WEBVTT - Nvidia Forecasts $1 Trillion in Revenue Through 2027

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<v Speaker 1>Bloomberg Audio Studios, Podcasts, radio news. Bloomberg Tech is a

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<v Speaker 1>live from coast to coast with Caroline Hyde in New

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<v Speaker 1>York and ed Lo Loow in San Francisco.

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

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<v Speaker 3>In video, CEO Jensen Wong makes a big forecast for

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<v Speaker 3>the AI buildout.

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<v Speaker 4>Writ your rice down, I see through twenty twenty seven

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<v Speaker 4>at least one trillion dollars.

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<v Speaker 5>As we discussed the AI and MNA landscape with the

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<v Speaker 5>CEO of IBM hot off the company's own GtC announcement.

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<v Speaker 3>And Gecko Robotics works to deploy its AI powered robots

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<v Speaker 3>to assess the condition and readiness of the US Navy's warships.

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<v Speaker 6>A first we turn around ten two.

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<v Speaker 5>Well, once again a market that is focused on geopolitics,

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<v Speaker 5>on war, but also on the eve of the federal

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<v Speaker 5>reserve rate decision.

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<v Speaker 6>We're currently seeing some buying of stocks. In fact, eighty.

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<v Speaker 5>Nine of these one hundred names in the green for

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<v Speaker 5>the NASAK one hundred. We're up for a second straight date.

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<v Speaker 5>We're up eight ten percent, and we're seeing a little

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<v Speaker 5>bit more of a risk on attitude there and you're

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<v Speaker 5>going to dig into well, perhaps one of the catalysts.

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<v Speaker 3>As I stand here right now in video, shares are

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<v Speaker 3>completely flat in the session, but they've been on a

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<v Speaker 3>roller coaster across two sessions. Late Monday, when jensenmong had

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<v Speaker 3>his keynote, you can see the big spike almost five

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<v Speaker 3>percent in the session of what was extended visibility into

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<v Speaker 3>the demand for invidious products.

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<v Speaker 2>Here's what he said, right, you're rise down.

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<v Speaker 4>I see through twenty twenty seven at least one trillion dollars.

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<v Speaker 4>A trillion dollars is an enormous amount of infrastructure. That

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<v Speaker 4>infrastructure investment you could make on Nvidia, you could make

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<v Speaker 4>with complete confidence. We have now proven that.

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<v Speaker 3>Let's get right into it with Bloomberg's Equities reporter Rhyan Vslica.

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<v Speaker 3>I mean you've summarized what the cell sized reaction has

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<v Speaker 3>been to that one trillion dollar number.

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<v Speaker 2>It's mixed, but on the whole bullish.

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<v Speaker 7>What do you say, Yeah, absolutely, I would say people

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<v Speaker 7>are in general pretty positive on this target. It really

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<v Speaker 7>speaks to how much visibility in Vidia has growing forward.

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<v Speaker 7>It really speaks to how they expect all this AI

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<v Speaker 7>infrastructure spending to remain pretty durable, which is something that

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<v Speaker 7>has come under question this year. And led to a

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<v Speaker 7>lot of volatility across the tech space. However, I think

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<v Speaker 7>it also just speaks to just a certain amount of

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<v Speaker 7>uncertainty and a certain amount of hesitancy when it comes

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<v Speaker 7>to this company and this stock. Now we wrote about

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<v Speaker 7>this earlier this week, but Nvidia has been stuck in

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<v Speaker 7>a pretty tight trading range for months. It's been unable

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<v Speaker 7>to break out, even on the back of strong earnings.

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<v Speaker 7>Even on the back of yes today's announcement, we did

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<v Speaker 7>see a brief spike, but then as people sort of

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<v Speaker 7>dissected the target, it came back down again. So I

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<v Speaker 7>think there's still a lot of skepticism out there. Now,

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<v Speaker 7>I would flag that it is hosting an analyst Q

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<v Speaker 7>and A. I think it starts in about an hour.

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<v Speaker 7>That is something. I think people are going to be

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<v Speaker 7>really drilling into this one trillion number trying to understand it,

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<v Speaker 7>and maybe that's something that will spur a little bit

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<v Speaker 7>more gaining. But so far it seems like there's been

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<v Speaker 7>nothing that has been able to lift the stock.

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<v Speaker 5>Yeah, because of those analysts, So it's going to be

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<v Speaker 5>tuning in seventy five, say by the stock only one

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<v Speaker 5>as ever, says stell Cell no, then to see more

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<v Speaker 5>broadly at price target in the next twelve months of

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<v Speaker 5>two hundred and sixty nine dollars, well above where we

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<v Speaker 5>currently trade Ryan. So they're still just waiting on some

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<v Speaker 5>other catalyst.

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<v Speaker 7>Yeah, it's hard to know what the catalyst is going

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<v Speaker 7>to be.

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<v Speaker 2>At this point.

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<v Speaker 7>They've really talked about their product lineup, they've talked about

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<v Speaker 7>their growth expectations. The multiple has really come in. It's

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<v Speaker 7>i think one of the cheapest stocks in the mag seven.

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<v Speaker 7>There is still a lot of questions about what is

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<v Speaker 7>growth going to look like, you know, years out, what

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<v Speaker 7>kind of deceleration could we see? And people are factoring that.

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<v Speaker 7>But certainly when you talk to a lot of people,

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<v Speaker 7>everybody still likes n Video. Everybody still thinks it's a

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<v Speaker 7>very well run stock. They don't really see demand drawing

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<v Speaker 7>up anytime soon. But it does seem like there's a

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<v Speaker 7>certain amount of hesitancy. You know, it's almost like they've

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<v Speaker 7>built up a tolerance for the kinds of games that

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<v Speaker 7>we've seen in quarters past, where they would give some

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<v Speaker 7>kind of big target and we'd see the stock jump

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<v Speaker 7>twenty percent. It's a lot harder to imagine anything like

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<v Speaker 7>that happening today.

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<v Speaker 3>Roan, what else you're seeing on your desk this morning

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<v Speaker 3>as it relates to GtC, Like, is there a broader

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<v Speaker 3>market digestion of the two and a half hour speech

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<v Speaker 3>that Jensen Wong gave yesterday?

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<v Speaker 2>Yeah, two and a half hour.

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<v Speaker 7>I did see a lot of people saying, you know,

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<v Speaker 7>this could have been a lot shorter, so that was

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<v Speaker 7>kind of funny. But beyond that, we are seeing a

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<v Speaker 7>lot of people just digesting this. We saw some moves

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<v Speaker 7>yesterday and IBM and optical companies and Intel, so there

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<v Speaker 7>are a lot of companies. Like it hasn't quite been

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<v Speaker 7>the same way that it was in years past, where

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<v Speaker 7>they would mention a company and we'd see that stock rally.

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<v Speaker 7>Everything is a bit more I muted right now. People

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<v Speaker 7>are really trying to understand this and trying to understand

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<v Speaker 7>where this trade goes from here. I've seen the sort

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<v Speaker 7>of excitement that we saw really at the onset of

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<v Speaker 7>the AI era.

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<v Speaker 5>Most Roun Vasilica with all the technicals on trading this stock. Now,

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<v Speaker 5>let's get you the fundamentals the market perspective. With Daniel Filling,

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<v Speaker 5>his senior research analyst and portfolio manager over it, sounds capital, Daniel.

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<v Speaker 5>I mean, let's talk about the demand for in videos products.

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<v Speaker 5>You still see them as insatiable. We've got GPU CPU

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<v Speaker 5>help you. What drove your optimism from yesterday's speech.

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<v Speaker 8>Yes, so, I think the proof is in the pudding,

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<v Speaker 8>I might say so when we look at sort of

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<v Speaker 8>the labs and the revenue growth this year today, it

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<v Speaker 8>has been massively accelerating. Right Zanthropics public's numbers went from

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<v Speaker 8>fourteen to nineteen billion literally within a few weeks. And

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<v Speaker 8>I think the crux of what is going on here

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<v Speaker 8>is that agentic ai is here. It is as viral

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<v Speaker 8>as zoom was at the beginning of COVID. And what

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<v Speaker 8>I mean with that is that once somebody starts using it,

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<v Speaker 8>it starts doing amazing things. Every colleague will follow over time,

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<v Speaker 8>and we just don't have enough computer to really satiate this.

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<v Speaker 9>And this is like a multi year process of sort.

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<v Speaker 8>Of everybody is starting to use agentic ai within their

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<v Speaker 8>own workflows. We have a billion people as knowledge workers,

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<v Speaker 8>and we maybe have a few million agents as of today,

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<v Speaker 8>so to me and to us, so this feels like

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<v Speaker 8>sort of the iPhone moment of two thousand and seven

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<v Speaker 8>and eight where everybody will want to buy an iPhone

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<v Speaker 8>and everybody will want to run an agent, which means

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<v Speaker 8>the numbers will likely continue to be much, much much

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<v Speaker 8>bigger over time.

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<v Speaker 5>And Jensen wants to be the infrastructure for that, but

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<v Speaker 5>also not just the chips, but the operating system that

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<v Speaker 5>goes with. Talk to us about openclore and how they're

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<v Speaker 5>developing sort of their own operating system for that and

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<v Speaker 5>for a gendki.

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<v Speaker 9>Yeah, so it's very interesting.

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<v Speaker 8>So Nvidia created the security framework to wrap these open

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<v Speaker 8>source agents within an enterprise, right And why do they

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<v Speaker 8>do that, right, Because then an agent will be able

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<v Speaker 8>to access your calendar, your payment mechanisms, your documents, so

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<v Speaker 8>it's got to be very, very safe and secure. So

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<v Speaker 8>this is one of the key bottlenecks that people have

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<v Speaker 8>to overcome to install all agents within the enterprise space.

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<v Speaker 8>And then, as n Video always does, they sort of

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<v Speaker 8>create their own markets. So they created this framework called

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<v Speaker 8>Nemo Claw, which means that everybody, every enterprise in the

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<v Speaker 8>world now can implement an agent locally on their devices,

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<v Speaker 8>which means that this growth can really start to accelerate

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<v Speaker 8>within the enterprise because the security is there.

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<v Speaker 3>Daniel my Bloomberg Terminal tells me SANS Capital has about

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<v Speaker 3>twenty million in video shares.

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<v Speaker 2>Is that right?

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<v Speaker 9>Yes, Ballparker.

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<v Speaker 3>Let's go back to the number twenty twenty five. Through

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<v Speaker 3>the end of calendar twenty twenty six five fiscal quarters

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<v Speaker 3>was five hundred billion dollars of demand just for Blackwell

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<v Speaker 3>and Reuben. I think that Bernstein were able to confirm

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<v Speaker 3>with in VIDEOSCFO that the one trillion is also Blackwell

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<v Speaker 3>and Rubin, including associated networking. But there was a bit

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<v Speaker 3>that Jensen said in passing right after that sentence, which

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<v Speaker 3>was we will be short. In other words, I think

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<v Speaker 3>they're still massively supply constrained relative to demand. How are

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<v Speaker 3>you interpreting that?

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<v Speaker 9>Yeah, so I would agree. I think there's two things

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<v Speaker 9>we need to see here.

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<v Speaker 8>One, the hyperscaler revenue growth has to accelerate to get

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<v Speaker 8>you know, to basically maybe get a market away from

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<v Speaker 8>focusing on some sort of peak cycle concern and back

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<v Speaker 8>to focusing on sort of this growth and tokens that

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<v Speaker 8>Jensen is talking about. So once we start seeing hyper

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<v Speaker 8>scalers really reaccelerate because they're buying all these chips, I

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<v Speaker 8>think that concern goes away. And then the second piece

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<v Speaker 8>is the demand is truly viral, right, so everybody.

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<v Speaker 9>In the world.

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<v Speaker 8>I think we'll start seeing these agents as a massive

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<v Speaker 8>productivity tool. If your colleagues are five to ten times

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<v Speaker 8>more productive than you, then you have to implement it

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<v Speaker 8>as well. And we think the penetration of agents today

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<v Speaker 8>is within single digits percentages, right, So as we go

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<v Speaker 8>from single digits tow one hundred percent, it's a billion people.

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<v Speaker 8>That means you need so much more canacter works.

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<v Speaker 3>The associated data point with the one trillion bar chart

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<v Speaker 3>was the pie chart that sixty percent of that demand

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<v Speaker 3>is still coming from the hyperscalers. It wasn't that long

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<v Speaker 3>ago that we were very focused on how much in

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<v Speaker 3>Nvidia diversified away from the hyperscalers. It seems like that

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<v Speaker 3>hyperscalar portions just going up.

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<v Speaker 9>Yes and no.

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<v Speaker 8>Right, So hyperscalers are by far the biggest purchases of

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<v Speaker 8>these things. But there's also the neo clouds, which are

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<v Speaker 8>investing heavily and actually also very interesting enough governments will

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<v Speaker 8>be able to invest more.

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<v Speaker 9>Going forward as well. And in Video is playing a

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<v Speaker 9>key role in that, right.

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<v Speaker 8>They're one of the leading open source providers of these models,

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<v Speaker 8>which means as a government, you can take the open

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<v Speaker 8>source nemotron model from Nvideo implemented locally, you can buy

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<v Speaker 8>all the chips from Nvidia at the same time and

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<v Speaker 8>sort of run your own local cloud within your country.

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<v Speaker 8>So I think those three will be quite important, but

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<v Speaker 8>hyperscalers will always be very important in all of us.

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<v Speaker 5>Daniel, It's interesting that really where Jensen always tries to

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<v Speaker 5>lean in is differentiation, the fact that he's got the

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<v Speaker 5>right chip for the right workload at the right time,

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<v Speaker 5>and that's why they started.

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<v Speaker 6>To talk a lot more about inference and growth for example.

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<v Speaker 5>But I'm interested about he usually pushes us forward a

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<v Speaker 5>little bit more.

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<v Speaker 6>Yes, we've already actually heard a.

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<v Speaker 5>Lot about Vera Rubin, we know a lot about Blackwell,

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<v Speaker 5>but why not even push us into feyn minimal. Why

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<v Speaker 5>not hear about the next situation, because it's like every

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<v Speaker 5>single year we've got a new architecture coming for us.

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<v Speaker 8>Yes, I would actually say what happened yesterday is quiet

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<v Speaker 8>revolution area. So Nvidia is the first company that we'll

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<v Speaker 8>have two different types of chips for inference. So for

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<v Speaker 8>calling on the AI models to get an answer, there's

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<v Speaker 8>a new LPU chip which is super fast.

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<v Speaker 9>Nobody else has that, and that's combined.

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<v Speaker 8>Together with sort of the old sort of the generalized

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<v Speaker 8>GPUs that they always had in the past. And then

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<v Speaker 8>he did give an astonishing quote that LPU are the

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<v Speaker 8>fast chips. There will be thirty five times more performant

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<v Speaker 8>on the performance per work basis, and anything that was

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<v Speaker 8>there before thirty five times. So I do think those

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<v Speaker 8>jumps are just as good, maybe even better than in

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<v Speaker 8>the past.

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<v Speaker 3>Daniel, you clearly have a command of the spec right

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<v Speaker 3>generations generation on the chips. I'll take it back to

0:11:11.040 --> 0:11:13.920
<v Speaker 3>the stock. You know, Carr outlined where the cell side

0:11:13.960 --> 0:11:16.520
<v Speaker 3>stands on this name. The question for you and for

0:11:16.600 --> 0:11:19.800
<v Speaker 3>sans capital, do you buy more based on what you

0:11:19.920 --> 0:11:21.319
<v Speaker 3>heard on stage in San Jose?

0:11:22.720 --> 0:11:23.040
<v Speaker 9>Yes.

0:11:23.400 --> 0:11:27.320
<v Speaker 8>So I think this event itself has been very reaffirming

0:11:27.400 --> 0:11:30.559
<v Speaker 8>of the future, but the entire debate about the stock

0:11:30.600 --> 0:11:33.960
<v Speaker 8>I think will be resolved truly by this. The market

0:11:34.200 --> 0:11:36.720
<v Speaker 8>is looking at n Video as a business that is.

0:11:36.760 --> 0:11:39.160
<v Speaker 9>At peak revenue and peak earnings.

0:11:40.040 --> 0:11:42.800
<v Speaker 8>We disagree, and the reason why we disagree is everything

0:11:42.800 --> 0:11:44.439
<v Speaker 8>we discussed before agentic.

0:11:44.080 --> 0:11:45.840
<v Speaker 9>Ai is exploding in terms of demand.

0:11:46.120 --> 0:11:49.520
<v Speaker 8>Now this all will get resolved once the free cash

0:11:49.559 --> 0:11:52.440
<v Speaker 8>flow and the revenue growth of the buyers of these chips.

0:11:52.440 --> 0:11:54.480
<v Speaker 8>Are you that sixty percent of the hyperskillers, for example,

0:11:54.520 --> 0:11:57.960
<v Speaker 8>will start growing again, And whenever you start seeing this,

0:11:57.960 --> 0:12:00.640
<v Speaker 8>this entire debate will be resolved because the market will

0:12:00.640 --> 0:12:04.240
<v Speaker 8>say we're going from peak concerns to actually this is

0:12:04.240 --> 0:12:07.760
<v Speaker 8>a very structural, durable growth trajectory the next five to

0:12:07.800 --> 0:12:11.160
<v Speaker 8>ten years. I don't know precisely when this will be solved,

0:12:11.360 --> 0:12:12.880
<v Speaker 8>but my guess is that we're going to see a

0:12:12.920 --> 0:12:16.719
<v Speaker 8>significant acceleration hyper skill and revenue growth within the next

0:12:16.800 --> 0:12:18.920
<v Speaker 8>one or two years because they're buying hundreds of billions

0:12:18.920 --> 0:12:22.160
<v Speaker 8>of dollars of these chips. And then maybe equally important,

0:12:22.480 --> 0:12:25.400
<v Speaker 8>the return or the payback periods off these chips is

0:12:25.440 --> 0:12:28.160
<v Speaker 8>actually improved in the past twelve months because we're completely

0:12:28.200 --> 0:12:31.839
<v Speaker 8>sold out, so basically you're buying a GPU and you're

0:12:31.840 --> 0:12:34.480
<v Speaker 8>getting your money back in record time, which again then

0:12:34.559 --> 0:12:36.960
<v Speaker 8>leads to the point of the hyper skills. We'll start

0:12:37.000 --> 0:12:39.880
<v Speaker 8>seeing more growth, better free cash for growth, which should

0:12:39.880 --> 0:12:42.120
<v Speaker 8>translate then hopefully to a positive outcome.

0:12:42.160 --> 0:12:42.880
<v Speaker 9>Fund video.

0:12:44.160 --> 0:12:46.680
<v Speaker 2>Daniel Pelling from SANSKAF, so, thank you very much.

0:12:52.679 --> 0:12:54.320
<v Speaker 5>Let's check in on the sheds of Uber and Lyft

0:12:54.360 --> 0:12:57.800
<v Speaker 5>right now in the green, as we'll see significantly, and

0:12:57.840 --> 0:13:01.240
<v Speaker 5>that's after both companies announced deepening partnerships within Video, which

0:13:01.280 --> 0:13:02.640
<v Speaker 5>is currently down three tens percent.

0:13:02.800 --> 0:13:03.000
<v Speaker 2>Look.

0:13:03.080 --> 0:13:05.600
<v Speaker 5>Uber says it plans to drull out a global fleet

0:13:05.600 --> 0:13:08.200
<v Speaker 5>of in Vidia powered self driving vehicles across twenty eight.

0:13:08.120 --> 0:13:11.400
<v Speaker 6>Cities by twenty twenty eight. Lift Meanwhile, we'll use in.

0:13:11.440 --> 0:13:13.959
<v Speaker 5>Video's AI to strengthen machine learning systems across it's on

0:13:14.200 --> 0:13:17.520
<v Speaker 5>operations for more blue most consumer apps and gig economy,

0:13:17.559 --> 0:13:20.400
<v Speaker 5>reported Natalie Lang joints this. Now, what's interesting with Uber

0:13:20.760 --> 0:13:23.839
<v Speaker 5>is that we've had some big, bold ambitions articulated back

0:13:23.880 --> 0:13:26.200
<v Speaker 5>in February was it and one hundred thousand cars are

0:13:26.200 --> 0:13:28.920
<v Speaker 5>going to be on the road in this partnership within video.

0:13:29.040 --> 0:13:31.120
<v Speaker 6>But what's the timeline now looking like?

0:13:31.760 --> 0:13:35.200
<v Speaker 10>So the updated timeline is that these vehicles will be

0:13:35.679 --> 0:13:38.880
<v Speaker 10>scaled across twenty eight studies by twenty twenty eight, and

0:13:38.920 --> 0:13:41.760
<v Speaker 10>that will really start in earnest in twenty twenty seven

0:13:41.800 --> 0:13:43.479
<v Speaker 10>in Los Angeles and San Francisco.

0:13:45.000 --> 0:13:47.280
<v Speaker 3>I mean, Uber is about a percentage point of having

0:13:47.320 --> 0:13:49.920
<v Speaker 3>its best days since June of last year. So like

0:13:49.960 --> 0:13:52.160
<v Speaker 3>at first You're like, this is a name check that's

0:13:52.240 --> 0:13:56.040
<v Speaker 3>driving the stock, but really it's it's more updates to.

0:13:56.000 --> 0:13:57.240
<v Speaker 2>An existing partnership.

0:13:57.480 --> 0:14:00.240
<v Speaker 3>What about Lift then, I mean this really is by

0:14:00.440 --> 0:14:03.320
<v Speaker 3>name association because it's more about internal use.

0:14:03.960 --> 0:14:07.040
<v Speaker 10>Yeah, it's about internal use. But part of the release

0:14:07.280 --> 0:14:11.880
<v Speaker 10>also mentions future possible deployments of n video powered vehicles

0:14:11.880 --> 0:14:13.679
<v Speaker 10>on the Lift platform, but we don't have a lot

0:14:13.720 --> 0:14:17.839
<v Speaker 10>of details on the manufacturer partner yet. Whereas for Uber,

0:14:18.080 --> 0:14:22.120
<v Speaker 10>they have a couple of partnerships already announced, such as

0:14:22.240 --> 0:14:26.200
<v Speaker 10>Lucid and neuro vehicles, wave vehicles or with Nissan that

0:14:26.240 --> 0:14:30.080
<v Speaker 10>will that will be powered by video chips and technology.

0:14:30.560 --> 0:14:33.080
<v Speaker 5>I think it sort of goes to what RBC's analyst

0:14:33.080 --> 0:14:35.600
<v Speaker 5>Brad Erickson was spelling out that all of this news

0:14:35.680 --> 0:14:40.200
<v Speaker 5>vindicates perhaps both Uber and Lift's role as platforms in

0:14:40.280 --> 0:14:43.360
<v Speaker 5>the av era. We'd all been worried about competition, but

0:14:43.440 --> 0:14:45.680
<v Speaker 5>actually they're the ones that can bring it all together.

0:14:45.480 --> 0:14:47.880
<v Speaker 10>Right, Yeah, and in this further shows it's not just

0:14:47.920 --> 0:14:50.320
<v Speaker 10>a demand generation platform. It's not just going to be

0:14:50.360 --> 0:14:53.680
<v Speaker 10>an app that will allow people to hail a robotaxi.

0:14:54.120 --> 0:14:56.400
<v Speaker 10>But here we can see that Uber wants to be

0:14:56.480 --> 0:14:59.560
<v Speaker 10>the fleet partner. It wants to support some remote assistance

0:14:59.640 --> 0:15:04.360
<v Speaker 10>operation for these fleets that they run themselves with partners

0:15:04.360 --> 0:15:04.800
<v Speaker 10>as well.

0:15:06.520 --> 0:15:08.800
<v Speaker 3>Blubos Natalie Lung across all the movies in the G

0:15:08.880 --> 0:15:12.760
<v Speaker 3>economy space. After GtC Thank You, another deal announced Amidia's

0:15:12.800 --> 0:15:16.160
<v Speaker 3>GtC conference. IBM will collaborate with the ship maker on

0:15:16.200 --> 0:15:19.640
<v Speaker 3>an open source project aim to help enterprises use AI

0:15:19.680 --> 0:15:22.880
<v Speaker 3>at scale. We sat down with IBM CEO Avin Krishna

0:15:23.040 --> 0:15:25.040
<v Speaker 3>for more in the deal and on his take about

0:15:25.040 --> 0:15:26.400
<v Speaker 3>the wider M and A landscape.

0:15:26.440 --> 0:15:26.920
<v Speaker 2>Listen to this.

0:15:27.880 --> 0:15:32.080
<v Speaker 11>I think the regulatory environment is definitely friendlier where we

0:15:32.160 --> 0:15:32.560
<v Speaker 11>got this.

0:15:32.640 --> 0:15:35.920
<v Speaker 2>Done in just under four months.

0:15:35.560 --> 0:15:38.240
<v Speaker 11>Where you used to take a lot longer a few

0:15:38.280 --> 0:15:38.840
<v Speaker 11>years back.

0:15:39.320 --> 0:15:43.320
<v Speaker 6>If regulatory environment is friendlier, should we be doing more

0:15:43.320 --> 0:15:43.520
<v Speaker 6>of it?

0:15:43.560 --> 0:15:45.360
<v Speaker 5>Should there be more M and A particularly with some

0:15:45.440 --> 0:15:49.000
<v Speaker 5>beaten up overall valuations of software companies at the moment.

0:15:49.440 --> 0:15:52.640
<v Speaker 11>I'll just say watch the space, Oh watch.

0:15:52.440 --> 0:15:54.080
<v Speaker 5>This space, okay, But where would you want to add

0:15:54.080 --> 0:15:55.960
<v Speaker 5>on in this moment and what would make sense to

0:15:55.960 --> 0:15:57.119
<v Speaker 5>be adding to your portfolio?

0:15:57.800 --> 0:16:01.160
<v Speaker 11>So we are very focused hybrid class and AI and

0:16:01.240 --> 0:16:04.520
<v Speaker 11>the intersection. The work we're doing together with Nvidia was

0:16:04.560 --> 0:16:08.160
<v Speaker 11>a five times speed up, so five times, not five percent,

0:16:08.320 --> 0:16:11.760
<v Speaker 11>not a little amount, but five times. So there we

0:16:12.000 --> 0:16:15.200
<v Speaker 11>began to leverage the Nvidia GPUs together with some of

0:16:15.280 --> 0:16:20.440
<v Speaker 11>their cudf or software, combining with our watsonex dot data

0:16:21.000 --> 0:16:24.920
<v Speaker 11>and the example we used was our client Nestley, where

0:16:25.000 --> 0:16:27.520
<v Speaker 11>together we managed to get that speed up across their

0:16:27.600 --> 0:16:31.680
<v Speaker 11>massive amounts of data. And that really is important in

0:16:31.720 --> 0:16:34.520
<v Speaker 11>that case, combining some of the technologies we work on

0:16:34.640 --> 0:16:38.080
<v Speaker 11>also an open source with the Presta Presto data engine

0:16:38.680 --> 0:16:41.960
<v Speaker 11>Nvidia and the example at NESLE. But then we're very

0:16:41.960 --> 0:16:44.400
<v Speaker 11>excited we're going to do more work on that and

0:16:44.440 --> 0:16:46.360
<v Speaker 11>then take it into the market and take it out

0:16:46.400 --> 0:16:48.360
<v Speaker 11>to hundreds of clients from there.

0:16:49.800 --> 0:16:53.280
<v Speaker 3>That was IBN CEO of Increationna Karen. Many more headlines

0:16:53.320 --> 0:16:54.000
<v Speaker 3>out there there is.

0:16:54.040 --> 0:16:56.000
<v Speaker 6>It's time to talk talking tech.

0:16:56.120 --> 0:16:58.720
<v Speaker 5>First up, the UK is ramping up it push into

0:16:58.760 --> 0:17:01.560
<v Speaker 5>quantum computing, committing well the one boy three billion dollars

0:17:01.600 --> 0:17:02.680
<v Speaker 5>over the next four years.

0:17:02.720 --> 0:17:05.399
<v Speaker 6>It's a major bet on a technology.

0:17:04.880 --> 0:17:09.320
<v Speaker 5>Increasingly seen as critical to national security, future economic competitiveness

0:17:09.480 --> 0:17:12.880
<v Speaker 5>for US. Don't expect memoryship shortages to ease anytime soon.

0:17:13.119 --> 0:17:15.960
<v Speaker 6>Sk Heinex well, it says that the crunch could last

0:17:16.000 --> 0:17:17.280
<v Speaker 6>another four to five years.

0:17:17.359 --> 0:17:20.880
<v Speaker 5>Sk Group chairman that's Anthony J notes that while chipmakers

0:17:20.880 --> 0:17:21.720
<v Speaker 5>have already.

0:17:21.440 --> 0:17:22.960
<v Speaker 6>Ramped up, capacity may.

0:17:22.800 --> 0:17:25.639
<v Speaker 5>Not be enough to satisfy demand until around twenty thirty.

0:17:26.200 --> 0:17:29.760
<v Speaker 5>And Samsung, while is already pulling back on its Galaxy

0:17:29.960 --> 0:17:32.760
<v Speaker 5>Z trifled just three months after the launch. So the

0:17:32.800 --> 0:17:35.680
<v Speaker 5>South Korean company plans to halt sales and the nearly

0:17:35.720 --> 0:17:38.359
<v Speaker 5>three thousand dollars device in its home market, and the

0:17:38.440 --> 0:17:40.560
<v Speaker 5>US discontinuation expected to follow it.

0:17:41.640 --> 0:17:44.439
<v Speaker 3>Okay, Coming up amid the chaos of the Iron conflict,

0:17:44.840 --> 0:17:49.280
<v Speaker 3>Bitcoin is emerging as an unlikely oasis for some investors.

0:17:49.280 --> 0:17:50.240
<v Speaker 2>We have more on that. Next.

0:17:50.640 --> 0:18:00.320
<v Speaker 3>This is Bloomberg Tech, one of the world's best known

0:18:00.359 --> 0:18:04.240
<v Speaker 3>investors in Nvidia rc CEO Kathy Woods, so she's optimistic

0:18:04.320 --> 0:18:08.119
<v Speaker 3>about the return on investment from Frontier AI model providers.

0:18:08.119 --> 0:18:10.479
<v Speaker 3>She spoke with Bloomberg's Anda Edwards in London.

0:18:10.600 --> 0:18:11.119
<v Speaker 2>Take a listen.

0:18:11.400 --> 0:18:16.080
<v Speaker 12>We are seeing a revenue generation exploding from the frontier

0:18:16.200 --> 0:18:23.320
<v Speaker 12>model providers. Athropics annualized revenue run rate so ARR went

0:18:23.440 --> 0:18:29.240
<v Speaker 12>from nine billion in December to nineteen billion today. So

0:18:29.720 --> 0:18:34.000
<v Speaker 12>annualizing revenue at nineteen billion that's that's astonishing growth open

0:18:34.040 --> 0:18:39.040
<v Speaker 12>AI from twenty to twenty five billion. The productivity that

0:18:39.720 --> 0:18:43.920
<v Speaker 12>we are enjoying from these large language models is astonishing.

0:18:44.000 --> 0:18:48.800
<v Speaker 12>Even within our own firm. I'm even former skeptics that

0:18:49.000 --> 0:18:51.600
<v Speaker 12>this was going to amount to very much, you know,

0:18:51.760 --> 0:18:57.200
<v Speaker 12>very New York skepticism. They're blown away by what they

0:18:57.240 --> 0:18:57.640
<v Speaker 12>can do.

0:18:57.960 --> 0:18:59.920
<v Speaker 13>Just to take a detail to geopolitics, because it's the

0:19:00.040 --> 0:19:02.919
<v Speaker 13>I'm such a dominant market driver, and I wonder how.

0:19:02.760 --> 0:19:04.600
<v Speaker 6>It influences your thinking.

0:19:04.880 --> 0:19:07.440
<v Speaker 13>We are week three of a wall that's taking place

0:19:07.440 --> 0:19:10.399
<v Speaker 13>in the Middle East. Many tech businesses, of course probably

0:19:10.480 --> 0:19:13.040
<v Speaker 13>quite insulated from everything that is happening there. But I wonder,

0:19:13.160 --> 0:19:16.800
<v Speaker 13>does it what rethinking? Does it prompt at arc? What

0:19:19.119 --> 0:19:22.320
<v Speaker 13>shift in in focus or shift in strategy if any

0:19:22.440 --> 0:19:23.639
<v Speaker 13>does this kind of thing.

0:19:23.480 --> 0:19:26.680
<v Speaker 12>Prompt Yes, well, of course it depends how long term

0:19:26.760 --> 0:19:30.240
<v Speaker 12>this is, and we are thinking it will be short term.

0:19:30.320 --> 0:19:34.399
<v Speaker 12>We do have midterm elections this year and other considerations.

0:19:35.359 --> 0:19:38.800
<v Speaker 12>But of course energy price is going up. Any supply

0:19:38.960 --> 0:19:43.640
<v Speaker 12>shock to the extent it slows unit growth down, it

0:19:43.680 --> 0:19:47.560
<v Speaker 12>will slow down the learning curves associated with various technologies.

0:19:47.920 --> 0:19:50.840
<v Speaker 12>If this is you know, a month or two months

0:19:51.800 --> 0:19:53.560
<v Speaker 12>it's not going to have a big impact at all

0:19:53.680 --> 0:19:55.040
<v Speaker 12>if this is extended.

0:19:55.280 --> 0:19:55.760
<v Speaker 2>COVID.

0:19:56.240 --> 0:20:00.800
<v Speaker 12>We did not understand that the supply shock would reverberate

0:20:00.840 --> 0:20:03.840
<v Speaker 12>for three years and that inflation would take off, and

0:20:03.880 --> 0:20:06.960
<v Speaker 12>that monetary policy would accommodate the inflation the way it did.

0:20:07.640 --> 0:20:10.760
<v Speaker 12>We're not in that situation right now. Monetary policy is

0:20:10.800 --> 0:20:15.399
<v Speaker 12>not accommodating inflation. We're at four point three percent M

0:20:15.440 --> 0:20:18.200
<v Speaker 12>two growth on a year over year basis, so nothing

0:20:18.359 --> 0:20:21.080
<v Speaker 12>like the high twenties, low thirties in COVID.

0:20:21.400 --> 0:20:25.080
<v Speaker 5>Oksen mkathy Wood there alongside Bloomberg's Anna Edwards, and let's

0:20:25.080 --> 0:20:26.840
<v Speaker 5>talk more about the war in Iraq because it is

0:20:26.880 --> 0:20:31.240
<v Speaker 5>fueling volatility across global markets. But cryptocurrencies I'm actually imagining

0:20:31.400 --> 0:20:34.439
<v Speaker 5>as an unexpected bright spot of late Bitcoin and its.

0:20:34.280 --> 0:20:35.919
<v Speaker 6>Peers of rally during these times geo.

0:20:35.800 --> 0:20:38.639
<v Speaker 5>Political stress for more Bloemberg cross ass that reports as well.

0:20:38.720 --> 0:20:40.879
<v Speaker 5>Lee joins us look on the day a little bit

0:20:40.920 --> 0:20:41.440
<v Speaker 5>of pullback.

0:20:41.680 --> 0:20:42.720
<v Speaker 6>Over the last few.

0:20:42.560 --> 0:20:46.920
<v Speaker 5>Weeks, we've actually finally seen somewhat more buying or less parishless.

0:20:47.119 --> 0:20:47.840
<v Speaker 6>I think it's both.

0:20:47.840 --> 0:20:50.240
<v Speaker 14>Bitcoin has been resilient, it's now on a sixth week

0:20:50.320 --> 0:20:53.639
<v Speaker 14>high and unlike it's other asset classes, gold equities or

0:20:53.680 --> 0:20:56.960
<v Speaker 14>even other ASEC classes, it's seen a relative calm. The

0:20:57.040 --> 0:20:59.840
<v Speaker 14>volatility of bitcoin has been kind of flat and really

0:21:00.080 --> 0:21:02.920
<v Speaker 14>can point to it to many things. Maybe it's institutional buying,

0:21:03.040 --> 0:21:05.040
<v Speaker 14>or maybe it's just a narrative. Although what a lot

0:21:05.040 --> 0:21:07.000
<v Speaker 14>of my analysts are saying, at least when they talk

0:21:07.000 --> 0:21:10.240
<v Speaker 14>to me, it's really more institutions, especially corporate treasuries. For

0:21:10.280 --> 0:21:12.679
<v Speaker 14>every fall they absorb it and they buy more of

0:21:12.680 --> 0:21:13.119
<v Speaker 14>the supply.

0:21:14.160 --> 0:21:17.160
<v Speaker 3>There is a technical or i guess a better phrase

0:21:17.240 --> 0:21:20.240
<v Speaker 3>rate transactional part of this story which you write about.

0:21:20.800 --> 0:21:24.320
<v Speaker 3>The rally is driven in parts by traders unwinding their

0:21:24.320 --> 0:21:25.080
<v Speaker 3>options bets.

0:21:25.080 --> 0:21:26.200
<v Speaker 2>Could you explain that quickly?

0:21:26.320 --> 0:21:28.359
<v Speaker 14>Is about this is the thing with bitcoin. It's interesting

0:21:28.359 --> 0:21:31.120
<v Speaker 14>because more than the sentiment, it's really all about this mechanic.

0:21:31.240 --> 0:21:34.440
<v Speaker 14>So we have traders unwinding their options bets, those that

0:21:34.480 --> 0:21:36.800
<v Speaker 14>bet that bitcoin will continue to fall, and so when

0:21:36.800 --> 0:21:39.480
<v Speaker 14>they underwind that, traders close out their negative positions.

0:21:39.600 --> 0:21:40.479
<v Speaker 6>Bitcoin rallies.

0:21:40.480 --> 0:21:42.560
<v Speaker 14>And we have about one point five billion dollars of

0:21:42.640 --> 0:21:45.479
<v Speaker 14>bitcoin puts clustered around the sixty thousand level, and now

0:21:45.480 --> 0:21:48.280
<v Speaker 14>we're around seventy five thousand level, which is again a

0:21:48.359 --> 0:21:50.520
<v Speaker 14>six month high, so which is really impressive. And there

0:21:50.520 --> 0:21:52.960
<v Speaker 14>are one point three billions of calls at seventy five thousand,

0:21:53.200 --> 0:21:55.800
<v Speaker 14>So that's why you see bitcoin rally. But again it's

0:21:55.800 --> 0:21:58.880
<v Speaker 14>more about narrative. We're moving beyond that now, it's about mechanics.

0:21:58.920 --> 0:22:00.920
<v Speaker 14>I mean, you look at etfight. One and a half

0:22:00.960 --> 0:22:03.040
<v Speaker 14>billion dollars have flown a month to day, so that's

0:22:03.040 --> 0:22:04.120
<v Speaker 14>really a sign of confidence.

0:22:04.119 --> 0:22:08.160
<v Speaker 3>Then Bloomberg Zazabellie, thank you, Carol. What you're looking at, well.

0:22:08.000 --> 0:22:09.439
<v Speaker 5>I just want to look at what's happening in the

0:22:09.440 --> 0:22:12.440
<v Speaker 5>world of stable coins because a bit of an acquisition

0:22:12.520 --> 0:22:16.280
<v Speaker 5>has happened with MasterCard and b the NK. Look, this

0:22:16.320 --> 0:22:18.040
<v Speaker 5>is a company that they're buying for one point eight

0:22:18.080 --> 0:22:21.000
<v Speaker 5>billion dollars to really ride into the infrastructure play of

0:22:21.000 --> 0:22:24.119
<v Speaker 5>stable coins. Remember Coinbase were looking at that asset and

0:22:24.119 --> 0:22:25.080
<v Speaker 5>they decided to walk.

0:22:24.960 --> 0:22:26.720
<v Speaker 6>Away when it cost them two billion. That were the

0:22:26.920 --> 0:22:27.600
<v Speaker 6>reports at.

0:22:27.560 --> 0:22:37.760
<v Speaker 3>Least, welcome back to Bloomberg Tech. One of the other

0:22:37.800 --> 0:22:40.879
<v Speaker 3>stories out this morning is Qualcomm buying back another twenty

0:22:40.920 --> 0:22:44.240
<v Speaker 3>billion dollars of shares, also boosting its dividend from eighty

0:22:44.320 --> 0:22:47.280
<v Speaker 3>nine cents to ninety two cents. The story is pretty simple,

0:22:47.520 --> 0:22:51.120
<v Speaker 3>as Qualcomm tells it, they want to bolster shareholder returns

0:22:51.320 --> 0:22:54.600
<v Speaker 3>while also continuing to try and diversify this business from

0:22:54.680 --> 0:22:58.440
<v Speaker 3>smartphone to things like automotive and increasingly and more recently

0:22:58.720 --> 0:23:01.359
<v Speaker 3>data centered. That's what the CEA, Christiano amon is talking

0:23:01.440 --> 0:23:04.000
<v Speaker 3>about in the statement, stock up two percent and then

0:23:04.080 --> 0:23:06.840
<v Speaker 3>another check on in video we're now modestly lower four

0:23:06.880 --> 0:23:10.400
<v Speaker 3>tenths of one percent. The peak of Monday session during

0:23:10.480 --> 0:23:13.360
<v Speaker 3>genson One's keynote was a gain of five percent, which

0:23:13.600 --> 0:23:17.840
<v Speaker 3>very quickly faded as the market interpreted the twenty twenty

0:23:17.840 --> 0:23:21.159
<v Speaker 3>five to twenty twenty seven outlook or forecast of a

0:23:21.240 --> 0:23:24.280
<v Speaker 3>trillion dollars of demand for its AI compute. We're now

0:23:24.440 --> 0:23:25.760
<v Speaker 3>down half percentage.

0:23:25.359 --> 0:23:27.800
<v Speaker 5>Point carac Yeah, and two and a half hours of

0:23:27.880 --> 0:23:31.919
<v Speaker 5>speeching it would feel Gensenhan didn't actually only just forcus

0:23:32.000 --> 0:23:35.200
<v Speaker 5>that trillion dollars, of course, said he also talked about

0:23:35.200 --> 0:23:37.920
<v Speaker 5>what the company will need to get there, including more

0:23:37.960 --> 0:23:41.240
<v Speaker 5>copper and optics capacity. That those comments really rattle shares

0:23:41.240 --> 0:23:44.480
<v Speaker 5>the companies that make data center optical components. Let's talk

0:23:44.480 --> 0:23:46.639
<v Speaker 5>about it overly most common rhinikey, we're off by one

0:23:46.720 --> 0:23:48.880
<v Speaker 5>and a half percent on Canning and some other suppliers

0:23:48.880 --> 0:23:52.280
<v Speaker 5>at the moment. But what's been interesting is Lamentum and Coherent.

0:23:52.480 --> 0:23:55.320
<v Speaker 5>They've been running up into this announcement on the anticipation

0:23:55.359 --> 0:23:58.320
<v Speaker 5>that we're all in on optics, and it looks as.

0:23:58.200 --> 0:24:00.000
<v Speaker 6>Though there's a double barreled strategy.

0:24:00.640 --> 0:24:03.120
<v Speaker 15>Yeah, totally. And it's so interesting because we see those

0:24:03.200 --> 0:24:05.359
<v Speaker 15>run ups and then we just have one little comment

0:24:05.640 --> 0:24:08.560
<v Speaker 15>from Jensen Wong and it just you know, unraveled right away.

0:24:08.720 --> 0:24:11.400
<v Speaker 15>So yeah, I mean what he said was basically that

0:24:11.640 --> 0:24:13.440
<v Speaker 15>you know, copper is still going to be or is

0:24:13.480 --> 0:24:16.560
<v Speaker 15>going to remain important in these data center buildouts, which

0:24:16.880 --> 0:24:19.359
<v Speaker 15>just I guess made some of the investors a little

0:24:19.359 --> 0:24:23.400
<v Speaker 15>bit concerned about all of these you know, optics components.

0:24:23.720 --> 0:24:26.040
<v Speaker 15>The thing that's interesting, a lot of analysts did say

0:24:26.080 --> 0:24:28.840
<v Speaker 15>this morning in some notes following GtC that you know,

0:24:28.880 --> 0:24:31.880
<v Speaker 15>both are definitely going to remain important in these buildouts

0:24:31.960 --> 0:24:36.000
<v Speaker 15>going forward, So there's probably not huge cause for concern here.

0:24:36.040 --> 0:24:38.000
<v Speaker 15>And we did see some some of those stocks were

0:24:38.000 --> 0:24:40.760
<v Speaker 15>covered today. I think Lumentum did kind of go back up,

0:24:40.800 --> 0:24:42.760
<v Speaker 15>and so is in positive territory.

0:24:42.400 --> 0:24:45.720
<v Speaker 3>Now common what's the experience of a GtC like for

0:24:45.760 --> 0:24:49.119
<v Speaker 3>the equities team. Every single time on stage there was

0:24:49.160 --> 0:24:52.600
<v Speaker 3>a name check of any given company, you'd notice a

0:24:52.640 --> 0:24:56.439
<v Speaker 3>little tick higher in some of those stocks, which were

0:24:56.480 --> 0:24:59.760
<v Speaker 3>the ones of substance and which were just literally name checks.

0:25:00.320 --> 0:25:02.199
<v Speaker 15>Yeah, I mean it ends up being such a like

0:25:02.240 --> 0:25:04.520
<v Speaker 15>a flurry of excitement as we're all rushing to you know,

0:25:04.560 --> 0:25:07.320
<v Speaker 15>send headlines and watch these shares move. I mean we

0:25:07.400 --> 0:25:09.919
<v Speaker 15>did see some things, you know, move quite materially, you know,

0:25:10.600 --> 0:25:15.320
<v Speaker 15>outside of Lumentum Coherent. We saw shares of Uber and

0:25:15.400 --> 0:25:20.399
<v Speaker 15>Lyft jump on partnerships that were announced. IBM shares also jumped,

0:25:20.440 --> 0:25:22.600
<v Speaker 15>and then there were some other little, smaller ones where

0:25:22.600 --> 0:25:24.840
<v Speaker 15>things quickly faded. I mean, one that was actually kind

0:25:24.880 --> 0:25:27.879
<v Speaker 15>of interesting is Nvidia itself had a very big spike,

0:25:28.240 --> 0:25:30.560
<v Speaker 15>you know, around that one trillion figure, and then actually

0:25:30.640 --> 0:25:32.919
<v Speaker 15>paired most of those gains sort of as the market

0:25:32.920 --> 0:25:36.439
<v Speaker 15>digested it. But yeah, overall, we really are seeing again

0:25:36.480 --> 0:25:40.000
<v Speaker 15>that you know, Jensen's comments have the ability to move markets,

0:25:40.040 --> 0:25:42.560
<v Speaker 15>to move these stocks, and it actually is a little

0:25:42.600 --> 0:25:44.960
<v Speaker 15>bit of a flip from last year. We didn't see

0:25:45.000 --> 0:25:47.880
<v Speaker 15>a ton of movement around GtC investors were really sort

0:25:47.880 --> 0:25:50.320
<v Speaker 15>of concerned about the macro and you know, had a

0:25:50.320 --> 0:25:51.560
<v Speaker 15>lot of AI skepticism.

0:25:51.640 --> 0:25:53.200
<v Speaker 6>So seeing a little bit of.

0:25:53.119 --> 0:25:55.760
<v Speaker 15>A trend kind of maybe back towards normal this year

0:25:55.920 --> 0:25:58.800
<v Speaker 15>where you know, they have the power to move stocks

0:25:58.800 --> 0:25:59.560
<v Speaker 15>of other companies.

0:26:00.400 --> 0:26:03.000
<v Speaker 3>Bloomber's Cullen Rhinike, thank you very much. Let's stick with

0:26:03.040 --> 0:26:05.879
<v Speaker 3>what's going on broader markets today, particularly for tech and

0:26:05.920 --> 0:26:09.640
<v Speaker 3>bringing Carosh Life, chief market strategists at BEMO Wealth Management,

0:26:09.720 --> 0:26:12.200
<v Speaker 3>and on a very serious note, like with everything going on,

0:26:13.200 --> 0:26:16.359
<v Speaker 3>you know, the war in Iran, considerations around trade, a

0:26:16.440 --> 0:26:20.040
<v Speaker 3>number of headlines relayings trade this morning, even a decline

0:26:20.040 --> 0:26:23.119
<v Speaker 3>of four tenths of a percent for Nvidia. It's the

0:26:23.160 --> 0:26:25.919
<v Speaker 3>second biggest points drag at the index level for then

0:26:25.960 --> 0:26:29.160
<v Speaker 3>as that one hundred, Carol, you know how closely were

0:26:29.200 --> 0:26:32.159
<v Speaker 3>you watching GtC of the last twenty four hours for

0:26:32.200 --> 0:26:34.240
<v Speaker 3>some macro level impact.

0:26:34.840 --> 0:26:39.080
<v Speaker 16>I think not necessarily a macro level impact. And it's

0:26:39.320 --> 0:26:41.600
<v Speaker 16>really important to zoom out from what's going on in

0:26:41.680 --> 0:26:44.240
<v Speaker 16>these day to day basises and try to think intermediate,

0:26:44.320 --> 0:26:47.399
<v Speaker 16>longer term. Clearly markets are trying to get beyond that,

0:26:47.480 --> 0:26:49.200
<v Speaker 16>and I think it's one of the reasons why you've

0:26:49.240 --> 0:26:54.320
<v Speaker 16>seen the aggregate indexes hold in so tightly because realistically,

0:26:54.400 --> 0:26:58.080
<v Speaker 16>given all the news we've had since basically the first

0:26:58.160 --> 0:27:04.480
<v Speaker 16>weekend before January, we've had several different wars, conflicts started here,

0:27:04.640 --> 0:27:06.680
<v Speaker 16>lots of stuff that have hit the markets, and yet

0:27:06.720 --> 0:27:11.240
<v Speaker 16>the aggregate averages are still hugging that close to all

0:27:11.280 --> 0:27:14.920
<v Speaker 16>time highs even though there's been a lot of turbulence underneath.

0:27:15.240 --> 0:27:17.640
<v Speaker 16>But I think that indicative of the fact that people

0:27:17.680 --> 0:27:21.159
<v Speaker 16>are really leaning into You've still got growth stories going on.

0:27:21.280 --> 0:27:24.080
<v Speaker 16>You had GtC reaffirm that growth story, I mean a

0:27:24.200 --> 0:27:28.000
<v Speaker 16>trillion dollars if you will out over the next couple

0:27:28.040 --> 0:27:30.920
<v Speaker 16>of years, and so you've got a lot of momentum underneath,

0:27:30.920 --> 0:27:33.600
<v Speaker 16>and investors don't want to be out of the market

0:27:33.800 --> 0:27:36.280
<v Speaker 16>when some of that macro clears.

0:27:37.400 --> 0:27:38.360
<v Speaker 2>I find that interesting.

0:27:38.400 --> 0:27:40.960
<v Speaker 3>You know, as Jensen Wong tells it, the global economy

0:27:41.040 --> 0:27:44.520
<v Speaker 3>is in the early phase of a transition spanning agentic

0:27:44.600 --> 0:27:47.120
<v Speaker 3>AI through to robotics in the physical AI space.

0:27:47.600 --> 0:27:48.360
<v Speaker 2>You know, if you've.

0:27:48.320 --> 0:27:52.359
<v Speaker 3>Started classic economics, how does one prepare for that as

0:27:52.400 --> 0:27:55.600
<v Speaker 3>an investor to understand where in that transition the global

0:27:55.640 --> 0:27:56.240
<v Speaker 3>economy is?

0:27:57.080 --> 0:27:59.000
<v Speaker 16>Well, I think one of the things you do is

0:27:59.119 --> 0:28:01.439
<v Speaker 16>understand we are in the middle of a transition. They

0:28:01.520 --> 0:28:04.720
<v Speaker 16>tend to be really muddy where you're in the very

0:28:04.720 --> 0:28:08.080
<v Speaker 16>short term or the new phases of a technology. I

0:28:08.119 --> 0:28:10.720
<v Speaker 16>was rolling it back thinking to when we first got

0:28:10.840 --> 0:28:16.439
<v Speaker 16>Excel and word perfect in some of the other early software,

0:28:16.480 --> 0:28:18.159
<v Speaker 16>and everyone was trying to figure out how do I

0:28:18.240 --> 0:28:18.520
<v Speaker 16>use it?

0:28:18.520 --> 0:28:19.120
<v Speaker 10>Do I have to.

0:28:19.080 --> 0:28:21.960
<v Speaker 16>Put everything into a spreadsheet or just some things into

0:28:22.000 --> 0:28:26.840
<v Speaker 16>a spreadsheet? And when you have that sort of reconfiguration,

0:28:27.000 --> 0:28:29.480
<v Speaker 16>if you will, it takes some period of time to

0:28:29.560 --> 0:28:32.879
<v Speaker 16>figure out what the impacts are. But rolling it back

0:28:33.000 --> 0:28:38.840
<v Speaker 16>and looking at company after company, country after country reinvesting

0:28:38.960 --> 0:28:41.280
<v Speaker 16>or investing for the first time in a long time

0:28:41.600 --> 0:28:45.520
<v Speaker 16>in some of those really important infrastructure and capital investments,

0:28:45.800 --> 0:28:48.600
<v Speaker 16>and that has a long, long, live and long tail

0:28:48.760 --> 0:28:51.200
<v Speaker 16>to it, if you will. But it's also important to

0:28:51.240 --> 0:28:54.720
<v Speaker 16>remember from economics one oh one that a lot of

0:28:54.720 --> 0:28:57.720
<v Speaker 16>the economic stats we have were meant to measure a

0:28:57.840 --> 0:29:01.760
<v Speaker 16>very different society than we have now or are emerging too,

0:29:01.960 --> 0:29:05.440
<v Speaker 16>and so that'll be part of the challenge. So as investors,

0:29:05.520 --> 0:29:09.120
<v Speaker 16>I think part of it is stay diversified, stay long,

0:29:09.440 --> 0:29:14.239
<v Speaker 16>lean into it, and don't get too don't hyperventilate too

0:29:14.360 --> 0:29:17.360
<v Speaker 16>much about day to day activity.

0:29:17.960 --> 0:29:21.320
<v Speaker 5>Should you be leaning more into the compute buildout, the

0:29:21.360 --> 0:29:22.640
<v Speaker 5>AI infrastructure build out.

0:29:22.680 --> 0:29:24.120
<v Speaker 6>That's what's worked for the last few years.

0:29:24.120 --> 0:29:27.320
<v Speaker 5>And I'm looking at Nevies today for example, it's selling

0:29:27.760 --> 0:29:31.360
<v Speaker 5>well convertible debt to be able to continue to build out.

0:29:31.400 --> 0:29:33.480
<v Speaker 5>It's so neocloud offering. We know it's going to deal

0:29:33.520 --> 0:29:35.600
<v Speaker 5>with meta. Should you belong that space?

0:29:36.560 --> 0:29:39.240
<v Speaker 16>Well, I think a piece of it is to understand

0:29:39.320 --> 0:29:44.080
<v Speaker 16>not only the buildout, but to look far and wide

0:29:44.080 --> 0:29:46.840
<v Speaker 16>for those companies that are leaning into using the new

0:29:46.880 --> 0:29:50.200
<v Speaker 16>technology as well, because there's lots of different applications, different

0:29:50.240 --> 0:29:57.760
<v Speaker 16>places that it has the chance to supplement if you will,

0:29:57.800 --> 0:30:01.360
<v Speaker 16>not necessarily replace everybody. But and so where are those

0:30:01.440 --> 0:30:06.200
<v Speaker 16>leaders that are encouraging in their employees, if you will,

0:30:06.240 --> 0:30:08.440
<v Speaker 16>and prepping their employees to be able to lean in

0:30:08.800 --> 0:30:10.640
<v Speaker 16>and those new technology.

0:30:10.680 --> 0:30:13.200
<v Speaker 5>I mean they've got to lean in because many of

0:30:13.240 --> 0:30:15.080
<v Speaker 5>them are going to be forced out. Look, there's another

0:30:15.120 --> 0:30:18.120
<v Speaker 5>headline in your space of a banking NUDEA, which is

0:30:18.120 --> 0:30:20.280
<v Speaker 5>a NAUDIC bank saying they're gonna be laying off some

0:30:20.320 --> 0:30:23.760
<v Speaker 5>five percent of staff because of AI productivity.

0:30:23.800 --> 0:30:27.280
<v Speaker 6>Now you can call it AI washing. But when someone.

0:30:27.000 --> 0:30:29.520
<v Speaker 5>Like Jack Dorsey is laying off forty percent of staff,

0:30:29.520 --> 0:30:31.640
<v Speaker 5>and he's thinking he can do that because of AI.

0:30:32.680 --> 0:30:34.000
<v Speaker 5>We just going to see more and more of that

0:30:34.240 --> 0:30:35.320
<v Speaker 5>impacting the labor force.

0:30:36.600 --> 0:30:39.800
<v Speaker 16>I think it's interesting because I do think there's a

0:30:40.960 --> 0:30:44.040
<v Speaker 16>a if you will have AI washing to some of it.

0:30:44.200 --> 0:30:47.480
<v Speaker 16>But there's also the issue that these leaders are looking

0:30:47.520 --> 0:30:50.360
<v Speaker 16>for people in their organizations who and they're giving them

0:30:50.400 --> 0:30:52.160
<v Speaker 16>seats at the table, the ones that are rolling up

0:30:52.200 --> 0:30:54.880
<v Speaker 16>their sleeves, getting messy trying this stuff out and figuring

0:30:54.920 --> 0:30:58.280
<v Speaker 16>it out. But also there was a reporter out recently

0:30:58.320 --> 0:31:01.160
<v Speaker 16>that talked about the bulk of the space being done

0:31:01.200 --> 0:31:03.960
<v Speaker 16>in AI is done on the technology, not on teaching

0:31:04.000 --> 0:31:06.320
<v Speaker 16>people how to use it. So there's a piece of

0:31:06.360 --> 0:31:08.560
<v Speaker 16>it where we have to create an environment where it's

0:31:08.600 --> 0:31:11.440
<v Speaker 16>okay for people to experiment with it. We're not going

0:31:11.480 --> 0:31:15.320
<v Speaker 16>to replace overnight some of these macro systems, and especially

0:31:15.320 --> 0:31:19.200
<v Speaker 16>in highly regulated industries like banking, it's hard to believe

0:31:19.200 --> 0:31:22.640
<v Speaker 16>that you're necessarily going to totally displace an old software

0:31:23.040 --> 0:31:26.080
<v Speaker 16>and allow agentic AI to take over all of it.

0:31:26.280 --> 0:31:28.760
<v Speaker 16>But it is going to supplement what each of us.

0:31:28.680 --> 0:31:31.320
<v Speaker 9>Are doing and how we're doing it.

0:31:31.360 --> 0:31:34.880
<v Speaker 16>And you go back and look just in my business

0:31:34.920 --> 0:31:38.480
<v Speaker 16>in analysis, where we started with hand plotted charts and

0:31:38.520 --> 0:31:42.000
<v Speaker 16>hand calculated moving averages to deploying new technology all the

0:31:42.000 --> 0:31:44.920
<v Speaker 16>way along makes me a lot more productive day to day.

0:31:45.400 --> 0:31:48.000
<v Speaker 16>And I think that's what companies are looking for. But

0:31:49.240 --> 0:31:51.200
<v Speaker 16>each of us individually is going to have to figure

0:31:51.200 --> 0:31:52.440
<v Speaker 16>out how to lean into that.

0:31:52.400 --> 0:31:56.120
<v Speaker 5>Too well, said Cowash Life, Chief Market Strutches. That be

0:31:56.200 --> 0:31:59.320
<v Speaker 5>my wealth management, who is appreciate your time. Let's talk

0:31:59.320 --> 0:32:02.160
<v Speaker 5>about that disrupt little bit more Now for labor, because China.

0:32:01.960 --> 0:32:03.320
<v Speaker 6>It faces a key test.

0:32:03.400 --> 0:32:06.040
<v Speaker 5>It's the nation's AI boom really reshaped industries while putting

0:32:06.080 --> 0:32:07.200
<v Speaker 5>millions of jobs at risk.

0:32:07.400 --> 0:32:08.600
<v Speaker 6>Now analysts worn that up.

0:32:08.560 --> 0:32:11.120
<v Speaker 5>To one hundred and forty two million urban jobs could

0:32:11.200 --> 0:32:14.360
<v Speaker 5>vanish by twenty forty nine due to rapid AI driven automation.

0:32:15.000 --> 0:32:17.840
<v Speaker 6>China correspondent Min Minla reports in Beijing.

0:32:19.080 --> 0:32:20.320
<v Speaker 2>Juju Hi.

0:32:21.200 --> 0:32:25.280
<v Speaker 17>You know financial tribium that almost looks like me, but

0:32:25.360 --> 0:32:28.120
<v Speaker 17>it's not. It's an AI generated video based on a

0:32:28.160 --> 0:32:32.480
<v Speaker 17>single screenshot. Tools from Earli, Bubba, ten Cent, Kwaisho are

0:32:32.480 --> 0:32:37.120
<v Speaker 17>making AI video generation accessible to millions, sometimes for free.

0:32:37.520 --> 0:32:40.760
<v Speaker 18>Our company, I can't imagine without AI, how can we survive?

0:32:41.320 --> 0:32:42.000
<v Speaker 6>At the beginning.

0:32:43.040 --> 0:32:46.360
<v Speaker 18>Without AI, I don't think our game can actually be

0:32:46.440 --> 0:32:47.720
<v Speaker 18>done in one year.

0:32:49.080 --> 0:32:52.600
<v Speaker 17>It's brought huge productivity gains for this game developer, but

0:32:52.760 --> 0:32:57.400
<v Speaker 17>also raised alarms in the entertainment industry. Disney and Paramount

0:32:57.360 --> 0:33:00.640
<v Speaker 17>to have accused by dons of IP infringement after its

0:33:00.720 --> 0:33:05.120
<v Speaker 17>video generator produced near cinematic scenes from just a text prompt.

0:33:05.360 --> 0:33:08.720
<v Speaker 17>The fear is that AI could replace not just mundane tasks,

0:33:08.800 --> 0:33:10.920
<v Speaker 17>but jobs across creative industries.

0:33:11.360 --> 0:33:14.960
<v Speaker 18>The painting, if we use like labor works, it's like

0:33:15.080 --> 0:33:19.480
<v Speaker 18>two thousands to four thousand for one piece, but with AI,

0:33:19.560 --> 0:33:24.080
<v Speaker 18>we only use like probably two R and B for

0:33:24.400 --> 0:33:24.920
<v Speaker 18>one piece.

0:33:25.520 --> 0:33:29.760
<v Speaker 17>For policymakers, the challenge is balancing growth will.

0:33:29.440 --> 0:33:32.320
<v Speaker 9>Nurture emerging industries and industries of the.

0:33:32.280 --> 0:33:36.920
<v Speaker 18>Future with disruption jingle jinin The rapid development of AI

0:33:37.200 --> 0:33:39.600
<v Speaker 18>is having a profound impact on employment.

0:33:40.040 --> 0:33:42.920
<v Speaker 17>The China Economic Journal projects that more than thirty percent

0:33:42.960 --> 0:33:45.280
<v Speaker 17>of urban jobs in China could be lost to AI

0:33:45.440 --> 0:33:48.280
<v Speaker 17>by twenty forty nine. That's one hundred and forty two

0:33:48.400 --> 0:33:52.080
<v Speaker 17>million jobs. That's a scenario that could threaten social stability.

0:33:52.480 --> 0:33:55.320
<v Speaker 17>Beijing is aiming to create another twelve million jobs this

0:33:55.520 --> 0:33:58.200
<v Speaker 17>year with just as many graduates set to enter an

0:33:58.240 --> 0:34:00.200
<v Speaker 17>already select labor market.

0:34:01.200 --> 0:34:03.680
<v Speaker 19>In finance and it if they're warn't for these kind

0:34:03.680 --> 0:34:06.520
<v Speaker 19>of regulatory barriers, about thirty to forty percent of the

0:34:06.640 --> 0:34:09.120
<v Speaker 19>job could have been lost right away. If you're thinking

0:34:09.160 --> 0:34:13.319
<v Speaker 19>about the automation AI replacement of a junior rows, it's

0:34:13.360 --> 0:34:15.720
<v Speaker 19>already happening massively in China.

0:34:16.160 --> 0:34:19.759
<v Speaker 17>That leads Seating Ping's government with a dilemma. China counterford

0:34:19.800 --> 0:34:22.520
<v Speaker 17>to fall behind, and it's tachways with the United States.

0:34:22.719 --> 0:34:26.000
<v Speaker 17>But the implications of a tech revolution are far from clear.

0:34:26.840 --> 0:34:31.360
<v Speaker 20>If we let AI replace the jobs without taxing the

0:34:31.360 --> 0:34:34.480
<v Speaker 20>AI appropriately, then then it can really get to the

0:34:34.520 --> 0:34:36.200
<v Speaker 20>core of the consumer economy. And we got to think

0:34:36.200 --> 0:34:39.359
<v Speaker 20>about the sort of tax policy that is targeted specifically

0:34:39.360 --> 0:34:41.240
<v Speaker 20>at what is driving those job job losses.

0:34:41.560 --> 0:34:45.240
<v Speaker 19>It will be in the regulatory framework at some point.

0:34:45.480 --> 0:34:49.880
<v Speaker 19>I just don't see it as a choice yet because

0:34:49.920 --> 0:34:52.640
<v Speaker 19>we're at the very early stage of promoting the application

0:34:52.719 --> 0:34:56.840
<v Speaker 19>of AI. So the great area must be caps actually

0:34:56.880 --> 0:34:58.840
<v Speaker 19>by a very wide margin.

0:34:59.320 --> 0:35:03.000
<v Speaker 17>Last de State Media published a landmark arbitration case in

0:35:03.040 --> 0:35:06.600
<v Speaker 17>Beijing that sets some early guard rails. Dismissing an employee

0:35:06.600 --> 0:35:10.320
<v Speaker 17>because of AI is illegal because it's a business decision

0:35:10.360 --> 0:35:14.320
<v Speaker 17>for profit, not an uncontrollable event. That means companies must

0:35:14.320 --> 0:35:19.200
<v Speaker 17>prioritize retraining and reassignment before dismissing an employee. But for now,

0:35:19.280 --> 0:35:21.719
<v Speaker 17>all signs that the two sessions suggest the government is

0:35:21.760 --> 0:35:24.920
<v Speaker 17>going all in on tech at the risk of leaving

0:35:24.960 --> 0:35:26.160
<v Speaker 17>some people behind.

0:35:28.680 --> 0:35:29.960
<v Speaker 2>That was Bloomberg's mem in Lau.

0:35:30.120 --> 0:35:32.799
<v Speaker 3>Coming up, Gecko Robotics makes a deal with the US

0:35:32.960 --> 0:35:36.400
<v Speaker 3>Navy to monitor and maintain it's warships. We speak with

0:35:36.520 --> 0:35:40.560
<v Speaker 3>CEO Jake Lucerian. That's next. This is Bloomberg Tech.

0:35:51.760 --> 0:35:52.480
<v Speaker 6>US government.

0:35:52.600 --> 0:35:55.600
<v Speaker 5>Well, it's stepping up its use of AI to monitor aging,

0:35:55.640 --> 0:35:58.720
<v Speaker 5>infrastructure and modernized military systems and a new push. Gecko

0:35:58.800 --> 0:36:01.719
<v Speaker 5>Robotics has announced seventy one million dollar partnership with the

0:36:01.800 --> 0:36:05.279
<v Speaker 5>US Navy, deploying its AI powered robots to assess the

0:36:05.320 --> 0:36:09.480
<v Speaker 5>condition the readiness of American warships joining US now. Jake

0:36:09.640 --> 0:36:14.480
<v Speaker 5>lucis Arian, Gecko Robotics CEO and co founder Jake can

0:36:14.520 --> 0:36:17.719
<v Speaker 5>you measure what your robots are able to achieve in

0:36:17.840 --> 0:36:20.040
<v Speaker 5>terms of real term military readiness?

0:36:20.320 --> 0:36:23.719
<v Speaker 21>We're all about measuring the real information and details on

0:36:23.760 --> 0:36:26.080
<v Speaker 21>the ground, and so we swarm our robots all over

0:36:26.080 --> 0:36:27.759
<v Speaker 21>these ships as you see in the videos, and what

0:36:27.760 --> 0:36:30.040
<v Speaker 21>they're doing is they're gathering ground truth and information that

0:36:30.080 --> 0:36:32.520
<v Speaker 21>would typically take three or four months to be done

0:36:32.520 --> 0:36:34.680
<v Speaker 21>and gather one one millionth of the amount of information

0:36:34.800 --> 0:36:37.640
<v Speaker 21>data set that is not filtered to any source of

0:36:37.680 --> 0:36:41.000
<v Speaker 21>truth and software that could be gathered and then and

0:36:41.040 --> 0:36:43.960
<v Speaker 21>then in perpetuity be evaluated to help with planning into

0:36:43.960 --> 0:36:47.040
<v Speaker 21>the future. What we're providing to the Navy, and kudos

0:36:47.040 --> 0:36:49.480
<v Speaker 21>to the Navy for adopting this technology, you know, in

0:36:49.480 --> 0:36:52.600
<v Speaker 21>a way that's giving them an advantage over others that

0:36:52.719 --> 0:36:55.680
<v Speaker 21>deal with the same problem every single day. They're taking

0:36:55.800 --> 0:36:58.760
<v Speaker 21>very seriously this demands of getting to eighty percent readiness

0:36:58.800 --> 0:37:01.600
<v Speaker 21>of their fleets and to collect all this information data

0:37:01.760 --> 0:37:04.560
<v Speaker 21>that can help perpetuate goodness both now saving three to

0:37:04.600 --> 0:37:08.120
<v Speaker 21>four months of cycle time in maintenance cycles, but also

0:37:08.239 --> 0:37:10.279
<v Speaker 21>to the future to plan smarter so that we have

0:37:10.360 --> 0:37:12.280
<v Speaker 21>less and less days of downtime for the vessels.

0:37:12.440 --> 0:37:14.920
<v Speaker 5>I mean, you're seeing them flying, we're seeing them climbing,

0:37:14.960 --> 0:37:18.640
<v Speaker 5>we're seeing the hardware, but you're also about the interpretation

0:37:18.719 --> 0:37:20.920
<v Speaker 5>of the data as well. How are you developing your

0:37:20.920 --> 0:37:23.680
<v Speaker 5>own models to ensure that the right information is getting

0:37:23.800 --> 0:37:25.000
<v Speaker 5>to the end user.

0:37:25.239 --> 0:37:29.040
<v Speaker 2>Yeah, well, it's this example. And when we say at.

0:37:28.680 --> 0:37:30.480
<v Speaker 21>The company, a lot is if it's not ready, it

0:37:30.480 --> 0:37:32.920
<v Speaker 21>doesn't count. And that's very important as it relates to

0:37:32.960 --> 0:37:34.680
<v Speaker 21>the readiness of our fleets, as it relates to the

0:37:34.719 --> 0:37:37.160
<v Speaker 21>Turing conflict, what's going on right now in the Middle East,

0:37:37.160 --> 0:37:39.360
<v Speaker 21>and then also on the Pacific side. And you know,

0:37:39.360 --> 0:37:41.000
<v Speaker 21>we've been doing this for thirteen years or sort of

0:37:41.000 --> 0:37:43.120
<v Speaker 21>the company of a college dorm with this idea of

0:37:43.120 --> 0:37:44.480
<v Speaker 21>what if you could diagnose.

0:37:44.120 --> 0:37:45.200
<v Speaker 2>The health of the built world?

0:37:45.360 --> 0:37:47.360
<v Speaker 21>You know, what could that enable as it relates to

0:37:47.400 --> 0:37:49.879
<v Speaker 21>predicting what the future structures, how they should be built,

0:37:49.920 --> 0:37:52.320
<v Speaker 21>and then what we're going to what's going to occur,

0:37:53.040 --> 0:37:55.759
<v Speaker 21>and how to prevent that from occurring. And so we've

0:37:55.760 --> 0:37:59.759
<v Speaker 21>been improving these models and believing that if you can

0:37:59.760 --> 0:38:02.239
<v Speaker 21>gather the information in data using robots, turn atoms and

0:38:02.280 --> 0:38:05.359
<v Speaker 21>the bits, you can have such an incredible advantage as

0:38:05.440 --> 0:38:08.319
<v Speaker 21>related to how to make infrastructure smarter, make it, make

0:38:08.360 --> 0:38:11.560
<v Speaker 21>it more efficiently, and make even new structures. And so

0:38:11.680 --> 0:38:13.959
<v Speaker 21>these models are all being fed into a central source

0:38:13.960 --> 0:38:17.560
<v Speaker 21>of truth, a digital thread for critical infrastructure called Candileer.

0:38:18.840 --> 0:38:19.440
<v Speaker 2>Jake youa.

0:38:19.640 --> 0:38:23.200
<v Speaker 3>You presented basically at the Winning the AI Race summer

0:38:23.280 --> 0:38:26.279
<v Speaker 3>in DC last year, which was very much focused on

0:38:26.680 --> 0:38:30.960
<v Speaker 3>this administration's policy platforms for AI. I'm curious in the

0:38:30.960 --> 0:38:32.880
<v Speaker 3>time that that since past you've done a deal with

0:38:32.920 --> 0:38:35.279
<v Speaker 3>the Navy. You got it done, and I wonder what

0:38:35.320 --> 0:38:38.120
<v Speaker 3>that's like, you know, to see a project through to

0:38:38.400 --> 0:38:41.439
<v Speaker 3>fruition with some of the military apparatus of this nation.

0:38:42.080 --> 0:38:44.400
<v Speaker 21>It is so exciting and so incredible to see the

0:38:44.480 --> 0:38:47.080
<v Speaker 21>Navy being a leader in the world as relates to

0:38:47.120 --> 0:38:51.440
<v Speaker 21>giving our warfighters an advantage and advantage that no other

0:38:51.560 --> 0:38:54.000
<v Speaker 21>navy around the world, including China, has, and that's the

0:38:54.040 --> 0:38:57.440
<v Speaker 21>ability to have this incredible advantage with robotics in AI

0:38:57.760 --> 0:38:59.880
<v Speaker 21>to speed up how quickly we're gathering information and then

0:38:59.880 --> 0:39:01.640
<v Speaker 21>to deploying it. We're not just doing that, you know,

0:39:01.640 --> 0:39:04.160
<v Speaker 21>for the US government, We're doing that for the largest

0:39:04.160 --> 0:39:07.640
<v Speaker 21>companies in the world, companies like ADOC ADNOC, who's giving

0:39:07.680 --> 0:39:11.279
<v Speaker 21>this AI and robotics native approach. It's such an incredibly

0:39:11.640 --> 0:39:14.680
<v Speaker 21>advanced way. We're bringing that same technology and beyond to

0:39:14.760 --> 0:39:17.960
<v Speaker 21>the Navy and ensuring as well that it's not just

0:39:18.000 --> 0:39:20.839
<v Speaker 21>about talk about five years or ten years where you're

0:39:20.840 --> 0:39:24.279
<v Speaker 21>going to see autonomous systems and robots and AI affecting

0:39:24.360 --> 0:39:27.400
<v Speaker 21>the Navy in our and helping our warfighters. No, this

0:39:27.440 --> 0:39:29.840
<v Speaker 21>is actually happening today, and that is something that the

0:39:29.840 --> 0:39:33.600
<v Speaker 21>administration cares deeply about. That's something that Secretary Phalan of

0:39:33.680 --> 0:39:36.040
<v Speaker 21>the Navy cares deeply about. If you want to have

0:39:36.160 --> 0:39:39.200
<v Speaker 21>the best Navy in the world, the best assets and

0:39:39.239 --> 0:39:42.080
<v Speaker 21>programs in the world, most robust, you need impact today

0:39:42.120 --> 0:39:45.200
<v Speaker 21>and as you're seeing today, matters, and it matters more

0:39:45.239 --> 0:39:45.640
<v Speaker 21>than ever.

0:39:46.239 --> 0:39:50.160
<v Speaker 3>Right, Jake, what is your core competence at Gecko Robotics.

0:39:50.400 --> 0:39:52.920
<v Speaker 3>Are you good at hardware or are you good at software?

0:39:53.440 --> 0:39:56.560
<v Speaker 21>We're good at building robotics systems that go out and

0:39:56.600 --> 0:40:00.239
<v Speaker 21>gather information and data sets that no one want knew

0:40:00.440 --> 0:40:03.000
<v Speaker 21>how to ever capture before, but then to interpreting it

0:40:03.080 --> 0:40:05.279
<v Speaker 21>to allow for decisions to be made, to give you

0:40:05.320 --> 0:40:09.279
<v Speaker 21>advantages that can speed up times to bring critical infrastructure

0:40:09.320 --> 0:40:12.040
<v Speaker 21>that's you know, constantly delayed, constantly over budget because of

0:40:12.080 --> 0:40:14.400
<v Speaker 21>how hard it is to find out where are things broken,

0:40:14.440 --> 0:40:16.719
<v Speaker 21>how to fix it. The robots are able to gather

0:40:16.760 --> 0:40:19.480
<v Speaker 21>all the information, not how to destroy the infrastructure and

0:40:19.520 --> 0:40:22.080
<v Speaker 21>assets to gather it and then provide the ability to

0:40:22.160 --> 0:40:25.000
<v Speaker 21>optimize where to make the repairs, the replacements, and then

0:40:25.040 --> 0:40:27.400
<v Speaker 21>into the future how to plan for that to potentially

0:40:27.400 --> 0:40:29.279
<v Speaker 21>never even have a shutdown. You know, we've been able

0:40:29.280 --> 0:40:32.359
<v Speaker 21>to prevent shutdowns at oil and gas facilities that were

0:40:32.360 --> 0:40:34.960
<v Speaker 21>going to occur that would have cause big explosions, and

0:40:35.000 --> 0:40:37.080
<v Speaker 21>for the Navy be able to accelerate and give them

0:40:37.120 --> 0:40:39.359
<v Speaker 21>advantages in terms of how to get our ships at

0:40:39.360 --> 0:40:42.200
<v Speaker 21>a dry dock and defending our values. And so we're

0:40:42.239 --> 0:40:45.800
<v Speaker 21>just so incredibly proud to be serving the Navy in

0:40:45.840 --> 0:40:48.279
<v Speaker 21>this way, and just kudos to the Navy for taking

0:40:48.280 --> 0:40:50.799
<v Speaker 21>a big, bold step as related to giving us this advantage.

0:40:51.520 --> 0:40:54.200
<v Speaker 3>J Luceerrarian of Gecko Robotics great to heavy back on

0:40:54.239 --> 0:40:54.560
<v Speaker 3>the show.

0:40:54.640 --> 0:40:55.399
<v Speaker 2>Thank you very much,