WEBVTT - Amazon Looks to Raise At Least $37 Billion with Bond Sale

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<v Speaker 1>Bloomberg Audio Studios, podcasts, radio news. Bloomberg Tech is alive

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<v Speaker 1>from coast to coast with Caroline Hide in New York

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<v Speaker 1>and ev Loow in San Francisco.

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<v Speaker 2>This is Bloomberg Tech coming up.

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<v Speaker 3>Amazon kicks off what is likely to be one of

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<v Speaker 3>the biggest corporate bond offerings ever.

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<v Speaker 2>In a bid to pay for the AI boom.

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<v Speaker 4>Plus, Google introduces AI agents across the Pentagon's workforce to

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<v Speaker 4>automate routine jobs. This is the Defense Department's fight with

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<v Speaker 4>anthropics drags.

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<v Speaker 3>On, and Hewlett Packard Enterprise projects sales topping estimates on

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<v Speaker 3>AI hardware demand. We'll break it all down with the CEO,

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<v Speaker 3>but now we break.

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<v Speaker 5>Down volatility in the market.

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<v Speaker 4>We once more focus in on the Middle East, the

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<v Speaker 4>conflict with Iran and the fact that it has been

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<v Speaker 4>upped in terms of aggressive force coming from the US

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<v Speaker 4>to Iran today, but also aggressive moves in oil markets.

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<v Speaker 5>Just drag down Brent.

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<v Speaker 4>Down ten percent, significant volatility in the oil contract, but

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<v Speaker 4>it means we're actually seeing some push higher in the

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<v Speaker 4>stock market, a regain on the NASAQ one hundred. In fact,

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<v Speaker 4>that a second straight day of games ed all of

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<v Speaker 4>this as we think about really the end goal and

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<v Speaker 4>whether this will be a short term or long term conflict.

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<v Speaker 3>I'm looking at the latest and what's been a wave

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<v Speaker 3>of AI related bond sales and it's Amazon. So this

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<v Speaker 3>is what Bloomberg's reporting, both US dollars denominated and Euro

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<v Speaker 3>denominated bonds in US eleven tranches of high grade the

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<v Speaker 3>longest duration I think twenty fifty six with a one

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<v Speaker 3>point five to five percent yield over treasuries.

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<v Speaker 2>But the goal is to raise up to forty.

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<v Speaker 3>Two billion dollars, maybe up to ten billion euros. And

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<v Speaker 3>we know the story, right, capital expenditures this year six

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<v Speaker 3>hundred and fifty billion dollars or so across the hyperscalers,

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<v Speaker 3>and many of them have looked to debt markets, looked

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<v Speaker 3>to raise money through bond saleales to finance that capex.

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<v Speaker 2>There's a lot to dig into here, there is, and.

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<v Speaker 4>We're going to continue the conversation. Therefore, Edward Robert Schiffman

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<v Speaker 4>and bretting Bag Intelligence, he's out with the reaction to

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<v Speaker 4>this morning, saying that the bond cell is quote likely

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<v Speaker 4>to draw a considerable demand despite a growing absolute debt

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<v Speaker 4>load that's poised to increase again next year as spending rises.

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<v Speaker 4>That the stock had been punished when they told us

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<v Speaker 4>that they were going to be spending up to two

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<v Speaker 4>hundred billion on capital expenditures.

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<v Speaker 5>But the bond market is going to lap this up.

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<v Speaker 6>It feels like, yeah, you know, My first thought was, Wow,

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<v Speaker 6>they must be sewing.

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<v Speaker 7>A lot of books.

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<v Speaker 6>My second thought is, this is so wildly bullish for

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<v Speaker 6>the credit markets and in particular for tech, impossibly the

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<v Speaker 6>worst potential macro environment. Bondholders are coming in saying we

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<v Speaker 6>want to own you. We want to own you in size,

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<v Speaker 6>and we're confident that your future growth plans are going

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<v Speaker 6>to play out.

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<v Speaker 5>And even though.

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<v Speaker 6>There's so much spending and we know more bonds are

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<v Speaker 6>likely to becoming, people are going to be lining up

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<v Speaker 6>for this deal.

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<v Speaker 3>I actually just misspoke at the board. I said twenty

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<v Speaker 3>fifty six, Actually twenty seventy six, the longest maturity that

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<v Speaker 3>Bloomberg's reporting Amazon's thinking about, the one that would yield

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<v Speaker 3>one point five five percent over treasuries. How does this

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<v Speaker 3>kind of stack up in the history of corporate debt markets,

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<v Speaker 3>recent and historic? Right, we talked a little bit about

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<v Speaker 3>what Alphabet's done most recently. Oracle is a slightly different

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<v Speaker 3>credit profile, but like a lot of focus on that too.

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<v Speaker 6>Well, this is going to be the biggest bond deal

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<v Speaker 6>of the year, it looks like by far, and I'll

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<v Speaker 6>tell you, I think people just need to get used

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<v Speaker 6>to this. These hyperscalers are effectively becoming serial issuers. The

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<v Speaker 6>one hundred billion dollar plus debt club is growing. So

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<v Speaker 6>not only do we have new current larger needs, but

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<v Speaker 6>just think about it, over the next handful of years,

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<v Speaker 6>as bonds mature, there's always going to be a constant

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<v Speaker 6>need to refinance and push out the curve. Amazon itself

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<v Speaker 6>is twenty billion dollars in debt maturing over the next

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<v Speaker 6>three years, so this is going to be a constant

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<v Speaker 6>and look for more of this action. Again, I think

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<v Speaker 6>bondholders can take huge advantage of this. The type of

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<v Speaker 6>concessions that are being offered here seem wildly wide to me.

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<v Speaker 6>I actually think the demand is going to be so

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<v Speaker 6>strong that they're going to come in dramatically, maybe twenty

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<v Speaker 6>thirty plus basis points, and.

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<v Speaker 5>They're tapping just every type of part of the market.

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<v Speaker 5>You've got like nineteen.

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<v Speaker 4>Different tranches, so different inspiration dates. Ultimately of when the

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<v Speaker 4>debt is going to becoming jew but also different currencies

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<v Speaker 4>as well. How are they managing to satiate all the

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<v Speaker 4>type of investor out there?

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<v Speaker 6>You know, we talked about this when Alphabet came that

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<v Speaker 6>they were doing a small tranches of Swiss francs and

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<v Speaker 6>British pounds and why they weren't tapping the Euro market.

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<v Speaker 6>You know, the r market is widely I think underinvested

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<v Speaker 6>in technology, and they're somewhat probably price agnostic. They're willing

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<v Speaker 6>to take down any Amazon bonds across the curve almost

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<v Speaker 6>at any price because they're so underweighted. So I think

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<v Speaker 6>there's a huge on tap market there that we're going

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<v Speaker 6>to see other companies come and grab as well.

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<v Speaker 3>That's the Bloomberg Intelligence react from Robert Schiffman. I would

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<v Speaker 3>say the details of Amazon's bond sale are according to

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<v Speaker 3>Bloomberg sources, and Bloomberg saying that the US side at

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<v Speaker 3>least mike price. Today a separate story, a court ruled

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<v Speaker 3>that Perplexity must stop using its Comet web browser agent

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<v Speaker 3>to make purchases on Amazon's marketplace. Amazon sued, accusing Perplexity

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<v Speaker 3>of computer fraud for not disclosing when Comet was shopping

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<v Speaker 3>for a user and refusing to stop when asked. The

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<v Speaker 3>order also bars access to password protected parts of Amazon

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<v Speaker 3>systems and requires destruction of Amazon data, with enforcement pause

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<v Speaker 3>for a week to allow for an appeal. Perplexity has

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<v Speaker 3>yet to respond to a messages seeking comment.

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<v Speaker 4>Cara, it's avas company. Then, of course it's about e

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<v Speaker 4>commerce and about cloud. Let's talk about Oracle now, because

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<v Speaker 4>it's about cloud and software and its earnings are after

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<v Speaker 4>the bell. It comes after recent Bloomberg reporting that Oracle

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<v Speaker 4>and OpenAI have ended plans to expand that flagship data

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<v Speaker 4>center project in Texas. While will investors be looking for

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<v Speaker 4>in the company's results, We want to talk it all

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<v Speaker 4>through with Gabrielle Borge's software sector analysts at Goldman Sachs Research.

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<v Speaker 4>How much of this is a test of Oracles all

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<v Speaker 4>bread and butter software or a test of how much

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<v Speaker 4>investors are willing to well stom at the capex of

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<v Speaker 4>getting into the cloud and furthering the AI focus.

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<v Speaker 8>Yeah, Hi, it's great to be back. Good morning. I

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<v Speaker 8>think you touched on it perfectly there where the capex

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<v Speaker 8>makes sense if you can justify the unit economics that

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<v Speaker 8>are attached to the AI infrastructure projects, and so Oracle's

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<v Speaker 8>given us a couple of nuggets in this regard. They've

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<v Speaker 8>taught us that they expect to be able to spend

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<v Speaker 8>less than one hundred billion in debt raised in order

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<v Speaker 8>to be able to fulfill north of five hundred billion

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<v Speaker 8>in cloud backlog that's now on their balance sheet. Those

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<v Speaker 8>are commitments from costomers for the next five six years.

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<v Speaker 8>They've also taught us that the gross margin on these

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<v Speaker 8>projects is thirty to forty percent over the lifetime of

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<v Speaker 8>a contract, so that's typically five to six years. And

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<v Speaker 8>so if you put those two data points together, whatever

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<v Speaker 8>incremental information we can get from the management team tonight

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<v Speaker 8>that helps make this less of a black box, I

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<v Speaker 8>think we'll go along way.

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<v Speaker 4>Because we are worried about turning cash flow negative, We

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<v Speaker 4>are worried about maybe some of the ability to drive

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<v Speaker 4>revenue growth to substantiate the capital expenditure spend. What do

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<v Speaker 4>you need to see in terms of growth and pointing

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<v Speaker 4>to growth because the stock is actually pretty cheap now.

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<v Speaker 8>Yeah, So when you actually break down the phases of

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<v Speaker 8>the different facilities coming online, so Abilene, for example in Texas,

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<v Speaker 8>that's a one point to big our capacity facility where

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<v Speaker 8>Oracle has already said that the four point five gigawats

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<v Speaker 8>that will be coming online to fulfill their existing commitments.

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<v Speaker 8>They already have all the leasing agreements for that already

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<v Speaker 8>signed and ready to go. What happens next is as

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<v Speaker 8>the revenue comes online, we expect to see is really

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<v Speaker 8>nice gross profit acceleration in Oracle's four co business that

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<v Speaker 8>includes the big part of OCI that's tied to some

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<v Speaker 8>of these contracts, that's Oracle Cloud. We've spect to see

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<v Speaker 8>that as we go through the year. And so what

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<v Speaker 8>we've noticed over the last three or four quarters with

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<v Speaker 8>our core is that it's less about the specific numbers

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<v Speaker 8>and some of the short term dynamics in the given

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<v Speaker 8>quarter and more about what they say about their ability

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<v Speaker 8>to fulfill some of these contracts over a longer time frame,

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<v Speaker 8>which is why just taking a step back, I do

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<v Speaker 8>think you'll see BREST profit acceleration and US as we'll

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<v Speaker 8>be looking for that as we go towards the end

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<v Speaker 8>of this year.

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<v Speaker 3>Gabriella, I hear you on that, but you know, the

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<v Speaker 3>streets expecting the infrastructure unit to grow almost eighty percent

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<v Speaker 3>in the quarter, you know what if they're off by

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<v Speaker 3>a few percentage points, because you know, in general that's

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<v Speaker 3>been the formula, right, a very high bar for tangible

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<v Speaker 3>AI related growth in those infrastructure divisions.

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<v Speaker 8>Yeah, I think you're making a really good point here,

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<v Speaker 8>because we have seen for a couple of quarters now

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<v Speaker 8>that the OCI estimate intra quarter can move around, and

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<v Speaker 8>part of that is the timing of any one piece

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<v Speaker 8>of facility coming online. I do think though, what we're

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<v Speaker 8>seeing from a land signal standpoint is still very strong.

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<v Speaker 8>And coming back to Abiline, Abiline has been rapping really

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<v Speaker 8>nice over the last three months. The one other thing

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<v Speaker 8>I'll say is ourcle stock does react to apros our

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<v Speaker 8>potential delays for example, so as we've gotten more headlines

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<v Speaker 8>out out of the new flow over the last two

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<v Speaker 8>three months now, I think expectations do move around. All

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<v Speaker 8>of which is to say what we've seen during software

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<v Speaker 8>earning season has got to have a clean print for

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<v Speaker 8>the stuff to work on the print, and so and

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<v Speaker 8>I hear you there, it's got to be a clean

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<v Speaker 8>print for the stock to work on the print.

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<v Speaker 3>What I reported with the team in the case of

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<v Speaker 3>Abilene was that simply Oracle and Crusoe decided not to

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<v Speaker 3>proceed from with an expansion from one point two gig

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<v Speaker 3>watts to two Google watts, and that Crusoe was negotiating

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<v Speaker 3>with Meta to come in and take that additional capacity,

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<v Speaker 3>which many of your colleagues on the cell side pointed

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<v Speaker 3>out might not have been reflected in RPO anyway. But

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<v Speaker 3>what the story does highlight, and you made the point

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<v Speaker 3>a moment ago on the four point five gigawatts agreed,

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<v Speaker 3>is concentration risk one customer, which is open AI.

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<v Speaker 2>Is that something you model for, Yeah, we.

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<v Speaker 8>Do actually in a couple of different ways. So we

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<v Speaker 8>take a discount to our open AI forecast and to

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<v Speaker 8>what ourcle has said their open AI backlog is to

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<v Speaker 8>account for dynamics like the one you're talking about, the

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<v Speaker 8>extreme customer concentration risk. The other thing I'll mention here though,

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<v Speaker 8>is Oracle will tell you that they can have fungibility

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<v Speaker 8>of CAPEX. What does that mean? That means you can

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<v Speaker 8>actually reconfigure a training cluster to be able to serve

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<v Speaker 8>inference use cases. It means you can reconfigure for one

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<v Speaker 8>customer to serve another customer, so there is some fungibility there.

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<v Speaker 8>What that means is that if AI demand remains strong

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<v Speaker 8>and that internalizes on enterprise AI option, which we've spoken

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<v Speaker 8>about before. Then someone should be able to come in

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<v Speaker 8>and pick up that capex in the event that it

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<v Speaker 8>needs to be moved around and it comes back to

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<v Speaker 8>the same air of fungibility.

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<v Speaker 3>Gary Ellavorg is Golm and Zach's research analyst looking ahead

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<v Speaker 3>to Oracle, which is after the bell.

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<v Speaker 2>Thank you very much.

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<v Speaker 3>Like coming up, we can to have the latest on

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<v Speaker 3>each expanding use of AI by the Pentagon.

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<v Speaker 2>That's next. This is Bloomberg Tech.

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<v Speaker 9>As President Trump declared yesterday, we're crushing the enemy in

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<v Speaker 9>an overwhelming display of technical skill and military force. We

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<v Speaker 9>will not relent until the enemy is totally and decisively defeated.

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<v Speaker 3>That was US Defense Secretary Pete Hegseef weighing in on

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<v Speaker 3>the war in Iran during a briefing. The Pentagon says

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<v Speaker 3>it's conducting the most intense day of attacks yet. This

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<v Speaker 3>is the Islamic Republic has been firing drones and missiles

0:11:44.000 --> 0:11:46.600
<v Speaker 3>at targets across the Middle East. In return, let's bring

0:11:46.679 --> 0:11:49.040
<v Speaker 3>in Bloomberg's Washington correspondent, Tyler kendo I saw a lot

0:11:49.080 --> 0:11:51.560
<v Speaker 3>of the headlines on the terminal this morning, for example,

0:11:51.600 --> 0:11:56.280
<v Speaker 3>around drone activity in the Gulf the UAE. We continue

0:11:56.320 --> 0:11:59.240
<v Speaker 3>to hear from this administration on or at least field

0:11:59.320 --> 0:12:01.240
<v Speaker 3>questions on the timeline for this war.

0:12:01.320 --> 0:12:02.440
<v Speaker 2>What's the latest we need to know?

0:12:03.960 --> 0:12:05.079
<v Speaker 8>Yeah, hey, and good morning.

0:12:05.120 --> 0:12:07.480
<v Speaker 10>Well, as you heard, their secretary Hexcess said that the

0:12:07.600 --> 0:12:11.040
<v Speaker 10>US will quote not relent until all of its objectives

0:12:11.080 --> 0:12:14.480
<v Speaker 10>are achieved. After yesterday, President Trump appeared to suggest that

0:12:14.520 --> 0:12:17.840
<v Speaker 10>the US was ahead of schedule when it comes to

0:12:18.440 --> 0:12:21.400
<v Speaker 10>maintaining its goals in the region. But then we heard

0:12:21.440 --> 0:12:23.920
<v Speaker 10>from Iran this morning and a new statement from the

0:12:23.920 --> 0:12:28.120
<v Speaker 10>country's parliament speaker saying that Iran is quote not at

0:12:28.160 --> 0:12:32.240
<v Speaker 10>all interested in a potential ceasefire deal, and the IRGC

0:12:32.559 --> 0:12:37.239
<v Speaker 10>released a statement overnight vowing to continue to block oil exports.

0:12:37.280 --> 0:12:37.400
<v Speaker 3>Now.

0:12:37.400 --> 0:12:40.480
<v Speaker 10>President Trump yesterday had threatened to widen the list of

0:12:40.679 --> 0:12:45.199
<v Speaker 10>US targets to electricity infrastructure if attacks in the Strait

0:12:45.240 --> 0:12:48.720
<v Speaker 10>of her moves and disruptions do continue. I will point

0:12:48.720 --> 0:12:51.520
<v Speaker 10>out that the President reiterated that he is prepared to

0:12:51.559 --> 0:12:54.880
<v Speaker 10>send a naval escort into the Strait to help those

0:12:54.920 --> 0:12:57.760
<v Speaker 10>tankers through. But when the Joint chiefs of Staffed Chair

0:12:57.880 --> 0:13:00.520
<v Speaker 10>Dan Kane was asked about this earlier this morning. It

0:13:00.559 --> 0:13:02.959
<v Speaker 10>does not appear that any of those plans have been

0:13:02.960 --> 0:13:06.640
<v Speaker 10>put into motion. Bloomberg News is also reporting that electronic

0:13:06.679 --> 0:13:10.000
<v Speaker 10>warfare is now jamming signals in the Critical Waterway, which

0:13:10.040 --> 0:13:13.439
<v Speaker 10>at this point really does remain effectively closed, and in Caroline.

0:13:13.440 --> 0:13:15.200
<v Speaker 10>Within the last hour, we got the headline that G

0:13:15.320 --> 0:13:18.760
<v Speaker 10>seven nations are now asking the International Energy Agency to

0:13:18.800 --> 0:13:22.679
<v Speaker 10>prepare scenarios for the potential release of emergency stockpiles as

0:13:22.720 --> 0:13:25.679
<v Speaker 10>these oil flows continue to be impacted in the region.

0:13:25.720 --> 0:13:29.640
<v Speaker 4>And the oil market certainly moves and despite the newsflow,

0:13:29.720 --> 0:13:33.160
<v Speaker 4>Tyler Kendall, we so appreciate it. Let's stick with Defense

0:13:33.280 --> 0:13:35.960
<v Speaker 4>News because Bloomberg has learned that the Pentagon plans to

0:13:36.040 --> 0:13:39.600
<v Speaker 4>add Google's AI agents to handle unclassified work and as

0:13:39.600 --> 0:13:42.079
<v Speaker 4>in talks to bring those tools to the classified and

0:13:42.200 --> 0:13:45.720
<v Speaker 4>top secret cloud. Bloomber's Katrina Manson has been importing on

0:13:45.760 --> 0:13:47.839
<v Speaker 4>this and in fact continues to report at the very

0:13:47.920 --> 0:13:51.920
<v Speaker 4>edge of AI adoption within the Pentagon. Look, what is

0:13:52.000 --> 0:13:54.040
<v Speaker 4>Emil Michael talking about in terms of Google.

0:13:54.120 --> 0:13:55.199
<v Speaker 5>Is this because they're having to.

0:13:55.120 --> 0:13:58.360
<v Speaker 11>Force out anthropic This I think is fair to see

0:13:58.360 --> 0:14:02.480
<v Speaker 11>as separate where Emil Michael came in in this senior

0:14:02.559 --> 0:14:05.400
<v Speaker 11>role very focused on AI. Back in August, he told

0:14:05.440 --> 0:14:07.800
<v Speaker 11>me he was shocked that the Pentagon had adopted so

0:14:07.920 --> 0:14:12.120
<v Speaker 11>few AI tools. It's brought in chatbots, that's thanks to Gemini.

0:14:12.200 --> 0:14:14.520
<v Speaker 11>It's had those for the last three months. One point

0:14:14.520 --> 0:14:17.400
<v Speaker 11>two million people in the Pentagon have used those or

0:14:17.400 --> 0:14:21.160
<v Speaker 11>in the Defense Department writ large. Now they're adding agents,

0:14:21.200 --> 0:14:24.160
<v Speaker 11>so that's going to automate some tasks that corporations, of

0:14:24.160 --> 0:14:25.960
<v Speaker 11>course across the country are already trying.

0:14:26.880 --> 0:14:27.600
<v Speaker 2>But it is.

0:14:27.520 --> 0:14:31.200
<v Speaker 11>Interesting timing because at this very moment they're bringing Gemini

0:14:31.360 --> 0:14:35.880
<v Speaker 11>agents onto unclassified networks and really quite pleased that they

0:14:35.920 --> 0:14:37.840
<v Speaker 11>have this partner in Google at a time that clearly

0:14:37.920 --> 0:14:39.400
<v Speaker 11>Anthropic has been cut.

0:14:40.640 --> 0:14:42.880
<v Speaker 3>Twenty four hours ago on this program, we broke the

0:14:42.920 --> 0:14:47.960
<v Speaker 3>news of Anthropic suit against the Defense Department. Late yesterday

0:14:48.000 --> 0:14:52.160
<v Speaker 3>evening we got more of a detailed response. What is

0:14:52.200 --> 0:14:56.280
<v Speaker 3>the Pentagon's official position and what does it see in

0:14:56.320 --> 0:14:57.880
<v Speaker 3>this suit from Anthropic against it.

0:14:58.480 --> 0:15:03.160
<v Speaker 11>Emil Michael told me that he was expecting this. He

0:15:03.240 --> 0:15:05.800
<v Speaker 11>doesn't think that bringing this to the courts is a

0:15:05.800 --> 0:15:08.920
<v Speaker 11>way to resolve this problem, and he said, call me

0:15:09.120 --> 0:15:09.720
<v Speaker 11>quite simply.

0:15:10.080 --> 0:15:10.760
<v Speaker 5>We're moving on.

0:15:11.120 --> 0:15:13.720
<v Speaker 11>So I do think that in this news today the

0:15:13.760 --> 0:15:17.040
<v Speaker 11>focus on Google. Of course, they've recently struck deals with

0:15:17.480 --> 0:15:20.680
<v Speaker 11>Xai and Open Ai to start operating on the classified cloud.

0:15:20.920 --> 0:15:24.000
<v Speaker 11>The Pentagon is really saying, we have three partners now

0:15:24.240 --> 0:15:26.600
<v Speaker 11>that we feel comfortable with and we are not expecting

0:15:26.800 --> 0:15:28.160
<v Speaker 11>to go back to anthropic.

0:15:28.360 --> 0:15:30.000
<v Speaker 4>Can you give us the context of just how much

0:15:30.040 --> 0:15:32.400
<v Speaker 4>AI is playing a role within the very here and

0:15:32.480 --> 0:15:35.440
<v Speaker 4>now geopolitical issue of Iran and the conflict there.

0:15:36.160 --> 0:15:39.520
<v Speaker 11>From our reporting, we understand the scent the central US

0:15:39.520 --> 0:15:45.520
<v Speaker 11>central commander conducting the operations in Iran is relying on

0:15:45.560 --> 0:15:48.800
<v Speaker 11>a variety of AI tools, and from separate reporting we

0:15:48.880 --> 0:15:51.360
<v Speaker 11>understand that means mayben smart system. This comes out of

0:15:51.440 --> 0:15:54.520
<v Speaker 11>Project Maven, an AI effort started in twenty seventeen.

0:15:54.720 --> 0:15:56.760
<v Speaker 5>You have a book coming out on I Do Yes,

0:15:56.800 --> 0:15:57.560
<v Speaker 5>I Do Yeah.

0:15:57.360 --> 0:16:02.240
<v Speaker 11>Thanks, and that helps narrow down time targets. Of course,

0:16:02.240 --> 0:16:05.040
<v Speaker 11>SKom is hitting I think they've hit five thousand targets

0:16:05.080 --> 0:16:08.120
<v Speaker 11>in ten days now, so an extraordinary number for the

0:16:08.200 --> 0:16:10.680
<v Speaker 11>US to be churning through. And at the same time

0:16:11.000 --> 0:16:15.120
<v Speaker 11>AI is helping with processors that enable fast movement.

0:16:17.120 --> 0:16:20.080
<v Speaker 3>Bloomers Katrina Manson with the latest reporting deep on what

0:16:20.360 --> 0:16:21.760
<v Speaker 3>the Pentagon is doing with AI.

0:16:21.840 --> 0:16:22.680
<v Speaker 2>Thank you very much.

0:16:22.720 --> 0:16:26.320
<v Speaker 3>Now coming up, AI start up Legora raises five hundred

0:16:26.360 --> 0:16:30.160
<v Speaker 3>and fifty million dollars, boosting its valuation to five point

0:16:30.200 --> 0:16:34.040
<v Speaker 3>five to five billion. We speak with the CEO, Max Unistrand. Next,

0:16:34.280 --> 0:16:35.280
<v Speaker 3>this is Bloomberg tech.

0:16:43.240 --> 0:16:46.320
<v Speaker 4>Logora, an AI platform built for lawyers, has just raised

0:16:46.360 --> 0:16:48.200
<v Speaker 4>a massive five hundred and fifty million dollars in a

0:16:48.240 --> 0:16:51.480
<v Speaker 4>series defunding round, pushing its valuation to an excess of

0:16:51.480 --> 0:16:53.520
<v Speaker 4>five and a half billion. Joining us now to talk

0:16:53.560 --> 0:16:55.440
<v Speaker 4>about the raise, the company's growth in the future of

0:16:55.480 --> 0:16:59.200
<v Speaker 4>AI and laws Lagora CEO Max Unistrand, Max, this is

0:16:59.240 --> 0:17:02.160
<v Speaker 4>only a few months after you just raised your previous series.

0:17:02.240 --> 0:17:03.560
<v Speaker 4>I mean, what are you going to be doing this

0:17:03.720 --> 0:17:04.399
<v Speaker 4>using this money for?

0:17:04.800 --> 0:17:08.119
<v Speaker 12>We are investing in the United States. We landed in

0:17:08.160 --> 0:17:10.560
<v Speaker 12>New York a year ago. This was the first week

0:17:10.600 --> 0:17:12.960
<v Speaker 12>in twenty twenty five New York Legal Week when Lagoire

0:17:13.080 --> 0:17:15.680
<v Speaker 12>launched in the United States. Now we've opened in New York,

0:17:15.720 --> 0:17:19.199
<v Speaker 12>We've opened in Denver, Chicago, Houston. We're investing in the

0:17:19.280 --> 0:17:24.040
<v Speaker 12>product and infrastructure, in customer support teams to support the

0:17:24.840 --> 0:17:28.399
<v Speaker 12>astronomic demand that we're seeing from the US, and that is.

0:17:28.400 --> 0:17:30.359
<v Speaker 4>What the vcs are responding to here, the fact that

0:17:30.359 --> 0:17:33.640
<v Speaker 4>you are signing more and more legal professionals to come

0:17:33.640 --> 0:17:36.840
<v Speaker 4>and join your platform. But yesterday we just had Harvey

0:17:36.880 --> 0:17:40.159
<v Speaker 4>AI on and what has it that they're a competitive

0:17:40.880 --> 0:17:43.840
<v Speaker 4>force out there? How are you seeing your space in

0:17:43.880 --> 0:17:46.720
<v Speaker 4>the world? How are you unique versus a Harvey for example.

0:17:46.920 --> 0:17:49.080
<v Speaker 12>So I think legal tech has for a long time

0:17:49.200 --> 0:17:51.920
<v Speaker 12>been sort of stuck in the pre digital era.

0:17:52.400 --> 0:17:54.920
<v Speaker 2>With llms. We're seeing a wave of.

0:17:54.920 --> 0:17:59.360
<v Speaker 12>Companies come and automated tasks, build new systems, and it's

0:17:59.359 --> 0:18:02.159
<v Speaker 12>a Renner songs for the industry. So there's lots of

0:18:02.160 --> 0:18:05.200
<v Speaker 12>companies going very quickly. There's a lot of green field opportunity.

0:18:05.520 --> 0:18:09.040
<v Speaker 12>We started in Stockholm, Sweden, just three years ago, and

0:18:09.119 --> 0:18:12.040
<v Speaker 12>now we've landed here. We're expanding with big law firms,

0:18:12.080 --> 0:18:14.960
<v Speaker 12>with big enterprises, and I think the reality is that

0:18:15.000 --> 0:18:18.240
<v Speaker 12>this market has only done zero to one. Now we

0:18:18.280 --> 0:18:20.480
<v Speaker 12>are on the journey of one to ten and ten

0:18:20.560 --> 0:18:23.080
<v Speaker 12>to one hundred, and there's so much left to build

0:18:23.280 --> 0:18:26.280
<v Speaker 12>and that's our opportunity and our challenge.

0:18:26.800 --> 0:18:27.040
<v Speaker 2>Max.

0:18:27.080 --> 0:18:31.160
<v Speaker 3>What's interesting about what you just outlined is different jurisdictions. Right,

0:18:31.200 --> 0:18:35.080
<v Speaker 3>You're talking about American law, Nordic law, European law.

0:18:35.600 --> 0:18:37.480
<v Speaker 2>Take us inside building.

0:18:38.600 --> 0:18:42.480
<v Speaker 3>Legora and the necessary data sets to be able to

0:18:42.640 --> 0:18:46.240
<v Speaker 3>service the legal profession in those different markets where laws

0:18:47.520 --> 0:18:49.040
<v Speaker 3>and fightings are completely different.

0:18:49.359 --> 0:18:52.200
<v Speaker 12>So in order to build systems and agents that perform

0:18:52.359 --> 0:18:54.919
<v Speaker 12>real work, there's really two different types of data that

0:18:55.000 --> 0:18:56.439
<v Speaker 12>you need to work with. As you said, it's the

0:18:56.520 --> 0:19:00.280
<v Speaker 12>local jurisdictional data, the case law, the legislation, and then

0:19:00.280 --> 0:19:03.360
<v Speaker 12>it's the firms and the enterprises own data. And it's

0:19:03.400 --> 0:19:06.040
<v Speaker 12>the combination of the two within a platform like Ligora

0:19:06.240 --> 0:19:09.880
<v Speaker 12>that becomes incredibly valuable because I think these systems used

0:19:09.880 --> 0:19:12.080
<v Speaker 12>to kind of feel like co pilots. You were working

0:19:12.119 --> 0:19:15.119
<v Speaker 12>together with them on small tasks, but now you're actually

0:19:15.160 --> 0:19:19.840
<v Speaker 12>able to offload entire end to end I mean agentic workflows,

0:19:19.880 --> 0:19:22.280
<v Speaker 12>and the systems are performing and to end work for you.

0:19:22.680 --> 0:19:24.040
<v Speaker 2>So when we started.

0:19:23.760 --> 0:19:26.680
<v Speaker 12>Out in Stockholm, Sweden, I mean that market is smaller

0:19:26.720 --> 0:19:28.680
<v Speaker 12>than one of the big law firms here in New York.

0:19:28.840 --> 0:19:32.359
<v Speaker 12>So we really practice that muscle. And now that we're here,

0:19:32.600 --> 0:19:35.760
<v Speaker 12>I'm an engineer, we really lid with a product.

0:19:36.480 --> 0:19:39.160
<v Speaker 3>Max I suffered through law school and I'm the son

0:19:39.200 --> 0:19:41.679
<v Speaker 3>of two lawyers, and I brought that up yesterday, so

0:19:41.680 --> 0:19:45.399
<v Speaker 3>I'll be consistent. And I know from that context the

0:19:45.560 --> 0:19:50.040
<v Speaker 3>lawyers build by the minute, sometimes scanning barcodes for five

0:19:50.040 --> 0:19:52.879
<v Speaker 3>minutes of work fifteen minutes work. How do you charge

0:19:53.240 --> 0:19:56.840
<v Speaker 3>and structure your revenues for the platform?

0:19:56.960 --> 0:19:59.159
<v Speaker 2>So which charge on a set basis? Today?

0:19:59.480 --> 0:20:01.639
<v Speaker 12>I think that that is the easiest way for some

0:20:01.680 --> 0:20:04.800
<v Speaker 12>of these customers to buy. But as we move towards

0:20:04.840 --> 0:20:08.040
<v Speaker 12>this world where leguore is performing more end to end work,

0:20:08.359 --> 0:20:11.480
<v Speaker 12>I think both consumption and outcome based pricing models will

0:20:11.480 --> 0:20:13.920
<v Speaker 12>make a lot of sense for our clients and also

0:20:14.160 --> 0:20:16.720
<v Speaker 12>in turn their clients. Right the way that law firms

0:20:16.720 --> 0:20:20.639
<v Speaker 12>are charging for tasks that AI can perform together with

0:20:20.720 --> 0:20:24.159
<v Speaker 12>them will have to move from a buildable hour model

0:20:24.440 --> 0:20:26.720
<v Speaker 12>to more of a fix thier outcome based system.

0:20:27.160 --> 0:20:30.359
<v Speaker 4>Can you just set the scene here, because you're building

0:20:30.800 --> 0:20:34.280
<v Speaker 4>upon in many ways the innovations of Anthropic, but Anthropic

0:20:34.359 --> 0:20:37.240
<v Speaker 4>is also doing its own claw plug in for law.

0:20:37.880 --> 0:20:43.440
<v Speaker 4>How does this competitive environment unfold for the future businesses

0:20:43.480 --> 0:20:45.399
<v Speaker 4>you want to sign on? How do they decide between

0:20:45.600 --> 0:20:49.240
<v Speaker 4>you and Thropic harvey what they already have as point solutions?

0:20:49.440 --> 0:20:49.600
<v Speaker 7>Yeah?

0:20:49.920 --> 0:20:52.720
<v Speaker 12>So I mean Legorre wouldn't exist without the llms. We

0:20:52.720 --> 0:20:55.639
<v Speaker 12>were founded in late spring of twenty twenty three off

0:20:55.720 --> 0:20:57.960
<v Speaker 12>the back of the release of GPT three point five.

0:20:58.080 --> 0:21:00.240
<v Speaker 12>That was the first time the models became good enough

0:21:00.280 --> 0:21:03.199
<v Speaker 12>to build any real software. In the beginning, there were

0:21:03.320 --> 0:21:05.639
<v Speaker 12>so many issues around the models. You had to reduce

0:21:05.680 --> 0:21:07.960
<v Speaker 12>the hallucinations, you had to guardrail them, We had to

0:21:07.960 --> 0:21:10.959
<v Speaker 12>build a lot of systems around them. Today we are

0:21:11.080 --> 0:21:14.520
<v Speaker 12>very focused on bringing the capabilities of those models into

0:21:14.520 --> 0:21:17.760
<v Speaker 12>an enterprise legal setting. So when we work with the

0:21:17.840 --> 0:21:21.359
<v Speaker 12>law firm like White and Case or Clearly Gottlib, they

0:21:21.359 --> 0:21:25.520
<v Speaker 12>are deploying Laguera and they're turning over, you know, billions

0:21:25.520 --> 0:21:30.560
<v Speaker 12>of dollars using our system. And the interesting thing for

0:21:30.680 --> 0:21:33.720
<v Speaker 12>us is every quarter the ground shakes a little bit.

0:21:34.400 --> 0:21:37.200
<v Speaker 12>The new models are capable of doing new things, which

0:21:37.280 --> 0:21:41.280
<v Speaker 12>needs to be reflected in our product roadmap. We cannot

0:21:41.320 --> 0:21:44.880
<v Speaker 12>plan for a year ahead because three months, in six

0:21:44.920 --> 0:21:47.639
<v Speaker 12>months the capabilities might have changed, so our product has

0:21:47.680 --> 0:21:48.159
<v Speaker 12>to change.

0:21:48.200 --> 0:21:48.560
<v Speaker 2>Max.

0:21:49.040 --> 0:21:51.119
<v Speaker 3>We just had twenty seconds. But I think what Caroline's

0:21:51.160 --> 0:21:53.400
<v Speaker 3>question is, what is your modes? Do you have a mote?

0:21:53.840 --> 0:21:54.720
<v Speaker 2>I think we have a real mold.

0:21:54.840 --> 0:21:57.240
<v Speaker 12>Of course, I mean the way that we're deployed within

0:21:57.280 --> 0:22:00.159
<v Speaker 12>this enterprise is connected to their data, the way we've

0:22:00.200 --> 0:22:03.760
<v Speaker 12>set up the permissions, whether we work with delivering work.

0:22:04.000 --> 0:22:07.240
<v Speaker 12>For instance, Deba Boys just launched their client portal on

0:22:07.280 --> 0:22:09.680
<v Speaker 12>the World where they are connecting their work to their

0:22:09.680 --> 0:22:12.520
<v Speaker 12>external clients. So there's a real network effect rates in

0:22:12.520 --> 0:22:13.200
<v Speaker 12>our product tool.

0:22:14.280 --> 0:22:16.720
<v Speaker 3>Max and Strand of Legora. Thank you very much for

0:22:16.760 --> 0:22:19.400
<v Speaker 3>your time here on Bloomberg Tech. Now coming up, Apple's

0:22:19.480 --> 0:22:22.119
<v Speaker 3>latest product is delayed because it waits the debut of

0:22:22.160 --> 0:22:25.000
<v Speaker 3>its new AI seri. We have more on that Bloomberg

0:22:25.080 --> 0:22:27.920
<v Speaker 3>reporting and some supply chain coverage as well with what's

0:22:27.960 --> 0:22:31.120
<v Speaker 3>going on with Apple. It's halftime. Don't go anywhere, We'll

0:22:31.160 --> 0:22:31.800
<v Speaker 3>be right back.

0:22:32.119 --> 0:22:42.800
<v Speaker 13>This is Bloomberg Tech. Welcome back to Bloomberg Tech.

0:22:42.880 --> 0:22:47.120
<v Speaker 3>Technology stocks actually in particular now pushing higher having seen

0:22:47.160 --> 0:22:49.399
<v Speaker 3>then as that one hundred lower earlier in the session.

0:22:49.400 --> 0:22:52.000
<v Speaker 3>Actually that chart tells the story pretty well, but a

0:22:52.040 --> 0:22:55.159
<v Speaker 3>lot of the story is still what's happening with the

0:22:55.200 --> 0:22:58.760
<v Speaker 3>war in Iran, the movement in oil, general risk sentiment

0:22:59.119 --> 0:23:03.000
<v Speaker 3>around geo politics. After the bell we get Oracle earnings,

0:23:03.040 --> 0:23:04.879
<v Speaker 3>and so once again we kind of focused on the

0:23:04.920 --> 0:23:09.200
<v Speaker 3>AI story. And capital expenditures. Amazon is up by almost

0:23:09.240 --> 0:23:11.280
<v Speaker 3>half percentage point. The big story of the day that

0:23:11.320 --> 0:23:14.159
<v Speaker 3>we hit earlier in the program is them looking at

0:23:14.200 --> 0:23:18.399
<v Speaker 3>a bond sale US dollar denominated and Euro denominated of

0:23:18.480 --> 0:23:20.399
<v Speaker 3>up to forty two billion dollars. And we had the

0:23:20.440 --> 0:23:23.640
<v Speaker 3>details on the program earlier. Oracles treading water of course

0:23:23.680 --> 0:23:26.480
<v Speaker 3>ahead of its print later today. But that is the

0:23:26.520 --> 0:23:31.000
<v Speaker 3>AI story once again, the credit conditions, the capital expenditures,

0:23:31.040 --> 0:23:32.919
<v Speaker 3>and whether this build out is intact Carrott.

0:23:33.119 --> 0:23:35.439
<v Speaker 4>We've got plenty more on the AI story and supply

0:23:35.520 --> 0:23:38.680
<v Speaker 4>chain stories now because Apple's manufacturing pivot to India and

0:23:38.680 --> 0:23:41.919
<v Speaker 4>away from China is picking up momentum. I've phoned production

0:23:42.080 --> 0:23:45.080
<v Speaker 4>in the country SAG fifty twenty five and now accounts

0:23:45.240 --> 0:23:46.880
<v Speaker 4>roughly a quarter of all.

0:23:46.760 --> 0:23:48.399
<v Speaker 5>iPhones made globally. For more.

0:23:48.480 --> 0:23:51.520
<v Speaker 4>Blomberg's Consumer Tech and Apple Managing editor Mark German joins

0:23:51.560 --> 0:23:54.120
<v Speaker 4>us now, and Mark, let's start with the supply chain

0:23:54.160 --> 0:23:56.840
<v Speaker 4>element of things. They've done this swiftly and effectively.

0:24:00.040 --> 0:24:02.440
<v Speaker 14>Yeah, our colleagues in India reporting that now about one

0:24:02.480 --> 0:24:06.080
<v Speaker 14>in four iPhones are produced in India. This is a

0:24:06.080 --> 0:24:08.679
<v Speaker 14>bit of an acceleration. About a year ago it was

0:24:08.800 --> 0:24:12.560
<v Speaker 14>one in five iPhones and a lot of the phone

0:24:12.600 --> 0:24:17.480
<v Speaker 14>production in India. That pivot happened because of tariffs about

0:24:17.480 --> 0:24:19.639
<v Speaker 14>a year ago. Apple looking for ways to produce the

0:24:19.680 --> 0:24:23.119
<v Speaker 14>phones without that potential tariff hit for devices built in

0:24:23.240 --> 0:24:25.080
<v Speaker 14>China and then imported.

0:24:26.960 --> 0:24:28.240
<v Speaker 2>Into the United States.

0:24:28.840 --> 0:24:30.840
<v Speaker 14>And they're going to continue doing more in India. They've

0:24:30.880 --> 0:24:35.400
<v Speaker 14>got AirPod development happening there at some point, more accessory

0:24:35.400 --> 0:24:39.240
<v Speaker 14>development happening there, more underline component development happening there. So

0:24:39.480 --> 0:24:42.480
<v Speaker 14>India not only big for Apple in terms of growth

0:24:42.600 --> 0:24:46.040
<v Speaker 14>in retail, but also for underlying manufacturing, not only in

0:24:46.040 --> 0:24:48.359
<v Speaker 14>India but in other parts of the world as well.

0:24:49.920 --> 0:24:52.080
<v Speaker 3>The other piece of reporting you have out this morning,

0:24:52.160 --> 0:24:56.119
<v Speaker 3>Mark is about the Apple Smart Home Display. Now in

0:24:56.160 --> 0:24:59.760
<v Speaker 3>my house, I right now have a lot of Amazon

0:24:59.760 --> 0:25:03.000
<v Speaker 3>ex devices, and so my understanding is that the Apples

0:25:03.040 --> 0:25:07.920
<v Speaker 3>Smart Home Display is like most akin to Amazon's Echo Show.

0:25:09.040 --> 0:25:12.320
<v Speaker 3>What are you learning? Why delayed? What's behind it?

0:25:15.800 --> 0:25:18.960
<v Speaker 14>Yeah, this device very much based on the new SERI

0:25:19.040 --> 0:25:21.160
<v Speaker 14>and the new AI features Apple has been working on.

0:25:21.800 --> 0:25:24.320
<v Speaker 14>Those features have yet to come to market, those continue

0:25:24.320 --> 0:25:26.879
<v Speaker 14>to be delayed, and as those features get delayed, the

0:25:26.920 --> 0:25:29.680
<v Speaker 14>hardware gets delayed. Because, as you know, Apple's very much

0:25:29.720 --> 0:25:33.359
<v Speaker 14>a hardware and software and services integrated company. It's all

0:25:33.600 --> 0:25:36.240
<v Speaker 14>one kit. It all comes together, so if one piece

0:25:36.280 --> 0:25:39.040
<v Speaker 14>is not working, you can't release the entire thing. It's

0:25:39.080 --> 0:25:41.120
<v Speaker 14>a pretty nifty device. You can walk up to it

0:25:41.440 --> 0:25:42.920
<v Speaker 14>and it can know who you are and give you

0:25:43.000 --> 0:25:46.440
<v Speaker 14>personalized content. And that very much relies on those new

0:25:46.520 --> 0:25:48.880
<v Speaker 14>serie features that the company announced a couple of years ago.

0:25:49.119 --> 0:25:50.879
<v Speaker 14>They're now aiming to roll them out before the end

0:25:50.920 --> 0:25:53.240
<v Speaker 14>of the year. And so this device, instead of launching

0:25:53.240 --> 0:25:55.359
<v Speaker 14>this month, likely to launch around September.

0:25:56.800 --> 0:25:59.560
<v Speaker 3>The famous Mark German and all things Apple, the Apple summary,

0:25:59.600 --> 0:26:02.200
<v Speaker 3>Thank you very much. There's a lot more news out there, Carrot.

0:26:02.280 --> 0:26:04.240
<v Speaker 4>There is ed and it's time now for talking tech

0:26:04.280 --> 0:26:07.040
<v Speaker 4>and first st up by d is exploring options to

0:26:07.200 --> 0:26:10.200
<v Speaker 4>enter the world of F one racing. According to sources,

0:26:10.200 --> 0:26:12.560
<v Speaker 4>it's a bid to boost the ev makers global appeal.

0:26:12.920 --> 0:26:14.800
<v Speaker 4>Now the move would mark a rare attempt by a

0:26:14.880 --> 0:26:18.120
<v Speaker 4>Chinese manufacturer to take on a sport dominated by European

0:26:18.119 --> 0:26:18.919
<v Speaker 4>and US teams.

0:26:19.359 --> 0:26:21.440
<v Speaker 5>Plus China's enthusiasm.

0:26:20.840 --> 0:26:23.639
<v Speaker 4>For all things open, Claw is igniting a stock rally

0:26:23.760 --> 0:26:26.480
<v Speaker 4>among local tech firms moving swiftly to embrace the open

0:26:26.480 --> 0:26:29.200
<v Speaker 4>source AI program, and I remember Openklaw is an agent

0:26:29.280 --> 0:26:33.480
<v Speaker 4>that leverages llms including anthropics Claude to perform daily functions

0:26:33.560 --> 0:26:37.440
<v Speaker 4>and the tool has garnered a cult like status in China.

0:26:37.680 --> 0:26:41.440
<v Speaker 4>And Polymarket is enlisting firms including Pan Andeer to help

0:26:41.480 --> 0:26:45.480
<v Speaker 4>police its force contracts. This is a prediction market faces

0:26:45.520 --> 0:26:48.440
<v Speaker 4>really intense scrutiny over inside of training. It's all according

0:26:48.440 --> 0:26:50.439
<v Speaker 4>to the sources, who say that the firms will prevent

0:26:50.600 --> 0:26:54.560
<v Speaker 4>and report suspicious activity with a monitoring system. The Polymarket

0:26:54.640 --> 0:26:55.440
<v Speaker 4>is building.

0:26:55.080 --> 0:26:59.000
<v Speaker 3>Out ed Okay, coming up, a three month old startup

0:26:59.040 --> 0:27:02.760
<v Speaker 3>founded by AI pioneer Yan Lacoon has raised over a

0:27:02.840 --> 0:27:05.720
<v Speaker 3>billion dollars in seed funding. I'll tell you about the

0:27:05.720 --> 0:27:10.680
<v Speaker 3>company called Advanced Machine Intelligence as next. This is Bloomberg Tech,

0:27:19.560 --> 0:27:22.560
<v Speaker 3>a startup founded by French AI pioneer Yan Lacun has

0:27:22.640 --> 0:27:25.720
<v Speaker 3>raised over a billion dollars in its initial funding round.

0:27:25.720 --> 0:27:29.960
<v Speaker 3>Advanced Machine Intelligence or AMI, is focused on building world

0:27:30.040 --> 0:27:33.320
<v Speaker 3>models that use visual and spatial data. Bloomberg's venture reporter

0:27:33.600 --> 0:27:37.119
<v Speaker 3>Natasha Mascarinus broke the story and joins us, Now the

0:27:37.200 --> 0:27:40.560
<v Speaker 3>Internet is kind of reacted by another one and what

0:27:40.680 --> 0:27:42.280
<v Speaker 3>is it that they do? But you know, there's a

0:27:42.400 --> 0:27:46.080
<v Speaker 3>history with Yandlercun and his work with Meta in particular.

0:27:46.280 --> 0:27:48.520
<v Speaker 3>Let's start with the vision for AMI. What is it

0:27:48.560 --> 0:27:50.040
<v Speaker 3>they're seeking to break through on?

0:27:50.400 --> 0:27:53.240
<v Speaker 15>Sure? I mean Yan Lacoon has been a long critic

0:27:53.320 --> 0:27:57.040
<v Speaker 15>of LM's being the best way to advance AI. So

0:27:57.240 --> 0:28:01.400
<v Speaker 15>a ME is a new company that'socused on world models.

0:28:02.280 --> 0:28:04.800
<v Speaker 15>The idea is that they are going to be able

0:28:04.800 --> 0:28:09.960
<v Speaker 15>to integrate with enterprises like robotics companies or car manufacturers

0:28:10.080 --> 0:28:12.440
<v Speaker 15>and help build AI that can operate in the real

0:28:12.440 --> 0:28:17.800
<v Speaker 15>world versus being something that consumers everyday. Consumers interact with

0:28:18.359 --> 0:28:20.960
<v Speaker 15>via chatbots, and so let's focus on text and think

0:28:21.040 --> 0:28:25.600
<v Speaker 15>more around spatial data, visual data and trying to operate

0:28:25.640 --> 0:28:28.280
<v Speaker 15>again in real world and real industries.

0:28:27.960 --> 0:28:30.080
<v Speaker 4>And maybe even the future of defense. There were so

0:28:30.080 --> 0:28:32.600
<v Speaker 4>many interesting parts to this story, Natasha that I want

0:28:32.640 --> 0:28:34.560
<v Speaker 4>to dig in on, but won't call my eye as

0:28:34.600 --> 0:28:36.680
<v Speaker 4>someone who sat in New York, they're not going to

0:28:36.840 --> 0:28:39.280
<v Speaker 4>Silicon Valley. This is because they really feel that there's

0:28:39.640 --> 0:28:42.000
<v Speaker 4>what did he call it, that they've been LLLM pilled there.

0:28:42.120 --> 0:28:44.280
<v Speaker 4>This is a European story at it's hot, but it's

0:28:44.320 --> 0:28:46.120
<v Speaker 4>also a non Silicon Valley one.

0:28:47.360 --> 0:28:48.280
<v Speaker 5>You're exactly right.

0:28:48.360 --> 0:28:51.000
<v Speaker 15>I mean, this is one of the largest venture rounds

0:28:51.200 --> 0:28:55.000
<v Speaker 15>raised ever in Europe and it is actively one that

0:28:55.040 --> 0:28:58.800
<v Speaker 15>has not included a lot of the traditional Silicon Valley investors.

0:28:59.160 --> 0:29:01.880
<v Speaker 15>When I asked you about that decision, he said that

0:29:02.080 --> 0:29:05.760
<v Speaker 15>Silicon Valley investors were looking for really high ownership in

0:29:05.880 --> 0:29:08.840
<v Speaker 15>the business, and he believed that it was important to

0:29:09.600 --> 0:29:12.200
<v Speaker 15>try and to check talent that wasn't just focused on

0:29:12.360 --> 0:29:15.640
<v Speaker 15>building within the large language models, which means not going

0:29:15.720 --> 0:29:19.280
<v Speaker 15>to where people are working for Anthropic Open AI, even

0:29:19.320 --> 0:29:23.400
<v Speaker 15>his former employer Meta, and trying to go to different geographies. Now,

0:29:23.680 --> 0:29:25.719
<v Speaker 15>I did ask if he will have to raise from

0:29:25.760 --> 0:29:28.640
<v Speaker 15>Silicon Valley eventually, and he said he's definitely open to

0:29:28.680 --> 0:29:29.600
<v Speaker 15>that for his next round.

0:29:31.120 --> 0:29:34.800
<v Speaker 3>Lakuma is at Meta for almost fifteen years, more than

0:29:34.880 --> 0:29:38.280
<v Speaker 3>ten years at least. Is there any evidence of reporting

0:29:38.440 --> 0:29:41.080
<v Speaker 3>that that that's the way they go, some kind of

0:29:41.160 --> 0:29:45.000
<v Speaker 3>relationship with Meta, some collaborative work something like that.

0:29:45.400 --> 0:29:45.560
<v Speaker 2>Yeah.

0:29:45.640 --> 0:29:48.200
<v Speaker 15>So at this point, Meta was not listed as an

0:29:48.280 --> 0:29:51.400
<v Speaker 15>investor in the new business, but we did ask him

0:29:51.440 --> 0:29:55.080
<v Speaker 15>about possible partnerships, which he did confirm. So while the

0:29:55.280 --> 0:29:58.960
<v Speaker 15>average consumer may not interact with his new company through

0:29:59.160 --> 0:30:02.200
<v Speaker 15>a chatbot, there's not a too far of a world

0:30:02.200 --> 0:30:04.800
<v Speaker 15>where we could see it showing up in the meta

0:30:04.880 --> 0:30:07.760
<v Speaker 15>ray bands or other AI ware of all the meta's

0:30:07.840 --> 0:30:10.680
<v Speaker 15>working on. So we're definitely tracking the possible partnership and

0:30:10.760 --> 0:30:12.880
<v Speaker 15>you can birm that there are ongoing discussions there.

0:30:13.600 --> 0:30:16.960
<v Speaker 4>Natasha Mascarinis just scoop off to scoot. We so appreciate

0:30:17.080 --> 0:30:20.680
<v Speaker 4>coming on without reporting. Let's not talk about another funding

0:30:20.960 --> 0:30:21.920
<v Speaker 4>or indeed relationship.

0:30:21.960 --> 0:30:24.240
<v Speaker 5>In Video is investing in Thinking Machines Lab.

0:30:24.720 --> 0:30:27.520
<v Speaker 4>It's an AI startup founded by opening Ey executive mirror

0:30:27.560 --> 0:30:29.760
<v Speaker 4>Marati now and Video is set to provide it's Vera

0:30:29.800 --> 0:30:32.960
<v Speaker 4>Ruben systems to power Thinking Machines AI models as part

0:30:33.000 --> 0:30:36.040
<v Speaker 4>of a multi year agreement. Blomberg AI reporter Rachel Metz

0:30:36.120 --> 0:30:39.280
<v Speaker 4>joins us some more so, what is Thinking Machines Lab doing?

0:30:40.760 --> 0:30:44.800
<v Speaker 16>Yeah, so this company, they are building their own AI

0:30:44.960 --> 0:30:48.320
<v Speaker 16>models and they have a deal that they just announced

0:30:48.360 --> 0:30:51.480
<v Speaker 16>with in Video. They're getting investment from the Video and

0:30:51.600 --> 0:30:55.320
<v Speaker 16>they are also going to be using quite a lot

0:30:55.480 --> 0:30:59.560
<v Speaker 16>of in Vidia's chip power to train and run their

0:30:59.600 --> 0:31:00.440
<v Speaker 16>AI models.

0:31:01.440 --> 0:31:04.080
<v Speaker 3>I posted your story on X and you know noting

0:31:04.160 --> 0:31:06.200
<v Speaker 3>that up to a gig or what ver Rubin or

0:31:06.280 --> 0:31:09.120
<v Speaker 3>a minimum of a giga what sorry, ver Rubin systems like,

0:31:09.200 --> 0:31:10.320
<v Speaker 3>that's a lot of compute.

0:31:10.720 --> 0:31:11.880
<v Speaker 2>But the unknowns are.

0:31:11.960 --> 0:31:14.640
<v Speaker 3>Is in video making this investment in cash or chips

0:31:14.680 --> 0:31:15.280
<v Speaker 3>in lieu of cash.

0:31:15.360 --> 0:31:16.000
<v Speaker 2>We just don't know.

0:31:16.440 --> 0:31:18.880
<v Speaker 3>And the response that everyone gets back is, so, what

0:31:19.000 --> 0:31:22.480
<v Speaker 3>does thinking Machines do? What is thinking machines other than AI?

0:31:23.800 --> 0:31:27.800
<v Speaker 16>Okay, so so far, Thinking Machines has released one product,

0:31:28.040 --> 0:31:30.960
<v Speaker 16>and it is called Tinker, and it came out last year,

0:31:31.400 --> 0:31:36.120
<v Speaker 16>and that is a software that companies can use to

0:31:36.280 --> 0:31:39.760
<v Speaker 16>fine tune AI models. What they're working on as well

0:31:40.120 --> 0:31:43.200
<v Speaker 16>is some AI models. It's not quite known yet what

0:31:43.320 --> 0:31:46.120
<v Speaker 16>the details of those are. It sounds like they will

0:31:46.160 --> 0:31:49.640
<v Speaker 16>be things that will be useful to a range of enterprises,

0:31:50.240 --> 0:31:52.920
<v Speaker 16>but it's not entirely clear yet if they're going to

0:31:52.960 --> 0:31:55.680
<v Speaker 16>be focused on specific uses or if it's going to

0:31:55.720 --> 0:31:57.960
<v Speaker 16>be a more general kind of thing like the models

0:31:58.000 --> 0:31:59.840
<v Speaker 16>that underpin say chat GPT or.

0:32:00.880 --> 0:32:04.320
<v Speaker 4>To have just issued or developed a model called Tinker

0:32:04.400 --> 0:32:07.240
<v Speaker 4>and already the talked of as in the realm of

0:32:07.280 --> 0:32:10.760
<v Speaker 4>a fifty billion dollar market capitalization, it's on us to

0:32:10.840 --> 0:32:14.160
<v Speaker 4>remind ourselves why Mira Marati is taken so seriously by

0:32:14.200 --> 0:32:16.480
<v Speaker 4>this market for a hot second, she led open Ai,

0:32:16.600 --> 0:32:20.560
<v Speaker 4>but really she was the CTO, right, Yes, she was.

0:32:20.600 --> 0:32:24.320
<v Speaker 16>The CTO Opening Eye. She's worked add a number of

0:32:24.600 --> 0:32:26.600
<v Speaker 16>tech companies over the years, so she's been in the

0:32:26.680 --> 0:32:29.360
<v Speaker 16>industry for quite a long time. I think the challenge

0:32:29.680 --> 0:32:33.160
<v Speaker 16>that she's facing here with this company is can she

0:32:33.640 --> 0:32:36.720
<v Speaker 16>build large language models? Not just can she build them?

0:32:37.280 --> 0:32:40.400
<v Speaker 16>A handful of companies can build them. They require obviously

0:32:40.520 --> 0:32:44.360
<v Speaker 16>a lot of money, a lot of expertise, and a

0:32:44.440 --> 0:32:48.400
<v Speaker 16>lot of data, but also can she then convince companies

0:32:48.680 --> 0:32:50.959
<v Speaker 16>or some other form of customer to pay for them.

0:32:51.760 --> 0:32:56.360
<v Speaker 16>Tinker is an effort to help people fine tune models,

0:32:56.640 --> 0:32:59.880
<v Speaker 16>so it's not quite up to having It's not the

0:33:00.080 --> 0:33:02.520
<v Speaker 16>same as having a model and then having people use it.

0:33:03.200 --> 0:33:05.760
<v Speaker 16>But that was sort of their first step into business,

0:33:05.880 --> 0:33:08.000
<v Speaker 16>and they do have customers for that, so it'll be

0:33:08.040 --> 0:33:10.640
<v Speaker 16>interesting to see over the next year or so what

0:33:10.840 --> 0:33:12.040
<v Speaker 16>happens with their business.

0:33:13.240 --> 0:33:17.560
<v Speaker 3>We'd reported at the end of last year the Thinking

0:33:17.600 --> 0:33:20.280
<v Speaker 3>Machines was going out doing an early round at like

0:33:20.360 --> 0:33:22.960
<v Speaker 3>a fifty billion dollar valuation when it was basically a

0:33:23.040 --> 0:33:26.160
<v Speaker 3>handful of people, and then what followed was all kinds

0:33:26.200 --> 0:33:30.400
<v Speaker 3>of media reports about internally things not being well right,

0:33:30.520 --> 0:33:33.240
<v Speaker 3>people leaving. We never really got to the bottom of it.

0:33:33.360 --> 0:33:35.200
<v Speaker 3>I mean, this is a big piece of news for them,

0:33:35.280 --> 0:33:38.000
<v Speaker 3>but we have a sense of how it's going otherwise

0:33:38.080 --> 0:33:39.680
<v Speaker 3>beyond getting the backing of Nvidia.

0:33:40.840 --> 0:33:43.120
<v Speaker 16>Yeah, that is a bit of a question mark. We

0:33:43.480 --> 0:33:46.680
<v Speaker 16>know that the company has about one hundred employees and

0:33:47.400 --> 0:33:50.480
<v Speaker 16>it has, as you mentioned, it recently lost some employees

0:33:50.520 --> 0:33:54.000
<v Speaker 16>who went back to Opening I. Initially, when Mira Murradi

0:33:54.080 --> 0:33:57.080
<v Speaker 16>started this company, she started it with a quite a

0:33:57.160 --> 0:33:59.840
<v Speaker 16>number of people that came from Opening I, so that

0:34:00.000 --> 0:34:02.160
<v Speaker 16>it was certainly a signal if people were going back

0:34:02.240 --> 0:34:05.280
<v Speaker 16>to that company that they had come from. But I mean,

0:34:05.320 --> 0:34:07.840
<v Speaker 16>I think this is still a very new company, and

0:34:08.040 --> 0:34:11.880
<v Speaker 16>sometimes these things take time to get going, get off

0:34:11.920 --> 0:34:14.719
<v Speaker 16>the ground, and we'll see what happens throughout the rest

0:34:14.760 --> 0:34:15.160
<v Speaker 16>of this year.

0:34:16.280 --> 0:34:18.799
<v Speaker 2>Bloomberg's Retro mets top Reporting. Thank you very much.

0:34:19.080 --> 0:34:22.799
<v Speaker 3>Coming up on the show, HPE exceeds expectations on its

0:34:22.840 --> 0:34:26.080
<v Speaker 3>forecast for the current quarter. It's all about AI demand

0:34:26.400 --> 0:34:28.759
<v Speaker 3>and all about AI hardware demand. We can discuss what's

0:34:28.840 --> 0:34:32.520
<v Speaker 3>driving that outlet next with HPE CEO Antonio Neeri.

0:34:32.880 --> 0:34:33.960
<v Speaker 2>This is Blomberg Tech.

0:34:43.719 --> 0:34:47.080
<v Speaker 3>Shares of HPE modestly higher, up about six tens of

0:34:47.160 --> 0:34:49.400
<v Speaker 3>one percent. Been chopping around in the session, but the

0:34:49.440 --> 0:34:52.480
<v Speaker 3>company gave a strong sales and revenue projection for the

0:34:52.520 --> 0:34:53.160
<v Speaker 3>current quarter.

0:34:53.640 --> 0:34:54.320
<v Speaker 2>What's driving it?

0:34:54.440 --> 0:34:57.480
<v Speaker 3>Demand demand for AI hardware in particular, has discussed with

0:34:57.640 --> 0:35:01.320
<v Speaker 3>HPE CEO Antonio Nery, and let's start with that. You know,

0:35:01.800 --> 0:35:05.960
<v Speaker 3>clearly there is some staying power in that demand at

0:35:06.120 --> 0:35:08.520
<v Speaker 3>rack scale, you know, crystallize it for us.

0:35:08.600 --> 0:35:10.080
<v Speaker 2>What are you seeing in real time?

0:35:11.520 --> 0:35:14.279
<v Speaker 7>Yeah, good morning, Ed, and thanks for having me. We

0:35:14.440 --> 0:35:18.480
<v Speaker 7>saw a tremendous demand throughout the quarter. I think the

0:35:18.600 --> 0:35:21.400
<v Speaker 7>momentum in I continues in the build out of the

0:35:21.520 --> 0:35:24.280
<v Speaker 7>data center. But what I'm really pleased is the momentum

0:35:24.320 --> 0:35:27.680
<v Speaker 7>we see an enterprise. In fact, most of our revenue

0:35:27.719 --> 0:35:30.279
<v Speaker 7>in AI that we're recognize in Q one came from

0:35:30.320 --> 0:35:34.399
<v Speaker 7>the enterprise segment, which shows you two key elements. One

0:35:34.560 --> 0:35:38.680
<v Speaker 7>is the adoption of agentic AI into the company's workflow,

0:35:38.800 --> 0:35:41.239
<v Speaker 7>and second is the growing of influencing. A lot of

0:35:41.280 --> 0:35:45.560
<v Speaker 7>focuses always around the training and training these new models,

0:35:45.680 --> 0:35:48.840
<v Speaker 7>but for us, our focus being both the sovereign space

0:35:49.120 --> 0:35:53.760
<v Speaker 7>and the influencing and enterprise space. But in our portfolio,

0:35:53.840 --> 0:35:58.120
<v Speaker 7>we saw tremendous momentum networking. Our strategy where journeys has

0:35:58.200 --> 0:36:01.359
<v Speaker 7>paid off, and that's why we see double digits year

0:36:01.400 --> 0:36:03.040
<v Speaker 7>over your growth in the order intake.

0:36:03.760 --> 0:36:08.520
<v Speaker 3>You know post Juniper networking is is upside for you, right.

0:36:08.600 --> 0:36:10.840
<v Speaker 3>I think you have a lot of confidence that growth

0:36:10.880 --> 0:36:14.120
<v Speaker 3>will come in networking. For the audience that doesn't understand

0:36:14.160 --> 0:36:16.480
<v Speaker 3>what it is you do in that space. Why is

0:36:16.640 --> 0:36:20.160
<v Speaker 3>networking on the rise in parallel with just kind of

0:36:20.239 --> 0:36:22.280
<v Speaker 3>the broader AI hardware demand that you're seeing.

0:36:23.960 --> 0:36:27.000
<v Speaker 7>Well, I do believe ed and this was the coresis

0:36:27.040 --> 0:36:30.680
<v Speaker 7>of the Juniper acquisation that the next inflection point in

0:36:30.760 --> 0:36:35.239
<v Speaker 7>terms of disruption will come from the networking connectivity layer.

0:36:35.520 --> 0:36:38.120
<v Speaker 7>Think about when you build a data center, you have

0:36:38.280 --> 0:36:41.680
<v Speaker 7>to connect this data center to other data centers through

0:36:41.719 --> 0:36:44.839
<v Speaker 7>the Internet, and that's what we call data center interconnect.

0:36:45.000 --> 0:36:48.960
<v Speaker 7>Juniper has one of the most innovative products in the

0:36:49.080 --> 0:36:51.440
<v Speaker 7>route in space, by the way, this passport that we

0:36:51.520 --> 0:36:55.160
<v Speaker 7>grew mid twenty percent in the order intake. And then

0:36:55.239 --> 0:36:57.520
<v Speaker 7>once you are inside the data center, you need to

0:36:57.680 --> 0:37:00.640
<v Speaker 7>be able to connect large amount of GPU use and

0:37:00.800 --> 0:37:04.160
<v Speaker 7>CPUs together and that's why you need a data't set.

0:37:04.280 --> 0:37:06.880
<v Speaker 7>Data doesn't resewarching portfolio in addition to some of the

0:37:07.440 --> 0:37:10.840
<v Speaker 7>other core tenants of the technology and there you know,

0:37:11.080 --> 0:37:14.640
<v Speaker 7>the Juniper portfolio group mid forty percent in the order intake.

0:37:15.400 --> 0:37:18.560
<v Speaker 7>So I will say for us, that has been a

0:37:18.680 --> 0:37:22.640
<v Speaker 7>core tenant. That's why you know now they represent almost

0:37:22.920 --> 0:37:25.879
<v Speaker 7>thirty percent of the company revenues but more than half

0:37:25.960 --> 0:37:29.480
<v Speaker 7>of the profit. And for us, that's also an ability

0:37:29.520 --> 0:37:31.920
<v Speaker 7>to raise the outlook for the remainder of the year.

0:37:32.080 --> 0:37:35.640
<v Speaker 7>And also they're outlooking free cash flow because the structural

0:37:35.760 --> 0:37:39.239
<v Speaker 7>margins of that business and the working capital efficiency are very,

0:37:39.320 --> 0:37:40.960
<v Speaker 7>very different than the rest of the portfolio.

0:37:41.120 --> 0:37:43.800
<v Speaker 4>I mean you actually said, look, you're not done raising prices.

0:37:43.960 --> 0:37:47.160
<v Speaker 4>You talk about discipline and what is a very dynamic environment,

0:37:47.239 --> 0:37:48.360
<v Speaker 4>Antonio talk.

0:37:48.200 --> 0:37:51.080
<v Speaker 5>To us about well, how you're weathering.

0:37:50.680 --> 0:37:53.600
<v Speaker 4>The supply chain issue, in particularly the cost the memory

0:37:53.680 --> 0:37:54.399
<v Speaker 4>costs at the moment.

0:37:54.560 --> 0:37:55.400
<v Speaker 5>How do you navigate that?

0:37:56.880 --> 0:38:00.239
<v Speaker 7>Yeah, Carol, I mean, obviously the demand and supply has

0:38:00.320 --> 0:38:03.759
<v Speaker 7>a huge mismatch, and you actually need to go back

0:38:03.840 --> 0:38:06.680
<v Speaker 7>all the twenty two to twenty three timeframe to understand

0:38:06.719 --> 0:38:11.239
<v Speaker 7>how we got here. Accelerated by the hypercycle we see

0:38:11.520 --> 0:38:16.120
<v Speaker 7>in the AI space, but fundamentally in our guidance, the

0:38:16.200 --> 0:38:18.839
<v Speaker 7>new guidance, the new outlook that we raise for twenty

0:38:18.920 --> 0:38:23.480
<v Speaker 7>twenty six. We included our ability to see the supply

0:38:23.719 --> 0:38:26.040
<v Speaker 7>that we need to convert that into a revenue profit.

0:38:26.440 --> 0:38:29.000
<v Speaker 7>But the reality is that we do not have enough

0:38:29.080 --> 0:38:34.520
<v Speaker 7>supply against the order intake and the backlog, because otherwise

0:38:34.560 --> 0:38:37.560
<v Speaker 7>we'll have even a higher outlook. So what we're doing

0:38:37.680 --> 0:38:41.239
<v Speaker 7>we have taken three very unique steps. Number one is

0:38:41.520 --> 0:38:44.080
<v Speaker 7>securing as much supply as we can, but again we

0:38:44.120 --> 0:38:46.520
<v Speaker 7>don't have all the supply that we would like to have.

0:38:46.800 --> 0:38:50.360
<v Speaker 7>Number two is taking a very agile posture when it

0:38:50.440 --> 0:38:53.080
<v Speaker 7>comes down to pricing, and as I said yesterday, we

0:38:53.160 --> 0:38:57.360
<v Speaker 7>are not done raising pricing. I think that the cycle

0:38:57.400 --> 0:39:00.879
<v Speaker 7>will continue well into twenty twenty seven, although we will

0:39:00.960 --> 0:39:04.080
<v Speaker 7>hope that we will reach some sort of elevated price

0:39:04.200 --> 0:39:08.360
<v Speaker 7>in stability in twenty twenty six. And number three, you know,

0:39:08.520 --> 0:39:11.759
<v Speaker 7>my experience has thought me that ultimately you need to

0:39:11.840 --> 0:39:15.920
<v Speaker 7>have direct, transparent conversation both with customers and our partners.

0:39:16.040 --> 0:39:18.560
<v Speaker 7>Last week I was in Europe. I met more than

0:39:18.600 --> 0:39:22.800
<v Speaker 7>twenty customers the Mobile Congress in London, and they appreciate

0:39:22.880 --> 0:39:25.680
<v Speaker 7>that level of transparency, understanding the environment we're in.

0:39:26.040 --> 0:39:28.480
<v Speaker 4>I mean, you're actually forgoing supplying some equipment to mobile

0:39:28.600 --> 0:39:31.640
<v Speaker 4>service providers, So you're being choosy with who you work

0:39:31.719 --> 0:39:35.000
<v Speaker 4>with at this time of geopolitical angst and when we

0:39:35.200 --> 0:39:36.920
<v Speaker 4>question how much the Middle East is going to be

0:39:36.960 --> 0:39:39.560
<v Speaker 4>able to build out the data center capacity as once thought.

0:39:40.280 --> 0:39:43.600
<v Speaker 4>Has the Iran conflict impacted your view on the world

0:39:43.840 --> 0:39:46.839
<v Speaker 4>or indeed the supply of the world and chips.

0:39:48.280 --> 0:39:51.439
<v Speaker 7>Not on the supply side, Carol, And obviously our first

0:39:51.520 --> 0:39:56.400
<v Speaker 7>priority because we have businesses in that region, whether ue Qatar,

0:39:56.520 --> 0:39:59.920
<v Speaker 7>bar In, sauda Arabia, Israel, right is the well being

0:40:00.080 --> 0:40:03.600
<v Speaker 7>the safety of our employees. We have approximately one thousand

0:40:03.680 --> 0:40:06.080
<v Speaker 7>employees in that region and the good news all are

0:40:06.160 --> 0:40:09.560
<v Speaker 7>doing well at this point in time. But from a

0:40:09.600 --> 0:40:15.640
<v Speaker 7>supply perspective, no, But obviously as the conflict may gets elongated,

0:40:15.640 --> 0:40:18.520
<v Speaker 7>they may have other implications, particularly on the logistics side

0:40:18.560 --> 0:40:22.680
<v Speaker 7>of the equation. You know, look, air freight routes are

0:40:22.760 --> 0:40:25.239
<v Speaker 7>a little bit more complicated. We don't use boats of

0:40:25.360 --> 0:40:31.480
<v Speaker 7>ships for transporting our equipments. But over time we have

0:40:31.600 --> 0:40:33.920
<v Speaker 7>to assess if there is a revenue impact. What I

0:40:34.000 --> 0:40:36.680
<v Speaker 7>can tell you right now there is even more demand

0:40:36.960 --> 0:40:40.000
<v Speaker 7>then we saw particularly you know, three four months ago,

0:40:40.239 --> 0:40:42.480
<v Speaker 7>so we have to navigate that together. We have to

0:40:42.520 --> 0:40:43.239
<v Speaker 7>be smart about it.

0:40:44.320 --> 0:40:44.800
<v Speaker 2>Antonio.

0:40:44.960 --> 0:40:48.200
<v Speaker 3>You have never let me tear apart an HPE server,

0:40:48.480 --> 0:40:50.520
<v Speaker 3>and that's okay. But if I got my hands in

0:40:50.560 --> 0:40:53.800
<v Speaker 3>the compute trade, you'd have the high bandwidth memory around

0:40:53.800 --> 0:40:56.880
<v Speaker 3>the GPU wherever it comes from. You'd have the ddrs

0:40:56.960 --> 0:41:00.280
<v Speaker 3>around the CPU, and somewhere you'd have the SSDs.

0:41:00.000 --> 0:41:03.200
<v Speaker 2>And flash memory. Be very very specific.

0:41:03.480 --> 0:41:06.600
<v Speaker 3>Of those three, what's the biggest impact to you right

0:41:06.680 --> 0:41:11.279
<v Speaker 3>now in constraining your sales and your outlook, very simple.

0:41:11.120 --> 0:41:17.160
<v Speaker 7>Is DDR and nand or the SSDs. Hbm's less constrained,

0:41:17.320 --> 0:41:21.040
<v Speaker 7>but obviously a lot of the allocation on the capacity

0:41:21.120 --> 0:41:23.399
<v Speaker 7>has moved there. And as you know, there is also

0:41:23.400 --> 0:41:26.279
<v Speaker 7>a transition from the prior generation of hbms to the

0:41:26.360 --> 0:41:30.200
<v Speaker 7>new generation of HBM because you need more membody channels.

0:41:30.560 --> 0:41:34.600
<v Speaker 7>But it's really the DDR four and five which now

0:41:35.040 --> 0:41:37.919
<v Speaker 7>nobody almost use it, but DDR five and the nand

0:41:38.080 --> 0:41:39.360
<v Speaker 7>part which is the SSDs.

0:41:39.840 --> 0:41:40.760
<v Speaker 5>You said just earlier.

0:41:40.920 --> 0:41:43.520
<v Speaker 4>Look, one of your the three key steps you took

0:41:44.080 --> 0:41:46.000
<v Speaker 4>was to get as much supply as you could and

0:41:46.080 --> 0:41:48.000
<v Speaker 4>to ensure that that was locked in. You wish you

0:41:48.040 --> 0:41:50.000
<v Speaker 4>could have more Who is it that you need to

0:41:50.560 --> 0:41:52.719
<v Speaker 4>push more? Who is it do you need to have

0:41:52.840 --> 0:41:55.400
<v Speaker 4>more security for? How can you perhaps get hands on

0:41:55.480 --> 0:41:56.560
<v Speaker 4>further supply going forward.

0:41:57.960 --> 0:42:01.799
<v Speaker 7>Look, we have a long standard relationship with the three

0:42:01.960 --> 0:42:07.839
<v Speaker 7>core suppliers that provide DDR memory and hpms, and there

0:42:07.920 --> 0:42:11.520
<v Speaker 7>is a little bit a larger ecosystem for the land space,

0:42:11.719 --> 0:42:15.840
<v Speaker 7>but we're having weekly engagements with them. We are looking

0:42:16.000 --> 0:42:21.279
<v Speaker 7>to swap components driving different configurations, but the reality all

0:42:21.320 --> 0:42:23.080
<v Speaker 7>of them are significantly constrained.

0:42:23.160 --> 0:42:28.200
<v Speaker 3>Karl Antonio just twenty seconds, what's the dollar figure dollar terms,

0:42:28.280 --> 0:42:30.560
<v Speaker 3>and of what was left on the table, how much

0:42:30.640 --> 0:42:31.839
<v Speaker 3>better the outlook could have been.

0:42:33.719 --> 0:42:37.640
<v Speaker 7>Yeah, it's pretty sizable. I will say, you know, we

0:42:37.840 --> 0:42:42.560
<v Speaker 7>guided five pennies on the midpoint of the range and

0:42:42.760 --> 0:42:45.640
<v Speaker 7>then we raise our outlook for free cash flow by

0:42:46.080 --> 0:42:49.960
<v Speaker 7>almost two hundred million at the midpoint. But the backlog

0:42:50.120 --> 0:42:52.040
<v Speaker 7>is very very large at this point in time. If

0:42:52.080 --> 0:42:54.840
<v Speaker 7>you think about the AI system backlog is over five billion.

0:42:55.360 --> 0:43:00.239
<v Speaker 7>We raise again the networking for networks for AI goal

0:43:00.400 --> 0:43:02.319
<v Speaker 7>for the end of the year. So it's a very

0:43:02.400 --> 0:43:05.320
<v Speaker 7>sizeable backlog. So we hope we make progress as we

0:43:05.440 --> 0:43:09.400
<v Speaker 7>go along, but we categorize, we leveled it as a

0:43:09.520 --> 0:43:11.160
<v Speaker 7>proved guidance at this point in time.

0:43:11.280 --> 0:43:14.400
<v Speaker 4>Anthony Nari, CEO of HPE, thanks for the candid conversation.

0:43:14.760 --> 0:43:16.520
<v Speaker 5>We appreciate it. Now that does it with this addition

0:43:16.560 --> 0:43:17.040
<v Speaker 5>of Bloomberg

0:43:17.120 --> 0:43:21.000
<v Speaker 3>Tech ed, great interviews, great Bloomberg reporting, recap it on

0:43:21.080 --> 0:43:23.000
<v Speaker 3>the podcast new Where to find it on the terminal

0:43:23.040 --> 0:43:26.720
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