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Speaker 1: Bloomberg Audio Studios, podcasts, radio news. This is the Bloomberg

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Speaker 1: Surveillance Podcast. Catch us live weekdays at seven am Eastern

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Speaker 1: on Apple CarPlay or Android Auto with the Bloomberg Business app.

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Speaker 1: Listen on demand wherever you get your podcasts, or watch

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Speaker 1: us live on YouTube.

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Speaker 2: Okay, Isabelle manteos Lago joined us with B and B

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Speaker 2: Perry Bob, but I want to take a moment here

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Speaker 2: with just bulletproof academics out of Eana Sience Po and

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Speaker 2: of course they're working at Cambridge as well. Just a

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Speaker 2: wonderful synthesis of us here. All talk, no action. Are

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Speaker 2: we going to see from a central banker to the

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Speaker 2: world on Wednesday?

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Speaker 3: I'll talk and no action.

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Speaker 4: Good morning, tom So. I think of the four central

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Speaker 4: banks making decisions this week and last week, the FEDI

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Speaker 4: is perhaps the it's unlikely to stick to just talk,

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Speaker 4: although our base case remains that they also do nothing. However,

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Speaker 4: there is a case to hike, and several of the

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Speaker 4: fo MC members have been making it and so it

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Speaker 4: will probably be one of these good family fights that

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Speaker 4: Kevin Wassh has been talking about. But don't balance my

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Speaker 4: base cases. They don't act either on Wednesday, and we

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Speaker 4: get some stern talk about commitment to deliver price stability

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Speaker 4: and being prepared to act.

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Speaker 5: Is that we do have energy prices pulling back today,

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Speaker 5: but of course they're much higher than everyone would like them.

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Speaker 5: And it leads to the discussion of inflation.

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Speaker 2: Here.

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Speaker 5: What's your underlying view of inflation out there?

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Speaker 4: Well, first of all, on energy prices, I think what's

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Speaker 4: been happening over the last two weeks that when the

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Speaker 4: strike's resumed and now some instant relief, even though the

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Speaker 4: situation in the Strait hasn't really changed in terms of

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Speaker 4: ability of oil to flow out, what it's telling us

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Speaker 4: is we're unlikely to get meaningful this inflation from energy

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Speaker 4: prices for the foreseeable future. And the sharp decline that

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Speaker 4: we saw in June was probably excessive. So that's number one,

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Speaker 4: And so that means all the central banks have to

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Speaker 4: look at what are the other drivers of inflation. And

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Speaker 4: that's where we were a bit more concerned about the

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Speaker 4: situation in the US than say in the Eurozone or

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Speaker 4: in the UK, where there are no other meaningful drivers

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Speaker 4: of inflation, whereas in the US you see much more

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Speaker 4: broad based inflation drivers.

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Speaker 2: Is about as your Danny and Bloomberg Money on Friday

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Speaker 2: partitioned America in the supply side dynamics and demand side dynamics.

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Speaker 3: Can you do the same in Europe?

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Speaker 2: I mean, are these supply side shacks in Europe?

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Speaker 4: Well, in the US you see much more well, you

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Speaker 4: see both. You see demand and supply, but principally demand.

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Speaker 4: And remember that energy, US being a net energy producer,

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Speaker 4: doesn't face the supply angle to the same degree, whereas

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Speaker 4: in Europe it is principally a supply a supply shock.

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Speaker 4: Demand has been resilient, but it's not per se a

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Speaker 4: driver of inflation in the way that we're seeing it

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Speaker 4: in the US.

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Speaker 5: So in Europe, what is the sense of the consumer there?

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Speaker 5: How is the consumer faring across Europe these days?

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Speaker 4: Not great? The consumer is facing, at least as far

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Speaker 4: as the second quarter is concerned, purchasing power has been

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Speaker 4: knocked backwards. If you believe the ECB projections for the

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Speaker 4: year as a whole, the consumer will still be a

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Speaker 4: little bit ahead in terms of purchasing power. However, consumption

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Speaker 4: is growing at about half the pace it normally does.

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Speaker 4: And what's been sustaining the resilience of growth that we've

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Speaker 4: seen is really the corporate sector, and in particular the

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Speaker 4: manufacturing sector, which has been supported by the defense industry

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Speaker 4: and by a resumption of construction activity infrastructure in a

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Speaker 4: number of economies, especially Germany. But the consumer sector in

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Speaker 4: Europe has been relatively weak and we expect that's going

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Speaker 4: to remain that way until we get significant relief from

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Speaker 4: energy prices.

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Speaker 5: So on that front there in terms of business and

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Speaker 5: state investment here we had when the Trump tariffs came

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Speaker 5: out initially in his first year of the second term,

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Speaker 5: Europe really stepping up on some of their infrastructure spending,

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Speaker 5: their defense spending. How has that played out, Yes, so.

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Speaker 4: The tariff shock in the end has been quite manageable

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Speaker 4: for Europe and in fact, the of course at subsectoral level,

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Speaker 4: I don't want to say no what has been impacted,

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Speaker 4: but at the end of the day, exports to the

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Speaker 4: US have have remained pretty resilient. And more importantly, Europe

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Speaker 4: is shifting to a more domestically driven growth growth story

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Speaker 4: with very historically large stimulus out of Germany which took

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Speaker 4: a bit of time to kick in, but now it's

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Speaker 4: going at full steam. Defense and infrastructure principally, but also

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Speaker 4: the rest of Europe investing in AI, investing in defense,

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Speaker 4: and that's really sustaining domestic demand very meaningfully.

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Speaker 2: Isabelle, thank you so much, isabel Mateosi Lago is too

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Speaker 2: short a visit with BNP paribove from Queen Victoria Street.

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Speaker 3: In London, stay with us.

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Speaker 2: More from Bloomberg Surveillance coming up after this.

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Speaker 6: We from on you too.

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Speaker 2: It's like oops, defaultse credit left tail fold in private

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Speaker 2: credit in the angst over the weekend, on private credit,

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Speaker 2: public credit, private credit is your left.

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Speaker 7: Tail risk, good morning, Thank you for having me so

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Speaker 7: taking them into so. In the High Old market, we

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Speaker 7: did raise our default forecast last week because we're a

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Speaker 7: little bit concerned about this left tail of borrowers that

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Speaker 7: haven't been contributing to the overall resilience in the credit markets.

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Speaker 7: That coupled with higher AI related issuance in the High

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Speaker 7: Old market, that market's not immune higher commodity costs, higher

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Speaker 7: rates translating into a higher cost of capital leaves us

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Speaker 7: on the margin somewhat concerned.

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Speaker 8: On the private credit point, I mean.

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Speaker 7: In many ways we actually just treat this like broader credit.

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Speaker 7: We have flagged recently that non appruals in credit and

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Speaker 7: private credit have increased a little bit in the first quarter,

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Speaker 7: but it's not outsize relative to the broader trend. The

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Speaker 7: key point we are watching in private credit and the

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Speaker 7: leverage loan market is the twenty twenty eight maturity wall,

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Speaker 7: because there's a lot of software debt that needs to

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Speaker 7: be refinanced. So far that refinancing has been encouraging. So yeah,

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Speaker 7: and we've already.

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Speaker 9: Started keep your job for you two months.

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Speaker 7: We've already started chipping away at that. It's been encouraging.

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Speaker 7: But that's the key point we're watching, all.

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Speaker 5: Right, Tom and Amanda's latest report Exhibit five. We estimate

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Speaker 5: nearly two hundred billion dollars of data center deal activity

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Speaker 5: in the private market since it start of twenty twenty five.

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Speaker 5: Man I did not know that who's buying this stuff.

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Speaker 7: It's happening under the surface, above and beyond the very

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Speaker 7: meaningful supply that we've already had from the AI ecosystem.

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Speaker 8: We estimate that's five hundred billion year to date.

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Speaker 7: So just the numbers here are extraordinary private markets.

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Speaker 8: There's four and a half.

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Speaker 7: Trillion of dry powder in private markets across all categories

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Speaker 7: right now. So that two hundred billion sounds large, we

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Speaker 7: think it's actually just the early stages. The good I

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Speaker 7: think the good thing about the private markets as it

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Speaker 7: relates to the small to your issuing cycle is that

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Speaker 7: we do expect the private markets will provide some certainty

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Speaker 7: of financing in the later years. The simple point is

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Speaker 7: that credit markets work best in funding releveraging when it's

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Speaker 7: quantifiable and there's an end in sight. That's not really

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Speaker 7: the case with this AI built out, So we do

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Speaker 7: see a large role for private markets here.

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Speaker 5: Who are the borrowers when a data center gets announced

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Speaker 5: and gets built, is the borrower the construction company?

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Speaker 7: So typically the borrower is an SPV that is separate

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Speaker 7: from the hyperscaler. But I think what you are alluding

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Speaker 7: to is something that we've noticed in our investor conversations

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Speaker 7: is that a lot of investors are increasingly counting their

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Speaker 7: data center exposure in their hyperscaler bucket, and so I

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Speaker 7: think it further increases our view. This is actually something

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Speaker 7: we outlined in April that issuer concentration and market saturation

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Speaker 7: constraints will be binding.

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Speaker 2: Is okay to Paul's brilliant question, and your even better

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Speaker 2: answer is this visible accounting. Can can fancy people like

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Speaker 2: you or Frank FOBOSEI actually go in and understand the

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Speaker 2: balance sheets of.

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Speaker 3: This new debt.

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Speaker 7: You can if you're willing to look at ten k's

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Speaker 7: and ten q's, which we do, and actually just using

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Speaker 7: the hyperscaler universe, there's about one point two trillion of

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Speaker 7: least commitments for data centers. Of that, seven hundred billion

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Speaker 7: is for data centers that haven't started yet, they haven't

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Speaker 7: begun construction. So to your question, Tom, that's not yet

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Speaker 7: reflected in traditional leverage metrics, that that commitment for a

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Speaker 7: data center that hasn't begun isn't yet counted in the financials.

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Speaker 7: Some rating agencies and many investors are adjusting that after

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Speaker 7: the fact. But that it is possible to do it

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Speaker 7: if you're willing to get into the financials.

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Speaker 5: So there are special borrowers here. But again, is it

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Speaker 5: if I'm going to my credit officer, I'm getting approval

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Speaker 5: for this loan, can I tell them at the end

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Speaker 5: of the day, Microsoft is backstopping this thing.

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Speaker 7: All of the deals are different, and whether or not

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Speaker 7: they're fully admortizing, or how the guarantee works or for example,

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Speaker 7: if there is a construction delay, who's on the hook?

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Speaker 7: I unfortunately can't paint it with broadbrush.

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Speaker 8: But I think what is most.

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Speaker 7: Critical from our perspective is that there's there's a lot

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Speaker 7: of focus on the hyperscalerd issuance, but actually data centers

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Speaker 7: like the ones you are referencing have represented more than

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Speaker 7: twenty percent of AI related supply this year. So it's

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Speaker 7: important to track the AI related issuance from the broader

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Speaker 7: tech ecosystem, not just the hyperscalers, and it further increases

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Speaker 7: that competition for county.

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Speaker 2: And j Danny joined us twelve noon on Friday and

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Speaker 2: he said something profound. It it went out of those

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Speaker 2: zechgeist nicely. He said, these rates we're at now are

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Speaker 2: what we're normal years ago. So that's you know, to me,

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Speaker 2: that's a really profound idea. I looked at a yearly

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Speaker 2: chart of the tenure going back to Eisenhower, and the

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Speaker 2: answer is, after the Great Moderation, I guess we're back

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Speaker 2: to something new or to productor your Denny's point is

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Speaker 2: it's something that's normal.

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Speaker 8: I listened to that interview. It was great, did you.

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Speaker 9: Uniques?

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Speaker 7: I think while that's true, Tommy, the important consideration for

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Speaker 7: credit investors so is that the credit markets have grown

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Speaker 7: so much since that time, and.

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Speaker 8: The shape of the credit markets is very different.

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Speaker 7: And so the last time when we were at these

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Speaker 7: rate levels so kind of pre financial crisis, the credit

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Speaker 7: markets were tiny. We didn't have as much refinancing that

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Speaker 7: was happening. We didn't have this capital intensive build out,

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Speaker 7: where again, I think it's hard to understate the importance

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Speaker 7: of this being a multi year issuing cycle, and so

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Speaker 7: that's really what we think is most critical.

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Speaker 5: So I see a lot of these companies not borring,

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Speaker 5: not just in the US, but in Canada, in Europe.

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Speaker 5: I think that's a good thing, isn't It showed the

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Speaker 5: breadth of this yes, barring.

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Speaker 8: And that's something we expect to continue.

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Speaker 7: The thing that jumped out to us, actually European AI

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Speaker 7: related credit has been holding in a little bit better

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Speaker 7: than the US, and so we dug under the surface

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Speaker 7: as to why. It's exactly the point you raised. There's

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Speaker 7: been a global amount of issuance, but it hasn't been

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Speaker 7: as heavy in Europe. So we do see scope for

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Speaker 7: the issuance in Europe to increase. In smaller regional markets

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Speaker 7: like Canadian dollars, Swiss frank Those markets are tiny, so

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Speaker 7: they're not gonna be able to do the heavy lifting.

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Speaker 8: That's where we think the private markets will come in.

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Speaker 2: Amanda, thank you so much. Let us know, give us

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Speaker 2: a front, you know, and Goldman Sacks is doing the

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Speaker 2: next hyperscaler piece, you know, bring send a raven, psych

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Speaker 2: House of Dragons, Game of Throne, Send a raven. So

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Speaker 2: we know a man in the line in there with

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Speaker 2: Goldman Sacks.

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Speaker 3: Stay with us.

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Speaker 2: More from Bloomberg Surveillance coming up after this.

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Speaker 1: You're listening to the Bloomberg Surveillance podcast. Catch us live

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Speaker 1: weekday afternoons from seven to ten am Eastern. Listen on

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Speaker 1: Applecarplay and Android Otto with the Bloomberg Business app, or

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Speaker 1: watch us live on YouTube.

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Speaker 2: I'ving a low dark as the door had advice, planning

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Speaker 2: and fiduciar services B.

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Speaker 3: And why in mouth I don't care?

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Speaker 2: You had the most coveted scholarship in the world, the

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Speaker 2: Thomas Jefferson Scholarship. You How in God's name did you

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Speaker 2: get from civil engineering to working for the Bank.

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Speaker 3: Of New York.

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Speaker 10: Great question, So as a tax attorney, right, I went

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Speaker 10: from civil engineering into law thinking I was going to

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Speaker 10: be a patent attorney. Then I just fell in love

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Speaker 10: with trusting the safe law when I sort of started practicing,

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Speaker 10: because Thomas, you can imagine the tax cod is very

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Speaker 10: much like a puzzle, which is what engineers do, right

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Speaker 10: with reverse engineering.

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Speaker 11: And figure out the math.

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Speaker 10: I'm probably the only lawyer out not only but I'm

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Speaker 10: probably on a few lawyers out there who are not

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Speaker 10: afraid of numbers. I love people, and I think families

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Speaker 10: and wealth is messy and it's great.

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Speaker 11: That's how I got to.

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Speaker 2: Engineer this is the bull market in order? Is the

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Speaker 2: bull market in place right now?

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Speaker 5: Well?

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Speaker 10: The way I think about it is that your wealth

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Speaker 10: planning actually has drive a lot with investments. And while

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Speaker 10: a lot of our clients are of course asking is

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Speaker 10: the bull market in place, they're also asking a question

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Speaker 10: about what it looks like in the long horizon. And

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Speaker 10: this is where wealth transfer planning come in. As you know,

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Speaker 10: we just publish our wealth Emotion Report by Being my Wealth,

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Speaker 10: and it tells us that a lot of our clients

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Speaker 10: are thinking about wealth transfer. They know they need to

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Speaker 10: do it, but the conversation is not over and it's

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Speaker 10: not quite done.

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Speaker 5: So how are people. Are people prepared? What are they

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Speaker 5: doing for this? Because we hear about this great wealth

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Speaker 5: transfer from my generation to the rugrats. And I told

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Speaker 5: my kids last check, I rate is going to bounce

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Speaker 5: and I don't wait on anything. How are people doing this?

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Speaker 10: So you're right, you know, we're looking at the so

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Speaker 10: called Great Weald Transfer, the one hundred and twenty four

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Speaker 10: trillion dollars that's expected transfer from the baby boomer generation

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Speaker 10: to the next generation, that the next twenty years. Right, And

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Speaker 10: I will tell you that the great wealth transfer is

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Speaker 10: still happening, but it's happening a little different.

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Speaker 11: Than when we all anticipated.

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Speaker 10: It's happening slower, and so I would look at it

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Speaker 10: more as a journey as opposed to us thingle oh.

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Speaker 9: Listen to you. Okay, So it's happening slower. Is it

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Speaker 9: appening slower.

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Speaker 2: Because we're all living longer, which is actually real? Or

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Speaker 2: is it appening slower because the brats have no interest

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Speaker 2: in Bloomberg survey?

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Speaker 11: We hope they do.

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Speaker 10: So I would say it's three things, two of which

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Speaker 10: you hit. The first is longevity. Right, people are living longer,

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Speaker 10: they're a little bit more worried.

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Speaker 9: Borshton posted the great article on that this weekend.

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Speaker 10: So, and the second is is that people do feel

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Speaker 10: like the errors are not quite ready right, and they're

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Speaker 10: not ready to as certain corresponsibility.

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Speaker 2: The middle child is at a Backstreet Boy concert this weekend.

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Speaker 3: They're not ready.

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Speaker 11: They're not ready.

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Speaker 10: Yeah, and so and then the third that we found

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Speaker 10: in our survey is actually a fear of changing regulatory

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Speaker 10: and tax environment.

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Speaker 11: So those are the three factors. You've got two of

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Speaker 11: them right on the air I'll.

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Speaker 9: Take in the Texas.

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Speaker 5: So how about philanthropy. How are people concerned about philanthropy

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Speaker 5: or are they just thinking about what's the most tax

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Speaker 5: efficient way for me to get my answers.

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Speaker 3: To my errors.

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Speaker 10: It's a little both, because sometimes you philanthropy plan can

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Speaker 10: actually marry with your own estay plans on how to

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Speaker 10: get to your airs. There's a lot of strategies where

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Speaker 10: you used that benefit both charity and personal. But speaking

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Speaker 10: of philanthropy, this is one of the things out to me,

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Speaker 10: was the most startling, most interesting data point from this

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Speaker 10: whole entire report because it highlights the theme, which is

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Speaker 10: that for wealthy families, there is a huge gap between

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Speaker 10: intention and execution. In our survey, for example, we found

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Speaker 10: ninety one percent of our respondent wants to leave a

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Speaker 10: charitable legacy, and guess what, only thirty six per them

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Speaker 10: actually have the plan to do.

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Speaker 9: So that rings true.

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Speaker 2: I mean to say, at least alving and low with

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Speaker 2: this right now, head of advice, planning and fiduciary services,

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Speaker 2: passing on the money to the kids.

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Speaker 3: B and why wealth? I look at this and.

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Speaker 2: At the end of the day, it's the reality of

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Speaker 2: the modern world. We're underwilled and are we under trusted?

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Speaker 2: Are we not using the legal vehicles we need to

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Speaker 2: use to transfer and yet maintain control?

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Speaker 11: Quite the contrary.

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Speaker 10: Actually, and now we pour two thirds of a respondent

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Speaker 10: actually at least have one trust in place. The average

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Speaker 10: is two point seven trust in place. So no, I

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Speaker 10: don't think we're under trusted. We're under execute and undercarry

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Speaker 10: out the plan. Because just because you have one trust

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Speaker 10: in place and you have the document, it doesn't mean

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Speaker 10: your plan is finished.

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Speaker 11: It is just the beginning, all right.

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Speaker 5: For our listeners and viewers, that's the first step. Go

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Speaker 5: to their tax person, go to their financial advisor, call

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Speaker 5: up a wealth manager. I mean, how did they start?

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Speaker 11: Yeah, great question.

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Speaker 10: No, I will not call your lawyer to start, because

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Speaker 10: they are a part of this, but not the starting point.

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Speaker 10: I always feel like you need to start with the y,

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Speaker 10: you need to start with your end goal. So I

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Speaker 10: would be working with your financial advisors to figure out

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Speaker 10: what your end goal is, what is your north star,

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Speaker 10: and then assemble the team. And one thing I do

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Speaker 10: not want to forget, and this is definitely the trend

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Speaker 10: that we're seeing in the last ten plus years or so.

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Speaker 10: Don't just focus on the tax and legal structure. Honestly,

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Speaker 10: that's the easy part. The harder part, which is what's

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Speaker 10: holding a lot of people back because we have all

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Speaker 10: these brats in that system, is that you have to

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Speaker 10: have the conversation with your children and their In our survey,

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Speaker 10: we found that only each one twenty percent feels that

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Speaker 10: there are children are ready for this because they simply

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Speaker 10: have not had.

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Speaker 2: I would say that number is high. I mean, you know,

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Speaker 2: I mean, I grew up on a twisted house, folks.

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Speaker 2: It was decidedly not normal like me. But the answer

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Speaker 2: is even the kids that weren't engaged forty years ago

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Speaker 2: were somewhat engaged. I find not just you know, my

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Speaker 2: wonderful offspring. Most of the kids. They're literally like removed

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Speaker 2: from thinking about financial issues right.

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Speaker 10: And a lot of people confuse financial education with financial readiness.

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Speaker 4: Right.

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Speaker 8: A lot of people.

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Speaker 10: Nice to talk to us about Hey, can you come

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Speaker 10: and talk to our kids about basic investing?

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Speaker 11: What is the worst?

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Speaker 9: They have no interest is what I what I see

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Speaker 9: day to day.

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Speaker 10: That's why we actually need to engage them in doing right.

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Speaker 10: So it's not just teaching right. Anybody could get information

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Speaker 10: people doing.

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Speaker 2: Set up an account of b Nymels.

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Speaker 9: We would love that trade SpaceX.

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Speaker 10: Well, we would love to get them engaged in a conversation.

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Speaker 10: So for example, getting them to be co trustee of

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Speaker 10: their trust, not necessarily of all the decision when they

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Speaker 10: come off age, but be at a seat at the

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Speaker 10: table so they have a vote. Getting them involved with philanthropy,

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Speaker 10: set up a donor advice fund, do something small to

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Speaker 10: incremental to start, but have them actually making decisions rather

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Speaker 10: than talking to them.

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Speaker 11: Let's bring them along.

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Speaker 2: I mean, you borrow your kids nine years of paramount, right,

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Speaker 2: that worked out?

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Speaker 5: What's the reasonably proper age to start these discussions with

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Speaker 5: your children?

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Speaker 10: Well, I think it depends on It depends on what

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Speaker 10: type of conversation I think they can start as early

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Speaker 10: as elementary school. Not necessarily tell them, you know, net

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Speaker 10: worth and every dollar, but just talk to them about

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Speaker 10: investing in saving.

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Speaker 11: So I know we started off with this.

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Speaker 10: My son is actually on his college orientation today and

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Speaker 10: he had a job last summer at the local pool.

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Speaker 5: Right.

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Speaker 10: I got him to do a raw IRA and I

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Speaker 10: opened him of a small account. I told him about

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Speaker 10: what mommy matchew, which means if you put your money

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Speaker 10: into the IRA, I will give you an.

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Speaker 11: Equivalent amount to spend.

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Speaker 10: So he has this tiny little account, you know, and

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Speaker 10: he invested in you know, he looks up the app,

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Speaker 10: he looks at the investment, right, and he gets to

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Speaker 10: watch it. I want to engage him doing early on.

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Speaker 2: In civil engineering. To me, it's like microeconomics and economics.

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Speaker 2: There's a point like your sophomore year you take static

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Speaker 2: and dynamics. Oh yes, and that separates that separates the

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Speaker 2: women from the.

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Speaker 11: Girls, all the men from the boys, and.

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Speaker 2: Then you jump the thermodynamics and then it's like okay, you.

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Speaker 11: See, that's why the tax code doesn't scare me.

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Speaker 2: Yeah.

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Speaker 9: Are you based in New York, New York?

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Speaker 11: No, I'm in New York. I am in New York

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Speaker 11: right down the block.

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Speaker 9: She has to put up with Jeff Up. You know

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Speaker 9: Alicia Levine.

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Speaker 3: Oh, I love Alicia has some prodigious math skills. There

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Speaker 3: another one.

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Speaker 2: I mean, you know, talk about civil engineering. This has

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Speaker 2: been great, Alvina Lo, thank you so much for coming in.

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Speaker 2: Let me know when the kids figure it out, because

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Speaker 2: I don't say it.

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Speaker 3: She is with b and why it melt. Stay with us.

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Speaker 2: More from Bloomberg Surveillance coming up after this.

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Speaker 1: You're listening to the Bloomberg Surveillance podcast. Catch us Live

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00:21:17,480 --> 00:21:20,679
Speaker 1: weekday afternoons from seven to ten am Eastern. Listen on

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00:21:20,720 --> 00:21:24,399
Speaker 1: Applecarplay and Android Auto with the Bloomberg Business app, or

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00:21:24,560 --> 00:21:26,240
Speaker 1: watch us live on YouTube.

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Speaker 2: So Peter Orzeg shows up at Lazard and they go

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Speaker 2: yeah on the watch on aie and we got a

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Speaker 2: French literature major from Sult Korea that works out joining us.

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Speaker 2: Seline Wu, portfolio manager at Lizard Asset Management. Right now

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Speaker 2: in the Zeitgeist this weekend with Sacha n Adella.

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Speaker 3: There was others.

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Speaker 2: Jensen was out there, but Sacha Ndella at Microsoft has

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Speaker 2: a lot of headaches. I don't want you to do

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Speaker 2: by hold Sell. I know that's inappropriate on Microsoft. But

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Speaker 2: what is the character in the earning season of the

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Speaker 2: AI headaches of someone like Microsoft?

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Speaker 6: Well, I guess, I mean, thank you for having me first.

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Speaker 6: I guess the key events and development that we continue

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Speaker 6: to watch and scrutinize are how much is going to

445
00:22:09,400 --> 00:22:12,880
Speaker 6: be the cape expanding just to support this massive AI

446
00:22:12,960 --> 00:22:15,640
Speaker 6: datas into a build out? And where are the use cases?

447
00:22:15,720 --> 00:22:18,280
Speaker 6: Where are the return on investment? Where are you seeing

448
00:22:18,320 --> 00:22:21,000
Speaker 6: in terms of generating and accelerating revenue groows?

449
00:22:21,480 --> 00:22:22,800
Speaker 3: I get the use cases?

450
00:22:23,400 --> 00:22:26,640
Speaker 2: How in God's name can they generate a conference call

451
00:22:27,000 --> 00:22:29,760
Speaker 2: an ROI? Now, I don't see it.

452
00:22:30,119 --> 00:22:32,720
Speaker 6: You don't see any ROI use cases from their conference calls.

453
00:22:32,760 --> 00:22:33,760
Speaker 9: I'm asking you.

454
00:22:33,840 --> 00:22:36,680
Speaker 6: Well, I mean, let's start with the hyperscalers. I think

455
00:22:37,359 --> 00:22:40,320
Speaker 6: where we see the most immediate and the tensible areas

456
00:22:40,359 --> 00:22:43,560
Speaker 6: seeing the revenue acceleration is their core businesses, which is

457
00:22:43,600 --> 00:22:47,000
Speaker 6: their cloud services platform. Look at these companies. If you

458
00:22:47,080 --> 00:22:50,119
Speaker 6: see their ear and ear revenue glows for their cloud services,

459
00:22:50,359 --> 00:22:53,160
Speaker 6: it has started to accelerate shorting from the second half

460
00:22:53,160 --> 00:22:55,640
Speaker 6: of last year, which I saw that from the alphabet

461
00:22:55,680 --> 00:22:59,440
Speaker 6: last year, which is pretty fantastic. And these companies continue

462
00:22:59,480 --> 00:23:02,600
Speaker 6: to highlight that how it is so difficult for them

463
00:23:02,640 --> 00:23:06,800
Speaker 6: to meet all the customers the demand for their cloud services.

464
00:23:07,080 --> 00:23:10,040
Speaker 6: Hence the badlock number, which is another very important data

465
00:23:10,040 --> 00:23:12,240
Speaker 6: point to build the like to monitor and I think

466
00:23:12,280 --> 00:23:15,800
Speaker 6: only in all those are the most important short to

467
00:23:15,880 --> 00:23:19,000
Speaker 6: medium terms data points guiding lights. You continue to have

468
00:23:19,080 --> 00:23:21,879
Speaker 6: the monitor and understand why they continue to commit to

469
00:23:21,920 --> 00:23:22,959
Speaker 6: spend a lot of money.

470
00:23:23,440 --> 00:23:27,200
Speaker 5: You say to focus on enabling technologies. Examples of what

471
00:23:27,240 --> 00:23:28,680
Speaker 5: are enabling technologies?

472
00:23:28,880 --> 00:23:32,080
Speaker 6: Yeah, I mean that's actually one of the most important

473
00:23:32,200 --> 00:23:36,160
Speaker 6: and then may be relatively underappreciated compared to hardware infustrate companies.

474
00:23:36,320 --> 00:23:40,080
Speaker 6: When you think about AI spending, for Techi, we currently

475
00:23:40,119 --> 00:23:43,200
Speaker 6: allocate about twenty to twenty five percent of the portfolio

476
00:23:43,240 --> 00:23:47,879
Speaker 6: for these companies. These are basically referring to selective software

477
00:23:48,000 --> 00:23:52,480
Speaker 6: and technology companies for example, cybersecurity vendors which are critical

478
00:23:52,800 --> 00:23:56,320
Speaker 6: to maintain the AI systems seamlessly and safely as well

479
00:23:56,600 --> 00:24:00,520
Speaker 6: and some of the infestral software companies including opser ability

480
00:24:00,560 --> 00:24:04,600
Speaker 6: Software or the EDA, which is Electronic design automation software,

481
00:24:04,640 --> 00:24:07,240
Speaker 6: which is critical set of tools than you need when

482
00:24:07,240 --> 00:24:10,920
Speaker 6: you want to design and the manufacture electronic systems. Including

483
00:24:10,920 --> 00:24:14,119
Speaker 6: some conductors. I think there are a lot of selective

484
00:24:14,200 --> 00:24:19,280
Speaker 6: companies that present compelling investment opportunities within the AI tech stack,

485
00:24:19,600 --> 00:24:23,320
Speaker 6: and they are foundational onunder line software tools that are

486
00:24:23,320 --> 00:24:25,080
Speaker 6: critical to maintain AI systems.

487
00:24:25,640 --> 00:24:28,520
Speaker 5: Company like Microsoft socks down twenty one percent here to

488
00:24:28,560 --> 00:24:31,679
Speaker 5: data kind of got drawn down, pulled down with some

489
00:24:31,800 --> 00:24:34,359
Speaker 5: of these software as a service sector here. How do

490
00:24:34,440 --> 00:24:38,760
Speaker 5: you think about that scenario at maybe Microsoft in particularly.

491
00:24:38,800 --> 00:24:41,359
Speaker 6: Well, I can really comment specifically about one stuff, but

492
00:24:41,520 --> 00:24:44,880
Speaker 6: that being said, what I can present instead is the

493
00:24:44,920 --> 00:24:49,360
Speaker 6: definition of competitiveness for the traditional software are clearly changing

494
00:24:49,720 --> 00:24:52,760
Speaker 6: in the phase of innovation from the AI labs. We

495
00:24:52,840 --> 00:24:56,720
Speaker 6: have seen like major development and consequences and implications coming

496
00:24:56,760 --> 00:24:59,520
Speaker 6: out of the cloud code beginning of this year. So

497
00:24:59,680 --> 00:25:02,640
Speaker 6: that said, I think a lot of incumbent companies, it's

498
00:25:02,680 --> 00:25:05,879
Speaker 6: critical for you to prove to the market not only

499
00:25:05,920 --> 00:25:08,840
Speaker 6: from the offense but from the defense perspective that you're

500
00:25:08,920 --> 00:25:11,240
Speaker 6: not going to be disrupted, but you can actually use

501
00:25:11,280 --> 00:25:15,520
Speaker 6: this innovation to be accelerated. Your revenue line.

502
00:25:14,960 --> 00:25:17,520
Speaker 2: Will with this lazard as we dive into some of

503
00:25:17,560 --> 00:25:21,480
Speaker 2: the AI nic cities, particularly involving other nations. So over

504
00:25:21,520 --> 00:25:26,840
Speaker 2: the weekend, cx MT was a transaction in China, and

505
00:25:26,920 --> 00:25:30,960
Speaker 2: yet at the same time President g is pulling back

506
00:25:31,040 --> 00:25:36,199
Speaker 2: from overt economics and investment in finance outside of China.

507
00:25:36,960 --> 00:25:40,560
Speaker 2: Is China going to be capitalistic in the AI world

508
00:25:40,840 --> 00:25:42,760
Speaker 2: or are they going to be some unique calculus.

509
00:25:42,760 --> 00:25:45,640
Speaker 6: We don't know, and that's a great question. One thing

510
00:25:45,680 --> 00:25:48,199
Speaker 6: for sure is what China is trying to build and

511
00:25:48,320 --> 00:25:51,800
Speaker 6: intend to innovate is just trying to proliferate open source

512
00:25:51,920 --> 00:25:55,520
Speaker 6: models as soon as possible, as fast as possible, because

513
00:25:55,600 --> 00:25:58,760
Speaker 6: ultimately that is going to be solved in proliferation in

514
00:25:58,840 --> 00:26:00,159
Speaker 6: terms of AI application And.

515
00:26:00,359 --> 00:26:03,719
Speaker 2: So non sophisticates like me go there the phrase we

516
00:26:03,800 --> 00:26:05,679
Speaker 2: use selene as they're cleaning our clock.

517
00:26:05,920 --> 00:26:09,159
Speaker 6: Are they they're cleaning the clock? I mean, it remains

518
00:26:09,200 --> 00:26:12,160
Speaker 6: to be seen. But basically you know that open source

519
00:26:12,520 --> 00:26:15,359
Speaker 6: compared to the closed source frontier models in the US

520
00:26:15,400 --> 00:26:19,560
Speaker 6: in the West, have different use cases, different cost understanding analysis.

521
00:26:19,600 --> 00:26:22,520
Speaker 6: So we will just like we will monitor how depends

522
00:26:22,520 --> 00:26:24,720
Speaker 6: out in terms of the application layer in China.

523
00:26:24,840 --> 00:26:26,280
Speaker 5: What do you mean looking for from the big tech

524
00:26:26,359 --> 00:26:32,080
Speaker 5: names this week? Are you doing more spending better ROI discussions?

525
00:26:32,119 --> 00:26:34,000
Speaker 5: What are you looking for from some of the big

526
00:26:34,040 --> 00:26:35,639
Speaker 5: tech names that are reporting this week.

527
00:26:36,440 --> 00:26:40,280
Speaker 6: I'm looking forward to see definitely the trajectory in terms

528
00:26:40,320 --> 00:26:42,560
Speaker 6: of CAPE expending, not just for the CERN next year

529
00:26:43,200 --> 00:26:46,880
Speaker 6: and how that recon cells with their expectation and outlook

530
00:26:46,880 --> 00:26:50,200
Speaker 6: for their revenue groups. But more importantly, I think again

531
00:26:50,400 --> 00:26:54,480
Speaker 6: for these hyperskillers and big tech companies, the definition of

532
00:26:54,520 --> 00:26:57,359
Speaker 6: traditional competitiveness and most are changing as well, and I

533
00:26:57,359 --> 00:27:01,000
Speaker 6: think we're actually seeing more in tension and interest for

534
00:27:01,080 --> 00:27:05,119
Speaker 6: them to build more vertically integrated business models across the

535
00:27:05,200 --> 00:27:06,960
Speaker 6: yet tax stack. You just don't want to be a

536
00:27:07,080 --> 00:27:10,520
Speaker 6: just frontier model providers or the software or the distribution

537
00:27:10,640 --> 00:27:13,560
Speaker 6: or data. You just want to own as much as

538
00:27:13,600 --> 00:27:17,439
Speaker 6: possible waiting because of the aetic step, because ultimately that

539
00:27:17,560 --> 00:27:19,680
Speaker 6: is what is going to pay off in the long engn.

540
00:27:19,560 --> 00:27:21,600
Speaker 9: Selin, thank you so much, slain Well, great brief.

541
00:27:21,960 --> 00:27:25,399
Speaker 2: Portfolio Manager, Lizard Asset Management, thank you for coming in.

542
00:27:25,920 --> 00:27:30,760
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543
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