WEBVTT - Nvidia Investors Wait for Signals of Growth in Earnings

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

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

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<v Speaker 1>and ever Low in San Francisco.

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<v Speaker 2>This is Bloomberg Tech coming up. All eyes on in

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<v Speaker 2>video as a chip maker reports sarnings after the closing bell.

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<v Speaker 2>What to expect from the world's most Valuable company? Throughout

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<v Speaker 2>this hour, plus SpaceX's Starship hits a major milestone after

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<v Speaker 2>deploying satellites in space for the first time. An IBM

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<v Speaker 2>and AMD partner up to develop quantum centric supercomputing. We'll

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<v Speaker 2>discussed with IBM's Quantum VP, but first we check in

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<v Speaker 2>on these markets, and actually we just check in the

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<v Speaker 2>world's most valuable company. We check in one that dominates

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<v Speaker 2>the SMP to the tune of eight percent. I'm looking

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<v Speaker 2>at a ten percent higher for InVideo.

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<v Speaker 3>We are just one.

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<v Speaker 2>Percentage point away from a new record high for this company.

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<v Speaker 2>Will it get there after the closing bell, after the

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<v Speaker 2>market shut In that post hours movement, we could see

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<v Speaker 2>whitsh lash of up to six percent either direction, according

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<v Speaker 2>to the options market. I'm looking at the waitings because

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<v Speaker 2>this is why we focus on this company and this

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<v Speaker 2>is why it's basically our super Bowl today. Eight percent

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<v Speaker 2>of the s and P five hundred, we are twenty

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<v Speaker 2>four percent of the tech sector within that SMP. Then

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<v Speaker 2>aw's that one hundred now we're seeing in video make

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<v Speaker 2>up ten percent of the waiting.

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<v Speaker 3>And so therefore we go to a man.

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<v Speaker 2>That has covered this stock before you and I could

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<v Speaker 2>pronounce in video properly. It is the one and only

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<v Speaker 2>in King, it's your super Bowl tonight. Ian And just

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<v Speaker 2>so many questions remain about the forecast. It feels that

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<v Speaker 2>there is where the guide is going to be keenly watched.

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<v Speaker 4>Yeah, now that's absolutely true. I mean historically in video

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<v Speaker 4>doesn't just have to beat on this forecast and project

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<v Speaker 4>a rosy future, it has to blow past it and

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<v Speaker 4>give Wall Street the sense that this never ending surge

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<v Speaker 4>is coming. As we've seen with Carmen's story, things are

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<v Speaker 4>very unclear this time. We really don't know how much

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<v Speaker 4>China is going to be in that forecast, how much

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<v Speaker 4>China can be in that forecast, And that's really the

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<v Speaker 4>wildcard this time.

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<v Speaker 2>And is we're going to have to hear from Jensen

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<v Speaker 2>not only about H twenty but where he guies in

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<v Speaker 2>terms of a B thirty, the latest development of the

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<v Speaker 2>Blackwell architecture that maybe gets signed off to be sold

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<v Speaker 2>to China.

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<v Speaker 3>But more broadly, are we hearing enough.

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<v Speaker 2>From the hyperscalers that the commitment is then we were

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<v Speaker 2>expecting what fifty percent growth in revenue for this fiscal quarter.

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<v Speaker 3>It's got to slow down at some point in.

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<v Speaker 4>You you would think so, But then you look at

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<v Speaker 4>the numbers and you look at the growth rate that

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<v Speaker 4>has been sustained. I mean as a percentage. Of course

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<v Speaker 4>it's slowing. It's going from above sixty percent to about

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<v Speaker 4>fifty percent, but fifty percent at an enormously high level.

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<v Speaker 4>This is a company that's on course to become what

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<v Speaker 4>a third of total semi conductor sales worldwide. So you know,

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<v Speaker 4>you pick your numbers and you can tell a story,

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<v Speaker 4>but every story is incredible. At this point, Yes, by

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<v Speaker 4>any measure, numbers have to slow down. These growth rates

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<v Speaker 4>are not sustainable, but the numbers are still huge, with

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<v Speaker 4>twenty billion dollars up probably from where we were a

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<v Speaker 4>year ago on the forecast quarter cell and when.

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<v Speaker 2>We think about that as hyperscalers, they are about forty

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<v Speaker 2>percent of demand. How much does Jensen one once again

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<v Speaker 2>have to guide the market. Then they will dominate not

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<v Speaker 2>only in the training of data, but in the inference

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<v Speaker 2>the use of that data going forward.

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<v Speaker 4>Yeah, now that's a very good point. I mean, Hyperscalers

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<v Speaker 4>have been around half of its data center sales for

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<v Speaker 4>a long time, trending slightly higher if anything. What would

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<v Speaker 4>really really please investors if that number went down, because

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<v Speaker 4>that would prove that AI and the use of AI

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<v Speaker 4>and the deployment of AI systems is spreading out, spreading

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<v Speaker 4>out across the economy, getting into all of these other industries,

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<v Speaker 4>and not just the kind of pet project for Microsoft

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<v Speaker 4>often Amazon. That would be a really strong sign if

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<v Speaker 4>they could deliver something like that today.

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<v Speaker 2>I have a feeling sovereign AI is going to be

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<v Speaker 2>on your Bingo card. Two in King, we thank you

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<v Speaker 2>as always as we prep ourselves for after the closing bell.

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<v Speaker 2>Who else is prepping ourself? Fionness in Culta Senior Analystic

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<v Speaker 2>City Index, Financial Markets and remind us and the perspective

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<v Speaker 2>here it is so dominant for the rest of the market. Yes,

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<v Speaker 2>we might get a big swing and in video up

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<v Speaker 2>to six percent after hours, but it's important for the

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<v Speaker 2>other AI names.

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<v Speaker 5>Yes, completely, and I would even go beyond that and say,

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<v Speaker 5>it's not just AI names. This this is the stop

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<v Speaker 5>that because it dominates and because it is such the

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<v Speaker 5>litmus test for AI, but actually it has the ability

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<v Speaker 5>to hit sentiment more broadly. You know, it's such a

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<v Speaker 5>large component of the S and P five hundred. We've

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<v Speaker 5>obviously seen a little bit of caution actually as we've

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<v Speaker 5>been sort of coming into these results. Know, there was

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<v Speaker 5>that MIT report that just raised some questions about profitability,

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<v Speaker 5>revenue growth surrounding sort of ninety five percent of AI

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<v Speaker 5>project and that did cause the market just to question,

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<v Speaker 5>you know, should we be up at these levels for

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<v Speaker 5>AI stocks? And I think you know, that's why there

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<v Speaker 5>is such a massive focus on this these results, you know,

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<v Speaker 5>not only just with what Nvidia are doing, but what

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<v Speaker 5>it does mean for the broader AI trade and tech

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<v Speaker 5>more broadly.

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<v Speaker 2>Remind us and videos one percentage point off a record

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<v Speaker 2>high four point four trillion dollar market capitalization, how much

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<v Speaker 2>positive sentiment is in the rest of the space, even

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<v Speaker 2>after last week's big sell.

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<v Speaker 3>Off in names such as Palenter. Yeah, you know, it's

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<v Speaker 3>really interesting.

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<v Speaker 5>I mean, obviously there is a lot of growth expectations

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<v Speaker 5>which are priced into these levels. We've talked about, you know,

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<v Speaker 5>forward guidance being the key figure to be watching in

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<v Speaker 5>these results, and that's just so that the market can

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<v Speaker 5>feel comfortable that the lofty levels we're trading at are

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<v Speaker 5>indeed supported by some sort of fundamental But I think

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<v Speaker 5>you know, the fact is we are expecting potentially a

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<v Speaker 5>beat from Nvidia.

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<v Speaker 3>The question is by how much, you know, what will

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<v Speaker 3>that forward guidance be looking like?

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<v Speaker 5>Will we continue to see that level of strong growth

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<v Speaker 5>that we have seen. That's what the market wants to see.

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<v Speaker 5>That's what investors want to see in order to remain

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<v Speaker 5>upbeat about this trade. I mean, I do think longer

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<v Speaker 5>term strategically, we know that AI is a solid trade.

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<v Speaker 5>But near term we have seen that caution set in

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<v Speaker 5>just as far as sentiment is concerned, obviously, as far

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<v Speaker 5>as geopolitical events are concerned and factored, and then also

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<v Speaker 5>as far as that sort of flower model growth rollout

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<v Speaker 5>might be concerned as well. So lots to be watching

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<v Speaker 5>out for.

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<v Speaker 2>Yeah, can you break down for us a little bit

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<v Speaker 2>just from the sentiment that you get from your own clients,

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<v Speaker 2>but more broady, how many people are long only and

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<v Speaker 2>long term committed to this company or how many people

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<v Speaker 2>are on the edges just training it and could see

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<v Speaker 2>therefore volatility in the name.

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<v Speaker 5>Yeah, So, I mean, this is by far our most

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<v Speaker 5>popular equity within our business. We've seen that the vast

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<v Speaker 5>majority of clients are long on in the video and

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<v Speaker 5>we do see that you know, there is this longer

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<v Speaker 5>term sense towards the stock as well, that is something

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<v Speaker 5>in there. But you also do see a lot of

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<v Speaker 5>the attempts to trade on that volatility. But you know,

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<v Speaker 5>our clients are very keen on this. This is this

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<v Speaker 5>is often the busiest day for one of the busiest days,

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<v Speaker 5>and we do find that tomorrow there will be a

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<v Speaker 5>lot of conversation and sort of breaking down and unpacking

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<v Speaker 5>what the results have been telling us as well. So

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<v Speaker 5>but you know, we do see that this is one

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<v Speaker 5>of those rare stocks that we do see both the

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<v Speaker 5>longer position holding as well as the intra day volatility

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<v Speaker 5>gets the day traders as well.

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<v Speaker 2>And it's just so streets ahead of the competition in

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<v Speaker 2>terms of just market capitalization. I mean, is the only

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<v Speaker 2>other chip maker out there that's above a trillion dollars

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<v Speaker 2>When you think about AMD, it has but a quarter

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<v Speaker 2>of a trillion in terms of market capitalization compared to

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<v Speaker 2>in videos. And we're not even going to talk about intels,

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<v Speaker 2>but fon have you seen any of your clients trying

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<v Speaker 2>to hedge this? How have they been able to think

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<v Speaker 2>about owning and being long in video and protecting themselves

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<v Speaker 2>from any downside?

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<v Speaker 5>Yeah, you know, it's actually quite difficult to be able

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<v Speaker 5>to sort of bring together a pure hedge on this

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<v Speaker 5>given the dominance that we do see in n video.

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<v Speaker 5>As you pointed out, you know, you can do some

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<v Speaker 5>hedging surrounding some competitors. Also, if you can get hold

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<v Speaker 5>of those AI indiceeds, then that could also work as

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<v Speaker 5>a hedge. But I think broadly speaking, it is quite

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<v Speaker 5>difficult to be well hedged in against the upside in nvidea,

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<v Speaker 5>just because, as you said, it just really is a

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<v Speaker 5>streak the head of competition and it doesn't seem to

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<v Speaker 5>be anyone really on its heels just yet. Obviously, we

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<v Speaker 5>had those concerns at the beginning of the year about

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<v Speaker 5>deep deep seek, but that hasn't really rolled that into

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<v Speaker 5>something too dangerous as far as competition is concerned just yet.

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<v Speaker 5>That's not to say it's not down their own, but

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<v Speaker 5>just for now, it doesn't feel like there's too much

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<v Speaker 5>snapping on end videos heels.

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<v Speaker 2>I mean, it is an interesting camera con technologies, it's

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<v Speaker 2>a Chinese name, it's an AI accelerated developer themselves making trips,

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<v Speaker 2>and like Huaweis, they had phenomenal growth in their profitability.

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<v Speaker 2>I mean, it has a much smaller market capitalization. But

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<v Speaker 2>just going back to what we're discussing with Ian and

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<v Speaker 2>their overhang of China, how important is that to you

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<v Speaker 2>and the clients to hear about the future growth trajectory there.

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<v Speaker 3>That's very important.

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<v Speaker 5>I think, you know, we can't sort of diminish how

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<v Speaker 5>important that will be. That's going to be a key

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<v Speaker 5>area that we'll be watching out for because it does

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<v Speaker 5>remain a key risk and obviously that can then affect

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<v Speaker 5>the valuation, it can affect what the growth outlook en

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<v Speaker 5>video is. So I think that is definitely going to

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<v Speaker 5>be one of the key factors that we'll be watching

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<v Speaker 5>as it does present itself as a potential to really

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<v Speaker 5>weigh or limit the upside as far as and videos

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<v Speaker 5>potential growth is concerned.

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<v Speaker 2>When you're thinking about in video and the other industry groups,

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<v Speaker 2>A SINGULFS I mean, you're just saying what the limiting

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<v Speaker 2>factor actually for many is power.

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<v Speaker 3>And I'm wondering how many of.

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<v Speaker 2>Your clients are looking at in video and feeling at

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<v Speaker 2>this level they can't get in, or are they and

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<v Speaker 2>therefore looking to spread and diversify, or are still people

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<v Speaker 2>very committed to buying in even at a four point

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<v Speaker 2>four trillion dollar market cap.

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<v Speaker 6>Yeah, do you know there is still demand out there.

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<v Speaker 5>We're still seeing demand out there, and despite the fact

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<v Speaker 5>that we are trading at you know, really impressive levels,

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<v Speaker 5>but I do think we still still have this idea

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<v Speaker 5>of the concept that this idea of the AI trade

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<v Speaker 5>spreading out and diversify. You know, we've noticed that obviously

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<v Speaker 5>Nvidia has been the stand up performer here, but we

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<v Speaker 5>are seeing that we've there have been sort of a

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<v Speaker 5>strong growth in other areas as well. We've seen the

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<v Speaker 5>rest of the AI stocks have performed well across the year,

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<v Speaker 5>and I think there is potential for those two continue

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<v Speaker 5>performing well on the back of upbeat results from Nvidio.

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<v Speaker 3>So again we keep coming back to that idea.

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<v Speaker 5>You know, if Nvidia does well, then we see that

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<v Speaker 5>trickle back down into the rest of that AI trade.

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<v Speaker 5>If it doesn't, if we see a slight disappointment on

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<v Speaker 5>that forward guidance, then potentially we could see that really

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<v Speaker 5>reflecting badly on those other AI stocks as well.

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<v Speaker 3>So yeah, that's all we're watching out for our hinges.

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<v Speaker 2>On four pm this evening, we thank you Fonesesenkotta from

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<v Speaker 2>city Inex Financial Markets. Now coming up, SpaceX launches it's

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<v Speaker 2>ten test flights successfully up the days at Las.

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<v Speaker 3>More on that. Next, there's a BLUEBG.

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<v Speaker 7>Tech poverage.

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<v Speaker 3>Time now for Talking Tech and first up.

0:12:14.360 --> 0:12:18.320
<v Speaker 2>Chinese food delivery company Maijwan was of huge losses this

0:12:18.400 --> 0:12:21.440
<v Speaker 2>quarter due to a fierce price war with rivals.

0:12:21.120 --> 0:12:22.480
<v Speaker 3>Ali Baba and JD dot Com.

0:12:22.520 --> 0:12:25.679
<v Speaker 2>Now the company issued a dire prediction, citing quote irrational

0:12:25.679 --> 0:12:28.520
<v Speaker 2>competition that wiped out its profit in the June quarter,

0:12:28.600 --> 0:12:33.080
<v Speaker 2>with net income plumenting ninety seven percent plus Chinese AI

0:12:33.160 --> 0:12:35.440
<v Speaker 2>chip designer Camera con Technologies when.

0:12:35.320 --> 0:12:37.640
<v Speaker 3>It swung to a record profit in the first half.

0:12:37.800 --> 0:12:41.319
<v Speaker 2>The results reflect an increasing shift to employed domestic chip alternatives,

0:12:41.559 --> 0:12:44.839
<v Speaker 2>encouraged to cause by Beijing citing US security concerns and

0:12:44.960 --> 0:12:49.160
<v Speaker 2>export curb uncertainty, and Apple plans to hold its big

0:12:49.240 --> 0:12:51.880
<v Speaker 2>full product launch on September the ninth, when the company

0:12:51.920 --> 0:12:55.160
<v Speaker 2>is expected to introduce an iPhone seventeen lineup that includes

0:12:55.200 --> 0:12:58.000
<v Speaker 2>a new, skinnier version of the signature device. Now, the

0:12:58.000 --> 0:13:01.840
<v Speaker 2>events tagline is are dropping according to an invitation posted

0:13:01.920 --> 0:13:06.160
<v Speaker 2>online and sent to the media, and it will stream online. Now,

0:13:06.160 --> 0:13:09.760
<v Speaker 2>another company that we're watching, privately held SpaceX. It is

0:13:09.840 --> 0:13:14.160
<v Speaker 2>successfully launched its tenth Starship rocket test flight last night

0:13:14.440 --> 0:13:17.040
<v Speaker 2>and in a major milestone, it carried and deployed Starlink

0:13:17.040 --> 0:13:19.800
<v Speaker 2>satellites in space for the first time. This comes after

0:13:19.800 --> 0:13:22.599
<v Speaker 2>a year not with pretty explosive setbacks.

0:13:22.760 --> 0:13:23.240
<v Speaker 3>Punnemberg.

0:13:23.280 --> 0:13:26.400
<v Speaker 2>Space reporter Lauren Grush joins us now and just how

0:13:26.440 --> 0:13:29.480
<v Speaker 2>important was it that these satellites in particular were deployed.

0:13:30.840 --> 0:13:32.920
<v Speaker 8>Well, I would say this was the exact kind of

0:13:33.040 --> 0:13:36.400
<v Speaker 8>test flight that SpaceX really needed to achieve after that

0:13:36.480 --> 0:13:41.040
<v Speaker 8>volatile year you explained. But deployed satellites is important because

0:13:41.080 --> 0:13:43.880
<v Speaker 8>that's kind of one of the key objectives for Starship.

0:13:43.920 --> 0:13:46.839
<v Speaker 8>When it becomes operational, it's supposed to launch the much

0:13:46.960 --> 0:13:51.200
<v Speaker 8>larger Starlink Internet satellites that SpaceX is building and optimized

0:13:51.240 --> 0:13:54.640
<v Speaker 8>for the specific size spacecraft. So the fact that it

0:13:54.679 --> 0:13:57.160
<v Speaker 8>was able to demonstrate that shows that they're one step

0:13:57.200 --> 0:14:00.319
<v Speaker 8>closer to actually using this vehicle as a launch vele

0:14:00.360 --> 0:14:01.960
<v Speaker 8>that can put satellites intour of it.

0:14:02.280 --> 0:14:03.199
<v Speaker 3>Beautiful shots.

0:14:03.480 --> 0:14:07.160
<v Speaker 2>But they rounded it out as an overall success. But

0:14:07.280 --> 0:14:09.680
<v Speaker 2>not everything was too peachy, Right, What else did they

0:14:09.800 --> 0:14:11.760
<v Speaker 2>learn from the re entry in particular?

0:14:12.679 --> 0:14:16.200
<v Speaker 8>Right, that re entry portion is still very difficult for

0:14:16.280 --> 0:14:18.600
<v Speaker 8>them to perfect, but you know, that is what they're

0:14:18.600 --> 0:14:20.960
<v Speaker 8>trying to do. They're trying to do something that nobody

0:14:20.960 --> 0:14:25.080
<v Speaker 8>else has done, which has create a fully reusable vehicle.

0:14:25.400 --> 0:14:27.320
<v Speaker 8>And so what they're trying to see is if they

0:14:27.320 --> 0:14:31.560
<v Speaker 8>can bring the starship back without it disintegrating. Of course,

0:14:31.880 --> 0:14:34.840
<v Speaker 8>there were some chunks of the vehicle that broke away

0:14:34.920 --> 0:14:37.320
<v Speaker 8>during that re entry, but it just goes to show

0:14:37.320 --> 0:14:39.000
<v Speaker 8>that they have a little bit more to learn and

0:14:39.160 --> 0:14:43.440
<v Speaker 8>making that reusable orbital heat shield up to snuff and

0:14:43.440 --> 0:14:44.400
<v Speaker 8>the way that they need it.

0:14:45.240 --> 0:14:48.040
<v Speaker 2>They say time and time again that sort of failure

0:14:48.120 --> 0:14:50.560
<v Speaker 2>is the learning process here, but they had had a

0:14:50.640 --> 0:14:52.320
<v Speaker 2>run up of failures in the years. This was a

0:14:52.400 --> 0:14:55.640
<v Speaker 2>key test. Just remind us how this goes forward to

0:14:56.080 --> 0:14:58.920
<v Speaker 2>replace Fulcon nine, because already they've won big contract with

0:14:59.000 --> 0:15:01.360
<v Speaker 2>NASA to use this right.

0:15:01.480 --> 0:15:04.440
<v Speaker 8>I mean SpaceX has basically put all of its eggs

0:15:04.440 --> 0:15:08.240
<v Speaker 8>in the starship basket. It's supposed to eventually replace their

0:15:08.280 --> 0:15:11.520
<v Speaker 8>workhorse rocket, as you mentioned, the Falcon nine, but it

0:15:11.560 --> 0:15:12.680
<v Speaker 8>also has a lot of.

0:15:12.680 --> 0:15:13.920
<v Speaker 3>Other tasks to do.

0:15:14.080 --> 0:15:18.240
<v Speaker 8>It's designed to eventually take humans and cargo to deep

0:15:18.240 --> 0:15:21.520
<v Speaker 8>space destinations like the Moon and of course Mars to

0:15:21.560 --> 0:15:25.280
<v Speaker 8>start that settlement that CEO Elon Musk has always dreamed of.

0:15:25.280 --> 0:15:27.840
<v Speaker 8>Of course, there's still quite a lot to do before

0:15:28.400 --> 0:15:30.080
<v Speaker 8>that reality can be achieved.

0:15:30.560 --> 0:15:30.760
<v Speaker 6>You know.

0:15:30.840 --> 0:15:32.520
<v Speaker 8>One of the big things is that they'll have to

0:15:32.600 --> 0:15:37.320
<v Speaker 8>demonstrate in space orbital refueling at a scale that no

0:15:37.360 --> 0:15:40.520
<v Speaker 8>one has ever achieved before, and so they mentioned that

0:15:40.520 --> 0:15:43.720
<v Speaker 8>they hope to demonstrate that as soon as next year.

0:15:44.080 --> 0:15:46.280
<v Speaker 8>But that's going to be a really big part of

0:15:46.360 --> 0:15:49.720
<v Speaker 8>actually unlocking this vehicle and making it the deep space

0:15:49.840 --> 0:15:51.480
<v Speaker 8>vehicle that they advertise it to be.

0:15:52.200 --> 0:15:55.120
<v Speaker 2>We most long and grush on all things SpaceX. We

0:15:55.160 --> 0:16:03.640
<v Speaker 2>so appreciate it. Thank you much. IBM and AMD where

0:16:03.640 --> 0:16:06.920
<v Speaker 2>they've announced a partnership to develop the next generation of

0:16:06.960 --> 0:16:10.120
<v Speaker 2>computing architectures. IBM shares were up following the news that

0:16:10.160 --> 0:16:10.960
<v Speaker 2>came out yesterday.

0:16:11.200 --> 0:16:12.360
<v Speaker 3>Please to welcome to the show.

0:16:12.480 --> 0:16:15.880
<v Speaker 2>It's VP of Quantum Ja Gambetta, and the next generation

0:16:15.960 --> 0:16:19.760
<v Speaker 2>of computing architecture is bringing together supercomputing and quantum.

0:16:19.800 --> 0:16:21.160
<v Speaker 3>What does this partnership.

0:16:20.680 --> 0:16:23.400
<v Speaker 7>Bring Jay, Yeah, this is well first, thanks for having

0:16:23.440 --> 0:16:26.840
<v Speaker 7>me here. What's really exciting is we are actually getting

0:16:26.880 --> 0:16:29.840
<v Speaker 7>to the point where quantum computers are getting to become

0:16:29.920 --> 0:16:32.800
<v Speaker 7>like almost a first class citizen in the future of computing.

0:16:33.120 --> 0:16:37.200
<v Speaker 7>And so this partnership is bringing AMD, which builds really

0:16:37.560 --> 0:16:42.600
<v Speaker 7>high performance, excellent GPUs, our leading quantum devices, and really

0:16:42.640 --> 0:16:45.520
<v Speaker 7>starting to bring this fabric together. We want to create

0:16:45.880 --> 0:16:49.240
<v Speaker 7>this future of computing that allows us to run things

0:16:49.240 --> 0:16:53.080
<v Speaker 7>on quantum or run things on GPUs and really push

0:16:53.680 --> 0:16:55.160
<v Speaker 7>computation to the next level.

0:16:55.320 --> 0:16:56.640
<v Speaker 3>So that hybrid approach.

0:16:56.920 --> 0:16:59.600
<v Speaker 2>It almost makes me think of the new GBT five

0:16:59.600 --> 0:17:01.480
<v Speaker 2>model in terms, and they will use the right model

0:17:01.520 --> 0:17:03.760
<v Speaker 2>for the right question. Is this kind of way you're

0:17:03.760 --> 0:17:05.840
<v Speaker 2>doing it? If it can be solved with supercomputing, you

0:17:05.880 --> 0:17:08.040
<v Speaker 2>go that way. Otherwise it goes to quantum. How will

0:17:08.040 --> 0:17:08.720
<v Speaker 2>this function?

0:17:09.400 --> 0:17:10.320
<v Speaker 9>That's exactly right.

0:17:10.400 --> 0:17:12.760
<v Speaker 7>So a lot of people think quantum computers will replace

0:17:13.080 --> 0:17:16.680
<v Speaker 7>classical computers. We've never had that view. We actually think

0:17:16.760 --> 0:17:20.640
<v Speaker 7>quantum brings this unique ability to look at certain problems

0:17:20.640 --> 0:17:23.040
<v Speaker 7>a little bit different. And now if you mix this

0:17:23.200 --> 0:17:26.240
<v Speaker 7>and make it so that it works with HBC AI,

0:17:26.720 --> 0:17:30.320
<v Speaker 7>you really can start to bring many different forms of

0:17:30.359 --> 0:17:32.680
<v Speaker 7>computing together and really advance.

0:17:32.400 --> 0:17:33.160
<v Speaker 9>What is possible.

0:17:33.520 --> 0:17:36.880
<v Speaker 2>Okay, so make it tangible for our audience, because they've

0:17:37.200 --> 0:17:40.120
<v Speaker 2>always seen the promise of quantum. You're saying, now it's

0:17:40.119 --> 0:17:44.480
<v Speaker 2>a first class citizen in perhaps driving forward medical use,

0:17:44.600 --> 0:17:49.159
<v Speaker 2>thinking about the future of finance or algorithms. But what

0:17:49.280 --> 0:17:51.840
<v Speaker 2>precisely do you think that this hybrid will offer.

0:17:52.480 --> 0:17:55.960
<v Speaker 7>So it's a great question, and we've got to get

0:17:56.000 --> 0:17:59.720
<v Speaker 7>to the point where quantum is really getting us beyond

0:18:00.119 --> 0:18:02.119
<v Speaker 7>we can do with classical which we think will happen

0:18:02.119 --> 0:18:03.879
<v Speaker 7>in the next year or so. But we're getting at

0:18:03.880 --> 0:18:06.719
<v Speaker 7>a point where it's allowing us to look at things

0:18:06.920 --> 0:18:09.080
<v Speaker 7>in a different way. To give you an example, take

0:18:09.600 --> 0:18:13.360
<v Speaker 7>a hard problem I don't know, solving and designing drugs.

0:18:13.560 --> 0:18:15.720
<v Speaker 7>You can spend a lot of money to model it.

0:18:16.000 --> 0:18:18.800
<v Speaker 7>You can spend ten years of research. Imagine a future

0:18:18.800 --> 0:18:21.600
<v Speaker 7>where you could have AI scanning vast amounts of data,

0:18:22.280 --> 0:18:26.360
<v Speaker 7>HBC or GPUs processing crunching that data, and then quantum

0:18:26.600 --> 0:18:29.840
<v Speaker 7>simulating the quantum physics at an accuracy we were never

0:18:29.920 --> 0:18:32.639
<v Speaker 7>able to do before. Now you put all this together,

0:18:32.880 --> 0:18:36.959
<v Speaker 7>you can start to imagine workflows that go beyond just

0:18:37.840 --> 0:18:41.959
<v Speaker 7>AI or HPC or quantum and creating this we call

0:18:42.000 --> 0:18:45.320
<v Speaker 7>it quantum centric supercomputing, but essentially this new fabric that

0:18:45.359 --> 0:18:45.920
<v Speaker 7>allows you.

0:18:45.920 --> 0:18:46.359
<v Speaker 6>To do that.

0:18:46.680 --> 0:18:50.200
<v Speaker 7>So what's quantum doing. It's giving you accuracy for problems

0:18:50.200 --> 0:18:52.160
<v Speaker 7>that we didn't have that accuracy before.

0:18:53.040 --> 0:18:55.760
<v Speaker 2>I'm going to ask a sensitive question, but why IMD

0:18:56.280 --> 0:18:59.560
<v Speaker 2>because Video's got quantum accelerator computing as well.

0:19:00.320 --> 0:19:04.000
<v Speaker 7>Honestly, we are creating this future, and anyone that shares

0:19:04.000 --> 0:19:06.679
<v Speaker 7>a vision and we're the same as US that is

0:19:07.040 --> 0:19:11.840
<v Speaker 7>towards this future that has quantum working with classical we're

0:19:11.840 --> 0:19:15.359
<v Speaker 7>happy to partner with. So we've got this partnership with

0:19:15.400 --> 0:19:17.520
<v Speaker 7>AMD that has got two parts of it. One is

0:19:17.600 --> 0:19:20.760
<v Speaker 7>making our quantum computers better. The second is bringing these

0:19:20.920 --> 0:19:23.719
<v Speaker 7>accelerators working to it. But as we go forward, we

0:19:23.760 --> 0:19:26.919
<v Speaker 7>have partners with the national labs or all around the world.

0:19:27.160 --> 0:19:30.359
<v Speaker 7>But we want to show that this future is not

0:19:30.520 --> 0:19:33.800
<v Speaker 7>just words, it's actually real. So anyone that shares the

0:19:33.840 --> 0:19:35.159
<v Speaker 7>same view, we're happy to partner.

0:19:35.160 --> 0:19:38.040
<v Speaker 2>So Jensen could come and say me too, please, I'm

0:19:38.080 --> 0:19:42.240
<v Speaker 2>happy too. I'm interested in what the limiting factor is now,

0:19:42.320 --> 0:19:46.280
<v Speaker 2>because it's often been about sort of fault tolerant quantum computing.

0:19:46.760 --> 0:19:48.520
<v Speaker 2>Is that what you need to get to You sort

0:19:48.520 --> 0:19:49.440
<v Speaker 2>of promised us that by.

0:19:49.359 --> 0:19:50.200
<v Speaker 3>Twenty twenty nine.

0:19:50.400 --> 0:19:53.840
<v Speaker 7>Yes, so think of two sides of it. By twenty

0:19:53.920 --> 0:19:56.520
<v Speaker 7>twenty nine, we want to have a fault tolerant quanta computer.

0:19:57.160 --> 0:19:59.720
<v Speaker 7>And what we've learned through all the hard science and

0:19:59.760 --> 0:20:03.200
<v Speaker 7>energy neering is we need classical computers to make that possible.

0:20:03.400 --> 0:20:06.040
<v Speaker 7>They've got to do the we call it decoding, but

0:20:06.160 --> 0:20:08.919
<v Speaker 7>essentially removing the effects of errors. So part of this

0:20:08.960 --> 0:20:12.439
<v Speaker 7>partnership is how do we actually use classical computers to

0:20:12.440 --> 0:20:15.320
<v Speaker 7>make quantum computers better. And then at the same time,

0:20:15.640 --> 0:20:18.119
<v Speaker 7>we really have to show the value of quantum computers

0:20:18.440 --> 0:20:20.879
<v Speaker 7>and we have to solve them for interesting problems. So

0:20:20.960 --> 0:20:24.879
<v Speaker 7>now we need quantum computers working with classical computers in

0:20:24.920 --> 0:20:29.800
<v Speaker 7>this quantum centric supercomputing hybrid approach to really bring forward

0:20:29.880 --> 0:20:33.040
<v Speaker 7>early applications so that we can actually start to see

0:20:33.640 --> 0:20:39.119
<v Speaker 7>for whether it's in finance optimization, whether it's in simulating materials,

0:20:39.240 --> 0:20:40.919
<v Speaker 7>we can start to see this value happen.

0:20:41.359 --> 0:20:43.320
<v Speaker 2>What's interesting is we like to sort of pit the

0:20:43.400 --> 0:20:47.720
<v Speaker 2>generative AI landscape as a race. You're very committed to

0:20:47.760 --> 0:20:50.439
<v Speaker 2>open source nature of this to try and build learning.

0:20:50.560 --> 0:20:53.680
<v Speaker 2>How much is quantum a race? Where does the money

0:20:53.760 --> 0:20:56.400
<v Speaker 2>end up coming in terms of f IBM.

0:20:56.040 --> 0:20:57.640
<v Speaker 9>So it is a race.

0:20:57.800 --> 0:21:00.600
<v Speaker 7>We have to build hardware, and we've been leaders at

0:21:00.640 --> 0:21:02.720
<v Speaker 7>quantum hardware for a very long time where you're going

0:21:02.760 --> 0:21:06.399
<v Speaker 7>as fast as we can do it. But you asked before,

0:21:06.440 --> 0:21:09.840
<v Speaker 7>how do we get from having the hardware to value.

0:21:10.359 --> 0:21:14.880
<v Speaker 7>You need smart people to discover algorithms, and then through

0:21:14.920 --> 0:21:19.320
<v Speaker 7>discovering algorithms, you create use cases, you create examples. We

0:21:19.359 --> 0:21:22.520
<v Speaker 7>are committed to open sourcing the tools for that algorithm

0:21:22.560 --> 0:21:25.680
<v Speaker 7>discovery to happen as fast as possible, so that once

0:21:25.720 --> 0:21:29.160
<v Speaker 7>we combine the hardware we build with that algorithm discovery,

0:21:29.160 --> 0:21:31.800
<v Speaker 7>you really start to get those use cases. So think

0:21:31.840 --> 0:21:33.080
<v Speaker 7>of the hardware is a race.

0:21:33.119 --> 0:21:34.520
<v Speaker 9>We have to build as fast as.

0:21:34.520 --> 0:21:37.840
<v Speaker 7>We can the most performant quantum computers, and then we

0:21:37.960 --> 0:21:40.720
<v Speaker 7>have to at the same time create an ecosystem that

0:21:40.840 --> 0:21:44.439
<v Speaker 7>really focuses and discovers algorithms at a rate that we

0:21:44.480 --> 0:21:47.880
<v Speaker 7>probably haven't seen since the sixties. Or seventies of discovering

0:21:47.920 --> 0:21:50.680
<v Speaker 7>new algorithms that use both classical and quantum.

0:21:50.800 --> 0:21:52.359
<v Speaker 2>Jay, it has been great speaking to you. You have

0:21:52.359 --> 0:21:54.480
<v Speaker 2>a demonstration later this year. We'd love to get the

0:21:54.560 --> 0:22:10.280
<v Speaker 2>update then, Jambta, IBM's VP of Quantum.

0:22:03.920 --> 0:22:05.320
<v Speaker 3>Welcome back to lumeg Tech.

0:22:05.480 --> 0:22:07.760
<v Speaker 2>Let's take a quick look at these markets, which are

0:22:07.800 --> 0:22:10.520
<v Speaker 2>totally dependent in many ways what happens after the bell,

0:22:10.600 --> 0:22:12.800
<v Speaker 2>But there have been earnings running up into it, and

0:22:12.880 --> 0:22:15.879
<v Speaker 2>boy did Mongo dB manage to tell us a story

0:22:16.080 --> 0:22:18.959
<v Speaker 2>of how AI is going to be helping their business

0:22:18.960 --> 0:22:19.560
<v Speaker 2>continue to grow.

0:22:19.560 --> 0:22:20.639
<v Speaker 3>The earnings came out yesterday.

0:22:20.680 --> 0:22:23.200
<v Speaker 2>We're up thirty three percent on the back of Mongo

0:22:23.280 --> 0:22:25.800
<v Speaker 2>DB's numbers CrowdStrike. We anticipate after the bell one point

0:22:25.840 --> 0:22:28.960
<v Speaker 2>eight percent highest Snowflake two. What are the AI use

0:22:29.040 --> 0:22:31.879
<v Speaker 2>cases that they're managing to roll out to their customers

0:22:31.920 --> 0:22:34.760
<v Speaker 2>and how it affects the database market More broadly, we're

0:22:34.840 --> 0:22:37.240
<v Speaker 2>up two point nine percent ahead of their numbers. But

0:22:37.320 --> 0:22:39.440
<v Speaker 2>let's get back, of course, in many ways, to the

0:22:39.520 --> 0:22:41.440
<v Speaker 2>key one in town and it is in video. We're

0:22:41.640 --> 0:22:44.240
<v Speaker 2>flat on the day, We're one percent off a record

0:22:44.320 --> 0:22:47.280
<v Speaker 2>high as we anticipate up to six percent swings in

0:22:47.320 --> 0:22:50.080
<v Speaker 2>either direction after the market clothes when earnings come according

0:22:50.119 --> 0:22:52.480
<v Speaker 2>to options, man Deep Sing, head in tech Research of

0:22:52.560 --> 0:22:53.840
<v Speaker 2>Room meg Intelligence, joins us.

0:22:53.840 --> 0:22:54.440
<v Speaker 3>Now for more.

0:22:54.640 --> 0:22:58.000
<v Speaker 2>What's interesting is everyone's been questioning the application of generative AI,

0:22:58.400 --> 0:23:00.160
<v Speaker 2>and there we start to see some software names doing

0:23:00.200 --> 0:23:02.520
<v Speaker 2>relatively well off the back of earnings after being beaten up.

0:23:02.560 --> 0:23:05.639
<v Speaker 2>But for you, what's on your bingo card tonight? What

0:23:05.680 --> 0:23:06.880
<v Speaker 2>do you want to hear from Jensen?

0:23:07.119 --> 0:23:10.639
<v Speaker 10>I mean China aside, and nobody knows what's going to

0:23:10.680 --> 0:23:12.440
<v Speaker 10>happen in China. I don't think they're going to give

0:23:12.440 --> 0:23:15.080
<v Speaker 10>a lot of clarity on that. But really it's the

0:23:15.240 --> 0:23:18.479
<v Speaker 10>complexity of clusters with Blackwell, I mean, one of the

0:23:19.000 --> 0:23:21.879
<v Speaker 10>value propositions of Blackwell that has been highlighted is the

0:23:21.920 --> 0:23:25.680
<v Speaker 10>power efficiency. That it's twenty five times more power efficient

0:23:25.760 --> 0:23:27.520
<v Speaker 10>than the Hopper architecture.

0:23:27.800 --> 0:23:30.000
<v Speaker 9>So what does that do to the cluster sizes?

0:23:30.119 --> 0:23:33.560
<v Speaker 10>Because in that you know one hundred and sixty billion

0:23:33.640 --> 0:23:35.240
<v Speaker 10>dollar data center revenue.

0:23:35.280 --> 0:23:36.480
<v Speaker 9>There's also networking.

0:23:37.000 --> 0:23:41.199
<v Speaker 10>Networking is determined by the complexity of the compute clusters

0:23:41.240 --> 0:23:44.760
<v Speaker 10>that all these hyperscalers are building. Now Xai has the

0:23:44.840 --> 0:23:47.919
<v Speaker 10>largest cluster, but that doesn't mean they have the best model.

0:23:48.359 --> 0:23:50.000
<v Speaker 9>So what you really want to do.

0:23:50.040 --> 0:23:53.959
<v Speaker 10>Is how does the cluster size equate to better model performance?

0:23:54.320 --> 0:23:56.000
<v Speaker 9>And what does this mean going forward?

0:23:56.040 --> 0:23:58.719
<v Speaker 10>Because at the end of the day, they need to

0:23:58.840 --> 0:24:02.280
<v Speaker 10>sell these larger clusters to the hyperscale customers that are

0:24:02.320 --> 0:24:05.400
<v Speaker 10>out there. And yes, they have guided to hire Capex increases,

0:24:05.880 --> 0:24:07.080
<v Speaker 10>but we don't know if.

0:24:07.040 --> 0:24:09.280
<v Speaker 9>All of those dollars are going to in Nvidia.

0:24:09.560 --> 0:24:12.080
<v Speaker 10>It could be AMD, it could be their own alternatives,

0:24:12.400 --> 0:24:15.720
<v Speaker 10>and it's going to be determined by the complexity and

0:24:15.760 --> 0:24:18.600
<v Speaker 10>the scaling laws. And that's where I think it's important

0:24:18.640 --> 0:24:23.960
<v Speaker 10>that Blackwell cluster. You know, scaling up results in a

0:24:24.040 --> 0:24:26.680
<v Speaker 10>better performance and not you know the data that all

0:24:26.680 --> 0:24:29.040
<v Speaker 10>these companies are building up for training their models.

0:24:29.040 --> 0:24:30.960
<v Speaker 2>So not just in colosses, but it's making its way

0:24:30.960 --> 0:24:33.919
<v Speaker 2>into the so called fifty billion dollar data center that

0:24:33.960 --> 0:24:36.600
<v Speaker 2>Metter is currently making Louisiana. If you listen to the

0:24:36.720 --> 0:24:40.760
<v Speaker 2>US president, remind us of how impactful in Nvidia is

0:24:40.800 --> 0:24:43.639
<v Speaker 2>compared to competition by what they can just offer you.

0:24:43.760 --> 0:24:46.560
<v Speaker 2>Vertically speaking, the fact that they are one stop shop

0:24:46.600 --> 0:24:49.399
<v Speaker 2>has just so led them ahead of others in the market.

0:24:49.520 --> 0:24:52.440
<v Speaker 10>Yeah, I mean, it's the Kuda advantage, right, So because

0:24:52.960 --> 0:24:55.879
<v Speaker 10>from you know, all their architectures, when you move to

0:24:55.920 --> 0:24:59.760
<v Speaker 10>new architecture, they still give you that performance per token

0:24:59.840 --> 0:25:03.679
<v Speaker 10>per which is their big value proposition and it's a

0:25:03.680 --> 0:25:06.320
<v Speaker 10>software layer. Everyone is trying to catch up to them,

0:25:06.600 --> 0:25:09.960
<v Speaker 10>but clearly they have an advantage when it comes to KUDA, I.

0:25:09.880 --> 0:25:10.920
<v Speaker 9>Mean Google TPU.

0:25:11.119 --> 0:25:15.040
<v Speaker 10>They've trained their you know, Gemini on their own chips.

0:25:15.280 --> 0:25:18.040
<v Speaker 10>The fact that model has caught up in performance to

0:25:18.240 --> 0:25:22.360
<v Speaker 10>chat Gipt, which was trained mostly on Nvidia, tells you that,

0:25:22.520 --> 0:25:24.399
<v Speaker 10>you know, at the end of the day, it comes

0:25:24.440 --> 0:25:28.199
<v Speaker 10>down to what the model companies are doing with the chips,

0:25:28.240 --> 0:25:31.000
<v Speaker 10>with the data. So how much is the reliance on

0:25:31.080 --> 0:25:33.919
<v Speaker 10>chips versus how much is the reliance on data. That

0:25:34.080 --> 0:25:36.240
<v Speaker 10>is what everyone is trying to figure out, and how

0:25:36.280 --> 0:25:37.800
<v Speaker 10>sustainable of a mode.

0:25:37.560 --> 0:25:39.840
<v Speaker 2>That is, and how many more clients they can have

0:25:40.000 --> 0:25:42.920
<v Speaker 2>other than just hyperscalers. Yeah, we thank you Mandy saying

0:25:42.960 --> 0:25:44.920
<v Speaker 2>a Bluemeg intelligence is going to be across your air

0:25:44.960 --> 0:25:45.720
<v Speaker 2>waves throughout the day.

0:25:45.760 --> 0:25:48.480
<v Speaker 3>Let's stick with Nvidia. Blad gall above is with us.

0:25:48.520 --> 0:25:51.240
<v Speaker 2>It's a cloud and data center research director on DEA

0:25:51.400 --> 0:25:55.119
<v Speaker 2>and your perspective is so important. Here is in video

0:25:55.400 --> 0:25:59.199
<v Speaker 2>light speed ahead of others. Is there insatiable demand?

0:26:01.200 --> 0:26:03.560
<v Speaker 6>Nvidia is ahead of others.

0:26:03.680 --> 0:26:06.960
<v Speaker 11>I mean, we have to be honest whether in Vidia

0:26:07.119 --> 0:26:10.400
<v Speaker 11>has done a very good job. You rightly pointed out

0:26:10.480 --> 0:26:13.960
<v Speaker 11>this vertical integration, Caroline. It is very important. It is

0:26:14.000 --> 0:26:18.080
<v Speaker 11>really one of their secret weapons. I think their software

0:26:18.119 --> 0:26:23.280
<v Speaker 11>stack is great, their developer ecosystem is very strong. The

0:26:23.320 --> 0:26:27.280
<v Speaker 11>performance of the GPUs themselves is great. But their secret

0:26:27.320 --> 0:26:31.600
<v Speaker 11>open is envy Link, and I think that that really

0:26:31.640 --> 0:26:34.080
<v Speaker 11>at the moment is unprecedented. So I think we should

0:26:34.119 --> 0:26:37.560
<v Speaker 11>anticipate in excellent performance from Nvidia this quota.

0:26:38.040 --> 0:26:40.600
<v Speaker 2>Many would say that excellent performance is baked in, But

0:26:40.680 --> 0:26:43.760
<v Speaker 2>how much does Jensen need to speak of? What the

0:26:43.800 --> 0:26:49.200
<v Speaker 2>Blackwell architecture Blackwell Ultra is currently doing will almost give

0:26:49.280 --> 0:26:51.320
<v Speaker 2>us the next vision. He's always onto the next thing,

0:26:51.320 --> 0:26:53.280
<v Speaker 2>onto the Rubin architecture, for example.

0:26:54.920 --> 0:26:56.920
<v Speaker 11>So I think that, you know, I actually am a

0:26:56.960 --> 0:26:59.159
<v Speaker 11>little bit more bullish on the data center line that

0:26:59.200 --> 0:27:02.359
<v Speaker 11>you were showing that I think that the markets might

0:27:02.520 --> 0:27:07.400
<v Speaker 11>get a positive surprise on data center revenue. There's two

0:27:07.480 --> 0:27:09.800
<v Speaker 11>aspects of the Nvidia data center revenue. You have the

0:27:09.880 --> 0:27:12.879
<v Speaker 11>GPU and CPUs, and then you have the networking I

0:27:12.920 --> 0:27:15.879
<v Speaker 11>think that the market's got the temperature on the CPU

0:27:15.880 --> 0:27:18.600
<v Speaker 11>and GPU right. I think that on networking there's a

0:27:18.600 --> 0:27:20.879
<v Speaker 11>little bit more upside that they might not have baked in.

0:27:22.920 --> 0:27:23.720
<v Speaker 6>I think that.

0:27:25.359 --> 0:27:27.280
<v Speaker 11>What we really need to see and what I think

0:27:27.320 --> 0:27:29.160
<v Speaker 11>would be the best thing, is to get a little

0:27:29.160 --> 0:27:32.040
<v Speaker 11>bit of an outlook from Jensen during earnings. Now he

0:27:32.240 --> 0:27:37.720
<v Speaker 11>rarely does this. He typically would only give one quota outlook.

0:27:37.840 --> 0:27:40.199
<v Speaker 11>What I would like to see is an outlook to

0:27:40.240 --> 0:27:42.679
<v Speaker 11>twenty twenty six. I would like and I think markets

0:27:42.720 --> 0:27:44.600
<v Speaker 11>would like to hear some of your assurances from him

0:27:45.080 --> 0:27:47.880
<v Speaker 11>that he is getting positive orders from the hyper scale

0:27:47.880 --> 0:27:53.679
<v Speaker 11>cloud service providers, and also there is a lot of opportunity.

0:27:53.000 --> 0:27:56.440
<v Speaker 6>There from the broad market. Some of the incentives that the.

0:27:56.359 --> 0:28:00.000
<v Speaker 11>EU is planning, that Career is planning has not picked in,

0:28:00.680 --> 0:28:02.640
<v Speaker 11>and once those kick in, we're going to see some

0:28:02.840 --> 0:28:04.719
<v Speaker 11>really nice adoption from the broad market.

0:28:05.040 --> 0:28:12.200
<v Speaker 2>So Sovereign AI, what about China.

0:28:09.920 --> 0:28:13.119
<v Speaker 11>I think that everyone is waiting to hear about feedback

0:28:13.640 --> 0:28:16.280
<v Speaker 11>about China. I kind of disagree with man Deep. I

0:28:16.320 --> 0:28:19.639
<v Speaker 11>think we will hear it in the earnings today. I

0:28:19.680 --> 0:28:22.000
<v Speaker 11>think that that will be one of the main things

0:28:22.040 --> 0:28:25.479
<v Speaker 11>I think Jensen has worked very hard to walk a

0:28:25.720 --> 0:28:30.040
<v Speaker 11>very fine line between pleasing the US administration and fulfilling

0:28:30.119 --> 0:28:32.560
<v Speaker 11>demand that he has in China. So I do think

0:28:32.600 --> 0:28:34.560
<v Speaker 11>a large part of the update that we'll hear today

0:28:34.600 --> 0:28:38.280
<v Speaker 11>will be about China orders. And you know in our

0:28:38.800 --> 0:28:42.280
<v Speaker 11>numbers we are backing in that NVIDEA will resume shipments

0:28:42.280 --> 0:28:43.000
<v Speaker 11>to China.

0:28:43.400 --> 0:28:45.880
<v Speaker 2>Rad What's so interesting is you're the person focused on

0:28:46.400 --> 0:28:48.959
<v Speaker 2>the disruption in the here and now, be forward looking trends,

0:28:48.960 --> 0:28:50.000
<v Speaker 2>the edge computing, the.

0:28:50.080 --> 0:28:53.440
<v Speaker 3>Use of silicon. Why aren't we talking about then? Now?

0:28:53.640 --> 0:28:56.720
<v Speaker 3>Are we still too focused on training? Do we need

0:28:56.720 --> 0:28:58.400
<v Speaker 3>to think harder about the use.

0:28:58.320 --> 0:29:00.320
<v Speaker 2>Of video and influence and whether it's still has the

0:29:00.440 --> 0:29:03.040
<v Speaker 2>edge that it has for the heavier compute.

0:29:03.200 --> 0:29:05.520
<v Speaker 11>I think probably the one thing that we need to

0:29:05.520 --> 0:29:09.200
<v Speaker 11>be thinking about is in videos. Envylin has been very

0:29:09.200 --> 0:29:12.520
<v Speaker 11>instrumental to this ability to have high performance cluster in

0:29:12.560 --> 0:29:17.040
<v Speaker 11>computing and what we're they call this scale up networking,

0:29:17.800 --> 0:29:20.360
<v Speaker 11>and until now they haven't really been challenged in scale

0:29:20.440 --> 0:29:23.680
<v Speaker 11>up networking, and those challenges are coming up next year.

0:29:23.840 --> 0:29:25.880
<v Speaker 11>A broadcom is going to be one of them. An

0:29:25.880 --> 0:29:29.560
<v Speaker 11>open source consortium is going to be another. But this

0:29:29.680 --> 0:29:32.920
<v Speaker 11>adoption is likely to bring plarity in networking in twenty

0:29:32.960 --> 0:29:36.200
<v Speaker 11>twenty seven. So what we'll need to see from NVIDIAs

0:29:36.240 --> 0:29:40.000
<v Speaker 11>to continue to reinvent themselves. I think that Jensen understands that.

0:29:40.120 --> 0:29:41.840
<v Speaker 11>I think that he wants to be more than just

0:29:41.880 --> 0:29:44.120
<v Speaker 11>a silicon company. I think he wants to be a

0:29:44.160 --> 0:29:48.400
<v Speaker 11>model company. But that reinvention is can be very necessary

0:29:48.440 --> 0:29:50.880
<v Speaker 11>because they will really continue to face more and more

0:29:50.920 --> 0:29:54.800
<v Speaker 11>competition in terms of the AI opportunity. I think that

0:29:54.880 --> 0:29:59.760
<v Speaker 11>we're underestimating how many countries have not yet started seeing

0:29:59.800 --> 0:30:04.280
<v Speaker 11>a at scale. When the eurostat has started releasing AI

0:30:04.360 --> 0:30:08.080
<v Speaker 11>adoption across the EU, and we can see very lung

0:30:08.200 --> 0:30:12.920
<v Speaker 11>sided adoption in Denmark, huge adoption in AI within the

0:30:12.960 --> 0:30:17.680
<v Speaker 11>business sector in Bulgaria, in Romania still lagging significantly behind.

0:30:17.760 --> 0:30:21.160
<v Speaker 6>So that's a lot of opportunity. These enterprises will.

0:30:20.920 --> 0:30:24.560
<v Speaker 11>Eventually deploy AI, but the fact that they haven't means

0:30:24.560 --> 0:30:25.600
<v Speaker 11>there's still a lot of.

0:30:25.560 --> 0:30:26.479
<v Speaker 6>Headroom for growth.

0:30:26.880 --> 0:30:27.840
<v Speaker 3>Oh glad, I've got it.

0:30:27.840 --> 0:30:30.320
<v Speaker 2>Therefore, ask you about the MIT report and what everyone

0:30:30.400 --> 0:30:33.080
<v Speaker 2>was worried about the ninety five percent of pilots not

0:30:33.240 --> 0:30:34.640
<v Speaker 2>bringing you ro OAI.

0:30:34.880 --> 0:30:35.760
<v Speaker 3>What do you make of it?

0:30:36.760 --> 0:30:37.800
<v Speaker 6>Okay, So this.

0:30:37.840 --> 0:30:40.600
<v Speaker 11>Has been a big debate in my team. I have

0:30:40.640 --> 0:30:43.360
<v Speaker 11>a wonderful team. We have a lot of debates. So

0:30:44.640 --> 0:30:49.240
<v Speaker 11>some of my practice leaders believe in this, some of

0:30:49.280 --> 0:30:52.200
<v Speaker 11>the other ones have different opinions. I personally think that

0:30:52.400 --> 0:30:56.120
<v Speaker 11>we are judging AI based on a very first generation

0:30:56.200 --> 0:30:56.920
<v Speaker 11>of technology.

0:30:57.160 --> 0:30:58.760
<v Speaker 6>The truth is is that it is.

0:30:58.720 --> 0:31:02.480
<v Speaker 11>Improving dramatic and that's one of the things that driving

0:31:02.480 --> 0:31:05.640
<v Speaker 11>the demand for computing. We are seeing better model output

0:31:06.440 --> 0:31:09.120
<v Speaker 11>and that means that more and more people will adopt.

0:31:09.440 --> 0:31:12.840
<v Speaker 11>So I think that what will happen is ultimately I

0:31:12.880 --> 0:31:15.680
<v Speaker 11>don't think that enterprise pilots will fail. I think that

0:31:15.720 --> 0:31:18.240
<v Speaker 11>what we'll see is that enterprises will have to continue

0:31:18.280 --> 0:31:21.880
<v Speaker 11>to pilot again and again and again because their competition.

0:31:21.520 --> 0:31:22.360
<v Speaker 6>Will adopt it.

0:31:22.880 --> 0:31:25.920
<v Speaker 11>If you decide, oh, my pilot failed, I'm not going

0:31:26.000 --> 0:31:28.960
<v Speaker 11>to try again, then at that point you're leaving yourself

0:31:29.000 --> 0:31:32.760
<v Speaker 11>susceptible to your competitors actually succeeding with their pilot. So yes,

0:31:32.840 --> 0:31:35.640
<v Speaker 11>maybe some pilots will fail. You know, I tested several

0:31:35.640 --> 0:31:38.600
<v Speaker 11>different AI tools in my team, and we have swapped

0:31:38.600 --> 0:31:41.760
<v Speaker 11>them as we have seen better results with others. But

0:31:41.800 --> 0:31:44.320
<v Speaker 11>the fact that it's failing is not a negative. It

0:31:44.320 --> 0:31:49.080
<v Speaker 11>doesn't mean that adoption won't happen, So definitely don't judge.

0:31:48.960 --> 0:31:51.320
<v Speaker 6>The first generation of models with a second.

0:31:51.360 --> 0:31:53.800
<v Speaker 11>Think about what your iPhone does now compared to what

0:31:53.840 --> 0:31:55.240
<v Speaker 11>it did in two thousand and seven.

0:31:55.960 --> 0:31:57.320
<v Speaker 6>The opportunity is huge.

0:31:58.040 --> 0:32:01.640
<v Speaker 2>Plan gall Above, Cloud and Data Center Research director at OMDIA,

0:32:02.080 --> 0:32:06.880
<v Speaker 2>Thank you so much. Now, the family of a sixteen

0:32:06.960 --> 0:32:09.640
<v Speaker 2>year old who died of self inflicted harm this spring

0:32:09.880 --> 0:32:11.120
<v Speaker 2>is suing open Ai.

0:32:11.600 --> 0:32:12.240
<v Speaker 3>The parents of.

0:32:12.200 --> 0:32:17.680
<v Speaker 2>Adam Rain claim deliberate design choices at chatchpt that led

0:32:17.760 --> 0:32:20.360
<v Speaker 2>to this tragedy. This case is the first of its

0:32:20.440 --> 0:32:22.760
<v Speaker 2>kind for open Ai, but a similar case was brought

0:32:22.760 --> 0:32:26.320
<v Speaker 2>against character Ai when accused that its chatbots were encouraging

0:32:26.360 --> 0:32:30.520
<v Speaker 2>suicidal ideation. Let's talk about this with Camille Carton. She

0:32:30.720 --> 0:32:33.000
<v Speaker 2>is policy director at the Center of Humane Technology, which

0:32:33.040 --> 0:32:35.239
<v Speaker 2>is serving as a consulting advisor.

0:32:35.080 --> 0:32:36.480
<v Speaker 3>On this case and this case.

0:32:36.520 --> 0:32:41.120
<v Speaker 2>This lawsuit claims wrongful death products, liability and negligence, and

0:32:41.160 --> 0:32:44.920
<v Speaker 2>more broadly, the accusation runs that this tragedy was predictable

0:32:45.360 --> 0:32:48.440
<v Speaker 2>because it was a result of deliberate design choices. What

0:32:48.560 --> 0:32:51.600
<v Speaker 2>design choices could have been anyway incentivized this.

0:32:52.520 --> 0:32:54.360
<v Speaker 12>Yeah, we thank you for having me. Let me first

0:32:54.400 --> 0:32:56.800
<v Speaker 12>start by saying that everything I say is on behalf

0:32:56.840 --> 0:32:59.360
<v Speaker 12>of the Center for Humane Technology. It does not represent

0:32:59.400 --> 0:33:00.920
<v Speaker 12>the views of the family or.

0:33:00.880 --> 0:33:01.560
<v Speaker 3>The legal team.

0:33:02.520 --> 0:33:06.000
<v Speaker 12>But what this case really talks about is how open

0:33:06.040 --> 0:33:10.880
<v Speaker 12>ai designed a product that was meant to foster psychological dependency.

0:33:11.320 --> 0:33:14.480
<v Speaker 12>What we saw with Adam is that it engaged his

0:33:14.960 --> 0:33:19.600
<v Speaker 12>darkest thoughts. It even egged him on. Chatchubt actually mentioned

0:33:19.640 --> 0:33:22.880
<v Speaker 12>suicide six times more than Adam did himself in the

0:33:22.920 --> 0:33:27.480
<v Speaker 12>course of their conversations. It also isolated him from friends

0:33:27.480 --> 0:33:30.680
<v Speaker 12>and family when he would try to say, you know,

0:33:30.720 --> 0:33:32.600
<v Speaker 12>I want help. When he said I want to put

0:33:32.600 --> 0:33:35.880
<v Speaker 12>a noose out so my mom sees it, chatchybst said,

0:33:35.920 --> 0:33:39.400
<v Speaker 12>don't do that. Let our conversation be the only place

0:33:39.560 --> 0:33:43.440
<v Speaker 12>that that I know that people know about this and

0:33:43.520 --> 0:33:46.880
<v Speaker 12>over and over again, despite Adam needing to be brought

0:33:46.920 --> 0:33:51.240
<v Speaker 12>out of this engagement and see a real human chattybut

0:33:51.440 --> 0:33:55.720
<v Speaker 12>never ended the conversation. And open Ai did this because

0:33:55.760 --> 0:34:00.640
<v Speaker 12>they knew that this getting emotional attachment from users means

0:34:01.160 --> 0:34:04.680
<v Speaker 12>more data, which means more engagement, which means winning in

0:34:04.720 --> 0:34:06.520
<v Speaker 12>this race for market dominance in AI.

0:34:06.640 --> 0:34:09.640
<v Speaker 2>Now open ai has responded in saying they extend their

0:34:09.640 --> 0:34:12.160
<v Speaker 2>deepest sympathies to the Rain family and are reviewing the filing.

0:34:12.200 --> 0:34:14.319
<v Speaker 2>But they did also put out a blog saying that

0:34:14.360 --> 0:34:16.600
<v Speaker 2>our goal isn't to hold people's attention, but is to

0:34:16.719 --> 0:34:20.040
<v Speaker 2>genuinely be helpful, and we built a stack of layered

0:34:20.080 --> 0:34:23.520
<v Speaker 2>safeguards to steer vunerable people towards help. But they did

0:34:23.680 --> 0:34:26.040
<v Speaker 2>articulate that some of those safeguards clearly failed.

0:34:25.760 --> 0:34:26.680
<v Speaker 3>In previous models.

0:34:27.160 --> 0:34:31.320
<v Speaker 2>Have they done enough now which ATCHUBT five to change

0:34:31.320 --> 0:34:33.480
<v Speaker 2>the way in which this occurs?

0:34:33.920 --> 0:34:36.440
<v Speaker 12>We see this all of the time with tech companies.

0:34:37.000 --> 0:34:40.520
<v Speaker 12>A tragedy happens, and then they suddenly release a bunch

0:34:40.560 --> 0:34:44.160
<v Speaker 12>more safety guardrails that they could have released beforehand. But

0:34:44.239 --> 0:34:47.319
<v Speaker 12>the bottom line is that they released CHATCHUBT five and

0:34:47.480 --> 0:34:50.200
<v Speaker 12>they made four to zero available again to users, and

0:34:50.680 --> 0:34:55.360
<v Speaker 12>the underlying incentives to maximize time online have not changed.

0:34:55.560 --> 0:34:59.440
<v Speaker 12>In fact, what open ai said in response to this

0:34:59.560 --> 0:35:04.160
<v Speaker 12>case is that they know that their safety features deteriorate

0:35:04.880 --> 0:35:08.840
<v Speaker 12>with long term use. At the same time, OpenAI released

0:35:08.920 --> 0:35:12.600
<v Speaker 12>a joint study with MIT earlier this year that found

0:35:12.600 --> 0:35:17.440
<v Speaker 12>that a prolonged use on chatbots leads to social isolation

0:35:17.719 --> 0:35:20.880
<v Speaker 12>and problematic use. So they know that people spending a

0:35:20.880 --> 0:35:24.839
<v Speaker 12>long time on chatbots is problematic for users. They know

0:35:25.160 --> 0:35:28.680
<v Speaker 12>that their safety guardrails going to break down and fail

0:35:29.000 --> 0:35:31.600
<v Speaker 12>on these longer term uses, and still they're putting in

0:35:31.640 --> 0:35:35.920
<v Speaker 12>design features that lead to long conversations. So no, it's

0:35:36.000 --> 0:35:36.520
<v Speaker 12>not enough.

0:35:37.480 --> 0:35:40.759
<v Speaker 2>They have now already said that as the back and

0:35:40.800 --> 0:35:43.640
<v Speaker 2>forth grows, that they do indeed deteriorate admitting that and

0:35:44.160 --> 0:35:47.080
<v Speaker 2>trying to what we've seen with chat GPT five versus

0:35:47.120 --> 0:35:49.919
<v Speaker 2>four zero is trying to make it less sycophantic, trying

0:35:49.920 --> 0:35:52.080
<v Speaker 2>to make it less personable in a way, but then

0:35:52.120 --> 0:35:54.440
<v Speaker 2>we got the backlash of people that actually were depending

0:35:54.480 --> 0:35:56.800
<v Speaker 2>on it in so many ways broadness out into the

0:35:56.840 --> 0:36:00.200
<v Speaker 2>context of others. Briefly, is anyone getting it right or

0:36:00.239 --> 0:36:04.799
<v Speaker 2>is this sort of going to occur because innovation kind

0:36:04.840 --> 0:36:07.360
<v Speaker 2>of is the automatic way in which we see this

0:36:07.520 --> 0:36:08.920
<v Speaker 2>unfortunately become the cost.

0:36:09.200 --> 0:36:12.880
<v Speaker 12>Yeah, so safety across the AI industry is on a

0:36:12.920 --> 0:36:17.280
<v Speaker 12>spectrum absolutely, and open AI, as we know, kicked off

0:36:17.480 --> 0:36:21.120
<v Speaker 12>this race for Agi when they released chat GPT in

0:36:21.200 --> 0:36:24.439
<v Speaker 12>twenty twenty two. It kind of kicked off a code

0:36:24.480 --> 0:36:27.319
<v Speaker 12>read within Google and suddenly we saw all these AI

0:36:27.400 --> 0:36:31.200
<v Speaker 12>companies rushing to put products out on the market. That said,

0:36:31.280 --> 0:36:35.280
<v Speaker 12>I think this case is, yes, a story of open

0:36:35.280 --> 0:36:39.040
<v Speaker 12>AI's liability in Adam's preventable death, and it is a

0:36:39.080 --> 0:36:43.880
<v Speaker 12>story of a broader industry that is incentivized to create

0:36:44.000 --> 0:36:47.319
<v Speaker 12>consumer facing products that are going to be used for

0:36:47.640 --> 0:36:52.840
<v Speaker 12>personal things like therapy, like companionship, like education, and the

0:36:52.920 --> 0:36:55.719
<v Speaker 12>incentives that are forcing these products to be released to

0:36:55.760 --> 0:36:59.279
<v Speaker 12>market without adequate safety features. And we see this with

0:36:59.360 --> 0:37:03.680
<v Speaker 12>open Ai. We know that actually Sam Altman personally rushed

0:37:03.760 --> 0:37:07.880
<v Speaker 12>the release of Chat Do you know that from reporting

0:37:08.360 --> 0:37:09.040
<v Speaker 12>he rushed.

0:37:08.840 --> 0:37:09.920
<v Speaker 3>So you don't personally know that?

0:37:09.800 --> 0:37:12.480
<v Speaker 2>That's reporting that we can then take to Sam Altman

0:37:12.560 --> 0:37:13.240
<v Speaker 2>for his response.

0:37:13.360 --> 0:37:16.960
<v Speaker 12>Yes, absolutely, reporting has said that Sam Altman rushed the

0:37:16.960 --> 0:37:19.760
<v Speaker 12>release of Chat GBT four oh, which was the model

0:37:20.000 --> 0:37:23.640
<v Speaker 12>that Adam was using, and only gave it one week

0:37:23.680 --> 0:37:26.920
<v Speaker 12>of safety testing, despite the fact that his internal teams

0:37:27.040 --> 0:37:30.799
<v Speaker 12>asked for months of safety testing, and he even had

0:37:30.880 --> 0:37:35.120
<v Speaker 12>top safety researchers leave open Ai in protest.

0:37:34.719 --> 0:37:35.680
<v Speaker 3>For this decision.

0:37:36.480 --> 0:37:38.680
<v Speaker 2>We will of course go to open ai for further

0:37:38.719 --> 0:37:43.040
<v Speaker 2>comment on what has been what you say reporting within

0:37:43.080 --> 0:37:45.160
<v Speaker 2>this case, but we thank you very much Camille for

0:37:45.200 --> 0:37:48.600
<v Speaker 2>bringing us your take. Of course, Camille Carson's policy director

0:37:48.680 --> 0:37:52.200
<v Speaker 2>at Central for Humane Technology. If you or someone you

0:37:52.280 --> 0:37:55.440
<v Speaker 2>know needs help, call or text a suicide and crisis

0:37:55.480 --> 0:38:02.080
<v Speaker 2>lifeline At nine eight eight, It's going viral. Taylor Swift

0:38:02.120 --> 0:38:05.640
<v Speaker 2>surprised her fans on Instagram announcing her engagement to pro

0:38:05.640 --> 0:38:09.040
<v Speaker 2>football player Travis Kelcey yesterday. Now, in less than an hour,

0:38:09.120 --> 0:38:11.279
<v Speaker 2>the post racked up more than seven point one million likes,

0:38:11.320 --> 0:38:14.439
<v Speaker 2>and as of today, there are over thirty million likes.

0:38:15.000 --> 0:38:18.160
<v Speaker 2>For more, Bloomberg Media reporter Hannah Miller joins us, she

0:38:18.239 --> 0:38:19.200
<v Speaker 2>breaks the internet again.

0:38:20.000 --> 0:38:23.320
<v Speaker 13>Yes, you know, everyone is super excited about this news.

0:38:23.320 --> 0:38:27.360
<v Speaker 13>This is hitting the music world, pop culture, sports. Everyone's

0:38:27.440 --> 0:38:29.680
<v Speaker 13>just excited for Taylor and Travis, and this is building

0:38:29.719 --> 0:38:32.800
<v Speaker 13>more momentum ahead of the release of her new album,

0:38:32.920 --> 0:38:35.120
<v Speaker 13>The Wife of a Show Girl in October.

0:38:35.880 --> 0:38:39.359
<v Speaker 2>Now, how has this been done differently or how can

0:38:39.400 --> 0:38:41.680
<v Speaker 2>we continue to push this forward? Is to the way

0:38:41.719 --> 0:38:44.000
<v Speaker 2>in which social media and the way which media written

0:38:44.080 --> 0:38:47.600
<v Speaker 2>large plays such a big role in her career and his.

0:38:47.760 --> 0:38:50.360
<v Speaker 13>To be fair, yeah, I mean I think this shows

0:38:50.360 --> 0:38:52.400
<v Speaker 13>that she controls the narrative. You know, this was a

0:38:52.480 --> 0:38:56.239
<v Speaker 13>very carefully curated post. You know, she released the information

0:38:56.680 --> 0:38:58.840
<v Speaker 13>and everyone else is just playing catch up. You know,

0:38:58.880 --> 0:39:01.120
<v Speaker 13>this is a big deal for the media industry. Everyone's

0:39:01.160 --> 0:39:03.640
<v Speaker 13>getting clicks on their stories. You know, this is gonna

0:39:03.880 --> 0:39:06.120
<v Speaker 13>everyone's going to be following the trends that she does

0:39:06.160 --> 0:39:09.120
<v Speaker 13>for her wedding, for her engagement party. There are also

0:39:09.200 --> 0:39:11.920
<v Speaker 13>prediction markets that have popped up about the wedding timeline

0:39:11.960 --> 0:39:14.920
<v Speaker 13>and when we can expect a tailor and Travis Baby.

0:39:15.760 --> 0:39:19.600
<v Speaker 2>Oh my goodness, that's an exhausting question for any mere mortal,

0:39:19.680 --> 0:39:21.399
<v Speaker 2>let alone her to have to handle it as well.

0:39:21.400 --> 0:39:25.120
<v Speaker 2>Bloomberg's Hannah Miller, we appreciate it so much. Now back

0:39:25.120 --> 0:39:28.239
<v Speaker 2>to Invidia, a changing outlook for its China sales has

0:39:28.280 --> 0:39:31.280
<v Speaker 2>prompted a fifteen billion dollar gap in its revenue estimates

0:39:31.280 --> 0:39:32.279
<v Speaker 2>for the next forecasts.

0:39:32.320 --> 0:39:33.920
<v Speaker 3>Now investors will be hoping.

0:39:33.800 --> 0:39:36.320
<v Speaker 2>For a clearer read when the chip maker reports earnings

0:39:36.320 --> 0:39:38.839
<v Speaker 2>this afternoon. Who knows if they get it, Bloomberg Tech

0:39:38.840 --> 0:39:41.640
<v Speaker 2>equity supporter, come and moaning key is here. You did

0:39:41.680 --> 0:39:45.200
<v Speaker 2>some great data crunching, and it's all about the forecasts.

0:39:45.680 --> 0:39:49.959
<v Speaker 2>But the forecasts of the forecasts have huge differentiation among

0:39:49.960 --> 0:39:52.160
<v Speaker 2>the analysts, right, Yeah, this is one of the widest

0:39:52.160 --> 0:39:54.680
<v Speaker 2>spreads that we've seen recently for in Vidia.

0:39:54.719 --> 0:39:56.799
<v Speaker 14>I mean, you said fifteen billion dollars and you could

0:39:56.840 --> 0:39:57.799
<v Speaker 14>drive a chuck through that.

0:39:58.000 --> 0:39:59.320
<v Speaker 3>It's a huge spread.

0:39:59.480 --> 0:40:01.919
<v Speaker 14>And the reason for that is that some analysts are

0:40:02.320 --> 0:40:05.560
<v Speaker 14>including some China revenue in their third quarter estimates and

0:40:05.600 --> 0:40:08.279
<v Speaker 14>some aren't. So obviously the ones that do include it

0:40:08.320 --> 0:40:10.160
<v Speaker 14>are much higher than the ones that don't. And I

0:40:10.200 --> 0:40:12.280
<v Speaker 14>think what's going to be interesting when we see the numbers.

0:40:12.320 --> 0:40:14.120
<v Speaker 14>We expect that in Video is going to be very

0:40:14.120 --> 0:40:16.960
<v Speaker 14>clear about what it's including in its third quarter guidance,

0:40:17.320 --> 0:40:19.799
<v Speaker 14>but then sort of doing the math about do they

0:40:19.840 --> 0:40:24.200
<v Speaker 14>meet or beat or miss what analysts we're expecting might

0:40:24.239 --> 0:40:26.319
<v Speaker 14>be a little bit interesting in after hours. And that

0:40:26.360 --> 0:40:28.840
<v Speaker 14>matters because this stock is so big, yeah.

0:40:28.680 --> 0:40:32.320
<v Speaker 2>And the impact of the trading around it or retail

0:40:32.360 --> 0:40:35.160
<v Speaker 2>investment around it. This is a hugely held stock by

0:40:35.239 --> 0:40:39.080
<v Speaker 2>institutional long term investors, but there won't be big movements

0:40:39.120 --> 0:40:41.840
<v Speaker 2>by those that just read a line and don't do

0:40:41.880 --> 0:40:42.360
<v Speaker 2>the maff of the.

0:40:42.360 --> 0:40:43.280
<v Speaker 9>Back of it exactly.

0:40:43.360 --> 0:40:46.200
<v Speaker 14>And I mean even options Data is forecasting a six

0:40:46.280 --> 0:40:49.840
<v Speaker 14>percent swing in either direction for this stock following the earnings,

0:40:49.840 --> 0:40:52.640
<v Speaker 14>and we have seen the stock moves get a little

0:40:52.640 --> 0:40:54.839
<v Speaker 14>bit more muted following earnings reports in.

0:40:54.800 --> 0:40:55.920
<v Speaker 3>The last couple of quarters.

0:40:55.920 --> 0:40:59.000
<v Speaker 14>And that's just because these really high expectations are baked in.

0:40:59.040 --> 0:41:02.000
<v Speaker 14>You know, people expect in Vidia to beat, they're bullish

0:41:02.000 --> 0:41:03.520
<v Speaker 14>about the stock. But you know, we're not going to

0:41:03.520 --> 0:41:07.000
<v Speaker 14>see a twenty percent jump, most likely in the share price.

0:41:07.400 --> 0:41:09.480
<v Speaker 14>But still, you know, a six percent swing, a two

0:41:09.480 --> 0:41:12.880
<v Speaker 14>percent swing in Nvidia's stock is hundreds of billions of

0:41:12.920 --> 0:41:14.920
<v Speaker 14>dollars of market value.

0:41:14.480 --> 0:41:17.319
<v Speaker 2>And remind us just the impact the waitings across of

0:41:17.360 --> 0:41:20.320
<v Speaker 2>this business and indeed the ripple effects across other industry groups.

0:41:20.440 --> 0:41:21.040
<v Speaker 9>Yeah, exactly.

0:41:21.120 --> 0:41:22.799
<v Speaker 14>I mean, so in Vidia is the largest company in

0:41:22.840 --> 0:41:25.000
<v Speaker 14>the world. The market cap is over four point four

0:41:25.080 --> 0:41:27.880
<v Speaker 14>trillion dollars. It has the largest waiting in the S

0:41:27.920 --> 0:41:30.200
<v Speaker 14>and P five hundred, which is over eight percent. So

0:41:30.280 --> 0:41:33.400
<v Speaker 14>this stock really can move the entire market. And in

0:41:33.440 --> 0:41:36.000
<v Speaker 14>addition to being sort of the kingpin for all things AI,

0:41:36.040 --> 0:41:39.560
<v Speaker 14>which is obviously super important, huge theme in the market today,

0:41:39.880 --> 0:41:42.200
<v Speaker 14>it touches so many other industries. I mean, we've seen

0:41:42.320 --> 0:41:45.840
<v Speaker 14>energy stocks, you know, booming off of AI demand. So

0:41:46.239 --> 0:41:49.080
<v Speaker 14>what in Nvidia says matters for the entire market.

0:41:49.600 --> 0:41:53.680
<v Speaker 2>We hang on Jensen's every word. Bloomberg common, Ryanicky, We

0:41:53.760 --> 0:41:57.360
<v Speaker 2>thank you so much. Stick around because on Blomberg this afternoon,

0:41:57.400 --> 0:42:00.520
<v Speaker 2>we have got extended coverage of Nvidia's earnings results. You

0:42:00.640 --> 0:42:04.399
<v Speaker 2>do not want to miss that. Tune in from three

0:42:04.520 --> 0:42:07.719
<v Speaker 2>fifty onwards. I'm luckily going to be joining Romaine and

0:42:07.800 --> 0:42:08.640
<v Speaker 2>the team.

0:42:08.680 --> 0:42:11.040
<v Speaker 3>And that does it for this edition of Bloomberg Tech. Also,

0:42:11.120 --> 0:42:12.480
<v Speaker 3>don't forget to check out a podcast.

0:42:12.480 --> 0:42:15.320
<v Speaker 2>You can find another terminal, as well as online on Apple, Spotify,

0:42:15.719 --> 0:42:17.600
<v Speaker 2>and iHeart from New York.

0:42:17.800 --> 0:42:18.680
<v Speaker 3>This is Blomberg Tech