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

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Speaker 1: from coast to coast with Caroline Hide in New York

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Speaker 1: and Vla Loow in San Francisco.

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Speaker 2: This is Bloomberg Tech.

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Speaker 3: Coming up, Open Ai releases GPT five. We'll discuss how

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Speaker 3: the rollout is going in the enterprise opportunity with Open

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Speaker 3: Ai COO Brad Lightcap, plus the race for AI data centers.

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Speaker 3: It heats up with Softbak making moves in Ohio, while

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Speaker 3: Meto announces financing for its expansion in Louisiana. And we

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Speaker 3: keep on these tech earnings. We'll speak with CEOs and Twilio,

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Speaker 3: Chime and Acami. The first we return to the public markets.

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Speaker 3: We're a new record high for the Nasdaq one hundred,

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Speaker 3: so we managed to push on higher, but I'm looking

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Speaker 3: at individual stocks that help contribute to the moves. Tesla

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Speaker 3: actually a decent points perspective higher.

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Speaker 2: We're up three point three percent.

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Speaker 3: Breaking news come Foring one and only Ed Ludlow about

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Speaker 3: Dojo the future of the supercomputer. Shares actually managed to

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Speaker 3: take high, even though we see that they're wrapping that

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Speaker 3: down focusing more on using third parties. We'll get to

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Speaker 3: that story a little bit later. I'm looking at Intel

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Speaker 3: off by two ten percent. Have been trading higher on

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Speaker 3: the pushback from the CEO saying he has committed the

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Speaker 3: US and National Security. Will get to that in a

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Speaker 3: moment as well, But first we want to really dive

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Speaker 3: into the world.

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Speaker 2: Of data centers.

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Speaker 3: SoftBank taking ownership of fox Conn's EV plant in Ohio

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Speaker 3: in order to kick SAT, the Japanese company's five hundred

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Speaker 3: billion dollar Stargate data center project with open Ai and Oracle.

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Speaker 3: Bloomberg's Peter Elstrom joins us for Ashleson reporting that Ed

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Speaker 3: Ludlow was really driving before he got on his flight

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Speaker 3: to the United Kingdom. Peter, it's an interesting deal. Basically

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Speaker 3: soft Bank kind of wanting to get fox Conn more

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Speaker 3: integrated with its manufacturing part of this.

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Speaker 4: Yeah, this is kind of a mysterious deal. So fox

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Speaker 4: Cohn made this announcement a couple days ago. They said

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Speaker 4: they were selling this facility to an entity called Crescent Dune,

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Speaker 4: that nobody knew who it was. So we've discovered that

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Speaker 4: in fact, at SoftBank they had been partners in the past.

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Speaker 4: Soft Bank is going to own the facility, and then

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Speaker 4: soft Bank and fox Con together are going to work

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Speaker 4: on these AI developments. They're probably going to build AI

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Speaker 4: servers in that plant to be able to use throughout

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Speaker 4: the Stargate venture that they're supposed to be building in

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Speaker 4: the US. As we've talked about a few times before,

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Speaker 4: open Ai and soft Bank announced that Stargate venture with

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Speaker 4: President Trump alongside them, talking about spending one hundred billion

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Speaker 4: dollars immediately at the beginning of the year or five

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Speaker 4: hundred billion dollars over the long term. But it's been

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Speaker 4: kind of slow to roll out in a number of

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Speaker 4: different cases. So this deal is aimed at giving them

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Speaker 4: a bit of a kickstart so they can move ahead

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Speaker 4: with some of those projects, be able to build the

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Speaker 4: AI servers, and then actually be able to build the

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Speaker 4: data centers over the long term.

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Speaker 3: It's interesting this pivot from a US macro perspective from

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Speaker 3: evs into AI data centers. But open ai has really

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Speaker 3: been pushing had almost on its own hair. It's been

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Speaker 3: going into Norway for its infrastructure, has been going to

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Speaker 3: the Middle East and in the United States with Oracle

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Speaker 3: and almost leaving well it felt like soft Bank behind

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Speaker 3: in EMO right.

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Speaker 4: Open Ai has a lot of power here to be

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Speaker 4: able to pick their partners, as we've talked about before. Also,

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Speaker 4: they are building this big data center in Avelene, Texas

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Speaker 4: that's been going quite well, quite aggressively. Open Ai course

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Speaker 4: was very closely affiliated with Microsoft in the early days.

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Speaker 4: It put in a bunch of money early on. It

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Speaker 4: had been kind of their cloud computing supportive partner for

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Speaker 4: a long period of time. Now they've also talked about

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Speaker 4: working with soft Bank Oracles. They're hurt too, so they're

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Speaker 4: sort of choosing their dance partners as it suits their need.

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Speaker 4: At this point, soft Bank, of course wants to be

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Speaker 4: able to move more aggressively into the AI field. Soft

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Speaker 4: Bank shares are actually on a tear right now. They're

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Speaker 4: an all time high. Masieo she Son is certainly getting

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Speaker 4: a bit of a tailwind because they put that money

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Speaker 4: into Open Ai at a lower valuation. Now they've been

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Speaker 4: able to ride that up quite a bit. So I

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Speaker 4: think there is some optimism that SoftBank is getting its

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Speaker 4: footing here, is being able to make some progress in

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Speaker 4: the AI feel bit Masio Sisnis wanted for.

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Speaker 5: A long time.

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Speaker 3: Great context. Peter Elstrom, we thank you so much. And look,

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Speaker 3: speaking of Stargate tune in later this hour for an

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Speaker 3: interview with the Open AI COO Brad Lightcap on GPT.

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Speaker 2: Five and much more.

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Speaker 3: But in more data center news, it keeps on coming.

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Speaker 3: Meta has announced financing for a twenty nine billion dollar

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Speaker 3: data center expansion in rural Louisiana. Now it's actually selected

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Speaker 3: Pimco and Blue Out Capital to lead theb in equity

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Speaker 3: financing here.

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Speaker 2: That's all according to sources.

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Speaker 3: Representatives of these three companies actually declined to comment. Let's

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Speaker 3: get back to also elsewhere in chips Intel, the saga continues.

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Speaker 3: After the US President, of course, called for at CEO's

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Speaker 3: resignation over conflicts of interest, Intel CEO lit Bhutan replied

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Speaker 3: in a letter to staff posted on the company's website,

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Speaker 3: where he says he got the full backing of the

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Speaker 3: board and what they are working on with the administration

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Speaker 3: to quote ensure they have the facts. Mags in King

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Speaker 3: rings us with more facts. What does he think there

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Speaker 3: is misinformation about Ian?

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Speaker 6: Yeah, I mean we saw that the Trump social media posting,

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Speaker 6: and this came on the back of what a senator

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Speaker 6: had done and sending a letter to Intel's chairman saying, hey, look,

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Speaker 6: all of these things have happened in Bhutan's past. Are

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Speaker 6: we sure he's the right person to be running Intel?

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Speaker 6: And there was a lot of sort of cluging of

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Speaker 6: facts together and in accusations made, which the President then

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Speaker 6: responded to, and finally late last night we had Lib

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Speaker 6: Bhutan directly addressing that and saying, look, there's a lot

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Speaker 6: of misinformation out there. You know, we look at the

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Speaker 6: facts and don't worry. I'm still going to be the

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Speaker 6: CEO of Intel, and I've got the boards backing.

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Speaker 3: Yeah, he's concerned about his past roles at Walden International

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Speaker 3: venture capital firm that does make bets in China and

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Speaker 3: based in Singapore. Is a founder of it. Also Kina's

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Speaker 3: Design Systems, which was CEO.

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Speaker 2: Of This sort of should have been known.

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Speaker 3: He was on the board of Intel for a long

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Speaker 3: time himself well known. What do you think this means

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Speaker 3: for their manufacturing presence in the United States? Because I

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Speaker 3: almost got a hint that maybe he is reing committing

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Speaker 3: to that here.

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Speaker 6: Yeah, I mean, this is arguably I mean, first of all,

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Speaker 6: there was nothing new about these accusations against him. Twenty

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Speaker 6: twenty three we had the House Committee looking into this,

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Speaker 6: so nothing really new here, But You're right. Perhaps the

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Speaker 6: trigger point had come a week earlier during earnings when

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Speaker 6: they discussed the possibility of not moving forward with the

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Speaker 6: latest manufacturing technology, of cutting back on spending, maybe not

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Speaker 6: building Ohio, maybe not building other plants. And this is

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Speaker 6: not what the Trump administration wants to hear when they

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Speaker 6: want to be talking about what we're bringing to America

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Speaker 6: and what we're doing as soft Bank has just played

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Speaker 6: too with the news that we broke there, So it

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Speaker 6: was a kind of counternews cycle there that they didn't

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Speaker 6: really think they were more perhaps talking about what investors

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Speaker 6: wanted to hear, which is we're going to get back

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Speaker 6: to profitability quicker, we're going to spend less, and that

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Speaker 6: kind of unfortunately appears to have blown up on them

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Speaker 6: in the political arena and they had to sort of

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Speaker 6: address that late last night in king.

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Speaker 3: I'm sure the story will continue, Thank you very much. Now,

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Speaker 3: let's bring in an investor perspective. Kim Forrest going to

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Speaker 3: break this all down. Your chief investment officer are Boca

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Speaker 3: Capital Partners.

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Speaker 2: You do have exposure to Intel.

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Speaker 3: I'm interested in your perspective on what they now need

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Speaker 3: to do in terms of turning the narrative.

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Speaker 7: Sure, well, this is just kind of a distraction the

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Speaker 7: whole CEO thing he's in. I'm sure the board thoroughly

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Speaker 7: looked at him, so I'm going to move on from that.

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Speaker 7: But he is there because the last several CEOs have

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Speaker 7: just kind of worn down the bright shining starre that

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Speaker 7: is Intel, and he is trying to find his way

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Speaker 7: and trying to find where Intel should play. And I

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Speaker 7: think it's pretty clear that he's looking at what they

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Speaker 7: can do right now. And let's just say they're not

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Speaker 7: up to the task of making a Blackwell competitor, but

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Speaker 7: they do have some good technologies that are used in AI,

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Speaker 7: mostly around packaging. And if I can feel your eyes

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Speaker 7: glazing over, don't do that, because packaging is the thing

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Speaker 7: that makes really low, you know, small scale chips work

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Speaker 7: because you have to make sure the electrons are staying

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Speaker 7: where they're supposed to be going.

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Speaker 8: So packaging is a big thing.

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Speaker 7: But he has a very large task ahead of him

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Speaker 7: of making Intel relevant because let's say it's been drifting

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Speaker 7: off for the past ten years.

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Speaker 3: Our eyes glazing over about parts of ship making never Kim,

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Speaker 3: I am interested though more broadly about Therefore, this overwhelming

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Speaker 3: drive towards data center capacity and what that does for

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Speaker 3: tailwinds for the chip makers that you look at that

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Speaker 3: we had a This week has been a long one

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Speaker 3: in the world of chips. You've got AMD numbers which

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Speaker 3: are still showing growth, it's not quite at the pace

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Speaker 3: that people wanted to see. You've also had, of cause,

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Speaker 3: this threat of one hundred percent tariffs on semiconductors coming

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Speaker 3: into the United States, but then huge carve outs. Where

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Speaker 3: do we focus attention when you want exposure to the sector?

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Speaker 7: Well, I would have to unbelievably agree that AI is

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Speaker 7: the thing that's driving it forward now, and it's a

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Speaker 7: very narrow slice of AI. We're talking about the data center.

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Speaker 7: What I'm really interested in is, yes, we're going to

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Speaker 7: have large language models, large reasoning models. I'm much more

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Speaker 7: interested in smaller models that companies are going to actually

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Speaker 7: use to become more productive. The large language models are

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Speaker 7: getting all the love, but I'm not sure that they

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Speaker 7: generate quite enough interest in direct measurable productivity.

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Speaker 5: Right.

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Speaker 7: They're being played around with at this point, But that's

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Speaker 7: where all the money's going into, is building data centers

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Speaker 7: that support large language and large reasoning models.

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Speaker 5: Will that go on for ever?

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Speaker 9: Know.

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Speaker 7: I think what's more interesting is the further we get

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Speaker 7: away from the data centers out to where the information

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Speaker 7: is going to be used. That's when more companies are

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Speaker 7: going to be involved in tel may have its place

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Speaker 7: out there, because what we really want are not necessarily

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Speaker 7: walking around robots, but robots that do things that are

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Speaker 7: under the control of the data center kind of computing.

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Speaker 7: So that is a very complicated world, and more semiconductors

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Speaker 7: are going to be needed.

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Speaker 2: Okay, so spread that love a little bit.

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Speaker 3: It's so interesting that this comes hot on the heels

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Speaker 3: of the scoop from Ludlow talking.

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Speaker 2: About how Teser itself is riding down.

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Speaker 3: It's focused on hardware and it's own chip making with

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Speaker 3: Dojo Supercomputer and looking to others to provide the hardware

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Speaker 3: going forward, more reliant.

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Speaker 2: On video and on Samsung kim.

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Speaker 3: Where else do we like then, other than all eyes

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Speaker 3: on in video and MD to a certain extent.

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Speaker 7: Well, I really love Micron, and because for many reasons,

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Speaker 7: Micron has the hot dram that goes on the Blackwell

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Speaker 7: chip and probably on AMD's chip, and that's memory that's

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Speaker 7: going to move data in and out of a chip, right,

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Speaker 7: So that's thing one. But thing two is we are

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Speaker 7: generating so much information and it's not on spinning discs anymore.

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Speaker 7: It's more on nand chips. So I love that area.

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Speaker 7: I think it's an unloved area and really unexplored. So

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Speaker 7: I think we could never underestimate the amount of storage

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Speaker 7: that AI uses and how much we're going to have

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Speaker 7: to store just to you know, get that data that

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Speaker 7: we want to have looked at by AI. Has to

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Speaker 7: live somewhere. I'm thinking against nand devices.

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Speaker 3: Micron currently up about five percent on the day. Also,

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Speaker 3: of course t SMC we're putting that twenty six percent

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Speaker 3: growth of a month of July. We're just on a

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Speaker 3: tear in many areas. Kim Forest of Boka Capital Partners.

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Speaker 3: It's always great to check in with you. Happy weekend.

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Speaker 3: Now coming out, we're going to take a look at Twilio.

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Speaker 3: Look at the shares currently off by eighteen percent. They

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Speaker 3: reported earnings yesterday. We go deep with the CEO.

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Speaker 2: This is Bloomberg Tech.

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Speaker 3: Let's talk about cloud communications platform Twilio reporting earnings after

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Speaker 3: the market closed yesterday. The report showed an acceleration in

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Speaker 3: revenue growth that the company's gross margin earnings for share

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Speaker 3: do seem to be a concern to some analysts. Let's

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Speaker 3: bring in Twilio CEO Couzema, Ship Chandler joining us. Now

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Speaker 3: I'm looking at your shares, they are down a lot.

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Speaker 3: Just give your perspective on the gross margin.

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Speaker 10: Well, I would say, in general, we delivered a solid quarter.

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Speaker 10: I mean it was a quarter of accelerated growth, record

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Speaker 10: non gap income from operations, free cash flow. And I

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Speaker 10: think what we're finding is is that at a time

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Speaker 10: when AI is kind of this generational opportunity, we're finding

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Speaker 10: some of those tailwinds get ascribed to Twilio. I understand

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Speaker 10: the gross margin dynamic. It's not necessarily a new phenomenon

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Speaker 10: for Twilio, but it hasn't impeded our ability to get

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Speaker 10: after operating profits and generate free cash. Importantly, on free

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Speaker 10: cash we raised our guidance for the year and so

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Speaker 10: we feel pretty good about the outlook.

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Speaker 3: So for now, is the opportunity more on growth and

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Speaker 3: revenue and the AI tailwinds.

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Speaker 2: As you call it.

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Speaker 3: Because Jefferies, for example, putting out saying there are big

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Speaker 3: hopes you're going to be a big beneficiary of AI, adoption.

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Speaker 3: How is that playing out for you, because many now

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Speaker 3: potentially question it.

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Speaker 10: Yeah, I do think we'll be a big beneficiary of AI.

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Speaker 10: What I don't want folks to take away from the

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Speaker 10: print is that somehow we're returning to kind of growth

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Speaker 10: at all costs dynamic. I think quite the contrary. We're

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Speaker 10: running the company with as much focus and discipline as

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Speaker 10: we ever have. We happen to be at a time

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Speaker 10: in which, number one, we're able to take share for

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Speaker 10: a number of our competitors, and we're doing that in

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Speaker 10: a price disciplined way. And I think the second thing

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Speaker 10: is is that given that the AI is a generation opportunity,

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Speaker 10: we do see an opportunity as well to make some

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Speaker 10: short term investments that we think will drive some medium

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Speaker 10: term benefits. And I think that's the right thing to do,

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Speaker 10: and so I'm not fixated on a particular quarter. I

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Speaker 10: think over the course of time that'll play out in

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Speaker 10: our favor and certainly be a good thing for investors.

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Speaker 3: What is that investment? Then, you detailed or platform vision

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Speaker 3: almost in signal your event you're thinking about audio in particular,

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Speaker 3: I mean you are the way in which I communicate

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Speaker 3: with LIFT or with any app and many as ways

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Speaker 3: that's going to move to voice.

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Speaker 2: Do you make acquisitions therefore, I.

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Speaker 10: Think acquisitions are something that we think about. I wouldn't

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Speaker 10: necessarily read anything into that. I mean, we obviously have

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Speaker 10: some flexibility in terms of what we can do with

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Speaker 10: our capital. But I think more importantly the investment in

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Speaker 10: the short term is around voice AI for example. I

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Speaker 10: mean voice AI is where so many different AI startups

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Speaker 10: are really launching right. I mean, a lot of these

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Speaker 10: use cases that you see are voice based. We have

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Speaker 10: the benefit of delivering incredible voice infrastructure that startups can

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Speaker 10: get going with almost immediately. That's kind of on the

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Speaker 10: low end, and then on the high end, you know,

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Speaker 10: there are fully orchestrated experiences that we drive, combining our

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Speaker 10: communications capabilities across a number of channels, utilizing data as

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Speaker 10: well as utilizing AI, plugging into all manner of different lms,

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Speaker 10: and I think that's going to be exciting for us

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Speaker 10: from a growth standpoint, and it's going to drive profitability

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Speaker 10: and cash over time.

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Speaker 3: I'm looking at your one year share price move, it's

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Speaker 3: up sixty three percent, so that puts what today's move

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Speaker 3: is in perspective. Because aim but you talk about making

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Speaker 3: perhaps your acquisition yourself, or having the flexibility to do so.

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Speaker 3: Someone as are saying that maybe you're a target. Have

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Speaker 3: you had any inbound would you ever consider that?

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Speaker 10: I mean, I wouldn't comment on on M and A

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Speaker 10: one way or the other. I think we're always going

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Speaker 10: to do things that are in the best interests of

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Speaker 10: our share owners. I can tell you with conviction that

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Speaker 10: we're very focused on running a great business. We think

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Speaker 10: that we have all of the necessary ingredients to create

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Speaker 10: tremendous value for our customers. And as you alluded to

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Speaker 10: a moment ago, over the last year or so, we've

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Speaker 10: shown that we can demonstrate focus, discipline, operating rigor in

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Speaker 10: the way that we're running the company. Investors have benefited

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Speaker 10: from those attributes. And again I don't get fixated on

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Speaker 10: a particular quarter. I think over periods of time this

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Speaker 10: is going to play out very much in investors favor,

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Speaker 10: and I think they're going to read really substantial benefits.

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Speaker 3: And where are your opportunities for new wins? In particular,

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Speaker 3: when you're getting new customers on because of the voice

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Speaker 3: offerings and the communication offerings, is it geographical in nature

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Speaker 3: that you look around for expansion.

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Speaker 10: I think there are international opportunities, no doubt, but I

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Speaker 10: would say in the near term. You know, what's really

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Speaker 10: starting to happen is we're We've always kind of been

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Speaker 10: like a product led growth company, and so the vast

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Speaker 10: majority of our customers, they're actually self starters. They come

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Speaker 10: to our console, they get going, they love the usability

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Speaker 10: and the features that are our platform gives them, and

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Speaker 10: so that's really the way that people get started. So

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Speaker 10: we've been putting investment into that making as simple as

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Speaker 10: possible for our customers to get going, and right now,

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Speaker 10: at least in the immediate term, that's really played out

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Speaker 10: with respect to voice AI. Again, so many different voice

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Speaker 10: AI companies that are launching they're choosing Twilio. We're the

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Speaker 10: best known brand in the space for super simple and

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Speaker 10: easy to use, and there's a ton of value that

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Speaker 10: our customers can get out of that opportunity. On the

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Speaker 10: enterprise side, I do think what we're finding is is

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Speaker 10: that they want the kind of broader offering. Right they

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Speaker 10: want our communications capabilities, but they also want to use

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Speaker 10: data and they want to plug in the LMS that

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Speaker 10: they're excited about to be able to drive both cost

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Speaker 10: and revenue opportunities.

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Speaker 3: Because aymanship Chandla Vilios a year. We thank you so

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Speaker 3: much for your time today after the earnings and coming

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Speaker 3: up more of them more earnings. Chime releases this in

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Speaker 3: orgeral reporters. A public company and investors a little disappointed.

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Speaker 2: This is a blue bag tech. Chime It put out.

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Speaker 3: Its first earning report since going public two months ago.

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Speaker 3: Revenue for the fintech company was strong, but customer growth

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Speaker 3: it failed to reach the top end of expectations. Let's

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Speaker 3: talk it through. Chime CEO Chris Spritt is with us. Chris,

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Speaker 3: solid thirty percent revenue growth. You've got gross margin of

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Speaker 3: eighty seven percent, but it seems to be this growth

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Speaker 3: in active members twenty three percent that just failed to

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Speaker 3: meet the bar for some What do you make of it?

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Speaker 8: Well, thanks for having me. It's great to be here.

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Speaker 9: I'm so proud to be reporting on an awesome Q

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Speaker 9: one that we've had our Q two in our first

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Speaker 9: quarter as a public company, and being on the show

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Speaker 9: to share more. We had a great quarter. We like

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Speaker 9: you said, we beat consensus on that top line. We

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Speaker 9: grew thirty seven percent. We saw outsized results exceeding expectation

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Speaker 9: across the board on growth of on the revenue side,

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Speaker 9: active member growth, and our success on adjusted EBITA, and

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Speaker 9: we raised our expectations for the year as well on

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Speaker 9: the call as it relates to the active member growth.

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Speaker 9: You know, it was a great quarter for us. I

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Speaker 9: think naturally as a new company, new issuance, I think

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Speaker 9: investors are just starting to understand the nuances of our

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Speaker 9: business a bit, and we do have a seasonal business,

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Speaker 9: so on a quarter to quarter basis, sequentially, the growth

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Speaker 9: for people that maybe don't understand the seasonality the business

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Speaker 9: might have been disappointing. But the way that you really

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Speaker 9: need to look at the business is how we're growing

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Speaker 9: on a year over year basis. So in Q one

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Speaker 9: we grew actives twenty three percent. In Q two again

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Speaker 9: we grew actives twenty three percent year over year, accelerating

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Speaker 9: that rate.

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Speaker 8: So we actually had an outstanding quarter.

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Speaker 9: And I think it's just natural now that need to

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Speaker 9: make sure that we educate investors on that some of

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Speaker 9: these details of the business, such as the seasonal elements

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Speaker 9: of it.

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Speaker 3: And maybe investors were looking to competitors in the space,

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Speaker 3: not direct competitors, but certainly in the fintech space so

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Speaker 3: far just had such strength. Do you think perhaps it

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Speaker 3: was what others are doing in the market, and how

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Speaker 3: can you show that you're winning as much and building

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Speaker 3: as much.

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Speaker 9: Well, you know, I think we have a different business

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Speaker 9: model than a lot of the other FinTechs out there

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Speaker 9: in that we're really focused on serving everyday consumers and

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Speaker 9: banking them in a primary account capacity. In other words,

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Speaker 9: people signing up for Chime and using us as their

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Speaker 9: primary direct deposit account. And we're really, at the day,

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Speaker 9: at the end of the day, a payments driven business,

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Speaker 9: not a lending business. And I think that's a real

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Speaker 9: differentiation that's important for investors to understand about the core

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Speaker 9: of our business model. You know, credit and lending is

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Speaker 9: sort of a mid teens percentage of our revenue. Were

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Speaker 9: predominantly a payment driven business, which I think is quite

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Speaker 9: a bit different. And you know, we love these relationships

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Speaker 9: because it allows us to develop long term partnerships with

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Speaker 9: our members and help them in the areas that matter

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Speaker 9: most around avoiding fees, around building credit, getting some short

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Speaker 9: term liquidity, around the edges, but also just helping them

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Speaker 9: get into a healthy rhythm of savings and moving their

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Speaker 9: financial progress.

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Speaker 3: Ahead, and many of them want to do that far

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Speaker 3: more efficiently using generative AI.

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Speaker 2: That's something you've been into weaving, you've.

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Speaker 3: Got the voice, what for example, Chris, why more can

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Speaker 3: you lean into that?

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Speaker 9: We're so excited about the opportunity in AI, and I

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Speaker 9: just think, you know, what, are an exciting time to

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Speaker 9: run a technology company. We feel like we're just in

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Speaker 9: the early stages of a new industrial revolution. If you

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Speaker 9: think about, you know, the original Industrial Revolution, it was

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Speaker 9: all about new sources of energy that created it and

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Speaker 9: unlocked so many new opportunities, new industries and so forth.

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Speaker 9: I kind of think of llms as the same sort

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Speaker 9: of new form of energy that. Sure, the LLLM companies

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Speaker 9: are incredible, amazing businesusinesses. We're all using them every day.

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Speaker 9: But the opportunities for companies like Chime to leverage AI

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Speaker 9: and move it into the product experience, the operations is

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Speaker 9: just enormous. We're already serving over seventy percent of our

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Speaker 9: customer interactions with generative AI, and not only is the

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Speaker 9: cost saving exciting, but the actual outcomes are even more

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Speaker 9: exciting because we're seeing a significant increase in the satisfaction

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Speaker 9: levels of consumers getting the answers they want.

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Speaker 8: Quickly through an AI.

439
00:22:29,640 --> 00:22:32,720
Speaker 9: Of course, you can always talk to a live customer

440
00:22:32,760 --> 00:22:35,480
Speaker 9: service rep. But we're really excited about the opportunities not

441
00:22:35,520 --> 00:22:38,240
Speaker 9: just on the service side, but even using AI as

442
00:22:38,280 --> 00:22:40,560
Speaker 9: a think of like a digital partner that kind of

443
00:22:40,600 --> 00:22:43,960
Speaker 9: helping you manage your data day, financial life.

444
00:22:44,080 --> 00:22:46,880
Speaker 3: I have to leave it there, fascinating. Chris bret Chime, CEO.

445
00:22:46,960 --> 00:22:49,199
Speaker 3: We thank you for your time coming out next one

446
00:22:49,240 --> 00:22:52,480
Speaker 3: of those lms, Open AI. The CEO joins us, this

447
00:22:52,600 --> 00:22:59,960
Speaker 3: is Broomberg Tech. We want to welcome our global audience

448
00:23:00,000 --> 00:23:04,480
Speaker 3: across Bloomberg Radio and television Open AI. It's released GPT five.

449
00:23:04,560 --> 00:23:07,480
Speaker 3: It's most advanced model yet. The company says it offers

450
00:23:07,560 --> 00:23:11,600
Speaker 3: key improvements in major areas like reliability, accuracy, and there's

451
00:23:11,640 --> 00:23:14,200
Speaker 3: the strongest generator of AI model yet incoding and writing

452
00:23:14,240 --> 00:23:14,720
Speaker 3: and health.

453
00:23:15,320 --> 00:23:15,720
Speaker 2: For more.

454
00:23:15,840 --> 00:23:19,199
Speaker 3: We bring in Brad Light Open AI COO and this

455
00:23:19,280 --> 00:23:22,880
Speaker 3: feels so primed for enterprise adoption. Brad, when I think

456
00:23:22,920 --> 00:23:24,840
Speaker 3: of writing, when I think of coding, what is the

457
00:23:24,840 --> 00:23:25,680
Speaker 3: opportunity there?

458
00:23:27,080 --> 00:23:29,960
Speaker 5: Yeah, well, good morning, thanks for having me.

459
00:23:30,600 --> 00:23:33,560
Speaker 11: GVT five is a significant step forward in a few

460
00:23:33,600 --> 00:23:34,320
Speaker 11: different domains.

461
00:23:34,320 --> 00:23:35,520
Speaker 5: So you mentioned coding.

462
00:23:35,560 --> 00:23:39,960
Speaker 11: You mentioned writing in health for consumers and medical professionals,

463
00:23:40,520 --> 00:23:43,359
Speaker 11: and we think that opportunity unlocks an amazing set of

464
00:23:43,359 --> 00:23:45,200
Speaker 11: things in the enterprise that now become possible.

465
00:23:46,119 --> 00:23:47,480
Speaker 5: It's a much more reliable model.

466
00:23:47,520 --> 00:23:50,160
Speaker 11: So it's better at things like calling tools, it's better

467
00:23:50,200 --> 00:23:53,840
Speaker 11: at things like structured thinking and reasoning, problem solving. And

468
00:23:53,880 --> 00:23:55,880
Speaker 11: what we see in the enterprise is when you make

469
00:23:55,920 --> 00:23:59,600
Speaker 11: these core capabilities better, the number of use cases enterprises

470
00:23:59,600 --> 00:24:03,680
Speaker 11: can adopt these models for increases and so coding being significant.

471
00:24:04,080 --> 00:24:05,280
Speaker 5: It really is the language of.

472
00:24:05,920 --> 00:24:09,040
Speaker 11: Computers, and that was a significant area of demand for

473
00:24:09,160 --> 00:24:11,280
Speaker 11: us when we were talking to customers about what they

474
00:24:11,280 --> 00:24:12,080
Speaker 11: wanted in this model.

475
00:24:12,320 --> 00:24:15,040
Speaker 3: I mean, PhD level is what many are calling it,

476
00:24:15,080 --> 00:24:17,360
Speaker 3: well what Sam is calling it, and I'm sure yourself.

477
00:24:17,680 --> 00:24:20,679
Speaker 3: What's interesting is when you've got seven hundred million weekly

478
00:24:20,800 --> 00:24:23,480
Speaker 3: users of chatchipt, how much is that a funnel a

479
00:24:23,520 --> 00:24:25,480
Speaker 3: read across into enterprise. How much you could get the

480
00:24:25,520 --> 00:24:27,919
Speaker 3: inbound because ultimately the people in the old workforce are

481
00:24:27,920 --> 00:24:28,600
Speaker 3: already using it.

482
00:24:30,600 --> 00:24:33,040
Speaker 11: Well, really early on when we launched chat Gipt, what

483
00:24:33,119 --> 00:24:36,240
Speaker 11: we found is I think, you know, a number of

484
00:24:36,280 --> 00:24:38,920
Speaker 11: months after we launched it, I think something like ninety

485
00:24:38,960 --> 00:24:42,920
Speaker 11: two percent of the Fortune five hundred we're actively using chatchipt,

486
00:24:43,000 --> 00:24:44,560
Speaker 11: or people at ninety two percent of the Fortune five

487
00:24:44,600 --> 00:24:46,720
Speaker 11: hundred were actively using it, and so it was very

488
00:24:46,720 --> 00:24:48,400
Speaker 11: obvious for us we needed to go build a work

489
00:24:48,440 --> 00:24:51,960
Speaker 11: product because I think chatchapt as a product is as

490
00:24:52,080 --> 00:24:55,320
Speaker 11: useful in an enterprise environment, in a work environment as

491
00:24:55,359 --> 00:24:59,440
Speaker 11: it is in your personal life. It's an amazing companion

492
00:25:00,000 --> 00:25:03,560
Speaker 11: if you do anything from marketing to software engineering, to

493
00:25:03,640 --> 00:25:06,199
Speaker 11: data analysis and research. And I think there was a

494
00:25:06,200 --> 00:25:09,400
Speaker 11: lot of organic adoption when people discovered the tool, realizing

495
00:25:09,440 --> 00:25:12,040
Speaker 11: that it could make people much better at their jobs

496
00:25:12,560 --> 00:25:14,440
Speaker 11: and able to do more. And so we really leaned

497
00:25:14,480 --> 00:25:16,479
Speaker 11: in with that and we're trying to build the best

498
00:25:16,480 --> 00:25:17,080
Speaker 11: product we can.

499
00:25:17,880 --> 00:25:21,040
Speaker 3: It's like one tenth of the planet using chat gpt Brad.

500
00:25:21,040 --> 00:25:24,679
Speaker 3: But I'm interested in some analysis that Meno Ventures has done.

501
00:25:24,840 --> 00:25:27,480
Speaker 3: They've analyzed the LLLM market, particularly in the enterprise space,

502
00:25:27,600 --> 00:25:29,399
Speaker 3: and they've just tried to push back saying, look, you

503
00:25:29,560 --> 00:25:30,600
Speaker 3: lost market share.

504
00:25:30,640 --> 00:25:32,240
Speaker 2: Open Ai went from fifty percent in the.

505
00:25:32,280 --> 00:25:35,640
Speaker 3: Enterprise market share down to twenty five percent, and funnily enough,

506
00:25:35,720 --> 00:25:38,400
Speaker 3: the company that they back, which is Anthropic, took the lead.

507
00:25:38,760 --> 00:25:40,760
Speaker 3: What do you say to those of statistics, is it

508
00:25:40,760 --> 00:25:42,399
Speaker 3: something you're seeing within your own numbers.

509
00:25:44,480 --> 00:25:45,680
Speaker 5: It's hard to measure these things.

510
00:25:45,920 --> 00:25:48,200
Speaker 11: You know, you can find you can find measurements that

511
00:25:48,480 --> 00:25:51,159
Speaker 11: say the opposite. But what we really focus on is

512
00:25:51,240 --> 00:25:53,440
Speaker 11: value for customers, Like we've got to deliver the absolute

513
00:25:53,480 --> 00:25:56,520
Speaker 11: best models and then the absolute best products for developers,

514
00:25:56,840 --> 00:26:01,160
Speaker 11: for startups, for enterprises large and small, and that's that's

515
00:26:01,160 --> 00:26:03,280
Speaker 11: been our focus. I think you know, our API is

516
00:26:03,320 --> 00:26:05,920
Speaker 11: a good example of where we've really invested lately. We've

517
00:26:05,920 --> 00:26:08,840
Speaker 11: got over four million developers now actively using the API

518
00:26:09,400 --> 00:26:12,679
Speaker 11: every day to build new products. We support thousands and

519
00:26:12,720 --> 00:26:16,080
Speaker 11: thousands of startups that are building with us that we

520
00:26:16,119 --> 00:26:18,760
Speaker 11: work deeply with on trying to improve our product so

521
00:26:18,800 --> 00:26:21,320
Speaker 11: that they can ultimately build a better product. And in

522
00:26:21,359 --> 00:26:23,159
Speaker 11: the enterprise, I think you know, the demand that we

523
00:26:23,200 --> 00:26:26,240
Speaker 11: see there is really unabated. We grew chat Gypt enterprise

524
00:26:26,280 --> 00:26:29,600
Speaker 11: seats from three million seats to five million seats in

525
00:26:29,640 --> 00:26:32,080
Speaker 11: a matter of two months, and so that growth is

526
00:26:32,119 --> 00:26:35,320
Speaker 11: accelerating and we're just starting to scratch the surface, I

527
00:26:35,320 --> 00:26:37,359
Speaker 11: think on the impact that we can have both for

528
00:26:37,520 --> 00:26:39,960
Speaker 11: developers and for enterprises. So we see it as a

529
00:26:39,960 --> 00:26:41,960
Speaker 11: long game, and you know we're here to just do

530
00:26:41,960 --> 00:26:43,200
Speaker 11: our best for customers.

531
00:26:44,040 --> 00:26:46,600
Speaker 2: For that, BOYD, you need infrastructure.

532
00:26:47,200 --> 00:26:49,439
Speaker 3: Tell us a little bit about the costs of training

533
00:26:49,440 --> 00:26:52,240
Speaker 3: this model and how you're looking to expand with Stargate,

534
00:26:52,280 --> 00:26:54,600
Speaker 3: the project we've just been talking about how SoftBank's been

535
00:26:54,600 --> 00:26:57,239
Speaker 3: teaming up with Foxcon, for example, to take over an

536
00:26:57,280 --> 00:27:01,640
Speaker 3: ohio ev plant. How is that continuing to meet your

537
00:27:01,680 --> 00:27:03,960
Speaker 3: demands or not meet them as the case may be.

538
00:27:05,600 --> 00:27:10,000
Speaker 11: Well, yeah, we've seen demand for AI increase at just

539
00:27:10,720 --> 00:27:13,879
Speaker 11: a torrid pace. Obviously, at the root of that is

540
00:27:13,960 --> 00:27:17,760
Speaker 11: getting right the infrastructure equation, and we think ultimately that's

541
00:27:17,760 --> 00:27:20,560
Speaker 11: going to be a critical input to the US and

542
00:27:20,600 --> 00:27:23,920
Speaker 11: its allies being competitive in this area. And so Stargate

543
00:27:23,960 --> 00:27:26,720
Speaker 11: for US was a five hundred billion dollar project to

544
00:27:26,800 --> 00:27:30,640
Speaker 11: invest here in the United States to build AI infrastructure

545
00:27:31,359 --> 00:27:34,560
Speaker 11: for open AI and ultimately for the country. We're working

546
00:27:34,560 --> 00:27:36,520
Speaker 11: with a lot of great partners on that project and

547
00:27:36,800 --> 00:27:39,159
Speaker 11: hope to bring in more and I think, you know,

548
00:27:39,200 --> 00:27:41,399
Speaker 11: that's just the beginning. We're going to continue it to

549
00:27:41,440 --> 00:27:44,360
Speaker 11: invest aggressively. We've always found ourselves somewhat on the wrong

550
00:27:44,400 --> 00:27:47,959
Speaker 11: side of the demand curve for AI, you know, despite

551
00:27:48,000 --> 00:27:50,520
Speaker 11: the investment, the significant investment to date, and so for

552
00:27:50,520 --> 00:27:52,119
Speaker 11: as long as we see demand, we're going to continue

553
00:27:52,119 --> 00:27:55,240
Speaker 11: to invest aggressively. AI is interesting in that the more

554
00:27:55,520 --> 00:27:57,320
Speaker 11: you invest and the more you make it available, the

555
00:27:57,320 --> 00:28:01,000
Speaker 11: more you make it, you know, cost cost approachable for

556
00:28:01,480 --> 00:28:04,119
Speaker 11: enterprises and for consumers, the more people want to use it.

557
00:28:04,400 --> 00:28:07,000
Speaker 11: So it's an amazing trend and we'll continue to invest

558
00:28:07,040 --> 00:28:07,399
Speaker 11: behind it.

559
00:28:07,720 --> 00:28:10,360
Speaker 2: We're speaking with Brad Lightcap of open Ai.

560
00:28:10,520 --> 00:28:12,840
Speaker 3: The CEO for our radio and TV audience is Brad,

561
00:28:13,480 --> 00:28:16,200
Speaker 3: how has the rollout ultimately been. Do you think because

562
00:28:16,440 --> 00:28:18,800
Speaker 3: so many people wanted to use the app that maybe

563
00:28:18,840 --> 00:28:20,880
Speaker 3: we hit limits quicker than some anticipated.

564
00:28:22,440 --> 00:28:25,000
Speaker 5: Well, we're trying our best to keep up with demand.

565
00:28:25,760 --> 00:28:29,080
Speaker 11: Serving infrastructure at scale at seven hundred million users and

566
00:28:29,080 --> 00:28:32,560
Speaker 11: then millions of developers and many billions of tokens per

567
00:28:32,560 --> 00:28:36,479
Speaker 11: minute that we process is not for the faint of heart. Thankfully,

568
00:28:36,520 --> 00:28:37,800
Speaker 11: I don't have to do that part of it. But

569
00:28:38,520 --> 00:28:40,760
Speaker 11: we're doing our best to make sure the rollout is

570
00:28:41,160 --> 00:28:43,120
Speaker 11: successful and we're hoping that by the end of the

571
00:28:43,160 --> 00:28:44,760
Speaker 11: week here everyone gets access.

572
00:28:44,960 --> 00:28:47,680
Speaker 3: Your job description is more about building the enterprise relationships

573
00:28:47,680 --> 00:28:49,720
Speaker 3: and partnerships. I also think about the partnership you have

574
00:28:49,760 --> 00:28:52,400
Speaker 3: with Microsoft and Sati and adelays out there really talking

575
00:28:52,440 --> 00:28:55,240
Speaker 3: about integrating already and how excited he was for the product.

576
00:28:55,520 --> 00:28:57,680
Speaker 2: But there's a tension in the relationship there.

577
00:28:58,120 --> 00:29:01,200
Speaker 3: I'm interested in what you think the progress being made.

578
00:29:01,240 --> 00:29:03,760
Speaker 2: Sam Alman was on Networks.

579
00:29:03,240 --> 00:29:06,480
Speaker 3: Talking about progress being made with a relationship going forward. Microsoft,

580
00:29:06,600 --> 00:29:08,800
Speaker 3: can you give us a timeline about when you think

581
00:29:08,960 --> 00:29:11,360
Speaker 3: a deal will be done in the future of how

582
00:29:11,440 --> 00:29:14,280
Speaker 3: they interact with your product and more broadly, how much

583
00:29:14,280 --> 00:29:16,440
Speaker 3: ownership they continue to have in the business as a

584
00:29:16,440 --> 00:29:17,320
Speaker 3: full profit one.

585
00:29:18,880 --> 00:29:21,360
Speaker 11: Yeah, Well, we feel really positive about the relationship with

586
00:29:21,400 --> 00:29:23,480
Speaker 11: Microsoft and they've they've been a great partner throughout the

587
00:29:23,520 --> 00:29:26,080
Speaker 11: history of open Ai. They've been with us from the

588
00:29:26,080 --> 00:29:30,240
Speaker 11: beginning really since before chatch Ept obviously have been a

589
00:29:30,320 --> 00:29:32,960
Speaker 11: huge infrastructure partner for us with Azure.

590
00:29:33,280 --> 00:29:36,040
Speaker 5: And so we continue expect that to continue. We see

591
00:29:36,480 --> 00:29:37,840
Speaker 5: we see no future.

592
00:29:37,480 --> 00:29:40,160
Speaker 11: That you know of open Ai that doesn't include Microsoft

593
00:29:40,200 --> 00:29:43,000
Speaker 11: in a significant way. We've got to work on what

594
00:29:43,000 --> 00:29:45,080
Speaker 11: that future looks like together. We're in that process with

595
00:29:45,120 --> 00:29:47,640
Speaker 11: them right now. We feel very good about it, but

596
00:29:47,720 --> 00:29:50,160
Speaker 11: we think also ultimately there's you know, the world is

597
00:29:50,240 --> 00:29:53,120
Speaker 11: really big and the demand for these systems and these

598
00:29:53,160 --> 00:29:56,200
Speaker 11: models in the enterprise and consumer is significant. And so

599
00:29:56,600 --> 00:29:59,400
Speaker 11: they represent not only an infrastructure partner for us, but

600
00:29:59,720 --> 00:30:01,600
Speaker 11: a a partner to be able to help distribute and

601
00:30:01,640 --> 00:30:04,000
Speaker 11: bring the benefits of the technology to the world given

602
00:30:04,000 --> 00:30:06,000
Speaker 11: the size of their footprint, so you know, more to

603
00:30:06,040 --> 00:30:06,720
Speaker 11: work through there.

604
00:30:07,120 --> 00:30:08,240
Speaker 5: But we feel good about it.

605
00:30:08,280 --> 00:30:10,320
Speaker 11: And like I said, I think you know, when we're

606
00:30:10,320 --> 00:30:11,880
Speaker 11: standing at the finish line of all this, they'll be

607
00:30:11,880 --> 00:30:12,320
Speaker 11: there with us.

608
00:30:13,120 --> 00:30:16,280
Speaker 3: Meanwhile, the stuff of sulimanover at Microsoft is busy in

609
00:30:16,280 --> 00:30:19,400
Speaker 3: the tussle for talent, so to plenty of other rivals

610
00:30:19,400 --> 00:30:23,040
Speaker 3: that we understand, Mark Zuckerberg busy. And what's interesting is

611
00:30:23,560 --> 00:30:26,680
Speaker 3: while you is one of those long tenured employees and

612
00:30:27,200 --> 00:30:30,320
Speaker 3: staff over at open Ai remain committed because of innovations

613
00:30:30,320 --> 00:30:32,840
Speaker 3: such as this. But what about the liquidity that we're

614
00:30:32,880 --> 00:30:36,360
Speaker 3: talking about bringing to some of your well people that

615
00:30:36,400 --> 00:30:37,520
Speaker 3: you work alongside.

616
00:30:37,640 --> 00:30:38,240
Speaker 2: How is that going?

617
00:30:38,280 --> 00:30:40,040
Speaker 3: We understand they might be even a five hundred billion

618
00:30:40,080 --> 00:30:42,680
Speaker 3: dollar valuation involved in what is a secondary sale of

619
00:30:43,280 --> 00:30:45,479
Speaker 3: your shares to the likes of Thrive Capital.

620
00:30:47,400 --> 00:30:51,080
Speaker 11: Yeah, well, nothing there to share here, but we continue

621
00:30:51,080 --> 00:30:54,920
Speaker 11: to see very healthy demand on the investors side for

622
00:30:55,320 --> 00:30:56,840
Speaker 11: wanting to be I think part of the Open Eye

623
00:30:56,880 --> 00:30:59,240
Speaker 11: journey and mission, and we're very grateful for that. And

624
00:30:59,280 --> 00:31:01,080
Speaker 11: on the talent side, look, I think you know, Opening

625
00:31:01,120 --> 00:31:03,080
Speaker 11: Eye was founded as a nonprofit. It was founded as

626
00:31:03,120 --> 00:31:06,040
Speaker 11: a mission driven company to be able to build you know,

627
00:31:06,280 --> 00:31:09,800
Speaker 11: general intelligence that's beneficial for all of humanity, and we

628
00:31:09,880 --> 00:31:12,520
Speaker 11: haven't strayed from that mission. I think ultimately that's what

629
00:31:12,600 --> 00:31:15,160
Speaker 11: attracts talent is people want to work for a project

630
00:31:15,160 --> 00:31:17,560
Speaker 11: that's bigger than themselves and something that's going to be

631
00:31:17,560 --> 00:31:20,360
Speaker 11: impactful for us and for you know, for for for

632
00:31:20,480 --> 00:31:23,320
Speaker 11: humanity and our species. And so I think that's the

633
00:31:23,320 --> 00:31:26,520
Speaker 11: thing that ultimately attracts people to where they work. Obviously,

634
00:31:26,560 --> 00:31:29,040
Speaker 11: like it's a competitive market and we continue to compete.

635
00:31:29,240 --> 00:31:30,600
Speaker 11: But at the end of the day, when we ask

636
00:31:30,640 --> 00:31:32,280
Speaker 11: people what it is that keeps them at Opening It

637
00:31:32,360 --> 00:31:32,920
Speaker 11: it's the mission.

638
00:31:33,360 --> 00:31:33,880
Speaker 2: The mission.

639
00:31:34,240 --> 00:31:38,000
Speaker 3: At the moment, you've got something that's generally intelligence, but

640
00:31:38,000 --> 00:31:39,960
Speaker 3: it's not artificial general intelligence.

641
00:31:39,960 --> 00:31:41,200
Speaker 2: Brad, when do you get there?

642
00:31:41,280 --> 00:31:46,040
Speaker 11: Briefly, you know, I've sworn off making predictions in AI.

643
00:31:46,160 --> 00:31:49,240
Speaker 11: It's too hard, the curves are too steep. But I think,

644
00:31:49,280 --> 00:31:51,240
Speaker 11: you know, we feel really good about the rate of progress.

645
00:31:51,320 --> 00:31:54,160
Speaker 11: GBD five is a great representation of how we start

646
00:31:54,160 --> 00:31:57,040
Speaker 11: to make progress on little things, you know, things like,

647
00:31:57,080 --> 00:31:59,600
Speaker 11: for example, being able to have the model dynamically reason

648
00:32:00,040 --> 00:32:03,080
Speaker 11: and decide how much it wants to think about the

649
00:32:03,120 --> 00:32:05,760
Speaker 11: problem that you ask it to solve. That's something that

650
00:32:05,800 --> 00:32:09,120
Speaker 11: we do natively as humans that previously our models couldn't do.

651
00:32:09,240 --> 00:32:11,800
Speaker 11: So it's these little steps forward that we think accumulated

652
00:32:11,800 --> 00:32:14,720
Speaker 11: and ultimately get us to something that will be truly remarkable.

653
00:32:15,320 --> 00:32:18,640
Speaker 3: Radi cap talking about the latest GPT five. We thank

654
00:32:18,680 --> 00:32:24,160
Speaker 3: you so much, Coeo of open Ai. Now let's check

655
00:32:24,200 --> 00:32:27,200
Speaker 3: back on these markets, because we are up three point

656
00:32:27,240 --> 00:32:29,040
Speaker 3: three percent over the course of five days, and then

657
00:32:29,080 --> 00:32:30,920
Speaker 3: that's that one hundred where are a new record high.

658
00:32:30,920 --> 00:32:32,440
Speaker 2: Folks. We have had one of.

659
00:32:32,440 --> 00:32:34,600
Speaker 3: The longest weeks and tech in terms of newsflow, whether

660
00:32:34,640 --> 00:32:36,440
Speaker 3: it's been about tariffs on chips, whether it's.

661
00:32:36,360 --> 00:32:38,200
Speaker 2: Been the onslaught of earnings, which.

662
00:32:38,080 --> 00:32:39,880
Speaker 3: We're going to be talking about time and time again.

663
00:32:40,200 --> 00:32:42,400
Speaker 3: Currently up three point three percent. Want to look about

664
00:32:42,400 --> 00:32:44,719
Speaker 3: what's happening in the rest of the industry and indeed

665
00:32:44,880 --> 00:32:47,920
Speaker 3: the market more broadly. Bitcoins down by percentage point, got

666
00:32:47,960 --> 00:32:49,120
Speaker 3: a bit of a risk off tone.

667
00:32:49,280 --> 00:32:50,800
Speaker 2: You have to keep an eye what's happening with.

668
00:32:50,760 --> 00:32:53,240
Speaker 3: Gold spot though, because talking of tariffs. While it's not

669
00:32:53,280 --> 00:32:56,000
Speaker 3: just semiconductors that's been in the eye the storm or pharmaceuticals,

670
00:32:56,000 --> 00:32:59,120
Speaker 3: but gold bars as well, huge volatility on the course

671
00:32:59,120 --> 00:33:01,080
Speaker 3: of the day. Meanwhile, coming up, we're going to be

672
00:33:01,120 --> 00:33:03,760
Speaker 3: speaking with akam I CEO to Tom Layton, I'm going

673
00:33:03,800 --> 00:33:06,360
Speaker 3: to go back to other earnings within this trade desk

674
00:33:06,480 --> 00:33:09,959
Speaker 3: is off by thirty nine percent. It's earnings underwhelmed significantly.

675
00:33:10,160 --> 00:33:13,320
Speaker 3: Amazon competition Pinterest off after its earnings, but Insta can't

676
00:33:13,320 --> 00:33:17,640
Speaker 3: trading higher Exipedia after Airbnb managed to underwhelm Expedia up

677
00:33:17,640 --> 00:33:20,320
Speaker 3: more than four percent. We can bring you Akami next though.

678
00:33:20,440 --> 00:33:23,560
Speaker 3: Tom Layton joins us the CEO, this is Blue Megtech.

679
00:33:37,800 --> 00:33:40,960
Speaker 3: Keep an eye on Akamai shares today, somewhat volatile after

680
00:33:41,000 --> 00:33:42,800
Speaker 3: posting second quarter results.

681
00:33:42,800 --> 00:33:45,400
Speaker 2: That across the board in general beat estimates.

682
00:33:45,440 --> 00:33:47,320
Speaker 3: But you have to read between the lines as to

683
00:33:47,320 --> 00:33:49,160
Speaker 3: where there was perhaps a bit of a pullback or

684
00:33:49,600 --> 00:33:51,840
Speaker 3: a miss when it came to Compute, for example, but

685
00:33:51,920 --> 00:33:55,120
Speaker 3: therefore you forecast that was raised. Tom Layton, Akami CEO

686
00:33:55,240 --> 00:33:58,320
Speaker 3: joins us now to demystify for us, Tom, because it's

687
00:33:58,320 --> 00:34:01,800
Speaker 3: interesting you have Hybisan really talking about lots of moving

688
00:34:01,880 --> 00:34:06,120
Speaker 3: parts and ultimately they see fairly cloudy still of what

689
00:34:06,200 --> 00:34:08,200
Speaker 3: the ultimate positioning is of the business.

690
00:34:08,560 --> 00:34:09,200
Speaker 2: Can you tell it.

691
00:34:09,160 --> 00:34:13,040
Speaker 3: You're really going in on well, cloud infrastructure here, not

692
00:34:13,200 --> 00:34:15,719
Speaker 3: just content delivery, not just security.

693
00:34:16,200 --> 00:34:22,279
Speaker 12: Oh yeah, security majority of our revenue Cloud infrastructure services.

694
00:34:22,400 --> 00:34:23,000
Speaker 5: My goodness.

695
00:34:23,000 --> 00:34:26,160
Speaker 12: We are up thirty percent year every year, and we

696
00:34:26,239 --> 00:34:28,640
Speaker 12: think that's going to accelerate. So by the end of

697
00:34:28,640 --> 00:34:31,560
Speaker 12: this year will be up forty percent plus year over year.

698
00:34:31,920 --> 00:34:37,360
Speaker 12: Tremendous market opportunity. There, strong tailwinds of course from jen Ai.

699
00:34:38,040 --> 00:34:41,360
Speaker 12: So I think very exciting results for Akamai. You know,

700
00:34:41,440 --> 00:34:45,080
Speaker 12: a strong beat on the quarter, very profitable earnings per

701
00:34:45,120 --> 00:34:48,400
Speaker 12: share up nine percent and a dollar and seventy three cents,

702
00:34:48,880 --> 00:34:51,800
Speaker 12: and I think a very good outlook, raising guidance for

703
00:34:51,840 --> 00:34:52,160
Speaker 12: the year.

704
00:34:52,880 --> 00:34:55,719
Speaker 3: So maybe just a little bit of a pause for investors.

705
00:34:55,760 --> 00:34:58,520
Speaker 3: I mean, the shows are still down over the year

706
00:34:58,640 --> 00:34:59,360
Speaker 3: or twelve months.

707
00:34:59,400 --> 00:35:02,760
Speaker 2: Tom. I'm sort of interested therefore on what they're not getting.

708
00:35:02,920 --> 00:35:06,440
Speaker 3: What is it about the opportunity in, for example, cloud infrastructure.

709
00:35:06,440 --> 00:35:09,360
Speaker 3: Why take on the hyperscalers, Well, it's.

710
00:35:09,200 --> 00:35:12,759
Speaker 12: A tremendous market opportunity. Our customers have asked us to

711
00:35:12,800 --> 00:35:16,239
Speaker 12: do that. You know, we with our distributed platform, which

712
00:35:16,280 --> 00:35:19,040
Speaker 12: is unique in the marketplace. We're in seven hundred and

713
00:35:19,080 --> 00:35:22,600
Speaker 12: fifty cities. With our points a presence, we can get

714
00:35:22,760 --> 00:35:28,200
Speaker 12: enterprise compute instances. They're containers closer to the end users,

715
00:35:28,640 --> 00:35:32,160
Speaker 12: and that gives you lower latency and better performance and

716
00:35:32,239 --> 00:35:35,879
Speaker 12: for a lot of applications that matters. Also, we could

717
00:35:35,920 --> 00:35:38,200
Speaker 12: do it at a lower price point. In fact, one

718
00:35:38,239 --> 00:35:40,799
Speaker 12: of the hyperscalers is an early adopter of our new

719
00:35:40,880 --> 00:35:44,640
Speaker 12: managed container service. They want to have their compute instances

720
00:35:44,680 --> 00:35:47,439
Speaker 12: and hundreds of cities around the world, which is something

721
00:35:47,480 --> 00:35:48,480
Speaker 12: all the Akamai can do.

722
00:35:49,040 --> 00:35:49,480
Speaker 2: Interesting.

723
00:35:49,719 --> 00:35:52,040
Speaker 3: I mean, maybe people are looking at what drove some

724
00:35:52,120 --> 00:35:54,040
Speaker 3: of the revenue beat and they're looking at FX, but.

725
00:35:54,040 --> 00:35:57,480
Speaker 2: They're also looking at TikTok inclusion. Have you decided that.

726
00:35:57,440 --> 00:35:59,440
Speaker 3: The risk of being managed just off the table and

727
00:35:59,480 --> 00:36:02,000
Speaker 3: you're going to really be startling talking about this client

728
00:36:02,000 --> 00:36:02,439
Speaker 3: once again?

729
00:36:03,560 --> 00:36:05,720
Speaker 8: Oh, there's always risk.

730
00:36:06,239 --> 00:36:09,080
Speaker 12: Though, it seems that from what we're hearing from public

731
00:36:09,160 --> 00:36:12,360
Speaker 12: sources that you know, a deal has basically been structured

732
00:36:12,600 --> 00:36:16,080
Speaker 12: and you know there's obviously caught up in trade negotiations,

733
00:36:16,960 --> 00:36:20,960
Speaker 12: but that at this point it seems like the ban

734
00:36:21,080 --> 00:36:24,960
Speaker 12: has been postponed several times, and so we're not seeing

735
00:36:24,960 --> 00:36:27,960
Speaker 12: anything that suggests that that that's going to change in

736
00:36:28,000 --> 00:36:28,760
Speaker 12: the near future.

737
00:36:29,239 --> 00:36:31,120
Speaker 2: You do that content delivery for them.

738
00:36:31,160 --> 00:36:34,200
Speaker 3: It's interesting that security is where a lot of your growth,

739
00:36:34,280 --> 00:36:36,160
Speaker 3: and as you say, the most part of your revenue

740
00:36:36,160 --> 00:36:40,400
Speaker 3: has been coming from. What insecurity is driving that growth?

741
00:36:40,440 --> 00:36:41,640
Speaker 3: Where are people coming to you?

742
00:36:42,920 --> 00:36:46,480
Speaker 12: Yeah, we have the market leading solutions for web app firewall,

743
00:36:47,160 --> 00:36:53,920
Speaker 12: for bought management, for API security, for stopping ransomware with segmentation,

744
00:36:54,560 --> 00:36:57,040
Speaker 12: and of course the attack rates have been going way up,

745
00:36:57,120 --> 00:36:59,840
Speaker 12: the penetrations have been going way up, and we have

746
00:37:00,080 --> 00:37:00,640
Speaker 12: a solution.

747
00:37:01,160 --> 00:37:04,240
Speaker 8: It stops the damage caused by those attacks.

748
00:37:04,320 --> 00:37:07,400
Speaker 12: So if the ransomware gets in, we identify it quickly,

749
00:37:07,440 --> 00:37:10,640
Speaker 12: we don't let it spread, and that protects our customers

750
00:37:10,680 --> 00:37:14,080
Speaker 12: so they don't, you know, have these huge costs associated

751
00:37:14,120 --> 00:37:15,880
Speaker 12: with being shut down by ransomware.

752
00:37:16,320 --> 00:37:18,480
Speaker 3: Of course, general to AI in many ways, making the

753
00:37:18,600 --> 00:37:23,480
Speaker 3: field of security ever more evolving and nimble is what's crucial. Tom.

754
00:37:23,840 --> 00:37:25,920
Speaker 3: What I'm also so interested in is the way in

755
00:37:25,960 --> 00:37:28,600
Speaker 3: which you're thinking about education here in the United States.

756
00:37:28,680 --> 00:37:31,400
Speaker 3: Skills in particular and upskilling. This is something that the

757
00:37:31,560 --> 00:37:33,560
Speaker 3: US government is calling for a lot, and I'm particularly

758
00:37:33,600 --> 00:37:35,600
Speaker 3: in the era of general to AI. How are you

759
00:37:36,200 --> 00:37:39,319
Speaker 3: seeing the skill set and the pool of talent? Is

760
00:37:39,320 --> 00:37:40,080
Speaker 3: it good enough for you?

761
00:37:41,400 --> 00:37:43,320
Speaker 8: It's going to change with Jenai.

762
00:37:43,800 --> 00:37:50,560
Speaker 12: We're seeing tremendous efficiencies across most job types at Okhami,

763
00:37:50,960 --> 00:37:53,719
Speaker 12: so that our employees can do more in the same

764
00:37:53,760 --> 00:37:57,480
Speaker 12: amount of time by leveraging Jenai. And I think you'll

765
00:37:57,520 --> 00:38:03,120
Speaker 12: see training. We're doing training ourselves so that employees will

766
00:38:03,200 --> 00:38:06,520
Speaker 12: change maybe how they do certain things and they'll be

767
00:38:06,560 --> 00:38:09,520
Speaker 12: more efficient by learning how to use the Genai tools.

768
00:38:09,560 --> 00:38:11,520
Speaker 12: I think it's really very exciting and it probably is

769
00:38:11,560 --> 00:38:14,160
Speaker 12: going to be a sea change over time and education.

770
00:38:14,960 --> 00:38:18,200
Speaker 3: Tominayton Avakami was great to have you on after your numbers.

771
00:38:18,200 --> 00:38:19,600
Speaker 3: Thank you very much for joining the show.

772
00:38:19,920 --> 00:38:20,359
Speaker 2: Stay well.

773
00:38:20,520 --> 00:38:23,880
Speaker 3: Meanwhile, coming up Tesla, well, it is disbanding the team

774
00:38:24,200 --> 00:38:26,400
Speaker 3: that was meant to give it the computing muscle in

775
00:38:26,480 --> 00:38:29,640
Speaker 3: the AI race. As an Ed Ludlow scoop, we'll get

776
00:38:29,680 --> 00:38:30,560
Speaker 3: behind it with you next.

777
00:38:30,600 --> 00:38:31,480
Speaker 2: This is bluembg Tech.

778
00:38:43,320 --> 00:38:46,560
Speaker 3: For decades, Samsung was the world's leading memory chip makup

779
00:38:46,640 --> 00:38:49,480
Speaker 3: but the tech chant was recently surpassed by smaller rival

780
00:38:49,560 --> 00:38:52,520
Speaker 3: sk Heinez, So how quickly can it reassert itself in

781
00:38:52,560 --> 00:38:54,920
Speaker 3: the AI race of Blue Beg Original's team to a

782
00:38:55,040 --> 00:38:55,799
Speaker 3: deep dive into this.

783
00:38:57,200 --> 00:38:59,959
Speaker 13: When you're out shopping for seven megawatts offshore winds turbin,

784
00:39:00,440 --> 00:39:03,960
Speaker 13: you think Samsung, right, Well, probably not. The brand is

785
00:39:04,040 --> 00:39:06,400
Speaker 13: much more famous for its phones and flat screens, but

786
00:39:06,560 --> 00:39:10,000
Speaker 13: arguably the most important drivers of South Korea's biggest family

787
00:39:10,000 --> 00:39:13,799
Speaker 13: business are these things. And for the first time in decades,

788
00:39:14,120 --> 00:39:16,560
Speaker 13: the company's got a massive problem here.

789
00:39:16,840 --> 00:39:20,239
Speaker 9: Samsung is under assault from all sides and they are

790
00:39:20,280 --> 00:39:21,120
Speaker 9: getting stretched.

791
00:39:21,239 --> 00:39:24,440
Speaker 6: Then Samsung is in this position of playing catchup, and

792
00:39:24,440 --> 00:39:27,440
Speaker 6: that's difficult to do if you don't have growing revenue,

793
00:39:27,440 --> 00:39:30,359
Speaker 6: if you don't have expanding profitability.

794
00:39:29,800 --> 00:39:35,359
Speaker 14: And unfortunately the ship profits tumble, big disappointment. The semiconducted

795
00:39:35,400 --> 00:39:38,560
Speaker 14: division reporting operating profit at four hundred billion one totally

796
00:39:38,600 --> 00:39:41,640
Speaker 14: missed analyst projections for two point seventy three trillion.

797
00:39:42,600 --> 00:39:45,680
Speaker 13: Samson shares of whipsword in value since their twenty twenty

798
00:39:45,719 --> 00:39:49,640
Speaker 13: peak and tanked in twenty twenty four, while long standing

799
00:39:49,719 --> 00:39:55,880
Speaker 13: rival sk Heinez searched the crisis is easy to miss

800
00:39:55,960 --> 00:39:56,719
Speaker 13: amid all this.

801
00:39:57,440 --> 00:40:01,040
Speaker 5: The Ultra experience is ready two.

802
00:40:01,200 --> 00:40:05,880
Speaker 13: A four, But behind the cats and choreography, Samsung's hidden

803
00:40:05,880 --> 00:40:10,440
Speaker 13: struggle threatens its national identity amongst a population that relies

804
00:40:10,480 --> 00:40:11,640
Speaker 13: on it like no other.

805
00:40:13,080 --> 00:40:15,879
Speaker 2: It is probably the most influential company in.

806
00:40:15,840 --> 00:40:20,279
Speaker 13: Korea because of the impuortance to the economy, and maintaining

807
00:40:20,320 --> 00:40:23,640
Speaker 13: that influence may hinge on a piece of technology you

808
00:40:23,800 --> 00:40:26,719
Speaker 13: probably own but have never even seen.

809
00:40:30,120 --> 00:40:32,960
Speaker 3: Catch the full episode at Bloomberg dot com, on YouTube

810
00:40:33,320 --> 00:40:36,120
Speaker 3: or on the terminal. Now, one company depending more on

811
00:40:36,160 --> 00:40:39,359
Speaker 3: Samsung for its future AI chips is Tesla, and we've

812
00:40:39,400 --> 00:40:42,160
Speaker 3: got some updated reporting from our own ed Ludlow. Tesla

813
00:40:42,239 --> 00:40:45,760
Speaker 3: is disbanding its Dojo supercomputer unit and its leader, Peter Bannon,

814
00:40:45,800 --> 00:40:48,120
Speaker 3: is leaving the company as it depends more on third

815
00:40:48,160 --> 00:40:51,160
Speaker 3: party hardware suppliers. It's all according to sources. Now, the team,

816
00:40:51,239 --> 00:40:54,280
Speaker 3: as we told you yesterday, had lost workers to Density AI.

817
00:40:54,480 --> 00:40:57,600
Speaker 3: It's a competing startup founded by former Dojo executives.

818
00:40:57,880 --> 00:40:58,480
Speaker 2: Let's get more of.

819
00:40:58,480 --> 00:41:02,440
Speaker 3: Bloomberg's Max Chaffkin, busy on his travels and Max, we

820
00:41:02,480 --> 00:41:06,040
Speaker 3: turned to you as elon inc Helmer, what do you

821
00:41:06,120 --> 00:41:08,520
Speaker 3: make of this move away? From making its own hardware

822
00:41:08,680 --> 00:41:10,920
Speaker 3: in the AI chip space.

823
00:41:12,040 --> 00:41:16,560
Speaker 15: I mean, it's definitely a setback because Tesla, of course,

824
00:41:16,960 --> 00:41:20,400
Speaker 15: if somewhat famously, likes to make everything that's kind.

825
00:41:20,280 --> 00:41:21,560
Speaker 8: Of Elon Musk's whole thing.

826
00:41:21,840 --> 00:41:25,719
Speaker 15: He's tried to make a vertically integrated auto manufacturer. That

827
00:41:25,760 --> 00:41:30,279
Speaker 15: makes Tesla very unusual, and also has been trying, you know,

828
00:41:30,400 --> 00:41:35,000
Speaker 15: obviously desperately to pivot towards AI. So this is a setback.

829
00:41:35,040 --> 00:41:37,800
Speaker 15: I will say it's a setback that I think people

830
00:41:37,840 --> 00:41:40,960
Speaker 15: saw coming to some extent. In twenty twenty four, during

831
00:41:41,000 --> 00:41:44,719
Speaker 15: an Ernie's call, Musk sort of started to tamp down

832
00:41:44,760 --> 00:41:48,040
Speaker 15: expectations said they were going to rely on two paths

833
00:41:48,080 --> 00:41:50,640
Speaker 15: for training its AI models.

834
00:41:50,880 --> 00:41:52,839
Speaker 8: One would be this dojo thing.

835
00:41:52,880 --> 00:41:57,319
Speaker 15: The other would would rely on Nvidia chips, the same

836
00:41:57,480 --> 00:42:00,680
Speaker 15: very expensive chips that everyone is essentially using to train

837
00:42:00,760 --> 00:42:04,760
Speaker 15: their models. So it is it's a setback, but maybe

838
00:42:04,800 --> 00:42:07,759
Speaker 15: but I don't think it's devastating. I think what is

839
00:42:08,040 --> 00:42:11,360
Speaker 15: maybe more troubling is just losing talent. Right we're in

840
00:42:11,360 --> 00:42:16,640
Speaker 15: the middle of this AI talent war. Tesla historically has

841
00:42:16,680 --> 00:42:18,960
Speaker 15: been very competitive. Of course, the stock you know, for

842
00:42:19,040 --> 00:42:22,839
Speaker 15: for a while was just exploding and it has been

843
00:42:22,840 --> 00:42:25,480
Speaker 15: fairly stagnant over the last couple of years.

844
00:42:25,640 --> 00:42:27,600
Speaker 8: And I think you're, you know, you're seeing that, right.

845
00:42:27,600 --> 00:42:30,879
Speaker 15: There are startups out there and these kind of very

846
00:42:31,000 --> 00:42:34,279
Speaker 15: large privately held companies like open Ai and Thenthropic that

847
00:42:34,400 --> 00:42:39,719
Speaker 15: are just throwing huge sums of money at developers, and you're,

848
00:42:39,760 --> 00:42:42,439
Speaker 15: you know, you're seeing Tesla clearly like struggle a little

849
00:42:42,480 --> 00:42:44,160
Speaker 15: bit to keep up and retain.

850
00:42:44,160 --> 00:42:47,200
Speaker 3: And does CI now forming as a new startup to

851
00:42:47,400 --> 00:42:50,280
Speaker 3: take on the world of hardware and AI max Briefly,

852
00:42:50,360 --> 00:42:52,600
Speaker 3: I mean Elon responded saying that it doesn't make sense

853
00:42:52,640 --> 00:42:55,520
Speaker 3: have two different avenues for chips, and AC.

854
00:42:55,560 --> 00:42:57,560
Speaker 2: Fifteen and A sixteen they're going to continue with.

855
00:42:58,040 --> 00:43:00,960
Speaker 3: But more broadly, this was thinking of the way it

856
00:43:01,040 --> 00:43:04,800
Speaker 3: set upself apart for the future of supercomputing being vertically integrated.

857
00:43:04,960 --> 00:43:07,000
Speaker 2: Maugazani thought would be five hundred million dollars added to

858
00:43:07,080 --> 00:43:07,680
Speaker 2: the market cap.

859
00:43:08,640 --> 00:43:12,440
Speaker 15: Yeah, and all those estimates, of course look look silly,

860
00:43:12,800 --> 00:43:15,839
Speaker 15: and I think you have to ask yourself there are

861
00:43:15,840 --> 00:43:20,760
Speaker 15: lots of estimates like that around Tesla and it's AI ambitions,

862
00:43:21,320 --> 00:43:23,759
Speaker 15: few of which are really realized yet, and it does

863
00:43:23,840 --> 00:43:25,960
Speaker 15: make you wonder like, should we revisit some of those

864
00:43:26,000 --> 00:43:30,320
Speaker 15: other assumptions, you know, people talking about valuations in the trillions.

865
00:43:31,239 --> 00:43:34,120
Speaker 8: You know. Look, Elon Musk said this was a moonshot.

866
00:43:34,200 --> 00:43:36,719
Speaker 15: I think it was kind of a moonshot because the

867
00:43:36,800 --> 00:43:41,200
Speaker 15: truth is Nvidia dominates this market, the market for training chips,

868
00:43:41,520 --> 00:43:44,239
Speaker 15: and Elon Musk took a crack but wasn't able to

869
00:43:44,239 --> 00:43:44,600
Speaker 15: get there.

870
00:43:45,000 --> 00:43:48,240
Speaker 3: Bloomberg's Max Chafkin. Tune in to Elon ink It's weekly.

871
00:43:48,280 --> 00:43:50,400
Speaker 3: We thank you so much. Now that does it for

872
00:43:50,480 --> 00:43:51,560
Speaker 3: this edition of Bloomberg Tech.

873
00:43:51,600 --> 00:43:53,000
Speaker 2: Quick check in on the markets for you.

874
00:43:53,280 --> 00:43:56,040
Speaker 3: We're off by eight ten percent on bitcoin, digital gold,

875
00:43:56,080 --> 00:43:59,319
Speaker 3: but real gold flat. But boy, we can potentially see

876
00:43:59,320 --> 00:44:01,880
Speaker 3: some tariffs on all bars affecting Switzerland in particular.

877
00:44:02,000 --> 00:44:02,719
Speaker 2: Keep an eye on that story.

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Speaker 3: Nasat one hundred are by eight ten percent, a new

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Speaker 3: record high.

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Speaker 2: Folks, check out our podcast. You can find one in

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Speaker 2: the terminal. This is Bluemberg Tech