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Speaker 1: This is Bloomberg Business Week with Carol Masser and Tim

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Speaker 1: Stenevek on Bloomberg Radio.

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Speaker 2: It is Bloomberg BusinessWeek. I'm Tim Stenevek. That is Carol Masser,

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Speaker 2: and we are following what's going on with all the

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Speaker 2: companies that are reporting right now so far. In terms

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Speaker 2: of the big companies that we're following this afternoon, Carol,

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Speaker 2: we're looking at shares of Tesla, which are lower in

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Speaker 2: the after hours. In addition to that, we're also looking

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Speaker 2: at shares of Microsoft, which are following after their report.

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Speaker 3: Yeah. Absolutely, we've got Microsoft down almost four percent here

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Speaker 3: in the aftermarket. As we said, some disappointment over maybe

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Speaker 3: some of the numbers in the second quarter revenue sixty

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Speaker 3: nine point sixty three billion estimate, estimate was sixty eight

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Speaker 3: point nine two.

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Speaker 4: That's actually better.

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Speaker 3: Second quarter Azure revenue was at thirty one percent. The

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Speaker 3: estimate was for gain of thirty one point eight percent.

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Speaker 3: But the second quarter cloud revenue that missed estimate, and

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Speaker 3: so that second quarter intelligent cloud revenue twenty five point

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Speaker 3: fifty four billion dollars, the estimate was just a tad

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Speaker 3: above that at twenty five point eighty nine billion. So again,

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Speaker 3: maybe some concerns over that and expectations are high right now.

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Speaker 2: Okay, he doesn't ignore it, but he doesn't cover it

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Speaker 2: like some of his colleagues. Man keep seeing his Bloomberg

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Speaker 2: Intelligence senior technology analyst as we await meta earnings to cross.

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Speaker 2: We're going to make him go a little out of

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Speaker 2: his element and speak to Microsoft, because you can't ignore

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Speaker 2: what's going on with Microsoft. Man, deep, give us an

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Speaker 2: idea of what sticks out to you from this company.

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Speaker 5: I mean, look, the Intelligent Cloud number missed. Probably that

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Speaker 5: has to do with, you know, a lower adoption of

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Speaker 5: three sixty five co pilots. They've been touting that and

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Speaker 5: the expectations had gone up. And look, it's one of

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Speaker 5: those products where the ROI so far hasn't been there.

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Speaker 5: The promise is there, and that's why they are emphasizing

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Speaker 5: the Azure number. The thirteen billion dollar rund rate, one

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Speaker 5: hundred and seventy five percent growth. Look, it's stellar by

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Speaker 5: any comparisons. And from that perspective, the infrastructure side looks

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Speaker 5: solid right now. It's the copilots and the application side

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Speaker 5: where you're seeing some hesitation. And look, I think the

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Speaker 5: native integration with open AI as long as it's there,

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Speaker 5: it should help all their products. But there's more competition.

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Speaker 5: I mean, Salesforce has been launching their agent so there

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Speaker 5: is more competition in the application there now than there

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Speaker 5: was before.

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Speaker 3: And the point is you will build it, but will

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Speaker 3: they come? And that's what it's kind of like what

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Speaker 3: they're waiting for.

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Speaker 5: Correct, Well, if you're asking enterprises to pay thirty dollars

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Speaker 5: extra per user for that copilot feature, it better be good.

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Speaker 5: I mean, that's the you know, the key takeaway is like,

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Speaker 5: if you want to upsell such an expensive product has

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Speaker 5: to have some level of productivity.

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Speaker 2: So remind everybody where Microsoft stands in terms of the lms,

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Speaker 2: because you mentioned a company like Salesforce. Is a company

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Speaker 2: like Salesforce building its own LLLM or they building an

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Speaker 2: agent on top now an existing LLLM, maybe from Microsoft,

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Speaker 2: maybe Lama from Meta, maybe chat GPT from open Ai

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Speaker 2: or claud from.

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Speaker 5: mPire exactly, So they are not building their own LLLM.

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Speaker 5: At the same time, they have gone big in their

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Speaker 5: agent force concepts and they're saying AI agency is where

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Speaker 5: they are doubling down on and they don't need to

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Speaker 5: own an LLLM. So that's where I think with the

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Speaker 5: open source saying, you know of deep seek and the

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Speaker 5: fact that pricing is coming down, all that is positive

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Speaker 5: for every application software provider, not just Salesforce, even word

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Speaker 5: Day or SAP. They can integrate LLLM functionality now and we.

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Speaker 3: Saw software names certainly rally this week. Having said that,

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Speaker 3: Microsoft has a specially unique exposure to open AI and

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Speaker 3: chat Gypt in terms of the what thirteen fourteen.

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Speaker 4: Billion dollars or so that they have invested.

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Speaker 3: So does that put them on a certain level of

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Speaker 3: vulnerability Perhaps, No.

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Speaker 5: Because they are benefiting from the infrastructure revenue that thirteen

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Speaker 5: billion dollar rund rate. It's all Azure cloud consumption, nothing

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Speaker 5: to do with the co pilots, just companies that are

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Speaker 5: leveraging their infrastructure to run their cloud operations or deploy

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Speaker 5: their applications. So that meter is still running, and it's

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Speaker 5: running very fast. I mean, one hundred and seventy five

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Speaker 5: percent growth just on infrastructure is very impressive. It's just

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Speaker 5: the application side, the lift from copilot.

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Speaker 2: I think that's.

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Speaker 5: Where they'll probably see more competition and probably expectations were

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Speaker 5: too high.

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Speaker 2: Well, speaking of expectations, we're expecting Meta platform shares with

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Speaker 2: platforms earnings across very soon. We have no idea what

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Speaker 2: those shares are going to do in the after hours

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Speaker 2: revenue estimate coming in at close to forty seven billion dollars,

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Speaker 2: what's the most important line item that you're looking at here?

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Speaker 5: So big Meta raised its capex right before we had

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Speaker 5: this deep sixty five billion dollars.

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Speaker 2: Okay, was that before? Because that had to be on

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Speaker 2: Mark Zuckerberger's radar.

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Speaker 5: It was, but still they chose to do it. Now

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Speaker 5: the fact that this is really a positive development for

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Speaker 5: open source, everyone is thinking Meta won't have to spend

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Speaker 5: sixty to sixty five and they will take it back.

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Speaker 5: So that capex number is still the key for me

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Speaker 5: because Meta has been known for spending spending big on

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Speaker 5: reality labs and now you know, building data centers.

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Speaker 2: Are you saying that there's a chance we could hear

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Speaker 2: a pullback in that capex number and investors might cheer

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Speaker 2: that Investors cheered the investment number on Friday. I was

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Speaker 2: surprised to see that.

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Speaker 5: Not so soon, I think with the deep seek, the

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Speaker 5: fact that you know, everyone is very excited about open

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Speaker 5: source Meta coming out and saying we can monetize lama

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Speaker 5: our model, which really no one will sure how are

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Speaker 5: they going to monetize it? Suddenly, I think that's that

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Speaker 5: becomes a very valuable proposition. And I think just his

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Speaker 5: plans around how do they plan to monetize AI and

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Speaker 5: really not going above sixty five billion, that's the other

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Speaker 5: rest because you know, you could revise it further upward.

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Speaker 5: At least, I think those fears have gone away, that

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Speaker 5: they're sixty five is a cap.

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Speaker 4: We talk so much about AI.

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Speaker 3: I mean for Meta, it's still though, advertising, like something.

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Speaker 4: As simple as that is still such an important indicator.

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Speaker 4: That's their business.

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Speaker 2: I mean, forty five point six of the forty seven

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Speaker 2: billion dollars Carrol that's expected to be reported advertising, And.

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Speaker 4: I understand it all plays together, but still that's the metric.

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Speaker 5: Yeah, And the best way to compare is compare Google

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Speaker 5: search revenue growth with Meta's you know, social media ad

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Speaker 5: revenue growth. So Google Search is a two hundred billion

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Speaker 5: dollar business growing at high single they did at best.

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Speaker 5: Meta is close to one hundred and sixty billion, growing

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Speaker 5: eighteen percent.

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Speaker 2: How does reality Labs how do Reality Labs products help

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Speaker 2: meta platforms sell advertising better? Well?

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Speaker 5: So their bed is on that Meta AI, which for

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Speaker 5: which they have six hundred million users now. And the

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Speaker 5: form factor, their own form factor is the glasses that

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Speaker 5: you can distill a model. And everyone is talking about

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Speaker 5: distillation right now because that's what deep Seek showed us.

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Speaker 5: That you can distill a larger model into a smaller model.

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Speaker 5: Maybe that model can run on your glasses.

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Speaker 2: Okay, how does that help me sell it more ads?

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Speaker 5: Well, they will learn so much more about you as

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Speaker 5: a person that they can show you a more personalized

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Speaker 5: ad when you go to Instagram or Facebook. And that's

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Speaker 5: where you know. Meta strength has always been the quality

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Speaker 5: of their ads.

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Speaker 2: So still, at the end of the day, that's what

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Speaker 2: it's all about.

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Speaker 5: Yeah, at least for now.

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Speaker 3: I just want to remind everybody. I'm looking at our

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Speaker 3: live blog, which is waiting for Meta's fourth quarter earnings.

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Speaker 3: Our Kurt Wagner says they usually drop a few minutes

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Speaker 3: after the market close at four pm New York time.

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Speaker 3: Still waiting on them, they say, He says, it's a

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Speaker 3: bit of a rare delay. We usually have them, like

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Speaker 3: we said, right after the market close, so we're waiting them.

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Speaker 3: As soon as they come across. We're going to have

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Speaker 3: men deep break them down. Also in studio is our

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Speaker 3: own Caroline Hyde, who's co host of Bloomberg Technology on

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Speaker 3: Bloomberg Television. And Caroline, we've also had Tesla earnings. We've

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Speaker 3: been talking with Man Deep about Microsoft as we await

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Speaker 3: Meta go where you are because it just feels like

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Speaker 3: both Microsoft and Tests I've seen some pressure here in

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Speaker 3: the act.

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Speaker 1: And also I don't know if you've broken down Service Now,

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Speaker 1: but suddenly software became quite the thing of this week

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Speaker 1: because we all suddenly freaked out about AI infrastructure and hardware.

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Speaker 1: But with software going to be gaining from these Deep

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Speaker 1: Seek revelations, Service now actually looking pretty lackluster. Outlook on

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Speaker 1: the slower than have been anticipated. We were thinking AI

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Speaker 1: was going to give it this massive bump. Overall fiscal

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Speaker 1: year sales outlook fell short of those expectations. Subscription revenue

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Speaker 1: going to be twelve point seven billion dollars twenty twenty five.

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Speaker 1: Market want to see more, so their shares are dropping hard,

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Speaker 1: and I think this is where we're going to have

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Speaker 1: to hear more from Microsoft as well. Is the Open

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Speaker 1: AI integrated offering not selling at the pace that they

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Speaker 1: previoubly expected. I've heard from experts out there saying it's

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Speaker 1: priced too high. Ultimately, at the moment, will Deep seek

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Speaker 1: force open AI's own offering to get cheaper, Microsoft's offering

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Speaker 1: to get cheaper, and therefore it becomes more ubiquitous.

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Speaker 6: We will start using it more. But ultimately they get

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Speaker 6: more bang for the back in the long term.

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Speaker 2: Doesn't mean that these companies could potentially pull back some

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Speaker 2: of the capeck they've already announced this year.

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Speaker 1: I think that was interesting in the and we talked

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Speaker 1: about it when the numbers dropped. Amy Hoard the CFOs

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Speaker 1: talking about the discipline.

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Speaker 6: Now, last year we were not talking about discipline. We

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Speaker 6: were talking like.

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Speaker 1: Let's throw eighty billion dollars at this. We just heard

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Speaker 1: another half a trillion being thrown at it from Oracle

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Speaker 1: Soft Bank and open Ai. I think you'll start to

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Speaker 1: hear this. This is why spending. This is return on

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Speaker 1: AI spending.

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Speaker 2: Not quite a year of efficiency like we saw in

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Speaker 2: you know, twenty twenty three, but now discipline spending.

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Speaker 6: When it comes to com we're just spending wisely on

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Speaker 6: your data.

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Speaker 4: Just because you say it doesn't mean you're going to

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Speaker 4: spend it ultimately too.

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Speaker 3: I do want to point out service now reports an

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Speaker 3: additional three billion dollars for share a buyback with the stuff.

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Speaker 4: Yeah, but it's still down about nine percent here in

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Speaker 4: the aftermarket. But men Deep come.

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Speaker 3: Back in because we were talking about, you know, the

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Speaker 3: news we got this week from deep seek that the

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Speaker 3: beneficiary seemed to be the software software providers. Not every

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Speaker 3: software provider though, is the same, correct.

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Speaker 5: Well, I mean a company like Service now in theory,

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Speaker 5: should benefit from lower LLM costs. I mean, all the

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Speaker 5: software companies could arbitrage against the LM providers and say,

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Speaker 5: if I have a cheaper open source option, I'm going

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Speaker 5: to go with that because the quality of responses are

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Speaker 5: very similar. So from that perspective, I mean, the news

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Speaker 5: just came out, so obviously they didn't embrace open source before.

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Speaker 5: And now a lot will change in the next three

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Speaker 5: to six months, But for now, I think expectator to

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Speaker 5: Caroline's point, expectations are high this quarter and a lot

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Speaker 5: of these companies have touted AI agents in a big way,

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Speaker 5: so the street wants to see their revenue and probably

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Speaker 5: it's not showing up right now.

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Speaker 1: And I had a really interesting conversation with that expert

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Speaker 1: who's helping integrate generative AI into enterprise offerings.

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Speaker 6: And here's the gap.

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Speaker 7: Right.

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Speaker 6: We've been talking.

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Speaker 1: Deeply, exuberantly about how it's going to make our productivity

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Speaker 1: so much better. Ultimately, enterprises need to know that their

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Speaker 1: models work and they need to stress test them. They

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Speaker 1: need to have the right companies in there ensuring that well,

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Speaker 1: when you're saying it's going to get you a better

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Speaker 1: mortgage outcome, when you're looking at insurance inquiries, you're actually

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Speaker 1: getting the right output.

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Speaker 6: Companies are trying.

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Speaker 1: To integrate it, but they've got to do this with

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Speaker 1: some rules of the road, so it actually takes a

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Speaker 1: bit of time.

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Speaker 2: Okay, speaking of rules to the road, perhaps a good

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Speaker 2: segue to get to Tesla because shares are down about

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Speaker 2: two point seven percent right now. It seems, Caroline like

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Speaker 2: it was the adjusted EPs that came in shy of

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Speaker 2: estimates seventy three cents per share versus estimates of seventy

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Speaker 2: five cents per share. Is it about a lack of

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Speaker 2: efficiency on the supply chain, on the product line? What

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Speaker 2: is it?

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Speaker 1: Am they're saying they're not getting the manufacturing savings that

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Speaker 1: they wanted to see efficiency.

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Speaker 2: Have they tried the blockchain?

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Speaker 7: Yeah?

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Speaker 6: Have they tried a blockchain.

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Speaker 1: Have they tried just making everyone have to come back

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Speaker 1: into the office, but more I mean, you know it's

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Speaker 1: been on that for a long time.

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Speaker 6: But more affordable models is where it's at.

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Speaker 1: This is a company that is having to compete from

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Speaker 1: a price perspective in China in a big way. And look,

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Speaker 1: we saw deliveries did not live up to expectations. So

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Speaker 1: already they're not selling as money, they're having to reduce

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Speaker 1: the costs. It's interesting they're seeing the automotive gross margin

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Speaker 1: ex regulatory credits still at thirteen point six percent. This

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Speaker 1: is a company that basically makes an awful lot of

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Speaker 1: money that because other car manufacturers can't get the climate

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Speaker 1: initiatives out there quickly enough.

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Speaker 6: I wonder if that'll dial back.

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Speaker 1: But ultimately they did say they achieved record deliveries in

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Speaker 1: China in fourth quarter. I wonder how they manage to

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Speaker 1: be able to just keep on competing there.

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Speaker 5: And no mention of robot taxis. I mean, the big

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Speaker 5: bet was this administration should help expedite the rollout of

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Speaker 5: Tesla robot taxis that's what investors are betting.

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Speaker 2: The letter they did say this is going to be

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Speaker 2: the year of supervised fully self driving, but we're still

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Speaker 2: waiting to see what the guidances from the federal government.

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Speaker 1: The cybercab is on track for twenty twenty six, so

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Speaker 1: ultimately they're talking about still being wanting to.

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Speaker 6: Get that cybercab out there. In the meanwhile, we're having

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Speaker 6: to see.

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Speaker 1: Whether or that cheaper price point new vehicle will happen.

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Speaker 1: He's saying, new vehicles remain on track for the output

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Speaker 1: start in the first half.

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Speaker 6: When where how I.

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Speaker 4: Just want to update.

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Speaker 3: Meta shares are just down about five tenths in the

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Speaker 3: after hours, five tens of one percent.

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Speaker 4: Our Kurt Wagner and.

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Speaker 3: Our live blog says, the latest Meta or Facebook they

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Speaker 3: ever posted earnings is for sixteen pm. We have now

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Speaker 3: a new record because it's for twenty pm here on

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Speaker 3: this Wednesday. He says, in all seriousness, this is definitely unusual.

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Speaker 3: I've asked the company what is going on? Will report

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Speaker 3: back if I get any news. I was trying to

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Speaker 3: see if there was any interesting activity here in the

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Speaker 3: aftermarket ahead of the actual results. But again it's just

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Speaker 3: down a hair down about four tens of a percent,

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Speaker 3: but still waiting on Meta's results.

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Speaker 4: I don't know manty if you follow them, right, they're

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Speaker 4: usually up by now.

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Speaker 5: I mean it reminds me on when Nvidia, I think

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Speaker 5: it was a few quarters back they were delayed and

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Speaker 5: everyone was like, what's going on? And sometimes I think

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Speaker 5: it's one of those situations where yeah, there isn't much

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Speaker 5: to it.

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Speaker 2: It's just there is a delay and you just wait

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Speaker 2: it out.

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Speaker 5: But look, I think in the case of Meta, I mean,

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Speaker 5: there's so many things that I think investors are looking

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Speaker 5: forward to. Especially there was a number around Reality Laps

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Speaker 5: growing forty percent for twenty twenty four, right, I mean

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Speaker 5: you look at the census expectations for this quarter, it's

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Speaker 5: like three percent growth. Yeah, so I don't know how

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Speaker 5: they grew forty percent for the full year.

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Speaker 2: Caroline, come on in here. Is that? Is that because

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Speaker 2: the I don't know, the glasses exceeded expectations. Again, we're

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Speaker 2: still waiting for these numbers across Reality Lads a tiny,

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Speaker 2: tiny portion of the company's full revenue. I mean of

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Speaker 2: tiny fraction, but an area where they're investing a lot

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Speaker 2: and where they think there's a real future.

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Speaker 6: And people got very excited about the product. Did you

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Speaker 6: see how often Ed Ludlow has been wearing hiss. I've

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Speaker 6: heard they really did.

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Speaker 1: Blow people's minds as to how exciting the future could

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Speaker 1: be of just the integration within your everyday where suddenly,

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Speaker 1: you know, smart glasses became cool and thanks Raybound and

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Speaker 1: a large part of that.

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Speaker 2: But Google glasses calling. They're saying, hey, we had this

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Speaker 2: ten years ago, but it didn't stick, and what you want.

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Speaker 6: Is the zeitgeist.

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Speaker 1: Right, Sure, people might not buy that iteration, what about

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Speaker 1: the next iteration. What about the fact that this is

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Speaker 1: going to in some way be infused within your work

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Speaker 1: life environment as well, and suddenly you'll be able to

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Speaker 1: have forced meanes wherever you are, not just to I

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Speaker 1: think it suddenly just showed the power more than anything

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Speaker 1: of Mark Zuckerberg to interlace General to Bai everywhere. For me,

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Speaker 1: the big standout has been the fact that I do

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Speaker 1: use General to Bai within my Instagram.

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Speaker 2: What you do just out of curiosity my metter.

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Speaker 1: Ai psidekick and I ask it questions. I get it

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Speaker 1: to like design what one should wear for an event.

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Speaker 1: I give it pictures of my fridge and get it

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Speaker 1: to recommend what I should be.

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Speaker 6: Do you follow it?

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Speaker 4: Do you use it? I mean, do you like, take

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Speaker 4: these things and actually do something.

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Speaker 1: Yeah, yeah, yeah, definitely what they should cook sometimes the

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Speaker 1: fashion sense, I like, take a little.

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Speaker 2: But to be clear, you could also use chat gpt

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Speaker 2: from open Ai to do that or that.

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Speaker 1: I use what'sapp every day of my life to talk

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Speaker 1: with my family.

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Speaker 2: So I don't subscribe to the expensive versions of I

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Speaker 2: take the free version of not not for my personal

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Speaker 2: agent to you know, to get me a flight to wherever,

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Speaker 2: which I think is a really cool idea. And I

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Speaker 2: think that shows the promise of agents. And you know,

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Speaker 2: we hear salesforce talking about the promise of agents and

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Speaker 2: stuff like that. But are you able to do for

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Speaker 2: free with Lama what you could pay chat gpt to do?

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Speaker 2: Is that an issue?

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Speaker 1: I have to say personally, I'm not running the two

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Speaker 1: against each other, and I use chatchipt for other things.

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Speaker 1: I'm using chatchipt to articulate what my O pair because

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Speaker 1: we will have to rely while I'm at work on

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Speaker 1: wonderful people looking after your children, how her weak should look, and.

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Speaker 6: I just speak into it dictated.

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Speaker 1: So I'm using different things at different points, but for me,

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Speaker 1: I actually end up going towards the metal offerings A

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Speaker 1: bit more.

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Speaker 6: Just because they are here.

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Speaker 1: We're seeing interesting an agreement from the Wall Street Journal

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Speaker 1: talking about some Trump signing an agreement calling for Meta

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Speaker 1: to pay some element to settle a suit.

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Speaker 6: So maybe there's some breaking.

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Speaker 1: News there, But I am I am using Meta AI

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Speaker 1: just because it's already an app that I'm using when it's.

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Speaker 3: I just want to mention Microsoft is not down as

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Speaker 3: much as it was earlier. It's now down about three

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Speaker 3: quarters of one percentage point. Tesla is now down only

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Speaker 3: about nine tens of a percentage point. I want to

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Speaker 3: mention IBM because we are seeing this one rally in

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Speaker 3: the aftermarket following its earnings. This one's up about eight

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Speaker 3: percent here. IBM coming out with results kind of older tech,

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Speaker 3: if you will, but jumping after fiscal year revenue growth

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Speaker 3: outlook tops estimates. We mentioned service now, and we are

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Speaker 3: seeing that one move in a big way. We've seen

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Speaker 3: that move to the downside. Some concerns there. We do have,

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Speaker 3: as you said, that headline crossing from the Wall Street Journal,

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Speaker 3: Trump signs of settlement for Meta to pay twenty five

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Speaker 3: million dollars to settle a suit. So perhaps that is

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Speaker 3: why we might be waiting ultimately for Meta's results. Meta

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Speaker 3: in the aftermarket right now is just down about one

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Speaker 3: quarter of one percent. And I've been also looking at

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Speaker 3: the Nasdaq E Mini one hundred, Nasdaq one hundred E

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Speaker 3: mini futures pretty flat in the after market, and S

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Speaker 3: and P five hundred e mini futures they're down about

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Speaker 3: four tens of a percent, So just kind of rolling

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Speaker 3: everything together to see kind of market reaction.

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Speaker 2: In Tesla though, hire now by about one percent.

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Speaker 3: That's why I'm saying, it's like kind of fascinating to

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Speaker 3: see the bump up. You're right now up about one percent.

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Speaker 1: And I think what's interesting is remember in video you're

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Speaker 1: talking tim earlier about the hit and video took the

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Speaker 1: chairs a climbing now after hours because of Microsoft's long

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Speaker 1: term CAPEX commitment. So maybe even though we don't get

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Speaker 1: in video numbers until February the twenty sixth, Microsoft's already

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Speaker 1: coming out standing by its capital expenditure commitment. If we

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Speaker 1: get Meta committing to that sixty five billion dollars once

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Speaker 1: and again, maybe we do start to see in video

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Speaker 1: clowing back some of the loss that we've seen.

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Speaker 2: And a good reminder too that we still have a

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Speaker 2: lot of details that we're waiting on about deep Seek

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Speaker 2: and what exactly they were able to do with what.

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Speaker 6: So some investigations going on.

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Speaker 2: The investigation.

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Speaker 1: Microsoft got their ownings out on time and we're doing

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Speaker 1: an investigation.

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Speaker 2: Room of engineers reportedly, so I want to bring you

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Speaker 2: back in there.

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Speaker 3: Could it possibly be that there's a delay because of

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Speaker 3: this settlement and they want to kind of like roll

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Speaker 3: it all together.

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Speaker 5: That mountain looks too small to matter.

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Speaker 4: It doesn't matter.

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Speaker 2: Five million for Meta, it's like.

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Speaker 1: And that was under the over the Trump suspension to

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Speaker 1: the use of Facebook and its family of apps.

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Speaker 4: Yeah, I just think about the stories we've been putting out.

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Speaker 5: They're paying billion dollar fines in the EU, so this

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Speaker 5: is like a drop.

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Speaker 4: This is nothing.

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Speaker 3: I mean, it's kind of fascinating that to see that

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Speaker 3: we're just kind of waiting for.

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Speaker 1: Tesla's on time, on time, better is late what a

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Speaker 1: turnaround for and Test is now up.

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Speaker 3: About two point six percent in the aftermarket, So quite

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Speaker 3: a turn around here, wow.

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Speaker 1: I Yeah, it is notable metas delay and we have

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Speaker 1: got requests out for comment on what might be holding

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Speaker 1: them up. But this is I feel there's going to

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Speaker 1: be a lot of redrafting of messaging going on since Monday,

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Speaker 1: And look what of very difficult the week to have

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Speaker 1: your earnings on when you're trying to understand the competitive

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Speaker 1: threat of deep Seek to Alarma model, which are both

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Speaker 1: open source, but at the same time the way in

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Speaker 1: which it could enhance their products. Everyone read deep Seek

445
00:19:41,480 --> 00:19:44,359
Speaker 1: as a good thing for LLM, for Lama and open

446
00:19:44,359 --> 00:19:47,080
Speaker 1: source lms, but maybe there is a question of ultimately,

447
00:19:47,080 --> 00:19:50,360
Speaker 1: why should you be backing AI homegrown, open source versus

448
00:19:51,080 --> 00:19:52,120
Speaker 1: competing versus China.

449
00:19:52,119 --> 00:19:54,080
Speaker 3: I mean, men, Deep do you think that the narrative

450
00:19:54,240 --> 00:19:57,160
Speaker 3: like substantially should be different because of what we got

451
00:19:57,200 --> 00:19:59,760
Speaker 3: on Monday from deep Seek, Like the conversation that we

452
00:19:59,840 --> 00:20:02,320
Speaker 3: are having around AI in terms of the spend. Was

453
00:20:02,320 --> 00:20:03,639
Speaker 3: it smart for us to kind of all of a

454
00:20:03,680 --> 00:20:06,120
Speaker 3: sudden shift It felt like the narrative or time will

455
00:20:06,160 --> 00:20:08,840
Speaker 3: tell whether again with there's so many questions still about

456
00:20:08,840 --> 00:20:10,040
Speaker 3: the reality of what they did.

457
00:20:10,320 --> 00:20:12,800
Speaker 5: Yeah, I mean, look, last six months you've been talking

458
00:20:12,840 --> 00:20:16,639
Speaker 5: about scaling laws non stop. It's like everything is how

459
00:20:17,080 --> 00:20:19,200
Speaker 5: big are the data center is going to get? How

460
00:20:19,240 --> 00:20:23,040
Speaker 5: long will the scaling laws hold? So from that perspective,

461
00:20:23,119 --> 00:20:26,760
Speaker 5: I think this does put a question mark around the

462
00:20:26,800 --> 00:20:29,880
Speaker 5: scaling laws. You know, how big does the LLM need

463
00:20:29,920 --> 00:20:33,600
Speaker 5: to get to improve its reasoning? Well, a smaller LLM

464
00:20:33,680 --> 00:20:38,320
Speaker 5: can give you a similar reasoning as open AIE latest model.

465
00:20:38,400 --> 00:20:43,160
Speaker 5: And look, I think with llms, because it's so hard

466
00:20:43,200 --> 00:20:47,399
Speaker 5: to understand everything about how these llms are trained, the

467
00:20:47,520 --> 00:20:52,399
Speaker 5: data sources, the algorithmic improvements, it's still a black box.

468
00:20:52,440 --> 00:20:55,399
Speaker 5: I mean, things are getting better in terms of the transparency,

469
00:20:55,800 --> 00:20:59,640
Speaker 5: but in the end common people cannot interpret what's going

470
00:20:59,680 --> 00:21:02,879
Speaker 5: on in terms of building these llms, and it's really

471
00:21:02,960 --> 00:21:06,920
Speaker 5: hard to explain it to someone why an llm's quality

472
00:21:07,119 --> 00:21:11,080
Speaker 5: is better than the competing LLM. It's just almost impossible

473
00:21:11,119 --> 00:21:13,080
Speaker 5: because it's all vectorized map.

474
00:21:13,160 --> 00:21:15,840
Speaker 2: At the end of the day, do they become commodities?

475
00:21:15,880 --> 00:21:19,240
Speaker 6: Caroline, I think that has been the question for a while.

476
00:21:19,359 --> 00:21:24,600
Speaker 1: That will ultimately just move toggle between CHATCHBT, your meta offering,

477
00:21:24,640 --> 00:21:27,040
Speaker 1: what Anthropic has been up to. That doesn't mean that

478
00:21:27,080 --> 00:21:30,040
Speaker 1: you can't still see an awful lot of money having

479
00:21:30,080 --> 00:21:33,400
Speaker 1: to be invested in these latest and greatest underlying foundational models.

480
00:21:33,640 --> 00:21:37,560
Speaker 1: Whether eventually the money will accrue to the application layers,

481
00:21:37,600 --> 00:21:38,840
Speaker 1: to the software layer.

482
00:21:38,720 --> 00:21:40,520
Speaker 2: Well, I do think there's a compelling case for Google

483
00:21:40,520 --> 00:21:43,120
Speaker 2: to make that behind the scenes. If you're using an

484
00:21:43,119 --> 00:21:45,520
Speaker 2: AI agent and you ask it to do something complicated,

485
00:21:45,840 --> 00:21:48,800
Speaker 2: Google and actually Microsoft too with being has that search

486
00:21:48,880 --> 00:21:52,479
Speaker 2: engine built in that can actually do that stuff, and

487
00:21:52,600 --> 00:21:54,240
Speaker 2: perhaps they make money more.

488
00:21:54,160 --> 00:21:56,760
Speaker 6: Of integrated offering as well.

489
00:21:56,760 --> 00:21:58,760
Speaker 1: They have to have the foundational layer to then sell

490
00:21:58,800 --> 00:22:01,560
Speaker 1: you the software application as well. But would you rather

491
00:22:01,640 --> 00:22:04,280
Speaker 1: be a service now that just has the software margins

492
00:22:04,440 --> 00:22:07,080
Speaker 1: rather than having to do the underlying investment. What's been

493
00:22:07,080 --> 00:22:09,200
Speaker 1: so interesting has been that shift as well from investment

494
00:22:09,520 --> 00:22:11,440
Speaker 1: coming ultimately from private sources.

495
00:22:11,520 --> 00:22:14,080
Speaker 6: What we've seen with the announcement.

496
00:22:13,600 --> 00:22:16,760
Speaker 1: Of AI infrastructure money coming to the US is high

497
00:22:16,800 --> 00:22:20,240
Speaker 1: soft bank Oh thanks Ale, and the chips at like

498
00:22:20,240 --> 00:22:22,640
Speaker 1: nowhere to be seen for the last few weeks of late.

499
00:22:23,080 --> 00:22:25,879
Speaker 5: Now what happens to projects targeate, I mean the whole

500
00:22:26,000 --> 00:22:30,240
Speaker 5: timing of it, Meta raising their CAPEX projects target announcement

501
00:22:30,640 --> 00:22:32,679
Speaker 5: and then deep Sea coming out. Just think of the

502
00:22:32,720 --> 00:22:36,480
Speaker 5: sequence of events and they're not in sync with each other.

503
00:22:36,640 --> 00:22:39,760
Speaker 5: So that's where you know, if you're trying to follow

504
00:22:39,800 --> 00:22:42,320
Speaker 5: the big trend, it's not very clear what the big

505
00:22:42,320 --> 00:22:45,680
Speaker 5: trend is right now in terms of scaling versus you know,

506
00:22:45,800 --> 00:22:49,600
Speaker 5: how do you go about data center investments medium to

507
00:22:49,640 --> 00:22:50,240
Speaker 5: long term?

508
00:22:50,280 --> 00:22:54,560
Speaker 1: And do you buy the inference argument though that was

509
00:22:54,600 --> 00:22:56,920
Speaker 1: the argument of videos. You're still going to need all

510
00:22:56,920 --> 00:22:59,920
Speaker 1: of our very expensive GPUs for inference, and we're still

511
00:23:00,320 --> 00:23:04,480
Speaker 1: all ubiquitously using gender to AI more and more and more. Well,

512
00:23:04,560 --> 00:23:07,080
Speaker 1: that's when the Jevins paradox comes in that Satia wants

513
00:23:07,080 --> 00:23:09,560
Speaker 1: to learn to you more than the data centers with cloud.

514
00:23:09,400 --> 00:23:13,119
Speaker 5: Yeah, more than that. I think compute inherently is fungible.

515
00:23:13,400 --> 00:23:16,920
Speaker 5: So if I'm using you know, certain chips for training

516
00:23:16,960 --> 00:23:19,800
Speaker 5: now and I don't need to build a you know,

517
00:23:19,920 --> 00:23:23,520
Speaker 5: million chip cluster, then I can use some of that

518
00:23:23,600 --> 00:23:27,399
Speaker 5: compute for inferencing because it's the same GPU. So from

519
00:23:27,440 --> 00:23:30,679
Speaker 5: that perspective, I do buy that argument that if AI

520
00:23:30,880 --> 00:23:34,240
Speaker 5: is more pervasive and accessible, then I'll use more of

521
00:23:34,280 --> 00:23:37,679
Speaker 5: that chip capacity for inferencing because everyone realizes there is

522
00:23:37,880 --> 00:23:40,760
Speaker 5: ROI and you know, deploying the generator of AI.

523
00:23:40,880 --> 00:23:42,960
Speaker 3: I mean, this is the technological cycle at work, right,

524
00:23:43,000 --> 00:23:44,720
Speaker 3: I mean, stuff comes out of the gate initially, it

525
00:23:44,760 --> 00:23:47,160
Speaker 3: catches all of our tension. We've been obsessed with really

526
00:23:47,240 --> 00:23:49,600
Speaker 3: kind of a very few companies over the last couple

527
00:23:49,640 --> 00:23:51,560
Speaker 3: of years here. We are more than two years in

528
00:23:51,640 --> 00:23:55,040
Speaker 3: on this right, it makes sense, you guys, Caroline Mande,

529
00:23:55,160 --> 00:23:57,840
Speaker 3: that we're going to start seeing other companies come to

530
00:23:57,880 --> 00:23:58,400
Speaker 3: the forefront.

531
00:23:58,440 --> 00:24:00,439
Speaker 4: There's going to be some competition. The model might be

532
00:24:01,040 --> 00:24:02,200
Speaker 4: tweaked a little bit here.

533
00:24:02,280 --> 00:24:05,880
Speaker 5: Yeah, I mean, and look the commoditization. I do think

534
00:24:05,960 --> 00:24:10,119
Speaker 5: you know the modes around, Oh, you've used this LLLM

535
00:24:10,160 --> 00:24:13,680
Speaker 5: and you can never get out of that. It's so sticky.

536
00:24:14,280 --> 00:24:16,680
Speaker 5: I think that is going away because now you can

537
00:24:16,840 --> 00:24:20,760
Speaker 5: swap you know, API from one LLLM to another, and

538
00:24:20,840 --> 00:24:24,480
Speaker 5: that should be doable. And companies will arbitrage, you know,

539
00:24:24,600 --> 00:24:28,400
Speaker 5: against which is the cheapest model provider because it impacts

540
00:24:28,400 --> 00:24:30,600
Speaker 5: your margins. I mean, look at the scale of some

541
00:24:30,640 --> 00:24:34,320
Speaker 5: of these LM deployments. We're talking about billion users, so

542
00:24:34,440 --> 00:24:38,200
Speaker 5: billion users are using a generative AI query. That's all

543
00:24:38,280 --> 00:24:40,840
Speaker 5: API revenue that these companies are getting. And if I'm

544
00:24:40,840 --> 00:24:44,080
Speaker 5: paying the highest price per API, that's going to hurt

545
00:24:44,080 --> 00:24:45,960
Speaker 5: my margins. So I'm going to go with the cheapest

546
00:24:45,960 --> 00:24:46,960
Speaker 5: option that's out there.

547
00:24:47,400 --> 00:24:49,480
Speaker 3: I mean, Caroline, when you think about like the conversations

548
00:24:49,480 --> 00:24:51,680
Speaker 3: you have over and over, what changed so dramatically this week?

549
00:24:51,840 --> 00:24:53,680
Speaker 3: Is it just kind of a rethink of these long

550
00:24:54,000 --> 00:24:55,359
Speaker 3: held beliefs about AI.

551
00:24:55,280 --> 00:24:57,719
Speaker 1: And I think for lots of people it was felt

552
00:24:57,760 --> 00:25:01,640
Speaker 1: that people acted before or they really knew, so it's

553
00:25:01,800 --> 00:25:02,359
Speaker 1: just sell.

554
00:25:02,720 --> 00:25:03,840
Speaker 6: I've seen this headline.

555
00:25:03,920 --> 00:25:06,280
Speaker 1: I'm worried about the valuations of these companies anyway, and

556
00:25:06,359 --> 00:25:08,919
Speaker 1: video was trading at forty one times. We see generally

557
00:25:08,960 --> 00:25:12,479
Speaker 1: everyone elevated versus the Nasdaq get out then ask our questions.

558
00:25:12,600 --> 00:25:14,640
Speaker 1: People started to come back to software after they asked

559
00:25:14,680 --> 00:25:16,919
Speaker 1: those questions, and I thought, oh, maybe this could actually

560
00:25:17,200 --> 00:25:19,840
Speaker 1: change the game and make things even more margin rich

561
00:25:19,920 --> 00:25:22,320
Speaker 1: for these types of companies. But I think the question

562
00:25:22,440 --> 00:25:25,040
Speaker 1: is still out of ultimately, what access did they have

563
00:25:25,119 --> 00:25:28,879
Speaker 1: to end? In video, GPUs were ultimately they say that

564
00:25:28,880 --> 00:25:32,000
Speaker 1: they got them totally legitimately, and in video would say

565
00:25:32,000 --> 00:25:35,560
Speaker 1: the same. How much it is ultimately spark inferences the

566
00:25:35,640 --> 00:25:38,200
Speaker 1: use and what does it mean in terms of ultimate

567
00:25:38,240 --> 00:25:40,840
Speaker 1: and infrastructure investment. I think people for the short term,

568
00:25:40,880 --> 00:25:43,160
Speaker 1: most analysts I speak to say, we're misticking by it,

569
00:25:43,280 --> 00:25:44,760
Speaker 1: like we're not going to see a cap it's pulled

570
00:25:44,800 --> 00:25:45,760
Speaker 1: back anytime soon.

571
00:25:46,320 --> 00:25:48,160
Speaker 2: Interesting stuff. We're gonna have to wait also to hear

572
00:25:48,240 --> 00:25:51,639
Speaker 2: what David Sachs the ais are for the Trump administration

573
00:25:51,720 --> 00:25:52,680
Speaker 2: has to say, all.

574
00:25:52,640 --> 00:25:53,840
Speaker 4: Right, I think we're going to let you go.

575
00:25:54,000 --> 00:25:56,040
Speaker 3: I'm really fearful to do that in both of you,

576
00:25:56,160 --> 00:25:57,919
Speaker 3: because I know the minute you get out of your

577
00:25:58,000 --> 00:26:01,840
Speaker 3: chair and walk it out in our studio. All right,

578
00:26:01,840 --> 00:26:03,680
Speaker 3: But Mandy, we're going to let you go, and hopefully

579
00:26:03,720 --> 00:26:05,480
Speaker 3: we'll maybe even bring you back a little bit later on.

580
00:26:05,520 --> 00:26:09,240
Speaker 3: Mandy Seeing, of course, a key member of our technology

581
00:26:09,280 --> 00:26:11,680
Speaker 3: team at our Bloomberg Intelligence unit we.

582
00:26:11,680 --> 00:26:14,040
Speaker 4: Are waiting Meta results.

583
00:26:14,600 --> 00:26:16,399
Speaker 3: Also a key member of our technology team here at

584
00:26:16,400 --> 00:26:18,720
Speaker 3: Bloomberg News, of course, Caroline High So lucky for us,

585
00:26:18,960 --> 00:26:20,639
Speaker 3: she's going to stick around. One of the co hosts

586
00:26:20,920 --> 00:26:23,119
Speaker 3: of Bloomberg Technology. We do have another guest so that

587
00:26:23,119 --> 00:26:25,679
Speaker 3: we want to bring into the conversation who really follows

588
00:26:25,680 --> 00:26:27,720
Speaker 3: the tech sector very closely and invests in it.

589
00:26:27,920 --> 00:26:30,000
Speaker 2: Yeah, I want to bring in James Chalkmack. He's technology

590
00:26:30,000 --> 00:26:33,920
Speaker 2: analyst at Clockwise Capital. Clockwise Capital is the Core Equity

591
00:26:33,960 --> 00:26:37,320
Speaker 2: and Innovation ETF. The ticker is time. Biggest holdings are

592
00:26:37,320 --> 00:26:41,000
Speaker 2: the companies we're talking about Meta, Amazon, Microsoft, and Apple,

593
00:26:41,200 --> 00:26:44,480
Speaker 2: along with smaller companies including Palanteer, Spotify, and Netflix. The

594
00:26:44,520 --> 00:26:47,520
Speaker 2: ETF up about thirty five percent over the last year,

595
00:26:47,560 --> 00:26:49,879
Speaker 2: four percent year to date. So let's go through it

596
00:26:50,080 --> 00:26:53,240
Speaker 2: and bring in James. He joins us from Miami this afternoon. James,

597
00:26:53,320 --> 00:26:55,360
Speaker 2: good to have you as always with us. I want

598
00:26:55,359 --> 00:26:58,480
Speaker 2: to start with your impression of Microsoft shares following after

599
00:26:58,520 --> 00:27:01,280
Speaker 2: reporting slow in growth in the cloud unit. What sticks

600
00:27:01,320 --> 00:27:01,760
Speaker 2: out to you?

601
00:27:03,480 --> 00:27:05,560
Speaker 7: Yeah, the big thing there with Microsoft is that the

602
00:27:05,640 --> 00:27:07,800
Speaker 7: bogie was a couple of points higher than where they

603
00:27:07,840 --> 00:27:11,359
Speaker 7: reported on Azure. The street was looking for around thirty

604
00:27:11,359 --> 00:27:13,800
Speaker 7: three thirty four percent growth to keep the momentum in

605
00:27:13,800 --> 00:27:16,680
Speaker 7: the stock going. They posted around thirty one thirty two,

606
00:27:17,359 --> 00:27:19,480
Speaker 7: so it was a couple of points light. But the

607
00:27:19,520 --> 00:27:22,600
Speaker 7: main thing is that the undercurrent the trends that you're

608
00:27:22,600 --> 00:27:25,879
Speaker 7: seeing in productivity and the shift to the cloud and

609
00:27:25,920 --> 00:27:30,240
Speaker 7: AI offerings continues. You know, you're still talking about three

610
00:27:30,280 --> 00:27:33,639
Speaker 7: handle on that growth rate. So we'll see what they

611
00:27:33,680 --> 00:27:36,000
Speaker 7: say on the call. As far as Capex is concerned,

612
00:27:36,040 --> 00:27:37,960
Speaker 7: we do think that's going to start to come down

613
00:27:37,960 --> 00:27:42,040
Speaker 7: here as we look into twenty twenty five. So I

614
00:27:42,119 --> 00:27:44,159
Speaker 7: think I think it's gonna be all right. You know,

615
00:27:44,200 --> 00:27:47,080
Speaker 7: we hold a position in it. We are underweight relative

616
00:27:47,080 --> 00:27:50,560
Speaker 7: to the index for this very reason because though the

617
00:27:50,720 --> 00:27:54,160
Speaker 7: run up, but overall, I think everything's okay with Microsoft.

618
00:27:54,240 --> 00:27:56,080
Speaker 1: I'm going to jump in because we are getting Amy

619
00:27:56,080 --> 00:27:58,760
Speaker 1: Hood the CFO giving an interview with our own Bloomberg

620
00:27:58,800 --> 00:28:00,639
Speaker 1: reporters saying that they.

621
00:28:00,240 --> 00:28:02,360
Speaker 6: Constrained in cloud capacity.

622
00:28:02,480 --> 00:28:05,359
Speaker 1: Remember we got that sort of shop move that open

623
00:28:05,400 --> 00:28:08,040
Speaker 1: ai is going to be building out AI infrastructure with Oracle.

624
00:28:08,080 --> 00:28:09,720
Speaker 1: Of course, they signed a deal with Oracle in the

625
00:28:09,760 --> 00:28:13,120
Speaker 1: summer because Microsoft just can't build them quickly enough. Talking

626
00:28:13,160 --> 00:28:16,280
Speaker 1: about the bookings rising sixty seven percent partly due to

627
00:28:16,320 --> 00:28:19,439
Speaker 1: the open Ai commitments and commercial bookings were better than

628
00:28:19,440 --> 00:28:21,480
Speaker 1: they forecast, they're still trying to talk about how much

629
00:28:21,680 --> 00:28:24,640
Speaker 1: more percentage point add ai is giving.

630
00:28:24,400 --> 00:28:26,520
Speaker 6: Them to as you're more broadly.

631
00:28:26,280 --> 00:28:29,639
Speaker 3: All right, so James so remains constrained in cloud capacity

632
00:28:29,720 --> 00:28:31,320
Speaker 3: from the Microsoft CEO.

633
00:28:31,520 --> 00:28:32,359
Speaker 4: What's your read on that?

634
00:28:34,480 --> 00:28:36,280
Speaker 7: Yeah, I mean they're going to have to keep building.

635
00:28:36,560 --> 00:28:40,080
Speaker 7: I'm not suggesting that capex needs to stop. It's more

636
00:28:40,240 --> 00:28:42,880
Speaker 7: just what is the growth rate of that spent. You know,

637
00:28:42,920 --> 00:28:45,960
Speaker 7: you saw a massive investment tiers in twenty twenty three,

638
00:28:46,080 --> 00:28:49,920
Speaker 7: twenty twenty four, and we think that that sprend will

639
00:28:49,960 --> 00:28:51,800
Speaker 7: be growing at a slower clip.

640
00:28:52,160 --> 00:28:55,040
Speaker 2: Do you change in turn will help. Sorry, James, do

641
00:28:55,400 --> 00:28:58,200
Speaker 2: you change your your holdings? Do you sell Microsoft?

642
00:29:00,040 --> 00:29:04,400
Speaker 7: Actually trimmed Microsoft into the quarter today. You know, we're

643
00:29:04,440 --> 00:29:06,800
Speaker 7: now at three percent weight. It's around eight percent in

644
00:29:06,840 --> 00:29:11,000
Speaker 7: the in the NAVASDAK, so we are underweight there. But

645
00:29:11,440 --> 00:29:13,560
Speaker 7: I would say, you know, we.

646
00:29:13,600 --> 00:29:14,480
Speaker 2: Still want to hold it.

647
00:29:14,520 --> 00:29:16,240
Speaker 7: You know, you still want to be there. The company

648
00:29:16,320 --> 00:29:19,240
Speaker 7: is incredibly important, but at the same time, we think

649
00:29:19,240 --> 00:29:22,600
Speaker 7: that there's better opportunity elsewhere with companies that offer and

650
00:29:22,640 --> 00:29:24,080
Speaker 7: stocks that offer better convexity.

651
00:29:24,160 --> 00:29:25,920
Speaker 2: Okay, so where does that money go? You trimmed your

652
00:29:25,920 --> 00:29:28,080
Speaker 2: holding in Microsoft, where are you spending it? What are

653
00:29:28,080 --> 00:29:29,480
Speaker 2: you buying?

654
00:29:30,400 --> 00:29:33,120
Speaker 7: So we're looking at a lot of software names right now.

655
00:29:33,240 --> 00:29:35,800
Speaker 7: You know, with the disruption in the market that was

656
00:29:35,840 --> 00:29:37,600
Speaker 7: caused by deep Seek, I don't think you can take

657
00:29:37,640 --> 00:29:40,800
Speaker 7: that lightly. I think that you have to re examine

658
00:29:41,280 --> 00:29:45,560
Speaker 7: kind of all of your assumptions top down. You know,

659
00:29:45,680 --> 00:29:48,760
Speaker 7: from that, we we did cut Nividia before the market

660
00:29:48,800 --> 00:29:52,480
Speaker 7: opened on Monday and cut that exposure, and we've been

661
00:29:52,560 --> 00:29:56,720
Speaker 7: rotating to software names. We picked up Data Dog for example.

662
00:29:57,840 --> 00:30:00,480
Speaker 7: You know, we think that race will continue to uh

663
00:30:00,760 --> 00:30:01,440
Speaker 7: trend lower.

664
00:30:02,640 --> 00:30:02,800
Speaker 3: Uh.

665
00:30:02,920 --> 00:30:05,640
Speaker 7: You know this year obviously two estimates baked in, but

666
00:30:05,760 --> 00:30:08,160
Speaker 7: I think that that trend will help a company like

667
00:30:08,560 --> 00:30:12,360
Speaker 7: an I'll start, you know, we continue to like Spotify.

668
00:30:13,080 --> 00:30:16,000
Speaker 7: We actually grossed up our metaposition heading into the quarter,

669
00:30:17,080 --> 00:30:18,680
Speaker 7: so we'll see how that plays out. I don't know

670
00:30:18,680 --> 00:30:19,880
Speaker 7: if the numbers are out yet.

671
00:30:20,080 --> 00:30:22,240
Speaker 4: No, we're still we're still awaiting meta.

672
00:30:22,280 --> 00:30:25,520
Speaker 3: I want to ask you something though, from our BI team,

673
00:30:25,560 --> 00:30:29,000
Speaker 3: our Ana Agrana writing about Microsoft and says Microsoft's close

674
00:30:29,040 --> 00:30:32,520
Speaker 3: relationship with open AI makes it better position than most

675
00:30:32,560 --> 00:30:36,360
Speaker 3: of its software arrivals to capitalize that increased generative AI spending.

676
00:30:37,320 --> 00:30:38,040
Speaker 4: You agree with that.

677
00:30:38,200 --> 00:30:39,680
Speaker 3: I mean they're you know, they know a little bit

678
00:30:40,080 --> 00:30:41,880
Speaker 3: about software certainly Microsoft.

679
00:30:42,080 --> 00:30:45,760
Speaker 7: Yeah, I'm not sure about the health of that relationship.

680
00:30:45,840 --> 00:30:46,640
Speaker 7: To be honest with you.

681
00:30:47,280 --> 00:30:48,240
Speaker 2: Why so.

682
00:30:50,280 --> 00:30:53,920
Speaker 7: Well, I think that you know, deep seek certainly changes

683
00:30:53,920 --> 00:30:56,280
Speaker 7: the game a little bit. I think that they'll increasingly

684
00:30:56,320 --> 00:31:01,360
Speaker 7: have less reliance on on open AI and and as

685
00:31:01,400 --> 00:31:03,600
Speaker 7: their costs come down, they'll continue to be able to

686
00:31:04,360 --> 00:31:08,160
Speaker 7: you know, drive the inference and all the AI tools

687
00:31:08,200 --> 00:31:14,040
Speaker 7: for their customers. So I'm not sure exactly how healthy

688
00:31:14,080 --> 00:31:17,120
Speaker 7: that relationship is or how it will lay out. But

689
00:31:17,240 --> 00:31:20,280
Speaker 7: at the end of the day, you know, Microsoft continues

690
00:31:20,320 --> 00:31:24,160
Speaker 7: to be well positioned exsllically, I would say following Deep Seek,

691
00:31:24,160 --> 00:31:29,560
Speaker 7: we came away in incrementally positive on meta on Microsoft

692
00:31:30,360 --> 00:31:34,520
Speaker 7: and Amazon. So those are the three that we like

693
00:31:34,720 --> 00:31:38,000
Speaker 7: following that news, and then we became incrementally negative on Nividia.

694
00:31:38,040 --> 00:31:39,000
Speaker 4: All right, hang on for a second.

695
00:31:39,000 --> 00:31:41,320
Speaker 3: We're talking with James CHOCKMOG partner and tech analyst Everrett

696
00:31:41,360 --> 00:31:44,480
Speaker 3: clockwise Capital Caroline Hyde, co host of Bloomberg Technology, also

697
00:31:44,480 --> 00:31:47,160
Speaker 3: in studio with us and just walking in our own

698
00:31:47,000 --> 00:31:49,719
Speaker 3: anarag Rana. He is with our technology team with our

699
00:31:49,720 --> 00:31:54,360
Speaker 3: Bloomberg Intelligence unit. He's a senior industry analyst writing. I

700
00:31:54,400 --> 00:31:57,480
Speaker 3: am reading from the research he just put out on Microsoft.

701
00:31:58,120 --> 00:32:00,680
Speaker 3: Microsoft now on AROG just down that eight tons of

702
00:32:00,680 --> 00:32:02,760
Speaker 3: a percent, so it's definitely come off the lows that

703
00:32:02,800 --> 00:32:04,360
Speaker 3: we saw earlier in the aftermarket.

704
00:32:04,440 --> 00:32:06,440
Speaker 4: So far tell us what we need to know.

705
00:32:06,960 --> 00:32:09,240
Speaker 8: Yeah, it's all the guidance on the conference call. We

706
00:32:09,280 --> 00:32:12,239
Speaker 8: want to hear that that AZ your growth is going

707
00:32:12,280 --> 00:32:14,800
Speaker 8: to pick up over the next twelve months. And I

708
00:32:14,800 --> 00:32:17,520
Speaker 8: think that's really the biggest thing that we see now,

709
00:32:17,520 --> 00:32:20,400
Speaker 8: that's assuming all the investments they have made in the

710
00:32:20,920 --> 00:32:23,960
Speaker 8: data center side. Is picking up because I just saw

711
00:32:23,960 --> 00:32:26,280
Speaker 8: the news go by what the CFO is saying that

712
00:32:26,320 --> 00:32:30,040
Speaker 8: they're still supply constrained. Now, the supply constraint doesn't mean

713
00:32:30,080 --> 00:32:32,920
Speaker 8: it had an impact on the current quarter growth, which is,

714
00:32:33,160 --> 00:32:35,320
Speaker 8: you know, which was below the thirty one thirty two

715
00:32:35,360 --> 00:32:37,800
Speaker 8: that they gave, or will it impact in the next quarter.

716
00:32:37,840 --> 00:32:39,680
Speaker 8: I think that's the single biggest question right now.

717
00:32:39,760 --> 00:32:43,280
Speaker 2: So is it fair to say this is totally supply side.

718
00:32:43,000 --> 00:32:46,560
Speaker 1: And japin because we do have meta finalite please, And

719
00:32:46,600 --> 00:32:49,480
Speaker 1: the fourth quarter revenue is beating expectations. Forty eight point

720
00:32:49,520 --> 00:32:52,440
Speaker 1: three to nine billion is coming for fourth quarter, it

721
00:32:52,480 --> 00:32:54,760
Speaker 1: was expected to be forty six point nine to eight billion,

722
00:32:54,760 --> 00:32:56,400
Speaker 1: and they're pushing us forward to a guide of the

723
00:32:56,400 --> 00:32:58,120
Speaker 1: first quarter to be thirty nine and a half to

724
00:32:58,160 --> 00:33:01,800
Speaker 1: forty one point eight billion. That slightly shy of the

725
00:33:01,840 --> 00:33:05,080
Speaker 1: midpoint where the expectations were for forty one point six billion.

726
00:33:05,160 --> 00:33:06,600
Speaker 6: So forecast a little bit light.

727
00:33:06,920 --> 00:33:09,680
Speaker 1: Fourth quarter at beats on Family of App revenue doing well.

728
00:33:09,800 --> 00:33:13,920
Speaker 1: They're seeing Reality Labs operating loss of almost five billion,

729
00:33:13,960 --> 00:33:16,080
Speaker 1: but the estimate was free for more than that, so

730
00:33:16,120 --> 00:33:18,480
Speaker 1: I think you are seeing perhaps a slightly shy forecast,

731
00:33:18,480 --> 00:33:20,880
Speaker 1: but they're seeing first quarter revenue of thirty nine and

732
00:33:20,920 --> 00:33:22,680
Speaker 1: a half to forty one point eight billion, and the

733
00:33:22,720 --> 00:33:24,760
Speaker 1: market wanted forty one point seven billion.

734
00:33:24,800 --> 00:33:25,680
Speaker 4: Stack bouncing around.

735
00:33:25,720 --> 00:33:27,840
Speaker 3: It was down five percent, it's now down about three

736
00:33:27,880 --> 00:33:29,960
Speaker 3: point eight percent. Now it's down about five percent. It

737
00:33:30,000 --> 00:33:33,520
Speaker 3: is bouncing around. Also some commentary in terms of the capex.

738
00:33:33,560 --> 00:33:36,800
Speaker 3: We anticipate our full year twenty twenty five capital expenditures

739
00:33:36,800 --> 00:33:39,120
Speaker 3: will be in the range of sixty to sixty five

740
00:33:39,160 --> 00:33:42,000
Speaker 3: billion dollars, So a little bit more about that, which

741
00:33:42,000 --> 00:33:43,560
Speaker 3: we just got news last week.

742
00:33:43,680 --> 00:33:45,800
Speaker 2: The company also says we're not providing a full year

743
00:33:45,800 --> 00:33:49,040
Speaker 2: twenty twenty five revenue outlook. Is that a surprise to you, Caroline.

744
00:33:49,120 --> 00:33:51,360
Speaker 1: Yeah, Usually they are able to give clarity, And it's

745
00:33:51,400 --> 00:33:54,480
Speaker 1: interesting that they're giving so much clarity on their capital expenditure,

746
00:33:54,760 --> 00:33:58,120
Speaker 1: perhaps not clarity on forward revenue at the moment. Is

747
00:33:58,160 --> 00:33:59,640
Speaker 1: that because they think it's just going to go through

748
00:33:59,680 --> 00:34:02,680
Speaker 1: the room. Is that because they do feel that they

749
00:34:02,720 --> 00:34:06,520
Speaker 1: can't give as much forward looking guidance at the moment.

750
00:34:06,960 --> 00:34:08,200
Speaker 6: But whether it's an.

751
00:34:08,160 --> 00:34:11,120
Speaker 1: FX perspective, cost and expenses, they're still dictating. But I'm

752
00:34:11,200 --> 00:34:13,920
Speaker 1: just scrolling through the CFO and they expect first call

753
00:34:13,960 --> 00:34:17,040
Speaker 1: to twenty five total revenue to be in that range,

754
00:34:17,120 --> 00:34:20,360
Speaker 1: which reflects eight to fifteen percent year over year growth

755
00:34:20,600 --> 00:34:23,480
Speaker 1: or eleven to eighteen percent on a constant currency basis.

756
00:34:23,480 --> 00:34:25,759
Speaker 1: But we are not providing fully a twenty twenty five

757
00:34:25,840 --> 00:34:28,359
Speaker 1: revenue outlook. We expect the investments we are making in

758
00:34:28,400 --> 00:34:31,080
Speaker 1: our core business this year will give us an opportunity

759
00:34:31,120 --> 00:34:34,640
Speaker 1: to continue delivering strong revenue growth through twenty twenty five.

760
00:34:34,600 --> 00:34:37,520
Speaker 3: Also saying the regulatory landscape in the European Union the

761
00:34:37,600 --> 00:34:39,960
Speaker 3: United States could impact business. We do see the stock

762
00:34:40,320 --> 00:34:43,160
Speaker 3: now just down about one percent. Again, the key that

763
00:34:43,200 --> 00:34:45,680
Speaker 3: everybody seems to be focusing on is that first quarter

764
00:34:45,680 --> 00:34:49,040
Speaker 3: sales forecast trailing at the midpoint, also saying fiscal year

765
00:34:49,080 --> 00:34:53,120
Speaker 3: depreciation expends about two point nine billion dollars less than before,

766
00:34:53,360 --> 00:34:55,719
Speaker 3: again bouncing around big time in the aftermark.

767
00:34:55,840 --> 00:34:57,640
Speaker 2: Yeah, I want to draw your attention to what's going

768
00:34:57,680 --> 00:35:01,000
Speaker 2: on with Reality Labs, the company, saying that revenue coming

769
00:35:01,040 --> 00:35:03,160
Speaker 2: in at one point oh eight billion dollars, shy of

770
00:35:03,239 --> 00:35:06,000
Speaker 2: estimates of one point one to one billion dollars. I

771
00:35:06,040 --> 00:35:07,719
Speaker 2: don't want to say there was a whisper number ahead

772
00:35:07,719 --> 00:35:11,080
Speaker 2: of this Caroline, but folks were bullish on Reality Labs

773
00:35:11,120 --> 00:35:13,040
Speaker 2: going into this. There was that report from Insider that

774
00:35:13,080 --> 00:35:15,960
Speaker 2: came out earlier this week that talked about growth at

775
00:35:15,960 --> 00:35:18,439
Speaker 2: growth in that unit. How are you, again, a very

776
00:35:18,480 --> 00:35:21,640
Speaker 2: small portion but a very important part of the company,

777
00:35:21,880 --> 00:35:23,120
Speaker 2: How are you looking into that number?

778
00:35:23,560 --> 00:35:27,280
Speaker 6: Yeah, I do think that overall the losses are big.

779
00:35:28,160 --> 00:35:29,440
Speaker 2: So you think the losses should be more of a

780
00:35:29,440 --> 00:35:30,480
Speaker 2: focus than the revenue.

781
00:35:30,680 --> 00:35:34,160
Speaker 1: Well, I think revenue one point zero eight is slightly

782
00:35:34,239 --> 00:35:36,759
Speaker 1: less than anticipated, but at least their operating loss is

783
00:35:36,760 --> 00:35:39,120
Speaker 1: slightly less than expected. But I think there's going to

784
00:35:39,120 --> 00:35:41,960
Speaker 1: be a lot of digestion of restructuring that's currently going

785
00:35:42,000 --> 00:35:43,760
Speaker 1: on in that business, and the fact that they're shifting

786
00:35:44,000 --> 00:35:46,160
Speaker 1: over to the overall unit COO and they're putting up

787
00:35:46,200 --> 00:35:49,520
Speaker 1: some operational changes at play. But how much is Mark

788
00:35:49,680 --> 00:35:52,000
Speaker 1: Zuckerberg going to speak to his commitment to this part

789
00:35:52,040 --> 00:35:54,000
Speaker 1: of the business, how much he wants to invest in

790
00:35:54,040 --> 00:35:57,279
Speaker 1: Reality Labs, how much of that sixty five billion dollar

791
00:35:57,400 --> 00:36:00,319
Speaker 1: up to capex in AI is ultimately going to today

792
00:36:00,400 --> 00:36:01,359
Speaker 1: it's a products.

793
00:36:01,000 --> 00:36:03,480
Speaker 4: All right, We're going to keep watching and reporting on Meta.

794
00:36:03,520 --> 00:36:06,960
Speaker 3: As we mentioned, stock is bopping around here in the aftermarkets,

795
00:36:07,680 --> 00:36:10,600
Speaker 3: really a focus on the outlook. But it's right now

796
00:36:10,640 --> 00:36:13,000
Speaker 3: we're looking at just a slight move to the upside

797
00:36:13,040 --> 00:36:14,920
Speaker 3: of about one quarter one percent. I want to go

798
00:36:15,000 --> 00:36:17,799
Speaker 3: back to Microsoft for just a moment because we have

799
00:36:17,800 --> 00:36:20,319
Speaker 3: Anna rag Rana in here, another big one after the

800
00:36:20,360 --> 00:36:22,560
Speaker 3: close which has been bouncing around to you, it's now

801
00:36:22,560 --> 00:36:23,560
Speaker 3: only down about eight.

802
00:36:23,400 --> 00:36:24,600
Speaker 4: Tens of one percent.

803
00:36:24,880 --> 00:36:28,080
Speaker 3: The Bloomberg audience thinking about these earnings, the crazy week

804
00:36:28,120 --> 00:36:30,439
Speaker 3: that's been in the tech community around AI.

805
00:36:31,480 --> 00:36:33,319
Speaker 4: What to be top of mind was top of mind

806
00:36:33,320 --> 00:36:33,640
Speaker 4: for you?

807
00:36:34,200 --> 00:36:36,960
Speaker 8: I think the biggest question is, you know, they have

808
00:36:37,000 --> 00:36:40,040
Speaker 8: a commercial booking number that just you know, was absolutely

809
00:36:40,080 --> 00:36:44,000
Speaker 8: spectacular and it was driven by Azure commitments and the

810
00:36:44,040 --> 00:36:46,320
Speaker 8: opening eye work that they are getting. But the question

811
00:36:46,440 --> 00:36:48,359
Speaker 8: is do you can you fulfill that demand or you're

812
00:36:48,360 --> 00:36:50,640
Speaker 8: going to go to third party providers to take care

813
00:36:50,680 --> 00:36:53,080
Speaker 8: of it? And that's really what it is. I mean, frankly,

814
00:36:53,160 --> 00:36:56,200
Speaker 8: at this point, more color in that, you know, the

815
00:36:56,200 --> 00:36:59,680
Speaker 8: big commercial booking number would be helpful. And also about

816
00:36:59,760 --> 00:37:03,440
Speaker 8: what what does Microsoft CEO think about all the things

817
00:37:03,440 --> 00:37:06,600
Speaker 8: that are happening with deep seek, because he did tweet

818
00:37:06,680 --> 00:37:09,120
Speaker 8: something very interesting that you know, if the costco goes down,

819
00:37:09,160 --> 00:37:12,000
Speaker 8: the adoption rate improves, which is good. But at the

820
00:37:12,040 --> 00:37:15,600
Speaker 8: same time, you know he has a very strong partnership

821
00:37:15,600 --> 00:37:18,719
Speaker 8: with Opening Eye right another, So there's a lot. I

822
00:37:18,760 --> 00:37:23,000
Speaker 8: think we will learn about the tech landscape in general

823
00:37:23,040 --> 00:37:26,920
Speaker 8: from him, not just about Microsoft's clouds numbers. Now, frankly speaking,

824
00:37:27,160 --> 00:37:29,440
Speaker 8: let's say, for the sake of argument, that they do

825
00:37:29,560 --> 00:37:32,640
Speaker 8: misguidance for three Q. I think people will still give

826
00:37:32,680 --> 00:37:34,560
Speaker 8: them a pass over the next several days. May not

827
00:37:34,560 --> 00:37:37,120
Speaker 8: give them a pass tomorrow because the bookings number is

828
00:37:37,160 --> 00:37:37,640
Speaker 8: so strong.

829
00:37:37,920 --> 00:37:40,960
Speaker 3: Another headline of Microsoft to add jobs and infrastructure, jen

830
00:37:41,000 --> 00:37:42,320
Speaker 3: Ai and reality labs.

831
00:37:42,360 --> 00:37:43,480
Speaker 2: So that's matter right.

832
00:37:43,560 --> 00:37:47,719
Speaker 3: Oh did I say, oh Microsoft, they must have made

833
00:37:47,719 --> 00:37:48,200
Speaker 3: a mistake.

834
00:37:48,400 --> 00:37:49,920
Speaker 4: Okay, so there is a headline.

835
00:37:50,040 --> 00:37:53,319
Speaker 2: We will we are going to keep covering that this

836
00:37:53,400 --> 00:37:56,480
Speaker 2: is coming fast and furious. I do want to do

837
00:37:56,560 --> 00:37:58,759
Speaker 2: a big thank you to Anna rog Rana for joining us.

838
00:37:58,880 --> 00:38:01,239
Speaker 2: He is going to go off and listen to more

839
00:38:01,280 --> 00:38:03,879
Speaker 2: of the call and as well as have more notes

840
00:38:03,880 --> 00:38:06,600
Speaker 2: out for Bloomberg Intelligence. I'm putting pressure on you, unfortunately,

841
00:38:06,640 --> 00:38:09,320
Speaker 2: I'm sorry. Thank you for stopping by usually in Chicago

842
00:38:09,560 --> 00:38:10,960
Speaker 2: joining us here. I do want to get back to

843
00:38:11,000 --> 00:38:13,360
Speaker 2: James Chockmack he's technology correction.

844
00:38:13,040 --> 00:38:14,960
Speaker 4: META, which makes sense because of Reality Lab.

845
00:38:14,880 --> 00:38:18,400
Speaker 2: Technology analyst at Clockwise Capital. We gave you a little break, James,

846
00:38:18,400 --> 00:38:21,839
Speaker 2: to jump in and look at those META numbers as

847
00:38:21,840 --> 00:38:25,240
Speaker 2: they were breaking just past four thirty five. What sticks

848
00:38:25,239 --> 00:38:25,640
Speaker 2: out to you?

849
00:38:27,280 --> 00:38:28,799
Speaker 7: Yeah, I mean the big thing is the first quarter

850
00:38:28,920 --> 00:38:31,560
Speaker 7: guide coming in a touch light. But the fourth quarter

851
00:38:31,600 --> 00:38:35,839
Speaker 7: itself was solid pretty much across the board. So we'll

852
00:38:35,840 --> 00:38:39,520
Speaker 7: have to decipher what exactly is going on in the

853
00:38:39,560 --> 00:38:44,400
Speaker 7: first quarter guide on the call. But as it stands,

854
00:38:44,440 --> 00:38:46,640
Speaker 7: if you look at four Q in a vacuum, you know,

855
00:38:46,680 --> 00:38:50,520
Speaker 7: it seems like it's all systems go. But I just

856
00:38:50,520 --> 00:38:51,239
Speaker 7: got to drill down.

857
00:38:51,120 --> 00:38:53,040
Speaker 4: A little bit more, all right, we want to get.

858
00:38:53,080 --> 00:38:55,200
Speaker 7: Why I think this stock is bouncing around so much.

859
00:38:55,320 --> 00:38:56,680
Speaker 7: Down five to three.

860
00:38:56,840 --> 00:38:57,759
Speaker 4: Everything's bouncing around.

861
00:38:57,840 --> 00:38:59,600
Speaker 3: Meta is now down about two tents of a verse.

862
00:38:59,640 --> 00:39:01,839
Speaker 3: That man keep saying, who follows metaphor us here at

863
00:39:01,840 --> 00:39:02,720
Speaker 3: our Bloomberg.

864
00:39:02,280 --> 00:39:03,800
Speaker 2: Intelligence giving them a workout today.

865
00:39:04,719 --> 00:39:07,359
Speaker 4: Get your steps in, buddy, get your steps in. What's

866
00:39:07,400 --> 00:39:08,840
Speaker 4: your reaction to the results?

867
00:39:08,960 --> 00:39:11,920
Speaker 5: Well, so one is obviously the guide for one Q

868
00:39:12,680 --> 00:39:16,000
Speaker 5: is lower than consensus. The big number that sticks out

869
00:39:16,040 --> 00:39:19,000
Speaker 5: to me is the total expense guide of one hundred

870
00:39:19,080 --> 00:39:22,760
Speaker 5: and fourteen two hundred and nineteen billion. That is almost

871
00:39:22,920 --> 00:39:27,439
Speaker 5: you know, eight billion higher than the consensus. So what

872
00:39:27,480 --> 00:39:30,759
Speaker 5: that tells you is the gross margins are going down

873
00:39:31,560 --> 00:39:35,880
Speaker 5: and plus the depreciation costs, the costs that they are

874
00:39:35,920 --> 00:39:39,279
Speaker 5: spending on data centers, they have to depreciate those servers, right,

875
00:39:39,719 --> 00:39:41,719
Speaker 5: that's going to eat into the margins. So we are

876
00:39:41,760 --> 00:39:45,360
Speaker 5: talking about at least a four to five percent margin

877
00:39:45,480 --> 00:39:50,040
Speaker 5: impact for twenty twenty five just from the data center costs,

878
00:39:50,120 --> 00:39:53,280
Speaker 5: the depreciation costs, and so clearly there is a gross

879
00:39:53,320 --> 00:39:59,360
Speaker 5: margin degradation happening here and the revenue growth is decelerating,

880
00:39:59,560 --> 00:40:01,800
Speaker 5: which is what we are seeing in one queue. The

881
00:40:01,880 --> 00:40:04,840
Speaker 5: Kapex guide is what they gave you know, on Friday,

882
00:40:05,000 --> 00:40:08,000
Speaker 5: so no change in that, but clearly the data center

883
00:40:08,040 --> 00:40:09,719
Speaker 5: expenses are eating into the.

884
00:40:09,680 --> 00:40:12,000
Speaker 3: Margins, which is something Gina Martin Adams has said, watch

885
00:40:12,040 --> 00:40:14,160
Speaker 3: with all of the companies reporting, but the tech guys

886
00:40:14,880 --> 00:40:17,560
Speaker 3: as well in terms of margins and seeing some pressure

887
00:40:17,600 --> 00:40:18,000
Speaker 3: on margins.

888
00:40:18,280 --> 00:40:20,759
Speaker 5: We seem to be the case with Microsoft there. So

889
00:40:20,880 --> 00:40:25,040
Speaker 5: that's the surprise here that Microsoft didn't call out, you know,

890
00:40:25,200 --> 00:40:29,040
Speaker 5: that kind of a margin impact from depreciation expenses in

891
00:40:29,080 --> 00:40:31,720
Speaker 5: their quarter, at least from the print that I saw,

892
00:40:32,360 --> 00:40:34,640
Speaker 5: But clearly it is having an impact on matter.

893
00:40:34,680 --> 00:40:38,120
Speaker 1: When you dig into what the CFO has been saying

894
00:40:38,200 --> 00:40:41,640
Speaker 1: as well, and ultimately she's talking about how the single

895
00:40:41,719 --> 00:40:43,960
Speaker 1: largest driver of their expense growth that you speak to

896
00:40:44,080 --> 00:40:46,760
Speaker 1: is going to be infrastructure costs. They say, hire operating

897
00:40:46,800 --> 00:40:50,040
Speaker 1: expenses depreciation as well of those assets or those data

898
00:40:50,040 --> 00:40:51,879
Speaker 1: centers more broadly, of the chips they have to keep

899
00:40:51,880 --> 00:40:54,920
Speaker 1: buying again. But then they say, employee conversations with the

900
00:40:54,960 --> 00:40:58,360
Speaker 1: second largest factor, as we add technical talent.

901
00:40:58,520 --> 00:41:01,759
Speaker 2: It's a good time priority that technical talent, right it.

902
00:41:01,719 --> 00:41:03,239
Speaker 6: Is you can go in charge a pretty penny if

903
00:41:03,280 --> 00:41:04,040
Speaker 6: you've got a nice computer.

904
00:41:04,320 --> 00:41:05,520
Speaker 2: So what is that? How do you read into that?

905
00:41:05,560 --> 00:41:08,120
Speaker 2: Does that mean that the folks who are the engineers

906
00:41:08,400 --> 00:41:13,120
Speaker 2: doing the AI stuff? Yeah, say the helpful demand, who.

907
00:41:13,120 --> 00:41:18,200
Speaker 1: Is that areas of infrastructure monetization, So interestingly obviously monetizing

908
00:41:18,200 --> 00:41:21,960
Speaker 1: their referable business reality labs, generative artificial intelligence as well

909
00:41:22,000 --> 00:41:26,720
Speaker 1: as regulation and compliance. They are the hr GO gets

910
00:41:26,880 --> 00:41:29,560
Speaker 1: for this particular year, and they are actually overall saying

911
00:41:29,600 --> 00:41:32,840
Speaker 1: that headcount has ticked high at ten percent year of

912
00:41:32,840 --> 00:41:35,200
Speaker 1: a year. Despite this efficiency mode they've been in.

913
00:41:35,400 --> 00:41:37,919
Speaker 2: There's also this note the majority of twenty twenty five

914
00:41:37,960 --> 00:41:41,560
Speaker 2: capex to be directed to core business. What's the definition

915
00:41:41,600 --> 00:41:44,320
Speaker 2: of metas core business? Is it the family of apps?

916
00:41:44,920 --> 00:41:47,399
Speaker 2: The Instagrams and the WhatsApp And to say, okay, we're

917
00:41:47,400 --> 00:41:51,399
Speaker 2: going to invest in that, so don't worry investors, We're

918
00:41:51,440 --> 00:41:53,359
Speaker 2: spending money on the company, on the parts of our

919
00:41:53,400 --> 00:41:55,319
Speaker 2: business that make money. Is that the message there?

920
00:41:55,560 --> 00:41:57,880
Speaker 6: I mean, Mandeep is your man to ask what's a

921
00:41:57,920 --> 00:41:58,440
Speaker 6: core business?

922
00:41:58,480 --> 00:42:01,520
Speaker 1: But I'd say Reality Labs isn't it even though their

923
00:42:01,560 --> 00:42:02,720
Speaker 1: company name is Meta.

924
00:42:03,360 --> 00:42:06,480
Speaker 5: Yeah. Look, I think overall they will be prudent when

925
00:42:06,520 --> 00:42:09,120
Speaker 5: it comes to headcom growth. They may have to pay

926
00:42:09,160 --> 00:42:11,920
Speaker 5: more for the AI talent, that's what they are alluding to.

927
00:42:12,400 --> 00:42:15,200
Speaker 5: But at the same time they are continuing to lose

928
00:42:15,239 --> 00:42:18,160
Speaker 5: money on Reality Labs. I would have expected, you know,

929
00:42:18,239 --> 00:42:21,680
Speaker 5: that will be your offset. If you see margin degradation,

930
00:42:22,360 --> 00:42:24,920
Speaker 5: you offset it in terms of Reality Labs losses.

931
00:42:25,000 --> 00:42:27,120
Speaker 2: You're not seeing that, So James chalk mark, this is

932
00:42:27,160 --> 00:42:32,080
Speaker 2: still a company that you know to The message to

933
00:42:32,120 --> 00:42:34,120
Speaker 2: investors is this is this is a company that makes

934
00:42:34,160 --> 00:42:38,800
Speaker 2: money because we're opening Instagram and we're using reels and

935
00:42:38,920 --> 00:42:41,919
Speaker 2: we're using the family of apps the core business. Right,

936
00:42:42,520 --> 00:42:44,680
Speaker 2: that's their message. They don't want people to get worried

937
00:42:44,719 --> 00:42:48,279
Speaker 2: that this is another you know, meta a foray into

938
00:42:48,280 --> 00:42:48,840
Speaker 2: the metaverse.

939
00:42:50,719 --> 00:42:53,560
Speaker 7: No, I mean, I think the metaverse continues to be

940
00:42:53,920 --> 00:42:56,200
Speaker 7: a long term vision for the company. But you know,

941
00:42:56,640 --> 00:42:59,440
Speaker 7: in this kind of market, you can't be looking at things,

942
00:43:00,120 --> 00:43:03,680
Speaker 7: you know, on a moonshots. Yeah, you have to be

943
00:43:03,719 --> 00:43:06,759
Speaker 7: able to just focus on the quarter and focus on

944
00:43:06,800 --> 00:43:09,200
Speaker 7: the year, and then most of some cases, you know,

945
00:43:09,239 --> 00:43:13,239
Speaker 7: even just focus on the week. So you know, the

946
00:43:13,320 --> 00:43:15,920
Speaker 7: duration that you evaluate these companies is becoming a lot

947
00:43:15,960 --> 00:43:19,640
Speaker 7: shorter and shorter, so as a volatility increase is given

948
00:43:19,680 --> 00:43:23,520
Speaker 7: the increase in uncertainty. So that being said, you know,

949
00:43:23,560 --> 00:43:26,480
Speaker 7: for a company like Meta, yeah, that's exactly how I

950
00:43:26,760 --> 00:43:30,759
Speaker 7: describe it and think about it. And those moonshots you

951
00:43:30,800 --> 00:43:33,759
Speaker 7: know as a TVD but not part of the calculus

952
00:43:33,800 --> 00:43:34,560
Speaker 7: as it stands today.

953
00:43:34,600 --> 00:43:36,920
Speaker 3: Hey, for those who care, and videos up about two

954
00:43:36,960 --> 00:43:39,160
Speaker 3: point one percent here in the aftermarket, so we're seeing

955
00:43:39,160 --> 00:43:39,879
Speaker 3: some movement there.

956
00:43:40,960 --> 00:43:43,880
Speaker 4: Meta not giving a full year.

957
00:43:43,760 --> 00:43:46,560
Speaker 3: Twenty twenty five revenue outlook mandep is that significant?

958
00:43:47,520 --> 00:43:50,120
Speaker 5: No, I think based on the one Q guide you

959
00:43:50,160 --> 00:43:52,480
Speaker 5: can see currency as a headmin In fact, it's a

960
00:43:52,520 --> 00:43:55,640
Speaker 5: three percent headmind, so quite significant. And the other thing

961
00:43:55,680 --> 00:43:59,520
Speaker 5: I can point out in the print is six percent

962
00:43:59,600 --> 00:44:02,839
Speaker 5: in pressure growth. That's the weakest they have had. So

963
00:44:02,880 --> 00:44:06,320
Speaker 5: fourteen percent pricing growth that's a result of AI, so

964
00:44:06,400 --> 00:44:10,120
Speaker 5: it's paying off in ad pricing, but six percent impressions growth.

965
00:44:10,400 --> 00:44:14,160
Speaker 5: There are two reasons why it's decelerating. One is they're

966
00:44:14,200 --> 00:44:17,320
Speaker 5: showing you less ads and to make a better experience.

967
00:44:17,400 --> 00:44:20,120
Speaker 5: Other is people are spending less time. I mean, it's

968
00:44:20,160 --> 00:44:23,600
Speaker 5: still the you know, they have three billion family users

969
00:44:23,600 --> 00:44:27,600
Speaker 5: across their family of apps, but incrementally there that engagement

970
00:44:27,640 --> 00:44:30,880
Speaker 5: growth is slowing down because they're not showing those ads

971
00:44:30,880 --> 00:44:32,200
Speaker 5: on elections over election.

972
00:44:32,280 --> 00:44:33,000
Speaker 4: No, I'm just kidding.

973
00:44:33,640 --> 00:44:36,280
Speaker 5: It could very well be, you know, a slew of factors,

974
00:44:36,320 --> 00:44:40,239
Speaker 5: but engagement growth is how impressions grow, and so six

975
00:44:40,280 --> 00:44:42,440
Speaker 5: percent is the weakest they've had for a while.

976
00:44:42,600 --> 00:44:45,360
Speaker 2: Well, Caroline, our own Kurt Wagner pointing out that Meta's

977
00:44:45,400 --> 00:44:48,960
Speaker 2: average price per ad increased by fourteen percent year over year.

978
00:44:49,000 --> 00:44:50,879
Speaker 2: It increased ten percent year over year for the full

979
00:44:50,920 --> 00:44:54,320
Speaker 2: year of twenty twenty four. Is it because the AI

980
00:44:54,840 --> 00:44:57,839
Speaker 2: that they've the AA investments they've made are making those

981
00:44:57,920 --> 00:45:01,440
Speaker 2: ads so much more targeted, better targeted, or.

982
00:45:01,400 --> 00:45:04,080
Speaker 1: Whether people just know that if you're going to be

983
00:45:04,120 --> 00:45:06,759
Speaker 1: committing any capital anywhere in terms of marketing, it's a

984
00:45:06,840 --> 00:45:08,920
Speaker 1: very good bet to be doing it on the Family

985
00:45:08,920 --> 00:45:11,359
Speaker 1: of Apps. That met her off as it's interesting, We've

986
00:45:11,360 --> 00:45:14,680
Speaker 1: had Mick Mac on the show, which is a company

987
00:45:14,719 --> 00:45:18,480
Speaker 1: the tracks digital spend in particular and efficacy, and she

988
00:45:18,600 --> 00:45:19,080
Speaker 1: came on and.

989
00:45:19,000 --> 00:45:20,280
Speaker 6: Said ash biograph.

990
00:45:20,640 --> 00:45:22,840
Speaker 1: Rachel came on and said, the beginning of this year,

991
00:45:23,440 --> 00:45:25,400
Speaker 1: we have seen a big dive in the amount of

992
00:45:25,440 --> 00:45:28,920
Speaker 1: money and marketing being committed to the likes of metas

993
00:45:29,040 --> 00:45:31,399
Speaker 1: Family of Apps was her take, and the data which

994
00:45:31,440 --> 00:45:33,439
Speaker 1: she was seeing in her theory was on the back

995
00:45:33,480 --> 00:45:36,879
Speaker 1: of some of the politicization of Mark Zuckerberg of late,

996
00:45:37,160 --> 00:45:41,719
Speaker 1: and indeed, therefore, without the assessment of some of the

997
00:45:41,760 --> 00:45:44,680
Speaker 1: content and some of the fact checkers that are there anymore,

998
00:45:44,800 --> 00:45:48,120
Speaker 1: people have started to shy away from committing their brands.

999
00:45:47,760 --> 00:45:48,440
Speaker 6: Onto that company.

1000
00:45:48,520 --> 00:45:50,759
Speaker 1: Now that is Mick Mac's perspective, and we'll have to

1001
00:45:50,760 --> 00:45:52,480
Speaker 1: see whether it's be indicated through what is said on

1002
00:45:52,480 --> 00:45:54,239
Speaker 1: this particular part of the business. But as you say,

1003
00:45:54,280 --> 00:45:56,360
Speaker 1: if there's a slight pulling back in impressions, but the

1004
00:45:56,400 --> 00:45:58,719
Speaker 1: average prices are managing to go up. They're managing to

1005
00:45:58,760 --> 00:46:01,600
Speaker 1: remain incredibly important to the brands that do remain committed

1006
00:46:01,640 --> 00:46:02,600
Speaker 1: and charge more for it.

1007
00:46:02,719 --> 00:46:04,719
Speaker 3: Going back to Meta and the business, and I think

1008
00:46:04,760 --> 00:46:08,080
Speaker 3: it's interesting coming off of a FED meeting today where

1009
00:46:08,760 --> 00:46:11,080
Speaker 3: certainly the FED chair was asked about policies coming out

1010
00:46:11,120 --> 00:46:14,960
Speaker 3: of the administration, regulatory or others. A little warning from

1011
00:46:15,360 --> 00:46:19,120
Speaker 3: our live blog when it comes to Meta metas CFO

1012
00:46:19,320 --> 00:46:21,720
Speaker 3: in the release, saying, in addition, we continue to monitor

1013
00:46:22,120 --> 00:46:25,719
Speaker 3: an active regulatory landscape, including legal and regulatory headwinds in

1014
00:46:25,760 --> 00:46:28,400
Speaker 3: the EEU and the US that could significantly impact our

1015
00:46:28,440 --> 00:46:31,560
Speaker 3: business and our financial results. James Chacmat, come on back in.

1016
00:46:31,640 --> 00:46:34,040
Speaker 3: I mean, let's not forget there are things that are

1017
00:46:34,080 --> 00:46:36,400
Speaker 3: overhanging some of these big tech companies like a Meta.

1018
00:46:38,760 --> 00:46:41,920
Speaker 7: Yes, that's true, but that's the case always. You know,

1019
00:46:42,520 --> 00:46:45,719
Speaker 7: all of these companies constantly face regular stories scrutiny both

1020
00:46:45,800 --> 00:46:48,879
Speaker 7: here and abroad. But I think with the change in administration,

1021
00:46:49,120 --> 00:46:53,680
Speaker 7: some of that may alleviate here at least the state side.

1022
00:46:53,920 --> 00:46:57,480
Speaker 7: We'll see what happens overseas, but overall, I mean that's

1023
00:46:57,480 --> 00:46:59,920
Speaker 7: an overhang I think you constantly have to grapple with,

1024
00:47:01,200 --> 00:47:04,239
Speaker 7: so you know, it's it's something that kind of been

1025
00:47:04,280 --> 00:47:04,959
Speaker 7: meal into at.

1026
00:47:04,840 --> 00:47:07,440
Speaker 2: This point, Caroline. Is the regulatory landscape in the US

1027
00:47:07,719 --> 00:47:11,239
Speaker 2: less worrisome for meta platforms now than it was a

1028
00:47:11,280 --> 00:47:15,640
Speaker 2: year ago? Given Mark Zuckerberg's relationship with Donald Trump, his

1029
00:47:15,760 --> 00:47:18,279
Speaker 2: visit Tomorrow Lago, his trip to Washington, d C. What

1030
00:47:18,440 --> 00:47:21,160
Speaker 2: he's saign the Joe Rogues podcast, great point, Dana White

1031
00:47:21,160 --> 00:47:21,640
Speaker 2: on the board.

1032
00:47:22,320 --> 00:47:24,400
Speaker 1: I mean, they've just settled twenty five million dollars for

1033
00:47:24,600 --> 00:47:27,879
Speaker 1: kicking Trump off their family of apps previously, So maybe

1034
00:47:27,880 --> 00:47:31,480
Speaker 1: we'll see some culmination of what that previously no love

1035
00:47:31,520 --> 00:47:34,440
Speaker 1: lost will currently end up being. I think people had

1036
00:47:34,440 --> 00:47:38,840
Speaker 1: felt actually the realignment of Zuckerberg, whether that's from a

1037
00:47:38,840 --> 00:47:42,000
Speaker 1: fiduciary duty perspective or whether that's just actually where he

1038
00:47:42,080 --> 00:47:46,719
Speaker 1: feels in terms of personal persuasion, have ultimately will bear

1039
00:47:46,760 --> 00:47:48,719
Speaker 1: fruit when it comes to doing business. Look, we've seen

1040
00:47:49,120 --> 00:47:53,080
Speaker 1: from Oracle, from open Ai, from SoftBank, from you name it, Dubai,

1041
00:47:53,520 --> 00:47:57,319
Speaker 1: wealth magnates and real estate billionaires.

1042
00:47:57,480 --> 00:48:00,120
Speaker 6: How do you do business in America? Now?

1043
00:48:00,640 --> 00:48:03,200
Speaker 1: You go visit mar A Lago, you pay some money

1044
00:48:03,200 --> 00:48:06,720
Speaker 1: to attend ultimately the inauguration, and you see what deals

1045
00:48:06,719 --> 00:48:08,480
Speaker 1: can be done. And I think many would say that

1046
00:48:08,520 --> 00:48:10,759
Speaker 1: what Zuckoworg's been doing is in line with that.

1047
00:48:10,880 --> 00:48:13,200
Speaker 6: I think the regulatory landscape from an M and.

1048
00:48:13,160 --> 00:48:17,080
Speaker 1: A perspective becomes different with a new FTC, new ultimate

1049
00:48:17,800 --> 00:48:19,640
Speaker 1: overseeing of what happens with the SEC.

1050
00:48:20,200 --> 00:48:23,000
Speaker 6: But I'm sure there's still some.

1051
00:48:22,920 --> 00:48:24,640
Speaker 1: He's got some way to go to make up for

1052
00:48:25,160 --> 00:48:26,840
Speaker 1: some of the lines that were said last year of

1053
00:48:26,840 --> 00:48:30,000
Speaker 1: maybe he'll end up in jail because of Trump's irritation

1054
00:48:30,280 --> 00:48:32,000
Speaker 1: with past misdemeanors.

1055
00:48:32,080 --> 00:48:34,359
Speaker 3: I'm only going to mention some of them because there's

1056
00:48:34,400 --> 00:48:36,080
Speaker 3: a ton of earnings out here after the close, But

1057
00:48:36,200 --> 00:48:38,800
Speaker 3: just to rehash, Microsoft down about one point six percently

1058
00:48:38,840 --> 00:48:42,200
Speaker 3: after markets, certainly off its loads of the earlier trade

1059
00:48:42,239 --> 00:48:45,560
Speaker 3: right after earnings. Tusla now up about three point four percent.

1060
00:48:45,600 --> 00:48:48,240
Speaker 3: It had been down about four or five percent.

1061
00:48:48,320 --> 00:48:48,480
Speaker 4: Here.

1062
00:48:48,600 --> 00:48:52,279
Speaker 3: IBM has rallied about eight percent after its earnings. We've

1063
00:48:52,280 --> 00:48:54,520
Speaker 3: been talking about Meta, it is up about one percent,

1064
00:48:54,520 --> 00:48:58,160
Speaker 3: and Nvidia, which doesn't report until late February, is up

1065
00:48:58,200 --> 00:49:01,879
Speaker 3: almost two percent in today's trade here in the aftermarket.

1066
00:49:02,160 --> 00:49:03,640
Speaker 3: James CHOCKMK it's been.

1067
00:49:03,520 --> 00:49:04,160
Speaker 4: Quite a week.

1068
00:49:04,880 --> 00:49:05,080
Speaker 5: You know.

1069
00:49:05,120 --> 00:49:06,799
Speaker 3: One of the things when I think about big tech

1070
00:49:06,840 --> 00:49:10,759
Speaker 3: in particular is the environment for rates. And we had

1071
00:49:10,760 --> 00:49:13,520
Speaker 3: a FED decision, right and it seems like FED rate

1072
00:49:14,080 --> 00:49:17,120
Speaker 3: moves to the downside cuts seem to be putting off

1073
00:49:17,600 --> 00:49:20,080
Speaker 3: more and more this year here in twenty twenty five.

1074
00:49:20,400 --> 00:49:23,920
Speaker 3: How are you thinking about valuations and the rate environment

1075
00:49:23,960 --> 00:49:26,080
Speaker 3: and what that potentially needs for some of these names

1076
00:49:26,160 --> 00:49:28,879
Speaker 3: or is that not as important versus maybe hearing about

1077
00:49:28,920 --> 00:49:31,280
Speaker 3: their AI spend or other things.

1078
00:49:32,360 --> 00:49:35,640
Speaker 7: Valuation is certainly a factor, you know, when it comes

1079
00:49:35,680 --> 00:49:37,920
Speaker 7: to rates. Now it's a big picture. When it comes

1080
00:49:38,000 --> 00:49:40,640
Speaker 7: to rates, we do think, you know, we perhaps have

1081
00:49:40,680 --> 00:49:45,399
Speaker 7: a more slightly more dobbish stance than some of the market. Well,

1082
00:49:45,440 --> 00:49:48,359
Speaker 7: we do kind of agree with Powell that the rates

1083
00:49:48,400 --> 00:49:52,880
Speaker 7: are likely trending towards zero, not zero, towards two percent

1084
00:49:53,640 --> 00:49:57,720
Speaker 7: inflation rates. So you know, we think that the market's

1085
00:49:57,719 --> 00:50:00,920
Speaker 7: currently expecting two rate cuts this year June and December.

1086
00:50:00,960 --> 00:50:04,200
Speaker 7: That's pretty probable scenario.

1087
00:50:04,800 --> 00:50:05,479
Speaker 2: So that's good.

1088
00:50:06,600 --> 00:50:10,040
Speaker 7: That being said, the stocks that were primarily focused on

1089
00:50:10,160 --> 00:50:13,680
Speaker 7: and weigh leaning into are the ones that have not

1090
00:50:13,719 --> 00:50:17,840
Speaker 7: only upside to estimates but also upside to their valuation.

1091
00:50:18,000 --> 00:50:22,400
Speaker 7: Multiple now across the big tax tech space, there's not

1092
00:50:22,440 --> 00:50:25,000
Speaker 7: that many of those, I'd say, with the exception of

1093
00:50:25,440 --> 00:50:28,719
Speaker 7: Meta really and to a certain extent Google or Alphabet.

1094
00:50:29,400 --> 00:50:33,480
Speaker 7: The other ones are pretty much in. Apple's up there,

1095
00:50:33,520 --> 00:50:38,759
Speaker 7: Microsoft's up there. You know, Tesla's certainly not cheap. So yeah,

1096
00:50:39,280 --> 00:50:41,200
Speaker 7: it's something that we have to be mindful of. We're

1097
00:50:41,239 --> 00:50:44,080
Speaker 7: there because you know, you have to benchmark yourself to

1098
00:50:44,120 --> 00:50:47,360
Speaker 7: a certain extent on the top ten names in the Nasdaq.

1099
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Speaker 7: But that's certainly not our oversize and we've.

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Speaker 4: Only got about a minute left here.

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Speaker 1: Does TikTok matter to the revenue guide for the future

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00:50:54,920 --> 00:50:57,040
Speaker 1: of Meta and just quickly.

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00:50:57,600 --> 00:50:59,320
Speaker 7: Yeah, I mean I think TikTok matters to all of

1104
00:50:59,360 --> 00:51:04,240
Speaker 7: these companies. We'll see what happens, but it's certainly something

1105
00:51:04,280 --> 00:51:08,440
Speaker 7: to be mindful of, cognizant and follow extremely closely. You know,

1106
00:51:08,480 --> 00:51:11,680
Speaker 7: if it does come in two domestic hands, you know,

1107
00:51:11,719 --> 00:51:14,200
Speaker 7: that could change the calculus to a certain extent. So

1108
00:51:14,960 --> 00:51:17,240
Speaker 7: I think Meta will be fine regardless. You know, TikTok

1109
00:51:17,280 --> 00:51:20,719
Speaker 7: is obviously already here, but you know, what does that

1110
00:51:20,719 --> 00:51:24,759
Speaker 7: mean for the valuations and and whatnot? So my mind

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00:51:24,760 --> 00:51:27,840
Speaker 7: full of it, not worried about it right now, but

1112
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Speaker 7: definitely keeping an eye all.

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Speaker 3: Right, Well, we are keeping an eye on a lot

1114
00:51:31,360 --> 00:51:33,160
Speaker 3: of stuff, and we ain't done yet because it's still

1115
00:51:33,200 --> 00:51:35,359
Speaker 3: got We've got more stuff to come this week. Our

1116
00:51:35,400 --> 00:51:38,520
Speaker 3: thanks to our external guests and also of course our

1117
00:51:38,560 --> 00:51:41,880
Speaker 3: incredible in house team James Chackmok, thank you, first partner

1118
00:51:41,920 --> 00:51:43,800
Speaker 3: and technology Analystic Clockwise Capital.

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00:51:44,280 --> 00:51:45,040
Speaker 4: They're in Miami.

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Speaker 3: Caroline Hyde, you rock covering so much about the tech community,

1121
00:51:50,280 --> 00:51:52,759
Speaker 3: and be sure to check her out on Bloomberg Technology

1122
00:51:52,760 --> 00:51:55,200
Speaker 3: on Bloomberg TV at eleven am Wall Street Time. She

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00:51:55,360 --> 00:51:57,480
Speaker 3: is one of the co hosts of Bloomberg Technology.

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00:51:58,520 --> 00:52:01,000
Speaker 2: Yeah, just a big thank you to our Bloomberg Intelligence

1125
00:52:01,000 --> 00:52:03,479
Speaker 2: team too, both here in the studio today, Man Deep

1126
00:52:03,520 --> 00:52:06,920
Speaker 2: Saying covering all things Meta and Moran anurad Rana on Microsoft.

1127
00:52:07,040 --> 00:52:10,120
Speaker 2: Check out their notes. They're out now on the Bloomberg.

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00:52:09,680 --> 00:52:11,600
Speaker 3: Terminal, and be sure to check out all of the

1129
00:52:11,880 --> 00:52:14,640
Speaker 3: write throughs on the stories and on the names that

1130
00:52:14,680 --> 00:52:17,160
Speaker 3: have been reporting here because they are moving in the aftermarket.

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00:52:17,160 --> 00:52:18,279
Speaker 4: That's going to do it for Tim And we have

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Speaker 4: a good and safe evening.