WEBVTT - US Eases Path for Nvidia to Sell H200s to China

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

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

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<v Speaker 1>and Eva Low in Sent Francisco.

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<v Speaker 2>This is Bloomberg Tech coming up. The US combust Department

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<v Speaker 2>moves closer to allowing Nvidia to sell its h two

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<v Speaker 2>hundred AI chips to China.

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<v Speaker 3>Plus robotics startup Skilled Ai just closed a one point

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<v Speaker 3>four billion dollar funding round, tripling its valuation in seven months.

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<v Speaker 4>We'll discuss with the CEO Depact PAPAC.

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<v Speaker 2>And Netflix is working to revise its bid for Warner

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<v Speaker 2>Brothers Discovery, shifting to an all cash offer.

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<v Speaker 3>As you see though those names in the red and

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<v Speaker 3>in general the market on the downside, we still got

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<v Speaker 3>geopolitical anxiety, We've still got earnings coming thick and fast,

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<v Speaker 3>and we've still got and as that one hundred off

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<v Speaker 3>by one and a half percent, not so in the

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<v Speaker 3>world of come on to a search for safety a

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<v Speaker 3>bid as the dollar falls. We see two point eight

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<v Speaker 3>percent higher on the bitcoin rally, so maybe a bit

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<v Speaker 3>of catch up with digital gold where we see spot

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<v Speaker 3>gold and a new record high up seven tens percent.

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<v Speaker 3>Copper all important commodity to our world of AI and

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<v Speaker 3>data center zed we ran a new record high on

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<v Speaker 3>an interday basis. We're up five tens percent just coming

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<v Speaker 3>off of that high on the day. But en it's

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<v Speaker 3>notable and shift of this year.

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<v Speaker 2>Right, rules and requirements are changing in the world of

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<v Speaker 2>AI chips. The US Commerce Department out with clarification which

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<v Speaker 2>impacts in video and it's H two hundred that it

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<v Speaker 2>wants to shift to China, but also impacts AMD as well.

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<v Speaker 2>AMD has been trading all over the place this morning,

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<v Speaker 2>at one point notably higher in the session, but in

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<v Speaker 2>Vidia markedly down now trading at its lowest level in

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<v Speaker 2>around a month. What are these new rules and what

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<v Speaker 2>do they mean and why is this significant? Bloomberg Senior

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<v Speaker 2>Tech editor Mike Shepherd joins us out of DC lay

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<v Speaker 2>out the new rules and requirements for US. But what

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<v Speaker 2>we're saying in the Bloomberg story is this marks a

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<v Speaker 2>significant moment for the companies in their efforts to set

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<v Speaker 2>into China.

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<v Speaker 5>Why well, this is a small but critical bureaucratic step

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<v Speaker 5>that paves the way for Nvidia and and D to

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<v Speaker 5>be able to sell H two hundred incomparable AI chips

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<v Speaker 5>to China. What it does is it now says that

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<v Speaker 5>the US government will review requests for export licenses on

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<v Speaker 5>a case by case basis and move away from the

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<v Speaker 5>past policy of a presumption of denial of any such

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<v Speaker 5>request and that had in the past been really an

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<v Speaker 5>effective export ban. Now these companies can't be there expecting

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<v Speaker 5>a rubber stamp for their requests. The US government is

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<v Speaker 5>laying out some pretty specific requirements. One that the companies

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<v Speaker 5>must show that the exports to China will not create

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<v Speaker 5>a supply shortage here. This is addressing, in a way,

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<v Speaker 5>some of the concerns that lawmakers here in Washington have

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<v Speaker 5>been raising with attempts to pass their own version of

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<v Speaker 5>export controls. Two, they must show that any manufacturing done

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<v Speaker 5>for China must not displace any production capacity intended for

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<v Speaker 5>US customers here. And three, the companies must implement strict

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<v Speaker 5>know your Customer procedures to ensure that these chips and

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<v Speaker 5>the related technology don't get out to unauthorized users.

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<v Speaker 3>It's interesting, Mike, that we are seeing Nvidia down on

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<v Speaker 3>the day AIMD. Do we get any sense of how

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<v Speaker 3>many they might be able to ship, Because it's not

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<v Speaker 3>without its intricacies as you say fifty percent of the

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<v Speaker 3>overall made in the US.

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<v Speaker 5>Well, it is the question of the moment surrounding this

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<v Speaker 5>rule just how this cap that it lays out would function.

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<v Speaker 5>The rule says that the exports to China can go

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<v Speaker 5>more than no more than fifty percent of total product

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<v Speaker 5>here in the US. But does that mean H two

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<v Speaker 5>hundreds produced from this day going forward. If that's the case,

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<v Speaker 5>it would not be a very big set and it

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<v Speaker 5>would mean a far smaller number of exports to China,

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<v Speaker 5>and that would certainly not go anywhere near meeting the

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<v Speaker 5>huge demand that Jensen Wang has said that he is

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<v Speaker 5>getting from Chinese customers. And we have reported that Ali

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<v Speaker 5>Baba and Bite the Answer interested in buying as many

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<v Speaker 5>as two hundred thousand chips each. Now, if we are

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<v Speaker 5>talking about all the H two hundreds produce over all time,

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<v Speaker 5>that would be a much bigger universe and that would

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<v Speaker 5>be a much happier outcome for Nvidia, AMD and their investors.

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<v Speaker 5>So we will have to see exactly how that is interpreted.

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<v Speaker 6>If that gets spelled out.

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<v Speaker 5>Another big question Caro is answered, how quickly the government

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<v Speaker 5>can move to actually process these export requests. Because we

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<v Speaker 5>have been hearing over the past year and longer that

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<v Speaker 5>they are simply running into capacity problems in the bureaucracy

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<v Speaker 5>at commerce and being able to turn these around.

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<v Speaker 3>Bottlenecks throughout the world of AI. Mike Sheperd, thanks so much.

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<v Speaker 3>Let's stick with what this means for Nvidia and more

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<v Speaker 3>broadly for semiconductors. Beth Kennick's with us IO fun lead

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<v Speaker 3>tech analyst. So, is this a fifty billion dollar annual

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<v Speaker 3>revenue opportunity?

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<v Speaker 4>Is China that for Nvidia?

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<v Speaker 7>Hey, Caroline jensen Wok has stated it's a fifty billion

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<v Speaker 7>per year annual opportunity. When we left off, it was

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<v Speaker 7>about five billion a quarter. That's twenty five billion, so

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<v Speaker 7>somewhere between twenty five billion and fifty billion, which really

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<v Speaker 7>means that as we look into analyst estimates, they are

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<v Speaker 7>probably too low. And that has been something from the

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<v Speaker 7>very beginning that we have found Alpha in is that

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<v Speaker 7>analysts are really struggling to wrap their head around the

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<v Speaker 7>opportunity of Nvidia. And now here comes back the aged

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<v Speaker 7>two hundreds, and where my firm is very focused is

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<v Speaker 7>calendar year twenty twenty seven. If you look at these estimates,

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<v Speaker 7>they are too low, as it is let alone if

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<v Speaker 7>China revenue resumes.

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<v Speaker 3>What's really interesting, though, is China's response to all of this.

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<v Speaker 4>You say it's too low.

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<v Speaker 3>How much might be the revenue for Nvidia in China.

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<v Speaker 4>But at the same time we understand.

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<v Speaker 3>That deep seats driving new models with seeing them use

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<v Speaker 3>what they have in the different method that maybe Ali

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<v Speaker 3>Barbara and why do you don't need those two hundred

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<v Speaker 3>thousand that they've already put off efforts and offers in

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<v Speaker 3>for what do you make of the way in which

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<v Speaker 3>China is going to pivot to domestic chips?

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<v Speaker 7>I would argue that right now the number I had

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<v Speaker 7>was about two million, h two hundreds and there's only

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<v Speaker 7>about seven hundred thousand available, which means that once again

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<v Speaker 7>in videos oversubscribed. I have been asked before, who is

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<v Speaker 7>the next in Vidia to something like Huawei, you know,

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<v Speaker 7>is it Google's TPUs? And the answer is the next

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<v Speaker 7>in Vidia is in video. They are extremely hard to disrupt,

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<v Speaker 7>and that goes for China or even United States competitors BEV.

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<v Speaker 2>Taking into account that the news story that Mike Shephard

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<v Speaker 2>just brought us, Jensen Wong told us at CS that

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<v Speaker 2>the five hundred billion dollar forecast for five fiscal quarters.

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<v Speaker 2>It includes this one for Blackwell Rubin could get bigger

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<v Speaker 2>because they could factor into H two hundred sales in

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<v Speaker 2>twenty six. I know twenty seven to a year, but

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<v Speaker 2>if you model for that little update that the Jensen

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<v Speaker 2>one gave.

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<v Speaker 7>Yes, so right now the analyst estimates did actually catch up.

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<v Speaker 7>They're about three to twenty billion this calendar year. Let's

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<v Speaker 7>just go with twenty twenty six. I want to really

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<v Speaker 7>emphasize that its next calendar year that we're going to

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<v Speaker 7>start to see analyst estimates too low. That is where

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<v Speaker 7>the alpha is at right now, and it only takes

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<v Speaker 7>one or two quarters for us to really see Nvidia's

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<v Speaker 7>price movement from all of the all of the momentum

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<v Speaker 7>we're seeing not only from Blackwell Ultra, but then we've

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<v Speaker 7>got Vera Rubin second half of this year. Now we

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<v Speaker 7>have the H two hundreds coming back. Where that falls

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<v Speaker 7>specifically in what quarter matters less to me, and what

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<v Speaker 7>matters more is that those analyst estimates are far too low.

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<v Speaker 2>Bes The big story in global markets this morning is

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<v Speaker 2>a blistering rally in metals, particularly copper copper, as S

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<v Speaker 2>and P Global wrote January eight foundational to the expanding

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<v Speaker 2>electricity supply that will power the data center build out,

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<v Speaker 2>and it's now a big growth area in that market.

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<v Speaker 2>How worried are you about that copper in the supply

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<v Speaker 2>chain and how it relates to the power needs of

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<v Speaker 2>the data centers that Nvidia's chips go into.

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<v Speaker 7>These are excellent questions, and across the board resources when

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<v Speaker 7>it comes to this data center expansion are extremely stretched,

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<v Speaker 7>especially anything that supports the electrical grids, such as copper.

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<v Speaker 7>What I would really emphasize is those alternative sources of

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<v Speaker 7>energy is a great way to position going into twenty

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<v Speaker 7>twenty six. One thing to my firm has dug up

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<v Speaker 7>is that in order for us to get to VERA,

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<v Speaker 7>Ruben and then Reuben Ultra power has to precede that

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<v Speaker 7>we have to really get this power to these data

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<v Speaker 7>centers before those systems can really ship in volume and

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<v Speaker 7>be installed. Things like net gas, even solid oxide fuel cells,

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<v Speaker 7>those that do not need great dependency on the electrical

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<v Speaker 7>grid is a wonderful way to position, and copper surging

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<v Speaker 7>today is a reminder of that.

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<v Speaker 4>What's interesting is we've hit in video.

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<v Speaker 3>We're talking about the supply chain therein we're also getting

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<v Speaker 3>the idea that CPUs.

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<v Speaker 4>As well at s US as well.

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<v Speaker 3>And you just think about the moves that we've seen

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<v Speaker 3>yesterday today in Intel, I mean, where do you think

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<v Speaker 3>the glutts or the bottlenecks are really going to be

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<v Speaker 3>hitting hard?

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<v Speaker 4>We are?

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<v Speaker 3>I mean, analysts keep Bank saying Intel and AMDA basically

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<v Speaker 3>sold out for twenty twenty six on the CPU service

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<v Speaker 3>side exactly.

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<v Speaker 7>And what's even more interesting is that AMD was up

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<v Speaker 7>more or last year than Nvidia, and they are such

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<v Speaker 7>a strong CPU player as well as Intel. There are

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<v Speaker 7>many bottlenecks. Caroline networking is another one that comes to mind.

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<v Speaker 7>Of course, energy we just spoke about. Just keep in

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<v Speaker 7>mind that it's not just GPUs, but there's almost an

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<v Speaker 7>equal amount of money being spent on all of the components,

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<v Speaker 7>all of the networking, all of the power, and we

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<v Speaker 7>are no longer compute constraint, We're no longer GPU constraint.

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<v Speaker 7>It really is becoming a power problem and a networking

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<v Speaker 7>problem that needs to be solved, especially as we move

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<v Speaker 7>into the inference market, which is only going to require

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<v Speaker 7>more memory, more bandwidth, less latency, and more and more energy.

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<v Speaker 2>Beth do AMD and Intel just accept that it's the

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<v Speaker 2>CPU market where they can do battle and just let

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<v Speaker 2>the accelertor market go to Nvidia and other specialists.

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<v Speaker 4>No, I do not believe that will be the outcome.

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<v Speaker 7>I think AMD is a strong contender, a strong number two,

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<v Speaker 7>especially in the second half of this year. They've really

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<v Speaker 7>been preparing to bring the rack scale architecture to market,

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<v Speaker 7>which is called Helios and ED what was I've covered

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<v Speaker 7>AMD very thoroughly and we could get into the specs

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<v Speaker 7>all day long.

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<v Speaker 4>But open AI giving them.

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<v Speaker 7>That six gigawad deal is a massive nod. I mean

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<v Speaker 7>that is a big nod that AMD is a contender

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<v Speaker 7>from the leading R and D firm.

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<v Speaker 2>Helios, AMD's first rack scale solution, but then in the

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<v Speaker 2>world's first two nanimeter chip inside, which they talked up

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<v Speaker 2>in our interview last week. Be f Kindig the IO Fund.

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<v Speaker 2>Great to have you back on Bloomberg Tech. Thank you

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<v Speaker 2>very much. Now coming up, anger grows over sexually explicit,

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<v Speaker 2>non consensual AI generated images on x We have the latest.

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<v Speaker 6>This is Bloomberg Tech.

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<v Speaker 3>The Supreme Court still hasn't ruled on challenges to President

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<v Speaker 3>Trump's tariffs, leaving the world to wait until at least

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<v Speaker 3>next week to learn the fate of visits signature economic

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<v Speaker 3>policy from a massurveillance. Co host Amriy Horden joins us

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<v Speaker 3>right here for more. So we delay once again, and

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<v Speaker 3>that timing could be awkward. It could be awkward. So

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<v Speaker 3>Supreme Court punts it once again.

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<v Speaker 8>They do not come out with the decision on whether

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<v Speaker 8>or not the majority of Actually a lot of this

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<v Speaker 8>terriphone venue we're bringing in into the United States, more

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<v Speaker 8>than seventies percent, is tethered to the president using aiber flexible,

0:12:00.720 --> 0:12:02.920
<v Speaker 8>a blunt tool that he has used since he came

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<v Speaker 8>back into office. And why it could be so awkward

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<v Speaker 8>is because the President will be in Davos next week

0:12:07.280 --> 0:12:09.520
<v Speaker 8>and he's going to be meeting with global leaders, the

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<v Speaker 8>world elite. Last year he joined on remote really Lambasstard,

0:12:15.360 --> 0:12:19.000
<v Speaker 8>the global elite. And at this point, potentially we could

0:12:19.000 --> 0:12:22.199
<v Speaker 8>get the decision next Tuesday or Wednesday, because that's when the.

0:12:22.240 --> 0:12:23.280
<v Speaker 4>Justices will be meeting again.

0:12:23.440 --> 0:12:25.920
<v Speaker 8>That's when potentially we can get the decision and he

0:12:26.200 --> 0:12:29.760
<v Speaker 8>could potentially be facing a Supreme Court saying you cannot

0:12:29.840 --> 0:12:33.200
<v Speaker 8>use that legal authority while he's talking to all these

0:12:33.240 --> 0:12:35.199
<v Speaker 8>countries that he already did trade deals with.

0:12:36.480 --> 0:12:39.880
<v Speaker 2>Bloomberg zamree, Howden, thank you very much. Another top story,

0:12:39.960 --> 0:12:43.720
<v Speaker 2>the US Senate unanimously passed a bill allowing victims of

0:12:43.800 --> 0:12:48.160
<v Speaker 2>sexually explicit AI images to sue the creators of that content.

0:12:48.520 --> 0:12:51.040
<v Speaker 2>The move is in response to growing public anger after

0:12:51.040 --> 0:12:54.640
<v Speaker 2>Bloomberg reported the Lelon musk x has become a top

0:12:54.720 --> 0:12:58.000
<v Speaker 2>site for generating pictures of people who have been non

0:12:58.040 --> 0:13:01.680
<v Speaker 2>consensually undressed by a must post it on x that

0:13:01.720 --> 0:13:05.960
<v Speaker 2>he wasn't aware of any naked underage images generated by Grock.

0:13:06.320 --> 0:13:10.640
<v Speaker 2>That's Xai's generative AI tool. Let's bring in Bloomberg's Emily Burnbaum,

0:13:10.800 --> 0:13:15.840
<v Speaker 2>who covers corporate lobbying government. The Defiance Act confers on

0:13:16.000 --> 0:13:21.719
<v Speaker 2>American citizens a civil right to sue, take that information

0:13:21.960 --> 0:13:23.920
<v Speaker 2>and give the rest of the details. Because that's the

0:13:23.960 --> 0:13:25.679
<v Speaker 2>bit that's new here.

0:13:26.520 --> 0:13:31.120
<v Speaker 9>Yes, that's exactly what it does. It essentially empowers victims

0:13:31.320 --> 0:13:34.960
<v Speaker 9>of this non consensual deep fake technology, people who have

0:13:35.040 --> 0:13:38.480
<v Speaker 9>been non consensually undressed by this AI tool, and it

0:13:38.520 --> 0:13:42.080
<v Speaker 9>allows them to sue the people responsible for posting that.

0:13:42.480 --> 0:13:45.920
<v Speaker 9>And it's a companion to a bill, to a bill

0:13:45.960 --> 0:13:48.640
<v Speaker 9>that was signed into law last year by President Trump

0:13:49.400 --> 0:13:53.679
<v Speaker 9>that creates criminal penalties for distributing that kind of content.

0:13:54.240 --> 0:13:58.440
<v Speaker 3>Ah, it didn't go through the House last time, the

0:13:58.480 --> 0:14:02.160
<v Speaker 3>Defiance Act, whereas take Down did, And why would this

0:14:02.240 --> 0:14:03.439
<v Speaker 3>time be any different?

0:14:03.640 --> 0:14:06.040
<v Speaker 4>Is the pushback becoming enough.

0:14:05.840 --> 0:14:08.959
<v Speaker 3>Because thus far, all we've really seen is the Department

0:14:09.000 --> 0:14:12.960
<v Speaker 3>of Defense put groquai within its military system instead of

0:14:12.960 --> 0:14:16.320
<v Speaker 3>pushing back on this being something that Grocco X needs

0:14:16.360 --> 0:14:19.680
<v Speaker 3>to camp down in some way, that's true.

0:14:20.240 --> 0:14:23.280
<v Speaker 9>There definitely is more of an appetite in Congress to

0:14:23.520 --> 0:14:28.560
<v Speaker 9>pass this legislation. There have been six new co sponsors

0:14:28.560 --> 0:14:30.760
<v Speaker 9>that have come on board since the beginning of the year.

0:14:31.560 --> 0:14:36.440
<v Speaker 9>I think that the issue of non consensual AI generated

0:14:36.520 --> 0:14:41.720
<v Speaker 9>images has become so vivid to lawmakers. Many of them,

0:14:42.200 --> 0:14:45.280
<v Speaker 9>like Alexandria Ocasio Cortez, are themselves the victims of this.

0:14:45.520 --> 0:14:48.040
<v Speaker 9>So I think the appetite has really broadened this year.

0:14:49.120 --> 0:14:53.480
<v Speaker 2>Emily, where does the company X and the platform X

0:14:53.520 --> 0:14:57.840
<v Speaker 2>fit into this in a citizen's right to sue and

0:14:57.880 --> 0:14:59.480
<v Speaker 2>those that distribute the content.

0:15:01.080 --> 0:15:05.000
<v Speaker 9>So the Defiance Act, which passed the Sunate this week,

0:15:05.160 --> 0:15:09.440
<v Speaker 9>that probably would not impact GROC, that impacts the people

0:15:09.480 --> 0:15:12.920
<v Speaker 9>who are responsible for distributing the images. But there is

0:15:12.960 --> 0:15:15.000
<v Speaker 9>a lot of conversation right now about whether the Take

0:15:15.040 --> 0:15:19.840
<v Speaker 9>It Down Act would empower Attorney's General to sue Grock

0:15:20.120 --> 0:15:26.520
<v Speaker 9>Xai Elon Musk over some level of responsibility for you know,

0:15:26.680 --> 0:15:29.160
<v Speaker 9>thousands of these images proliferating every hour.

0:15:29.960 --> 0:15:31.840
<v Speaker 4>So far, no Attorney's.

0:15:31.360 --> 0:15:35.560
<v Speaker 9>General have taken that up, but it's definitely under serious consideration.

0:15:35.640 --> 0:15:38.360
<v Speaker 3>Certainly something that maybe Malaysia has been putting forward about

0:15:38.360 --> 0:15:41.400
<v Speaker 3>whether or not it's Xai's responsibility in some way. Blueing

0:15:41.400 --> 0:15:44.640
<v Speaker 3>Magzemine van Bound, fantastic reporting, thank you very much. Indeed,

0:15:45.080 --> 0:15:48.920
<v Speaker 3>not coming up. ABMB has a new chief technology officer.

0:15:49.040 --> 0:15:50.840
<v Speaker 3>We'll hear about his plans for the short term mental

0:15:50.840 --> 0:15:52.080
<v Speaker 3>company that's next is.

0:15:52.000 --> 0:15:52.720
<v Speaker 4>A body meg Tech.

0:16:05.240 --> 0:16:08.480
<v Speaker 10>I'm extremely excited, like Brian said, to bring craft to

0:16:08.960 --> 0:16:12.480
<v Speaker 10>the art of deploying AI first features and products. So

0:16:13.320 --> 0:16:15.400
<v Speaker 10>I hope to be able to surprise the world with

0:16:15.520 --> 0:16:18.240
<v Speaker 10>really beautiful features that they're going to love using every day.

0:16:19.640 --> 0:16:23.720
<v Speaker 2>That was Airbnb's new CTO, Armadal Dala, weighing in on

0:16:23.760 --> 0:16:26.720
<v Speaker 2>the short term rental platforms AI efforts. Let's get more

0:16:26.880 --> 0:16:29.560
<v Speaker 2>wherever and Latterly Lung, who spoke with our Dala and

0:16:29.640 --> 0:16:32.960
<v Speaker 2>Airbnb CEO Brian Chesky. I think an interesting base start

0:16:33.000 --> 0:16:35.400
<v Speaker 2>is what is Airbnb trying to solve for here by

0:16:35.400 --> 0:16:37.200
<v Speaker 2>bringing in a new CTO. What is it they want

0:16:37.200 --> 0:16:38.680
<v Speaker 2>to change about the platform.

0:16:39.080 --> 0:16:41.600
<v Speaker 11>So after a few years of sort of working on

0:16:41.680 --> 0:16:45.000
<v Speaker 11>the plumbing of Airmb's app, like vamping the app, they

0:16:45.000 --> 0:16:48.480
<v Speaker 11>are ready to take it forward, adding AI across the app,

0:16:48.560 --> 0:16:51.520
<v Speaker 11>including customer service with which they did last year, and

0:16:51.560 --> 0:16:53.360
<v Speaker 11>now they're going to do more with search as well,

0:16:53.400 --> 0:16:56.840
<v Speaker 11>like letting people discover listings and also cross markets who

0:16:56.840 --> 0:17:00.240
<v Speaker 11>have their new services like tours and experiences going forward.

0:17:00.720 --> 0:17:02.760
<v Speaker 3>And I think you sort of put that exact question

0:17:02.800 --> 0:17:04.800
<v Speaker 3>to Brancheski himself. Let's just take a listen to how

0:17:04.840 --> 0:17:08.120
<v Speaker 3>he responded as to why they're pivoting and focusing all

0:17:08.119 --> 0:17:09.760
<v Speaker 3>in on AI at this moment, and take a listen.

0:17:10.720 --> 0:17:13.760
<v Speaker 12>We are at the beginning of this incredibly exciting technological

0:17:13.800 --> 0:17:16.600
<v Speaker 12>transformation with AI. It's going to be a journey. And

0:17:16.680 --> 0:17:19.320
<v Speaker 12>I couldn't be more excited about Ahmed because he's one

0:17:19.320 --> 0:17:21.480
<v Speaker 12>of the leading AI experts in the world, but he

0:17:21.560 --> 0:17:24.240
<v Speaker 12>also brings a sense of craft Airbnb, something we're really

0:17:24.280 --> 0:17:26.120
<v Speaker 12>known for. And I think what you're going to see

0:17:26.119 --> 0:17:29.640
<v Speaker 12>in Airbnb is not only AI search, but a very

0:17:29.680 --> 0:17:32.520
<v Speaker 12>personalized AI experience where I think we're going to bring

0:17:32.600 --> 0:17:36.400
<v Speaker 12>great design sensibility into the experience of Airbnb.

0:17:38.000 --> 0:17:40.879
<v Speaker 3>Let's talk a little bit about how they're talking of

0:17:40.880 --> 0:17:44.159
<v Speaker 3>the narrative of change because they've said farewell to the

0:17:44.160 --> 0:17:47.160
<v Speaker 3>previous CTO who's there for about seven years, and brought

0:17:47.200 --> 0:17:49.920
<v Speaker 3>in this expert from Meta. So who do they say

0:17:49.920 --> 0:17:52.320
<v Speaker 3>you farewell to and why is this Meta executed the

0:17:52.359 --> 0:17:52.879
<v Speaker 3>best place?

0:17:54.280 --> 0:17:57.760
<v Speaker 11>So Aribalo, the previous CTO came in during our time

0:17:57.800 --> 0:18:01.560
<v Speaker 11>when Airbnb was going through hypergrowth. There was seven more

0:18:01.560 --> 0:18:04.320
<v Speaker 11>than seven years ago. And now Airbnb is sort of,

0:18:04.760 --> 0:18:07.919
<v Speaker 11>as Cheskey said, going through a technological revolution of you

0:18:07.960 --> 0:18:11.480
<v Speaker 11>know lms and chat agents, and now Airbnb sort of

0:18:11.520 --> 0:18:13.840
<v Speaker 11>wants to use sort of the unique data they have

0:18:13.960 --> 0:18:17.399
<v Speaker 11>on the platform to differentiate itself from other you know,

0:18:17.560 --> 0:18:21.880
<v Speaker 11>chatbots to provide better recommendations to customers on their platform.

0:18:22.440 --> 0:18:26.080
<v Speaker 2>Abnb the company who stock growse about three percent last year,

0:18:26.600 --> 0:18:28.560
<v Speaker 2>down a couple of percent so far this year.

0:18:29.000 --> 0:18:30.200
<v Speaker 6>And Cheski was one of those.

0:18:30.040 --> 0:18:34.800
<v Speaker 2>People that was the early vocal behind founder mode it.

0:18:34.880 --> 0:18:36.920
<v Speaker 2>What's the health of Airbnb right now. Is this them

0:18:36.960 --> 0:18:39.280
<v Speaker 2>saying we've got to do something to re accelerate.

0:18:39.560 --> 0:18:44.040
<v Speaker 11>Yeah, Brian was not satisfied with the below ten percent

0:18:44.119 --> 0:18:46.520
<v Speaker 11>growth rate we've seen last year, and so he's been

0:18:46.640 --> 0:18:51.840
<v Speaker 11>very active in wanting to pilot more businesses for this year.

0:18:52.240 --> 0:18:55.880
<v Speaker 11>They're piloting boutique hotels and server cities, and they're trying

0:18:55.920 --> 0:18:59.359
<v Speaker 11>to add grocery delivery for people to pre stock their

0:18:59.440 --> 0:19:01.960
<v Speaker 11>kitchens before or are they check in. So they're trying

0:19:01.960 --> 0:19:04.240
<v Speaker 11>to get their growth free BACKRUP as sort of the

0:19:04.359 --> 0:19:06.200
<v Speaker 11>core rental service for chors.

0:19:06.560 --> 0:19:06.720
<v Speaker 4>Now.

0:19:06.760 --> 0:19:08.400
<v Speaker 3>So you've also got a story about how the chief

0:19:08.400 --> 0:19:11.120
<v Speaker 3>information officer has departed after the CTO shakeup.

0:19:11.359 --> 0:19:13.360
<v Speaker 4>Is there more executive leadership changes to come?

0:19:14.600 --> 0:19:16.800
<v Speaker 11>Yeah, so there would be. They're still looking for the

0:19:16.920 --> 0:19:20.960
<v Speaker 11>new CIO. We can expect that to come in in

0:19:21.000 --> 0:19:23.119
<v Speaker 11>the months in the year ahead.

0:19:23.600 --> 0:19:26.480
<v Speaker 3>Most Natalie Lung, thank you very much. Indeed, let's turn

0:19:26.480 --> 0:19:30.040
<v Speaker 3>out attention to entertainment now. Netflix is working to revise

0:19:30.160 --> 0:19:33.439
<v Speaker 3>it's been for Warner Brothers Discovery, potentially shifting to an

0:19:33.440 --> 0:19:36.240
<v Speaker 3>all cash offer, according to sources. Now the moves aimed

0:19:36.240 --> 0:19:38.640
<v Speaker 3>at speeding up a deal that lookers face pushback from

0:19:38.720 --> 0:19:43.360
<v Speaker 3>Washington and competition from rival, bit of Paramounts guidance for more, Let's.

0:19:43.200 --> 0:19:43.760
<v Speaker 4>Get to the new most.

0:19:43.800 --> 0:19:47.159
<v Speaker 3>Lucas Shaw, who covers media and entertainment, hit this story

0:19:47.160 --> 0:19:51.400
<v Speaker 3>hard and Lucas, I mean the all cash narrative. Why

0:19:51.480 --> 0:19:53.880
<v Speaker 3>is that important? Why would that be the winning formula

0:19:53.920 --> 0:19:54.520
<v Speaker 3>for Netflix?

0:19:56.080 --> 0:20:00.320
<v Speaker 13>Because investors like cash now versus stock, and that's that

0:20:00.359 --> 0:20:01.480
<v Speaker 13>they could sell later.

0:20:01.600 --> 0:20:01.760
<v Speaker 11>Right.

0:20:02.440 --> 0:20:05.440
<v Speaker 13>One of the knocks against the Netflix deal as perpetuated

0:20:05.440 --> 0:20:08.240
<v Speaker 13>at least by by Paramounts guidance. The rival bidder has

0:20:08.240 --> 0:20:11.159
<v Speaker 13>been that Paramount's deal is all cash, and that Netflix

0:20:11.240 --> 0:20:14.600
<v Speaker 13>deal contains you know, between four and five dollars a.

0:20:14.640 --> 0:20:15.440
<v Speaker 6>Share of stock.

0:20:15.520 --> 0:20:17.960
<v Speaker 13>Now, Netflix stock is pretty valuable, something that you think

0:20:18.000 --> 0:20:20.320
<v Speaker 13>people would want to have, but most people would rather

0:20:20.400 --> 0:20:23.080
<v Speaker 13>just take the cash now and get paid. And so

0:20:23.800 --> 0:20:26.720
<v Speaker 13>that I think Netflix hopes will accelerate on many fronts.

0:20:26.720 --> 0:20:26.760
<v Speaker 11>It.

0:20:27.160 --> 0:20:30.120
<v Speaker 13>You know, it'll assuage any shareholder concerns about their bid

0:20:30.200 --> 0:20:34.440
<v Speaker 13>and also eliminate any potential complexities as they continue to

0:20:34.920 --> 0:20:35.919
<v Speaker 13>negotiate and pursue it.

0:20:37.119 --> 0:20:39.359
<v Speaker 2>Lucas, when we were reporting this out, you know, the

0:20:39.440 --> 0:20:42.359
<v Speaker 2>Netflix response and the tit for tat, you know, Paramounts

0:20:42.359 --> 0:20:44.760
<v Speaker 2>suing earlier this week and nominated our It's to the board.

0:20:45.040 --> 0:20:47.600
<v Speaker 2>Do you get the sense that Netflix think this will work,

0:20:48.440 --> 0:20:51.320
<v Speaker 2>that they now are back in sort of the lead

0:20:51.359 --> 0:20:53.240
<v Speaker 2>in a tight race for the assets.

0:20:54.280 --> 0:20:54.879
<v Speaker 6>Well, I don't.

0:20:55.280 --> 0:20:57.040
<v Speaker 13>I think if you were to talk to the people

0:20:57.040 --> 0:20:59.600
<v Speaker 13>at Netflix, they've never felt they were out of the lead,

0:20:59.720 --> 0:21:03.639
<v Speaker 13>right know, they are obviously facing a stiff challenge from Paramount,

0:21:04.119 --> 0:21:07.840
<v Speaker 13>but they're the ones who have an approved deal, and

0:21:07.880 --> 0:21:11.760
<v Speaker 13>they have yet to see kind of some they have

0:21:11.840 --> 0:21:14.160
<v Speaker 13>yet to see shareholders say and masks we don't want

0:21:14.160 --> 0:21:15.879
<v Speaker 13>the Netflix deal. They have yet to see the federal

0:21:15.920 --> 0:21:18.000
<v Speaker 13>government say we're going to block this deal. There are

0:21:18.119 --> 0:21:21.080
<v Speaker 13>certainly some kind of blinking yellow lights, but I don't

0:21:21.080 --> 0:21:23.880
<v Speaker 13>think they've they've seen anything yet that that gives makes

0:21:23.920 --> 0:21:26.240
<v Speaker 13>them too concerned. They seem still pretty confident that they'll

0:21:26.240 --> 0:21:26.600
<v Speaker 13>get this.

0:21:26.600 --> 0:21:29.680
<v Speaker 3>Done and in a week January twenty first, that's when

0:21:29.680 --> 0:21:33.680
<v Speaker 3>the tend to offer for certainly the Paramount Skuydance side

0:21:33.680 --> 0:21:35.960
<v Speaker 3>of the equation runs out, right. I mean, do you

0:21:35.960 --> 0:21:38.080
<v Speaker 3>get any signal for investors that they were tool interested

0:21:38.119 --> 0:21:38.800
<v Speaker 3>in that side?

0:21:39.880 --> 0:21:43.880
<v Speaker 13>You know, investors have been split some of the big

0:21:43.880 --> 0:21:46.560
<v Speaker 13>investor investment funds, you know, they don't say anything, but

0:21:46.560 --> 0:21:48.919
<v Speaker 13>we have spoken with a number of the major shareholders

0:21:48.920 --> 0:21:52.040
<v Speaker 13>and I'd say their reactions range from we prefer Netflix,

0:21:52.240 --> 0:21:54.399
<v Speaker 13>do we prefer Paramount, And then a lot of people

0:21:54.400 --> 0:21:57.120
<v Speaker 13>in the middle are basically saying, you know, tie right

0:21:57.160 --> 0:21:59.360
<v Speaker 13>now goes to the winner, which is Netflix. But we

0:21:59.480 --> 0:22:03.160
<v Speaker 13>hope Slash expect that Paramount will increase its offer, which

0:22:03.240 --> 0:22:04.760
<v Speaker 13>Lucas is a pretty clear Paramount move.

0:22:06.080 --> 0:22:08.280
<v Speaker 2>Just very quickly remind us of the state of play.

0:22:08.440 --> 0:22:10.000
<v Speaker 2>The difference between the two bids.

0:22:11.160 --> 0:22:15.000
<v Speaker 13>Well, Netflix's bid is for just the studio and streaming service,

0:22:15.160 --> 0:22:19.320
<v Speaker 13>so Warner Brothers and HBO. Paramount's bid is for the

0:22:19.359 --> 0:22:22.280
<v Speaker 13>whole company, so that includes all the cable networks like CNNT, N,

0:22:22.320 --> 0:22:23.399
<v Speaker 13>T TBS and the like.

0:22:24.560 --> 0:22:27.280
<v Speaker 2>Bloombos Lucas Shaw, who leads the team at screen time,

0:22:27.359 --> 0:22:29.080
<v Speaker 2>that has led the way on reporting this story.

0:22:29.119 --> 0:22:31.600
<v Speaker 6>Thank you so much. Now coming up on Bloomberg.

0:22:31.280 --> 0:22:34.960
<v Speaker 2>Tech, robotics startup Skilled Ai just closed a one point

0:22:34.960 --> 0:22:39.440
<v Speaker 2>four billion dollar funding round, a big valuation, tripling.

0:22:39.440 --> 0:22:43.160
<v Speaker 6>From a year. This is next. This is Bloomberg Tech.

0:23:02.920 --> 0:23:04.879
<v Speaker 4>Welcome back to Bloomberg Tech. Let's check in on the

0:23:04.960 --> 0:23:06.159
<v Speaker 4>markets that are under pressure.

0:23:06.160 --> 0:23:08.359
<v Speaker 3>Look we've got a wall of warriors to come to

0:23:08.400 --> 0:23:12.119
<v Speaker 3>the earning season geopolitical risks, and we see some dragged

0:23:12.119 --> 0:23:13.560
<v Speaker 3>down and big tech. We're off by one point few

0:23:13.600 --> 0:23:15.359
<v Speaker 3>percent on the NASDAK. In fact, two straight days of

0:23:15.359 --> 0:23:17.800
<v Speaker 3>losses on the SMP. We're coming off of record highs

0:23:17.920 --> 0:23:19.879
<v Speaker 3>in video, of course, confronting that news that maybe EAH

0:23:19.880 --> 0:23:22.639
<v Speaker 3>two hundreds could be getting closer to exporting to China.

0:23:22.880 --> 0:23:24.520
<v Speaker 3>But at the moment we're under pressure. It's one of

0:23:24.520 --> 0:23:26.800
<v Speaker 3>the key drags on the downside. Bitcoin though, of three

0:23:26.840 --> 0:23:28.920
<v Speaker 3>point four percent. We're seeing maybe a bit of love

0:23:28.960 --> 0:23:31.640
<v Speaker 3>for digital gold, not just gold, silver and copper. We're

0:23:31.680 --> 0:23:34.159
<v Speaker 3>also seeing maybe some shorts getting squeezed out. Move on,

0:23:34.359 --> 0:23:36.239
<v Speaker 3>have a look at what's happening in individual stocks. I'm

0:23:36.280 --> 0:23:38.480
<v Speaker 3>trying to light on Honeywell, look, we're at one point

0:23:38.480 --> 0:23:42.640
<v Speaker 3>eight percent. Maybe an asset that it controls quantinum could

0:23:42.680 --> 0:23:45.520
<v Speaker 3>be looking for an IPO. We're an understanding that they're

0:23:45.560 --> 0:23:49.119
<v Speaker 3>potentially filing for an IPO with the SEC. We know

0:23:49.200 --> 0:23:51.359
<v Speaker 3>that this last valuation was about eleven billion dollars Z

0:23:51.440 --> 0:23:53.680
<v Speaker 3>We've got other key strategics and videos in their GP

0:23:53.760 --> 0:23:56.000
<v Speaker 3>Morgans in there as well, so all eyes on quantum

0:23:56.040 --> 0:23:58.160
<v Speaker 3>computing as we look towards twenty twenty six.

0:23:57.960 --> 0:23:58.680
<v Speaker 4>What are you looking at?

0:23:59.119 --> 0:24:01.360
<v Speaker 6>Yeah, we also have a big deal in private markets.

0:24:01.440 --> 0:24:04.600
<v Speaker 2>Robotic startup Skilled Ai has just closed a one point

0:24:04.640 --> 0:24:08.320
<v Speaker 2>four billion dollar funding around the valuation more than fourteen

0:24:08.440 --> 0:24:11.320
<v Speaker 2>billion dollars and that's for a company only founded in

0:24:11.359 --> 0:24:13.960
<v Speaker 2>twenty twenty three. Skilled is aiming to stand out in

0:24:14.000 --> 0:24:18.240
<v Speaker 2>what's a crowded field by building an AI powered robotic brain.

0:24:18.880 --> 0:24:20.960
<v Speaker 2>The goal is to develop a system that can adapt

0:24:21.040 --> 0:24:24.879
<v Speaker 2>across environments and form factors and crucially learn from its

0:24:24.960 --> 0:24:28.480
<v Speaker 2>own mistakes. Joining us to discuss a Skilled co founder

0:24:28.520 --> 0:24:31.119
<v Speaker 2>and CEO, Deepak Pathak, It's great to have you on

0:24:31.119 --> 0:24:35.080
<v Speaker 2>Bloomberg Tech. What's interesting. Let's start with the round. It's

0:24:35.160 --> 0:24:38.080
<v Speaker 2>not just the volume, it's not just the valuation. Some

0:24:38.200 --> 0:24:41.520
<v Speaker 2>of the strategics that are backing you in Nvidia, others

0:24:41.520 --> 0:24:45.320
<v Speaker 2>in consumer electronics, Samsung LG and in the software sector

0:24:45.359 --> 0:24:49.000
<v Speaker 2>as well. What are they recognizing is your core competence?

0:24:49.040 --> 0:24:50.479
<v Speaker 6>Do you think so?

0:24:51.800 --> 0:24:53.680
<v Speaker 14>If you're thinking about the robotics today is one of

0:24:53.720 --> 0:24:58.040
<v Speaker 14>the oldest areas in technology. In EI was big for robotics.

0:24:58.560 --> 0:25:01.200
<v Speaker 14>We have seen amazing they're more robotics for the last

0:25:01.440 --> 0:25:04.439
<v Speaker 14>seventy years, not four or five years, seventy years. But

0:25:04.480 --> 0:25:07.679
<v Speaker 14>we are robots around us. And this is what people

0:25:07.760 --> 0:25:10.440
<v Speaker 14>often get wrong. When you think of robots in your mind,

0:25:10.760 --> 0:25:13.560
<v Speaker 14>you imagine hardware like that comes to a point in

0:25:13.560 --> 0:25:15.960
<v Speaker 14>your mind first, because that's how Hollywood has primed us.

0:25:16.400 --> 0:25:19.800
<v Speaker 14>But the main thing in behind that not having robots

0:25:19.800 --> 0:25:22.360
<v Speaker 14>around us today is the brain is missing. And if

0:25:22.400 --> 0:25:25.520
<v Speaker 14>you have the brain for robots, you can really enable

0:25:25.560 --> 0:25:28.159
<v Speaker 14>them around in variety of areas. We active applications, and

0:25:28.240 --> 0:25:30.960
<v Speaker 14>that's what exactly SCARED is doing. We are building what

0:25:31.000 --> 0:25:35.080
<v Speaker 14>we call only bodied brain, any robot, any task one brain.

0:25:35.440 --> 0:25:36.840
<v Speaker 6>I'm interested in how you're building it.

0:25:36.880 --> 0:25:38.840
<v Speaker 2>The limitation that a lot of people are talking about

0:25:38.920 --> 0:25:42.199
<v Speaker 2>right now is real world data and training. There are

0:25:42.240 --> 0:25:47.879
<v Speaker 2>different approaches digital twins, trying to simulate physics in digital worlds.

0:25:47.920 --> 0:25:49.879
<v Speaker 2>This is very much what in video is focused on,

0:25:50.000 --> 0:25:53.879
<v Speaker 2>right is that the approach you've taken simulated or synthetic data.

0:25:53.960 --> 0:25:57.000
<v Speaker 14>So I think I will draw analogy to lllms like Jagpity,

0:25:57.080 --> 0:25:59.960
<v Speaker 14>like models like if you see open a head Jadgepitty,

0:26:00.240 --> 0:26:03.200
<v Speaker 14>And soon after many companies had their own LM models,

0:26:03.280 --> 0:26:05.359
<v Speaker 14>and the reason for that is data exist on the

0:26:05.440 --> 0:26:08.720
<v Speaker 14>Internet for language or vision, but robotics there is no

0:26:08.880 --> 0:26:12.320
<v Speaker 14>Internet of robotics today. So what we do is we

0:26:12.359 --> 0:26:16.560
<v Speaker 14>look for alternate sources. One such source is human videos.

0:26:17.000 --> 0:26:20.840
<v Speaker 14>We look at how humans operate in their scenarios in

0:26:20.880 --> 0:26:25.720
<v Speaker 14>your kchareen in while working in factories, and combine that

0:26:25.880 --> 0:26:28.520
<v Speaker 14>with training come simulation, which companies like Nvidia invest a

0:26:28.560 --> 0:26:29.960
<v Speaker 14>lot on, like omni.

0:26:29.760 --> 0:26:30.480
<v Speaker 4>Verse and all those.

0:26:30.720 --> 0:26:34.920
<v Speaker 14>So these two things watching people and then practicing in simulation.

0:26:35.160 --> 0:26:39.160
<v Speaker 14>That's how we combine and scale these models to large scale.

0:26:39.440 --> 0:26:42.200
<v Speaker 4>Your software can be put within the GPU.

0:26:42.840 --> 0:26:45.320
<v Speaker 3>And what's interesting is you're already going from what we

0:26:45.400 --> 0:26:48.680
<v Speaker 3>understand zero to tens of millions of dollars deepak in

0:26:48.760 --> 0:26:52.040
<v Speaker 3>revenue just a few months in twenty twenty five.

0:26:52.400 --> 0:26:55.720
<v Speaker 4>Where's that revenue coming from? Who is using your software already?

0:26:56.680 --> 0:26:59.720
<v Speaker 14>Yep, So this is the revenue has mostly been from

0:26:59.720 --> 0:27:05.479
<v Speaker 14>the price applications. And the idea is in like instead

0:27:05.480 --> 0:27:09.280
<v Speaker 14>of instead of going for our end goal is a

0:27:09.280 --> 0:27:14.320
<v Speaker 14>consumer homelike applications. But right now, since it's just a

0:27:14.359 --> 0:27:16.639
<v Speaker 14>beginning of the field, we are taking this model and

0:27:16.680 --> 0:27:18.919
<v Speaker 14>we are deploying it in variety of applications, like we

0:27:18.960 --> 0:27:24.400
<v Speaker 14>are deploying robots in sectors like point to point delivery applications,

0:27:25.040 --> 0:27:31.119
<v Speaker 14>security applications, data centers, and manufacturing and warehouse so the

0:27:31.160 --> 0:27:33.160
<v Speaker 14>revenue is coming from most of these applications.

0:27:33.480 --> 0:27:37.000
<v Speaker 3>You're born out of academia and you're still professor kind

0:27:37.040 --> 0:27:39.480
<v Speaker 3>of emlan. But what's interesting is you're not without some

0:27:39.480 --> 0:27:42.359
<v Speaker 3>competition out there. I think about physical intelligence for example,

0:27:42.480 --> 0:27:45.240
<v Speaker 3>you're all trying to intend to get robots to become

0:27:45.280 --> 0:27:48.720
<v Speaker 3>intelligent and situationally aware. Do you think you can take

0:27:48.760 --> 0:27:50.240
<v Speaker 3>on Are you worried about competition?

0:27:51.600 --> 0:27:54.800
<v Speaker 14>Well, competition is always good and turns out like the

0:27:54.880 --> 0:27:59.360
<v Speaker 14>AI community born from very small circles. So they're all

0:27:59.400 --> 0:28:04.520
<v Speaker 14>our friends and colleagues from earlier. But what's unique about

0:28:04.560 --> 0:28:07.879
<v Speaker 14>what we are building is this only bodied brain, like

0:28:08.320 --> 0:28:11.640
<v Speaker 14>any robot, any task one brain. Now, if you really

0:28:12.160 --> 0:28:16.000
<v Speaker 14>think deeply about this, it sounds absurd, like a humanoid

0:28:16.080 --> 0:28:18.919
<v Speaker 14>robot with a human like body, a dog robot and

0:28:18.960 --> 0:28:21.880
<v Speaker 14>they share the same brain. And that's what you see

0:28:22.119 --> 0:28:23.680
<v Speaker 14>in the reserves we release.

0:28:24.200 --> 0:28:25.760
<v Speaker 6>The difference in approach is fascinating.

0:28:25.800 --> 0:28:28.040
<v Speaker 2>It is a crowded failed you know, Burnt from one

0:28:28.160 --> 0:28:30.159
<v Speaker 2>X was on the show yesterday. They have a world

0:28:30.240 --> 0:28:35.560
<v Speaker 2>model that essentially allows NEO to carry out a task.

0:28:35.640 --> 0:28:39.360
<v Speaker 2>It's it's never seen before and that largely you know,

0:28:39.400 --> 0:28:41.640
<v Speaker 2>I'm not an engineer, right, but what you have in

0:28:41.640 --> 0:28:46.600
<v Speaker 2>common is VLN. Those are the inputs distinguish your approach

0:28:46.640 --> 0:28:48.520
<v Speaker 2>to one X's as an example.

0:28:48.640 --> 0:28:52.520
<v Speaker 14>So in our case, the robot learns by watching people.

0:28:52.640 --> 0:28:54.680
<v Speaker 14>Right now, imagine I have to pick up this cup

0:28:54.680 --> 0:28:57.520
<v Speaker 14>in front of mee do I have to exactly imagine?

0:28:57.520 --> 0:29:01.360
<v Speaker 14>So scary By the way, watching me you learned when

0:29:01.360 --> 0:29:03.320
<v Speaker 14>you were a kid. You learned by watching your periods.

0:29:03.760 --> 0:29:07.200
<v Speaker 14>You learn watching others. Now, if you think about how

0:29:07.240 --> 0:29:09.640
<v Speaker 14>you how you operate. Every time you pick up a cup,

0:29:09.920 --> 0:29:12.080
<v Speaker 14>do you imagine in your head a picture of cup

0:29:12.120 --> 0:29:14.360
<v Speaker 14>and then putting your finger in the handle, And no,

0:29:14.480 --> 0:29:17.800
<v Speaker 14>it's all mushed in like somehow it's consciousness inside your

0:29:17.800 --> 0:29:20.480
<v Speaker 14>body and then you imagine in some abstract space and

0:29:20.680 --> 0:29:23.080
<v Speaker 14>then do it. And that is the main idea here.

0:29:23.360 --> 0:29:25.560
<v Speaker 14>That's how we do it. But just ted being said,

0:29:26.000 --> 0:29:28.520
<v Speaker 14>watching alone is not enough because if it was enough,

0:29:28.520 --> 0:29:31.320
<v Speaker 14>I could play like Federer, keep watching his games all day.

0:29:31.640 --> 0:29:35.080
<v Speaker 14>And that's where practice comes into play now. Practicing in

0:29:35.120 --> 0:29:38.440
<v Speaker 14>the real world in the making mistakes is expensive, and

0:29:38.480 --> 0:29:42.960
<v Speaker 14>that's where become mind simulation. So videos alone is not enough.

0:29:43.200 --> 0:29:45.719
<v Speaker 14>Same alone is not enough. But put them together and

0:29:45.840 --> 0:29:48.800
<v Speaker 14>boom you have a magic recipe to really figure out

0:29:48.840 --> 0:29:49.800
<v Speaker 14>how to scale robotics.

0:29:50.480 --> 0:29:53.440
<v Speaker 3>Magic recipe that values are forteen billion dollars as far

0:29:53.560 --> 0:29:57.240
<v Speaker 3>Deepak Pathact co found a CEO skilled AI. Thanks so

0:29:57.320 --> 0:30:00.520
<v Speaker 3>much for joining us today coming out more funn around news.

0:30:00.560 --> 0:30:03.280
<v Speaker 3>Excel partner Sarah Dlston joins us to talk about her

0:30:03.360 --> 0:30:07.200
<v Speaker 3>latest investment in AI security startup debt First.

0:30:07.560 --> 0:30:08.480
<v Speaker 4>There's somebody meg tech.

0:30:20.600 --> 0:30:23.800
<v Speaker 2>Security startup debt First, has closed a forty million dollars

0:30:23.920 --> 0:30:27.480
<v Speaker 2>Series A funding round. The company uses AI to identify

0:30:27.840 --> 0:30:29.560
<v Speaker 2>and harden software vulnerabilities.

0:30:29.560 --> 0:30:31.120
<v Speaker 6>The round led by Excel.

0:30:31.440 --> 0:30:35.280
<v Speaker 2>Joining us to discuss Excel partner Sarah Wilson Debt First.

0:30:35.760 --> 0:30:38.320
<v Speaker 2>This was a big theme actually at AWS reinvent the

0:30:38.400 --> 0:30:41.640
<v Speaker 2>idea that particularly sort of swarm based agents can go

0:30:41.680 --> 0:30:44.480
<v Speaker 2>on the offense, not just defense. So it's a sensible

0:30:44.520 --> 0:30:47.280
<v Speaker 2>place to start with. Why you made the investment in

0:30:47.320 --> 0:30:51.120
<v Speaker 2>general security intelligence is what can it do that existing

0:30:51.160 --> 0:30:55.400
<v Speaker 2>app SEC and other sort of static analysis tools just can't.

0:30:56.360 --> 0:30:59.240
<v Speaker 15>I think the main thing is performance and speed and

0:30:59.280 --> 0:31:01.880
<v Speaker 15>the ratio of signal to noise. So I think what

0:31:01.920 --> 0:31:04.440
<v Speaker 15>we have to realize in this moment is, as we're

0:31:04.480 --> 0:31:07.440
<v Speaker 15>all so excited about how AI is making it possible

0:31:07.440 --> 0:31:10.920
<v Speaker 15>to ship software so much more quickly, that same AI

0:31:10.960 --> 0:31:13.520
<v Speaker 15>tool is being used by the bad guys to ship

0:31:13.560 --> 0:31:17.320
<v Speaker 15>attacks more quickly. And so the historical ratio of signal

0:31:17.360 --> 0:31:20.160
<v Speaker 15>to noise just won't stand in the current era. And

0:31:20.240 --> 0:31:23.160
<v Speaker 15>so the security platform that Debt first has made is

0:31:23.320 --> 0:31:27.520
<v Speaker 15>AI native. And what they are doing is continuously agentically

0:31:27.560 --> 0:31:31.480
<v Speaker 15>scanning a company's code. They're looking at its architecture, they're

0:31:31.480 --> 0:31:36.200
<v Speaker 15>looking at its business logic, and they're finding verified vulnerabilities

0:31:36.440 --> 0:31:39.400
<v Speaker 15>eight times more than the previous best in class. And

0:31:39.440 --> 0:31:41.840
<v Speaker 15>I think the key there is verified vulnerability is they're

0:31:41.880 --> 0:31:44.520
<v Speaker 15>not raving their hands about things that aren't really a problem.

0:31:44.760 --> 0:31:47.479
<v Speaker 15>They're finding real problems, and then they're also serving up

0:31:47.480 --> 0:31:50.360
<v Speaker 15>a solution. You can press one button and say fix it,

0:31:51.160 --> 0:31:52.240
<v Speaker 15>and folks are doing that.

0:31:52.760 --> 0:31:56.400
<v Speaker 2>In mass I was looking at the round. It's a

0:31:56.440 --> 0:31:59.000
<v Speaker 2>sizable series A. You know, in the last couple of

0:31:59.120 --> 0:32:03.680
<v Speaker 2>years the market has been somewhat distorted depending on the

0:32:03.720 --> 0:32:05.480
<v Speaker 2>company's type.

0:32:05.920 --> 0:32:08.320
<v Speaker 6>But what you just said eight times invest in class.

0:32:08.360 --> 0:32:10.880
<v Speaker 2>How critical is a data point like that to you

0:32:10.960 --> 0:32:13.040
<v Speaker 2>when you decide do I want to be in this

0:32:13.160 --> 0:32:14.760
<v Speaker 2>round a tool or not evidence?

0:32:15.280 --> 0:32:18.400
<v Speaker 15>It's really critical, and I think, particularly in the case

0:32:18.400 --> 0:32:22.000
<v Speaker 15>of security, there's just a societal imperative that we get

0:32:22.040 --> 0:32:24.600
<v Speaker 15>this right. And I think Excel We've been investing for

0:32:24.600 --> 0:32:28.320
<v Speaker 15>forty three years. Throughout that time, security has been a

0:32:28.440 --> 0:32:32.720
<v Speaker 15>key category of investment for US folks like CrowdStrike or netscope,

0:32:32.760 --> 0:32:36.400
<v Speaker 15>that IPO just last year, and what we've seen is

0:32:36.440 --> 0:32:41.400
<v Speaker 15>in these major innovation transitions, these major you know, cycles

0:32:41.720 --> 0:32:45.880
<v Speaker 15>of transition, the security apparatus has to be replaced.

0:32:45.960 --> 0:32:47.600
<v Speaker 4>It has to evolve to that new era.

0:32:48.040 --> 0:32:50.760
<v Speaker 15>And that's why we're so excited about companies like Depth first.

0:32:50.960 --> 0:32:54.160
<v Speaker 15>But you're exactly right, you know, it has to work.

0:32:54.920 --> 0:32:56.960
<v Speaker 15>It's imperative that it works, and so those stats are

0:32:57.000 --> 0:32:59.560
<v Speaker 15>really important. They're important to the CISOs, they're important to

0:32:59.560 --> 0:33:02.560
<v Speaker 15>the fortune fifty that are evaluating these companies. And so

0:33:03.040 --> 0:33:06.000
<v Speaker 15>if we're gonna, you know, put ourselves in our funds

0:33:06.040 --> 0:33:09.560
<v Speaker 15>behind a company, it's imperative that we believe that the

0:33:09.600 --> 0:33:12.600
<v Speaker 15>thing works and not just not just today, but that

0:33:12.680 --> 0:33:16.120
<v Speaker 15>you have the team that can drive over this next

0:33:16.200 --> 0:33:19.560
<v Speaker 15>era of transition, that you have the talent that can

0:33:19.600 --> 0:33:21.880
<v Speaker 15>sort of weather this moment.

0:33:22.520 --> 0:33:27.560
<v Speaker 3>The talent is Hanley Soltofta, and you're seeing Palo Alto Networks.

0:33:27.760 --> 0:33:30.479
<v Speaker 3>Even so it's now he's in big acquisitions in the space,

0:33:31.040 --> 0:33:33.360
<v Speaker 3>trying to get ahead of the cyber risks around AI.

0:33:33.920 --> 0:33:36.920
<v Speaker 4>Do you think that this is a long term bet?

0:33:36.920 --> 0:33:39.200
<v Speaker 4>Will this company go public or do you think it

0:33:39.240 --> 0:33:40.400
<v Speaker 4>will be an M and A story.

0:33:41.960 --> 0:33:44.440
<v Speaker 15>You know, I think this is absolutely a long term bet.

0:33:44.520 --> 0:33:48.200
<v Speaker 15>That is always our you know, our focus when we

0:33:48.400 --> 0:33:51.520
<v Speaker 15>do our investing, and I think that this is a

0:33:51.560 --> 0:33:54.480
<v Speaker 15>team that's really uniquely qualified to go that distance. So

0:33:55.120 --> 0:33:58.520
<v Speaker 15>this is technical leaders from companies like Data Bricks, from

0:33:58.600 --> 0:34:02.719
<v Speaker 15>Google DeepMind, from fair These are folks who have built

0:34:03.160 --> 0:34:08.480
<v Speaker 15>you know, large durable companies and confronted these security problems.

0:34:08.000 --> 0:34:09.400
<v Speaker 4>At an incredible scale.

0:34:09.800 --> 0:34:13.919
<v Speaker 15>But mirroring that cyber experience with the AI experience, very

0:34:13.920 --> 0:34:18.240
<v Speaker 15>few people have had sort of the experience of building.

0:34:17.920 --> 0:34:19.759
<v Speaker 4>At a place like Google.

0:34:19.480 --> 0:34:23.040
<v Speaker 15>Deep Mind and can now apply that to this context.

0:34:23.040 --> 0:34:26.960
<v Speaker 15>So it's a really interdisciplinary team, a highly technical team

0:34:27.520 --> 0:34:31.200
<v Speaker 15>that we believe is very unique in their ability to

0:34:31.200 --> 0:34:32.120
<v Speaker 15>tackle this problem.

0:34:32.360 --> 0:34:35.239
<v Speaker 3>Sarah, you a head of strategy Partnerships at fair So

0:34:36.400 --> 0:34:38.600
<v Speaker 3>when you're thinking about who are the talent you want

0:34:38.640 --> 0:34:40.680
<v Speaker 3>to go for, is it your own network you need

0:34:40.760 --> 0:34:44.000
<v Speaker 3>upon Is it that you're hearing these companies being born

0:34:44.080 --> 0:34:46.440
<v Speaker 3>out of these big deep minds even before they're a

0:34:46.440 --> 0:34:50.040
<v Speaker 3>really created. How you tapping into a really early stage

0:34:50.040 --> 0:34:51.520
<v Speaker 3>business that needs financing?

0:34:53.040 --> 0:34:55.280
<v Speaker 4>Yeah, I think it's all of the above.

0:34:55.600 --> 0:34:57.560
<v Speaker 15>And then you know, we hope to spend a lot

0:34:57.600 --> 0:34:59.919
<v Speaker 15>of time with folks during the early days when they're

0:35:00.000 --> 0:35:03.520
<v Speaker 15>really you know, considering starting a company or the early

0:35:03.560 --> 0:35:06.200
<v Speaker 15>definition of the company. You know, our goal is to

0:35:06.280 --> 0:35:11.400
<v Speaker 15>be along the journey for decades, right the generational companies

0:35:11.440 --> 0:35:14.280
<v Speaker 15>that are going to solve these security problems will last

0:35:14.320 --> 0:35:16.359
<v Speaker 15>that long, and so we do we try and find

0:35:16.360 --> 0:35:18.240
<v Speaker 15>them early. And it can be through a lot of things,

0:35:18.280 --> 0:35:20.680
<v Speaker 15>but certainly one of the greatest signals is when we

0:35:20.719 --> 0:35:24.640
<v Speaker 15>see incredibly talented people that we know to be excellent

0:35:25.120 --> 0:35:27.080
<v Speaker 15>aggregating around an opportunity.

0:35:27.640 --> 0:35:29.600
<v Speaker 4>And I think what really emerged.

0:35:29.200 --> 0:35:33.200
<v Speaker 15>About this team is that they're incredibly motivated by this mission.

0:35:33.440 --> 0:35:36.920
<v Speaker 15>And if you look around all of our critical systems

0:35:36.920 --> 0:35:40.520
<v Speaker 15>in society are powered by software. Software that people can

0:35:40.520 --> 0:35:45.120
<v Speaker 15>write increasingly quickly with AI, and the other dimension that's

0:35:45.200 --> 0:35:49.000
<v Speaker 15>changing is increasingly we're giving this software more autonomy, we're

0:35:49.040 --> 0:35:52.040
<v Speaker 15>giving it more access, we're giving it the ability to reason,

0:35:52.440 --> 0:35:57.200
<v Speaker 15>and that's really exciting, but it's also something that would

0:35:57.239 --> 0:35:59.719
<v Speaker 15>be concerning if those things aren't secure. We just watch

0:35:59.800 --> 0:36:02.759
<v Speaker 15>your segment talking about the robots, right. We want to

0:36:02.800 --> 0:36:06.160
<v Speaker 15>make sure if we're getting these devices access to our homes,

0:36:06.200 --> 0:36:09.120
<v Speaker 15>to our businesses, that they're secure. And I think that

0:36:09.120 --> 0:36:11.520
<v Speaker 15>that is a is a belief that's shared by the

0:36:11.520 --> 0:36:15.040
<v Speaker 15>Depth First team that they this is sort of an

0:36:15.080 --> 0:36:17.440
<v Speaker 15>imperative for society that we get this right, that we

0:36:17.600 --> 0:36:21.000
<v Speaker 15>ensure that all of this new AI generated code that's

0:36:21.040 --> 0:36:23.720
<v Speaker 15>being shipped at increasing rates is all secure.

0:36:23.880 --> 0:36:26.280
<v Speaker 3>What's being shipped by a load of your portfolio companies Cursor,

0:36:26.320 --> 0:36:29.080
<v Speaker 3>Lovable and Thrope among some of the bets over Accel.

0:36:29.120 --> 0:36:32.520
<v Speaker 3>We really appreciate your time, Accel partner Sarah Itttleston. Now

0:36:32.600 --> 0:36:36.160
<v Speaker 3>coming up Spotify, f co, CEOs my Face are host

0:36:36.200 --> 0:36:39.040
<v Speaker 3>of challenges more the Audio Giants plans next.

0:36:38.880 --> 0:36:39.480
<v Speaker 4>That's a blue bag.

0:36:39.560 --> 0:36:51.840
<v Speaker 2>Tech Salesforce is looking to bolster AI capabilities for Slack users.

0:36:51.840 --> 0:36:54.640
<v Speaker 2>The company is releasing an upgraded slack bot that uses

0:36:54.680 --> 0:36:58.160
<v Speaker 2>anthropics claud model, joining us to discuss Rob Seaman's Slack

0:36:58.200 --> 0:37:01.480
<v Speaker 2>interim CEO and Chief Products Office. You know, I have

0:37:01.640 --> 0:37:05.040
<v Speaker 2>not yet got access to this, this updated slack bot,

0:37:05.280 --> 0:37:08.560
<v Speaker 2>but as a Slack user, very interested to see where

0:37:08.600 --> 0:37:09.080
<v Speaker 2>this goes.

0:37:09.480 --> 0:37:09.719
<v Speaker 6>Rob.

0:37:09.960 --> 0:37:13.919
<v Speaker 2>The general idea, right was that Mark Bennioff, the parent

0:37:14.000 --> 0:37:17.360
<v Speaker 2>company CEO, was using chat GPT and you guys are like,

0:37:17.440 --> 0:37:19.320
<v Speaker 2>we want to have an internal tool.

0:37:19.560 --> 0:37:22.560
<v Speaker 6>So has it worked? What is he using it for?

0:37:22.880 --> 0:37:26.000
<v Speaker 6>What are you using it for? Absolutely? So one.

0:37:26.000 --> 0:37:28.279
<v Speaker 16>I can't wait for you to try it. So we're

0:37:28.360 --> 0:37:30.799
<v Speaker 16>using it internally. Marcus certainly using it. I'm using it.

0:37:30.840 --> 0:37:32.960
<v Speaker 16>I'll give you a few examples of how I use it.

0:37:33.640 --> 0:37:36.600
<v Speaker 16>I used it recently. I just said, hey, go find

0:37:36.680 --> 0:37:39.319
<v Speaker 16>the most recent all hands deck that we're working on.

0:37:39.320 --> 0:37:40.960
<v Speaker 16>One of the things that we do is actually introduce

0:37:41.040 --> 0:37:43.520
<v Speaker 16>every single new hire every month, and I said, tell

0:37:43.520 --> 0:37:46.440
<v Speaker 16>me how to pronounce the names of all the new hires,

0:37:46.480 --> 0:37:49.360
<v Speaker 16>and that goes off and finds the presentation without me

0:37:49.440 --> 0:37:53.279
<v Speaker 16>saying reads the presentation figures out where the new hires are,

0:37:53.360 --> 0:37:56.000
<v Speaker 16>loops through all of them, and figures out their highest

0:37:56.000 --> 0:37:58.239
<v Speaker 16>probability nationality and tells me how to pronounce them. I

0:37:58.239 --> 0:37:59.600
<v Speaker 16>don't have to go bug people to figure that out.

0:37:59.640 --> 0:38:00.879
<v Speaker 16>It's awesome and it saves me time.

0:38:01.800 --> 0:38:02.760
<v Speaker 6>In the first instance.

0:38:02.800 --> 0:38:05.239
<v Speaker 2>It is underpinned by Anthropics Claude, Right, and you're going

0:38:05.280 --> 0:38:07.319
<v Speaker 2>to tell me, well, this is interim and we're going

0:38:07.360 --> 0:38:09.360
<v Speaker 2>to look at all kinds of different model options.

0:38:09.360 --> 0:38:10.320
<v Speaker 6>We're model agnostic.

0:38:10.680 --> 0:38:13.480
<v Speaker 2>But it is an interesting and the latest example of

0:38:13.520 --> 0:38:17.160
<v Speaker 2>how Claude helps people in the enterprise get to market quick.

0:38:17.400 --> 0:38:19.360
<v Speaker 6>You know what was your experience of that, rob.

0:38:20.160 --> 0:38:22.080
<v Speaker 16>The biggest thing for us was being able to take

0:38:22.120 --> 0:38:24.000
<v Speaker 16>an m pick it up and set it down in

0:38:24.040 --> 0:38:27.319
<v Speaker 16>our infrastructure in a way that our customer's data never

0:38:27.440 --> 0:38:30.080
<v Speaker 16>left our security boundary and wasn't used for the training

0:38:30.080 --> 0:38:32.279
<v Speaker 16>of the model. And that's what we got with Anthropic

0:38:32.400 --> 0:38:34.759
<v Speaker 16>and Claude. And on top of that, we've done a

0:38:34.760 --> 0:38:38.640
<v Speaker 16>bunch of sophisticated prompt and context engineering that makes slack

0:38:38.680 --> 0:38:42.560
<v Speaker 16>bot deeply personal and a deeply personal agent to every

0:38:42.600 --> 0:38:43.759
<v Speaker 16>single person that uses it.

0:38:44.360 --> 0:38:45.960
<v Speaker 4>Well, but how are you thinking about security?

0:38:47.480 --> 0:38:49.560
<v Speaker 16>Oh, I mean, it's a paramount for us. It's been

0:38:49.560 --> 0:38:52.239
<v Speaker 16>something that's been the very very top of our priorities

0:38:52.520 --> 0:38:55.880
<v Speaker 16>since the foundation of slack and so one slack bot

0:38:55.960 --> 0:38:58.800
<v Speaker 16>is a personal agent. It needs to be deeply trusted

0:38:58.880 --> 0:39:01.400
<v Speaker 16>by the user, but also trusted by the enterprise. And

0:39:01.440 --> 0:39:05.759
<v Speaker 16>so what we do is the user, the slack bot

0:39:05.840 --> 0:39:07.839
<v Speaker 16>is acting on behalf of the user, so it can

0:39:07.880 --> 0:39:10.840
<v Speaker 16>access the information that a user can their direct messages,

0:39:11.120 --> 0:39:14.240
<v Speaker 16>their private channels, and the public channels within a particular

0:39:14.280 --> 0:39:15.000
<v Speaker 16>slack instance.

0:39:15.080 --> 0:39:15.560
<v Speaker 6>And as I.

0:39:15.560 --> 0:39:19.200
<v Speaker 16>Mentioned before, from a company perspective, you can rest assured

0:39:19.239 --> 0:39:21.600
<v Speaker 16>that your data is not being used to train the model,

0:39:21.600 --> 0:39:24.040
<v Speaker 16>nor is it leaving the security boundary. So it's all

0:39:24.080 --> 0:39:27.360
<v Speaker 16>adhering to your existing security policies and slack this.

0:39:27.239 --> 0:39:29.840
<v Speaker 4>Is all about return on AI investment.

0:39:30.040 --> 0:39:32.600
<v Speaker 3>It's all about making it clear to me, to you,

0:39:32.760 --> 0:39:35.520
<v Speaker 3>to the users that the stuff saves you time makes

0:39:35.680 --> 0:39:36.240
<v Speaker 3>more productive.

0:39:36.400 --> 0:39:38.040
<v Speaker 4>How are you measuring that role.

0:39:39.360 --> 0:39:42.520
<v Speaker 16>We don't measure individual productivity, but we do measure the

0:39:42.640 --> 0:39:45.040
<v Speaker 16>usage of slack bots. So we measure the penetration, so

0:39:45.080 --> 0:39:47.440
<v Speaker 16>the number of users that actually use slack bot over

0:39:47.480 --> 0:39:49.319
<v Speaker 16>the number of users that have access to it, but

0:39:49.360 --> 0:39:52.400
<v Speaker 16>at week over week retention and then message intensity, and

0:39:52.400 --> 0:39:55.360
<v Speaker 16>that allows us to approximate the value that's being created,

0:39:55.600 --> 0:39:58.160
<v Speaker 16>and the week over week retention force slackbot is higher

0:39:58.200 --> 0:40:00.920
<v Speaker 16>than any other feature we've ever had, and slack and

0:40:00.960 --> 0:40:04.040
<v Speaker 16>the message intensity keeps growing, and to us, that's a

0:40:04.120 --> 0:40:07.400
<v Speaker 16>quantitative signal of qualitative value that's being derived from our

0:40:07.520 --> 0:40:10.680
<v Speaker 16>users for time savings, but also we're seeing through our

0:40:10.719 --> 0:40:14.240
<v Speaker 16>qualitative surveys people use this for brainstorming and creative pursuits

0:40:14.239 --> 0:40:15.440
<v Speaker 16>that we didn't even expect.

0:40:16.480 --> 0:40:19.640
<v Speaker 3>Rob Seman, Slack intro CEO, and great speaking with you

0:40:20.120 --> 0:40:20.919
<v Speaker 3>about slack bot.

0:40:21.040 --> 0:40:21.960
<v Speaker 4>We'll see how it catches on.

0:40:22.040 --> 0:40:24.399
<v Speaker 3>Meanwhile, let's take a look at shares of Spotify right

0:40:24.440 --> 0:40:27.759
<v Speaker 3>now and indeed over the start of the year well

0:40:27.800 --> 0:40:30.560
<v Speaker 3>off by nine percent. That's, of course, when the new

0:40:30.640 --> 0:40:35.640
<v Speaker 3>co CEOs have joined the company. Gusta Sworderstrom Alex Norstrom

0:40:35.880 --> 0:40:39.560
<v Speaker 3>took over as from the Spotify founder Daniel Eck. Now

0:40:39.560 --> 0:40:41.399
<v Speaker 3>they've both been out the business for a long time,

0:40:41.440 --> 0:40:42.840
<v Speaker 3>but Eck himself.

0:40:42.520 --> 0:40:45.120
<v Speaker 4>Grew the platform from money suck to.

0:40:45.040 --> 0:40:47.280
<v Speaker 3>One of the most powerful businesses in the music industry,

0:40:47.280 --> 0:40:50.120
<v Speaker 3>and the new CEOs have to steer that powerful ship

0:40:50.160 --> 0:40:54.880
<v Speaker 3>around some pretty tough headwinds AI angry creators, user fatigue

0:40:55.080 --> 0:40:57.479
<v Speaker 3>to turn around that share drop and most actually Commen

0:40:57.520 --> 0:40:59.760
<v Speaker 3>has been writing about all of this by the Audio

0:40:59.800 --> 0:41:01.160
<v Speaker 3>GI's leadership transition.

0:41:01.200 --> 0:41:05.000
<v Speaker 4>It's in BusinessWeek and there are a lot of headwinds.

0:41:05.000 --> 0:41:06.560
<v Speaker 4>What is front and center for them?

0:41:06.600 --> 0:41:11.000
<v Speaker 3>How are they're taking on the algos and the AI story.

0:41:10.880 --> 0:41:13.640
<v Speaker 17>They're coming up with a lot of different products that

0:41:13.680 --> 0:41:16.480
<v Speaker 17>they're hoping will kind of buy them some time and

0:41:16.520 --> 0:41:18.799
<v Speaker 17>also maybe address some of what users want to do. So,

0:41:18.840 --> 0:41:23.319
<v Speaker 17>for example, they're integrating Spotify into jack shipt. They've made

0:41:23.360 --> 0:41:25.400
<v Speaker 17>a partnership with Meta on its glasses.

0:41:25.840 --> 0:41:27.000
<v Speaker 4>They are letting you.

0:41:27.400 --> 0:41:30.600
<v Speaker 17>Enter prompts to get a playlist in return, using even

0:41:30.680 --> 0:41:34.400
<v Speaker 17>like online contexts so that you can get the top

0:41:34.760 --> 0:41:37.480
<v Speaker 17>rated albums of the year from Pitchfork or something like that.

0:41:37.640 --> 0:41:39.840
<v Speaker 17>So they really want to give people both this personalization,

0:41:40.040 --> 0:41:42.919
<v Speaker 17>more options showing up where people are. Podcasts are coming

0:41:42.960 --> 0:41:46.160
<v Speaker 17>to Netflix. They're really trying to meet people where they

0:41:46.200 --> 0:41:51.120
<v Speaker 17>are rather than forcing them to just come to Spotify.

0:41:51.160 --> 0:41:56.040
<v Speaker 2>YouTube not a new issue, but the biggest in front

0:41:56.080 --> 0:41:58.160
<v Speaker 2>of them. It seems like, you know, it's very detailed

0:41:58.160 --> 0:42:01.720
<v Speaker 2>in the BusinessWeek story. This competition for eyeballs and YouTube

0:42:01.800 --> 0:42:04.399
<v Speaker 2>is the thing on both of those CEO's deaths right

0:42:04.400 --> 0:42:05.279
<v Speaker 2>now Acshually.

0:42:05.680 --> 0:42:09.600
<v Speaker 17>Yes, YouTube, Spotify has moved into video. One of the

0:42:09.760 --> 0:42:12.920
<v Speaker 17>scoops from our story is that they're now actually focusing

0:42:12.960 --> 0:42:16.880
<v Speaker 17>on fitness content. So as a result of them pushing

0:42:16.920 --> 0:42:20.080
<v Speaker 17>into video podcasts, creators who we see on YouTube that

0:42:20.440 --> 0:42:23.680
<v Speaker 17>actually put out guided workouts have started uploading their content

0:42:23.719 --> 0:42:25.960
<v Speaker 17>to Spotify, and Spotify is seeing that.

0:42:25.920 --> 0:42:27.400
<v Speaker 4>People really enjoy that content.

0:42:27.480 --> 0:42:30.560
<v Speaker 17>So instead of just using playlists to soundtrack their runs,

0:42:30.719 --> 0:42:33.719
<v Speaker 17>they're actually watching yoga on Spotify, for example. So this

0:42:33.800 --> 0:42:35.920
<v Speaker 17>is an area they're pretty excited about and seemed to

0:42:35.920 --> 0:42:36.600
<v Speaker 17>be investing in.

0:42:37.520 --> 0:42:39.640
<v Speaker 4>We know a lot about Daniellek.

0:42:39.680 --> 0:42:42.120
<v Speaker 3>We've sort of grown up alongside him as he's taken

0:42:42.160 --> 0:42:44.960
<v Speaker 3>this European success story global.

0:42:45.520 --> 0:42:46.840
<v Speaker 4>What do we know about the co CEOs?

0:42:46.880 --> 0:42:49.720
<v Speaker 17>Who are they? Well, their descents, what are they about?

0:42:50.320 --> 0:42:53.839
<v Speaker 17>So both of them are Swedish. Alex is of half

0:42:53.920 --> 0:42:56.279
<v Speaker 17>Chinese half Swedish descent. His mother was a single mother,

0:42:56.400 --> 0:42:58.719
<v Speaker 17>Sharan a Chinese restaurant. Growing up, he's really kind of

0:42:58.719 --> 0:43:02.399
<v Speaker 17>the culture guy. He gets a playlist regularly that keeps

0:43:02.480 --> 0:43:04.520
<v Speaker 17>him on top of trends. It seems like he's really

0:43:04.520 --> 0:43:06.759
<v Speaker 17>sort of a social person who's doing all these partnership

0:43:06.760 --> 0:43:10.440
<v Speaker 17>deals with the labels and audiobooks and such. Gustave formerly

0:43:10.480 --> 0:43:13.400
<v Speaker 17>really focused on product now co CEO also Swedish. He

0:43:13.480 --> 0:43:15.799
<v Speaker 17>sold a startup to Yahoo back in two thousand and six.

0:43:16.160 --> 0:43:18.319
<v Speaker 17>He did a stint in the Swedish military, and he's

0:43:18.400 --> 0:43:21.280
<v Speaker 17>really tech philosophy focused.

0:43:21.520 --> 0:43:23.280
<v Speaker 4>He was really excited about a book.

0:43:23.040 --> 0:43:25.960
<v Speaker 17>He read from the inventor of quantum computing, so he

0:43:26.000 --> 0:43:26.640
<v Speaker 17>really gets.

0:43:26.480 --> 0:43:27.040
<v Speaker 4>Deep on that.

0:43:27.080 --> 0:43:29.360
<v Speaker 17>And supposedly the two of them together are really like

0:43:29.400 --> 0:43:30.080
<v Speaker 17>a yin and yang.

0:43:30.120 --> 0:43:30.920
<v Speaker 4>They go well together.

0:43:31.440 --> 0:43:35.680
<v Speaker 17>A fun tidbit, Nordstrom means north stream, Soderstrom means south stream,

0:43:36.600 --> 0:43:38.880
<v Speaker 17>so it's written at the universe.

0:43:38.920 --> 0:43:40.000
<v Speaker 4>I guess.

0:43:41.120 --> 0:43:44.120
<v Speaker 2>This really is a must read on Bloomberg online or

0:43:44.120 --> 0:43:46.719
<v Speaker 2>in a magazine coming to you very soon in BusinessWeek.

0:43:46.719 --> 0:43:49.160
<v Speaker 2>Bloomberg's actually come and with the deep dive in Spotify.

0:43:49.200 --> 0:43:51.560
<v Speaker 2>Thank you very much, Caro. That does it for another

0:43:51.719 --> 0:43:55.640
<v Speaker 2>edition of Bloomberg. Tech markets still continuing to start the

0:43:55.719 --> 0:43:56.640
<v Speaker 2>year pretty.

0:43:56.320 --> 0:43:58.000
<v Speaker 4>Hot, pretty hot.

0:43:58.040 --> 0:43:59.799
<v Speaker 3>Well, we're under pressure if you're not a big tech

0:44:00.000 --> 0:44:02.040
<v Speaker 3>they're hot if you're looking at commodities. And that too

0:44:02.200 --> 0:44:04.040
<v Speaker 3>is an AI story. I mean, the joke of twenty

0:44:04.080 --> 0:44:06.879
<v Speaker 3>twenty two and onwards. Everything's an AI story, don't forget

0:44:06.880 --> 0:44:07.879
<v Speaker 3>to check out or all of them.

0:44:07.760 --> 0:44:08.480
<v Speaker 4>On our podcast.

0:44:08.760 --> 0:44:10.560
<v Speaker 3>Find on The Terminal, as well as online on Apple,

0:44:10.920 --> 0:44:13.480
<v Speaker 3>on Spotify, and on iHeart as a Bloomberg