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Speaker 1: Bloomberg Audio Studios, podcasts, radio news. Bloomberg Tech is alive

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Speaker 1: from coast to coast with Caroline Hyde and New York

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Speaker 1: and ed Lo Loow in San Francisco.

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Speaker 2: This is Bloomberg Tech coming up. SpaceX pitches a twenty

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Speaker 2: eight point five trillion dollar opportunity from AI to Mars

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Speaker 2: ahead of an all time blockbuster IPO. We break down

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Speaker 2: the S one plus and video fails to reignite the

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Speaker 2: AI trade as CEO Jensen Wang pushes to diversify the

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Speaker 2: chip maker, saying AI is set to go mainstream and

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Speaker 2: another major IPO on the horizon Open AI preparing for

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Speaker 2: a filing which could come as soon as tomorrow. Let's

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Speaker 2: get straight to our top story. SpaceX has publicly filed

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Speaker 2: for an IPO, and in the process this closed billions

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Speaker 2: of dollars in losses along with a super voting share

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Speaker 2: structure that would give Elon Musk sweeping control over the company.

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Speaker 2: The ticker will be sp c X. The filing also

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Speaker 2: underscores just how ambitious SpaceX believes its future could be.

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Speaker 2: Today's big number twenty eight point five trillion dollars the

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Speaker 2: total addressable market. The company says it's pursuing according to

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Speaker 2: the documents. So let's get more on SpaceX's IPO and

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Speaker 2: on Starship at the heart of it. Bloomberg Managing editor

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Speaker 2: for space Benedict Cammell, Bloomberg Deals reporter Ryan Gord Benny,

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Speaker 2: I start with you. We learned a lot about the

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Speaker 2: reality of where SpaceX's business is right now, So let's

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Speaker 2: start there. The numbers that jumped out of you as

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Speaker 2: we poured through the document and went through it with

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Speaker 2: a fine tooth comb.

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Speaker 3: Yeah, I mean you've already mentioned some of them, and

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Speaker 3: the one that really was a Bonker's number, let's say

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Speaker 3: it is the total addressable market. The market they're targeting

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Speaker 3: just shy of ninety twenty nine trillion, And so that's

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Speaker 3: one number that I think everyone sort of gulped at.

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Speaker 3: But also on the other sort of end of the spectrum,

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Speaker 3: the sales and the loss are actually not that great.

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Speaker 3: So you've got a company here with quarterly sales of

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Speaker 3: just shy of five billion and with a loss that's

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Speaker 3: not that dissimilar. So for a company with those kind

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Speaker 3: of numbers to seek a valuation of two trillion, that

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Speaker 3: is obviously pretty steep. We then saw what Musk is

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Speaker 3: trying to sort of retain the control he's trying to control.

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Speaker 3: He wants to retain in the company about forty one

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Speaker 3: percent of a control that he wants to keep, so

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Speaker 3: that obviously gives them a really hard sort of control

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Speaker 3: of the company. So he's the man in charge and

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Speaker 3: he will remain so going forward.

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Speaker 2: The debt pile twenty nine billion dollars. I want to

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Speaker 2: get into how this IPO is going to work, Ryan,

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Speaker 2: What do we confirm about the banks, whose lead left,

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Speaker 2: whose lead, and who's behind? But also like the because

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Speaker 2: if this is going to be the biggest IPO of

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Speaker 2: all time, dollars raised or valuation doesn't matter in your world,

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Speaker 2: it does matter who's trying to pull it off.

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Speaker 4: It does.

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Speaker 5: And you know, there's been so much said and written

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Speaker 5: over the past what two, three, four, five months around

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Speaker 5: who's actually going to be quote unquote leading this deal.

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Speaker 5: I mean, if you look at the s one Goldman

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Speaker 5: Sex is in that plum left position to the right

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Speaker 5: of them, and Morgan Stanley, Bank of America's City Group

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Speaker 5: and JP Morgan that the last three sort of in

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Speaker 5: alphabetical order as it were. But you know, I think

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Speaker 5: if you're Goldman Sex, You're looking at this and saying,

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Speaker 5: this is a great marketing win for us. You know,

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Speaker 5: we are the preeminent franchise for IPOs and technology on

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Speaker 5: the street. And then you're Morgan Stanley, who maybe is saying, well,

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Speaker 5: you know, we've done a lot of work for Elon

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Speaker 5: Musk over the years, what does that mean for us? Well,

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Speaker 5: if you actually dig down into the final you can

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Speaker 5: see that Morgan Stanley does have that stabilization agent role,

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Speaker 5: which I will say, you know is not something to

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Speaker 5: you know, really pass over. The stabilization role is crucial

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Speaker 5: to trading that very first day flow and in some

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Speaker 5: cases that could be up to twenty to thirty percent

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Speaker 5: of that flow on day one, and they're obviously going

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Speaker 5: to take a certain cut of that revenue. So you know,

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Speaker 5: it comes down at the end of the day to

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Speaker 5: sort of marketing vesus economics. I mean, our understanding is

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Speaker 5: that the economic structure in terms of who's getting the

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Speaker 5: fees is roughly equal. But if you're goldm and Sex,

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Speaker 5: you're able to go out to your investors and say, oh,

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Speaker 5: your shareholders and say, you know, we are leading the

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Speaker 5: biggest IPO of all time.

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Speaker 2: And that's clearly huge, and we got the reporting that

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Speaker 2: David Solomon Goldman CEO slid into us DMS to get

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Speaker 2: that win. Benny. The other important thing is who controls

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Speaker 2: this company? What do we learn about Elon Musk's voting power.

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Speaker 3: Yeah, so he retains absolute control over the company overall,

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Speaker 3: just north of forty percent. Some other interesting investors in there.

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Speaker 3: We're not quite sure what the role of Google is.

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Speaker 3: They're obviously an early investor in this, but this is

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Speaker 3: a company that will mint lots of billionaires and possibly

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Speaker 3: the first trillion there if Musk gets his way, if

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Speaker 3: the pricing turns out as hoped, and he could really

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Speaker 3: get into a very different stratusphere altogether, if he gets

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Speaker 3: those bonus shares. That's something that was also teased yesterday.

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Speaker 3: If you managed to actually put people on Mars, if

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Speaker 3: you managed to inhabitate Mars with a colony.

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Speaker 4: I know this all.

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Speaker 3: Sounds deeply science fiction, but if he does that, and

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Speaker 3: if he takes the valuation of the company to a

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Speaker 3: certain level, he stands to gain another one billion and

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Speaker 3: bonus shares, so again, that will sort of lift an

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Speaker 3: already very wealthy man into a very different stratosphere.

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Speaker 2: Bloombergs, Benedict camaon Wrangel, thank you very much. The SpaceX

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Speaker 2: prospectus ask investors to believe in three things AI in space,

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Speaker 2: a million people on Mars, and Elon Musk's ability to

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Speaker 2: make it all happen. But that's also what great IPO

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Speaker 2: storytelling is supposed to do, sell the investors on a

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Speaker 2: future that doesn't yet fully exist. Joining us now is

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Speaker 2: Lauren Webster, Piper Sandler's head of investment banking. Just stay

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Speaker 2: off the bat. You know, Piper Sandler is not involved

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Speaker 2: in this IPO, but you know this industry, you know

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Speaker 2: how an IPO works, and this will be the biggest

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Speaker 2: IPO of all time. When you read that document as

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Speaker 2: far fetched and out of this world as it was,

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Speaker 2: what were you thinking?

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Speaker 6: I was certainly thinking aspirational visionary. But let's unpack for

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Speaker 6: starters the TAM that you spoke about.

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Speaker 2: Okay, so you have this document and you have to

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Speaker 2: say something, yes, and what you say is we see

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Speaker 2: a world where the market ahead of us is twenty

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Speaker 2: eight point five trillion dollars, but twenty six point five

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Speaker 2: trillion is just AI.

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Speaker 4: Yep.

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Speaker 7: Yeah, So two observations.

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Speaker 6: First, I think every prospectus has a very lofty TAM

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Speaker 6: in it, so.

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Speaker 7: This is not out of the ordinary. It truly is

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Speaker 7: par for the course.

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Speaker 6: The second one is every company going public wants to

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Speaker 6: be able to tell investors we have multiple ways to

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Speaker 6: win in multiple tams to be able to touch So, yes,

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Speaker 6: huge numbers. We can kind of quarterback Monday morning, quarterback,

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Speaker 6: what's right, what's wrong in there? But it is saying

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Speaker 6: to investors we have multiple paths here to really meet

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Speaker 6: that growth outlook that you're investing us to achieve.

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Speaker 2: Is it believable the term number any of it.

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Speaker 6: I don't know if I've fully truly believed any tam

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Speaker 6: put in a prospectus, and I've always been able to

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Speaker 6: poke holes in it. I think probably the one that

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Speaker 6: was the biggest gap for me is really that enterprise

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Speaker 6: application Wedge right, So you saw.

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Speaker 7: A very sort of rational stare step.

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Speaker 6: The enterprise application one needs a lot of unpacking, but

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Speaker 6: I think that's part of the story here, is that

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Speaker 6: there are really three core pieces and each of these

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Speaker 6: are going to be foundational to the future of how

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Speaker 6: enterprises deliver services to their customers.

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Speaker 2: I think what SpaceX is arguing through Xai, which is

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Speaker 2: part of the story it owns Xai is that they

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Speaker 2: are going to take on your open Ais anthropics googles

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Speaker 2: in the market for agentic AI talk about how white

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Speaker 2: collar work will be transformed. But is the TAM even

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Speaker 2: from a potential investors perspective, calculable, whether you believe it

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Speaker 2: or not. You know, there has to be some math

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Speaker 2: involved on how SpaceX we get into that market.

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Speaker 6: Yeah, look, I think I think they're already delivering in

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Speaker 6: some of those areas, certainly on let's just take the

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Speaker 6: Xai piece and what they're doing with the Colossus data

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Speaker 6: centers and now having Anthropic come in as a key

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Speaker 6: customer there. But that is a market that we are

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Speaker 6: going to hear over and over again throughout this year.

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Speaker 6: You mentioned open Ai IPO coming up potentially really large

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Speaker 6: TAM numbers because it really does touch every part of

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Speaker 6: the enterprise ecosystem and then flowing down into consumer daily life.

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Speaker 2: We maybe should have started here, But why does the

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Speaker 2: preliminary prospectus matter? What is it that needs to happen,

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Speaker 2: you know, in convince and seeing the market to participate

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Speaker 2: in this IPO.

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Speaker 6: Yeah, so a good question. In a few areas where

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Speaker 6: it's really really critical. One is the storytelling, and I

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Speaker 6: think unpacking that story, there's three core parts that we've

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Speaker 6: talked about in terms of what are you investing in.

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Speaker 6: You're investing a core space business, really the foundation of

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Speaker 6: SpaceX launch rocket, where they have a tremendous leg up

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Speaker 6: on the competition and have really bent the cost curve

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Speaker 6: associated with the future space economy. Two is really telling

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Speaker 6: the story around autonomy and connectivity for that autonomy at

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Speaker 6: the edge with Starlink, and that we as Starlink are

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Speaker 6: going to be able to empower power the connect to

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Speaker 6: be required for everything we're going to do with autonomous

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Speaker 6: vehicles robots go down the list. And then three is

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Speaker 6: really the aipiece. So that's the storytelling. And then of

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Speaker 6: course you also have the numbers behind that, risks associated

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Speaker 6: with it and informing investors of what they're getting into.

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Speaker 7: But first inform I was telling that story prior.

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Speaker 2: To the offering. Elon Musk has eighty five point one

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Speaker 2: percent voting power based on the structure of the shares.

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Speaker 2: Historically in big IPOs, how has that been a factor.

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Speaker 6: Yeah, so you've certainly seen across the tech industry these

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Speaker 6: you know, dual share classes where founders retain significant, if

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Speaker 6: not nearly total control.

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Speaker 2: In terms of what spep of voting share class exactly.

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Speaker 6: I think for Musk in particular, he has a very

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Speaker 6: long leash with investors in terms of capital intensive projects,

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Speaker 6: in part because what he's delivered with Tesla, what he's

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Speaker 6: been able to do in the space economy today. And

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Speaker 6: so while you know there is some potential caution, it's

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Speaker 6: not unexpected that he would retain this type of control.

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Speaker 6: And we've certainly seen it in prior tech IPOs.

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Speaker 2: And we just have about a minute left. What do

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Speaker 2: you think is going to happen? How do you think

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Speaker 2: this is going to go?

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Speaker 6: Drawing your experience, Yeah, yeah, So a few things I'm

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Speaker 6: really looking forward to the Starship launch this evening is that.

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Speaker 7: I think it is important. It is not binary.

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Speaker 6: What it does is you're we're already seeing tremendous investor

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Speaker 6: enthusiasm around the SpaceX IPO. I think that enthusiasm holds

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Speaker 6: even if Starship doesn't go. Musk and SpaceX have primed

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Speaker 6: us to understand there is failure when you're doing big things.

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Speaker 6: But if it goes well this evening, I think that

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Speaker 6: creates even greater enthusiasm and sort of creates the crescendo

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Speaker 6: around this opportunity, which is of course what he's hoping for.

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Speaker 2: Lauren Webster of Pipe Sandler Post SPACEXS one terrific. Now

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Speaker 2: coming up. By the way, the world's biggest company, most

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Speaker 2: valuable company, reported earnings last night. You may not be aware,

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Speaker 2: but we got Toro Prices Tony one to break down

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Speaker 2: in Vidia's earnings results and get a real investors reaction.

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Speaker 2: That's next. This is Bloomberg Tech reality check for Nvidia

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Speaker 2: shares now down two percent. We've been flat for most

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Speaker 2: of the pre market. We kind of had choppy trading,

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Speaker 2: swinging between modest gains and modest losses early in this

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Speaker 2: Thursday session after actually a strong forecast and a pitch

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Speaker 2: that Nvidia is diversifying from the data center giants. Gens

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Speaker 2: One said on a conference called Analysts that from robots

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Speaker 2: to row of taxis and every kind of startup in between. Quote,

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Speaker 2: we got it all covered, but investors have become harder

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Speaker 2: to impress. Joining us to break it all down. Tony One,

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Speaker 2: portfolio manager of the t row Price science and technology

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Speaker 2: funding across the firm in different guises. You know, trow

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Speaker 2: a big investor of in videos. Okay, let's start ninety

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Speaker 2: one billion dollars plus or minus two percent in the

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Speaker 2: second quarter. It was like almost the whisper number the

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Speaker 2: cell side and the buy side, but not enough, you know,

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Speaker 2: and why is that?

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Speaker 8: Hey, Look, I think that the growth at this scale

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Speaker 8: is just unprecedented. I don't think the market's ever seen

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Speaker 8: anything like it. And I think you think about traditional

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Speaker 8: semi investors, you know, the playbook is to sell this

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Speaker 8: type of growth, right because it's not sustainable.

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Speaker 4: You know, the margins are peaked.

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Speaker 8: But I think if you really look at what's going

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Speaker 8: on at the driver of the driver, like what's going

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Speaker 8: on in the end demand, I think it's like really

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Speaker 8: phenomenal in terms of agentic AI really taking off. The

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Speaker 8: time of work or like time of task is expanding.

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Speaker 8: Instead of being one shot or the you know, the

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Speaker 8: agent working for a few minutes, I think we're going

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Speaker 8: to go towards like months of work and that's requires

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Speaker 8: like a lot of compute to have an agent go

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Speaker 8: off and like complete a task and think and be persistent.

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Speaker 8: And then this other thing is I think that scaling

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Speaker 8: laws continue to hold like the frontiers are getting better.

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Speaker 8: The more compute throw at it, the better they get.

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Speaker 8: And you actually save money by being on the frontier

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Speaker 8: because it doesn't go through so many rabbit holes in

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Speaker 8: terms of trying to.

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Speaker 4: Complete your task.

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Speaker 8: So I think if you look at like the end

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Speaker 8: of Man, it's actually very encouraging, and I think we're climbing.

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Speaker 4: A wild worry here as a result.

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Speaker 2: So the thing that I was trying to digest throughout

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Speaker 2: the call is with the data points that Jensenmong and

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Speaker 2: collect Cress put forward as evidence of that, right, the

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Speaker 2: scaling laws and the dollar pot token, and they go

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Speaker 2: to this one trillion dollar figure, which I think they

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Speaker 2: clarified is Blackwell Rubin and it's for calendar year twenty

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Speaker 2: twenty five to twenty twenty seven, and it's basically a backlog, right,

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Speaker 2: But the main overarching point is that they would argue

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Speaker 2: that in Nvidia's own growth is trending ahead of even

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Speaker 2: the hyperscale capex growth. How do you model for that? Like,

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Speaker 2: is that the math that you would do.

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Speaker 4: Yeah.

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Speaker 8: One of the things that was really encouraging I think

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Speaker 8: of the quarter is that I actually broke out like

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Speaker 8: hyperscale versus the prize and sovereign and so, you know,

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Speaker 8: I think the baarrecase is that, you know, in Nvidia

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Speaker 8: can't outgrow the hyper hyperscale CAPEX numbers, but there's all

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Speaker 8: this new tam that's emerging that's not hyperscale, and you know,

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Speaker 8: I think they continue to do well in hyperscale, but

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Speaker 8: there's also new areas of a gentic enterprise adoption.

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Speaker 4: I think you look at.

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Speaker 8: Talks to financial services firms, they're adopting a lot of

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Speaker 8: a lot of this end demand that in Nvidia is producing.

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Speaker 8: And so I think that plus robotics that's on the

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Speaker 8: on the to come in the future, I think that

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Speaker 8: you know, allows them to see you know, not just

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Speaker 8: not bet bracketed in this like hyperscale kind of compute,

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Speaker 8: you know, paradigm here.

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Speaker 2: A tiny, slightly unusual situation. But I spoke to Jensen

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Speaker 2: at some length for Monday prior to earnings, but actually

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Speaker 2: a lot of what he said about the demand supply

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Speaker 2: equation was very prescient salient. Just listen to what he said.

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Speaker 4: We have the largest supplied chain in the world.

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Speaker 9: Our partners have done a great job securing supply for

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Speaker 9: and so all of the pieces go together, the silicon,

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Speaker 9: photonics is lined up, everything is all lined up. It's

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Speaker 9: just that the demand is much greater than the overall

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Speaker 9: capacity of the world.

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Speaker 2: If you are a student of technology history, finding yourself

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Speaker 2: in a situation where demand is vastly outpacing your ability

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Speaker 2: to supply, even in a world where supply chains are

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Speaker 2: doubling or quadrupling panon, which is what he went on

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Speaker 2: to say, that's been an enviable position. But right now

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Speaker 2: it's not moving the needle for this stock.

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Speaker 8: Yeah, I mean I think that you know, the market

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Speaker 8: is looking at relative earnings growth and where the bottlenecks are,

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Speaker 8: so capital's flowing there. But at some point, you know,

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Speaker 8: you look at the multiple for nvideo, it's like really attractive.

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Speaker 8: And in addition, like there's there's a point where, you know,

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Speaker 8: for the growth it is like tremendous looking at the

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Speaker 8: peg ratio of the expectations. So if the growth is durable,

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Speaker 8: you know, I think you can see multiple expansion actually

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Speaker 8: from the levels and that's pretty exciting for holders. And

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Speaker 8: in addition that it is the platform that a lot

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Speaker 8: of this AI infancing is going to be built on.

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Speaker 8: I think infancing is going to be much bigger than training,

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Speaker 8: and training is also still growing because of scaling loss.

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Speaker 8: In addition, I would say that like at this valuation,

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Speaker 8: you know, they are doing a capital return program. And

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Speaker 8: so I covered Apple and in Nvidia for t ROW

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Speaker 8: and I was super lucky to get that. I saw, like,

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Speaker 8: you know what Apple did with the return program. You know,

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Speaker 8: it didn't like you know, re rate the stock from

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Speaker 8: day one, but over time, consistent capital turn at that

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Speaker 8: evaluation really expand the multiple. I think within Vidia it

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Speaker 8: could be a similar story where it becomes less cyclical

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Speaker 8: more durable as a result. So I think it's you know,

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Speaker 8: they're doing the right things here with the disclosure as

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Speaker 8: well as, like you know, with the capital turn program.

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Speaker 4: I think just a matter of time here.

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Speaker 2: I think right now in videos trading it like twenty

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Speaker 2: two times forward twelve months earnings, right, I think I'll

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Speaker 2: double check it. Something you just is really interesting, which

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Speaker 2: is basically use of capital. So the frustration with Apple

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Speaker 2: is like do something. And maybe that story is changing

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Speaker 2: with Apple in the handover to John Turnus, but in

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Speaker 2: Nvidia has gone out there and invested in the ecosystem

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Speaker 2: in small increments. Two billion here, two billion dollars there.

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Speaker 2: How does Tony Wong read that strategy of investing.

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Speaker 4: I think it's really smart.

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Speaker 8: I mean, I think that when you're at the frontier

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Speaker 8: of technology, you have to build the ecosystem and bring

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Speaker 8: up the supply chain, bring up the partners. And you know,

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Speaker 8: Video has been really smart in terms of using their

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Speaker 8: free cash flow to extend that it also builds their

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Speaker 8: ecosystem as well as further's the you know, the technology frontier.

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Speaker 4: So I think it's it makes a lot of sense.

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Speaker 8: And you look at the deals they've done in the

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Speaker 8: private markets, they've been pretty good, so like great for shareholders,

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Speaker 8: great for building the ecosystem, and they have excess cash still,

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Speaker 8: so I think that just goes back to like they

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Speaker 8: are like this single architecture platform and there's tremendous leverage

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Speaker 8: on it and you see where the margins are gone,

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Speaker 8: and so that's been their whole whole you know, bed

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Speaker 8: from like day one, I think is that they're an

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Speaker 8: ecosystem company, and I think you're seeing it play through

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Speaker 8: here as they build it out continuously.

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Speaker 2: We actually have a VC on later in the program

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Speaker 2: whose portfolio companies you know, are so tied to in video,

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Speaker 2: and we'll have that conversation just to close the loop.

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Speaker 2: By the way, in video does trade twenty two times

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Speaker 2: forward earnings, but historically it's like nearer to thirty four.

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Speaker 2: Jensen has this equation, more compute equals more tokens equals

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Speaker 2: more revenues. Do you see those revenues coming out the

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Speaker 2: other side for all of Nvidia's customers.

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Speaker 4: Absolutely, yeah, definitely.

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Speaker 8: I know you look at like the cloud demand, you

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Speaker 8: look at pricing for GPUs, I mean these are all

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Speaker 8: GPUs pricing is holding up phenomenally well. And you know

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Speaker 8: you look at like the enterprise demand inflection that's happening,

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Speaker 8: and you see it. You know, we see in our

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Speaker 8: own company we're developing AI solutions and it's eating up

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Speaker 8: a bunch of tokens where you know, we see the promise.

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Speaker 8: Obviously there's experimentation. I think you're seeing that like come

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Speaker 8: through then just real.

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Speaker 2: Quick, like on on on the socials. That's what people

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Speaker 2: just go nuts over right h one hundred, h one

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Speaker 2: hundred pricing right now? Like are you tracking that?

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Speaker 4: Oh?

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Speaker 8: Yeah, yeah, I mean I think you think about the barcase.

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Speaker 8: You know, twenty four months ago it was that like oh,

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Speaker 8: like the obsolescence of video GPUs is like three or

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Speaker 8: four years. Well, well, first of all, the warranty on

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Speaker 8: these things are three or four years, and then also

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Speaker 8: you know, you have that depreciation and so you're able

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Speaker 8: to like adjust the pricing, you know. But even so,

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Speaker 8: like the demand's been so good that you know, we're

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Speaker 8: seeing more value coming out of the older GPUs and

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Speaker 8: even a one hundreds if you were using.

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Speaker 2: Them, even a one hundreds, if you're out there running

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Speaker 2: workloads on a one hundreds, give me a call. I

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Speaker 2: want to know turny one with trow price back on

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Speaker 2: b Tech. Thank you so much. Now coming up, we're

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Speaker 2: gonna hear from airbnbc O Brian Chesky actually on the

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Speaker 2: company's use of AI models from China. That's next. This

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Speaker 2: is Bloomberg Tech. The CEO of Airbnb has defended his

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Speaker 2: company's use of open source AI models from China. Last month,

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Speaker 2: the Congressional Committee asked Airbnb for more information about its

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Speaker 2: use of these models as part of a broader investigation.

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Speaker 2: The committee says it has concerns about the implication for

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Speaker 2: Airbnb's American customers. Here's what Brian Chesky told me in

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Speaker 2: response to that yesterday.

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Speaker 10: We are not a customer of those companies. We're using

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Speaker 10: a variety of different open source models. I just want

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Speaker 10: to say a few things about this matter. Number One,

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Speaker 10: data in privacy is most important to Airbnb. I think

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Speaker 10: anyone who knows knows we have an outstanding track record

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Speaker 10: on data security and privacy. Number two, all of our

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Speaker 10: data is vaulted. No company has access to our data.

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Speaker 10: It is vaulted in Airbnb. Number three, the Congressional Committee

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Speaker 10: has reached out to us.

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Speaker 4: They said they have some questions.

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Speaker 10: We said, we want to coroborate, and so we're in

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Speaker 10: direct contact, in cooperation with them.

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Speaker 2: Airbnbco Brian Chesky in a conversation yesterday, how's everyone doing

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Speaker 2: out there. Let's take a quick check on the markets,

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Speaker 2: and it's taken a little bit of time to kind

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Speaker 2: of find the story now as that one hundred is

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Speaker 2: now down half a percentage point, the socks is basically

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Speaker 2: flat in Nvidia is now firmly lower down two percent.

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Speaker 2: But actually, funny enough, Walmart in its earnings is the

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Speaker 2: biggest points drag at least on the Nasdaq one hundred.

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Speaker 2: We have a lot more to come in the program

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Speaker 2: about Nvidia, about the historic SpaceX S one and a

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Speaker 2: whole lot more. Stay with us because it's halftime in

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Speaker 2: the program, and this is Bloomberg Tech.

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Speaker 9: The world is rebuilding computing for agentic EI, in robotic

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Speaker 9: physical EI.

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Speaker 7: Nvidia sits at the center of these transitions.

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Speaker 2: Welcome back to Bloomberg Tech. That was in Vidia CEO

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Speaker 2: Jensen Wong speaking on the earning score from fiscal second

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Speaker 2: chord of financial year twenty seven earnings. One of the

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Speaker 2: big takeaways from Nvidia's earnings was the rise in demand

435
00:23:25,640 --> 00:23:28,960
Speaker 2: beyond the hyperscalers, Bloomberg Intelligence writing that it was a

436
00:23:28,960 --> 00:23:32,480
Speaker 2: more important signal for the future than in Vidia's signature

437
00:23:32,880 --> 00:23:36,800
Speaker 2: beat and raise. The author of that research, Bloomberg Intelligence

438
00:23:36,880 --> 00:23:41,520
Speaker 2: is congensabani here with us. What is the world outside

439
00:23:41,520 --> 00:23:44,200
Speaker 2: of the hyperscaler? What are we talking about? You know,

440
00:23:44,359 --> 00:23:46,560
Speaker 2: some people would say, oh, this is about companies big

441
00:23:46,600 --> 00:23:49,639
Speaker 2: and small building on prem right, and the Nvidia is

442
00:23:49,640 --> 00:23:52,119
Speaker 2: going to have this whole new customer list that is

443
00:23:52,840 --> 00:23:55,720
Speaker 2: that of that size. It's hard to see. Give me

444
00:23:55,760 --> 00:23:56,600
Speaker 2: the full thesis.

445
00:23:57,600 --> 00:24:00,840
Speaker 11: Yeah, you know that second segment is vial fragmented, but

446
00:24:00,880 --> 00:24:04,120
Speaker 11: people keep missing because it's very diverse. So, first of all,

447
00:24:04,160 --> 00:24:07,080
Speaker 11: it has sob in right, which is itself driving billions

448
00:24:07,080 --> 00:24:10,080
Speaker 11: of dollars of revenue all of the AI neo clouds.

449
00:24:10,080 --> 00:24:12,080
Speaker 11: So when we look at the space in the AI

450
00:24:12,119 --> 00:24:15,520
Speaker 11: neo clouds, that keeps on growing higher and higher, and

451
00:24:15,560 --> 00:24:18,800
Speaker 11: they are becoming now a significant spender of CAPEX, which

452
00:24:18,840 --> 00:24:21,679
Speaker 11: does not get captured in most of the CAPEX discussions

453
00:24:21,680 --> 00:24:24,480
Speaker 11: from the public clouds that we hear. You have all

454
00:24:24,480 --> 00:24:28,240
Speaker 11: of your AI labs up and coming, enterprise and industries

455
00:24:28,320 --> 00:24:32,040
Speaker 11: deployment of on prem AI as well as these data

456
00:24:32,040 --> 00:24:35,479
Speaker 11: center you know, guys who run the data centers are

457
00:24:35,520 --> 00:24:38,800
Speaker 11: now becoming much more high GPU based AI data center

458
00:24:38,840 --> 00:24:42,359
Speaker 11: cloud renters. So this fifty percent, which is expected to

459
00:24:42,359 --> 00:24:45,480
Speaker 11: grow faster than the top hyperscaler segment, by the way,

460
00:24:45,840 --> 00:24:48,920
Speaker 11: is getting more and more significant, especially for n Media,

461
00:24:48,960 --> 00:24:52,080
Speaker 11: because this is where you have the least competition. The

462
00:24:52,160 --> 00:24:55,520
Speaker 11: A six and the TPUs and the traineums don't compete

463
00:24:55,560 --> 00:24:58,520
Speaker 11: in this segment, so it's purely monopolistic for Nvidia, and

464
00:24:58,720 --> 00:25:02,280
Speaker 11: Media gets the highest stack attached to it means they

465
00:25:02,280 --> 00:25:04,440
Speaker 11: can sell a lot more of their networking and their

466
00:25:04,480 --> 00:25:07,320
Speaker 11: other components here and they get the best margins in

467
00:25:07,359 --> 00:25:07,840
Speaker 11: this segment.

468
00:25:09,440 --> 00:25:12,040
Speaker 2: I think during the call there was an attempt to

469
00:25:12,119 --> 00:25:16,080
Speaker 2: clarify that that kind of mysterious one trillion dollar figure.

470
00:25:16,480 --> 00:25:19,040
Speaker 2: So it runs calendar twenty five to the end of

471
00:25:19,040 --> 00:25:22,560
Speaker 2: twenty seven. It is Blackwell and Reuben Systems, but it

472
00:25:22,680 --> 00:25:26,520
Speaker 2: excludes Veri CPU and some of the other networking components

473
00:25:26,520 --> 00:25:30,280
Speaker 2: you were just talking about. I always come to you.

474
00:25:30,119 --> 00:25:33,080
Speaker 2: You always have your feet on the ground, right, It

475
00:25:33,080 --> 00:25:35,040
Speaker 2: doesn't really matter what the number is that hits on

476
00:25:35,080 --> 00:25:38,040
Speaker 2: the second quarter, ninety one billion pus minus two percent.

477
00:25:38,480 --> 00:25:41,080
Speaker 2: That number, the one trillion, give me your kind of

478
00:25:41,200 --> 00:25:43,280
Speaker 2: like base level understanding of it.

479
00:25:44,560 --> 00:25:47,239
Speaker 11: Yeah, all it includes is just the black Bell and

480
00:25:47,280 --> 00:25:50,480
Speaker 11: the Vera rubin the full stack that is going to

481
00:25:50,520 --> 00:25:51,760
Speaker 11: start ramping in three Q.

482
00:25:52,480 --> 00:25:53,400
Speaker 2: That's all it includes.

483
00:25:53,440 --> 00:25:56,399
Speaker 11: It does not include, like you mentioned, that twenty billion

484
00:25:56,520 --> 00:25:59,880
Speaker 11: CPU stand alone that they mentioned, right for twenty six

485
00:26:00,040 --> 00:26:03,040
Speaker 11: and twenty seven. It does not include the grap based

486
00:26:03,160 --> 00:26:06,159
Speaker 11: LPX server. It does not include the new launch of

487
00:26:06,240 --> 00:26:10,639
Speaker 11: their storage based CPX servers and a few other networking components.

488
00:26:10,680 --> 00:26:13,760
Speaker 11: So a lot of good, creamy revenues are not included

489
00:26:13,840 --> 00:26:16,160
Speaker 11: in that. The one trillion number, by the way, based

490
00:26:16,160 --> 00:26:18,879
Speaker 11: on our estimate, is rising so we think now it

491
00:26:18,960 --> 00:26:21,439
Speaker 11: will be an upside to one trillion plus all these

492
00:26:21,480 --> 00:26:23,639
Speaker 11: other list of items that are outlisted could be an

493
00:26:23,680 --> 00:26:24,240
Speaker 11: upside to.

494
00:26:24,200 --> 00:26:25,240
Speaker 4: That for revenues.

495
00:26:26,320 --> 00:26:29,720
Speaker 2: Congensubarnie from Blueberg Intelligence. Your research is always the go

496
00:26:29,880 --> 00:26:32,520
Speaker 2: to man. Thanks so much. That's far deeper into the

497
00:26:32,560 --> 00:26:36,000
Speaker 2: Nvidia story. But also like the market reaction with Anna Rathmann,

498
00:26:36,119 --> 00:26:39,879
Speaker 2: founder and CEO Agred of Deller Advisory, you know what

499
00:26:40,000 --> 00:26:44,560
Speaker 2: we get ourselves into these frenzies. Well, like the Nvidia earnings,

500
00:26:44,560 --> 00:26:47,480
Speaker 2: they're gonna hit, and they hit right, and you get

501
00:26:47,480 --> 00:26:50,040
Speaker 2: the red headline on the Bloomberg and it's ninety one

502
00:26:50,040 --> 00:26:52,960
Speaker 2: billion dollars plus or minus two percent, and then everyone

503
00:26:52,960 --> 00:26:54,959
Speaker 2: goes But it doesn't even matter what the number is.

504
00:26:55,440 --> 00:26:58,639
Speaker 2: It's everything else you're in the markets. Why do we

505
00:26:58,720 --> 00:26:59,520
Speaker 2: behave like that?

506
00:27:00,400 --> 00:27:01,760
Speaker 7: It's lonely at the top.

507
00:27:02,000 --> 00:27:04,280
Speaker 12: I mean, when you're the largest company in the world,

508
00:27:04,680 --> 00:27:06,680
Speaker 12: I don't think there's anything you can do to surprise

509
00:27:06,760 --> 00:27:10,959
Speaker 12: investors to the upside. So you've become a company that

510
00:27:11,040 --> 00:27:13,920
Speaker 12: needs to defend itself. And Vidia hit it out of

511
00:27:13,920 --> 00:27:17,000
Speaker 12: the park in many ways, in almost all the ways

512
00:27:17,000 --> 00:27:19,120
Speaker 12: that we expected them to, not only in the top

513
00:27:19,160 --> 00:27:22,680
Speaker 12: line and earnings, but also you know, networking business growing

514
00:27:22,800 --> 00:27:26,600
Speaker 12: as well as diversifying its customer base. Everything we've asked for,

515
00:27:26,760 --> 00:27:29,200
Speaker 12: they've given us. But I think there are other things

516
00:27:29,280 --> 00:27:32,919
Speaker 12: like is the growth actually slowing? Is the growth what

517
00:27:32,920 --> 00:27:35,760
Speaker 12: we've been expecting for the last two or three years?

518
00:27:36,080 --> 00:27:38,760
Speaker 12: And that's the question that I don't think and Video

519
00:27:38,840 --> 00:27:42,560
Speaker 12: was able to answer. And the dividend increase, to me,

520
00:27:42,920 --> 00:27:46,080
Speaker 12: was a big signal that what the investors had been

521
00:27:46,119 --> 00:27:48,880
Speaker 12: worrying about might be coming true.

522
00:27:49,320 --> 00:27:51,760
Speaker 2: Okay, I actually I apologize to my team in the

523
00:27:51,760 --> 00:27:53,480
Speaker 2: control room. I'm going to do the opposite of what

524
00:27:53,600 --> 00:27:56,280
Speaker 2: I just said. Okay, let's linger, then, let's linger on

525
00:27:56,680 --> 00:27:57,960
Speaker 2: the shareholder returns.

526
00:27:58,960 --> 00:27:59,399
Speaker 4: What were you.

527
00:27:59,400 --> 00:28:01,080
Speaker 2: Getting at there? Give me a little bit more.

528
00:28:01,440 --> 00:28:04,600
Speaker 12: Yeah, so you know, the buybacks, it's not that big,

529
00:28:04,680 --> 00:28:07,919
Speaker 12: because if you're a multi trillion dollar company, eighty billion

530
00:28:08,000 --> 00:28:11,639
Speaker 12: isn't that huge. See, it was really the dividend side

531
00:28:11,680 --> 00:28:13,879
Speaker 12: of it. When a company starts to return to events,

532
00:28:14,000 --> 00:28:18,160
Speaker 12: that's a multi year commitment, right. So that means while

533
00:28:18,200 --> 00:28:20,919
Speaker 12: maybe we're not going to be finding other areas to

534
00:28:21,040 --> 00:28:23,600
Speaker 12: invest in, we're just going to be returning some cash

535
00:28:23,600 --> 00:28:27,359
Speaker 12: to the investors and that's a signal for growth companies

536
00:28:27,400 --> 00:28:30,040
Speaker 12: that says, Okay, maybe we're not going to be growing

537
00:28:30,080 --> 00:28:33,439
Speaker 12: as fast as you had anticipated. So that was a

538
00:28:33,560 --> 00:28:36,480
Speaker 12: small signal. We'll see what happens. I still think in

539
00:28:36,600 --> 00:28:39,080
Speaker 12: video is going to continue to grow because of this

540
00:28:39,280 --> 00:28:42,520
Speaker 12: massive ecosystem there at the center of but it was

541
00:28:42,560 --> 00:28:46,400
Speaker 12: definitely a signal, maybe a small one, but a certain one.

542
00:28:47,120 --> 00:28:49,680
Speaker 2: We're sharing this image on the screen, right, and we

543
00:28:49,720 --> 00:28:52,600
Speaker 2: went into this earnings prior to them hitting saying two things.

544
00:28:53,000 --> 00:28:57,080
Speaker 2: Everyone expects a beaten raised situation, but also it doesn't

545
00:28:57,080 --> 00:29:01,040
Speaker 2: really matter historically what in Vidia says that data. I

546
00:29:01,080 --> 00:29:03,400
Speaker 2: appreciate there's a lot there is how the S and

547
00:29:03,440 --> 00:29:05,680
Speaker 2: P five hundred trades in the days and months that

548
00:29:05,800 --> 00:29:09,720
Speaker 2: follow in Nvidia earnings even when they beat big and

549
00:29:09,760 --> 00:29:12,040
Speaker 2: there's no guarantee that the market is going to sort

550
00:29:12,040 --> 00:29:17,080
Speaker 2: of respond with euphoria, you know, does that matter anymore?

551
00:29:17,120 --> 00:29:19,880
Speaker 2: This kind of story that the index level, given in

552
00:29:19,960 --> 00:29:22,600
Speaker 2: Vidia's size and scale, that was kind of what we

553
00:29:22,600 --> 00:29:23,640
Speaker 2: were all bracing for.

554
00:29:24,200 --> 00:29:26,640
Speaker 12: Yeah, I mean it matters because of its size, right,

555
00:29:26,680 --> 00:29:29,160
Speaker 12: the largest company behaving this way is going to have

556
00:29:29,200 --> 00:29:33,000
Speaker 12: an impact on the index. Now, this reminds me of

557
00:29:32,600 --> 00:29:36,200
Speaker 12: how Apple used to behave about ten plus years ago.

558
00:29:36,440 --> 00:29:39,800
Speaker 12: There is nothing that Apple could do to satisfy investors.

559
00:29:40,160 --> 00:29:42,880
Speaker 12: The market would actually punish them for it. So I

560
00:29:42,880 --> 00:29:45,200
Speaker 12: think this is just what happens when you are at

561
00:29:45,240 --> 00:29:49,120
Speaker 12: the top and you have high investors have high expectations

562
00:29:49,160 --> 00:29:51,080
Speaker 12: of you, and if you happen to have a high

563
00:29:51,120 --> 00:29:53,880
Speaker 12: concentration in the index, you can take everyone down with you.

564
00:29:56,520 --> 00:29:58,840
Speaker 2: It's really really tempting always to look at how a

565
00:29:58,920 --> 00:30:01,520
Speaker 2: stock trades in the moment and try and find the story.

566
00:30:02,040 --> 00:30:03,840
Speaker 2: But what I would also say is that, you know,

567
00:30:03,880 --> 00:30:07,040
Speaker 2: if you think about last Friday, Monday Tuesday, when the

568
00:30:07,040 --> 00:30:10,720
Speaker 2: President of the United States returned from China, in Vidia

569
00:30:10,880 --> 00:30:14,400
Speaker 2: and in the sector, the socks were close to correction territory,

570
00:30:15,200 --> 00:30:17,440
Speaker 2: you know we're down again now post learnings on video.

571
00:30:17,680 --> 00:30:19,480
Speaker 2: What lesson would you learn from that?

572
00:30:20,480 --> 00:30:21,800
Speaker 7: You know, there are two things.

573
00:30:21,800 --> 00:30:25,640
Speaker 12: I think the reaction today really is about Nvidia itself.

574
00:30:25,680 --> 00:30:27,480
Speaker 12: It's not even about the AI industry.

575
00:30:27,560 --> 00:30:28,480
Speaker 7: It's about Nvidia.

576
00:30:29,160 --> 00:30:33,600
Speaker 12: Friday was a huge disappointment, and since then we've learned

577
00:30:33,760 --> 00:30:38,160
Speaker 12: that China actually banned the gaming chips while Jensen Huang

578
00:30:38,280 --> 00:30:41,760
Speaker 12: was there. So when we're looking at China and Nvidia.

579
00:30:42,280 --> 00:30:44,640
Speaker 12: It's not a reliable market as much as is the

580
00:30:44,680 --> 00:30:47,560
Speaker 12: market that we would like to be in. So it

581
00:30:47,600 --> 00:30:49,760
Speaker 12: is I think right for Jensen Wang to sort of

582
00:30:49,800 --> 00:30:52,640
Speaker 12: pay attention to other areas in which they can expand

583
00:30:53,200 --> 00:30:58,080
Speaker 12: think about sovereign ais outside of China really and I

584
00:30:58,120 --> 00:31:02,320
Speaker 12: think China would be sort of a and upside optionality

585
00:31:02,400 --> 00:31:05,240
Speaker 12: if it happens, But that if is a very big if.

586
00:31:06,720 --> 00:31:10,080
Speaker 2: Nana Rathban, founder and CEO of Grenada Advisory, thank you

587
00:31:10,160 --> 00:31:12,600
Speaker 2: very much. Now coming up, we're going to be joined

588
00:31:12,600 --> 00:31:15,960
Speaker 2: by Saragwark from Conviction to drill down on kind of

589
00:31:16,000 --> 00:31:19,640
Speaker 2: the impact of Nvidia on a much broader ecosystem of startups.

590
00:31:19,920 --> 00:31:23,680
Speaker 2: These are companies of all sizes that use the compute

591
00:31:24,000 --> 00:31:28,280
Speaker 2: or the library of data and models themselves. Can't wait,

592
00:31:28,320 --> 00:31:37,240
Speaker 2: this is Bloomberg Tech. Let's get back to video earnings.

593
00:31:37,320 --> 00:31:39,760
Speaker 2: A part of Jensen Wong's latest message to investors in

594
00:31:39,880 --> 00:31:42,840
Speaker 2: video isn't just selling chips to big tech anymore. It's

595
00:31:42,920 --> 00:31:46,000
Speaker 2: applying the picks and shovels for an AI goal rush,

596
00:31:46,000 --> 00:31:51,880
Speaker 2: where startups are building everything from AI agents to humanoid robots, robotaxis,

597
00:31:51,920 --> 00:31:55,080
Speaker 2: everything in between. But on in video compute joining us.

598
00:31:55,120 --> 00:31:57,760
Speaker 2: One of the key backers of that ecosystem, Seragwark, founder

599
00:31:57,880 --> 00:32:01,040
Speaker 2: of Conviction, an AI native venture firm, And I think

600
00:32:01,120 --> 00:32:04,320
Speaker 2: that's true, right. I think the best place I think

601
00:32:04,360 --> 00:32:06,960
Speaker 2: to start with you is think about all your portfolio companies.

602
00:32:07,360 --> 00:32:09,440
Speaker 2: Many of them come on the show and we say, Okay,

603
00:32:09,520 --> 00:32:12,480
Speaker 2: what's the biggest constraint on you right now? Where are

604
00:32:12,480 --> 00:32:16,160
Speaker 2: you most focused? And oftentimes it is compute And they're

605
00:32:16,200 --> 00:32:19,200
Speaker 2: sometimes super proud that they are working on in video gear.

606
00:32:19,960 --> 00:32:23,360
Speaker 2: But are they accessing that compute through the cloud provider

607
00:32:23,720 --> 00:32:26,600
Speaker 2: or are they able to get the cluster themselves direct control?

608
00:32:27,120 --> 00:32:29,480
Speaker 13: It depends on what they're trying to do, right. We

609
00:32:29,560 --> 00:32:33,520
Speaker 13: have companies that are you know, building at the infrastructure layer,

610
00:32:33,560 --> 00:32:35,880
Speaker 13: building at the model layer, building at the application layer.

611
00:32:36,200 --> 00:32:37,720
Speaker 13: One of the first things we did when we started

612
00:32:37,760 --> 00:32:40,560
Speaker 13: the fund was go buy compute for our companies, just

613
00:32:40,600 --> 00:32:42,480
Speaker 13: because we can take the timing risk as a venture

614
00:32:42,480 --> 00:32:44,800
Speaker 13: fund and we conclude it exactly what you just described,

615
00:32:44,840 --> 00:32:48,480
Speaker 13: which is they're all going to need it, right and.

616
00:32:48,040 --> 00:32:49,720
Speaker 2: What did that look like, Sarah? Sorry to interrupt you,

617
00:32:49,720 --> 00:32:52,560
Speaker 2: but like maybe literally.

618
00:32:51,560 --> 00:32:54,640
Speaker 13: We went and bought you know, h one hundreds at

619
00:32:54,640 --> 00:32:59,040
Speaker 13: the time a bunch of nodes cloud. But the point was, like,

620
00:32:59,160 --> 00:33:02,880
Speaker 13: you know, the market is gone through different shortages and

621
00:33:03,040 --> 00:33:06,800
Speaker 13: now people are predicting a lot of ongoing constrained supply,

622
00:33:07,280 --> 00:33:09,640
Speaker 13: and we were worried about access for startups in that

623
00:33:09,640 --> 00:33:12,480
Speaker 13: period of time, which is why we did it. But

624
00:33:13,000 --> 00:33:17,440
Speaker 13: our companies, to your actual question, if almost all of

625
00:33:17,480 --> 00:33:20,680
Speaker 13: them want want to do experimentation and they all start

626
00:33:20,720 --> 00:33:24,120
Speaker 13: with frontier performance, which is in vidio chips today, right,

627
00:33:24,120 --> 00:33:27,040
Speaker 13: because that allows you to do new things. And then

628
00:33:27,200 --> 00:33:31,960
Speaker 13: as these companies mature, they tend to post train smaller models,

629
00:33:32,080 --> 00:33:35,960
Speaker 13: think about cost, think about how to be able to

630
00:33:37,160 --> 00:33:38,880
Speaker 13: even just being able to use more tokens on the

631
00:33:38,920 --> 00:33:41,800
Speaker 13: same task allows you to change the user experience. But

632
00:33:41,880 --> 00:33:44,200
Speaker 13: everybody wants to start with current generationships.

633
00:33:45,160 --> 00:33:49,240
Speaker 2: The state of play that Jensen describes is demand vastly

634
00:33:49,360 --> 00:33:53,240
Speaker 2: outpacing Nvidia, but also in aggregate the industry's ability to

635
00:33:53,480 --> 00:33:56,000
Speaker 2: supply on the other side of the table. Would you

636
00:33:56,080 --> 00:33:58,480
Speaker 2: say that that state of play is true for the

637
00:33:58,520 --> 00:34:01,800
Speaker 2: founders that you're trying to help, right, It's.

638
00:34:01,680 --> 00:34:07,160
Speaker 13: Probably been a two quarters of increasing stress in the

639
00:34:07,160 --> 00:34:11,319
Speaker 13: ecosystem about access to supply at different scales. Wow, and

640
00:34:11,360 --> 00:34:13,800
Speaker 13: so I, you know, have spent a good amount of

641
00:34:13,840 --> 00:34:18,120
Speaker 13: time with the leaders of companies that you know, serve

642
00:34:18,200 --> 00:34:22,520
Speaker 13: in video chips, in cloud asking to buy one hundred

643
00:34:22,520 --> 00:34:26,399
Speaker 13: million dollars of a time of compute. And I've never

644
00:34:26,400 --> 00:34:28,960
Speaker 13: been in that scenario before. We're trying very hard to

645
00:34:28,960 --> 00:34:31,800
Speaker 13: pay somebody a lot of money with a multi year commitment. Yeah,

646
00:34:31,920 --> 00:34:34,279
Speaker 13: and it just speaks to the shortage dynamics. I think

647
00:34:34,280 --> 00:34:37,880
Speaker 13: it's very hard to get on demand small scale compute

648
00:34:38,000 --> 00:34:41,080
Speaker 13: right now, which is what many starts are starting with,

649
00:34:41,200 --> 00:34:46,040
Speaker 13: as you we're describing, And so I think the shortage

650
00:34:46,120 --> 00:34:49,680
Speaker 13: dynamic is real. And what is more interesting to me is,

651
00:34:51,960 --> 00:34:56,560
Speaker 13: you know, in Nvidia have this amazing outperformance on the

652
00:34:56,600 --> 00:35:01,239
Speaker 13: earning side, and Jensen will repeatedly tell people demand is parabolic.

653
00:35:01,640 --> 00:35:05,319
Speaker 13: Humans struggle to consume that. And you know, it's hard

654
00:35:05,360 --> 00:35:07,799
Speaker 13: to feel bad for Jensen, Juan Jensen's winner in all

655
00:35:07,840 --> 00:35:11,920
Speaker 13: of this, but you know he's like, yeah, yeah, but

656
00:35:12,200 --> 00:35:16,319
Speaker 13: like and his amazing leader. But he's like, I'm telling you,

657
00:35:16,760 --> 00:35:20,080
Speaker 13: honestly the reality of what I project repeatedly, and you

658
00:35:20,160 --> 00:35:22,319
Speaker 13: just keep not believing me. Yeah, right, And I'd say,

659
00:35:22,360 --> 00:35:25,680
Speaker 13: like I believe him. From the demand side, because what

660
00:35:25,719 --> 00:35:30,279
Speaker 13: I expect will happen is this, you know, massive exponential

661
00:35:30,320 --> 00:35:33,040
Speaker 13: growth that shows up in things like Claude code revenue

662
00:35:33,800 --> 00:35:36,919
Speaker 13: is really because you have long horizon agents that people

663
00:35:36,960 --> 00:35:39,560
Speaker 13: are using in this one use case already. But the

664
00:35:39,600 --> 00:35:43,160
Speaker 13: world is not just code, right, and so if there's zero,

665
00:35:43,400 --> 00:35:46,280
Speaker 13: not zero, but small scale a few billion to forty

666
00:35:46,360 --> 00:35:49,760
Speaker 13: billion of revenue and a very small number of months

667
00:35:50,000 --> 00:35:53,040
Speaker 13: because we figured out how to use the models more

668
00:35:53,080 --> 00:35:55,719
Speaker 13: productively on long horizon agent tasks. We're going to do

669
00:35:55,760 --> 00:35:58,520
Speaker 13: that for lots of different functions in the knowledge economy.

670
00:35:59,440 --> 00:36:02,480
Speaker 2: While you here, if you don't mind, like SPACEXS one.

671
00:36:02,400 --> 00:36:05,080
Speaker 7: Wow, yes, wow, it's inspiring.

672
00:36:05,120 --> 00:36:07,160
Speaker 2: You have a big event today right where I believe

673
00:36:07,200 --> 00:36:09,080
Speaker 2: like some of the cursor guys will be there, and

674
00:36:09,160 --> 00:36:12,680
Speaker 2: so we learn a little bit about that. But there's

675
00:36:12,719 --> 00:36:16,080
Speaker 2: this number total addressable market for AI twenty six point

676
00:36:16,160 --> 00:36:19,880
Speaker 2: five trillion dollars super focused on enterprise. You know they

677
00:36:19,920 --> 00:36:23,080
Speaker 2: literally label it as such in the in the deck

678
00:36:24,520 --> 00:36:25,760
Speaker 2: go ahead, I mean.

679
00:36:25,800 --> 00:36:29,000
Speaker 13: Yeah, I think it's it's a it's a funny number.

680
00:36:29,040 --> 00:36:30,960
Speaker 13: And then like a funny you know diagram when you

681
00:36:31,040 --> 00:36:35,440
Speaker 13: visualize the tan because it's like starlink. And then enterprising Yeah, yeah, yeah,

682
00:36:35,440 --> 00:36:37,799
Speaker 13: and you know, much of what we invest in is

683
00:36:37,920 --> 00:36:41,360
Speaker 13: enterprise AI. My friend Andre Carpathi described this well, which

684
00:36:41,400 --> 00:36:44,880
Speaker 13: is the simplest way to think about the use of

685
00:36:44,920 --> 00:36:49,200
Speaker 13: AI is automation. Right, there's automation of tasks we already do, right,

686
00:36:49,760 --> 00:36:52,120
Speaker 13: And if we give these models the tools and the

687
00:36:52,160 --> 00:36:55,000
Speaker 13: harness such that they can do these tasks, they can

688
00:36:55,040 --> 00:36:58,600
Speaker 13: take over things for us. And so I do think

689
00:36:58,640 --> 00:37:02,200
Speaker 13: that the the opportunity.

690
00:37:01,640 --> 00:37:04,239
Speaker 2: Is as big as does Elon believe the opportunity or

691
00:37:04,320 --> 00:37:07,640
Speaker 2: is this him trying to justify why SpaceX took XAI.

692
00:37:08,040 --> 00:37:11,080
Speaker 13: I think it's interesting that you know, what you put

693
00:37:11,120 --> 00:37:13,759
Speaker 13: in the S one is a choice, right, And he

694
00:37:13,800 --> 00:37:17,600
Speaker 13: could have easily just said, you know, like something broader

695
00:37:18,080 --> 00:37:21,200
Speaker 13: or you know, focus on other parts of the SpaceX

696
00:37:21,239 --> 00:37:24,279
Speaker 13: tam overall. But he is making a commitment that we

697
00:37:24,320 --> 00:37:28,440
Speaker 13: are going to go make you know, our offerings relevant

698
00:37:28,480 --> 00:37:31,320
Speaker 13: in enterprise AI. And so I think he's very committed

699
00:37:31,360 --> 00:37:31,719
Speaker 13: to Yes, so.

700
00:37:31,760 --> 00:37:33,399
Speaker 2: No, you think he will pull it off.

701
00:37:34,960 --> 00:37:38,000
Speaker 13: So there's a question about whether the value is infrastructure

702
00:37:38,160 --> 00:37:41,040
Speaker 13: models or applications. And see this in the you know,

703
00:37:41,120 --> 00:37:43,560
Speaker 13: Anthropic deal and the Cursor deal as well.

704
00:37:44,120 --> 00:37:45,239
Speaker 7: They have the infrastructure.

705
00:37:45,320 --> 00:37:49,840
Speaker 13: The infrastructure and the capability to build more is extraordinarily valuable.

706
00:37:50,239 --> 00:37:52,440
Speaker 13: And I think the question will be, like, I think

707
00:37:52,480 --> 00:37:54,000
Speaker 13: he's going to make money on that. No matter what

708
00:37:54,040 --> 00:37:56,319
Speaker 13: the question is, do they also need to own the

709
00:37:56,360 --> 00:37:57,680
Speaker 13: model and the application layer?

710
00:37:57,880 --> 00:38:00,359
Speaker 2: To Sarah's point, yes, one said the Anthropic would pay

711
00:38:00,880 --> 00:38:03,520
Speaker 2: SpaceX one point two five billion dollars per month through

712
00:38:03,560 --> 00:38:07,160
Speaker 2: twenty nine for compute ceregor of conviction across every part

713
00:38:07,200 --> 00:38:09,680
Speaker 2: of it. Thank you very much. All right, a lot

714
00:38:09,680 --> 00:38:11,920
Speaker 2: more to come still in the malts of the program,

715
00:38:12,040 --> 00:38:14,879
Speaker 2: we'll be breaking down two blockbuster IPOs on the docket too,

716
00:38:15,360 --> 00:38:30,600
Speaker 2: SpaceX and Open AI. Maybe this is Bloomberg Tech, Let's

717
00:38:30,600 --> 00:38:33,480
Speaker 2: get back to SpaceX. In addition to the company's blockbuster

718
00:38:33,560 --> 00:38:38,239
Speaker 2: IPO filing, investors are also closely watching tonight's highly anticipated

719
00:38:38,280 --> 00:38:42,439
Speaker 2: starship launch. The mission marks SpaceX twelfth major starship test flight,

720
00:38:42,719 --> 00:38:45,719
Speaker 2: a critical milestone as the company pushes to advance its

721
00:38:45,719 --> 00:38:49,520
Speaker 2: next gen rocket program while preparing for what could become

722
00:38:49,760 --> 00:38:52,600
Speaker 2: the biggest IPO in history. Bloomberg Suna passion kar joins

723
00:38:52,640 --> 00:38:54,879
Speaker 2: us now and you're probably sick of me, right, Sana,

724
00:38:54,960 --> 00:38:57,040
Speaker 2: because how many times did I post in the blog

725
00:38:58,080 --> 00:39:01,560
Speaker 2: Starship is central to all of this. It said it

726
00:39:01,960 --> 00:39:04,640
Speaker 2: in the s one could not be more clear. Let's

727
00:39:04,640 --> 00:39:06,960
Speaker 2: start with tonight's test. What are we expecting, what does

728
00:39:07,000 --> 00:39:10,040
Speaker 2: it look like? How long does it run for? Right?

729
00:39:10,200 --> 00:39:14,319
Speaker 14: So today, you know, Starship is slated to take off

730
00:39:14,360 --> 00:39:17,680
Speaker 14: from the launch pad at Starbase, Texas at around six

731
00:39:17,760 --> 00:39:21,880
Speaker 14: thirty pm ET five thirty pm Texas time. It's going

732
00:39:21,960 --> 00:39:24,719
Speaker 14: to take off, ignite it's Raptor engines, and lift off

733
00:39:24,719 --> 00:39:28,360
Speaker 14: into space. It is debuting an upgraded version of the vehicle,

734
00:39:28,400 --> 00:39:32,640
Speaker 14: it's called Version three that has upgraded engines. It's supposed

735
00:39:32,680 --> 00:39:36,759
Speaker 14: to have improved power and capability. It's going to yeah,

736
00:39:36,800 --> 00:39:39,319
Speaker 14: lift off into space, lap around the globe, and then

737
00:39:39,400 --> 00:39:42,200
Speaker 14: eventually splash down into the Indian Ocean. And you know,

738
00:39:42,239 --> 00:39:44,880
Speaker 14: as you were mentioning ed, this is a really crucial

739
00:39:44,960 --> 00:39:48,279
Speaker 14: test for this vehicle. That is just you know, so

740
00:39:49,160 --> 00:39:53,239
Speaker 14: important for all of Elon Musk's ambitions for SpaceX and

741
00:39:53,400 --> 00:39:55,800
Speaker 14: you know the valuation of the company for the coming IPO.

742
00:39:56,080 --> 00:39:58,399
Speaker 2: So let's talk a little bit about those ambitions, right.

743
00:39:58,480 --> 00:40:01,200
Speaker 2: The idea is that Starship is capable of carrying a

744
00:40:01,280 --> 00:40:05,680
Speaker 2: much greater payload to orbit. So I think starlink, think

745
00:40:05,760 --> 00:40:08,440
Speaker 2: space based data center and humans getting to Mars. Explain

746
00:40:08,480 --> 00:40:08,920
Speaker 2: it to us.

747
00:40:09,920 --> 00:40:14,239
Speaker 14: Yeah, yeah, totally. So you know, Starship has kind of

748
00:40:14,239 --> 00:40:17,000
Speaker 14: the payload capacity that will enable something, let's start with

749
00:40:17,120 --> 00:40:21,080
Speaker 14: orbital data centers. It will enable an orbital data center

750
00:40:21,160 --> 00:40:24,080
Speaker 14: of you know, as many as one million spacecraft orbiting

751
00:40:24,080 --> 00:40:26,759
Speaker 14: the Earth, which is what you know SpaceX has said

752
00:40:26,800 --> 00:40:30,680
Speaker 14: they want to do. You can't do that to scale

753
00:40:30,760 --> 00:40:33,760
Speaker 14: as well with the Falcon rockets. There are current rockets.

754
00:40:33,760 --> 00:40:38,640
Speaker 14: You really need much larger vehicle that can carry sixty

755
00:40:38,920 --> 00:40:42,640
Speaker 14: satellites to space, and so you know it will they

756
00:40:42,640 --> 00:40:46,480
Speaker 14: will need Starship to effectively build these orbital data centers

757
00:40:46,560 --> 00:40:49,040
Speaker 14: at a timeline and a pace that really makes sense

758
00:40:49,080 --> 00:40:52,080
Speaker 14: and could actually lead to a profit one day to

759
00:40:52,160 --> 00:40:55,480
Speaker 14: get humans to Moon, to the Moon and mariners. You

760
00:40:55,480 --> 00:40:58,440
Speaker 14: will also need, you know, that type of capability, that

761
00:40:58,520 --> 00:41:02,480
Speaker 14: type of thrust. Starship is advertised as the most powerful

762
00:41:02,560 --> 00:41:05,960
Speaker 14: rocket ever Bill and you know, Starship is so important

763
00:41:05,960 --> 00:41:09,560
Speaker 14: to SpaceX's ambitions, but it's also key to America space

764
00:41:09,560 --> 00:41:14,120
Speaker 14: ambitions because Starship has a contract. SpaceX has a contract

765
00:41:14,120 --> 00:41:17,000
Speaker 14: with NASA for Starship to land humans on the mod.

766
00:41:17,800 --> 00:41:21,080
Speaker 2: Bloomberg Senta passion card, Thank you very much. Fresh off

767
00:41:21,120 --> 00:41:23,719
Speaker 2: a courtroom win over Elon Musk, the race for the

768
00:41:23,760 --> 00:41:27,319
Speaker 2: trillion dollar AI mega ipo is on. Did you have

769
00:41:27,360 --> 00:41:29,839
Speaker 2: this on your bingo cards? Sources say Open AI may

770
00:41:29,920 --> 00:41:33,640
Speaker 2: make a confidential filing as soon as this Friday, joining

771
00:41:33,680 --> 00:41:37,560
Speaker 2: us now with the details Bloomberg Sharen Gafari yesterday afternoon.

772
00:41:37,680 --> 00:41:39,719
Speaker 2: It's the last thing anyone needed was to see that

773
00:41:39,800 --> 00:41:43,600
Speaker 2: headline here. But the timing is interesting. What do we

774
00:41:43,640 --> 00:41:45,920
Speaker 2: know about an Open AI path to an IPO?

775
00:41:47,239 --> 00:41:51,160
Speaker 15: That's right, So an opening filing would be a confidential filing,

776
00:41:51,239 --> 00:41:53,760
Speaker 15: could come as soon as Friday or in the coming weeks.

777
00:41:54,800 --> 00:41:58,880
Speaker 15: That would obviously put it in a close competition with Anthropic,

778
00:41:58,960 --> 00:42:03,160
Speaker 15: which is also expected to potentially file this fall, as

779
00:42:03,200 --> 00:42:05,279
Speaker 15: well as SpaceX, which is already out there with the

780
00:42:05,400 --> 00:42:06,000
Speaker 15: S one listing.

781
00:42:06,080 --> 00:42:08,080
Speaker 2: Yeah, I'm going to let us put SpaceX to one

782
00:42:08,120 --> 00:42:09,719
Speaker 2: side for a second. So let's say it's a race

783
00:42:09,960 --> 00:42:13,920
Speaker 2: open Irononthropic for September October. What do we know about

784
00:42:14,120 --> 00:42:17,239
Speaker 2: about that timeline? But also the numbers involved? Right, do

785
00:42:17,280 --> 00:42:20,359
Speaker 2: we have a sense of valuation or whatever company wants

786
00:42:20,360 --> 00:42:20,719
Speaker 2: to raise?

787
00:42:21,280 --> 00:42:25,720
Speaker 15: That's right, So the valuations are already you know, nearing

788
00:42:25,760 --> 00:42:28,480
Speaker 15: a trillion right. Open Ai was last value valued it

789
00:42:28,520 --> 00:42:31,720
Speaker 15: over eight hundred and fifty billion just earlier this spring.

790
00:42:32,120 --> 00:42:36,520
Speaker 15: Anthropic similarly also you know, in talks to raise ad

791
00:42:36,760 --> 00:42:40,600
Speaker 15: up to nine hundred valuation, as we've reported. So when

792
00:42:40,600 --> 00:42:44,320
Speaker 15: we're thinking about an IPO months out, you can only

793
00:42:44,400 --> 00:42:47,160
Speaker 15: you know, you would hope that for these companies at

794
00:42:47,239 --> 00:42:49,359
Speaker 15: least they're thinking they want to go further north of that,

795
00:42:49,400 --> 00:42:51,719
Speaker 15: getting us closer to potentially that trillion mark.

796
00:42:51,960 --> 00:42:54,080
Speaker 2: There's an idea that when Elon Musk was told by

797
00:42:54,080 --> 00:42:56,080
Speaker 2: the jury and judge he's not allowed to perceive as

798
00:42:56,120 --> 00:42:58,960
Speaker 2: his suit, it removed an overhang to open Ai, let

799
00:42:58,960 --> 00:43:02,759
Speaker 2: them kind of proceed their ambitions. But why does open

800
00:43:02,800 --> 00:43:04,600
Speaker 2: Ai want to go public? I know it seems silly,

801
00:43:04,640 --> 00:43:07,319
Speaker 2: but do they need money? Is it the public perception thing?

802
00:43:07,400 --> 00:43:08,840
Speaker 2: Is it always been in the plans.

803
00:43:09,280 --> 00:43:11,120
Speaker 15: It's a good question because on the one hand, these

804
00:43:11,120 --> 00:43:14,000
Speaker 15: companies like open Ai in Anthropic can command these massive

805
00:43:14,040 --> 00:43:16,960
Speaker 15: private bidancing rounds that we've never seen before and precedented

806
00:43:17,040 --> 00:43:20,719
Speaker 15: levels of cash. However, access to public markets allows them

807
00:43:20,760 --> 00:43:24,080
Speaker 15: to do that with much more ease frequency. It also

808
00:43:24,120 --> 00:43:26,720
Speaker 15: allows everyday people to get in on the AI boom

809
00:43:28,200 --> 00:43:31,000
Speaker 15: or bust, which is a risk right if it does change,

810
00:43:31,360 --> 00:43:33,880
Speaker 15: But that also, you know, then potentially is allowing a

811
00:43:33,960 --> 00:43:35,840
Speaker 15: larger group of sort of retail investors to have a

812
00:43:35,880 --> 00:43:38,720
Speaker 15: stake in the company, but really large pools of capital

813
00:43:38,760 --> 00:43:41,960
Speaker 15: being more easy to access without all the funding round

814
00:43:42,040 --> 00:43:44,880
Speaker 15: song and Dance I think helps them.

815
00:43:44,360 --> 00:43:47,520
Speaker 2: Biver shrin Gafari all over the open AI and the

816
00:43:47,560 --> 00:43:50,120
Speaker 2: anthropic story and will be for the rest of this year.

817
00:43:50,440 --> 00:43:52,799
Speaker 2: That does it for this edition of Bloomberg Tech. That's

818
00:43:52,840 --> 00:43:55,480
Speaker 2: what markets look like. Not too much going on at

819
00:43:55,520 --> 00:44:00,720
Speaker 2: the index level, basically flat. Nvidia is down a half percent,

820
00:44:01,040 --> 00:44:04,680
Speaker 2: but in the background there's still this idea that the

821
00:44:04,719 --> 00:44:08,080
Speaker 2: big one is coming SpaceX's IPO. This is Bloomberg Tech