WEBVTT - AWS CEO Matt Garman Lays Out Amazon’s AI Plans

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<v Speaker 1>Bloomberg Audio Studios, podcasts, radio news from the heart of

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<v Speaker 1>where innovation, money and power collide in Silicon Valley and beyond.

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<v Speaker 1>This is Bloomberg Technology with Caroline Hyde and Ed Ludlow.

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<v Speaker 2>Live from San Francisco. This is Bloomberg Technology coming up.

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<v Speaker 2>US President Trump accuses China of violating an agreement with

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<v Speaker 2>the US to east tariffs, escalating tensions between the two countries.

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<v Speaker 3>Plus sales of Apple's.

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<v Speaker 2>iPhone are set to take a big hit from Trump's

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<v Speaker 2>new tariff policy. We get into the numbers and we

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<v Speaker 2>speak with the CEO of AWS as the leading Hyperscala

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<v Speaker 2>runs faster on a What a week it has been

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<v Speaker 2>in the world of technology.

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<v Speaker 3>I'm looking at the Nazak one hundred.

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<v Speaker 2>It is a megacap and technology heavy index, and over

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<v Speaker 2>the course of the week we're up a percentage point.

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<v Speaker 2>We're actually lower in Friday session, but this is a

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<v Speaker 2>rebound from last week where earnings and that tariff story

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<v Speaker 2>have been the driver of the markets and the headlines.

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<v Speaker 2>There are two names in particular that we have been

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<v Speaker 2>so focused on. Those names are in video. Of course,

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<v Speaker 2>we had earnings twenty four hours ago, thirty eight hours ago,

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<v Speaker 2>forty eight hours ago, and then we spoke to Gensen one.

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<v Speaker 2>It's giving some of the gains that it had seen back,

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<v Speaker 2>but there is a big question still about China and

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<v Speaker 2>cross border trade of the lead edge technology. And then

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<v Speaker 2>Apple again softer four tens and one percent just twenty

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<v Speaker 2>four hours ago, and Video was the world's most valuable company.

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<v Speaker 2>Apple had regained some status as a three trillion dollar club.

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<v Speaker 3>We're under pressure. Now. Here's the top story.

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<v Speaker 2>China's planning to allocate seventy billion dollars of capital in

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<v Speaker 2>a new effort to fast track new infrastructure projects and

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<v Speaker 2>up its own economy from ongoing US tariffs.

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<v Speaker 3>That's according to sources.

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<v Speaker 2>Meanwhile, President Trump reigniting those tariff war concerns, posting on

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<v Speaker 2>True Social that China has quote totally violated its agreement

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<v Speaker 2>with US or US, offering no details of what agreements

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<v Speaker 2>China could have violated. Let's get more from Bloomberg's Mike Shephard.

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<v Speaker 2>Do we know what the president is talking about here?

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<v Speaker 4>Well, we haven't gotten a clear signal from him directly

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<v Speaker 4>about what had set him off this morning, but we

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<v Speaker 4>have seen ed over the past few weeks since that

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<v Speaker 4>sit down in Geneva, between Treasury Secretary Scott Besson and

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<v Speaker 4>his Chinese counterparts signed that that little agreement that that

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<v Speaker 4>daytime that they had forged there in Switzerland was starting

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<v Speaker 4>to come apart. The Chinese government had objected to some

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<v Speaker 4>export controls that the US has increasingly been applying to China,

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<v Speaker 4>keeping advanced technology from getting in there, And of course

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<v Speaker 4>this has been a sore spot for Beijing for years,

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<v Speaker 4>with limits on exports of semikins, but they have been escalating,

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<v Speaker 4>and in more recent weeks we even saw the US

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<v Speaker 4>go after makers of chip design software, telling them essentially,

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<v Speaker 4>you can't sell to China without violating our export restrictions.

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<v Speaker 4>So that is something that already Beijing was seeing as

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<v Speaker 4>a violation of the spirit of those conversations. We had

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<v Speaker 4>heard that a week ago, but now today we hear

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<v Speaker 4>from the top US trade negotiator Jamison Greer talking about

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<v Speaker 4>rare earths and critical minerals. And during that discussion in Geneva,

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<v Speaker 4>the two sides had agreed that Beijing might lift some

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<v Speaker 4>of the barriers that it had placed in retaliation for

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<v Speaker 4>US export curbs on exports to the US of critical minerals.

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<v Speaker 3>So there is a bit of.

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<v Speaker 4>Tit for tat that we are seeing here, and it

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<v Speaker 4>may be bubbling over in the form of Donald Trump's

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<v Speaker 4>truth social feed here today.

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<v Speaker 2>Yet Yeah, I'm reading the news on the Bloomberg terminal,

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<v Speaker 2>and I go back to what Michael Kratsios, who runs

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<v Speaker 2>the White House Office of Science and Technology, right told us.

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<v Speaker 2>The policy from this administration is promote and protect. Protect

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<v Speaker 2>is the tariffs bit right. Promote is on shoring and

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<v Speaker 2>stimulus for the tech industry. China is doing the same thing, right,

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<v Speaker 2>It's trying to drum up some money seventy billion dollars

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<v Speaker 2>we're reporting for its own industries in China.

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<v Speaker 3>What do we know about that?

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<v Speaker 4>Well, And that's a good question, and I'm glad you

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<v Speaker 4>brought that up, because it's unclear whether the administration here

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<v Speaker 4>is responding to that report of additional Chinese stimulus toward

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<v Speaker 4>artificial intelligence and other high tech projects that they have

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<v Speaker 4>planned as a way to spark their economy and make

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<v Speaker 4>sure that they have some domestic demand to satisfy the

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<v Speaker 4>industry that is trying to cultivate. But nonetheless it would

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<v Speaker 4>not sit well with the US administration here because they

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<v Speaker 4>are trying to bring some of that manufacturing to American

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<v Speaker 4>shores to try to build up the American tech manufacturing base.

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<v Speaker 4>We've seen so much of it, especially in semiconductors over decades,

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<v Speaker 4>move to Asia, and Donald Trump there's been applying pressure

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<v Speaker 4>to none other than Tim Cook, the Apple CEO, to

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<v Speaker 4>try to get the iPhone production moved here. Of course,

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<v Speaker 4>in our conversations with Mark German and so many others,

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<v Speaker 4>we know that that is a bit of a pipe dream,

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<v Speaker 4>but nonetheless it is a priority for the administration, and

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<v Speaker 4>so you do see, as you said from your interview

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<v Speaker 4>with Michael Kratzios, this desire to promote American tech here

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<v Speaker 4>at home, but also protect it against the challenge it

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<v Speaker 4>sees coming.

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<v Speaker 2>From China, Bluembos, Mike Shephard, do not go far, how

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<v Speaker 2>a sense, more news is coming on those topics. Meanwhile,

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<v Speaker 2>sales of Apple's iPhone and those of its rivals are

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<v Speaker 2>set to take a significant blow from President Trump's tariffs.

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<v Speaker 2>IDC research showing smartphone growth of just zero point six

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<v Speaker 2>percent post tariffs. For more, Nabila popeu IDC senior research director,

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<v Speaker 2>joins us, I always track your data, not just the

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<v Speaker 2>backward looking data, but extrapolating out and looking forward, you've

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<v Speaker 2>kind of now got the post tariffscenario. Just explain what

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<v Speaker 2>you published overnight and how this impacts in particular Apple.

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<v Speaker 5>Hi, thank you and nice to be here as always. Yeah,

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<v Speaker 5>so exactly, And whenever we publish our forecast, we always

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<v Speaker 5>have to show what was the scenario before, right, So

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<v Speaker 5>in our latest forecast, which we just published, we're showing

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<v Speaker 5>a flat growth and it's really important to see how

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<v Speaker 5>that's changed, right, because twenty four was.

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<v Speaker 3>You know, the year of we had like twenty three.

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<v Speaker 5>We basically we've been in a few years of decline.

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<v Speaker 5>In the twenty four exactly, thank you for showing that

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<v Speaker 5>up was a big year of growth. And then twenty

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<v Speaker 5>five was supposed to continue this growth. But we were

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<v Speaker 5>supposed to have about two percent two point three percent,

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<v Speaker 5>you know, continued recovery. But since February, when was our

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<v Speaker 5>last forecast was published, we've been going through such tumulus times. Right,

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<v Speaker 5>there's been a world ruin of uncertainty. You've seen that

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<v Speaker 5>we're thrown around many times. We've had to pull down

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<v Speaker 5>the forecast because of our we see high uncertainty, so

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<v Speaker 5>much terrrift supply chain turmoil, and there's a lot of

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<v Speaker 5>you know, just soft demand across the board in large

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<v Speaker 5>global markets.

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<v Speaker 2>I'm trying to understand policy and how you factor policy

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<v Speaker 2>into that model. Right, So, the situation was that smartphones

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<v Speaker 2>were given a tariff exemption.

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<v Speaker 3>That was mid April.

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<v Speaker 2>Then President Donald Trump just this month May said that

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<v Speaker 2>for smartphones made outside of America there should be a well,

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<v Speaker 2>let's be honest, not just smartphones, the iPhone made outside

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<v Speaker 2>of America, there should be a levy of twenty five percent.

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<v Speaker 3>How have you factored that in?

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<v Speaker 5>So you know, that came out right actually after we

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<v Speaker 5>had finalized our forecast. So we you know, what we

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<v Speaker 5>had taken into consideration, right, because we knew that even

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<v Speaker 5>when the exemptions were announced or whatever wherever the tariff stood,

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<v Speaker 5>that it was all temporary. That things could always change.

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<v Speaker 5>So we had to draw a line under stand at

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<v Speaker 5>some point.

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<v Speaker 6>But there was you know.

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<v Speaker 5>We had we did bacon that there is I think

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<v Speaker 5>things could always change. So there the what we're you know,

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<v Speaker 5>saying to our clients or anyone that you know essentially

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<v Speaker 5>asked us this question is that that there is a

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<v Speaker 5>huge downside risk to the US forecast and the tariffs

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<v Speaker 5>that twenty five percent essentially brings, you know, would impose

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<v Speaker 5>the US market, right, It would impact increased prices, It

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<v Speaker 5>would change the demand right to.

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<v Speaker 3>The US market.

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<v Speaker 5>Right now, we're expecting the US market to grow about

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<v Speaker 5>one point nine percent, and what which is actually US

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<v Speaker 5>and China are what are holding up that even that

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<v Speaker 5>flat zero point six percent growth that we're seeing globally,

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<v Speaker 5>but it was pulled down Both those large markets were

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<v Speaker 5>previously expected to grow higher. And if this twenty five

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<v Speaker 5>percent were to grow go into effect, you know, US

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<v Speaker 5>market would potentially even go into a decline.

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<v Speaker 2>We should say that that this data from you and

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<v Speaker 2>the newsflow, it doesn't just apply to the iPhone, right,

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<v Speaker 2>it also applies to other smartphone makers like on Android

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<v Speaker 2>os as well. But this has been our focus, which

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<v Speaker 2>is Apple and the pressure that Tim Cook has been

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<v Speaker 2>under from this administration. The supply chain is a question mark.

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<v Speaker 2>But right now, do you envisage any impact to pricing

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<v Speaker 2>of iPhone or any giant shift to where that company

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<v Speaker 2>manufactures that handset.

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<v Speaker 5>So I'll address the second part first, right even you know,

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<v Speaker 5>when when you know President Trump announced this potential twenty

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<v Speaker 5>five percent for anywhere he even said that it's not

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<v Speaker 5>just Apple, it would be to any brand that as

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<v Speaker 5>long as phones coming into the US were not made

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<v Speaker 5>in the US, it would they would face potentially twenty

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<v Speaker 5>five percent or anything wherever they lack, Right, We do

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<v Speaker 5>think that despite wherever, whatever, if you wherever the tears

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<v Speaker 5>happen to land eventually if they do, regardless of that,

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<v Speaker 5>we think smartphone OEMs will continue to diversify outside of

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<v Speaker 5>China and Vietnam and India. We said this in our

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<v Speaker 5>press release, will continue to be the two primary, you know,

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<v Speaker 5>global hubs for smartphone manufacturing for reasons that everyone on

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<v Speaker 5>your show that has come on to say, right, for

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<v Speaker 5>because of the supply chain ecosystem that has already been

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<v Speaker 5>established there prior to all this tariffs madness that began

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<v Speaker 5>earlier this year. Right, it's really hard. I think anyone

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<v Speaker 5>that says smartphone manufacturing, I mean, you understand that, I

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<v Speaker 5>understand the ideal ideology behind bringing manufacturing to the US,

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<v Speaker 5>And the question has also been asked, it's a dream,

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<v Speaker 5>but I you know, I don't see any reality where

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<v Speaker 5>that is possible. So it's just yeah, So that's the

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<v Speaker 5>reason why we do feel that it's continued, those two

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<v Speaker 5>regions are going to continue to be the focus of

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<v Speaker 5>oh m's diversification plans.

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<v Speaker 2>IDC Senior Research Director Nabila Popad's great to have you

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<v Speaker 2>on the show.

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<v Speaker 3>Thank you so much.

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<v Speaker 2>Now coming up, UiPath raised its outlook, but competition in

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<v Speaker 2>agentic WORKFOW solutions it's intensifying. We'll talk to CEO Daniel

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<v Speaker 2>Dines about what that means for his company.

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<v Speaker 3>That's next. This is Bloomberg Technology.

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<v Speaker 2>Automation software company UiPath raised its full years sales outlook

0:11:35.679 --> 0:11:38.720
<v Speaker 2>yesterday when it released its earnings. The company also stressed

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<v Speaker 2>that it's public sector clients renewed contracts. Let's get more

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<v Speaker 2>on this with UIPAR CEO Daniel Dines. Daniel, it's great

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<v Speaker 2>to have you back here on Bloomberg Technology. You know,

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<v Speaker 2>a point of discussion for most of the year so

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<v Speaker 2>far has been the impact on of joje on companies

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<v Speaker 2>just like yours that have government federal level contracts. I'm

0:12:03.520 --> 0:12:05.280
<v Speaker 2>trying to read between the lines and the transfer to

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<v Speaker 2>the earnest call. Was there any impact to you, positive

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<v Speaker 2>or negative from that doge activity.

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<v Speaker 7>Thank you for having me. Look, we had a great

0:12:16.400 --> 0:12:20.080
<v Speaker 7>event in dc A month ago and we talked to

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<v Speaker 7>it a lot of agency. There is a renewed interest

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<v Speaker 7>in agentic automation as a space, and we basically renewed

0:12:32.280 --> 0:12:35.480
<v Speaker 7>our contract. We have a great deal with the Air Force.

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<v Speaker 7>They are coming with a great initiative called Airmen which

0:12:40.360 --> 0:12:44.959
<v Speaker 7>is aiming at a very transformative of their business processes.

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<v Speaker 6>So on.

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<v Speaker 7>In one, I think it's a more positive environment in DC,

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<v Speaker 7>but still there is a lot of moving pieces in

0:12:57.960 --> 0:13:04.280
<v Speaker 7>transition there. From our perspective and our guidance, it's not

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<v Speaker 7>a big difference.

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<v Speaker 2>Many points to new ar R R additions and then

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<v Speaker 2>being low.

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<v Speaker 3>What then accounts for that.

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<v Speaker 7>Well, we continue to execute. Well, we just finish a

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<v Speaker 7>big transition. We had an entire year of changes in

0:13:26.600 --> 0:13:31.800
<v Speaker 7>the company. We accommodate everything to go really big in

0:13:31.920 --> 0:13:33.599
<v Speaker 7>agentic automation.

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<v Speaker 3>Basically, what is the growth picture?

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<v Speaker 2>Our analyst right that growth indicators a mix for UiPath.

0:13:42.880 --> 0:13:45.240
<v Speaker 2>Would you agree with that analysis of it being mixed?

0:13:45.280 --> 0:13:49.559
<v Speaker 2>And if you do see growth, where's it coming from?

0:13:49.679 --> 0:13:54.240
<v Speaker 7>Well, I think that agentic automation is a tremendous opportunity

0:13:54.320 --> 0:13:58.959
<v Speaker 7>and it's I think everybody agrees that this is gonna

0:13:59.000 --> 0:14:02.439
<v Speaker 7>be very trans formative on the business landscape.

0:14:02.720 --> 0:14:03.800
<v Speaker 3>We believe this is.

0:14:03.720 --> 0:14:06.840
<v Speaker 7>Going to be a bigger opportunity than RPA, and we

0:14:06.920 --> 0:14:11.600
<v Speaker 7>are really well positioned to capture a significant share of it.

0:14:11.880 --> 0:14:15.640
<v Speaker 7>So all in once, I think this is really our

0:14:15.679 --> 0:14:17.360
<v Speaker 7>biggest opportunity for growth.

0:14:18.720 --> 0:14:21.080
<v Speaker 2>I'm looking at the cost of inference right now, you know,

0:14:21.120 --> 0:14:24.760
<v Speaker 2>particularly in the context of companies just like yours trickling down.

0:14:26.320 --> 0:14:30.440
<v Speaker 2>A lot of companies are talking about the momentum that

0:14:30.520 --> 0:14:33.760
<v Speaker 2>agent KI is giving them. What's your point of difference.

0:14:33.880 --> 0:14:36.200
<v Speaker 2>What is it that you're able to offer that others

0:14:36.240 --> 0:14:36.480
<v Speaker 2>are not.

0:14:39.000 --> 0:14:41.200
<v Speaker 7>I think a lot of agents that we are seeing

0:14:41.200 --> 0:14:46.120
<v Speaker 7>today are conversational agents, but customers would like agents that

0:14:46.240 --> 0:14:51.000
<v Speaker 7>are deployed in the context of their existing business processes.

0:14:51.360 --> 0:14:55.520
<v Speaker 7>And how can you trust the agents? It's the main

0:14:55.560 --> 0:14:59.480
<v Speaker 7>point of the conversations. And we offer a technology to

0:14:59.800 --> 0:15:05.200
<v Speaker 7>ork straight between RPA bots and agents and humans that

0:15:05.520 --> 0:15:10.160
<v Speaker 7>really enhance the reliability of agents and the trust of customers.

0:15:12.680 --> 0:15:15.760
<v Speaker 2>Right now, what is the biggest cost consideration for you?

0:15:16.120 --> 0:15:20.800
<v Speaker 2>I talked about inference costs coming down. Even so, investors

0:15:20.800 --> 0:15:25.080
<v Speaker 2>in particular love to see a commitment to access to

0:15:25.120 --> 0:15:29.400
<v Speaker 2>compute and also just some like long term commitment that

0:15:29.440 --> 0:15:30.720
<v Speaker 2>the investment's worthwhile.

0:15:32.920 --> 0:15:34.920
<v Speaker 7>Yeah, I would not say that. In our business, the

0:15:34.960 --> 0:15:41.840
<v Speaker 7>infant cost is significant. The real cost comes with the

0:15:41.880 --> 0:15:47.720
<v Speaker 7>implementing of the agents. Still, the capability is required to

0:15:47.920 --> 0:15:55.360
<v Speaker 7>create really good agents that mimic the capability of humans

0:15:55.600 --> 0:15:58.720
<v Speaker 7>are kind of rare, and we are working a lot

0:15:58.760 --> 0:16:04.120
<v Speaker 7>to build technology that helped to democratize the ability to

0:16:04.160 --> 0:16:07.520
<v Speaker 7>build agents. To me, this is gonna be the real

0:16:07.600 --> 0:16:10.160
<v Speaker 7>cost of deploying a gentic automation.

0:16:10.320 --> 0:16:10.760
<v Speaker 8>That's key.

0:16:12.000 --> 0:16:15.520
<v Speaker 2>Daniel dines UiPath CEO, thank you so much for joining

0:16:15.600 --> 0:16:18.520
<v Speaker 2>us here on Bloomberg Technology. Now coming up, Microsoft's push

0:16:18.600 --> 0:16:22.120
<v Speaker 2>to get corporate customers on board with co Pilot seems

0:16:22.120 --> 0:16:23.840
<v Speaker 2>to be taking off. We've got the details on its

0:16:23.840 --> 0:16:25.520
<v Speaker 2>AI sales coming up next.

0:16:25.720 --> 0:16:26.960
<v Speaker 3>This is Bloomberg Technology.

0:16:42.200 --> 0:16:45.120
<v Speaker 2>A growing push for sovereign AI has led to a

0:16:45.120 --> 0:16:48.280
<v Speaker 2>wave of data center announcements, including one this week from

0:16:48.320 --> 0:16:51.280
<v Speaker 2>Bell Canada. It plans to invest hundreds of millions of

0:16:51.280 --> 0:16:54.560
<v Speaker 2>dollars to build AI data centers across the country, and

0:16:54.640 --> 0:16:58.040
<v Speaker 2>it is named chip startup Grock as the project's exclusive

0:16:58.160 --> 0:17:01.960
<v Speaker 2>inference partner. Grock CEO Jonathan Ross spoke with Caroline Hyde

0:17:02.000 --> 0:17:05.199
<v Speaker 2>about sovereign AI, but also US chip curbs on China.

0:17:05.800 --> 0:17:08.720
<v Speaker 9>From grox's beginning, we have done no business in China,

0:17:08.880 --> 0:17:10.920
<v Speaker 9>and this is not a geopolitical thing. This is just

0:17:10.960 --> 0:17:13.840
<v Speaker 9>a shrewd business thing. We saw all of these very

0:17:13.880 --> 0:17:17.119
<v Speaker 9>large tech companies go into China and lose over and

0:17:17.119 --> 0:17:18.879
<v Speaker 9>over and again, and there's just a thumb on the

0:17:18.920 --> 0:17:23.560
<v Speaker 9>scale for any Western company. I hope that someday China

0:17:23.640 --> 0:17:27.240
<v Speaker 9>allows real competition because real competition makes people stronger, and

0:17:27.280 --> 0:17:30.240
<v Speaker 9>I want to compete against those Chinese companies. But until

0:17:30.240 --> 0:17:32.760
<v Speaker 9>they allow real competition, we can't do that. So we've

0:17:32.800 --> 0:17:36.080
<v Speaker 9>blocked all Chinese companies from having access to our API.

0:17:36.400 --> 0:17:38.280
<v Speaker 9>We will not sell chips in China because they're just

0:17:38.280 --> 0:17:40.399
<v Speaker 9>going to reverse engineer them and try and build them themselves,

0:17:40.400 --> 0:17:43.040
<v Speaker 9>and they're not going to compete fairly. As a result,

0:17:43.200 --> 0:17:46.320
<v Speaker 9>when we do these deals, we're not allowing Chinese companies

0:17:46.320 --> 0:17:49.240
<v Speaker 9>to run on them, and we do build operate transfer.

0:17:49.280 --> 0:17:51.960
<v Speaker 9>In these sovereign cases, we're doing build operate, so we're

0:17:52.000 --> 0:17:55.159
<v Speaker 9>the ones operating that, and that actually gives commerce and

0:17:55.200 --> 0:17:57.879
<v Speaker 9>others a lot of comfort that Chinese companies aren't going

0:17:57.880 --> 0:17:58.560
<v Speaker 9>to be getting.

0:17:58.280 --> 0:18:01.520
<v Speaker 10>Access, But does the strictions on say in video selling

0:18:01.640 --> 0:18:04.240
<v Speaker 10>H twenties, as Jensen would say, mean that China just

0:18:04.280 --> 0:18:04.960
<v Speaker 10>gets better at.

0:18:04.840 --> 0:18:05.439
<v Speaker 3>Doing it themselves.

0:18:05.480 --> 0:18:07.920
<v Speaker 10>In a Huawei will be able to compete with growth in.

0:18:07.840 --> 0:18:12.440
<v Speaker 9>The future potentially. However, the reality is if you enable

0:18:12.480 --> 0:18:14.720
<v Speaker 9>people now, then they're going to be able to use

0:18:14.720 --> 0:18:17.040
<v Speaker 9>that advantage to keep growing quicker. We're going to be

0:18:17.080 --> 0:18:19.639
<v Speaker 9>using AI to design our chips, We're going to be

0:18:19.720 --> 0:18:22.800
<v Speaker 9>using AI to design our software, So why would you

0:18:22.800 --> 0:18:25.359
<v Speaker 9>give that advantage? I think it's different going back to

0:18:25.400 --> 0:18:29.040
<v Speaker 9>information age technology, it's about replicating and distributing. Compute is

0:18:29.080 --> 0:18:32.000
<v Speaker 9>about doing something specific. If you don't have the compute,

0:18:32.000 --> 0:18:36.000
<v Speaker 9>you can't do it, whereas information knowledge sort of diffuses

0:18:36.119 --> 0:18:39.239
<v Speaker 9>and you'll catch up. With generative age technology you can

0:18:39.280 --> 0:18:39.840
<v Speaker 9>pull ahead.

0:18:40.800 --> 0:18:44.199
<v Speaker 10>You talk about wand in competition and to be competitive

0:18:44.600 --> 0:18:47.359
<v Speaker 10>in China, for example, what about the competition within VideA.

0:18:47.640 --> 0:18:49.720
<v Speaker 10>How do you stand compared to AMD and the other

0:18:49.800 --> 0:18:51.680
<v Speaker 10>offerings Here in the United States.

0:18:51.440 --> 0:18:53.040
<v Speaker 9>We actually think we're one of the best things that's

0:18:53.040 --> 0:18:57.359
<v Speaker 9>ever happened to in Vidia shareholders. So in Vidia sells

0:18:57.400 --> 0:18:59.960
<v Speaker 9>a product that is a premium product. It's a luxury good,

0:19:00.280 --> 0:19:02.919
<v Speaker 9>it's for training the models. When you train a model,

0:19:03.119 --> 0:19:05.399
<v Speaker 9>you're willing to spend more money because you get to

0:19:05.400 --> 0:19:08.920
<v Speaker 9>amortize that across an enormous number of users. If in

0:19:09.040 --> 0:19:11.639
<v Speaker 9>Vidia continues focusing on inference, which they have to do

0:19:11.760 --> 0:19:14.479
<v Speaker 9>right now because there isn't enough inference capacity, they're going

0:19:14.520 --> 0:19:16.280
<v Speaker 9>to have to bring their margins down. They're going to

0:19:16.359 --> 0:19:18.360
<v Speaker 9>have to sell their chips for a lot less. Remember,

0:19:18.640 --> 0:19:22.119
<v Speaker 9>our cost is much less than in Vidia's cost. On

0:19:22.200 --> 0:19:26.320
<v Speaker 9>top of that, higher volume, lower margin. And so the

0:19:26.359 --> 0:19:29.479
<v Speaker 9>more inference compute we deploy, the more demand there is

0:19:29.480 --> 0:19:31.760
<v Speaker 9>for training compute. The more demand for training compute, the

0:19:31.800 --> 0:19:34.240
<v Speaker 9>more GPUs and VideA sells. And the one thing that's

0:19:34.320 --> 0:19:36.840
<v Speaker 9>really important here in Video wants to do between three

0:19:36.840 --> 0:19:39.880
<v Speaker 9>and five million GPUs for AI this year. But that's

0:19:39.960 --> 0:19:43.080
<v Speaker 9>based on what's called HPM high bandwidth memory. It's this

0:19:43.240 --> 0:19:45.960
<v Speaker 9>very scarce component. They can make as many GPU chips

0:19:46.000 --> 0:19:47.199
<v Speaker 9>as they want, they can't make as much of the

0:19:47.200 --> 0:19:49.359
<v Speaker 9>memories they want. Those chips are going to be built

0:19:49.359 --> 0:19:51.119
<v Speaker 9>and sold, and the only question is what are they

0:19:51.119 --> 0:19:53.320
<v Speaker 9>going to be sold to do when we come in

0:19:53.640 --> 0:19:56.639
<v Speaker 9>and we sell inference chips than what we're doing is

0:19:56.640 --> 0:19:58.520
<v Speaker 9>we're allowing those GPUs to be sold into training, which

0:19:58.560 --> 0:20:00.639
<v Speaker 9>is a higher margin business. The video is going to

0:20:00.720 --> 0:20:03.320
<v Speaker 9>make more profit thanks to us.

0:20:05.520 --> 0:20:08.480
<v Speaker 2>All Right, we have some breaking news crossing the Bloomberg terminal.

0:20:08.720 --> 0:20:13.080
<v Speaker 2>Utel Sat satellite based internet providers in talks to Rays

0:20:13.480 --> 0:20:18.240
<v Speaker 2>one point five billion euros. This is interesting because in Europe,

0:20:18.280 --> 0:20:21.280
<v Speaker 2>the continent's hoping that you tel Sat will be able

0:20:21.720 --> 0:20:25.720
<v Speaker 2>to displace and compete against the likes of Elon, Musk

0:20:25.720 --> 0:20:27.000
<v Speaker 2>Starlink in Europe.

0:20:27.119 --> 0:20:28.040
<v Speaker 3>That's the red headline.

0:20:28.080 --> 0:20:31.480
<v Speaker 2>You tail Satin talks to Rays one point five billion

0:20:31.920 --> 0:20:35.840
<v Speaker 2>euros with a doubling of the steak from French entities.

0:20:35.880 --> 0:20:37.840
<v Speaker 3>We get more on that story as we get more

0:20:37.840 --> 0:20:38.119
<v Speaker 3>on it.

0:20:38.200 --> 0:20:39.760
<v Speaker 2>All right, let's get back to what's happening in the

0:20:39.760 --> 0:20:44.200
<v Speaker 2>world of AI, and Microsoft is focused in driving adoption

0:20:44.400 --> 0:20:46.720
<v Speaker 2>of its AI tool co Pilot, and at a town

0:20:46.720 --> 0:20:49.240
<v Speaker 2>hall this week, it touted its progress.

0:20:49.280 --> 0:20:51.840
<v Speaker 3>Who broke the story, Bloomberg's Brody Ford.

0:20:51.840 --> 0:20:53.920
<v Speaker 2>I think this is really interesting, right because it's quick

0:20:53.960 --> 0:20:56.320
<v Speaker 2>on the heels of this deep dive we did in

0:20:56.400 --> 0:21:00.000
<v Speaker 2>Business Week about co Pilot, how it happened, how it launched,

0:21:00.119 --> 0:21:03.800
<v Speaker 2>What Microsoft shypes are for it, what you reported are

0:21:04.119 --> 0:21:09.360
<v Speaker 2>names across various industries, big corporate names that are doing deals.

0:21:10.640 --> 0:21:10.840
<v Speaker 5>Right.

0:21:11.000 --> 0:21:14.840
<v Speaker 11>Yeah, The background here is that Microsoft salesforce companies like

0:21:14.920 --> 0:21:17.879
<v Speaker 11>them they have these AI tools, right. I mean, in

0:21:17.880 --> 0:21:20.720
<v Speaker 11>the consumer space, Chat, GPT and tools like it have

0:21:20.880 --> 0:21:24.359
<v Speaker 11>ramped incredibly. In the enterprise, it hasn't been quite as

0:21:24.400 --> 0:21:28.320
<v Speaker 11>easy of an adoption path, and so with tools like Copilot,

0:21:28.400 --> 0:21:32.720
<v Speaker 11>Microsoft's AI assistance, we don't have great intel over how

0:21:32.760 --> 0:21:35.000
<v Speaker 11>many folks are really using it, how many folks are

0:21:35.040 --> 0:21:38.840
<v Speaker 11>really paying for it. What we learned from the meeting yesterday,

0:21:38.920 --> 0:21:42.359
<v Speaker 11>which sources we're telling us about, is that you know,

0:21:42.640 --> 0:21:45.920
<v Speaker 11>there are dozens of customers who are having over one

0:21:45.960 --> 0:21:49.720
<v Speaker 11>hundred thousand paid users. That's a pretty significant amount. I mean,

0:21:49.760 --> 0:21:52.199
<v Speaker 11>of course, you know there's some discounting in that, but

0:21:52.720 --> 0:21:56.480
<v Speaker 11>this is a sign that adoption is ramping, maybe more

0:21:56.640 --> 0:21:58.840
<v Speaker 11>than investors had been appreciating.

0:22:00.160 --> 0:22:00.840
<v Speaker 3>Your reporting.

0:22:00.880 --> 0:22:05.120
<v Speaker 2>We note that Microsoft CEO Sati Endella is very closely

0:22:05.200 --> 0:22:09.680
<v Speaker 2>tracking all kinds of data, including who is using co

0:22:09.800 --> 0:22:11.159
<v Speaker 2>pilot and how they're using it.

0:22:11.200 --> 0:22:12.880
<v Speaker 3>Why is that important, right?

0:22:12.920 --> 0:22:15.760
<v Speaker 11>I Mean, what's really important is that you don't have shelfware,

0:22:15.840 --> 0:22:18.840
<v Speaker 11>but you don't buy one hundred thousand licenses, but you know,

0:22:19.040 --> 0:22:22.080
<v Speaker 11>fifty people use it in finance, right. I mean, this

0:22:22.160 --> 0:22:24.560
<v Speaker 11>is the classic problem with software where maybe you can

0:22:24.600 --> 0:22:26.520
<v Speaker 11>sell a lot of things, but you have to really

0:22:26.520 --> 0:22:28.680
<v Speaker 11>make sure they're using it.

0:22:28.760 --> 0:22:31.560
<v Speaker 2>Bloomberg's Brodie Ford another excellent piece of reporting.

0:22:31.600 --> 0:22:32.360
<v Speaker 3>Thank you very much.

0:22:32.440 --> 0:22:36.560
<v Speaker 2>Okay, coming up, Patrick McGoldrick from JP Morgan Private Capital

0:22:36.680 --> 0:22:40.440
<v Speaker 2>joins us to talk about its approach to AI investment opportunities.

0:22:40.720 --> 0:22:55.119
<v Speaker 2>Their conversation's next, This is Bloomberg Technology. Welcomes back to

0:22:55.160 --> 0:22:58.119
<v Speaker 2>Bloomberg Technology, Amed Ludlow in San Francisco. It's kind of

0:22:58.160 --> 0:23:00.879
<v Speaker 2>like the last day of technology earning and we're seeing

0:23:00.880 --> 0:23:03.720
<v Speaker 2>movers in the market on some numbers that got posted

0:23:03.760 --> 0:23:07.160
<v Speaker 2>last night, those of Dell and Marvel. In Dell's case,

0:23:07.200 --> 0:23:09.720
<v Speaker 2>it was all about the profit outlook in topped estimates.

0:23:09.920 --> 0:23:13.480
<v Speaker 2>There is clearly a backlog for AI serve demand, but

0:23:13.600 --> 0:23:17.240
<v Speaker 2>shares are a little bit softer. Marvel a slightly different story.

0:23:17.600 --> 0:23:21.320
<v Speaker 2>They kind of have like strong sales targets, they've won

0:23:21.400 --> 0:23:23.480
<v Speaker 2>some business and they were pretty clear with the market,

0:23:23.480 --> 0:23:27.320
<v Speaker 2>but investors still tip it on that chip name stock

0:23:27.359 --> 0:23:30.200
<v Speaker 2>down five percent. That's having an impact at the index

0:23:30.320 --> 0:23:33.439
<v Speaker 2>level as well. Let's go from public markets now to

0:23:33.480 --> 0:23:37.760
<v Speaker 2>private markets. JP Morgan private Capital's Growth Equity Partners. It's

0:23:37.760 --> 0:23:41.000
<v Speaker 2>a one billion dollar fund focusing on Series B right

0:23:41.040 --> 0:23:44.680
<v Speaker 2>through the pre IPO startups. Managing partner Patrick McGoldrick joins

0:23:44.760 --> 0:23:48.080
<v Speaker 2>us the focus right now the AI opportunity. I find

0:23:48.119 --> 0:23:51.280
<v Speaker 2>this so interesting and it's part of today's VC spotlight.

0:23:52.040 --> 0:23:54.359
<v Speaker 2>In my world, when I break a story about an

0:23:54.400 --> 0:23:58.760
<v Speaker 2>AI startup or a new round, it's so interesting to

0:23:58.800 --> 0:24:02.600
<v Speaker 2>look at the cat table traditional venture capital, traditional but

0:24:02.680 --> 0:24:05.680
<v Speaker 2>also people like you coming in more in the private

0:24:05.720 --> 0:24:08.520
<v Speaker 2>growth equity space. Would you just talk a bit about

0:24:08.520 --> 0:24:10.280
<v Speaker 2>that business model and what you try to do.

0:24:10.960 --> 0:24:13.160
<v Speaker 12>Sure, and thanks for having me on today. I appreciate

0:24:13.320 --> 0:24:16.159
<v Speaker 12>the opportunity. So the way we position our strategy is

0:24:16.200 --> 0:24:18.880
<v Speaker 12>to operate like a traditional venture and growth equity investor.

0:24:18.960 --> 0:24:22.399
<v Speaker 12>So we started investing at the earlier stages of a

0:24:22.400 --> 0:24:25.720
<v Speaker 12>company's formation, Series B through pre IPO on the technology

0:24:25.720 --> 0:24:29.920
<v Speaker 12>and consumer side, all the way through that last inflection.

0:24:29.600 --> 0:24:30.800
<v Speaker 8>Point before going public.

0:24:31.080 --> 0:24:33.919
<v Speaker 12>I think for us, we seek to leverage the whole

0:24:34.080 --> 0:24:36.920
<v Speaker 12>firm to deliver value to companies, and in a world

0:24:36.960 --> 0:24:41.720
<v Speaker 12>where capital is just that, but value add in changing

0:24:41.760 --> 0:24:45.040
<v Speaker 12>the inflection curve, of a company's growth de risking. We

0:24:45.080 --> 0:24:47.399
<v Speaker 12>think JP Morgan is well suited to be that partner

0:24:47.440 --> 0:24:47.879
<v Speaker 12>of choice.

0:24:49.160 --> 0:24:53.560
<v Speaker 2>So interesting you're talking about leveraging the full scale of

0:24:53.640 --> 0:24:54.359
<v Speaker 2>JP Morgan.

0:24:54.560 --> 0:24:55.359
<v Speaker 3>Right as you're pitched.

0:24:55.600 --> 0:24:58.600
<v Speaker 2>The traditional VC would say, don't just take our check,

0:24:58.680 --> 0:25:02.800
<v Speaker 2>take our operators. Many of us are entrepreneurs or startup founders.

0:25:03.200 --> 0:25:05.000
<v Speaker 2>Your pitches, we're JP Morgan.

0:25:05.960 --> 0:25:08.439
<v Speaker 12>Yes, I think in the simplest of essence, of course,

0:25:08.480 --> 0:25:10.480
<v Speaker 12>I think we're privileged to be part of an organization

0:25:10.520 --> 0:25:13.399
<v Speaker 12>that spends eighteen billion dollars a year in technology spend.

0:25:13.480 --> 0:25:16.680
<v Speaker 8>We have sixty three thousand technologists.

0:25:16.000 --> 0:25:18.320
<v Speaker 12>And I think what is really important to recognize is

0:25:18.359 --> 0:25:21.439
<v Speaker 12>we will work with companies across our firm as early

0:25:21.480 --> 0:25:24.640
<v Speaker 12>as the seed stage, so we're on the hunt for

0:25:24.760 --> 0:25:28.680
<v Speaker 12>exceptional technologies. Now as investors, of course, first and foremost

0:25:28.720 --> 0:25:31.640
<v Speaker 12>we assess product market fit, the strength of the management team.

0:25:31.680 --> 0:25:35.320
<v Speaker 12>But then where can we pair in those relationships covering

0:25:35.359 --> 0:25:37.600
<v Speaker 12>ninety percent of the Fortune five hundred or forty five

0:25:37.640 --> 0:25:40.240
<v Speaker 12>thousand private companies, So we have the privilege of those

0:25:40.280 --> 0:25:42.960
<v Speaker 12>operators that other VC firms have. But I think the

0:25:43.000 --> 0:25:45.480
<v Speaker 12>global footprint of a firm like JP.

0:25:45.359 --> 0:25:49.520
<v Speaker 3>Morgan, what are you saying in private markets right now?

0:25:49.960 --> 0:25:53.240
<v Speaker 12>Yeah, it's a complicated question. It depends on the topic.

0:25:53.280 --> 0:25:55.720
<v Speaker 12>But let's start with where we see the investment opportunity set.

0:25:55.720 --> 0:25:57.840
<v Speaker 12>I think for us, we're spending a lot of time

0:25:58.200 --> 0:26:03.160
<v Speaker 12>in areas like artificial intelligence and cybersecurity, both incredibly resilient.

0:26:02.680 --> 0:26:04.200
<v Speaker 8>From a tech spend perspective.

0:26:04.240 --> 0:26:08.119
<v Speaker 12>There is a recent review of chief information officers and

0:26:08.200 --> 0:26:11.359
<v Speaker 12>chief technology officers budgeting priorities, and I think for different reasons,

0:26:11.359 --> 0:26:15.359
<v Speaker 12>you're seeing increased commitments to those areas. In AI, I

0:26:15.400 --> 0:26:18.879
<v Speaker 12>think it's a world of now having gone from experimentation

0:26:19.080 --> 0:26:22.359
<v Speaker 12>to actual deployment. Over sixty five percent of companies are

0:26:22.359 --> 0:26:24.160
<v Speaker 12>now deploying AI in.

0:26:24.200 --> 0:26:25.800
<v Speaker 8>Their full production suite.

0:26:26.440 --> 0:26:29.639
<v Speaker 12>Those companies are now automating tasks, they're creating efficiency and

0:26:29.680 --> 0:26:34.120
<v Speaker 12>making a more delightful consumer and enterprise experience. In cyber unfortunately,

0:26:34.320 --> 0:26:37.040
<v Speaker 12>you could have a version of me that's virtually produced

0:26:37.040 --> 0:26:40.760
<v Speaker 12>my cadence inflection, a little bit of my positioning, and

0:26:41.080 --> 0:26:42.959
<v Speaker 12>you'd have to be able to protect against that. So

0:26:43.440 --> 0:26:47.159
<v Speaker 12>that defensive posture is critical. It's why even in tougher

0:26:47.520 --> 0:26:51.920
<v Speaker 12>macro environments, the defensiveness of the spend there is very

0:26:51.960 --> 0:26:54.040
<v Speaker 12>clear and so you'll see that reflected in some of

0:26:54.040 --> 0:26:55.520
<v Speaker 12>our portfolio companies.

0:26:55.920 --> 0:26:58.440
<v Speaker 2>Some of your portfolio companies we just showed Alpha Sense.

0:26:58.480 --> 0:27:01.280
<v Speaker 2>Of course, the maker of Cursor such a hot property

0:27:01.359 --> 0:27:03.919
<v Speaker 2>right now, tell me what's going on with that. But

0:27:03.960 --> 0:27:08.280
<v Speaker 2>also data breaks like data Breaks recently has been relying

0:27:08.359 --> 0:27:13.240
<v Speaker 2>on tenders like employee liquidity rather than a primary raise.

0:27:13.600 --> 0:27:17.400
<v Speaker 2>How have you navigated those two mechanisms in these two

0:27:17.560 --> 0:27:18.760
<v Speaker 2>hot names in the world of AI.

0:27:19.160 --> 0:27:22.560
<v Speaker 12>Well, let's start with Alpha Sense, because I think that

0:27:22.600 --> 0:27:24.840
<v Speaker 12>company think of it really as a market research and

0:27:24.880 --> 0:27:27.520
<v Speaker 12>intelligence platform that in two thousand and eight had the

0:27:27.560 --> 0:27:32.040
<v Speaker 12>idea of bringing publicly available data in the world of markets,

0:27:32.680 --> 0:27:36.040
<v Speaker 12>also accessing the research reports that are put up by

0:27:36.040 --> 0:27:40.119
<v Speaker 12>Wall Street firms, digesting that and giving research analysts, corporate

0:27:40.160 --> 0:27:43.680
<v Speaker 12>development arms as well as portfolio managers the right solutions

0:27:43.680 --> 0:27:45.840
<v Speaker 12>at their fingertips to make informed decisions.

0:27:46.160 --> 0:27:47.320
<v Speaker 8>With the auDA end of AI.

0:27:47.520 --> 0:27:49.959
<v Speaker 12>That's gotten even more acute and clear as how they

0:27:49.960 --> 0:27:53.639
<v Speaker 12>deliver value. And they recently acquired a company called Tigis,

0:27:53.960 --> 0:27:57.680
<v Speaker 12>which provides private market perspective, so customer interviews that could

0:27:57.680 --> 0:28:01.720
<v Speaker 12>transcribe that marriage of data is critical to making better

0:28:01.800 --> 0:28:03.560
<v Speaker 12>decisions on data Bricks.

0:28:03.560 --> 0:28:04.640
<v Speaker 8>You bring up an interesting point.

0:28:04.760 --> 0:28:07.120
<v Speaker 12>I think the evolution of the private markets are such

0:28:07.160 --> 0:28:10.840
<v Speaker 12>that companies are staying private longer in order to provide liquidity.

0:28:10.880 --> 0:28:16.000
<v Speaker 12>They look to access this tender solutions and letting employees.

0:28:15.600 --> 0:28:16.520
<v Speaker 8>Seek some liquidity.

0:28:16.960 --> 0:28:20.600
<v Speaker 12>For us, we want to be active in names like

0:28:20.680 --> 0:28:23.080
<v Speaker 12>Data Bricks, where it's critical in the world of infrastructure

0:28:23.119 --> 0:28:26.360
<v Speaker 12>for AI growing well in excess of the public markets

0:28:26.359 --> 0:28:28.960
<v Speaker 12>with an exceptional management team, and so we're thrilled to

0:28:28.960 --> 0:28:31.000
<v Speaker 12>be involved in both of those and think they're critical

0:28:31.040 --> 0:28:32.160
<v Speaker 12>in this new advent of AI.

0:28:32.880 --> 0:28:35.880
<v Speaker 2>Patrick, we just have thirty seconds. But you see some

0:28:35.960 --> 0:28:38.240
<v Speaker 2>kind of exit coming in either of those names.

0:28:38.520 --> 0:28:40.760
<v Speaker 12>Well, I wouldn't want to speculate on that too much.

0:28:40.800 --> 0:28:42.440
<v Speaker 12>I think the management teams are better suits to do that.

0:28:42.480 --> 0:28:44.520
<v Speaker 12>What I would say about the exit environment more broadly

0:28:44.640 --> 0:28:47.600
<v Speaker 12>is we've gone from a faucet that's completely shut off

0:28:47.640 --> 0:28:51.120
<v Speaker 12>to a trickle where you have companies like in health

0:28:51.600 --> 0:28:54.360
<v Speaker 12>service Titan of course Core Weave that have used the

0:28:54.360 --> 0:28:56.080
<v Speaker 12>public markets, which is important.

0:28:56.480 --> 0:28:58.720
<v Speaker 8>Hopefully the back half of the year produces.

0:28:58.320 --> 0:29:01.360
<v Speaker 12>More of that, but they are companies that could effectively

0:29:01.360 --> 0:29:03.640
<v Speaker 12>go public by virtue of their performance.

0:29:03.800 --> 0:29:05.840
<v Speaker 8>Again, the management team and the market.

0:29:05.560 --> 0:29:09.960
<v Speaker 2>Size, Patrick, open up that tap next time. Come back

0:29:10.000 --> 0:29:12.120
<v Speaker 2>on and tell us when you have an ex Patrichan McGoldrick,

0:29:12.160 --> 0:29:15.720
<v Speaker 2>Managing Partner, JP Morgan Private Capital, Thank you very much.

0:29:15.800 --> 0:29:17.160
<v Speaker 3>Coming up, we.

0:29:17.120 --> 0:29:21.520
<v Speaker 2>Speak with AWS CEO Matt Garman in an exclusive conversation.

0:29:22.160 --> 0:29:26.640
<v Speaker 2>One year in the role, so much has happened, from

0:29:26.800 --> 0:29:30.800
<v Speaker 2>the sort of hyperscale perspective right through to the models

0:29:30.840 --> 0:29:33.400
<v Speaker 2>that AWS is hosting large through Bedrock.

0:29:33.960 --> 0:29:36.040
<v Speaker 3>We also got some breaking news. Let's take a look

0:29:36.000 --> 0:29:39.360
<v Speaker 3>at DJT hitting session higher, raising his decline.

0:29:39.520 --> 0:29:43.120
<v Speaker 2>Just confirmation the company's closed about two point four billion

0:29:43.160 --> 0:29:46.440
<v Speaker 2>dollars in a bitcoin treasury deal, something.

0:29:46.160 --> 0:29:48.640
<v Speaker 3>We brought you a little bit of earlier this week.

0:29:48.960 --> 0:30:05.000
<v Speaker 3>We'll be right back. Don't go far. This is Bloomberg Technology.

0:30:05.960 --> 0:30:09.360
<v Speaker 2>Welcome to our Bloomberg radio and television audiences worldwide. We

0:30:09.400 --> 0:30:14.120
<v Speaker 2>go right now to a conversation with Matt Garman, AWS CEO.

0:30:14.640 --> 0:30:16.000
<v Speaker 3>Matt, it's good to catch up.

0:30:16.280 --> 0:30:19.280
<v Speaker 2>It has been basically one year that you've been in

0:30:19.280 --> 0:30:20.840
<v Speaker 2>the role as AWS CEO.

0:30:21.760 --> 0:30:22.440
<v Speaker 3>Is a place to.

0:30:22.520 --> 0:30:26.360
<v Speaker 2>Start what has been the biggest achievement in that time

0:30:26.720 --> 0:30:27.640
<v Speaker 2>for AWS.

0:30:28.680 --> 0:30:30.520
<v Speaker 13>Yeah, thanks for having me on. It's nice to be

0:30:30.560 --> 0:30:34.320
<v Speaker 13>here again. Yeah, It's been a fantastic year of innovation.

0:30:35.160 --> 0:30:38.400
<v Speaker 13>It's really been incredible, and as I look out there,

0:30:38.800 --> 0:30:40.640
<v Speaker 13>one of the things that I've been most excited about

0:30:40.720 --> 0:30:44.400
<v Speaker 13>is how fast our customers are innovating and ten adopting

0:30:44.480 --> 0:30:47.040
<v Speaker 13>many of the new technologies that we have. And as

0:30:47.040 --> 0:30:50.560
<v Speaker 13>you think about customers that are on this cloud migration journey,

0:30:50.760 --> 0:30:52.520
<v Speaker 13>many of them have been doing that for over the

0:30:52.600 --> 0:30:55.560
<v Speaker 13>last several years, but this year in particular, that we've

0:30:55.600 --> 0:30:59.440
<v Speaker 13>really seen an explosion of AI technologies, of agentic technologies,

0:30:59.760 --> 0:31:03.720
<v Speaker 13>and increasingly we're seeing more and more customers move their

0:31:03.880 --> 0:31:06.880
<v Speaker 13>entire estates into the cloud and AWS.

0:31:06.920 --> 0:31:08.480
<v Speaker 6>So it's been really fun to see.

0:31:08.520 --> 0:31:11.520
<v Speaker 13>It's been an incredible pace of technology and it's been

0:31:11.560 --> 0:31:12.600
<v Speaker 13>a really fun first year.

0:31:13.640 --> 0:31:16.320
<v Speaker 2>The moment that investors kind of sat up and paid

0:31:16.320 --> 0:31:21.680
<v Speaker 2>attention was when Amazon said that it's AI business was

0:31:21.720 --> 0:31:24.680
<v Speaker 2>at a multi billion dollar run rate in terms of sales.

0:31:25.080 --> 0:31:27.760
<v Speaker 2>What we don't understand as well is what proportion of

0:31:27.800 --> 0:31:29.680
<v Speaker 2>that is AWS infrastructure.

0:31:30.800 --> 0:31:33.440
<v Speaker 13>Yeah, that is AWS, right, and so the key is

0:31:33.480 --> 0:31:37.320
<v Speaker 13>that's a mix of customers running their own models. Some

0:31:37.360 --> 0:31:40.160
<v Speaker 13>of that is on Amazon Bedrock, which is our own

0:31:40.200 --> 0:31:43.480
<v Speaker 13>hosted models where we have first party models like Amazon Nova,

0:31:43.520 --> 0:31:45.400
<v Speaker 13>as well as many of the third party models like

0:31:45.440 --> 0:31:48.800
<v Speaker 13>anthropics models, and some of those are applications things like

0:31:49.440 --> 0:31:54.520
<v Speaker 13>Amazon Q which helps people do automated software developments, as

0:31:54.520 --> 0:31:56.720
<v Speaker 13>well as a host of other capabilities, and so there's

0:31:56.760 --> 0:31:58.480
<v Speaker 13>a mix of that. And I think part of the

0:31:58.480 --> 0:32:01.040
<v Speaker 13>most interesting thing about being at a multi billion dollar

0:32:01.160 --> 0:32:04.040
<v Speaker 13>run rate is we're at the very earliest stages of

0:32:04.080 --> 0:32:07.600
<v Speaker 13>how AI is going to completely transform every single customer

0:32:07.600 --> 0:32:09.959
<v Speaker 13>out there. And we talk to customers and we look

0:32:10.000 --> 0:32:13.120
<v Speaker 13>at where the technology landscape is, and we firmly believe

0:32:13.200 --> 0:32:16.520
<v Speaker 13>that every single business, every single industry, and really every

0:32:16.560 --> 0:32:19.640
<v Speaker 13>single job is going to be fundamentally transformed by AI.

0:32:20.120 --> 0:32:22.120
<v Speaker 13>And I think we're starting to see the early start

0:32:22.320 --> 0:32:24.440
<v Speaker 13>the stages of that. But again, we're just at the

0:32:24.560 --> 0:32:26.880
<v Speaker 13>very earliest stages that I think what's going to be possible,

0:32:27.120 --> 0:32:29.040
<v Speaker 13>and so that multi billion dollar business that we have

0:32:29.080 --> 0:32:30.680
<v Speaker 13>today is really just the start.

0:32:31.760 --> 0:32:35.720
<v Speaker 3>Can you give me a generative AI revenue number.

0:32:36.680 --> 0:32:38.920
<v Speaker 6>For the world or for awls?

0:32:38.960 --> 0:32:41.720
<v Speaker 2>Are you guys for AWS? Maybe Amazon as a whole.

0:32:41.920 --> 0:32:44.920
<v Speaker 13>Yeah, Like I said, we are in multiple billions of dollars,

0:32:45.280 --> 0:32:48.920
<v Speaker 13>and that's for customers using AWS. We also use lots

0:32:48.960 --> 0:32:51.840
<v Speaker 13>of generative AI inside of Amazon for a wide range

0:32:51.840 --> 0:32:54.720
<v Speaker 13>of things. We use it to optimize our fulfillment centers.

0:32:55.160 --> 0:32:56.920
<v Speaker 13>We use it when you go to the retail site

0:32:56.960 --> 0:33:01.320
<v Speaker 13>to summarize reviews, or to help customer find products in

0:33:01.360 --> 0:33:04.920
<v Speaker 13>a faster and more interesting way. We use AI in

0:33:05.160 --> 0:33:08.840
<v Speaker 13>Alexa in our new Alexa Plus offering, where we conversationally

0:33:08.880 --> 0:33:13.360
<v Speaker 13>talk to customers through the Alexa interface and help them

0:33:13.360 --> 0:33:16.320
<v Speaker 13>accomplish things through voice that they were never able to

0:33:16.320 --> 0:33:19.960
<v Speaker 13>do before. So every single aspect of what Amazon does

0:33:20.760 --> 0:33:24.920
<v Speaker 13>leverages AI, and our customers are exactly the same. Customers

0:33:24.960 --> 0:33:28.240
<v Speaker 13>are looking to AWS to completely change, whether it's their

0:33:28.280 --> 0:33:32.560
<v Speaker 13>contact centers through something like Amazon Connect where it shows

0:33:32.640 --> 0:33:35.000
<v Speaker 13>AI capabilities so that you don't have to go program

0:33:35.000 --> 0:33:37.600
<v Speaker 13>it all the way down to our custom chips or

0:33:37.720 --> 0:33:40.800
<v Speaker 13>Nvidia processors, or anything where customers at the metal are

0:33:40.800 --> 0:33:43.200
<v Speaker 13>building their own models. We have the whole range of

0:33:43.200 --> 0:33:46.680
<v Speaker 13>people that are building AI on top of AWS, as

0:33:46.680 --> 0:33:48.080
<v Speaker 13>well as Amazon themselves.

0:33:48.960 --> 0:33:54.200
<v Speaker 2>We always credit AWS as being number one HYPERSCALA. But

0:33:54.640 --> 0:33:57.080
<v Speaker 2>just what you said there about what the client's using

0:33:57.640 --> 0:34:01.760
<v Speaker 2>in the silicon level through the capacity, it would really

0:34:01.880 --> 0:34:05.560
<v Speaker 2>help if you could proportionately tell me what percentage of

0:34:05.600 --> 0:34:09.120
<v Speaker 2>workloads are being run for training and which proportion of

0:34:09.560 --> 0:34:11.239
<v Speaker 2>workloads being run for inference.

0:34:11.600 --> 0:34:14.680
<v Speaker 6>Sure, yeah, and that changes over time. I think.

0:34:14.719 --> 0:34:18.279
<v Speaker 13>Look as we progress over time, more and more of

0:34:18.320 --> 0:34:20.920
<v Speaker 13>the AI workloads are being inference. I'd say in the

0:34:20.960 --> 0:34:24.239
<v Speaker 13>early stages of AI and generate of AI, a lot

0:34:24.280 --> 0:34:26.520
<v Speaker 13>of that usage was dominated by training as people were

0:34:26.520 --> 0:34:29.760
<v Speaker 13>building these very large models with small amounts of usage.

0:34:29.800 --> 0:34:31.040
<v Speaker 6>Now the models are.

0:34:30.920 --> 0:34:33.560
<v Speaker 13>Getting bigger and bigger, but the usage is exploding at

0:34:33.560 --> 0:34:36.040
<v Speaker 13>a rapid rate, and so I expect that over the

0:34:36.040 --> 0:34:39.480
<v Speaker 13>fullness of time, eighty percent, ninety percent, the vast majority

0:34:39.480 --> 0:34:41.839
<v Speaker 13>of usage is going to be in inference out there,

0:34:42.080 --> 0:34:45.000
<v Speaker 13>and really, and just for all those out there, inference

0:34:45.320 --> 0:34:48.839
<v Speaker 13>it really is how AI is embedded in the applications

0:34:48.840 --> 0:34:51.319
<v Speaker 13>that everybody uses. And so as we think about our

0:34:51.360 --> 0:34:53.720
<v Speaker 13>customers building, you know, there's a small number of people

0:34:53.719 --> 0:34:56.400
<v Speaker 13>who are going to be building these models, but everyone

0:34:56.440 --> 0:34:58.640
<v Speaker 13>out there is going to use inference as a core

0:34:58.719 --> 0:35:02.040
<v Speaker 13>building block in every they do, and every application is

0:35:02.040 --> 0:35:04.480
<v Speaker 13>going to have inference, and already is starting to see

0:35:04.719 --> 0:35:07.719
<v Speaker 13>inference built in to every application, and we think about

0:35:07.760 --> 0:35:10.800
<v Speaker 13>it as just the new building block. It's just like compute,

0:35:10.840 --> 0:35:13.640
<v Speaker 13>it's just like storage, it's just like a database. Inference

0:35:13.719 --> 0:35:15.719
<v Speaker 13>is a core building block, and so as you talk

0:35:15.760 --> 0:35:18.600
<v Speaker 13>to people who are building new applications, they don't think

0:35:18.600 --> 0:35:20.840
<v Speaker 13>about it as AI is over here and my application

0:35:20.960 --> 0:35:23.640
<v Speaker 13>is over here. They really think about AI is embedded

0:35:23.640 --> 0:35:26.640
<v Speaker 13>in the experience. And so it's increasingly I think it's

0:35:26.680 --> 0:35:28.799
<v Speaker 13>going to be difficult for people to say what part

0:35:28.800 --> 0:35:30.960
<v Speaker 13>of your revenue is going to be driven by AI.

0:35:31.200 --> 0:35:33.520
<v Speaker 13>It's just part of the application that you're building, and

0:35:33.560 --> 0:35:35.560
<v Speaker 13>it's going to be a core part of that experience,

0:35:35.640 --> 0:35:38.600
<v Speaker 13>and it's going to deliver lots of benefits from efficiency,

0:35:39.200 --> 0:35:42.000
<v Speaker 13>from capabilities, and from user experience for all sorts of

0:35:42.000 --> 0:35:43.120
<v Speaker 13>applications and industries.

0:35:43.920 --> 0:35:47.280
<v Speaker 2>The present day, it's fair to say majority is still training.

0:35:47.760 --> 0:35:50.120
<v Speaker 13>No, I think that at this point more definitely more

0:35:50.200 --> 0:35:51.640
<v Speaker 13>usage as inference than training.

0:35:52.600 --> 0:35:55.719
<v Speaker 2>We want to welcome our radio and television audiences around

0:35:55.719 --> 0:35:59.680
<v Speaker 2>the world. We're speaking to AWSCO Matt Garman, who officially

0:35:59.760 --> 0:36:03.960
<v Speaker 2>next week celebrates one year in that role leading AWS.

0:36:04.360 --> 0:36:06.239
<v Speaker 3>A new metric that.

0:36:06.520 --> 0:36:09.640
<v Speaker 2>Has been discussed particularly this earning season. We discussed it

0:36:09.640 --> 0:36:14.120
<v Speaker 2>with Nvidia CEO Jensen One this week is token growth

0:36:14.320 --> 0:36:17.759
<v Speaker 2>and tokenization. Has AWS got a metric to share on

0:36:17.800 --> 0:36:18.240
<v Speaker 2>that front.

0:36:18.760 --> 0:36:20.439
<v Speaker 13>I don't have any metrics to share on that front,

0:36:20.440 --> 0:36:22.319
<v Speaker 13>but I think it's one of the measures that we

0:36:22.360 --> 0:36:24.759
<v Speaker 13>can look at as the numbers of tokens that are

0:36:24.800 --> 0:36:26.920
<v Speaker 13>being served out there, but it's not the only one,

0:36:27.160 --> 0:36:29.840
<v Speaker 13>and I increasingly think that people are going to be

0:36:29.840 --> 0:36:33.600
<v Speaker 13>thinking about these things differently. Tokens are a particularly interesting

0:36:34.400 --> 0:36:36.720
<v Speaker 13>thing to look at when you're thinking about text generation,

0:36:37.239 --> 0:36:40.040
<v Speaker 13>but not all things are created equal. I think, particularly

0:36:40.080 --> 0:36:42.799
<v Speaker 13>as you think about AI reasoning models, the input and

0:36:42.800 --> 0:36:47.560
<v Speaker 13>output tokens don't necessarily talk about the work that's being done.

0:36:47.600 --> 0:36:50.520
<v Speaker 13>And increasingly you're seeing models that can do work for

0:36:50.560 --> 0:36:53.160
<v Speaker 13>a really long period of time before they output tokens.

0:36:53.520 --> 0:36:57.000
<v Speaker 13>And so you're having these models that can sometimes think

0:36:57.040 --> 0:36:59.520
<v Speaker 13>for hours at a time. Right, they might you ask

0:36:59.600 --> 0:37:02.280
<v Speaker 13>these things a go and actually do research on your behalf.

0:37:02.280 --> 0:37:04.120
<v Speaker 13>They can go out to the internet, they can pull

0:37:04.200 --> 0:37:07.440
<v Speaker 13>information back, they can synthesize, they can redo things. If

0:37:07.440 --> 0:37:11.280
<v Speaker 13>you think about coding and que developer, we're seeing lots

0:37:11.320 --> 0:37:14.120
<v Speaker 13>of coding where it goes and actually reasons and does

0:37:14.520 --> 0:37:17.480
<v Speaker 13>iterations and iterations and improves on itself. Looks at what

0:37:17.520 --> 0:37:20.840
<v Speaker 13>it's done and then eventually outputs the end result, and

0:37:20.920 --> 0:37:24.040
<v Speaker 13>so at some point kind of the final output token

0:37:24.160 --> 0:37:26.440
<v Speaker 13>is not really the best measure of how much work

0:37:26.520 --> 0:37:28.840
<v Speaker 13>is being done. If you think about images, if you

0:37:28.840 --> 0:37:31.439
<v Speaker 13>think about videos, there's a lot of content that's being

0:37:31.480 --> 0:37:33.680
<v Speaker 13>created and a lot of thought that's being done, and

0:37:33.719 --> 0:37:36.080
<v Speaker 13>so tokens are one aspect of it, and it's an

0:37:36.160 --> 0:37:38.640
<v Speaker 13>interesting measure, but I don't think it's the only measure

0:37:38.920 --> 0:37:42.480
<v Speaker 13>to look at. Although they are rapidly increasing.

0:37:43.520 --> 0:37:48.520
<v Speaker 2>Project Rainier, massive Custom server design project. What is the

0:37:48.560 --> 0:37:51.719
<v Speaker 2>operational status and latest on Project Ray now?

0:37:51.880 --> 0:37:55.480
<v Speaker 13>Yeah, so we're incredibly excited about so project right here

0:37:56.520 --> 0:37:59.440
<v Speaker 13>is a collaboration that we have with our partners at

0:37:59.560 --> 0:38:04.040
<v Speaker 13>Entthropic to build the largest compute cluster that they'll use

0:38:04.120 --> 0:38:07.080
<v Speaker 13>to train their next generation of their claud models. And

0:38:07.760 --> 0:38:10.320
<v Speaker 13>Anthropic has the very best models out there today. Claude

0:38:10.320 --> 0:38:12.960
<v Speaker 13>four just launched, I think it was last week, and

0:38:13.480 --> 0:38:18.080
<v Speaker 13>it's been getting incredible adoption out there from our customer base.

0:38:19.440 --> 0:38:21.560
<v Speaker 13>Nthropic is going to be training their next version of

0:38:21.560 --> 0:38:24.920
<v Speaker 13>their model on top of Trainium two, which is Amazon's

0:38:24.960 --> 0:38:30.120
<v Speaker 13>custom built accelerator processors purpose built for AI workloads and

0:38:30.120 --> 0:38:33.759
<v Speaker 13>we're building one of the largest clusters ever released. It's

0:38:33.800 --> 0:38:36.840
<v Speaker 13>an enormous cluster, more than five times the size of

0:38:36.840 --> 0:38:39.840
<v Speaker 13>the cluster compared to the last one that they trained on,

0:38:39.880 --> 0:38:41.840
<v Speaker 13>which again is the world's leading model.

0:38:42.000 --> 0:38:43.480
<v Speaker 6>So we're super excited about that.

0:38:44.120 --> 0:38:47.200
<v Speaker 13>We're landing TRAININGUM to servers now and they're already in operation,

0:38:47.320 --> 0:38:50.800
<v Speaker 13>and Entthropic is already is already using parts of that cluster,

0:38:50.840 --> 0:38:53.200
<v Speaker 13>and so super excited about that. And the performance that

0:38:53.200 --> 0:38:56.200
<v Speaker 13>we're seeing out of TRAININGUM two continues to be very

0:38:56.200 --> 0:38:59.479
<v Speaker 13>impressive and really pushes the envelope I think on what's

0:38:59.520 --> 0:39:02.640
<v Speaker 13>possible both from an absolute performance basis as well as

0:39:02.680 --> 0:39:04.560
<v Speaker 13>a cost, performance and scale basis.

0:39:04.719 --> 0:39:05.640
<v Speaker 6>I think some of those.

0:39:05.719 --> 0:39:07.719
<v Speaker 13>Are equally going to be really important as we move

0:39:07.760 --> 0:39:10.920
<v Speaker 13>forward in this world, because today much of the feedback

0:39:10.960 --> 0:39:13.480
<v Speaker 13>you get is that AI is still too expensive. But

0:39:13.560 --> 0:39:16.840
<v Speaker 13>costs are coming down pretty aggressively, and it's still too expensive,

0:39:16.880 --> 0:39:18.759
<v Speaker 13>and so we think there's a number of things that

0:39:18.800 --> 0:39:21.600
<v Speaker 13>need to happen there. Innovation on the silicon level is

0:39:21.640 --> 0:39:23.239
<v Speaker 13>one of those things that needs to help bring the

0:39:23.280 --> 0:39:26.160
<v Speaker 13>cost down, as well as innovation on the software side

0:39:26.160 --> 0:39:28.640
<v Speaker 13>and algorithmic side, so that you have to use less

0:39:28.640 --> 0:39:32.480
<v Speaker 13>compute per unit of inference or training. So all of

0:39:32.480 --> 0:39:34.680
<v Speaker 13>those are important to bring that cost down, to make

0:39:34.719 --> 0:39:37.760
<v Speaker 13>it more and more possible for ADI to be used

0:39:37.760 --> 0:39:39.600
<v Speaker 13>in all of the places that we think that it

0:39:39.640 --> 0:39:40.359
<v Speaker 13>will be over time.

0:39:41.840 --> 0:39:45.800
<v Speaker 2>Matt and Wednesday, Nvidia CEO Jensen Wang summarized inference demand

0:39:45.840 --> 0:39:47.840
<v Speaker 2>for me. I just wanted to play you that SoundBite.

0:39:47.960 --> 0:39:50.720
<v Speaker 4>Sure, well, we got a whole bunch of engines firing

0:39:50.800 --> 0:39:54.000
<v Speaker 4>right now. The biggest one, of course, is the reasoning

0:39:54.520 --> 0:39:55.760
<v Speaker 4>AI inference.

0:39:56.239 --> 0:39:58.720
<v Speaker 6>The demand is just off the charts.

0:40:00.120 --> 0:40:03.240
<v Speaker 12>You see the popularity of all these AI services.

0:40:03.280 --> 0:40:07.200
<v Speaker 2>Now your pitch for trainium too, And as you know,

0:40:07.239 --> 0:40:09.360
<v Speaker 2>I've kind of taken a part the serve of design

0:40:09.400 --> 0:40:13.040
<v Speaker 2>and looked at it is the efficiency and cost efficiency

0:40:13.080 --> 0:40:16.800
<v Speaker 2>relative to Nvidia Tech. Are you seeing that same demand

0:40:16.920 --> 0:40:21.480
<v Speaker 2>Jensen outlined for TRAININGUM two outside of the relationship with Mthropic.

0:40:22.800 --> 0:40:25.320
<v Speaker 13>Yeah, Look, we're seeing it across a number of different places,

0:40:25.320 --> 0:40:28.320
<v Speaker 13>but it's not really TRAININGUM two versus in Nvidia, and

0:40:28.360 --> 0:40:29.920
<v Speaker 13>I think that's not really the right way to think

0:40:29.920 --> 0:40:32.320
<v Speaker 13>about it. I think there's plenty of room. The opportunity

0:40:32.320 --> 0:40:34.960
<v Speaker 13>in this space is massive. It's not one versus the other.

0:40:35.000 --> 0:40:37.120
<v Speaker 13>We think that there's plenty of room for both these

0:40:37.480 --> 0:40:39.400
<v Speaker 13>and Jensen and I speak about this all the time

0:40:39.640 --> 0:40:43.200
<v Speaker 13>that in Vidia is an incredibly fantastic platform. They've built

0:40:43.200 --> 0:40:46.840
<v Speaker 13>a really strong platform that's useful and is the leading

0:40:46.840 --> 0:40:49.960
<v Speaker 13>platform for many many applications out there, and so we

0:40:50.160 --> 0:40:53.319
<v Speaker 13>are incredible design partners with them. We make sure that

0:40:53.360 --> 0:40:55.920
<v Speaker 13>we have the latest in Vidia technology for everyone, and

0:40:55.960 --> 0:40:58.560
<v Speaker 13>we continue to push the envelope on what's possible with

0:40:58.680 --> 0:41:01.520
<v Speaker 13>all of the latest in Vidia capabilities. And we think

0:41:01.560 --> 0:41:04.520
<v Speaker 13>there's room for Trainium and other technologies as well, and

0:41:04.560 --> 0:41:07.919
<v Speaker 13>we're really excited about that, and so we have many

0:41:07.960 --> 0:41:11.400
<v Speaker 13>of the leading AI labs are incredibly excited about using

0:41:11.680 --> 0:41:14.120
<v Speaker 13>Trainium too and really leaning into the benefits that you

0:41:14.160 --> 0:41:17.000
<v Speaker 13>get there. But for the law for a long time,

0:41:17.080 --> 0:41:19.600
<v Speaker 13>these things are going to be living in concert together,

0:41:19.760 --> 0:41:22.000
<v Speaker 13>and I think there's plenty of room. And customers want

0:41:22.080 --> 0:41:24.200
<v Speaker 13>choice at the end of the day. Customers don't want

0:41:24.239 --> 0:41:25.560
<v Speaker 13>to be forced into using.

0:41:25.320 --> 0:41:26.279
<v Speaker 6>One platform or the other.

0:41:26.440 --> 0:41:28.520
<v Speaker 13>They'd love to have choice in Our job at AWS

0:41:28.600 --> 0:41:30.840
<v Speaker 13>is to give customers as much choice as possible.

0:41:31.800 --> 0:41:36.680
<v Speaker 2>What is general availability of Nvidia GB two hundred for AWS,

0:41:36.719 --> 0:41:42.400
<v Speaker 2>and have you I guess launched Grace Blackwell backed instances yet, Yes.

0:41:42.360 --> 0:41:45.759
<v Speaker 13>Yep, so we've launched our they would call them P

0:41:45.960 --> 0:41:49.280
<v Speaker 13>six instances. And so those are available in AWS today

0:41:49.920 --> 0:41:51.759
<v Speaker 13>and customers are using them and liking them, and the

0:41:51.800 --> 0:41:54.920
<v Speaker 13>performance is fantastic. So those are available today. We're continuing

0:41:54.920 --> 0:41:58.760
<v Speaker 13>to ramp capacity. We work very closely with the Nvidia

0:41:58.800 --> 0:42:02.319
<v Speaker 13>team to aggressively mp capacity and demand is strong for

0:42:02.400 --> 0:42:05.520
<v Speaker 13>those P six instances, but customers are able to go

0:42:05.560 --> 0:42:09.520
<v Speaker 13>and test those out today. And like I said, we're

0:42:09.560 --> 0:42:12.160
<v Speaker 13>ramping capacity incredibly fast all around the world and in

0:42:12.200 --> 0:42:14.080
<v Speaker 13>our various different regions.

0:42:15.440 --> 0:42:20.040
<v Speaker 2>Now, what is your attitude to Claude anthropics model being

0:42:20.080 --> 0:42:23.640
<v Speaker 2>available elsewhere on Azure Foundry for example.

0:42:24.680 --> 0:42:26.560
<v Speaker 6>Great, I mean that's okay too.

0:42:26.560 --> 0:42:30.400
<v Speaker 13>I think many of our customers make their applications available

0:42:30.520 --> 0:42:34.440
<v Speaker 13>in different places, and we understand that various different customers

0:42:34.520 --> 0:42:38.160
<v Speaker 13>want to use capabilities in different areas and different clouds.

0:42:38.600 --> 0:42:40.960
<v Speaker 13>Our job is to make AWS and this is what

0:42:41.000 --> 0:42:44.319
<v Speaker 13>we do, is to make AWS the best place to

0:42:44.400 --> 0:42:47.600
<v Speaker 13>run every type of workload and that includes anthropic claud models,

0:42:48.160 --> 0:42:50.200
<v Speaker 13>but it includes a wide range of things and frankly,

0:42:50.440 --> 0:42:54.799
<v Speaker 13>that's why we see big customers migrating over to AWS.

0:42:55.040 --> 0:42:58.279
<v Speaker 13>Take somebody like a Mandoli's who's really gone all in

0:42:58.520 --> 0:43:01.239
<v Speaker 13>with AWS and move some of their workloads to there.

0:43:01.480 --> 0:43:03.239
<v Speaker 13>One of the reasons is that they see that we

0:43:03.320 --> 0:43:06.680
<v Speaker 13>have capabilities sometimes using AI by the way, in order

0:43:06.719 --> 0:43:10.520
<v Speaker 13>to really help them optimize their costs and have the

0:43:10.560 --> 0:43:14.279
<v Speaker 13>most available, most secure platform in monthlies. This case, they're

0:43:14.280 --> 0:43:18.120
<v Speaker 13>taking many of their legacy Windows platforms and transforming them

0:43:18.200 --> 0:43:21.880
<v Speaker 13>into Linux applications and saving all of that licensing costs.

0:43:22.120 --> 0:43:24.680
<v Speaker 13>But we have many customers who are doing that, and

0:43:25.120 --> 0:43:27.920
<v Speaker 13>so our job is to make AWS by far the

0:43:27.960 --> 0:43:32.080
<v Speaker 13>most technically capable platform that has the most and widest

0:43:32.120 --> 0:43:34.280
<v Speaker 13>set of services, and that's.

0:43:34.160 --> 0:43:34.600
<v Speaker 6>What we do.

0:43:35.040 --> 0:43:37.560
<v Speaker 13>But I'm perfectly happy for other people to use Like

0:43:37.800 --> 0:43:41.320
<v Speaker 13>it's great that Claud's making their services available elsewhere and

0:43:41.960 --> 0:43:44.320
<v Speaker 13>we see the vast majority of that usage happening in AWS.

0:43:44.360 --> 0:43:48.319
<v Speaker 2>Though, will we see open AI models on AWS this year?

0:43:49.040 --> 0:43:49.879
<v Speaker 6>Well, just like you.

0:43:49.840 --> 0:43:52.959
<v Speaker 13>Know, we encourage all of our partners to be able

0:43:52.960 --> 0:43:55.960
<v Speaker 13>to be available elsewhere, I'd love for others to take

0:43:55.960 --> 0:43:56.640
<v Speaker 13>that same tack.

0:43:58.440 --> 0:44:01.600
<v Speaker 2>Let's end it with this question from the audience, Actually,

0:44:01.680 --> 0:44:03.920
<v Speaker 2>which is where you're going to grow data center capacity?

0:44:03.960 --> 0:44:04.520
<v Speaker 3>Around the world.

0:44:04.560 --> 0:44:07.360
<v Speaker 2>I got a lot of questions from Latin America and

0:44:07.480 --> 0:44:10.200
<v Speaker 2>Europe in particular, where Jensen flies to you next week?

0:44:10.320 --> 0:44:11.840
<v Speaker 6>Yeah? Great.

0:44:12.560 --> 0:44:15.719
<v Speaker 13>So in Latin America we're continuing to span expand our

0:44:15.719 --> 0:44:17.120
<v Speaker 13>capacity pretty aggressively.

0:44:17.280 --> 0:44:17.600
<v Speaker 6>Actually.

0:44:17.640 --> 0:44:20.920
<v Speaker 13>Earlier this year we launched our Mexico region, which has

0:44:20.920 --> 0:44:23.560
<v Speaker 13>been really well received by customers, and we've announced a

0:44:23.560 --> 0:44:26.560
<v Speaker 13>new region in Chile, and we already have for many

0:44:26.600 --> 0:44:28.879
<v Speaker 13>years have had a region in Brazil which is quite

0:44:28.960 --> 0:44:33.120
<v Speaker 13>popular and has many of the largest financial institutions in

0:44:33.160 --> 0:44:37.120
<v Speaker 13>South America running there. So across Central and South America,

0:44:37.160 --> 0:44:40.760
<v Speaker 13>we are continuing to rapidly expand. In Europe, we're expanding

0:44:40.800 --> 0:44:43.080
<v Speaker 13>as well. We have many regions already in Europe. One

0:44:43.120 --> 0:44:45.080
<v Speaker 13>of the things I'm most excited about actually is at

0:44:45.120 --> 0:44:47.000
<v Speaker 13>the end of this year we're going to be launching

0:44:47.000 --> 0:44:50.680
<v Speaker 13>the European Sovereign Cloud, which is a unique capability that

0:44:50.719 --> 0:44:55.120
<v Speaker 13>no one has, which is completely designed for critical EU

0:44:55.239 --> 0:44:58.759
<v Speaker 13>focused sovereign workloads, and we think given some of the

0:44:58.800 --> 0:45:03.320
<v Speaker 13>concerns that folk have around data sovereignty, particularly for government

0:45:03.320 --> 0:45:06.239
<v Speaker 13>workloads as well as regulator workloads, we think that's going

0:45:06.280 --> 0:45:09.560
<v Speaker 13>to be an incredibly oper popular opportunity for everybody.

0:45:10.600 --> 0:45:13.239
<v Speaker 3>Matt Garman, AWS CEO, thank you.

0:45:13.280 --> 0:45:14.799
<v Speaker 6>Very much, thank you for having me.

0:45:16.920 --> 0:45:19.840
<v Speaker 2>Let's get other headlines in talking tech. First up, TikTok

0:45:19.960 --> 0:45:22.920
<v Speaker 2>shop is cutting several hundred jobs in Indonesia in this

0:45:23.080 --> 0:45:26.319
<v Speaker 2>latest round of cuts. This after taking over the operations

0:45:26.360 --> 0:45:30.040
<v Speaker 2>of local rival tocopedia last year. Sources say the cuts

0:45:30.040 --> 0:45:32.839
<v Speaker 2>are mainly in e commerce teams, and more cuts are

0:45:32.840 --> 0:45:35.680
<v Speaker 2>set to happen as soon as July. Plus Reform UK

0:45:35.840 --> 0:45:39.680
<v Speaker 2>leader Nigel Farage announced plans to introduce a Crypto Assets

0:45:39.719 --> 0:45:42.839
<v Speaker 2>and Digital Finance Bill if his party wins the next

0:45:42.840 --> 0:45:46.120
<v Speaker 2>general election, aiming to launch what he calls a crypto

0:45:46.200 --> 0:45:49.479
<v Speaker 2>revolution in the UK. The legislation would include a cut

0:45:49.480 --> 0:45:53.240
<v Speaker 2>in capital gains tax on crypto investments to ten percent,

0:45:53.520 --> 0:45:55.880
<v Speaker 2>the creation of a bitcoin digital reserve at the BOE,

0:45:56.160 --> 0:45:59.120
<v Speaker 2>and provisions that will make it illegal to restrict services

0:45:59.120 --> 0:46:01.440
<v Speaker 2>for people who want to pay with crypto and Stripe

0:46:01.520 --> 0:46:04.319
<v Speaker 2>has held early discussions with banks about the potential use

0:46:04.320 --> 0:46:07.400
<v Speaker 2>of stable coins. This comes as the payment firm debuted

0:46:07.440 --> 0:46:10.040
<v Speaker 2>a number of stable coin related products.

0:46:09.600 --> 0:46:10.480
<v Speaker 3>In recent months.

0:46:11.920 --> 0:46:15.040
<v Speaker 2>That does it for this edition of Bloomberg Technology. What

0:46:15.120 --> 0:46:17.760
<v Speaker 2>a week it's been don't forget check out the podcast.

0:46:17.760 --> 0:46:19.759
<v Speaker 2>You can find it on the terminal as well as

0:46:19.800 --> 0:46:24.319
<v Speaker 2>online on Apple, on Spotify, and on iHeart. From San Francisco,

0:46:24.760 --> 0:46:28.640
<v Speaker 2>this is Bloomberg Technology.