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

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Speaker 1: lie from coast to coast, with Caroline Hyde in New

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Speaker 1: York and Vla Loow in San Francisco.

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Speaker 2: This is Bloomberg Tech coming up.

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Speaker 3: Cisco ches jump the most since twenty eleven of the

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Speaker 3: company's earnings results will break them down. Plus, China's Jijingping

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Speaker 3: gives a warning to President Trump on Taiwan that tells

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Speaker 3: US tech CEOs China will open up more, and ai

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Speaker 3: chipmaker Cerebras raises five point five five billion dollars in

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Speaker 3: its USIPO, seizing on the surging demand for semiconductors. Will

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Speaker 3: be joined by the CEO later this hour. Cisco is

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Speaker 3: our top story, and it is actually rising with the

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Speaker 3: rest of the market. We're up fifteen percent, on track

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Speaker 3: for our biggest jump since twenty eleven, after the open

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Speaker 3: hit seventeen percent, putting Cisco on track for its best

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Speaker 3: day since two thousand and two.

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Speaker 2: It's a pretty simple story.

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Speaker 3: Hyperscala demand calendar year twenty six nine billion dollars, up

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Speaker 3: from a previous forecast of five billion dollars. Four billion

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Speaker 3: of that will translate into actual revenues sales on the

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Speaker 3: income statement in this year.

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Speaker 2: There are many more.

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Speaker 3: Threads, but Cisco is finding its place in this AI

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Speaker 3: infrastructure story. It's got out to Bloomberg Equities reporder Ryan V.

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Speaker 2: Selica.

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Speaker 3: I think Ryan, the best place to start is what

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Speaker 3: has the cell side reaction been to this? What are

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Speaker 3: the analysts saying? The main thread of their enthusiasm for

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Speaker 3: Cisco has been this morning.

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Speaker 4: Analysts are very positive and very optimistic that Cisco will

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Speaker 4: be able to continue kind of putting up these numbers

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Speaker 4: that we saw in this past quarter. There is a

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Speaker 4: lot of optimism that Cisco is now really part of

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Speaker 4: the AI infrastructure of firmament. It showed very strong demand,

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Speaker 4: as you said, from the hype scalers, it's pointing to

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Speaker 4: very strong growth going forward. I think there's been a

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Speaker 4: growing realization this year that the sort of optical and

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Speaker 4: networking companies are a huge part of the whole data

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Speaker 4: center build out. And obviously we have seen no end

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Speaker 4: of demand and growth for data centers related to AI.

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Speaker 4: And Cisco is really well positioned in that it's a

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Speaker 4: legacy company, it has a wide product suite that.

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Speaker 2: People are using here.

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Speaker 4: It seems very well positioned, and it does seem like

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Speaker 4: analysts are really sort of seeing additional confirmation of this trend.

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Speaker 3: Right, And there's so much to pack into Bloomberg Tech today.

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Speaker 3: People are saying, why you're starting on Cisco. The market's

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Speaker 3: team is looking at the equities market widely, and Cisco

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Speaker 3: is a big factor in kind of the feel good

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Speaker 3: that's out there networking is your cables, your switches, your routers,

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Speaker 3: that all goes into real data centers, right. But the

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Speaker 3: other part of the story is Cisco's discipline. They're cutting

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Speaker 3: about four thousand rolls. The company kind of spin that

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Speaker 3: as a positive in that that sort of feel good

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Speaker 3: around AI in the market today.

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Speaker 4: Well, they talked about how they are really focusing and

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Speaker 4: prioritizing AI.

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Speaker 2: You mentioned the job cuts.

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Speaker 4: It does seem like all of their investments are really

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Speaker 4: geared toward this in market in particular, So there is.

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Speaker 2: A lot of optimism about that.

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Speaker 4: And I would just say, as I'm sure you remember,

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Speaker 4: Cisco is one of the major companies of the dot

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Speaker 4: com era build out. Now, it saw huge growth at

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Speaker 4: that time and it only recently surpassed its dot com

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Speaker 4: era high. So there's a certain amount of poetic justice,

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Speaker 4: I guess, and the fact that AI is a thing

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Speaker 4: that is finally bringing it back to record levels. It

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Speaker 4: does seem like it is now becoming a real part

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Speaker 4: of this technology buildout, just as it was in the

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Speaker 4: Internet tech buildout.

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Speaker 3: Ryan, you and I were not doing this in the

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Speaker 3: dot com era, but you know here and now, Cisco

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Speaker 3: is a big story. Bloombers rhyme lslica on the equities desk,

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Speaker 3: Thank you so much. Another start we're watching is Klana

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Speaker 3: looking at shares, also up fifteen sixteen percent. The company

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Speaker 3: posted just one million dollars in first coordinet income, but

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Speaker 3: it beat estimates, swinging from a ninety nine million dollar

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Speaker 3: loss a year ago. This in the fintech space right,

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Speaker 3: revenue jumping forty four percent to one billion dollars, driven

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Speaker 3: by higher interest income, growth in debit card sign ups

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Speaker 3: partnership fees. It's another one that we had to fit

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Speaker 3: in in a very busy Thursday morning. Today, all eyes

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Speaker 3: are on Cerebras, the company set to begin trading after

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Speaker 3: pricing its IPO at one hundred and eighty five dollars

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Speaker 3: a share, raising five point five five billion dollars. The

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Speaker 3: biggest USIPO of the year so far, it has been

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Speaker 3: mayhem in the market. So far, shares were indicated at

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Speaker 3: one point to open at four hundred dollars a share,

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Speaker 3: four hundred having priced at one eighty five. I think

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Speaker 3: we're now back down at three hundred and fifty dollars

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Speaker 3: a share as of one minute past eight Pacific time

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Speaker 3: one minute past eleven am Eastern time. Bloomberg's Bailey lip

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Speaker 3: Schultz has been my partner in tracking the chaos of

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Speaker 3: this IPO for a good few days.

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Speaker 2: Now start with the math.

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Speaker 3: Yeah, the indicated opening price well beyond one hundred.

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Speaker 2: And eighty five dollars a share. What's that telling us?

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Speaker 5: It tells us that there's untapped demand. And when you

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Speaker 5: look at a deal like this, more than twenty times

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Speaker 5: over subscribe. We reported before it even launched there was

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Speaker 5: ten billion dollars of demand. So these are huge numbers.

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Speaker 5: This is the hottest stock, at least from an IPO

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Speaker 5: perspective this year bar none. The big question and you

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Speaker 5: asked me, you know, look at the market cap of

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Speaker 5: where this could open. If we're getting closer to eighty

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Speaker 5: billion dollars, talking to folks on the buy side, they're

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Speaker 5: still saying, you know, if in Videa's worth five trillion dollars,

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Speaker 5: who's to say that this company doesn't easily treat closer

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Speaker 5: to one hundred billion. I don't know what you've been

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Speaker 5: hearing about that from your.

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Speaker 2: Side, yees so exactly.

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Speaker 3: That brings us back to like what is Cerebras.

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Speaker 2: What does it do well?

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Speaker 3: It is a full stack, vertally integrated supercomputer maker right

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Speaker 3: and video makes largely the chips, but the server trays.

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Speaker 3: These days, it doesn't build its own servers. Dell does that,

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Speaker 3: super Micro does that. Cerebras does the full send package.

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Speaker 3: But even at one hundred billion dollars, it's a drop

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Speaker 3: in the ocean. Why the market's so enthusiastic about its technology? Like,

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Speaker 3: what else do we know about this company's financials or

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Speaker 3: its customer backlog?

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Speaker 5: The big thing initially when they tried to go public

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Speaker 5: call it two years ago was concentration risks, so G

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Speaker 5: forty two was pretty much their only customer. They've expanded

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Speaker 5: that now you have open AI and others in the

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Speaker 5: big pitch ed, at least when I talked to folks

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Speaker 5: on the buyside, is how broad based can that be?

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Speaker 5: If we're dealing with a market, especially as it relates

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Speaker 5: to building some of the compute and everything that goes

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Speaker 5: into building out the AI future. If this is just

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Speaker 5: the start and we're an early innings, what does this

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Speaker 5: ultimately look like? Call it five years from now, and

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Speaker 5: the big question is back to your point earlier. If

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Speaker 5: this is just a drop in the bucket, there's a

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Speaker 5: pretty much massive potential as it relates to going forward.

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Speaker 5: Though again, all things considered, we've seen semi sconductor index

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Speaker 5: up what thirty percent since they started this process.

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Speaker 3: I would say indicated opening prices. They're on the Bloomberg terminal.

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Speaker 2: They're not always right.

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Speaker 3: Who knows what happened when trade starts with Bloombo's baited

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Speaker 3: at Schultz.

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Speaker 2: Please don't go far.

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Speaker 3: Stay with Bloomberg Tech because coming up later this hour

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Speaker 3: we will speak with Cerebra CEO Andrew Feldman, and if

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Speaker 3: you're on the socials, hit me up.

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Speaker 2: I'll welcome your questions.

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Speaker 3: Now, coming up, China's Jujingping gives a warning to President

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Speaker 3: Trump on Taiwan. We're gonna have those details next. This

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Speaker 3: is Bloomberg Tech, one.

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Speaker 6: Of the most important summit in human history, and the

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Speaker 6: two the two presidents.

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Speaker 7: President, you don't Trump have such a monty relationship. This

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Speaker 7: is an incredible opportunity for us to rely on the

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Speaker 7: relationships to build up much munch partnership.

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Speaker 6: Did you get any specific customers for your chips for

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Speaker 6: the eighths two hundred we didn't really talk about. I'm

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Speaker 6: here to support the president and to represent the unity.

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Speaker 3: That was in Nvidia CEO Jensen Wong speaking to reporters

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Speaker 3: in Beijing and telling Bloomberg the company hasn't really discussed

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Speaker 3: the h two hundred chips during the president's trips to China.

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Speaker 3: He's there to support President Trump. What was discussed though,

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Speaker 3: it's Taiwan Jijingping through state news agency calling it quote

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Speaker 3: highly dangerous situation for the world's biggest economies. Let's get

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Speaker 3: out to bloembig Tyler Kendall, who joins us from Beijing.

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Speaker 2: There are many threads.

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Speaker 3: We also have the breaking news of the last fifteen minutes,

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Speaker 3: the President saying that Iran was discussed and that there

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Speaker 3: is some sort of agreement there.

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Speaker 2: What do we need to know? What's the latest from China?

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Speaker 8: Well, at this point, as you're saying, there are a

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Speaker 8: lot of different threads that we could pull on here.

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Speaker 2: I can't say that the.

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Speaker 8: Overarching theme appears to be that the efforts here in

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Speaker 8: Beijing are aimed at stabilizing ties between the US and

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Speaker 8: China rather than overhauling them. If we start with the

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Speaker 8: latest news, President Trump out saying that Jijingping has pledged

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Speaker 8: not to supply with any weapons and that it's going

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Speaker 8: to help get Ran to the negotiating table. Perhaps this

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Speaker 8: will help make some progress when it comes to what

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Speaker 8: has been gridlock in those ongoing discussions, as well as

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Speaker 8: a reopening in the Strait of hermus Though we would

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Speaker 8: be remiss if we didn't point out that from the

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Speaker 8: Chinese readout, we didn't really get any indications that China

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Speaker 8: is willing to go further in terms of helping to

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Speaker 8: ease that conflict, saying instead that they had extensive dialogue

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Speaker 8: about the situation in the Middle East, but not really

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Speaker 8: giving us any firmer details there. Another point where there

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Speaker 8: appeared to be a mismatch in terms of the public

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Speaker 8: readouts from what happened behind closed doors was, as you mentioned,

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Speaker 8: that issue related to Taiwan, as Chinese President Jijingping basically

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Speaker 8: threatened that Taiwan could derail the US China relationship. That

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Speaker 8: was not mentioned when it came to the US readout

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Speaker 8: in this and in fact, we just heard from Secretary

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Speaker 8: of State Marco Rubio, who appeared to downplane, that the

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Speaker 8: concerns were raised after we really saw US officials in

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Speaker 8: recent days signal that there would not be a change

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Speaker 8: when it comes to US policy regarding Taiwan. Now, we

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Speaker 8: can't say, though, that there was a more optimistic tone

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Speaker 8: reached when it came to the economic issues, including the

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Speaker 8: fact that Chinese President Jijingping did appear to signal a

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Speaker 8: move towards greater openness, telling tech execs in the room,

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Speaker 8: including Elon Musk, Tim Cook, Jensen Wong, who traveled with

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Speaker 8: President Trump in part quote that China's door to the

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Speaker 8: outside world will only open wider. Though despite the messaging,

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Speaker 8: we haven't really seen tangible signs yet that any steps

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Speaker 8: have been taken. But Chinese state media did report that

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Speaker 8: these executives told Jijingping directly that they highly value the

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Speaker 8: Chinese market and ed as you well know, this US

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Speaker 8: business delegation includes these companies that already have high exposure

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Speaker 8: to the Chinese market, but also companies like Micron, which

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Speaker 8: have seen some of their products barred over cybersecurity concerns

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Speaker 8: here in China. We can't say at this point there's

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Speaker 8: still a lot that we are waiting for purchase agreements

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Speaker 8: when it comes to agriculture, Boeing aircraft, or energy products

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Speaker 8: from the US. But the dialogue does continue. These pair

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Speaker 8: of leaders do have bilateral meetings going into tomorrow as well.

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Speaker 3: Bloomberg's Tyler Kendall with everything you need to know out

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Speaker 3: of China so far in the meeting between President Trump

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Speaker 3: and China's using ping. Thank you very much, And let's

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Speaker 3: get the broader picture with Michelle Guide, the CEO the

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Speaker 3: Crack Institute for Tech Diplomacy at Purdue, also served as

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Speaker 3: Assistant Secretary of State for Global Public Affairs under the

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Speaker 3: first Trump administration. You understand how this works and you

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Speaker 3: understand what's at stake, and like here on Bloomberg Tech, right,

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Speaker 3: I want to start with Taiwan because for a very

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Speaker 3: long time you've been coming on this program and we've

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Speaker 3: been talking about Taiwan in the context of America's dependence

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Speaker 3: on that nation for semiconductor supply. Right, I'm literally talking

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Speaker 3: about TSMC and the manufacturing footprint in China in Taiwan.

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Speaker 3: Apologies if we learn anything new here on Taiwan. What

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Speaker 3: did you make of President G's statement? I suppose through

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Speaker 3: the State.

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Speaker 9: Agency, nothing's new here. I think the position that China

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Speaker 9: has taken on Taiwan being really important to them when

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Speaker 9: it comes to US China relations has been the case

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Speaker 9: for quite some time. We know that General Secretary Shijinping

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Speaker 9: has been pressuring the President on arm sales to Taiwan

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Speaker 9: for a while, so that's not new at all, and

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Speaker 9: neither is the United States position on maintaining the status quo.

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Speaker 9: As Secretary Rubio said, there's been no change on the

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Speaker 9: US position here with regards to Taiwan. But as you

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Speaker 9: had mentioned, the ties between Taiwan United States are strong,

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Speaker 9: they run deep. Some MY conductors are a critical piece

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Speaker 9: of that, and there's been a lot of collaboration with

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Speaker 9: TSMC building out here the United States increasingly more over time,

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Speaker 9: and I think ultimately the status quo hasn't changed.

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Speaker 3: A red headline on the Bloomberg terminal just before we

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Speaker 3: came on air, President Trump saying that President G offered

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Speaker 3: help on Iran and pledged not to send weapons to Iran.

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Speaker 2: The President has said that.

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Speaker 3: It wouldn't be an important topic of conversation, but actually,

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Speaker 3: if you look at what markets are saying and what

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Speaker 3: people are saying on socials, it's a key issue, particularly

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Speaker 3: on how it would have a bearing on the straight

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Speaker 3: of hormus.

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Speaker 9: It's been one of several key issues. I think it's

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Speaker 9: not surprising that they talked about Iran. It was looming

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Speaker 9: over this entire thirty six hour summit. The fact that

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Speaker 9: you had mentioned this breaking news that presidency is going

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Speaker 9: to stop supporting the Iranian regime is a positive step

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Speaker 9: and I think one that the United States would welcome,

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Speaker 9: So again not surprising, And I think overall, the big

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Speaker 9: picture on this is, you know, this is a thirty

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Speaker 9: six hour summit on all of these agenda items and

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Speaker 9: ultimately micro movements in a much bigger picture here of

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Speaker 9: the United States and its long term view to achieve

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Speaker 9: the Golden Age of America and retain our leadership across

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Speaker 9: the world. And China is on its own path to

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Speaker 9: China rejuvenation, and the big question is who gets there first?

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Speaker 9: And did the thirty six hours in this summit helped

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Speaker 9: the United States move incrementally faster toward our vision.

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Speaker 3: I just want to disclose the Bloomberg Tech audience that

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Speaker 3: President Trump in those comments about Iran and President G's

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Speaker 3: commitment for run that was part of a Fox News interview,

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Speaker 3: a clip that Bloomberg reviewed. Michelle, would you kindly draw

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Speaker 3: on your experience from participating in the first Trump administration?

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Speaker 3: What does it take to put a delegation like this

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Speaker 3: together that includes Elon Musk Jensen one, picking them up

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Speaker 3: in Alaska for the Refield stop on Air Force one,

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Speaker 3: and taking the world's most important tech CEOs to China

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Speaker 3: as part of a high stakes meeting between President Trump

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Speaker 3: and President G.

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Speaker 9: Yeah, these things take a lot of preparation historically and

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Speaker 9: especially in terms of what you want the meetings to

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Speaker 9: be about the readouts coming out of these meetings. However,

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Speaker 9: I will say this, this type of delegation is unprecedented,

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Speaker 9: and I think if you look at how the President

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Speaker 9: has been agile and maybe non traditional in his work,

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Speaker 9: so are these tech CEOs. They move fast, and they're disruptive,

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Speaker 9: and it's easy to hop on a plane in Alaska

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Speaker 9: and go to China. So I'd say, you know, there's

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Speaker 9: a lot of planning at the same time with this administration,

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Speaker 9: with these types of disruptive tech leaders, there's also a

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Speaker 9: lot of room for ad libbing and improvisation, and I

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Speaker 9: think that's what we're seeing here.

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Speaker 3: Michelle Goad to see you at the Correct Institute for

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Speaker 3: Tech Diplomacy at Purdue.

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Speaker 2: Thank you very much.

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Speaker 3: Now coming up, we're going to get out to Napa

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Speaker 3: Valley for our own Caroline Hyde set to speak with

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Speaker 3: the CEO of Ericsson on the sidelines of the Spark

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Speaker 3: Global Leadership Summit.

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Speaker 2: It's coming up next. This is Bloomberg Tech.

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Speaker 3: Nuclear power is trying to make a comeback, but the

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Speaker 3: resources required are in short supply. From uranium mining to enrichment.

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Speaker 3: The supply chain is being reshaped by geopolitics, lobbyists, rising

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Speaker 3: energy demand, new technologies. That's the focus of Bloomberg this week.

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Speaker 2: Listen to this.

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Speaker 10: Global investment in nuclear energy since twenty twenty is estimated

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Speaker 10: to be around three hundred billion dollars, with ambitious plans

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Speaker 10: in Europe, North America and Asia to revive or kickstart

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Speaker 10: their nuclear energy sectors. Every step of the supply chain,

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Speaker 10: from mining to enrichment to building reactors is highly regulated

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Speaker 10: and controlled. Because a single misstep could be catastrophic and

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Speaker 10: erode the public trust nuclear has worked decades to regain.

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Speaker 11: It's a real shift from when I came of age

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Speaker 11: and everyone was worried about nuclear war because the process

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Speaker 11: of enriching uranium for a nuclear fuel the same technology

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Speaker 11: that they use for enriching uranium to make nuclear weapon.

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Speaker 3: Catch the full episode of Primer on Bloomberg dot com

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Speaker 3: and YouTube. Let's get over to the Spark Global Leadership

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Speaker 3: Summit in Napo, where own Caroline Hyde is standing.

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Speaker 12: By carroc It is a tough life being hosted by

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Speaker 12: Consello here in Napa Valley, and I'm very pleased to

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Speaker 12: say I'm joined by a giant in telecoms based in Sweden.

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Speaker 12: Eriksson is a global company and bory at Com.

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Speaker 2: Is here with me. Who is the CEO?

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Speaker 12: Tell me about the China exposure you have, You have

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Speaker 12: supply chain, that you have, consumer and competition is really

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Speaker 12: what you have from China? What did you make of

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Speaker 12: the relationship between us and China that we just said overnight?

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Speaker 13: Thanks for having me, And that's a great question to ask,

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Speaker 13: very hard to answer. Actually we like to do that

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Speaker 13: in Jennal No I know, but I think there is

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Speaker 13: You know, China is started out as I often look

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Speaker 13: at the old telecom movie from China, right, it actually

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Speaker 13: started out as being a prioritized sector in China. So

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Speaker 13: they had almost one hundred vendors if you go back

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Speaker 13: thirty years. They consolidated into really two that became fierce

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Speaker 13: competitors in the over a decade, que one Key one

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Speaker 13: One Way of course being the biggest, and they started

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Speaker 13: out being of course low cost and fairly simple. Today

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Speaker 13: they are, of course a phenomenal competitor, and it's the

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Speaker 13: one that we benchmark ourselves with and said that's.

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Speaker 14: The one we need to beat.

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Speaker 13: Actually, we need to win on technology, we need to

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Speaker 13: win on cost positions. So for us, the competition with

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Speaker 13: China is front and center and has been, and.

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Speaker 14: I do believe that for the rest of the world

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Speaker 14: to compete with China, you need to lead on technology.

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Speaker 12: But you've been outspoken in the past sort of pushing

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Speaker 12: against this idea of sort of a focus on your

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Speaker 12: own country and banning. In Sweden they pushed out Chinese competition,

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Speaker 12: and you actually at the times that that's the wrong

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Speaker 12: thing to do in the US. That is your key

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Speaker 12: markets now are the US, that Japan, there are other nations.

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Speaker 12: How do you think about the China being excluded and

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Speaker 12: should they be?

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Speaker 13: You know, the way to think about about China is

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Speaker 13: actually it's multi pronent. So if you take telecom again

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Speaker 13: scale game, they have scale in their domestic market.

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Speaker 14: That's a market you need to be in.

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Speaker 13: But more importantly, what was also clear is that given

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Speaker 13: the development in China economically and use case wise youse

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Speaker 13: so data consumption grow much.

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Speaker 14: Faster in China than anywhere else in the world.

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Speaker 13: That led them to lead on or demanding certain technologies

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Speaker 13: ahead of the rest of the world. So unless you're

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Speaker 13: on the same development curve as they are in China,

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Speaker 13: we're not going to be able to bring those solutions globally.

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Speaker 13: So if we take in our case, we have what's

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Speaker 13: called massive MIMO. Basically it's a way to increase capacity

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Speaker 13: in the radio network. They needed that earlier than in

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Speaker 13: the rest of the world, and therefore if you're not

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Speaker 13: there when that happens, you don't develop the technologies at

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Speaker 13: the same pace as they do in China. So I

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Speaker 13: think it's a much more interdependent world. You need to

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Speaker 13: think of the world as being interdependent.

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Speaker 12: And you're dependent on geopolitics, tariffs, inflationary pressures, the straight

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Speaker 12: up all moves again front and center today. How are

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Speaker 12: you managing that?

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Speaker 13: You know, we actually took a decision a number of

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Speaker 13: years ago now to say that we have three home markets.

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Speaker 13: So that was recognizing the US because it's a.

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Speaker 14: Front runder market.

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Speaker 13: Big India in those days was big today it's starting

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Speaker 13: also to be front runder on technology Japan. Japan is

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Speaker 13: very big in telecom and also an early adopter of telecom,

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Speaker 13: so we said that's markets we need to win in

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Speaker 13: to make sure that we combat the scale of China.

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Speaker 13: So we did that. Then we said we need a

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Speaker 13: flexible supply chain in order to manage any disturbances. So

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Speaker 13: we built a factory here in the US.

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Speaker 12: How big is you're manufacturing now here in the US?

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Speaker 13: We manufactured pretty in a large portion of what's supplied

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Speaker 13: to the US manufactured here in the US. So we

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Speaker 13: built that in twenty commissioned at about twenty twenty, so

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Speaker 13: we were ahead of the really supplied constraints in that

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Speaker 13: sense and the tariff issues. So we've been able to

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Speaker 13: use that manufacturing footprint. R and D footprint to actually

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Speaker 13: manage a bit of the geopolitical exposure.

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Speaker 12: Now we look at the markets today and extraordinary rampire

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Speaker 12: on the back of AI. AI is the excitement in

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Speaker 12: your area as well. Look, you've got competition with Nokia,

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Speaker 12: who has got a strong relation with n Video and

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Speaker 12: they've gone big into data center. Briefly, how do you

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Speaker 12: think about the AA opportunity.

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Speaker 13: We think of the AA opportunity as a massive opportunity

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Speaker 13: for us for the simple reason that AI will ultimately

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Speaker 13: move out to the physical world call it industrial AI,

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Speaker 13: physical AI, and that's going to require inference at the

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Speaker 13: edge of the network to manage the latency requirements, et cetera.

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Speaker 13: And then connectivity be needed. So we will start to

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Speaker 13: enter the world where everything has to be connected. So

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Speaker 13: when everything is connected, you can't connect them with wires.

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Speaker 13: It just simply doesn't work. You're going to need the

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Speaker 13: terrestrial cellular network to provide the backbone to scale AI.

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Speaker 13: So I think of AI. Yes, it's going to fundamentally

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Speaker 13: change the economy. It's going to be a driver or productivity.

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Speaker 13: It's hugely positive and for us it will be a

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Speaker 13: benefit because we will see a new type of traffic

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Speaker 13: coming in.

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Speaker 12: The network, I can talk to you more. I'm luckily

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Speaker 12: going to be talking to you in a panel a

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Speaker 12: little bit later here at the Spark Leadership Summit, hosted

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Speaker 12: by Cancillo, ed back to you, all right, coming.

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Speaker 2: Up, rebrass IPO time a big conversation. This is Bloomberg.

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Speaker 2: Welcome back to Bloomberg.

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Speaker 3: Tech to our TV viewers and radio listeners around the world.

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Speaker 3: Were joined by Andrew Feldman Cerebres CEO Cerebrest priceless IPO.

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Speaker 3: Andrew one hundred and eighty five dollars a share above

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Speaker 3: the top end of the marketing range. I'm looking at

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Speaker 3: the Bloomberg terminal shares indicated to open three hundred and

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Speaker 3: fifty dollars a share.

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Speaker 2: Your reaction to that.

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Speaker 15: Pretty good day? Huh?

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Speaker 2: How you feel? I mean, did you see this coming?

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Speaker 3: There's some mechanics to it, right, but you know, I

440
00:23:28,240 --> 00:23:30,480
Speaker 3: know you, I know you like to let's be honest,

441
00:23:30,800 --> 00:23:33,159
Speaker 3: you like to talk about what's happening in AI. The

442
00:23:33,200 --> 00:23:36,960
Speaker 3: big focus on inference Cerebress is place in it. But

443
00:23:37,040 --> 00:23:39,000
Speaker 3: this is the biggest IPO of the year so far.

444
00:23:39,680 --> 00:23:41,280
Speaker 3: You know, what does it mean to you and your

445
00:23:41,320 --> 00:23:42,760
Speaker 3: employees and your back is.

446
00:23:44,440 --> 00:23:47,280
Speaker 16: It's the biggest tech one of the biggest tech IPOs

447
00:23:47,280 --> 00:23:50,879
Speaker 16: in history, and it's the biggest SEMIIPO in history.

448
00:23:52,280 --> 00:23:53,520
Speaker 15: We couldn't be more proud.

449
00:23:54,359 --> 00:23:58,399
Speaker 16: This is the coumbination of a decade, a work of

450
00:23:58,640 --> 00:24:05,200
Speaker 16: countless late nights and long weekends. We are enormously proud

451
00:24:05,280 --> 00:24:09,520
Speaker 16: and excited and ready to get back to work and

452
00:24:10,600 --> 00:24:13,720
Speaker 16: start working on the next, on the next great thing.

453
00:24:14,760 --> 00:24:17,919
Speaker 3: Again, the market is indicating shares to open at three

454
00:24:18,000 --> 00:24:19,720
Speaker 3: hundred and fifty dollars a share. Let's see where we're

455
00:24:19,760 --> 00:24:24,040
Speaker 3: at when trading starts. But you're being priced in as

456
00:24:24,080 --> 00:24:28,440
Speaker 3: a major player in this field. Now, what evidence would

457
00:24:28,480 --> 00:24:31,159
Speaker 3: you point to that you are in fact a major payer.

458
00:24:31,400 --> 00:24:34,359
Speaker 3: A lot of focus is on the concentration in the

459
00:24:34,400 --> 00:24:37,080
Speaker 3: relationship with open Ai. Tell me about some of the

460
00:24:37,119 --> 00:24:41,480
Speaker 3: other frontier labs or other names that you have some

461
00:24:41,600 --> 00:24:42,560
Speaker 3: concrete talks with.

462
00:24:42,840 --> 00:24:46,200
Speaker 16: Sure in the last four months, we announced a deal

463
00:24:46,240 --> 00:24:50,120
Speaker 16: with open ai and that's north of twenty billion dollars

464
00:24:50,240 --> 00:24:54,520
Speaker 16: for seven hundred and fifty megawads of compute. We also

465
00:24:54,560 --> 00:25:01,119
Speaker 16: announced a major engagement with AWS. Our equipment would be

466
00:25:01,160 --> 00:25:05,160
Speaker 16: deployed in their data centers. I think those are obviously

467
00:25:05,200 --> 00:25:08,160
Speaker 16: the largest, but there are dozens of others that are

468
00:25:09,600 --> 00:25:12,520
Speaker 16: in what used to be a big deal in the

469
00:25:12,560 --> 00:25:15,600
Speaker 16: ten to fifty million dollar category, and so there's just

470
00:25:16,200 --> 00:25:20,679
Speaker 16: an extraordinary demand right now for fast inference. We're the fastest,

471
00:25:20,760 --> 00:25:22,720
Speaker 16: not by a little bit, but by more than an

472
00:25:22,880 --> 00:25:26,120
Speaker 16: order of magnitude. You know, we're fifteen times faster than

473
00:25:26,160 --> 00:25:30,080
Speaker 16: the next nearest competitor. And as AI has become useful,

474
00:25:30,359 --> 00:25:31,760
Speaker 16: everybody wants it to be fast.

475
00:25:31,840 --> 00:25:32,920
Speaker 15: Nobody wants to wait.

476
00:25:33,880 --> 00:25:36,919
Speaker 3: On that, you know, twenty one x on you know

477
00:25:37,040 --> 00:25:39,040
Speaker 3: performance and also like a lot of emphasis on the

478
00:25:39,080 --> 00:25:42,359
Speaker 3: dollar PA token, right that is the metric that the

479
00:25:42,400 --> 00:25:43,560
Speaker 3: field cares about.

480
00:25:44,200 --> 00:25:45,200
Speaker 2: But that's on paper.

481
00:25:45,560 --> 00:25:48,000
Speaker 3: You know, you just talked about the AWS relationship as

482
00:25:48,040 --> 00:25:51,639
Speaker 3: an engagement. When does the word engagement end and real

483
00:25:51,720 --> 00:25:55,680
Speaker 3: revenues start to show up for you from those relationships.

484
00:25:56,000 --> 00:25:59,560
Speaker 16: Sure, we signed a binding term shoot with AWS as

485
00:25:59,600 --> 00:26:03,720
Speaker 16: described in RS one, and we're working through the master agreement.

486
00:26:05,240 --> 00:26:08,280
Speaker 16: I think in dealing with organizations of that size, it

487
00:26:08,320 --> 00:26:11,480
Speaker 16: takes a little time to dot all the i's and

488
00:26:11,560 --> 00:26:14,879
Speaker 16: cross the t's, but we are extremely confident that they

489
00:26:14,920 --> 00:26:18,960
Speaker 16: will be an enormous channel for us and a partner

490
00:26:19,040 --> 00:26:25,520
Speaker 16: in delivering our technology to large enterprises and medium sized

491
00:26:25,600 --> 00:26:29,720
Speaker 16: enterprises around the world. I think they are one of

492
00:26:29,760 --> 00:26:33,399
Speaker 16: the preferred cloud providers for just about every enterprise on Earth,

493
00:26:34,000 --> 00:26:38,560
Speaker 16: and so an opportunity to have your solution embedded in

494
00:26:38,600 --> 00:26:43,520
Speaker 16: their offering as part of their bedrock offering, that's a

495
00:26:43,600 --> 00:26:44,480
Speaker 16: huge win for us.

496
00:26:45,920 --> 00:26:48,240
Speaker 3: We're live on Bloomberg Television and Radio. This is a

497
00:26:48,280 --> 00:26:51,280
Speaker 3: Bloomberg Tech takeover, and we're speaking to Andrew Feldman, the

498
00:26:51,320 --> 00:26:54,439
Speaker 3: CEO of Crebrius, whose company just priced the IPO at

499
00:26:54,440 --> 00:26:56,320
Speaker 3: one hundred and eighty five dollars a share and is

500
00:26:56,359 --> 00:26:59,560
Speaker 3: indicated right now, I'm looking on the Bloomberg terminal maybe

501
00:26:59,600 --> 00:27:02,560
Speaker 3: to start trade at three hundred and fifty dollars a share. Andrew,

502
00:27:02,640 --> 00:27:04,680
Speaker 3: I think you know this about me. Whenever we have

503
00:27:05,080 --> 00:27:07,320
Speaker 3: a big moment, to have a conversation like this, I

504
00:27:07,320 --> 00:27:09,840
Speaker 3: always go to the Bloomberg Tech audience. What do they

505
00:27:09,880 --> 00:27:14,640
Speaker 3: want to know? And actually the first question is what

506
00:27:14,760 --> 00:27:19,280
Speaker 3: was your attitude toward retail investors? Why did you not

507
00:27:19,400 --> 00:27:22,280
Speaker 3: do more for the retail investor in this big moment

508
00:27:22,320 --> 00:27:23,000
Speaker 3: for your company?

509
00:27:24,960 --> 00:27:27,600
Speaker 15: We were more than twenty five x oversubscribed.

510
00:27:27,720 --> 00:27:31,040
Speaker 16: There was a lot of hard decisions that needed to

511
00:27:31,080 --> 00:27:35,840
Speaker 16: be made, and nobody got what they wanted, and you know,

512
00:27:35,920 --> 00:27:36,920
Speaker 16: we did our best.

513
00:27:37,119 --> 00:27:38,240
Speaker 15: It's about all you can do.

514
00:27:38,320 --> 00:27:41,679
Speaker 16: When there's twenty five times more demand for your stock

515
00:27:42,119 --> 00:27:46,119
Speaker 16: at the institutional level and at the retail level, then

516
00:27:46,280 --> 00:27:47,600
Speaker 16: there are shares to be sold.

517
00:27:47,760 --> 00:27:50,080
Speaker 15: So we're really proud of the way we chose to

518
00:27:50,119 --> 00:27:50,359
Speaker 15: do it.

519
00:27:50,440 --> 00:27:54,200
Speaker 16: We thought we did it with integrity, and I think

520
00:27:54,240 --> 00:27:57,879
Speaker 16: we are very comfortable with the ending allocation.

521
00:27:59,040 --> 00:28:02,400
Speaker 3: Full stack, fully vertically integrated. And what I mean by

522
00:28:02,400 --> 00:28:05,680
Speaker 3: that is you literally build the supercomputer top to tail, right,

523
00:28:05,720 --> 00:28:08,240
Speaker 3: so in Video will do the tray, not just GPU,

524
00:28:08,320 --> 00:28:12,240
Speaker 3: but then Dell super Micro will assemble it. Dell's margins

525
00:28:12,280 --> 00:28:18,000
Speaker 3: low teens, in Video's margins mid seventies, Your margins forty

526
00:28:18,080 --> 00:28:20,359
Speaker 3: forty one percent. And what I'm trying to help the

527
00:28:20,400 --> 00:28:24,920
Speaker 3: audience understand is why that strategy of owning everything top

528
00:28:24,960 --> 00:28:26,879
Speaker 3: to sail is going to pay off in the long run.

529
00:28:26,960 --> 00:28:28,600
Speaker 3: And I would say that The other question I get

530
00:28:28,640 --> 00:28:31,760
Speaker 3: for you is what's the future outlook for margins based

531
00:28:31,760 --> 00:28:32,439
Speaker 3: on your plans?

532
00:28:34,119 --> 00:28:35,440
Speaker 15: Well, I think a couple things.

533
00:28:36,040 --> 00:28:41,200
Speaker 16: I think we have obviously opportunities at to improve our

534
00:28:41,280 --> 00:28:44,760
Speaker 16: cost structure. You know, we did half a billion last

535
00:28:44,800 --> 00:28:47,760
Speaker 16: year in sales. That means we put two hundred and

536
00:28:47,760 --> 00:28:50,480
Speaker 16: fifty million in the supply chain. Obviously that's not an

537
00:28:50,520 --> 00:28:51,560
Speaker 16: efficient spot.

538
00:28:51,960 --> 00:28:53,880
Speaker 15: As we grow, we will have.

539
00:28:53,840 --> 00:28:56,640
Speaker 16: More leverage in the supply chain and our cost of

540
00:28:56,720 --> 00:29:03,320
Speaker 16: goods will come down. I think we have an opportunity to.

541
00:29:01,720 --> 00:29:03,920
Speaker 15: To increase prices.

542
00:29:04,400 --> 00:29:08,080
Speaker 16: I think the demand for for fast inference is overwhelming

543
00:29:08,160 --> 00:29:10,720
Speaker 16: this minute, and so I think in the in the

544
00:29:10,720 --> 00:29:13,160
Speaker 16: long run will be really proud of our of our

545
00:29:13,200 --> 00:29:16,320
Speaker 16: gross margins and where they will sort of wash out

546
00:29:16,360 --> 00:29:17,880
Speaker 16: as we hit scale.

547
00:29:18,880 --> 00:29:20,520
Speaker 3: I've got a question for you from a from a

548
00:29:20,600 --> 00:29:23,040
Speaker 3: terminal client via i B. Thank you for the question.

549
00:29:23,600 --> 00:29:25,960
Speaker 3: Everyone's tuned in right now, Andrew. They want they want

550
00:29:26,000 --> 00:29:28,680
Speaker 3: they want the detail. And so one way that people

551
00:29:28,680 --> 00:29:30,960
Speaker 3: look at it is that you know, this is custom silicon,

552
00:29:31,480 --> 00:29:34,240
Speaker 3: but Cerebrius isn't. Isn't a chip per se. It's like

553
00:29:34,320 --> 00:29:38,000
Speaker 3: wafer level, right. Is there a reason why you can't

554
00:29:38,040 --> 00:29:40,360
Speaker 3: just sell that versus the whole server?

555
00:29:42,200 --> 00:29:44,760
Speaker 15: Yeah, that that's a good question.

556
00:29:47,040 --> 00:29:49,760
Speaker 16: For the entire seventy year history of the computer industry,

557
00:29:49,880 --> 00:29:52,720
Speaker 16: every previous effort had failed to build a chip of

558
00:29:52,760 --> 00:29:56,360
Speaker 16: the size. So for your for your audience. This chip

559
00:29:56,480 --> 00:30:00,000
Speaker 16: is the size of a dinner plate, while traditional chips

560
00:30:00,040 --> 00:30:04,680
Speaker 16: through the size of a postage stamping. And not only

561
00:30:04,720 --> 00:30:07,959
Speaker 16: had everybody failed until we succeeded, but several tried to

562
00:30:07,960 --> 00:30:09,480
Speaker 16: copy us and have since.

563
00:30:09,280 --> 00:30:13,080
Speaker 15: Failed as well. Part of what we.

564
00:30:12,880 --> 00:30:16,160
Speaker 16: Were capable of doing and able to do was that

565
00:30:16,680 --> 00:30:19,239
Speaker 16: we were able to use not just the chip, but

566
00:30:19,320 --> 00:30:23,080
Speaker 16: also our expertise in packaging and in system design to

567
00:30:23,200 --> 00:30:27,760
Speaker 16: solve some of the problems and build a truly compelling solution. Right,

568
00:30:27,880 --> 00:30:30,720
Speaker 16: you don't just get fifteen or eighteen or twenty times

569
00:30:30,760 --> 00:30:33,840
Speaker 16: faster than the competition because you built a good chip.

570
00:30:34,360 --> 00:30:38,280
Speaker 16: That's one of a collection of different things that enable

571
00:30:38,360 --> 00:30:41,000
Speaker 16: that sort of performance. You can build a great chip,

572
00:30:41,720 --> 00:30:46,920
Speaker 16: and the system vendor, the ODM, can nibble away at

573
00:30:46,960 --> 00:30:49,720
Speaker 16: your performance by not delivering the right amount of power

574
00:30:49,800 --> 00:30:54,080
Speaker 16: or the right amount of IO. Right, there's a reason

575
00:30:54,120 --> 00:30:56,680
Speaker 16: why in Nvidia then sought to control the IO the

576
00:30:57,080 --> 00:31:00,440
Speaker 16: Envy link, because they didn't want others to nibble away

577
00:31:01,360 --> 00:31:05,680
Speaker 16: at their performance. And so by building the system, we're

578
00:31:05,720 --> 00:31:08,920
Speaker 16: able to optimize all parts. I mean, you could ask

579
00:31:08,960 --> 00:31:11,040
Speaker 16: the same thing about Porschow. You know, why don't you

580
00:31:11,080 --> 00:31:14,760
Speaker 16: sell just engines, right, Andrew. It turns out that that's

581
00:31:15,840 --> 00:31:18,520
Speaker 16: a nine to eleven is a beautiful car because of

582
00:31:18,520 --> 00:31:21,120
Speaker 16: the engine and everything else they put in it.

583
00:31:21,360 --> 00:31:23,560
Speaker 3: Andrew, the team's telling me we've got to go, But

584
00:31:23,600 --> 00:31:26,320
Speaker 3: I got to ask you five point five billion dollars,

585
00:31:26,600 --> 00:31:29,440
Speaker 3: what do you use the proceeds for? And actually, how

586
00:31:29,480 --> 00:31:32,840
Speaker 3: flexible can you now be an allocating capacity to new customers.

587
00:31:32,960 --> 00:31:34,120
Speaker 3: We just have thirty seconds.

588
00:31:35,000 --> 00:31:39,520
Speaker 16: Oh, I think we will use it to increase capacity.

589
00:31:39,680 --> 00:31:43,040
Speaker 16: We are excited to bring many new customers on board.

590
00:31:43,080 --> 00:31:46,800
Speaker 16: There's tremendous demand for what we're doing. I think we

591
00:31:46,800 --> 00:31:48,120
Speaker 16: can be aggressive on that front.

592
00:31:49,680 --> 00:31:54,000
Speaker 3: Andrew Feldman, Cerebras CEO pricing the IPO one eighty five

593
00:31:54,680 --> 00:31:57,080
Speaker 3: indicated to open three hundred and fifty dollars a share.

594
00:31:57,480 --> 00:31:58,320
Speaker 2: Thank you for your time.

595
00:32:00,040 --> 00:32:03,800
Speaker 3: Now coming up, Tom Hale, the Aura CEO, discusses the

596
00:32:03,840 --> 00:32:05,720
Speaker 3: future of wearables. So you're going to go back to

597
00:32:05,720 --> 00:32:17,960
Speaker 3: the Spark Summit next. This is Bloomberg Tech. Let's go

598
00:32:18,040 --> 00:32:20,320
Speaker 3: back to the Spark Summit where our own Caroline Hyde

599
00:32:20,520 --> 00:32:21,160
Speaker 3: is standing by.

600
00:32:22,000 --> 00:32:24,720
Speaker 12: I am the Cancello Sparks Summit right here in Napa Valley,

601
00:32:25,040 --> 00:32:28,400
Speaker 12: and with wine comes a focus on your health, and

602
00:32:28,440 --> 00:32:30,280
Speaker 12: many might be looking at their orering today is to

603
00:32:30,280 --> 00:32:32,640
Speaker 12: see how they're feeling after a day in Napa Valley.

604
00:32:32,680 --> 00:32:34,760
Speaker 12: And I'm joined by Tom hale acause, the CEO of Aura,

605
00:32:35,320 --> 00:32:39,120
Speaker 12: and with so exuberant in the market, whether it be

606
00:32:39,160 --> 00:32:43,080
Speaker 12: personally about artificial intelligence, I'm interested as to how you're

607
00:32:43,120 --> 00:32:46,320
Speaker 12: seeing your own product iterate or all about now prediction

608
00:32:46,520 --> 00:32:48,480
Speaker 12: not just assessing how I might feel on the day

609
00:32:48,560 --> 00:32:50,640
Speaker 12: or the inputs that I'm getting, but predicting how I

610
00:32:50,720 --> 00:32:51,360
Speaker 12: might in the future.

611
00:32:51,440 --> 00:32:53,600
Speaker 17: Yeah, We've been doing AI for many years, so I

612
00:32:53,600 --> 00:32:55,640
Speaker 17: think that's most interesting is that the predictions that we

613
00:32:55,720 --> 00:32:58,800
Speaker 17: make generally are short term. You might be getting sick

614
00:32:58,840 --> 00:33:00,920
Speaker 17: in a couple of days, is coming in a couple

615
00:33:00,960 --> 00:33:03,280
Speaker 17: of days, and they're very accurate because they're short term.

616
00:33:03,360 --> 00:33:05,120
Speaker 17: But I think where this starts to get really interesting

617
00:33:05,200 --> 00:33:08,560
Speaker 17: is if you can make predictions over a longer timeframe,

618
00:33:08,960 --> 00:33:11,959
Speaker 17: you're starting to help people understand how their behaviors can

619
00:33:12,000 --> 00:33:14,280
Speaker 17: bend the curve on their health outcomes or maybe even

620
00:33:14,360 --> 00:33:16,600
Speaker 17: ultimately on the cost of healthcare. I think this is

621
00:33:16,720 --> 00:33:20,440
Speaker 17: really disruptive but also really positive because one of the

622
00:33:20,480 --> 00:33:23,160
Speaker 17: biggest problems with healthcare is there's just simply not enough

623
00:33:23,160 --> 00:33:25,800
Speaker 17: care to be provided for everybody, and AI lowers the

624
00:33:25,840 --> 00:33:29,880
Speaker 17: cost and provides access and provides medical information. It has

625
00:33:29,920 --> 00:33:32,400
Speaker 17: to be high quality, it has to be scientifically validated,

626
00:33:32,480 --> 00:33:35,320
Speaker 17: has to be accurate and good. But that opportunity exists,

627
00:33:35,360 --> 00:33:38,120
Speaker 17: and so we're pretty excited about, Hey, how AI can

628
00:33:38,160 --> 00:33:39,360
Speaker 17: transform healthcare and the.

629
00:33:39,280 --> 00:33:41,800
Speaker 12: Moment an order RING is deemed in general wellness product,

630
00:33:42,360 --> 00:33:44,760
Speaker 12: but there could be even further ways in which you

631
00:33:44,800 --> 00:33:48,320
Speaker 12: move within the medical space that requires FDA approval, particularly

632
00:33:48,320 --> 00:33:50,440
Speaker 12: for blood pressure for example. How are you thinking about

633
00:33:50,440 --> 00:33:51,800
Speaker 12: that getting the science on board?

634
00:33:51,960 --> 00:33:55,440
Speaker 17: Well, our view is that we want to be as

635
00:33:55,440 --> 00:33:58,200
Speaker 17: aligned with the FDA as possible. We want to make

636
00:33:58,200 --> 00:34:00,479
Speaker 17: sure that what we do is in the path of

637
00:34:00,520 --> 00:34:03,400
Speaker 17: scientific and medical validation that includes the FDA. So we're

638
00:34:03,400 --> 00:34:06,640
Speaker 17: working closely on multiple submissions. Blood pressure is certainly one

639
00:34:06,680 --> 00:34:09,000
Speaker 17: of them. We're currently running something called the Blood Pressure

640
00:34:09,040 --> 00:34:13,040
Speaker 17: Profile Study. That's almost three hundred thousand people who are

641
00:34:13,200 --> 00:34:15,719
Speaker 17: taking CUUGH measurements and comparing to the predictions that the

642
00:34:15,800 --> 00:34:17,680
Speaker 17: RING is making. So we all have a data set

643
00:34:17,800 --> 00:34:21,239
Speaker 17: that will support the idea that what this does is accurate, validated,

644
00:34:21,440 --> 00:34:24,960
Speaker 17: clinically relevant until that time, we'll probably operate as a

645
00:34:24,960 --> 00:34:27,400
Speaker 17: wellness device, which means that we can provide insight, but

646
00:34:27,480 --> 00:34:29,200
Speaker 17: not something that's like a diagnosis.

647
00:34:29,200 --> 00:34:30,680
Speaker 14: Will stop short of that, the.

648
00:34:30,680 --> 00:34:32,799
Speaker 12: FDA doesn't have someone at the top right now, Does

649
00:34:32,800 --> 00:34:34,239
Speaker 12: that affect the way and what you want with you?

650
00:34:34,360 --> 00:34:35,440
Speaker 15: Yeah, not really.

651
00:34:35,800 --> 00:34:38,440
Speaker 17: I think we're very excited to see how we can

652
00:34:38,480 --> 00:34:40,680
Speaker 17: work with CDRH, which is the division of the FDA

653
00:34:40,719 --> 00:34:42,919
Speaker 17: that focused on that. So we're working with the rank

654
00:34:42,920 --> 00:34:45,440
Speaker 17: and file that people who are focused on medical devices,

655
00:34:45,680 --> 00:34:47,200
Speaker 17: and we have a great collaboration with them.

656
00:34:47,480 --> 00:34:49,600
Speaker 12: You have a great collaboration with Apple, but you're also

657
00:34:49,640 --> 00:34:51,560
Speaker 12: kind of friend of mees in some way to derise

658
00:34:51,600 --> 00:34:55,719
Speaker 12: it that way, Well, you've taken some significant talent from them.

659
00:34:55,920 --> 00:34:58,400
Speaker 17: Well, I think the interesting thing about how Apple and

660
00:34:58,520 --> 00:35:01,680
Speaker 17: Aura interact is that turns out that almost two thirds

661
00:35:01,719 --> 00:35:04,600
Speaker 17: of Aora ringwears have a second wearable, most often a

662
00:35:04,680 --> 00:35:07,200
Speaker 17: risk wearable, and most often an Apple watch. So we're

663
00:35:07,200 --> 00:35:12,360
Speaker 17: actually highly complimentary now going to the people, there's great talent.

664
00:35:12,440 --> 00:35:15,600
Speaker 17: Apple is produced some of the you know, the icons

665
00:35:15,640 --> 00:35:19,080
Speaker 17: of health and hardware, and I think having some of

666
00:35:19,080 --> 00:35:21,880
Speaker 17: those people join our team has been an incredible uh

667
00:35:22,640 --> 00:35:24,160
Speaker 17: I don't know. We feel very proud of the people

668
00:35:24,160 --> 00:35:27,160
Speaker 17: who've joined us, and we've got some We've got some

669
00:35:27,200 --> 00:35:29,080
Speaker 17: great connectivity with Apple as well.

670
00:35:29,680 --> 00:35:31,040
Speaker 2: I'm a long.

671
00:35:30,840 --> 00:35:34,319
Speaker 17: Time independent software developer on the Apple platform, so we

672
00:35:34,320 --> 00:35:35,840
Speaker 17: have a lot of people that we, you know, have

673
00:35:36,040 --> 00:35:37,080
Speaker 17: been working with for years.

674
00:35:37,200 --> 00:35:39,719
Speaker 12: Software developers are not cheap in this age of AI.

675
00:35:39,840 --> 00:35:41,000
Speaker 12: How are you thinking about your talent?

676
00:35:41,000 --> 00:35:44,640
Speaker 17: More broadly, so for us, the interesting thing is about

677
00:35:44,640 --> 00:35:47,120
Speaker 17: a year ago, people were like, wow, I.

678
00:35:47,040 --> 00:35:47,960
Speaker 14: Mean hardware is hard.

679
00:35:47,960 --> 00:35:48,920
Speaker 2: Why are you doing hardware?

680
00:35:48,920 --> 00:35:51,520
Speaker 17: And of course the first rule of software school is

681
00:35:51,800 --> 00:35:55,040
Speaker 17: you don't do hardware. So I've obviously I missed that

682
00:35:55,040 --> 00:35:57,600
Speaker 17: that class or lessons school. But it's worked out okay

683
00:35:57,680 --> 00:35:59,480
Speaker 17: because now what people tell us is they say, we

684
00:35:59,520 --> 00:36:02,600
Speaker 17: can't believe how resilient you are to the AI disruption

685
00:36:02,680 --> 00:36:03,320
Speaker 17: to software.

686
00:36:03,440 --> 00:36:04,680
Speaker 2: It turns out haftware.

687
00:36:04,840 --> 00:36:07,959
Speaker 17: Hardware is very very attractive right now because you can't

688
00:36:08,080 --> 00:36:10,799
Speaker 17: vibe code atoms right you can't.

689
00:36:10,520 --> 00:36:11,640
Speaker 2: Just summon them into existence.

690
00:36:11,640 --> 00:36:15,359
Speaker 17: And so interestingly, I think for Aura, steering the way

691
00:36:15,360 --> 00:36:17,680
Speaker 17: we have and having always been a hardware company with

692
00:36:17,680 --> 00:36:20,520
Speaker 17: a very strong software backing, it's actually been really advantageous

693
00:36:20,520 --> 00:36:22,439
Speaker 17: in investors look at us and they say, good, We're

694
00:36:22,480 --> 00:36:24,480
Speaker 17: so glad that you're not in the software space and

695
00:36:24,520 --> 00:36:25,560
Speaker 17: that you're a hardware provider.

696
00:36:26,040 --> 00:36:29,000
Speaker 12: You've just been luring more investment and you've got a

697
00:36:29,080 --> 00:36:32,520
Speaker 12: bigger market cap. On the private side, I'm interested is

698
00:36:32,520 --> 00:36:35,479
Speaker 12: to whether there's any inflationy pressures your investors are worried about.

699
00:36:35,480 --> 00:36:37,640
Speaker 12: How are you thinking about manufacturing, the stage of supply chain.

700
00:36:37,640 --> 00:36:39,560
Speaker 12: We think about home moves, we think about China today.

701
00:36:39,760 --> 00:36:43,120
Speaker 17: Yeah, I don't think we've really had seen the impact

702
00:36:43,200 --> 00:36:47,040
Speaker 17: of inflation on demand, which is good. We've certainly seen

703
00:36:47,200 --> 00:36:52,600
Speaker 17: some inflation impacts on kind of supply chain, but nothing material.

704
00:36:52,880 --> 00:36:54,920
Speaker 17: And interestingly the last year, of course, there was all

705
00:36:54,960 --> 00:36:57,080
Speaker 17: this drama about tariffs, and I think as a company

706
00:36:57,600 --> 00:37:00,880
Speaker 17: we were quite lucky. One we actually announced an intention

707
00:37:00,920 --> 00:37:02,880
Speaker 17: to have a factory built in the US, and so

708
00:37:02,920 --> 00:37:06,360
Speaker 17: that's actually one really interesting that it's just underway. You know,

709
00:37:06,640 --> 00:37:08,840
Speaker 17: we'll let you know when it's all rolled out. But

710
00:37:08,960 --> 00:37:11,040
Speaker 17: at the same time, I think we also were able to,

711
00:37:11,280 --> 00:37:13,480
Speaker 17: because we manufacture around the globe, be very careful to

712
00:37:13,520 --> 00:37:16,320
Speaker 17: sort of manage the terror issues very effectively.

713
00:37:16,760 --> 00:37:19,040
Speaker 12: Somehow could speak to you for much longer. CEO of

714
00:37:19,200 --> 00:37:21,440
Speaker 12: or a fascinating to catch up. We hand it back

715
00:37:21,440 --> 00:37:24,920
Speaker 12: to you from the concllo's Spark summit here in napavaliad.

716
00:37:25,880 --> 00:37:26,200
Speaker 2: Okay.

717
00:37:26,200 --> 00:37:28,320
Speaker 3: More interviews to come out of the Spark Summit throughout

718
00:37:28,320 --> 00:37:31,359
Speaker 3: the afternoon. Tune in for a conversation with open Ai

719
00:37:31,560 --> 00:37:37,440
Speaker 3: CFO Sarah Fryer eight thirty pm Eastern, five thirty pm Pacific.

720
00:37:38,600 --> 00:37:42,839
Speaker 3: Elon Musk is taking Grock to Wall Street. Sources tell

721
00:37:42,880 --> 00:37:47,360
Speaker 3: Bloomberg the heavyweights like Morgan Stanley and Apollo A testing

722
00:37:47,560 --> 00:37:52,560
Speaker 3: Xai's grok chatbox as SpaceX now parent of Xai, prepares

723
00:37:52,600 --> 00:37:55,400
Speaker 3: for an IPO. Bloom Best Carmen and Royer breaks the

724
00:37:55,440 --> 00:37:59,080
Speaker 3: story wide open. No surprise that you wake up. It's

725
00:37:59,120 --> 00:38:01,120
Speaker 3: one of the most read stories on the Bloomberg Terminal

726
00:38:01,520 --> 00:38:04,480
Speaker 3: and Bloomberg dot Com. There's so much detail in the

727
00:38:04,520 --> 00:38:10,000
Speaker 3: report about the Xai strategy. The players involved give us

728
00:38:10,000 --> 00:38:11,480
Speaker 3: as much of that detail as you can.

729
00:38:11,840 --> 00:38:12,880
Speaker 18: Sure, thanks for having me.

730
00:38:12,960 --> 00:38:13,080
Speaker 17: Yet.

731
00:38:13,560 --> 00:38:17,800
Speaker 18: Basically, Xai is trying to boost their corporate client roster

732
00:38:17,880 --> 00:38:21,400
Speaker 18: ahead of the IPO, and John Schalkin, who's been the

733
00:38:21,440 --> 00:38:24,840
Speaker 18: chief revenue officer the company has been really driving this strategy.

734
00:38:25,280 --> 00:38:27,480
Speaker 18: In order to do that, they've mainly gone to Wall

735
00:38:27,520 --> 00:38:30,800
Speaker 18: Street clients that have previously worked with MASK companies before.

736
00:38:31,360 --> 00:38:36,400
Speaker 18: Among them is Apollo, which helped finance XAIS access to chips.

737
00:38:36,440 --> 00:38:38,400
Speaker 18: It's Morgan Stanley, which is one of the go to

738
00:38:39,239 --> 00:38:42,440
Speaker 18: banks that has worked with MUSK for years, and it's

739
00:38:42,440 --> 00:38:44,600
Speaker 18: also Valor Equity, which is a venture capital firm that

740
00:38:44,640 --> 00:38:50,760
Speaker 18: has backed MASK companies for a long time. They're testing

741
00:38:50,880 --> 00:38:55,239
Speaker 18: Rock and they're using it alongside other AI models. But

742
00:38:55,320 --> 00:38:58,440
Speaker 18: this is happening while like you know, on Thropic and

743
00:38:58,480 --> 00:39:01,280
Speaker 18: Open AI are really trying to fight the same piece

744
00:39:01,280 --> 00:39:04,600
Speaker 18: of the pie, so the adoption is going very slowly.

745
00:39:05,640 --> 00:39:08,320
Speaker 3: No, So one real quick interesting thing is that actually

746
00:39:08,320 --> 00:39:12,400
Speaker 3: in your reporting they're not using it necessarily for work,

747
00:39:12,560 --> 00:39:13,160
Speaker 3: is that right?

748
00:39:13,440 --> 00:39:15,560
Speaker 2: Like on desk work in those firms.

749
00:39:15,360 --> 00:39:17,239
Speaker 18: They're trying to adopt it and use it along other

750
00:39:17,280 --> 00:39:21,719
Speaker 18: AI models, but the chadbod has been falling behind on

751
00:39:21,880 --> 00:39:25,040
Speaker 18: coding and a financial implementation, which is why XAI is

752
00:39:25,080 --> 00:39:28,120
Speaker 18: trying to like really ramp that effort up, and they've

753
00:39:28,120 --> 00:39:30,400
Speaker 18: been trying to move more stuff internally to work on

754
00:39:30,800 --> 00:39:34,719
Speaker 18: training Rock for financial modeling and like boosting also like

755
00:39:34,760 --> 00:39:38,320
Speaker 18: the sales team, So they're trying to really prepare the

756
00:39:38,400 --> 00:39:41,200
Speaker 18: chadbot for that use case, but it's not really being

757
00:39:41,239 --> 00:39:41,680
Speaker 18: ready for.

758
00:39:41,640 --> 00:39:45,080
Speaker 3: Idiot also reporting that John Shulking stepping back as chief

759
00:39:45,080 --> 00:39:47,520
Speaker 3: revenue Officer of course a partner at Valor Now and

760
00:39:47,600 --> 00:39:49,640
Speaker 3: advisor recommon story Bloomers coming.

761
00:39:49,440 --> 00:39:50,600
Speaker 2: To Royal Thank you very much.

762
00:39:50,880 --> 00:39:53,800
Speaker 3: All right, coming up on the program, Alphabet is taking

763
00:39:53,800 --> 00:39:56,799
Speaker 3: the AI race the global bomb market. I'm going to

764
00:39:56,800 --> 00:40:07,480
Speaker 3: discuss that next. This is Bloomberg Tech Time now for

765
00:40:07,520 --> 00:40:10,360
Speaker 3: Talking Tech and first STARp. Hon High, also known as

766
00:40:10,440 --> 00:40:13,680
Speaker 3: fox Conn, reported a nineteen percent jump in quarterly profit,

767
00:40:14,000 --> 00:40:17,400
Speaker 3: says the US will gradually become the company's largest AI

768
00:40:17,480 --> 00:40:20,240
Speaker 3: server production hub. The company has become a key AI

769
00:40:20,280 --> 00:40:25,360
Speaker 3: hardware player by assembling servers that house Nvidia accelerators. Plus,

770
00:40:25,440 --> 00:40:28,720
Speaker 3: China's tech leaders are facing a reality check. Ali Barba

771
00:40:28,840 --> 00:40:31,879
Speaker 3: narrowly missed revenue targets this morning as e commerce war

772
00:40:31,960 --> 00:40:35,680
Speaker 3: was blunted its cloud search, while ten Cent reported its

773
00:40:35,680 --> 00:40:39,080
Speaker 3: slowest growth in over a year, and ad Tech is

774
00:40:39,120 --> 00:40:42,000
Speaker 3: eyeing a potential four billion dollar debut in Hong Kong.

775
00:40:42,239 --> 00:40:45,799
Speaker 3: The optical connectivity specialist is reportedly seeking to raise at

776
00:40:45,880 --> 00:40:49,400
Speaker 3: least five hundred million dollars or more at evaluation of

777
00:40:49,520 --> 00:40:51,280
Speaker 3: three to four billion dollars.

778
00:40:51,360 --> 00:40:54,120
Speaker 2: According to sources, Big story.

779
00:40:53,840 --> 00:40:56,520
Speaker 3: On the terminal Alphabet is taking the AI race to

780
00:40:56,560 --> 00:41:00,200
Speaker 3: the global bomb market. After a blockbuster seventeen billion million

781
00:41:00,200 --> 00:41:03,160
Speaker 3: dollars sale at home, the Google parents now tapping the

782
00:41:03,239 --> 00:41:07,200
Speaker 3: Japanese yen market for the first time. Bloomberg's Tasos Vossas

783
00:41:07,280 --> 00:41:10,400
Speaker 3: joins us to explain Big Text move into what is

784
00:41:10,480 --> 00:41:14,319
Speaker 3: international debt? Right, So that's the evolution here, looking at

785
00:41:14,400 --> 00:41:16,479
Speaker 3: international markets outside of its home.

786
00:41:16,880 --> 00:41:20,480
Speaker 19: Why well, at that point, you have to if you

787
00:41:20,840 --> 00:41:24,280
Speaker 19: look at issuans. This year, for example, non financial corporates

788
00:41:24,320 --> 00:41:27,439
Speaker 19: in the US, which is the deepest, biggest credit market

789
00:41:27,520 --> 00:41:30,320
Speaker 19: in the world, forty cent out of every dollar was

790
00:41:30,400 --> 00:41:33,440
Speaker 19: raised came from the tech sector, which is which is

791
00:41:33,520 --> 00:41:35,920
Speaker 19: rather large. So you have to think in order to

792
00:41:35,920 --> 00:41:38,239
Speaker 19: avoid saturating even the biggest market in the world, you

793
00:41:38,320 --> 00:41:40,759
Speaker 19: actually have to look at every corner out there. So

794
00:41:40,880 --> 00:41:45,200
Speaker 19: hyperscalers in particular Alphabet, but also Amazon have taken steps

795
00:41:45,239 --> 00:41:48,200
Speaker 19: to diversify that. So they they've tapped every every big

796
00:41:48,200 --> 00:41:51,480
Speaker 19: market they can imagine. So it's been Euros, pound, Sterling,

797
00:41:51,600 --> 00:41:54,360
Speaker 19: it's been Swiss Franks, and now we're looking at the

798
00:41:54,440 --> 00:41:57,319
Speaker 19: yen market, so it's pretty much a global race in

799
00:41:57,400 --> 00:42:00,239
Speaker 19: order to finance this massive cap expending the way we're

800
00:42:00,239 --> 00:42:01,440
Speaker 19: going to see in the next few years.

801
00:42:01,880 --> 00:42:04,000
Speaker 3: Right, and then in the eurobond market, we're talking about

802
00:42:04,040 --> 00:42:07,480
Speaker 3: the second biggest credit market. Why is it different this

803
00:42:07,560 --> 00:42:09,840
Speaker 3: time around TuS US? Like we've done a lot of

804
00:42:09,880 --> 00:42:13,080
Speaker 3: breaking news on this show in corporate bonds, is there

805
00:42:13,080 --> 00:42:13,799
Speaker 3: something new here?

806
00:42:15,320 --> 00:42:18,000
Speaker 19: There is actually, and we've had mega deals in the

807
00:42:18,000 --> 00:42:20,080
Speaker 19: past where you have tens of billions of dollars being

808
00:42:20,120 --> 00:42:22,840
Speaker 19: issued in a single day. The problem with well, the

809
00:42:22,880 --> 00:42:24,960
Speaker 19: difference with that is that that was a one off.

810
00:42:25,040 --> 00:42:26,520
Speaker 19: Usually it's on the back of M and A. You

811
00:42:26,560 --> 00:42:29,560
Speaker 19: have to raise massive amounts of cash or to do that.

812
00:42:29,640 --> 00:42:32,000
Speaker 19: But once you've done that, then you can just absorb

813
00:42:32,040 --> 00:42:34,439
Speaker 19: the company we've just bought. The difference here is that

814
00:42:34,520 --> 00:42:37,640
Speaker 19: because cap expending is going to be so large in

815
00:42:37,640 --> 00:42:40,080
Speaker 19: the next few years, hundreds of billions of dollars, you

816
00:42:40,160 --> 00:42:43,920
Speaker 19: have massive deal after massive deal, which is a conundrum

817
00:42:43,920 --> 00:42:46,520
Speaker 19: that investors are facing. They want to be involved in them.

818
00:42:46,960 --> 00:42:49,400
Speaker 19: The main issue is that in other massive deals is

819
00:42:49,480 --> 00:42:51,640
Speaker 19: just around the corner. So the previous one is going

820
00:42:51,680 --> 00:42:54,680
Speaker 19: to weekend in the back of that, so that that

821
00:42:55,360 --> 00:42:57,920
Speaker 19: trend of big deal after big deal is something that

822
00:42:57,920 --> 00:43:00,279
Speaker 19: we haven't seen before. Pretty much in there sure as

823
00:43:00,280 --> 00:43:04,400
Speaker 19: a gread market. Bloomberg's taslos fossos, Thank you very much.

824
00:43:04,640 --> 00:43:07,560
Speaker 19: Let's get back to Cisco before we leave today. Today's

825
00:43:07,560 --> 00:43:10,320
Speaker 19: big number nine billion dollars. That's how much the company

826
00:43:10,320 --> 00:43:14,040
Speaker 19: expects to get in orders from hyperscalers in calendar twenty six,

827
00:43:14,160 --> 00:43:17,560
Speaker 19: up from previous five billion dollar target. Suggest this company's

828
00:43:17,600 --> 00:43:21,799
Speaker 19: AI shift is showing a payoff, right Cisco, welcome to

829
00:43:21,840 --> 00:43:24,040
Speaker 19: the AI party. That's part of the story, and the

830
00:43:24,120 --> 00:43:27,040
Speaker 19: shares really reflecting that we're up fifteen percent, on track

831
00:43:27,080 --> 00:43:30,279
Speaker 19: for the best day for Cisco since twenty eleven. At

832
00:43:30,280 --> 00:43:32,920
Speaker 19: the open, seventeen percent gain put them on track for

833
00:43:32,960 --> 00:43:38,600
Speaker 19: their best day since two thousand and two. Networking routers, switches,

834
00:43:38,680 --> 00:43:43,000
Speaker 19: cables make those components the story again. Wonderful, That does

835
00:43:43,040 --> 00:43:46,960
Speaker 19: it for this edition of Bloomberg Tech, Standing by for

836
00:43:47,040 --> 00:43:49,680
Speaker 19: Cerebres to start trading, priced at one eighty five for

837
00:43:49,719 --> 00:43:53,160
Speaker 19: its IPO indicated to open three hundred and fifty dollars

838
00:43:53,320 --> 00:43:56,719
Speaker 19: per share. Check out the podcast, A stunning show to

839
00:43:56,800 --> 00:43:59,080
Speaker 19: recap Apple, Spotify, iHeart and

840
00:43:59,160 --> 00:44:01,080
Speaker 2: On Bloomberg, this is Bloomberg Tech