that I visit. And

778
00:42:23,200 --> 00:42:26,720
Speaker 6: we're in many different loyalty programs but we shouldn't start

779
00:42:26,760 --> 00:42:29,360
Speaker 6: with the value. The value should be what helps close

780
00:42:29,400 --> 00:42:31,439
Speaker 6: the sale, not what helps open the sale. Let's talk

781
00:42:31,440 --> 00:42:35,439
Speaker 6: about leather, Let's talk about cashmere, Let's talk about lab

782
00:42:35,480 --> 00:42:38,359
Speaker 6: grown diamonds, Let's talk about fragrance. Let's talk about the

783
00:42:38,360 --> 00:42:41,520
Speaker 6: things that people actually attracted to. And then if value

784
00:42:41,600 --> 00:42:44,200
Speaker 6: is a way to close the sale, so be it.

785
00:42:44,200 --> 00:42:46,520
Speaker 15: It's a testament to a power shift from the old

786
00:42:46,640 --> 00:42:49,080
Speaker 15: days where department stores and their fashion buyers where the

787
00:42:49,120 --> 00:42:53,200
Speaker 15: taste makers, to today where the customer is firmly in charge.

788
00:42:53,400 --> 00:42:56,080
Speaker 15: So how does a department store meet shoppers on their terms?

789
00:42:56,320 --> 00:42:58,760
Speaker 8: I mean, in America, it's not like we really need

790
00:42:58,800 --> 00:43:02,440
Speaker 8: to purchase apparel or accessories. This is something you do

791
00:43:02,480 --> 00:43:04,319
Speaker 8: if you have a kid and they outgrow it. But

792
00:43:04,400 --> 00:43:08,319
Speaker 8: today's customer wants to be excited about buying something, and

793
00:43:08,400 --> 00:43:10,120
Speaker 8: I think that's what's missing.

794
00:43:10,880 --> 00:43:14,040
Speaker 15: Sean grain Carter is a branding expert and associate professor

795
00:43:14,080 --> 00:43:17,080
Speaker 15: at the Fashion Institute of Technology, and was once the

796
00:43:17,160 --> 00:43:20,960
Speaker 15: e commerce director for Macy's, helping launch its online strategy

797
00:43:20,960 --> 00:43:22,280
Speaker 15: in the late nineteen nineties.

798
00:43:22,560 --> 00:43:26,560
Speaker 8: It's the magic of wanting to shop, not having it

799
00:43:26,640 --> 00:43:29,120
Speaker 8: as drudgery. It's something you have to do because of

800
00:43:29,160 --> 00:43:31,080
Speaker 8: the holiday is coming up and therefore you have to

801
00:43:31,080 --> 00:43:34,200
Speaker 8: give a gift. It's the excitement of finding something new,

802
00:43:34,320 --> 00:43:38,160
Speaker 8: finding something that you think is sexy or interesting, or

803
00:43:38,280 --> 00:43:40,080
Speaker 8: just plain you know what you want.

804
00:43:40,600 --> 00:43:43,360
Speaker 15: These days, that excitement comes just as easily through a

805
00:43:43,360 --> 00:43:46,920
Speaker 15: few clicks, as e commerce offers customers and online version

806
00:43:47,040 --> 00:43:49,839
Speaker 15: of the everything store that department stores once were.

807
00:43:50,239 --> 00:43:54,000
Speaker 8: You could go to Macy's, you could go to Marshall Fields, Garfinkel's,

808
00:43:54,080 --> 00:43:57,640
Speaker 8: you know, Wannamakers, I'm Magnet, and feel that what you

809
00:43:57,840 --> 00:44:01,320
Speaker 8: bought was special because these stores made you feel special

810
00:44:01,400 --> 00:44:05,240
Speaker 8: and that experience made you feel special. Today it's almost

811
00:44:05,320 --> 00:44:08,960
Speaker 8: as if there's no excitement in shopping, and that's the

812
00:44:09,120 --> 00:44:12,000
Speaker 8: magic that's missing. I mean, we know Macy's with it

813
00:44:12,120 --> 00:44:16,480
Speaker 8: Thanksgiving Day parade and that's great, but customers don't want

814
00:44:16,520 --> 00:44:18,680
Speaker 8: to feel that you don't want them.

815
00:44:19,040 --> 00:44:21,799
Speaker 6: People love to be taken care of, and I think

816
00:44:22,040 --> 00:44:25,600
Speaker 6: with our environment, you know, to have a beauty advisor

817
00:44:26,000 --> 00:44:28,880
Speaker 6: tell you that that foundation doesn't really work on your skin.

818
00:44:29,400 --> 00:44:31,920
Speaker 6: To be able to mix different brands in beauty to

819
00:44:32,320 --> 00:44:36,120
Speaker 6: create what is your makeup regimen? That only happens when

820
00:44:36,160 --> 00:44:38,000
Speaker 6: you're working with people who will tell you the truth

821
00:44:38,239 --> 00:44:40,200
Speaker 6: that looks good on you, that doesn't look good on you.

822
00:44:40,440 --> 00:44:42,439
Speaker 6: And I think we learned a long time ago in

823
00:44:42,760 --> 00:44:45,560
Speaker 6: kind of retail sales one oh one to tell somebody

824
00:44:45,600 --> 00:44:47,799
Speaker 6: somebody looks good in something just to make a sale

825
00:44:48,040 --> 00:44:50,359
Speaker 6: only means you lose a customer for life. So you're

826
00:44:50,400 --> 00:44:53,280
Speaker 6: better to give them the honest opinion and find something

827
00:44:53,320 --> 00:44:55,040
Speaker 6: that works for them. I kind of come back to

828
00:44:55,520 --> 00:44:58,600
Speaker 6: multi brand, multi category and multiprisers. It is really an

829
00:44:58,640 --> 00:45:02,879
Speaker 6: effective advantage in this environment where people really aren't sure

830
00:45:03,280 --> 00:45:05,080
Speaker 6: what brand is right for them.

831
00:45:05,120 --> 00:45:07,880
Speaker 15: Online shopping in the US topped one point three trillion

832
00:45:07,920 --> 00:45:10,719
Speaker 15: dollars last year, but in store shopping is still the

833
00:45:10,760 --> 00:45:14,280
Speaker 15: preferred method for most Americans, with almost six trillion dollars

834
00:45:14,280 --> 00:45:18,000
Speaker 15: in sales, according to a report from Capital One. Bloomingdale

835
00:45:18,080 --> 00:45:21,520
Speaker 15: CEO Olivia A. Braun interprets these trends as complimentary.

836
00:45:21,880 --> 00:45:24,480
Speaker 18: Of course, digital will keep growing. It's a fast green

837
00:45:24,560 --> 00:45:27,800
Speaker 18: channel for US, and it's been the case for many years.

838
00:45:27,960 --> 00:45:30,800
Speaker 18: I think we have seen more and more transactions happening online.

839
00:45:30,920 --> 00:45:34,000
Speaker 18: But for me, the best way to actually invest online

840
00:45:34,360 --> 00:45:38,080
Speaker 18: is keep investing in the stores. The best branding investment

841
00:45:38,120 --> 00:45:40,759
Speaker 18: we can make as a department stores is investing in

842
00:45:40,840 --> 00:45:41,280
Speaker 18: the store.

843
00:45:41,680 --> 00:45:44,480
Speaker 15: Bloomingdale seems to have cracked the code under the Macy's

844
00:45:44,480 --> 00:45:47,560
Speaker 15: ink umbrella. The department store has leaned into its high

845
00:45:47,560 --> 00:45:48,759
Speaker 15: income consumer base.

846
00:45:49,080 --> 00:45:53,719
Speaker 11: Bloomingdale's emerged from the MRK of a middle ground, non

847
00:45:53,800 --> 00:45:58,040
Speaker 11: differentiated store on Third Avenue in the shadow of the

848
00:45:58,080 --> 00:46:02,839
Speaker 11: Third Avenue l I'm Sure showing you My age, and

849
00:46:02,880 --> 00:46:07,319
Speaker 11: became a real destination by virtue of the assortments that

850
00:46:07,360 --> 00:46:12,280
Speaker 11: it presented, the ambiance that created the mojo that it delivered.

851
00:46:13,239 --> 00:46:17,600
Speaker 15: Tony Spring is widely credited with restoring Bloomingdale's success, serving

852
00:46:17,640 --> 00:46:20,759
Speaker 15: as CEO from twenty fourteen to twenty twenty three. He's

853
00:46:20,760 --> 00:46:23,440
Speaker 15: now looking to bring that same feeling to Macy's.

854
00:46:23,600 --> 00:46:26,120
Speaker 6: The wonder of blooming Dale's is that you kind of

855
00:46:26,120 --> 00:46:28,560
Speaker 6: come in and a lot of eye candy, You see

856
00:46:28,680 --> 00:46:32,400
Speaker 6: great brands. There's the real careful precision and the curation

857
00:46:32,520 --> 00:46:34,560
Speaker 6: and the editing of what you see and how it

858
00:46:34,600 --> 00:46:35,640
Speaker 6: all comes to life.

859
00:46:35,760 --> 00:46:38,000
Speaker 11: He did a great job as the CEO of Bloomingdale's.

860
00:46:38,080 --> 00:46:44,080
Speaker 11: He's now got this enormous task of recreating, creating some

861
00:46:44,320 --> 00:46:47,759
Speaker 11: form of magic that exists for real at Macy's.

862
00:46:48,080 --> 00:46:49,080
Speaker 4: It's a different customer.

863
00:46:49,080 --> 00:46:51,520
Speaker 11: Though at Macy's it's a different customer, but it's the

864
00:46:51,560 --> 00:46:56,280
Speaker 11: same challenge. It's the same challenge. You've got to be special.

865
00:46:56,840 --> 00:46:59,840
Speaker 15: So when the holiday lights come down, the Thanksgiving Day parade,

866
00:47:00,000 --> 00:47:03,280
Speaker 15: loans go back into Sorge, and the New York rush resumes,

867
00:47:03,640 --> 00:47:06,480
Speaker 15: Macy's is still faced with the reality of a shrinking

868
00:47:06,520 --> 00:47:09,400
Speaker 15: middle class. Who is the Macy's customer today?

869
00:47:09,680 --> 00:47:14,960
Speaker 6: So working woman, family, people who enjoy, I think, the

870
00:47:15,040 --> 00:47:18,160
Speaker 6: nicer things in life, but also like value. And I

871
00:47:18,200 --> 00:47:21,919
Speaker 6: think the balance of us as retailer is not determining

872
00:47:22,200 --> 00:47:24,479
Speaker 6: this is on sale or this is not on sale,

873
00:47:24,560 --> 00:47:26,360
Speaker 6: or that everything you buy is on sale, or that

874
00:47:26,440 --> 00:47:28,719
Speaker 6: everything you buy is at regular price. We like to

875
00:47:28,760 --> 00:47:31,000
Speaker 6: have a menu, and I think it allows you to

876
00:47:31,040 --> 00:47:33,520
Speaker 6: indulge in the people that you love. We have the

877
00:47:33,560 --> 00:47:37,279
Speaker 6: capacity to show retail, to show the consumer Macy's at

878
00:47:37,320 --> 00:47:40,319
Speaker 6: its best. It's opposed to just trying to survive. And

879
00:47:40,360 --> 00:47:42,399
Speaker 6: I think there's a fine line that you move from

880
00:47:42,440 --> 00:47:45,879
Speaker 6: surviving to getting into the game, to playing to win,

881
00:47:46,160 --> 00:47:48,640
Speaker 6: to making sure you're showing the customer the very best

882
00:47:48,640 --> 00:47:49,520
Speaker 6: that you're capable of.

883
00:48:00,920 --> 00:48:01,920
Speaker 7: Six