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

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Speaker 1: from the heart of Silicon Valley with ed La though

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Speaker 1: in Van Francisco.

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Speaker 2: This is Bloomberg Tech coming up.

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Speaker 3: Open Ai unveils its first custom AI chip called Kalapino,

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Speaker 3: developed in partnership with Broadcom, plus s k Highnex's plane

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Speaker 3: to raise twenty nine billion dollars in a landmark US listing,

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Speaker 3: racing to increased capacity to meet memory chip demand, and

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Speaker 3: Cerebrus reports quarterly earnings for the first time since going public.

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Speaker 3: CEO Andrew Feldman joins us later this hour. Let's get

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Speaker 3: to our top story custom Silicon open ai is tackling

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Speaker 3: one of AI's biggest challenges, the supply and costs of computing.

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Speaker 3: The company unveiled Kalapino Intelligence process. So that's the wafer,

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Speaker 3: a custom AI chip developed with broad coomp which the

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Speaker 3: companies say carries a fifty percent lower cost versus a

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Speaker 3: typical AIGPU. The focus faster, cheaper AI inference shares a

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Speaker 3: broad Open pretty higher round two percent. We're off session highs,

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Speaker 3: but still up a percentage point or so. In a

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Speaker 3: market where tech at the index level kind of flat.

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Speaker 3: This is outperformance. Blinbo Tech editor Seth Figgerman is here

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Speaker 3: with the details. This is the big picture, right, open

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Speaker 3: ai is compute constrained, heavily reliant on Nvidia.

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Speaker 2: They want to diversify. What do we need to know?

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Speaker 4: Yeah, that's very I think, you know, Opening I wants

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Speaker 4: to own more of the infrastructure stack, have more flexibility here,

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Speaker 4: and then I think importantly, use the expertise that it's

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Speaker 4: developed into what makes air models run better and more

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Speaker 4: efficiently and apply that to the hardware and the same

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Speaker 4: way that I think we're seeing Google do with its TPUs,

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Speaker 4: and the hope would be that over time they can

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Speaker 4: build a chip that's more cost efficient and also better

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Speaker 4: performing and eventually cuts down its own costs.

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Speaker 3: Bloomberg News spoke to both Hocktan the CEO of Broadcom,

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Speaker 3: and open ai is hardware chief. I guess you know,

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Speaker 3: from raw Comm's perspective, there was quite a lot of

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Speaker 3: fighting talk. Right, they see a lot of demand for

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Speaker 3: a six or custom silicon. But what was interesting to

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Speaker 3: me is hock Tans saying to us they see a

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Speaker 3: world where every frontier lab goes to have a custom chip.

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Speaker 2: Why yeah, I mean.

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Speaker 4: It gets back to what we said about Openny a

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Speaker 4: minie ago, I think giving them the versatility to kind

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Speaker 4: of control their infrastructure stack and build customer hardware that

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Speaker 4: meets their needs. And now I think Hocktan's com and

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Speaker 4: he's saying there's not that many of these frontier model developers.

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Speaker 4: So I think agree between the lines we're kind of

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Speaker 4: talking about. Is anthropic, I'm going to move in this

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Speaker 4: direction and that's certainly possibility. And to your other point,

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Speaker 4: I think Hocktan sounds quite bullish generally on the prospects

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Speaker 4: for this chip and chips like it going forward. He

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Speaker 4: sees no limit to the demand for this kind of

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Speaker 4: infrastructure and is predicting that the demand and roll out

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Speaker 4: for this chip next year will exceed his prior estimates

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Speaker 4: for one point three gigawads to supply on.

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Speaker 3: The open AI side, it's the latest example of them

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Speaker 3: being prepared to spend. Did we get any sense from

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Speaker 3: our conversation with the company about how this custom chip

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Speaker 3: will rank in their overall plan for compute, whether it's leasing,

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Speaker 3: data center, buying and video chips, et cetera.

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Speaker 4: Yeah, you know, they remain pretty tight. Lop DOWNE what

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Speaker 4: the financing for this will look like. We have previously

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Speaker 4: reported that Opening I planned to spend tens of billions

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Speaker 4: of dollars on these chips, with Broadcom part of its

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Speaker 4: hundreds of billions of dollars in infrastructure commitments. Seeing Broadcom

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Speaker 4: has previously said that they were standing up a chip

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Speaker 4: financing vehicle that could help Opening I's efforts, but it's

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Speaker 4: unclear that's the primary financing mechanism for what Opening I

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Speaker 4: will do here.

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Speaker 3: Bloomberg's AI editor Seth Figemann, thank you very much. Indeed,

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Speaker 3: s k Heinez plans to raise twenty nine point four

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Speaker 3: billion dollars in its US market debut, a deal large

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Speaker 3: enough to rank among the top five share sales of

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Speaker 3: all time. The listing comes at a time when markets

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Speaker 3: are hungry for memory chips and semicindut to companies are

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Speaker 3: rushing for capital to expand capacity meet that demand. The

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Speaker 3: BOS Peter Elstrom, who leads our coverage of Asia tech,

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Speaker 3: joins us that's part of it, right, Expand memory fab

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Speaker 3: capacity raise a lot of money. There's also this idea

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Speaker 3: of like valuation and prestige of an ADR situation where

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Speaker 3: you get exposure to American investors.

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Speaker 5: Yeah, that's right.

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Speaker 6: Sk Heinez is a company we don't talk about that

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Speaker 6: often on the show. Obviously a leading memory chip company,

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Speaker 6: but they often play second fiddle to Samsung, even in

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Speaker 6: South Korea. But what we've seen from them over the

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Speaker 6: past three years is really they've come from quite far

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Speaker 6: behind to essentially the same market cap size as Samsung

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Speaker 6: at this point. And that's largely because they've been so

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Speaker 6: successful in these memory chips for AI applications that HBM

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Speaker 6: chips that we've talked about before. They especially HBM chips

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Speaker 6: are DRAM chips stacked on top of each other, and

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Speaker 6: their technology for doing that stacking has been very good.

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Speaker 2: They got Nvidia's blessing.

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Speaker 6: They've been able to jump ahead of Samsung in that

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Speaker 6: market quite effectively.

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Speaker 5: Samsung has struggled a little bit.

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Speaker 6: So now what we're seeing with this twenty nine billion

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Speaker 6: dollar fundraising is really them announcing to the US, hey,

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Speaker 6: that they're ready to raise this kind of capital. They

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Speaker 6: want more exposure in the US and yeah, they'd like

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Speaker 6: more of that pe multiple that you see with the

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Speaker 6: US tech companies too. They've traded at a discount to that.

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Speaker 6: If they get some of that ADR exposure, that may

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Speaker 6: give them a little more opportunity to increase that valuation, and.

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Speaker 3: Just on the mechanics, Peter, so it will be ADRs

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Speaker 3: I believe, on the Nasdaq. So we have a timeline

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Speaker 3: for this. And how much of a surprise was it

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Speaker 3: that sk plowed ahead with this.

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Speaker 6: Well, it's certainly they've talked about wanting to raise money

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Speaker 6: in the US for a while, so I think in

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Speaker 6: terms of direction, this has been expected. I think in

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Speaker 6: terms of magnitude, it's a bit of a surprise though

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Speaker 6: it's a lot of money. As you mentioned, it could

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Speaker 6: be one of the top five offerings of its kind. Ever,

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Speaker 6: they plan to start trading these ADRs on July tenth.

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Speaker 6: They've talked about that. They still have a couple of

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Speaker 6: steps to go before they formally do that, but that's

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Speaker 6: the plan. At this point, they'd be able to raise

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Speaker 6: that money and then, as you say, they really want

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Speaker 6: to spend this money and trying to solve this choke

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Speaker 6: point that they've had in the AI industry where memory

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Speaker 6: chips are in short supply. Prices have been soaring, which

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Speaker 6: is driving profits for a bunch of companies, including Micron,

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Speaker 6: as we'll see after the bell today. But they want

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Speaker 6: to be able to build additional capacity in South Korea.

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Speaker 6: They're also expanding in the United States, where they have

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Speaker 6: some facilities too.

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Speaker 3: Bloomberg Tech Executive Editor details from Thank you very Much.

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Speaker 3: The AI hardware story and memory in particular are set

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Speaker 3: to dominate market conversation today. We've got the perfect person

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Speaker 3: to speak about it. Selin Wu is a portfolio manager

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Speaker 3: on Lazard Asset Management's Global Robotics and Automation team. She

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Speaker 3: manages the firms tech in Ai Focus ETF, called TECHI

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Speaker 3: or TEKY and actively managed ETF where sk Heinex and

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Speaker 3: its career and shares are the top holding.

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Speaker 2: Welcome to the program, Thanks for having me.

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Speaker 3: The situation with the memory makers is fascinating.

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Speaker 2: Demand is exceeding supply.

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Speaker 3: Historically, that's an enviable position to be in, and the

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Speaker 3: shares of those companies probably reflect that. How do you

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Speaker 3: see investor appetite to be exposed to the memory trade?

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Speaker 7: Yeah, I mean the shares have been fantastic, But even

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Speaker 7: after that, I think memory stocks still love for a

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Speaker 7: very compelling investment case. And here's why. I don't think

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Speaker 7: it's necessarily just driven by temporary supply bottlenecks. Instead, I

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Speaker 7: think there's something structured going on in the cycle. For example,

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Speaker 7: memory's strate peagic value is rising and changing to a

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Speaker 7: primary driver for performance. Think about how cloudsher providers, one

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Speaker 7: of their largest clients. They're still adding more memory despite

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Speaker 7: the price of inflation because this is still the most

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Speaker 7: cost efficient way to maximize their system level performance. And

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Speaker 7: when of the when token demand, excuse me, the token

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Speaker 7: demand is rising on the back of the inference as

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Speaker 7: well as agent the AI. I think the bottlenecks in

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Speaker 7: terms of the capacity and bendwidth are becoming even more challenging,

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Speaker 7: and this is a place where memory can come in

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Speaker 7: and help navigate those challenges.

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Speaker 3: Does it matter that investors will have the opportunity to

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Speaker 3: have US listed shares ADRs of sk How does that

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Speaker 3: kind of change the mechanics of the market for you

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Speaker 3: as well?

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Speaker 7: Yeah, I mean a clearly the more exposure to more

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Speaker 7: diverse type of shareholder base is clearly a very positive

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Speaker 7: indication for any company in the world, especially when your fundamentals,

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Speaker 7: when your fundamentals are improving. So yeah, super exciting us

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Speaker 7: and looking forward to the development.

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Speaker 3: A couple of months ago, sitting down with Jensen Wong

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Speaker 3: and I said to him, do we even need the

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Speaker 3: textbooks anymore? That would tell us historically memory is cyclical,

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Speaker 3: it is boom and bust. All of the evidence suggests

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Speaker 3: that in the context of HBM going into data center,

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Speaker 3: it just doesn't behave the same way.

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Speaker 2: What is your thesis on that?

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Speaker 7: I mean, I agree with that. I mean, like I said,

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Speaker 7: there's something structural going on. Yes, there is certain type

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Speaker 7: of cyclicality going on indoor market. But at the end

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Speaker 7: of at the end of the day, what you need

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Speaker 7: to remembered is structure side of booth, demand and supply,

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Speaker 7: and think about the supply side.

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Speaker 2: Despite the fact that all the three.

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Speaker 7: Major companies are scrambling to add new supply, there are

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Speaker 7: three factors that you have to remember. Number one, manufacturing intensity.

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Speaker 7: Manufacturing complexity is rising. Number two, capital intensity to open

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Speaker 7: a new fab is getting more expensive, and number three

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Speaker 7: the difficulty of technology and migration all together pointing out

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Speaker 7: that overall supply demand balance will stay in favor of

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Speaker 7: the memory stocks. I mean, I think that's really great.

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Speaker 3: I'd love to talk about your actively managed ETF for

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Speaker 3: a moment. T e k y Techy Techy I launched

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Speaker 3: last April, write sixty million in assets currently. What I

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Speaker 3: find so interesting about the composition of it is something

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Speaker 3: we've talked about quite recently on the show. There are

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Speaker 3: the capital expenditure deployers and there are the capital expenditure

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Speaker 3: recipients in the same basket when you look at the

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Speaker 3: top holdings. Is that a conscious, active decision on composition.

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Speaker 7: I think it's the composition from our bottom up stock

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Speaker 7: selection and portfolio construction. But like you said, that's exactly

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Speaker 7: where majority of the capital is invested in currently. On

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Speaker 7: one hand, there are big spenders, big kip expenders that

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Speaker 7: are trying to build new competitive positioning in this AI

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Speaker 7: homage pace. But on the other hand, we find a

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Speaker 7: lot of exciting opportunities on the companies that we see

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Speaker 7: these capitals AI hardware supply chain, for example. I think

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Speaker 7: that's why there's more to come. In fact, we just

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Speaker 7: recently came from Asia where we sat down with a

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Speaker 7: number of different companies into supply chain. Everyone is telling

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Speaker 7: us how they are seeing an extended visibility from customers,

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Speaker 7: how there are more conversations about ltas. Everything collectively is

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Speaker 7: highlighting that demand continues to substantially exceed the supply and

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Speaker 7: the AI demand outlook remains pretty robust as well.

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Speaker 3: For in the ETF context, it's a very competitive market.

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Speaker 3: How closely are you thinking about flows? And again, I

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Speaker 3: think people give you a lot of credit Sealine for

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Speaker 3: identifying sk as being just critical to the broader infrastructure

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Speaker 3: build out right now, But you know what happens next

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Speaker 3: to your mind? How do you see the world changing

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Speaker 3: in the next I guess six months to twelve months.

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Speaker 7: I mean even more than that. I mean that's why

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Speaker 7: we focus on AI tech stack, and at the top

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Speaker 7: of the step we have application layer and this is,

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Speaker 7: for example, where we are going to expect really large

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Speaker 7: opportunities from physical AI. We think physical AI is going

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Speaker 7: to be multi trillion dollars long term opportunity. Essentially, AI

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Speaker 7: is in because it's a primary driver for productivity gains,

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Speaker 7: and historically productivity growths tend to translate to massive economic expansions.

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Speaker 7: I think the same thing is going to happen for AI.

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Speaker 7: All the innovation we're seeing today is eventually going to

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Speaker 7: open up very significant new end markets in physical AI,

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Speaker 7: such as fully autonomous transformation transportations as well as a

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Speaker 7: humanoid robot. That's why we're really excited about physical AI

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Speaker 7: and in the meantime, that being said, it will still

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Speaker 7: take a couple of years for this to turn into

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Speaker 7: actual corporate earnings. So here's what we focus on instead.

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Speaker 7: Companies with vertically interiorted the manufacturing excellence that can speak

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Speaker 7: to the market with scale advantage for example, or open

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Speaker 7: source platform that can expedite the excelevation adoption and everything.

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Speaker 7: And lastly, global technology companies that can massively benefit from

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Speaker 7: the mass adoption of the application in it sulf something

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Speaker 7: to watch is something we're still pretty excited about.

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Speaker 3: Seline Wu from Lazard Asseid Management, first time on Bloomberg Tech.

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Speaker 3: Really grateful to have you here, Thank you very much. Indeed,

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Speaker 3: now coming up, Meta and Microsoft are leading the spending

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Speaker 3: spree on future data center leases, adding tens of billions

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Speaker 3: of dollars just last quarter alone. We'll get into the

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Speaker 3: details next. This is Bloomberg Tech. Okay, today's big number,

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Speaker 3: eight hundred and fifty billion dollars. That's how much the

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Speaker 3: world's largest cloud computing companies have committed in future data

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Speaker 3: center leases. Leading the charge in the AI spending spree,

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Speaker 3: Meta and Microsoft both committing tens of billions more just

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Speaker 3: last quarter. Bloombo's Brodie Ford has an astonishing story and

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Speaker 3: a hell of a.

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Speaker 2: Chart to show us.

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Speaker 3: What I find interesting about this is that these are

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Speaker 3: future leases, essentially leases planned or announced separate from what

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Speaker 3: is already in operation, what they are already contractually committed to.

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Speaker 8: It's a really good point, right, So we're talking about

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Speaker 8: eight hundred and fifty billion on data centers, which in

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Speaker 8: many cases aren't even built yet. It's they are working

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Speaker 8: through their current projects they have, and these are the

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Speaker 8: ones that they've committed to leasing once they're operational. And

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Speaker 8: so a lot of people wonder about what's the long

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Speaker 8: term spending trajectory on data centers? How long does this last? Well,

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Speaker 8: there's eight hundred and fifty billion dollars of leases that

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Speaker 8: are going to be starting in the coming years.

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Speaker 3: So when I was reading the story, I was trying

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Speaker 3: to understand the future costs. It's an amazing chart, by

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Speaker 3: the way, we're just showing on the screen right now,

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Speaker 3: like the level of capital and it's the commitment grows.

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Speaker 3: But where did their current financial healths and balance sheet

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Speaker 3: stand relative to those future commitments.

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Speaker 2: Is there a concern about that?

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Speaker 8: I think there's a lot of concern that seem to

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Speaker 8: always ebb and flow around the ROI of all this spending, right.

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Speaker 8: I mean, it feels like every quarter or two the

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Speaker 8: general sentiment flips about whether the market's worried or not,

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Speaker 8: but every hyperscaler seems to agree that they must spend

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Speaker 8: an incredible amount to catch up an AI to have

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Speaker 8: enough data center capacity. I think about Microsoft, who through

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Speaker 8: a lot of twenty twenty five said we're nervous, we're

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Speaker 8: actually going to put on ice a lot of these leases,

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Speaker 8: and they've come to regret it pretty deeply. And I

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Speaker 8: think a lot of the biggest tech companies, as we

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Speaker 8: can see in this chart, are hoping to avoid that

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Speaker 8: kind of scenario.

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Speaker 3: Microsoft added forty one billion dollars in commitments to a

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Speaker 3: total of almost one hundred and ninety seven billion dollars.

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Speaker 3: Compare and can trust really quick Oracle.

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Speaker 8: Oracle's very interesting because they signed a ton of leases,

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Speaker 8: largely for open AI, and they've been flat for the

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Speaker 8: last two quarters, which says to us that they're digesting

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Speaker 8: a lot of capacity, contrasted with somebody like Meta, who

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Speaker 8: is just signing as much much as they seem to

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Speaker 8: be able.

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Speaker 3: To Bloombanks, Brady Ford, thank you very much. Just get

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Speaker 3: out to New York where bloom Bek Jihara and and

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Speaker 3: is standing by Hi.

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Speaker 9: Yahara, Hi ed It's time now for talking tech. First

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Speaker 9: up Softbanks. Masayoshi Sun says he has no plans to

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Speaker 9: retire anytime soon as he looks to capitalize on the

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Speaker 9: AI boom. Speaking at an annual shareholder meeting, the sixty

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Speaker 9: eight year old visionary fired back at skeptics, saying, quote,

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Speaker 9: the AI revolution has only just begun. Calling it a

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Speaker 9: bubble is an insult plus and the latest showdown between

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Speaker 9: Chinese big tech and national security. Ali Baba has sued

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Speaker 9: the US Defense Department demanding removal from its blacklists. The

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Speaker 9: e commerce giant called a designation arbitrary and unjustified, following

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Speaker 9: a US crackdown earlier this month that accused several of

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Speaker 9: China's top companies of aiding Beijing's military, and TikTok parent

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Speaker 9: by Dance is in early talks to secure a record

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Speaker 9: twenty billion dollars global loan. Well the exact use of

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Speaker 9: the proceeds remains unclear. The massive borrowing push comes as

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Speaker 9: the company wis boosting data center and AI capital.

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Speaker 2: Spending ed Thank you very much, you Hira.

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Speaker 3: Now coming up on the program defense startup, Hadrian discusses

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Speaker 3: new funding at a seven point five billion dollar valuation

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Speaker 3: that would be four times its past or latest value.

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Speaker 2: We're going to discuss that next. This is Bloomberg Tech.

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Speaker 3: Can AI replace human effort in the realm of scientific discovery?

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Speaker 2: In the latest episode of The Circuit.

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Speaker 3: Bloomberg's Emily Chang spoke to Jennifer Dowdner, the inventor of

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Speaker 3: the groundbreaking crispher gene editing technology, about the future of biology.

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Speaker 2: Listened to this.

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Speaker 10: Biology is complex. We're not going to be able to

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Speaker 10: simulate our way to an understanding of the human. We're

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Speaker 10: not going to be able to avoid the need for

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Speaker 10: certain types of testing. I do think there are opportunities

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Speaker 10: to increase the efficiency in which we make discoveries about

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Speaker 10: the way our bodies work and the way they interact

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Speaker 10: with drugs that will be effective, and I think AI

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Speaker 10: will be helpful there. But it's going to come down

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Speaker 10: to training models on the right kind of data, and

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Speaker 10: a big need for better and more data for training

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Speaker 10: models if we want to achieve that.

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Speaker 9: An Open AI executive recently suggested that if a discovery

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Speaker 9: happens on chat GPT, let's say a drug discovery that

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Speaker 9: open AI should get a cut of sales.

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Speaker 11: What do you think of that?

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Speaker 10: Good luck expand how are chatbots going to change drug discovery?

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Speaker 10: I'm not sure the answer to that yet.

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Speaker 5: I don't know.

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Speaker 10: Lots of people are, of course, very very hopeful, so

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Speaker 10: I'm very helpeful about it. But I think that innovation

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Speaker 10: is still really in the domain of human beings right now.

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Speaker 10: I'm not seeing chatbots in our own experience innovating. They

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Speaker 10: can be helpful with summer rising data, that can be

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Speaker 10: helpful in writing reports and things of that nature, but

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Speaker 10: I'm not seeing chatbots coming up with a brand new

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Speaker 10: idea for something that nobody else ever thought of.

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Speaker 2: So you're saying AI can't innovate.

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Speaker 10: I don't know if it can't innovate, I just don't

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Speaker 10: think it is right now.

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Speaker 2: What about after the AGI moment?

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Speaker 10: Well, I never say never, so maybe that'll happen, but

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Speaker 10: I'm not holding my breath.

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Speaker 3: That was Bloomberg's Emily Chang speaking with Jennifer Dowdner, Nobel

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Speaker 3: Laureate and founder of Innovative Genomics Institute. What's the four

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Speaker 3: episode on Bloomberg Television tonight at six pm Eastern or

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Speaker 3: on Bloomberg Originals at eight pm Eastern time. Defense manufacturing

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Speaker 3: start up Hadrian has been in talks to more than

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Speaker 3: quadruple its valuation in a new funding round, according to sources,

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Speaker 3: Bloomberg's venture reporter of BEC and Torrents and I teamed

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Speaker 3: up on this one.

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Speaker 2: So let's go through the basics.

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Speaker 3: Right, these are talks, they're at a certain stage, but

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Speaker 3: they only raise money right at the beginning of this

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Speaker 3: year at a certain valuation. What's the jump and what

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Speaker 3: do we need to know?

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Speaker 2: That's correct ed?

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Speaker 12: So Hadrian raise money at a one point six billion

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Speaker 12: dollar valuation just in January. They've now had conversations to

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Speaker 12: raise up to a billion dollars in this latest round.

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Speaker 12: That would more than quadruple their valuation, as you said,

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Speaker 12: to seven point five billion dollars. The investor demand on

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Speaker 12: this one is pretty significant. We reported that several existing

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Speaker 12: investors are in talks for this one. We should note

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Speaker 12: that when we reach out to comment, Hadrian said that

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Speaker 12: the information provider was incorrect decline to provide further context.

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Speaker 2: That said, we sitten by our reporting.

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Speaker 12: This is an area that's extremely hot with investors right now,

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Speaker 12: defense tech broadly. Hadrian makes facilities to speed up domestic

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Speaker 12: manufacturing and that's been hugely of interest to a lot

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Speaker 12: of folks and Silicon Valley.

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Speaker 2: Thank you for that.

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Speaker 3: I would also add that s fokes first and Hadrium

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Speaker 3: said the reporting was incorrect but declined to add further context.

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Speaker 2: I would have done that for you. Thank you very much.

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Speaker 2: There is some reporting that we did about where they.

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Speaker 3: Approached debt or a lack of approach to debt.

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Speaker 12: Just explain that bites so building large automated factories often

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Speaker 12: means that companies need to take on debt to take

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Speaker 12: you know, on the risks of building these large facilities.

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Speaker 12: Hadrian currently has four factories, the latest which operate, which

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Speaker 12: opened in March off the back of a two point

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Speaker 12: four billion dollar contract with the US Navy. So this amount,

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Speaker 12: this up to one billion dollars is just equity that

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Speaker 12: they would raise. It doesn't include any debt that they

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Speaker 12: may be discussing.

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Speaker 3: Rebecca, you did a great job explaining, you know what

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Speaker 3: Hadrian does. It's basically an amazing factory or contract manufacturer. Generally,

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Speaker 3: what is bench capital attitude right now to defense technology

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Speaker 3: and this whole kind of reindustrializing America push.

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Speaker 2: There's tons of excitement here.

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Speaker 12: Ed investors in Hadrin include Andres and Horowitz through its

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Speaker 12: American Dynamism Fund, Pedersfield's founder's fund, Lux Capital. This effort

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Speaker 12: to sort of reshore manufacturing and create the cycle where

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Speaker 12: consumers and companies can just rely on production and consumption

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Speaker 12: within the US is a huge interesting.

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Speaker 3: These people Bloombergs, Rebecca Torrents teaming up with me on

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Speaker 3: that one on Hadrian potentially hitting seven point five billion

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Speaker 3: dollar valuation, Thank you very much. Now, coming up later

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Speaker 3: in the show, we're going to sit down with David

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Speaker 3: George and Drees and horror Itz general partner on a

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Speaker 3: sixteen c's big bet on SpaceX conversation that we're really

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Speaker 3: looking forward to right now. This is what technology looks

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Speaker 3: like in financial markets, particularly inequity markets, and we are

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Speaker 3: all waiting for what is a big one that is

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Speaker 3: Micron reporting earnings after the closing bell right now, Na's

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Speaker 3: like one hundred modestly hired, a flat underperformance in chip

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Speaker 3: stocks and bitcoin just shy of sixty one thousand US

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Speaker 3: dollars per token. Welcome back to Bloomberg Tech. It's a

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Speaker 3: big moment in time for Memory. The biggest headline is

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Speaker 3: probably the sk Heinex will try and raise twenty nine

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Speaker 3: billion dollars in a US listing.

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Speaker 2: But the AI trade is.

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Speaker 3: Going to get its next queue from Micron's earnings after

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Speaker 3: the bell. There's a lot of literature on the Bloomberg

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Speaker 3: about that. The stocks down about one zero point three

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Speaker 3: percent right now. It's highly analogous from what we saw

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Speaker 3: in some of the earlier days of Nvidia twenty twenty

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Speaker 3: three to twenty twenty five, massive growth year on year,

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Speaker 3: both on the top and bottom line. But the market

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Speaker 3: really wants a bullish signal, not that the bottleneck that

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Speaker 3: is Memory is unwinding a little on the AI infrastructure

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Speaker 3: build out, but that the demand has staying power. So

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Speaker 3: that is what we're watching for throughout the course of

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Speaker 3: the day. Another top story, Elon Musk is reshaping his

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Speaker 3: empire's balance sheet. SpaceX just pulled off a record twenty

438
00:23:51,119 --> 00:23:54,280
Speaker 3: five billion dollar investment grade bond sale, taking on more

439
00:23:54,320 --> 00:23:58,800
Speaker 3: debt while lowering overall borrowing costs across must sprawling businesses.

440
00:23:59,119 --> 00:24:03,160
Speaker 3: For more Bloombergs, Private credit reporter Paula Sellison joins us,

441
00:24:03,600 --> 00:24:04,199
Speaker 3: how did it go?

442
00:24:04,880 --> 00:24:07,760
Speaker 11: It went very well that the peak of demand. There

443
00:24:07,760 --> 00:24:10,119
Speaker 11: were eighty nine billion dollars in orders for what was

444
00:24:10,160 --> 00:24:13,240
Speaker 11: ultimately a twenty five billion dollar bond deal that allowed

445
00:24:13,640 --> 00:24:16,800
Speaker 11: the company to tighten or get lower borrowing costs over

446
00:24:16,800 --> 00:24:19,320
Speaker 11: the course of the marketing process, and investors are very

447
00:24:19,320 --> 00:24:20,000
Speaker 11: eager to lend.

448
00:24:21,320 --> 00:24:23,199
Speaker 2: There is a bit of a history lesson in this.

449
00:24:23,480 --> 00:24:24,359
Speaker 2: Find it fascinating.

450
00:24:24,440 --> 00:24:30,199
Speaker 3: So, yeah, must takes Twitter private, x joins Xai, Xai

451
00:24:30,320 --> 00:24:33,679
Speaker 3: merges with SpaceX, and then SpaceX does the biggest IPO

452
00:24:33,760 --> 00:24:35,600
Speaker 3: in history. And if you look at how they kind

453
00:24:35,600 --> 00:24:37,840
Speaker 3: of shuffled the deck with the proceeds of the bond

454
00:24:37,920 --> 00:24:40,200
Speaker 3: sale and what they planned to do in paying down

455
00:24:40,240 --> 00:24:43,800
Speaker 3: existing loans, it kind of takes us back to square one?

456
00:24:43,840 --> 00:24:44,320
Speaker 2: Is that right?

457
00:24:44,920 --> 00:24:48,080
Speaker 11: Well, this was really all one long, convoluted way of

458
00:24:48,119 --> 00:24:51,320
Speaker 11: allowing Xai to become part of an investment grade company

459
00:24:51,359 --> 00:24:54,639
Speaker 11: and then be able to borrow at those borrowing costs. So,

460
00:24:54,920 --> 00:24:57,399
Speaker 11: you know, we had the Twitter LBO which ended up

461
00:24:57,440 --> 00:24:59,560
Speaker 11: adding about thirteen billion dollars of debt, and then the

462
00:24:59,640 --> 00:25:02,800
Speaker 11: Xai leverage loan and hiled bond sales which added five

463
00:25:02,840 --> 00:25:06,439
Speaker 11: billion dollars of debt, So when SpaceX acquired XAI, there

464
00:25:06,520 --> 00:25:09,399
Speaker 11: was seventeen point five billion dollars of debt with interest

465
00:25:09,440 --> 00:25:11,320
Speaker 11: rates in the nine and a half percent to twelve

466
00:25:11,320 --> 00:25:13,840
Speaker 11: and a half percent range. All of that essentially just

467
00:25:13,920 --> 00:25:17,200
Speaker 11: got refinanced initially through a twenty billion dollar bridge loan

468
00:25:17,240 --> 00:25:19,520
Speaker 11: that was then taken out with the investment grade bond

469
00:25:19,560 --> 00:25:22,080
Speaker 11: sale on Tuesday, and now interest rates around five and

470
00:25:22,119 --> 00:25:22,920
Speaker 11: a half to six.

471
00:25:22,760 --> 00:25:23,439
Speaker 2: And a half percent.

472
00:25:24,480 --> 00:25:27,080
Speaker 3: We broke the story in just the days before the

473
00:25:27,119 --> 00:25:29,840
Speaker 3: IPO that SpaceX had got IG rating from the free

474
00:25:29,880 --> 00:25:33,560
Speaker 3: main agencies. That was really important, right The story right

475
00:25:33,600 --> 00:25:37,760
Speaker 3: now in the AI space is borrowing and the IG

476
00:25:37,960 --> 00:25:41,440
Speaker 3: rating has proved to be pretty handy to SpaceX.

477
00:25:41,280 --> 00:25:44,520
Speaker 11: Absolutely, so there is so much need for capital. Investment

478
00:25:44,600 --> 00:25:46,840
Speaker 11: companies just can't do it with cash flow. They have

479
00:25:46,920 --> 00:25:49,600
Speaker 11: to borrow, and they're borrowing across all the different debt markets.

480
00:25:49,800 --> 00:25:51,520
Speaker 11: But the best place to borrow for most of them

481
00:25:51,560 --> 00:25:54,159
Speaker 11: is the investment grade bond market because it's very large,

482
00:25:54,640 --> 00:25:57,359
Speaker 11: very deep pockets, and it's a cheaper borrowing cost. So

483
00:25:57,440 --> 00:25:59,720
Speaker 11: being able to get those investment grade ratings just opens

484
00:25:59,760 --> 00:26:02,399
Speaker 11: up access to capital that makes it so much easier

485
00:26:02,480 --> 00:26:04,560
Speaker 11: to borrow all this money to finance the AI build

486
00:26:04,560 --> 00:26:06,520
Speaker 11: out the most.

487
00:26:06,359 --> 00:26:07,960
Speaker 2: Paula Cellison, thank you very much.

488
00:26:08,040 --> 00:26:10,880
Speaker 3: Indeed, in the equity space SpaceX actually hire again today

489
00:26:10,880 --> 00:26:16,000
Speaker 3: one hundred and fifty eight dollars per share SpaceX David,

490
00:26:16,040 --> 00:26:19,080
Speaker 3: George Andresen horror it's general partner, is on set with

491
00:26:19,160 --> 00:26:21,720
Speaker 3: us right now. He led the firm's investment investment in SpaceX,

492
00:26:21,760 --> 00:26:23,520
Speaker 3: a state which is now valued at more than ten

493
00:26:23,560 --> 00:26:27,760
Speaker 3: billion dollars and it's proved to be Andresen's largest return

494
00:26:27,800 --> 00:26:30,000
Speaker 3: in history. And you're somebody that I've wanted to speak

495
00:26:30,040 --> 00:26:32,600
Speaker 3: to about the company for a long time. There's a

496
00:26:32,600 --> 00:26:35,640
Speaker 3: lot here, but I think just as an opening reflect

497
00:26:35,680 --> 00:26:39,080
Speaker 3: on the IPO, David, and I guess not just in

498
00:26:39,119 --> 00:26:42,080
Speaker 3: a moment in time for Andresen, but what you think

499
00:26:42,119 --> 00:26:45,560
Speaker 3: it's signified for what is a very big and now

500
00:26:45,640 --> 00:26:46,760
Speaker 3: quite diverse company.

501
00:26:47,000 --> 00:26:48,960
Speaker 13: Yeah, well, look, thanks for having me on. A great

502
00:26:48,960 --> 00:26:51,879
Speaker 13: to be here with you. The IPO is just a

503
00:26:51,920 --> 00:26:55,000
Speaker 13: milestone in the history of the company. I think it's

504
00:26:55,240 --> 00:26:58,920
Speaker 13: a great event for the company to be able to

505
00:26:59,000 --> 00:27:03,120
Speaker 13: access a new investor's access capital that they couldn't otherwise access.

506
00:27:03,160 --> 00:27:03,520
Speaker 2: Before.

507
00:27:04,119 --> 00:27:06,000
Speaker 13: And one of the things that I'm most excited about

508
00:27:06,119 --> 00:27:08,960
Speaker 13: as relates to the IPO is the fact that retail

509
00:27:09,119 --> 00:27:12,320
Speaker 13: was able to partake in such a big fashion. So

510
00:27:12,359 --> 00:27:14,480
Speaker 13: if you look at the allocation that went to retail

511
00:27:15,320 --> 00:27:18,639
Speaker 13: as a proportion of the overall IPO, it's around thirty percent.

512
00:27:19,160 --> 00:27:21,520
Speaker 13: And so if you just take that portion that went

513
00:27:21,560 --> 00:27:25,159
Speaker 13: to retail, it's almost the largest IPO by itself in

514
00:27:25,200 --> 00:27:26,160
Speaker 13: the history of IPOs.

515
00:27:26,320 --> 00:27:28,720
Speaker 2: So I think it's fantastic that. Why is that part

516
00:27:28,760 --> 00:27:30,359
Speaker 2: of that? David, Sorry to interrupt you.

517
00:27:30,720 --> 00:27:33,879
Speaker 13: Retail has proven to be an excellent group of buyers

518
00:27:33,880 --> 00:27:37,480
Speaker 13: and holders of stock. So obviously it's a large proportion

519
00:27:37,560 --> 00:27:40,240
Speaker 13: of the ownership of Tesla, but they also are large

520
00:27:40,240 --> 00:27:43,080
Speaker 13: owners of the meg seven at large, and so I

521
00:27:43,119 --> 00:27:45,520
Speaker 13: think it's excellent for SpaceX to be able to access that.

522
00:27:46,000 --> 00:27:48,400
Speaker 13: I think you know, in large part, retail is long

523
00:27:48,520 --> 00:27:51,119
Speaker 13: term thinking, which aligns with the way Elon thinks and

524
00:27:51,119 --> 00:27:53,000
Speaker 13: how he's built SpaceX, and so I love that they're

525
00:27:53,000 --> 00:27:53,680
Speaker 13: a big part of it.

526
00:27:54,359 --> 00:27:57,200
Speaker 3: Probably the question I get for you most commonly is

527
00:27:57,240 --> 00:27:58,000
Speaker 3: about the lock up.

528
00:27:58,119 --> 00:27:58,879
Speaker 2: What will happen?

529
00:27:59,240 --> 00:28:02,119
Speaker 3: You know, to the venture firms would say, well, we

530
00:28:02,160 --> 00:28:05,439
Speaker 3: will redistribute to our LPs the stock and we expect

531
00:28:05,520 --> 00:28:07,840
Speaker 3: lots of them to hold. But that would seem to

532
00:28:07,840 --> 00:28:11,320
Speaker 3: make the retail holders important. And what was like a

533
00:28:11,440 --> 00:28:13,480
Speaker 3: very complex lockup, It wasn't straightforward.

534
00:28:13,720 --> 00:28:16,119
Speaker 13: Yeah, look, I think this is a great step forward

535
00:28:16,160 --> 00:28:19,119
Speaker 13: generally and how lockups are run, and I expect for

536
00:28:19,240 --> 00:28:21,960
Speaker 13: IPOs going forward, this is probably going to be the

537
00:28:21,960 --> 00:28:25,359
Speaker 13: way it's run. So cerebristed something similar where you have

538
00:28:25,440 --> 00:28:28,680
Speaker 13: the lockups come off gradually over time, and I think

539
00:28:28,720 --> 00:28:29,800
Speaker 13: this is good, this is healthy.

540
00:28:30,119 --> 00:28:32,120
Speaker 2: It allows you know.

541
00:28:32,080 --> 00:28:34,119
Speaker 13: The public market investors to be able to buy stock

542
00:28:34,160 --> 00:28:36,560
Speaker 13: over time as opposed to you know at cliff events.

543
00:28:37,119 --> 00:28:39,280
Speaker 13: For us, we're very long term thinkers. You know, we're

544
00:28:39,600 --> 00:28:43,280
Speaker 13: happy shareholders of SpaceX. You know, we think very much

545
00:28:43,320 --> 00:28:44,880
Speaker 13: about the long term.

546
00:28:45,000 --> 00:28:45,200
Speaker 12: You know.

547
00:28:45,240 --> 00:28:49,000
Speaker 13: Obviously, what makes us so excited about the business is

548
00:28:49,120 --> 00:28:51,640
Speaker 13: all of the things that can go right for SpaceX,

549
00:28:51,680 --> 00:28:54,040
Speaker 13: all the optionality that you have. And so the way

550
00:28:54,080 --> 00:28:55,760
Speaker 13: that we look at it is you start with the

551
00:28:55,800 --> 00:28:58,360
Speaker 13: launch business, and in order to be successful as a

552
00:28:58,400 --> 00:29:00,880
Speaker 13: space business, you have to rely be able to get

553
00:29:00,880 --> 00:29:05,200
Speaker 13: things to space. And so SpaceX has the infrastructure in

554
00:29:05,240 --> 00:29:08,720
Speaker 13: an incredible way to be able to build applications on top. Obviously,

555
00:29:08,760 --> 00:29:12,560
Speaker 13: Starlink is the first one. We expect that with Starship

556
00:29:12,640 --> 00:29:16,800
Speaker 13: and V three, they've achieved some de risking in terms

557
00:29:16,800 --> 00:29:19,480
Speaker 13: of what they can bring up to space. Eventually they'll

558
00:29:19,520 --> 00:29:23,840
Speaker 13: have rapid reusability with multiple launches per day on Starship.

559
00:29:24,320 --> 00:29:29,560
Speaker 13: It's a feat of physics magnificence that they can take

560
00:29:29,600 --> 00:29:32,560
Speaker 13: something that's the size of larger than a football field,

561
00:29:32,920 --> 00:29:35,320
Speaker 13: send it up to space, grab it with chopsticks, and

562
00:29:35,360 --> 00:29:38,160
Speaker 13: then reuse it again. They'll rapidly be able to do that,

563
00:29:38,240 --> 00:29:40,239
Speaker 13: and that's going to enable all the applications that they

564
00:29:40,240 --> 00:29:41,000
Speaker 13: want to build on top.

565
00:29:41,160 --> 00:29:45,120
Speaker 3: It also now has a name starmind Yes as of

566
00:29:45,320 --> 00:29:48,200
Speaker 3: last night, and you know Elon Musk engaging with others

567
00:29:48,240 --> 00:29:52,680
Speaker 3: on X. There are many out there that believe that

568
00:29:52,840 --> 00:29:55,640
Speaker 3: the timeline that was presented in the perspectus of Orbital

569
00:29:55,680 --> 00:29:59,160
Speaker 3: Date Center SPACEXIT as early as twenty twenty eight, actually

570
00:29:59,200 --> 00:30:01,880
Speaker 3: we could see some pool forward on that. Again linked

571
00:30:01,920 --> 00:30:05,720
Speaker 3: to the tracking of Starship. Where do you sit in

572
00:30:06,120 --> 00:30:07,800
Speaker 3: what's realistic.

573
00:30:07,240 --> 00:30:10,880
Speaker 13: Near to Yeah, Look, I think the biggest hurdle to

574
00:30:10,960 --> 00:30:14,880
Speaker 13: cross is just rapid reusability of Starship, and I think

575
00:30:15,080 --> 00:30:17,640
Speaker 13: you know, there's a consistent theme with Elon's companies, and

576
00:30:17,640 --> 00:30:21,360
Speaker 13: certainly in SpaceX, which is physics has been de risked,

577
00:30:21,800 --> 00:30:22,440
Speaker 13: and so now.

578
00:30:22,320 --> 00:30:23,720
Speaker 2: It becomes an execution question.

579
00:30:23,880 --> 00:30:26,640
Speaker 13: And so as you think about timelines, we feel like

580
00:30:26,720 --> 00:30:29,360
Speaker 13: it is inevitable that they can achieve these milestones, just

581
00:30:29,400 --> 00:30:31,920
Speaker 13: a question of how quickly and at what cost. And

582
00:30:32,000 --> 00:30:34,760
Speaker 13: so if you have starship that can rapidly, you know,

583
00:30:35,200 --> 00:30:38,440
Speaker 13: reliably get things up and back to space, we think

584
00:30:38,480 --> 00:30:41,880
Speaker 13: that's the major unlock for bringing compute to space.

585
00:30:42,240 --> 00:30:43,760
Speaker 2: I know earlier you.

586
00:30:43,720 --> 00:30:45,840
Speaker 13: Were talking about the eight hundred and fifty billion dollars

587
00:30:45,880 --> 00:30:51,000
Speaker 13: of CAPEX for AI data centers on terrestrial grounds. Right

588
00:30:51,040 --> 00:30:54,280
Speaker 13: now it's getting harder and harder to get data centers

589
00:30:54,280 --> 00:30:58,160
Speaker 13: live on the ground here. I think it's a matter

590
00:30:58,200 --> 00:31:01,400
Speaker 13: of time before we have it in space. I actually

591
00:31:01,440 --> 00:31:03,640
Speaker 13: think I like to reframe it a little bit. I

592
00:31:03,680 --> 00:31:06,000
Speaker 13: don't talk about it as orbital data centers. I talk

593
00:31:06,040 --> 00:31:08,800
Speaker 13: about them as sort of airplane sized.

594
00:31:09,040 --> 00:31:10,320
Speaker 2: Gpu ras in space.

595
00:31:10,440 --> 00:31:12,960
Speaker 13: So think of it as you know, something like seventy

596
00:31:13,040 --> 00:31:17,160
Speaker 13: two GPUs up in space with big wings that are

597
00:31:17,440 --> 00:31:19,280
Speaker 13: solar arrays that are kind of the size of a

598
00:31:19,280 --> 00:31:21,920
Speaker 13: seven thirty seven. And then you can have many, many

599
00:31:21,960 --> 00:31:24,440
Speaker 13: of those in space. They've demonstrated that they can do this.

600
00:31:24,480 --> 00:31:27,400
Speaker 13: They have ten thousand LEO satellites, So we feel like

601
00:31:27,480 --> 00:31:29,920
Speaker 13: it's a matter of time and execution before they can

602
00:31:30,000 --> 00:31:33,400
Speaker 13: do that. The physics has been de risked, you know,

603
00:31:33,560 --> 00:31:35,920
Speaker 13: to the point about how it's getting harder and harder.

604
00:31:35,640 --> 00:31:36,040
Speaker 2: To do this.

605
00:31:36,840 --> 00:31:39,800
Speaker 13: You know, on the ground, I think at a minimum,

606
00:31:39,920 --> 00:31:43,200
Speaker 13: orbital data centers will be incremental capacity that you can

607
00:31:43,240 --> 00:31:46,080
Speaker 13: have in space on top of what we have on Earth.

608
00:31:46,840 --> 00:31:48,719
Speaker 13: And I think there's a case that in the fullness

609
00:31:48,720 --> 00:31:51,880
Speaker 13: of time, the economics actually get better than on the ground.

610
00:31:52,800 --> 00:31:56,160
Speaker 3: David the firm Andreessen Horowitz has been involved with must

611
00:31:56,240 --> 00:31:59,480
Speaker 3: companies in different ways for about six years, in different

612
00:31:59,520 --> 00:32:03,719
Speaker 3: ways x XAI, the different financial transactions that took place.

613
00:32:04,520 --> 00:32:06,280
Speaker 2: For you, how much was this this.

614
00:32:06,360 --> 00:32:12,640
Speaker 3: IPO a referendum essentially on Musk himself or how central

615
00:32:12,720 --> 00:32:15,600
Speaker 3: to the fate of this company do you see long being?

616
00:32:16,320 --> 00:32:19,320
Speaker 13: Yeah, Look, Elon is the centerpiece of all of those

617
00:32:19,320 --> 00:32:22,200
Speaker 13: investment thesis that we had right in backing his companies.

618
00:32:23,000 --> 00:32:26,360
Speaker 13: You know, he's he's been remarkably strategic and how he's

619
00:32:26,400 --> 00:32:29,360
Speaker 13: put the companies together, and you know, he has done

620
00:32:29,520 --> 00:32:30,640
Speaker 13: very well by shareholders.

621
00:32:30,680 --> 00:32:31,720
Speaker 2: He's taking care of shareholders.

622
00:32:31,800 --> 00:32:33,800
Speaker 13: He takes a lot of pride in that, and we

623
00:32:33,840 --> 00:32:36,640
Speaker 13: appreciate that As his partner. I think as it relates to,

624
00:32:37,000 --> 00:32:39,560
Speaker 13: you know, the go forward, he's been very smart. He

625
00:32:39,680 --> 00:32:42,480
Speaker 13: and Brett Johnson and the team ASPACEX have been very

626
00:32:42,600 --> 00:32:45,600
Speaker 13: very smart about capital allocation, right, you know, when they

627
00:32:45,640 --> 00:32:49,360
Speaker 13: have done acquisitions, they have been remarkably strategic in terms

628
00:32:49,360 --> 00:32:52,000
Speaker 13: of putting things together first, you know, and putting X

629
00:32:52,000 --> 00:32:55,480
Speaker 13: with Xai, which is very logical, and then obviously the

630
00:32:55,480 --> 00:32:58,920
Speaker 13: fit of XAI and SpaceX together, you know, is undeniable.

631
00:32:58,960 --> 00:33:01,120
Speaker 13: So we expect that will continue to be very smart

632
00:33:01,120 --> 00:33:04,160
Speaker 13: about capital allocation, take care of shoreholders, and we appreciate that.

633
00:33:04,960 --> 00:33:08,520
Speaker 3: Where do you stand, David then, on the transaction that

634
00:33:08,520 --> 00:33:10,560
Speaker 3: everyone continues to talk about, which is a future where

635
00:33:10,560 --> 00:33:14,000
Speaker 3: Tesla merges with SpaceX, Is it rational to your mind?

636
00:33:14,360 --> 00:33:17,000
Speaker 13: I go back to the things that he's done in

637
00:33:17,040 --> 00:33:19,600
Speaker 13: the past, and the things that he's done in the past,

638
00:33:19,760 --> 00:33:22,800
Speaker 13: is he has decided to do acquisitions of his companies

639
00:33:23,080 --> 00:33:26,000
Speaker 13: or mergers of his companies when there is very strong

640
00:33:26,160 --> 00:33:28,280
Speaker 13: strategic alignment and it makes business sense.

641
00:33:28,360 --> 00:33:30,480
Speaker 2: So I wouldn't expect it to be any different going forward.

642
00:33:32,040 --> 00:33:35,320
Speaker 3: There's this broader idea, if you extract it out from

643
00:33:35,360 --> 00:33:38,840
Speaker 3: from Elon Musk, that even at the growth stage, late

644
00:33:39,040 --> 00:33:42,360
Speaker 3: private companies staying private for longer, late stage growth, that

645
00:33:42,840 --> 00:33:46,080
Speaker 3: the investment thesis is still around the founder, the person

646
00:33:46,120 --> 00:33:48,760
Speaker 3: at the top. I don't know, how whether you share

647
00:33:48,800 --> 00:33:51,800
Speaker 3: that view of others that even if you are talking

648
00:33:51,840 --> 00:33:54,480
Speaker 3: in the tens hundreds of billions of dollars of value,

649
00:33:55,360 --> 00:33:58,120
Speaker 3: that value is assignable to an individual or a group

650
00:33:58,120 --> 00:33:58,880
Speaker 3: of individuals.

651
00:33:59,120 --> 00:33:59,440
Speaker 2: Yeah.

652
00:33:59,480 --> 00:34:02,200
Speaker 13: Look, I think you can see reflections of this actually

653
00:34:02,280 --> 00:34:04,480
Speaker 13: in the public markets. So I think you can see

654
00:34:04,480 --> 00:34:07,479
Speaker 13: this in Elon companies. Certainly. I think you could see this,

655
00:34:07,800 --> 00:34:11,000
Speaker 13: you know, with Apple under Steve Jobs. I think you

656
00:34:11,040 --> 00:34:14,360
Speaker 13: could see it with Meta under Mark Zuckerberg. But certainly

657
00:34:14,360 --> 00:34:18,239
Speaker 13: in the private markets. You know, this is a centerpiece

658
00:34:18,360 --> 00:34:21,080
Speaker 13: of our investment thesis when we're backing companies at any

659
00:34:21,120 --> 00:34:25,279
Speaker 13: stage and any size. I recently wrote a piece that

660
00:34:25,400 --> 00:34:28,800
Speaker 13: basically said late stage venture, which is our asset class,

661
00:34:29,400 --> 00:34:30,680
Speaker 13: is not about capital markets.

662
00:34:30,719 --> 00:34:31,560
Speaker 2: It's about founders.

663
00:34:31,719 --> 00:34:34,800
Speaker 13: Late stage venture is about late stage founders and enabling

664
00:34:34,880 --> 00:34:38,600
Speaker 13: them to think long term, make big decisions, and make

665
00:34:38,640 --> 00:34:41,239
Speaker 13: big bets, and oftentimes they choose to do that in

666
00:34:41,280 --> 00:34:42,120
Speaker 13: the private markets.

667
00:34:42,160 --> 00:34:44,440
Speaker 2: And so you know, our asset class.

668
00:34:44,120 --> 00:34:47,360
Speaker 13: That we play in, it's about five trillion dollars in size.

669
00:34:47,440 --> 00:34:49,960
Speaker 13: It's grown ten x over the last ten years. It's

670
00:34:50,040 --> 00:34:52,960
Speaker 13: larger than the Russell two thousand. It's almost twenty percent

671
00:34:52,960 --> 00:34:55,160
Speaker 13: as large as the Nasdaq. So this has become a

672
00:34:55,200 --> 00:34:58,120
Speaker 13: real asset class. And I think there's reasons that we

673
00:34:58,120 --> 00:35:00,920
Speaker 13: should explore. Why is it that cost a title?

674
00:35:00,920 --> 00:35:02,640
Speaker 2: What would you call that late stage venture?

675
00:35:02,760 --> 00:35:06,440
Speaker 13: Late stage privates with the value crews, where the value yeah,

676
00:35:06,440 --> 00:35:09,040
Speaker 13: and where the value crews, yeah. And the centerpiece of

677
00:35:09,080 --> 00:35:11,319
Speaker 13: the investment thesis is around the founder and the big

678
00:35:11,320 --> 00:35:12,839
Speaker 13: decisions that the founder has to make.

679
00:35:13,160 --> 00:35:15,200
Speaker 2: It's a lot of key man risk to model for.

680
00:35:15,440 --> 00:35:17,759
Speaker 13: Yes, that's right, But I think the more important thing

681
00:35:17,760 --> 00:35:19,799
Speaker 13: to model for is what can go right? Okay, you

682
00:35:19,800 --> 00:35:23,080
Speaker 13: know we always ask ourselves, you know, it's hard to

683
00:35:23,160 --> 00:35:25,520
Speaker 13: imagine what could go right. And we even see this

684
00:35:25,600 --> 00:35:27,959
Speaker 13: with mature companies. If you look back at the time

685
00:35:28,520 --> 00:35:30,960
Speaker 13: when you know the iPhone came out, If you look

686
00:35:30,960 --> 00:35:34,520
Speaker 13: at the two thousand and nine consensus analyst estimates for

687
00:35:34,560 --> 00:35:37,319
Speaker 13: what Apple was going to do, and that in two

688
00:35:37,320 --> 00:35:39,000
Speaker 13: thousand and nine. For the next four years, and then

689
00:35:39,040 --> 00:35:41,640
Speaker 13: fast forward four years, they actually beat those numbers by

690
00:35:41,680 --> 00:35:44,080
Speaker 13: three x. And that's probably the most covered company in

691
00:35:44,120 --> 00:35:46,600
Speaker 13: the world. So we like to think with a great founder,

692
00:35:46,640 --> 00:35:48,200
Speaker 13: with a technology trend on its.

693
00:35:48,080 --> 00:35:49,480
Speaker 2: Back, what can go right?

694
00:35:49,680 --> 00:35:52,240
Speaker 13: And you know, if you look at this last cycle

695
00:35:52,320 --> 00:35:54,920
Speaker 13: that we've just gone through pre AI, you know, this

696
00:35:55,040 --> 00:35:59,920
Speaker 13: cycle of mobile phones, social e commerce, SaaS, cloud all

697
00:36:00,120 --> 00:36:03,800
Speaker 13: put together, the big story is that that big trend

698
00:36:03,880 --> 00:36:06,040
Speaker 13: added about twenty five to thirty.

699
00:36:05,840 --> 00:36:07,120
Speaker 2: Trillion of new market cap.

700
00:36:07,600 --> 00:36:09,439
Speaker 13: And I happen to think that on this AI wave,

701
00:36:09,480 --> 00:36:11,120
Speaker 13: on the back of this AI wave, the.

702
00:36:11,080 --> 00:36:12,320
Speaker 2: Trend's going to be even bigger.

703
00:36:13,000 --> 00:36:16,040
Speaker 3: You head a growth team that manages twenty two billion

704
00:36:16,080 --> 00:36:20,160
Speaker 3: dollars across five funds. But if you think about it holistically,

705
00:36:20,320 --> 00:36:25,560
Speaker 3: you're basically in the top fifteen private companies by valuation,

706
00:36:25,640 --> 00:36:29,399
Speaker 3: which would have included SpaceX before it went public. How

707
00:36:29,400 --> 00:36:33,160
Speaker 3: are you now deploying capital new capital into new companies,

708
00:36:33,320 --> 00:36:35,720
Speaker 3: you know, with those existing investments in mind.

709
00:36:36,200 --> 00:36:38,799
Speaker 13: Yeah, Look, our whole thesis is we want to be

710
00:36:39,080 --> 00:36:42,680
Speaker 13: involved in the best companies at the earliest stage possible

711
00:36:42,880 --> 00:36:44,960
Speaker 13: and then continue to back them every step of the

712
00:36:44,960 --> 00:36:48,600
Speaker 13: way as they need capital, and often that has been

713
00:36:48,840 --> 00:36:49,960
Speaker 13: through late stage rounds in the.

714
00:36:49,920 --> 00:36:52,759
Speaker 3: Private market because you have a newer fund, right which

715
00:36:52,760 --> 00:36:54,359
Speaker 3: you can deploy capital out there.

716
00:36:54,360 --> 00:36:54,600
Speaker 2: We do.

717
00:36:54,719 --> 00:36:57,960
Speaker 13: Yeah, we we have our LSV five Late Stage Venture

718
00:36:58,040 --> 00:37:00,920
Speaker 13: Fund five as we call it, it's our fifth fund.

719
00:37:00,920 --> 00:37:03,680
Speaker 13: It's about a seven billion dollar fund that we're deploying

720
00:37:03,680 --> 00:37:06,240
Speaker 13: out of currently, and we see a ton of really

721
00:37:06,239 --> 00:37:08,480
Speaker 13: interesting opportunities. So you know, if you go back to

722
00:37:08,520 --> 00:37:11,920
Speaker 13: the market that we're seeing and just look at our

723
00:37:12,000 --> 00:37:15,359
Speaker 13: portfolio at a sixteen Z and our latest fund, our

724
00:37:15,400 --> 00:37:18,520
Speaker 13: portfolio dollar weighted is growing over one hundred percent year

725
00:37:18,560 --> 00:37:21,720
Speaker 13: over year. If you compare that to the size similar

726
00:37:21,760 --> 00:37:24,919
Speaker 13: sized companies in the public markets, those companies are growing

727
00:37:24,960 --> 00:37:26,880
Speaker 13: about twenty percent year over year. So we put a

728
00:37:26,960 --> 00:37:30,759
Speaker 13: huge premium on very fast growth, great founders, market leadership,

729
00:37:30,920 --> 00:37:32,239
Speaker 13: and sort of building.

730
00:37:31,880 --> 00:37:33,000
Speaker 2: On the back of the big trends.

731
00:37:33,680 --> 00:37:35,799
Speaker 3: Also noting the cap tables look a bit different like

732
00:37:35,800 --> 00:37:40,280
Speaker 3: with the mutual funds private growth equity. David George Havenjreson Horowitz,

733
00:37:40,440 --> 00:37:42,080
Speaker 3: head of Growth and general partner.

734
00:37:42,160 --> 00:37:43,840
Speaker 2: Really grateful to have you on Bloomberg Tech. Thank you

735
00:37:43,960 --> 00:37:44,399
Speaker 2: very much.

736
00:37:44,719 --> 00:37:48,520
Speaker 3: Coming up, Cerebris reported its first ever quarterly earnings since

737
00:37:48,560 --> 00:37:51,560
Speaker 3: going public. CEO Andrew Feldman's joining us. The stock is

738
00:37:51,600 --> 00:37:54,320
Speaker 3: down seventeen percent. There's a lot to unpack there. This

739
00:37:54,480 --> 00:38:12,320
Speaker 3: is Bloomberg Tech. Crebress reported quarterly earnings for the first

740
00:38:12,360 --> 00:38:15,720
Speaker 3: time since going public last month. It's sales outlook beat

741
00:38:15,840 --> 00:38:19,480
Speaker 3: Wall Street estimates, but still disappointed investors hoping to see

742
00:38:19,520 --> 00:38:22,440
Speaker 3: the company carve out a bigger slice of the aident

743
00:38:22,880 --> 00:38:26,440
Speaker 3: center market. Right now, shares down seventeen point five percent,

744
00:38:26,480 --> 00:38:29,080
Speaker 3: its biggest drop in its quite short history as a

745
00:38:29,080 --> 00:38:32,520
Speaker 3: public company. What's behind that? CEO Andrew Feldman's with us

746
00:38:32,560 --> 00:38:34,000
Speaker 3: and welcome back to Bloomberg Tech.

747
00:38:34,080 --> 00:38:34,440
Speaker 2: Andrew.

748
00:38:34,640 --> 00:38:36,120
Speaker 3: You know, there was a time where we would talk

749
00:38:36,160 --> 00:38:40,239
Speaker 3: about the merits of top to tail server ownership, how

750
00:38:40,360 --> 00:38:41,920
Speaker 3: owning all of the content of Now we're going to

751
00:38:41,920 --> 00:38:44,480
Speaker 3: talk about margin contraction, and we're going to talk about

752
00:38:44,520 --> 00:38:47,840
Speaker 3: the stock being down seventeen percent. That to me is

753
00:38:48,120 --> 00:38:50,720
Speaker 3: kind of the mismatch that the outlook on the sales

754
00:38:50,800 --> 00:38:53,360
Speaker 3: side beat Wall Street estimates. I think a lot of

755
00:38:53,360 --> 00:38:57,560
Speaker 3: people are trying to understand the sequential margin decline and

756
00:38:57,600 --> 00:39:00,000
Speaker 3: for me that this is about ramping output for two

757
00:39:00,120 --> 00:39:02,040
Speaker 3: big customers Is that true.

758
00:39:02,640 --> 00:39:02,920
Speaker 5: Yeah.

759
00:39:03,400 --> 00:39:05,920
Speaker 14: I think what we did is we put forward a

760
00:39:05,960 --> 00:39:09,080
Speaker 14: plan in the start of twenty six, we shared it

761
00:39:09,080 --> 00:39:12,839
Speaker 14: with investors as we went public, and we're ahead of plan.

762
00:39:13,360 --> 00:39:14,879
Speaker 5: You know. We delivered record.

763
00:39:14,640 --> 00:39:17,440
Speaker 14: Revenues of one hundred and ninety one million of ninety

764
00:39:17,480 --> 00:39:21,160
Speaker 14: two percent year over year, and for our cloud business,

765
00:39:21,480 --> 00:39:23,200
Speaker 14: you know, it was up one hundred and sixty seven

766
00:39:23,239 --> 00:39:30,719
Speaker 14: percent year over year. We beat margin consensus substantially, and

767
00:39:30,760 --> 00:39:33,920
Speaker 14: then we guided for full year the growth.

768
00:39:33,680 --> 00:39:35,800
Speaker 5: Margins would be ten percent better than plant.

769
00:39:36,719 --> 00:39:39,839
Speaker 14: We also shared the in Q two and Q three

770
00:39:40,680 --> 00:39:44,600
Speaker 14: we would go back to some of our customers and

771
00:39:44,640 --> 00:39:46,719
Speaker 14: we would rent back year that we'd sold them to

772
00:39:46,719 --> 00:39:48,759
Speaker 14: try and keep up with demand, and then that would

773
00:39:48,800 --> 00:39:50,680
Speaker 14: have a margin impact on the order ten.

774
00:39:50,560 --> 00:39:51,400
Speaker 5: Or fifteen points.

775
00:39:52,360 --> 00:39:56,680
Speaker 14: We did that to keep our customers close to be

776
00:39:56,719 --> 00:39:59,839
Speaker 14: sure we could keep up with their extraordinary demand for

777
00:40:00,080 --> 00:40:04,840
Speaker 14: or for our product for fast inference, and so that

778
00:40:05,000 --> 00:40:07,200
Speaker 14: that was the story.

779
00:40:09,239 --> 00:40:12,319
Speaker 5: On every metric we put out, we're ahead of plan.

780
00:40:13,680 --> 00:40:14,600
Speaker 2: Have the proceeds from.

781
00:40:14,520 --> 00:40:17,239
Speaker 3: The IPO actually allowed you to move more quickly in

782
00:40:17,360 --> 00:40:19,040
Speaker 3: ramping up capacity?

783
00:40:19,640 --> 00:40:24,719
Speaker 14: Yeah, I think capacity is the largest constraint right now

784
00:40:24,760 --> 00:40:25,280
Speaker 14: for everyone.

785
00:40:25,400 --> 00:40:27,120
Speaker 5: Data centers are and.

786
00:40:27,080 --> 00:40:34,200
Speaker 14: We've significantly increased our our ability and our pipeline for

787
00:40:34,280 --> 00:40:40,040
Speaker 14: data centers, which is now very large. You know, we

788
00:40:40,080 --> 00:40:44,279
Speaker 14: announced a data center partnership with Bell Canada for one

789
00:40:44,320 --> 00:40:47,360
Speaker 14: hundred and twenty megawatts that will be delivered in twenty

790
00:40:47,360 --> 00:40:53,040
Speaker 14: twenty seven. We are pursuing data centers across the US,

791
00:40:53,080 --> 00:40:55,840
Speaker 14: in Canada, in Europe, in the Middle East.

792
00:40:56,880 --> 00:40:57,560
Speaker 5: There are.

793
00:40:59,239 --> 00:41:04,319
Speaker 14: The resources that we have now at our disposal give

794
00:41:04,400 --> 00:41:07,640
Speaker 14: us tremendous advantage in the pursuit of this The limiting

795
00:41:07,680 --> 00:41:08,720
Speaker 14: factor data centers.

796
00:41:10,400 --> 00:41:13,919
Speaker 3: What you're talking about, like matter of factly, is buildings

797
00:41:14,239 --> 00:41:17,040
Speaker 3: not necessarily the compute, right It's not what you guys

798
00:41:17,040 --> 00:41:20,080
Speaker 3: are offering. How difficult right now is it is to

799
00:41:20,200 --> 00:41:24,239
Speaker 3: get moving in America or other markets, to get planning approval,

800
00:41:24,440 --> 00:41:26,600
Speaker 3: get the concrete, get the labor, get the thing built.

801
00:41:27,760 --> 00:41:30,800
Speaker 14: Now that that's the irony of this market, that the

802
00:41:32,200 --> 00:41:36,680
Speaker 14: AI market is moving at blistering speed and we are

803
00:41:36,680 --> 00:41:39,640
Speaker 14: being constrained by data centers which move with the speed

804
00:41:39,640 --> 00:41:43,319
Speaker 14: of real estate. And so that is a problem that

805
00:41:43,440 --> 00:41:48,440
Speaker 14: is being confronted by by everybody in the category, by

806
00:41:48,520 --> 00:41:53,240
Speaker 14: the hyperscalers, by the neo clouds, by the new generation clouds.

807
00:41:53,280 --> 00:41:56,520
Speaker 14: Everybody is confronting this similar problem.

808
00:41:56,719 --> 00:42:01,600
Speaker 3: Andrew Cerebris does not rely on traditional chip HBM. Would

809
00:42:01,680 --> 00:42:04,680
Speaker 3: you just explain that the basics of the technology, But

810
00:42:05,040 --> 00:42:08,040
Speaker 3: how insulated are you from the memory bottleneck that others

811
00:42:08,080 --> 00:42:08,919
Speaker 3: are experiencing.

812
00:42:09,920 --> 00:42:12,000
Speaker 5: Yeah, that's a really good point.

813
00:42:12,040 --> 00:42:16,000
Speaker 14: Because of our innovative architecture, because of our wafer scale approach,

814
00:42:16,719 --> 00:42:21,120
Speaker 14: we don't use HBM. HBM is a type of DRAM

815
00:42:21,160 --> 00:42:23,239
Speaker 14: and it's made by three companies, one of whom is

816
00:42:23,280 --> 00:42:28,239
Speaker 14: reporting shortly right. That's Microns, Heenex and Samsung. There's a

817
00:42:28,280 --> 00:42:32,040
Speaker 14: global shortage, it's extremely expensive, lead times are long, and

818
00:42:32,200 --> 00:42:35,320
Speaker 14: we don't use it, so we have a tremendous advantage there.

819
00:42:36,120 --> 00:42:42,160
Speaker 14: The other constraints in the supply chain for many are cooths,

820
00:42:42,200 --> 00:42:44,440
Speaker 14: which is a process inside of TSMC.

821
00:42:44,760 --> 00:42:45,920
Speaker 5: Again we don't use it.

822
00:42:46,840 --> 00:42:50,800
Speaker 14: And the third is a capacity at the three nanometer node.

823
00:42:51,040 --> 00:42:56,040
Speaker 14: That's space in TSMC's factory that makes three and nanimeter chips.

824
00:42:56,080 --> 00:42:59,240
Speaker 5: Again we don't use it. We're at the five nanometer node.

825
00:43:00,080 --> 00:43:03,520
Speaker 14: Our architecture has allowed us to deliver the fastest inference

826
00:43:03,560 --> 00:43:06,880
Speaker 14: in the world by an order of magnitude while avoiding

827
00:43:08,680 --> 00:43:13,880
Speaker 14: the main supply supply chain constraints faced by others in

828
00:43:13,920 --> 00:43:14,360
Speaker 14: the field.

829
00:43:15,440 --> 00:43:18,400
Speaker 3: Can you say, hand on heart, not just winning business,

830
00:43:18,400 --> 00:43:20,120
Speaker 3: but if you actually been able to go to a

831
00:43:20,160 --> 00:43:23,080
Speaker 3: customer and say we can get this compute online faster

832
00:43:23,120 --> 00:43:26,440
Speaker 3: than others for those reasons you just outlined and then actually.

833
00:43:26,239 --> 00:43:26,920
Speaker 2: Gone and done it.

834
00:43:27,600 --> 00:43:28,240
Speaker 5: Oh for sure.

835
00:43:29,200 --> 00:43:30,279
Speaker 2: I mean any cases I.

836
00:43:30,239 --> 00:43:36,160
Speaker 14: Signed, we signed. For example, we signed our contract with

837
00:43:36,239 --> 00:43:42,040
Speaker 14: open Ai on December twenty fourth and had them in

838
00:43:42,160 --> 00:43:46,160
Speaker 14: for production on February first. That's unheard of.

839
00:43:46,160 --> 00:43:50,120
Speaker 3: So that's quick as I went really quickly Andrew this morning.

840
00:43:50,200 --> 00:43:55,360
Speaker 3: Open Ai is out with Kalapino Intelligence processor. But everyone

841
00:43:55,440 --> 00:43:59,000
Speaker 3: is compute constrained, right, How do you interpret the Frontier

842
00:43:59,080 --> 00:44:02,359
Speaker 3: Labs going to custom and a six alongside their other

843
00:44:02,520 --> 00:44:03,720
Speaker 3: compute options.

844
00:44:04,200 --> 00:44:04,239
Speaker 12: Ed.

845
00:44:04,320 --> 00:44:06,000
Speaker 14: One of the things we've been saying all along is

846
00:44:06,280 --> 00:44:10,040
Speaker 14: that this market is enormous and is going to be

847
00:44:10,080 --> 00:44:15,840
Speaker 14: met with a heterogeneous collection of architectures for hardware. This

848
00:44:15,960 --> 00:44:19,799
Speaker 14: market will not be consolidated around GPUs. There will be

849
00:44:19,960 --> 00:44:22,759
Speaker 14: a six, There will be a six from Hyperscalers, there

850
00:44:22,760 --> 00:44:26,520
Speaker 14: will be a six from from Labs, and then there'll

851
00:44:26,520 --> 00:44:31,520
Speaker 14: be companies like Cerebrase with pioneering architectures who all of

852
00:44:31,600 --> 00:44:35,400
Speaker 14: us will will will take big bites of this enormous market.

853
00:44:35,440 --> 00:44:37,680
Speaker 14: I think one of the things that's difficult to get

854
00:44:37,719 --> 00:44:41,000
Speaker 14: your head around is just how big the compute market

855
00:44:41,080 --> 00:44:43,680
Speaker 14: is right now. That one of the things AI does

856
00:44:44,080 --> 00:44:48,439
Speaker 14: is it makes tractable for compute much of the world

857
00:44:48,440 --> 00:44:51,360
Speaker 14: around us, and that really wasn't the case prior to AI.

858
00:44:53,200 --> 00:44:55,319
Speaker 3: Andrew I it's if the world is simple, and it's

859
00:44:55,400 --> 00:44:58,400
Speaker 3: money that greases the wheels to get your industry going.

860
00:44:58,680 --> 00:45:01,080
Speaker 3: Can we see you come back to capital markets in

861
00:45:01,080 --> 00:45:02,840
Speaker 3: some form just so you can move quicker.

862
00:45:04,160 --> 00:45:06,600
Speaker 14: We have more than nine billion on the balance sheet,

863
00:45:06,800 --> 00:45:12,160
Speaker 14: I think, so we're really pleased with our position there.

864
00:45:12,200 --> 00:45:16,560
Speaker 14: But of course we are always scanning both the capital markets,

865
00:45:16,880 --> 00:45:20,360
Speaker 14: both equity and debt for ways to accelerate our growth.

866
00:45:22,560 --> 00:45:25,640
Speaker 3: Finally, how are you judging success yourself? What is the

867
00:45:25,640 --> 00:45:28,200
Speaker 3: milestone that you'd pitch to the market to keep closest

868
00:45:28,239 --> 00:45:28,879
Speaker 3: attention to.

869
00:45:30,080 --> 00:45:32,960
Speaker 14: Well, I think I think if my mother's proud of me,

870
00:45:33,520 --> 00:45:36,400
Speaker 14: I think that's the biggest.

871
00:45:35,960 --> 00:45:37,399
Speaker 5: Thing you can you can ask for.

872
00:45:38,040 --> 00:45:43,160
Speaker 14: I think for markets, I think when you lay out

873
00:45:43,200 --> 00:45:47,600
Speaker 14: a plan that is aggressive and you crush it, Uh,

874
00:45:48,120 --> 00:45:50,840
Speaker 14: that's how you feel good about both your ability to

875
00:45:51,280 --> 00:45:54,000
Speaker 14: execute in your ability to predict your own execution.

876
00:45:54,440 --> 00:45:59,000
Speaker 5: And so you know, we announced yesterday that.

877
00:45:58,840 --> 00:46:01,839
Speaker 14: That we would beat our our full year we give

878
00:46:01,920 --> 00:46:06,279
Speaker 14: full year guidance that was ten gross margin points above concernsus.

879
00:46:07,520 --> 00:46:09,319
Speaker 14: You ought to be proud of that, and we got

880
00:46:09,360 --> 00:46:12,560
Speaker 14: to continue to execute and continue to set extraordinarily high

881
00:46:12,600 --> 00:46:14,680
Speaker 14: barrows and then continue to.

882
00:46:16,440 --> 00:46:18,279
Speaker 5: Beat them.

883
00:46:18,680 --> 00:46:22,880
Speaker 3: Cerebra Ceo, Andrew Feldman, thank you very much. Indeed, really

884
00:46:23,320 --> 00:46:25,799
Speaker 3: Andrew alluded to it. Micron is the big one after

885
00:46:25,840 --> 00:46:28,560
Speaker 3: the closing bell. Top line growth almost three hundred percent

886
00:46:28,719 --> 00:46:32,080
Speaker 3: year on year, net income growth twelve hundred percent.

887
00:46:31,960 --> 00:46:35,640
Speaker 2: Year on year. The bar is very very high the market.

888
00:46:35,920 --> 00:46:38,840
Speaker 3: It's very analogous to Nvidia what we saw twenty twenty

889
00:46:38,840 --> 00:46:42,640
Speaker 3: two to twenty twenty five, massive growth, but investors always

890
00:46:42,680 --> 00:46:45,319
Speaker 3: wanting more. The stocks down eight ten percent going into

891
00:46:45,320 --> 00:46:49,680
Speaker 3: that print. Another stock we're watching today US fast food

892
00:46:49,760 --> 00:46:52,880
Speaker 3: chain Wendy's surging as much as forty two percent.

893
00:46:52,920 --> 00:46:55,320
Speaker 2: But wait, what does that have to do with tech?

894
00:46:55,880 --> 00:46:59,479
Speaker 3: Well, it appears Wendy's has become the latest memes stock

895
00:46:59,520 --> 00:47:02,840
Speaker 3: target shot up the rankings on stock Twitz climb to

896
00:47:02,840 --> 00:47:04,920
Speaker 3: the top of the platform's trending list. Seems to have

897
00:47:04,920 --> 00:47:07,520
Speaker 3: been sparked by a now deleted post on Reddit's Wall

898
00:47:07,560 --> 00:47:10,560
Speaker 3: Street Bets forum that urged members to save Wendy's before

899
00:47:10,600 --> 00:47:12,960
Speaker 3: it's too late. That does it for this edition of

900
00:47:12,960 --> 00:47:15,680
Speaker 3: Bloomberg Tech. Recap everything on the podcast. You know where

901
00:47:15,680 --> 00:47:18,360
Speaker 3: to find it online, Apple, Spotify and iHeart and all

902
00:47:18,400 --> 00:47:19,520
Speaker 3: the Bloomberg platforms.

903
00:47:19,560 --> 00:47:21,239
Speaker 2: This is Bloomberg Tech.