WEBVTT - Apple Picks Gemini to Run AI-Powered Siri

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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 San Francisco.

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<v Speaker 2>This is Bloomberg Tech coming up in video. Plans to

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<v Speaker 2>invest one billion dollars over five years in a new

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<v Speaker 2>lab with Eli Lilly to speed up the use of

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<v Speaker 2>AI in the pharmaceutical industry.

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<v Speaker 3>Plus paramount sues Warner Brothers Discovery, and plans to nominate

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<v Speaker 3>directors to the board as it's increasingly hostile. Takeover bid

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<v Speaker 3>takes aim to upset Netflix.

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<v Speaker 2>An alphabet breaches four trillion dollars in market value. This

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<v Speaker 2>is CNBC reports Apple has picked Gemini to power Siri

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<v Speaker 2>this year, and.

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<v Speaker 3>Then those moves fall again, and really we've got anxiety

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<v Speaker 3>across the market's more broadly aired digging into the market

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<v Speaker 3>implications of what seems to be a dialing up.

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<v Speaker 4>In the administration's fight with a FED.

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<v Speaker 3>That is what the market tries to digest and why

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<v Speaker 3>we see a bit of a sell America theme at

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<v Speaker 3>the moment. Yes, they're small moves in terms of benchmarks

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<v Speaker 3>for stocks were down by a tenth of a percent

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<v Speaker 3>on anastat one hundred, but we're seeing bigger moves when

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<v Speaker 3>you're looking what's happening in the bomb market. In the dollar,

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<v Speaker 3>for example, we're seeing thirty year years once again, pushing

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<v Speaker 3>up two basis points, seeing the dollar on the downside.

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<v Speaker 3>All of this as we try and bake in the

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<v Speaker 3>macro implications. We look to CPI tomorrow, but you're looking

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<v Speaker 3>at what's underneath the hood right now.

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<v Speaker 2>Yeah, the big breaking news of the last hour is

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<v Speaker 2>that Apple has selected Google's Gemini model to power serri

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<v Speaker 2>this year. Reporting from CNBC citing an Apple's statement, and

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<v Speaker 2>you can see a big reaction in the stock the

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<v Speaker 2>moment the headlines hit, it has faded.

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<v Speaker 5>I'll take you back to.

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<v Speaker 2>November when Bloomberg's Mark German reported that a deal was

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<v Speaker 2>very close, that Apple would pay Google one billion dollars

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<v Speaker 2>per year and that this was just an interim until

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<v Speaker 2>Apple could get its own foundation models together, but or

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<v Speaker 2>continue to track that story. Another interesting trends action in

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<v Speaker 2>the market this morning Nvidia co investing one billion dollars

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<v Speaker 2>with Eli Lilly into a Silicon Valley based lab split

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<v Speaker 2>over five years. AI Pharmaceuticals for the details are interesting here,

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<v Speaker 2>Cara and we.

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<v Speaker 3>Want to get those details, and we can do exactly

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<v Speaker 3>that with Katie Greifeld, which is over at the JP

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<v Speaker 3>Morgan Healthcare Conference, indeed looking at Silicon Valley, getting ever

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<v Speaker 3>closer to the world of health.

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<v Speaker 4>Katie, what'd you make of this deal?

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<v Speaker 6>Yeah, this was a really interesting headline to wake up to,

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<v Speaker 6>especially when you remember that Eli Lilly partnered with Nvivia

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<v Speaker 6>back in October to develop an AI supercomputer. So the

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<v Speaker 6>details on this specific deals as you guys run through them.

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<v Speaker 6>One billion dollars OVERFI fears to build a facility in

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<v Speaker 6>Silicon Valley, basically a new lab. We don't have much

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<v Speaker 6>details when it comes to the terms beyond that, but

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<v Speaker 6>both companies have described this as a joint investment. And

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<v Speaker 6>I just actually spoke to the CFO of Eli Lilly,

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<v Speaker 6>Lucas Montarge, about what the ultimate vision is here when

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<v Speaker 6>it comes to AI and healthcare and this specific partnership,

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<v Speaker 6>and he said, this is really about drug discovery. It's

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<v Speaker 6>still early days, of course, they haven't built the facility yet,

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<v Speaker 6>but the hope is that this will help basically in

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<v Speaker 6>discovering drugs to really target and treat those really hard

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<v Speaker 6>to treat diseases. Think gene therapy for example. So again

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<v Speaker 6>early days, but some big ambitions.

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<v Speaker 2>Here Bloomber's Katie Greefelk just down the road at the

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<v Speaker 2>JP Morgan Healthcare conference all day long here in San Francisco,

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<v Speaker 2>less than two weeks into the new year, and in

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<v Speaker 2>Video is already dominating the news flow. I want to

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<v Speaker 2>get to Denny Fish, portfolio manager on the Global Technology

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<v Speaker 2>an innovation team at Janis Henderson and the Frank Reality visit.

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<v Speaker 2>In video is the top holding across a number of

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<v Speaker 2>funds that you manage. What do you make of that

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<v Speaker 2>relationship between in video and ELI.

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<v Speaker 7>Yeah, well it actually it makes a ton of sense

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<v Speaker 7>to me.

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<v Speaker 8>I mean, if we think about what's grabbed all the

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<v Speaker 8>attention over the last three years since the chat ChiPT moment,

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<v Speaker 8>it's effectively been the idea of the digital manifestation of AI.

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<v Speaker 8>But the reality is, if we think about the profoundness

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<v Speaker 8>of how this will impact the economy over time and

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<v Speaker 8>society more broadly, the physical manifestation of AI is as big,

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<v Speaker 8>if not a bigger opportunity. And if you think about

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<v Speaker 8>drug discovery and what that means for society, and then

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<v Speaker 8>just think about how far we've come with autonomous driving,

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<v Speaker 8>where we're going with robotics. They are all these different

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<v Speaker 8>verticals where it makes a lot of sense for Nvidia

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<v Speaker 8>to be leaning into. And frankly, in Vidia has got

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<v Speaker 8>some of the most the best talent in the world

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<v Speaker 8>and to see these partnerships with market leaders makes a

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<v Speaker 8>ton of sense.

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<v Speaker 7>And you know, I bring it back.

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<v Speaker 8>Sometimes you get this argument of circularity, but the reality is,

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<v Speaker 8>if you're Jensen and you have a firm belief at

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<v Speaker 8>just how big these market opportunities are, you should be

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<v Speaker 8>leaning and hard to this intment co investments into labs

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<v Speaker 8>like they're doing with Lily, or direct investments into companies

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<v Speaker 8>like they're potentially doing with Open AI.

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<v Speaker 2>We a let's one of miss driving. A lot of

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<v Speaker 2>people get it. I wrote about it extensively this weekend.

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<v Speaker 2>We're going to talk about it later in the program.

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<v Speaker 2>The go to market in the first instance is for

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<v Speaker 2>Mercedes that we use hardware and software. But with pharmaceuticals

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<v Speaker 2>drug discovery research, what is the go to market that

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<v Speaker 2>then video is going to pull off in the future.

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<v Speaker 7>Well to the so so far.

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<v Speaker 8>If we think about pharmaceuticals, where we've seen the early

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<v Speaker 8>benefits of AI have been in things like the clinical process,

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<v Speaker 8>you know, getting drugs that have already been discovered through

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<v Speaker 8>that process, internal efficiencies, marketing, things like that. The real,

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<v Speaker 8>you know, the big prize out there is drug discovery.

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<v Speaker 8>It's finding solutions to problems that we just couldn't get

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<v Speaker 8>there without AI or would have taken much much longer.

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<v Speaker 8>So the go to market is actually direct partnerships with

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<v Speaker 8>these companies to fast forward the discovery process.

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<v Speaker 4>Denny.

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<v Speaker 3>That speaks to the broadening out that we're starting to

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<v Speaker 3>see the market. We're also going to talk about that

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<v Speaker 3>the fact that we are seeing the S and P

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<v Speaker 3>five hundred actually doing a bit of a challenge in

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<v Speaker 3>terms of returns versus some of the mags seven names.

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<v Speaker 3>How much does it mean that we've already juiced the

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<v Speaker 3>valuation side of the equation for in video or is

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<v Speaker 3>AI infrastructure still going to be the key watchword for twenty.

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<v Speaker 8>Six Well, so far, all the data points would suggest

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<v Speaker 8>that the investments into AI infrastructure are going to continue

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<v Speaker 8>to be quite robust, and we would fully expect that,

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<v Speaker 8>and you know, and so far, you know, I just

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<v Speaker 8>looking back, you know, I mean Ed was talking about

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<v Speaker 8>alphabet earlier in the relationship with Apple. Just watching the

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<v Speaker 8>leap frogging effects you know with you know, open Ai

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<v Speaker 8>and Xai and Gemini, that's very healthy and as long

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<v Speaker 8>as we continue to see that. And then bringing back

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<v Speaker 8>to you know, in Vidia and VideA now is you

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<v Speaker 8>know they announced last week Ruben is fully in production

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<v Speaker 8>that is going to have materi aerial impacts as it

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<v Speaker 8>relates to inference. Productivity versus training and inference is the

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<v Speaker 8>next big handoff. And so if you're a believer that

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<v Speaker 8>we are now in this period where we're going to

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<v Speaker 8>start seeing increasing deployment of these applications, inference is going

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<v Speaker 8>to go through the roof and as a result, that's

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<v Speaker 8>going to continue to sustain the investment profile.

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<v Speaker 7>So we expected to be pretty healthy.

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<v Speaker 8>Now, I will say when you're talking about the broader

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<v Speaker 8>SMP five hundred, I mean one of the thesis that

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<v Speaker 8>we've had for the last three years as AI has

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<v Speaker 8>really started to take hold, is this is going to

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<v Speaker 8>be very impactful across all industries. And if you believe that,

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<v Speaker 8>and the companies that are able to get revenue lift

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<v Speaker 8>because of deployment of AI, but then at the same

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<v Speaker 8>time are able to drive cost efficiencies that should be

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<v Speaker 8>pretty good for multiples. So I'm not surprised to see

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<v Speaker 8>the market, you know, sort of anticipating of sorts, some

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<v Speaker 8>of the benefits we might get from AI.

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<v Speaker 3>The market's all allo got more discerning on who has

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<v Speaker 3>to pay for the AI of structure and what that

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<v Speaker 3>costs in terms of debt. Denny, I'm looking at again

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<v Speaker 3>yet another number, three trillion dollars, this time coming from

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<v Speaker 3>Moody saying how much the data center infrastructure build out

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<v Speaker 3>is going to cost up until twenty thirty. I mean,

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<v Speaker 3>McKinsey had already put seven trillion dollars on that number.

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<v Speaker 3>But is there a worry as to who has to

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<v Speaker 3>actually pay for it?

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<v Speaker 7>Denny, Well, of course there is.

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<v Speaker 8>You know, the good news is the majority of this

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<v Speaker 8>is being funded by the hyperscalers, and they generate the

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<v Speaker 8>free cash flows to actually be able to fulfill the

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<v Speaker 8>commitments that they've made. And they're all playing the twenty

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<v Speaker 8>year game. I mean, we've just seen that with you know,

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<v Speaker 8>the number of you know, power agreements they're being struck

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<v Speaker 8>between you know, Meta and Google, Microsoft and others, and

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<v Speaker 8>so we feel pretty good there now. Now clearly, you know,

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<v Speaker 8>the debt markets are going to have to remain healthy.

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<v Speaker 7>We're going to have to continue to see a.

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<v Speaker 8>Progress as it relates to you know, you know the

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<v Speaker 8>ambitions of these companies, but there's also something else too.

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<v Speaker 8>You know, when you look those numbers, there's also a

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<v Speaker 8>lot of double counting in it. You really have to

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<v Speaker 8>parse it back to get to the real meat of

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<v Speaker 8>what's necessary. And then you know, also there are natural

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<v Speaker 8>governors at just how fast this can get deployed. So

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<v Speaker 8>the deployment of the capital is going to be pretty measured.

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<v Speaker 8>And that's what makes this very different than say the

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<v Speaker 8>dot com era, where so much capital came into areas

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<v Speaker 8>like telecom infrastructure so fast and it was very easy

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<v Speaker 8>to get that stuff deployed.

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<v Speaker 7>This is hard.

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<v Speaker 8>You look at what's going on at Stargate and Abilene,

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<v Speaker 8>Texas and trying to put up ten gigawatts, the labor

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<v Speaker 8>that's needed, the power, just the expertise, and you know,

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<v Speaker 8>it's a heavy lift, and so that it'selfs a natural

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<v Speaker 8>governor on just how fast it can get deployed.

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<v Speaker 2>This is what we were trying to pass at CES

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<v Speaker 2>last week. The baseline assumption very quickly, Denny, is that

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<v Speaker 2>demand still outstrips in video and AMD's ability to supply.

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<v Speaker 2>How does that set us up for this year?

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<v Speaker 8>Well, that's good for infrastructure, you know, because you're in

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<v Speaker 8>a situation like that, and even a TSMC for example,

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<v Speaker 8>we're second topic.

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<v Speaker 7>Yeah, yeah, where you.

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<v Speaker 8>Know, you only have so much capacity and you can

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<v Speaker 8>only bring up incremental founderies so quickly, and so as

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<v Speaker 8>a result, that's really good from a pricing standpoint, particularly

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<v Speaker 8>when you're the only game in town, and for certain

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<v Speaker 8>aspects Nvidia is still the only game in town too.

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<v Speaker 3>Denny Fish Janis Henderson Investors. Great to have you on

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<v Speaker 3>all the games we are coming up. Paramount in ram

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<v Speaker 3>sub efforts to caught a plan merger between Warner Brothers

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<v Speaker 3>Discovery and Netflix.

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<v Speaker 4>The latest in the media merger saga. That's next. There's

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<v Speaker 4>a bloom Beg Tech Paramounts guidance.

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<v Speaker 3>Well, it says it plans to nominate directors to Warner

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<v Speaker 3>Brothers Discoveries board to vote against the approval of a

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<v Speaker 3>merger with Netflix, of course, and the company has filed

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<v Speaker 3>a suit to force Warner Brothers to disclose information about

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<v Speaker 3>the proposed Netflix Warner Brothers tie ups entertained a reporter

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<v Speaker 3>Pholix Jillette joins us on what is an ever more

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<v Speaker 3>hostile potential takeover?

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<v Speaker 4>So suing for more information? What do they want to

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<v Speaker 4>really demonstrate to invest us here?

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<v Speaker 9>I mean, at this point, you know, they're choosing to

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<v Speaker 9>raise the hostility versus raising their bit Yes, and I

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<v Speaker 9>think you know they've been campaigning shareholders join our tender offer.

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<v Speaker 9>You know, they've said for weeks now our offer was

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<v Speaker 9>better than the Netflix offer, accusing you know, the Warner

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<v Speaker 9>Brothers board of not being transparent during the proceedings. And

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<v Speaker 9>now they're making this move to essentially say, you know,

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<v Speaker 9>you have to provide the information to shareholders so they

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<v Speaker 9>can judge which is a better offer. And to do that,

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<v Speaker 9>you know, the big most contentious issue for months now

0:11:42.760 --> 0:11:46.520
<v Speaker 9>has been how do you value the cable assets that

0:11:46.559 --> 0:11:49.320
<v Speaker 9>Warner Brothers has planned to spin off? Prior to selling

0:11:49.760 --> 0:11:52.800
<v Speaker 9>the studios and the streaming business to Netflix.

0:11:52.960 --> 0:11:55.240
<v Speaker 2>The Netflix offered twenty seven dollars a share for the

0:11:55.280 --> 0:11:59.120
<v Speaker 2>studios and streaming spin off the cable networks paramount thirty

0:11:59.160 --> 0:12:01.839
<v Speaker 2>dollars a share all of it, but basically assigning a

0:12:01.920 --> 0:12:05.800
<v Speaker 2>value to the networks of zero dollars. This is a saga.

0:12:05.880 --> 0:12:08.560
<v Speaker 2>It will play out over time. It's a really difficult

0:12:08.640 --> 0:12:11.880
<v Speaker 2>question for you as editor, hear Felix, But like what

0:12:11.960 --> 0:12:15.559
<v Speaker 2>happens next? Is there a real chance that Paramount can

0:12:15.640 --> 0:12:19.160
<v Speaker 2>force a hostile takeover through this mechanism.

0:12:19.000 --> 0:12:19.839
<v Speaker 10>They're going to try?

0:12:20.280 --> 0:12:20.520
<v Speaker 7>You know?

0:12:20.679 --> 0:12:23.199
<v Speaker 9>I mean I think, like you know, the shareholders at

0:12:23.200 --> 0:12:24.839
<v Speaker 9>this point, a lot of them seem to be sitting

0:12:24.880 --> 0:12:27.520
<v Speaker 9>on the fence, you know, in terms of who they're

0:12:27.520 --> 0:12:30.000
<v Speaker 9>going to support. I think a lot of them are

0:12:30.040 --> 0:12:32.960
<v Speaker 9>hoping that Paramount would come in with a higher bid,

0:12:33.080 --> 0:12:35.840
<v Speaker 9>go over the thirty dollars to share. That hasn't happened yet,

0:12:36.920 --> 0:12:41.040
<v Speaker 9>you know, I think again, you know, David Ellison and

0:12:41.120 --> 0:12:44.319
<v Speaker 9>Paramount have been trying to advocate for this notion that

0:12:44.400 --> 0:12:46.960
<v Speaker 9>like the Netflix deal isn't even going to happen. They

0:12:46.960 --> 0:12:50.960
<v Speaker 9>have too many regulatory issues, you know, putting aside the

0:12:51.000 --> 0:12:53.760
<v Speaker 9>fact that if Paramount offer was except that they'd have

0:12:53.840 --> 0:12:58.040
<v Speaker 9>their own issues in Europe with the States. So yeah,

0:12:58.120 --> 0:13:01.360
<v Speaker 9>I mean, this continues to just get more and more hostile,

0:13:01.920 --> 0:13:05.160
<v Speaker 9>and this is you know, the next step is this

0:13:05.240 --> 0:13:08.400
<v Speaker 9>lawsuit and a proxy fight over the director's.

0:13:08.760 --> 0:13:11.360
<v Speaker 2>Bloomberg's Feenix to that, thank you very much. Another top

0:13:11.400 --> 0:13:15.240
<v Speaker 2>story deep seek founder liangwen Feng's hedge fund surge more

0:13:15.280 --> 0:13:18.120
<v Speaker 2>than fifty percent last year, making it the second best

0:13:18.120 --> 0:13:20.400
<v Speaker 2>performer among China quant funds.

0:13:20.640 --> 0:13:21.960
<v Speaker 5>The strong performance.

0:13:21.480 --> 0:13:24.360
<v Speaker 2>Helped boost the cash available for deep seek itself. Let's

0:13:24.360 --> 0:13:28.200
<v Speaker 2>get out to Bloomberg Tech executive editor Peter Elstrom. You know, two,

0:13:28.280 --> 0:13:30.920
<v Speaker 2>there's the Bloomberg story, right, which is about a quant

0:13:30.920 --> 0:13:34.600
<v Speaker 2>funds you know, amazing performance. But in the reporting it's

0:13:34.600 --> 0:13:37.600
<v Speaker 2>super clear the read through that people are making is

0:13:37.640 --> 0:13:40.640
<v Speaker 2>that that the returns on that the earnings from that

0:13:40.679 --> 0:13:43.600
<v Speaker 2>fund's performance can be taken by deep Seak's founder and

0:13:43.760 --> 0:13:45.880
<v Speaker 2>used to give deep seek a bigger budget for research

0:13:45.920 --> 0:13:47.400
<v Speaker 2>and deploying its models.

0:13:48.520 --> 0:13:50.960
<v Speaker 11>Right right, That's exactly true. Yeah, there, So there's a

0:13:50.960 --> 0:13:53.160
<v Speaker 11>finance story here, but there's also a tech story, and

0:13:53.160 --> 0:13:56.600
<v Speaker 11>the finance story is very impressive. The hedge fund high Fire,

0:13:56.679 --> 0:13:58.840
<v Speaker 11>that was really the place where deep seek was born,

0:13:59.160 --> 0:14:01.800
<v Speaker 11>had a great year. Returns were fifty seven percent on

0:14:01.880 --> 0:14:05.400
<v Speaker 11>average across their various funds. That is very good for

0:14:05.640 --> 0:14:08.679
<v Speaker 11>the founder early on one thing, as you mentioned, it's

0:14:08.720 --> 0:14:11.319
<v Speaker 11>good performance compared with the other quant funds out there,

0:14:11.360 --> 0:14:14.400
<v Speaker 11>but it also gives him a much bigger checkbook to

0:14:14.440 --> 0:14:16.600
<v Speaker 11>be able to go out there and make new investments

0:14:16.640 --> 0:14:18.000
<v Speaker 11>now that probably.

0:14:17.559 --> 0:14:19.680
<v Speaker 7>Would be in Deep Seek. Deep Seek has.

0:14:19.520 --> 0:14:22.600
<v Speaker 11>Gained a lot of momentum since a year ago when

0:14:22.600 --> 0:14:25.200
<v Speaker 11>they had their big breakthrough dropped the bombshell that they

0:14:25.240 --> 0:14:27.880
<v Speaker 11>had invented this LLM for a fraction of the cost

0:14:27.960 --> 0:14:31.400
<v Speaker 11>of Opening Eyes with very similar performance. So now you

0:14:31.400 --> 0:14:34.480
<v Speaker 11>could see the founder invest more money into Deep Seek,

0:14:34.800 --> 0:14:37.960
<v Speaker 11>perhaps chase after a little bit of the capital intensive

0:14:37.960 --> 0:14:40.440
<v Speaker 11>projects that we've seen in the US in particular, we

0:14:40.520 --> 0:14:42.960
<v Speaker 11>haven't seen those kind of investments in China so far,

0:14:43.400 --> 0:14:46.040
<v Speaker 11>or he could invest in other kinds of AI initiatives

0:14:46.040 --> 0:14:48.640
<v Speaker 11>that may not be directly the same as Deep Seek.

0:14:48.640 --> 0:14:50.920
<v Speaker 3>Because the whole claim about Deep Sek has it only

0:14:50.920 --> 0:14:53.000
<v Speaker 3>cost them six million dollars, And the theory in this

0:14:53.080 --> 0:14:55.920
<v Speaker 3>particular reporting is that maybe they're getting revenues of some

0:14:56.000 --> 0:14:58.960
<v Speaker 3>seven hundred million dollars That could go a long way

0:14:59.080 --> 0:15:01.920
<v Speaker 3>if you're thinking about the costs of doing the business here.

0:15:02.160 --> 0:15:05.680
<v Speaker 3>But talk to us about why they're able to outperform

0:15:05.760 --> 0:15:07.880
<v Speaker 3>so much. What is it they're betting on? How these

0:15:07.960 --> 0:15:10.560
<v Speaker 3>quant funds managing to be so superior.

0:15:11.680 --> 0:15:14.720
<v Speaker 11>Well, partly with Deep Seek early on. They were able

0:15:14.760 --> 0:15:16.800
<v Speaker 11>to do this because there were a lot of constraints

0:15:16.840 --> 0:15:20.560
<v Speaker 11>around the AI initiatives in particular, and we've written a

0:15:20.600 --> 0:15:23.160
<v Speaker 11>fair bit about High Flyer in the past. They have

0:15:23.280 --> 0:15:27.160
<v Speaker 11>these quantitative techniques to be able to outstrip their peers

0:15:27.200 --> 0:15:29.320
<v Speaker 11>within the China market. They were the number two fund

0:15:29.320 --> 0:15:31.720
<v Speaker 11>as you mentioned. Also, the China market has been on fire.

0:15:31.800 --> 0:15:34.080
<v Speaker 11>There have been a lot of investments in other kinds

0:15:34.080 --> 0:15:36.520
<v Speaker 11>of AI models. Deep Seak hasn't gone public yet, but

0:15:36.840 --> 0:15:39.200
<v Speaker 11>two of the other AI models within the country have

0:15:39.320 --> 0:15:41.640
<v Speaker 11>gone public, giving them a lot of momentum here. So

0:15:41.680 --> 0:15:43.640
<v Speaker 11>the market's been very strong. They've been able to take

0:15:43.640 --> 0:15:45.800
<v Speaker 11>advantage of that. But again, as you say, they now

0:15:45.840 --> 0:15:47.760
<v Speaker 11>have one hundred times as much money as they used

0:15:47.800 --> 0:15:50.160
<v Speaker 11>to start up Deep Seek in the early days. What

0:15:50.200 --> 0:15:51.640
<v Speaker 11>are they going to do with that money? How are

0:15:51.640 --> 0:15:53.560
<v Speaker 11>they going to invest it? They're not talking about this

0:15:53.560 --> 0:15:55.760
<v Speaker 11>publicly of course at this point, but we would expect

0:15:55.760 --> 0:15:58.160
<v Speaker 11>more things to come from High Flyer and Deep Seek

0:15:58.200 --> 0:15:58.720
<v Speaker 11>in the future.

0:15:58.960 --> 0:16:00.960
<v Speaker 3>I mean, just think many Max went public on Friday.

0:16:00.960 --> 0:16:02.640
<v Speaker 3>It was a ut one hundred percent. It's up fifteen

0:16:02.640 --> 0:16:05.280
<v Speaker 3>percent again today. Peter Elstrom on all things Asia. We

0:16:05.320 --> 0:16:08.440
<v Speaker 3>so appreciate it, thank you. Coming up a bit more

0:16:08.440 --> 0:16:11.640
<v Speaker 3>on Asia. Could Chinese evs actually dodge tariffs in the EU.

0:16:11.840 --> 0:16:14.520
<v Speaker 3>We're going to discuss the global electric vehicle wars the

0:16:14.600 --> 0:16:18.360
<v Speaker 3>Stephanie Valdez Street from Cox of Automotive that's next as.

0:16:18.200 --> 0:16:18.920
<v Speaker 4>A BlueBag tech.

0:16:26.280 --> 0:16:29.920
<v Speaker 3>The European Union is weighing minimum prices for evs exported

0:16:29.960 --> 0:16:31.840
<v Speaker 3>to the block from China that actually.

0:16:31.640 --> 0:16:33.280
<v Speaker 4>Would replace steep tariffs.

0:16:33.640 --> 0:16:35.600
<v Speaker 3>Is it a sign that we've got some easy trade

0:16:35.640 --> 0:16:38.520
<v Speaker 3>tensions even as the US presses Europe to.

0:16:38.440 --> 0:16:39.200
<v Speaker 4>Take it off line?

0:16:39.200 --> 0:16:42.160
<v Speaker 3>On Beijing here to discuss this is Stephanie Valdez Street,

0:16:42.600 --> 0:16:45.320
<v Speaker 3>director of Industry Insights for Cox Automotive. That was sort

0:16:45.320 --> 0:16:48.240
<v Speaker 3>of the latest news headline that we get that maybe

0:16:48.280 --> 0:16:50.520
<v Speaker 3>BYD will be able to sell into Europe and not

0:16:50.560 --> 0:16:53.080
<v Speaker 3>have to have huge tarifts that eats its margin. Are

0:16:53.120 --> 0:16:55.440
<v Speaker 3>we going to see them able to tackle the European

0:16:55.480 --> 0:16:56.840
<v Speaker 3>market and continue to scale.

0:16:58.200 --> 0:17:01.440
<v Speaker 12>Yeah, you know, we look at the electric vehicle market, right,

0:17:01.560 --> 0:17:04.560
<v Speaker 12>China definitely is dominating and you think about their strategy

0:17:04.720 --> 0:17:08.800
<v Speaker 12>is to export, Right, They've exported millions of vehicles and

0:17:08.880 --> 0:17:11.439
<v Speaker 12>they've had a lot of luck in increasing share and

0:17:11.480 --> 0:17:15.000
<v Speaker 12>so the UK, it's basically, you know, it's a compromise, right,

0:17:15.119 --> 0:17:19.840
<v Speaker 12>the EU, Europe needs to meet those climate goals, right,

0:17:19.880 --> 0:17:24.000
<v Speaker 12>they need to increase their EV adoption. They rely on

0:17:24.119 --> 0:17:27.159
<v Speaker 12>China for minerals, right, batteries. So I think it's a

0:17:27.200 --> 0:17:31.320
<v Speaker 12>good compromise, and I think China will continue to increase

0:17:31.359 --> 0:17:33.800
<v Speaker 12>their share in those markets, not only UK, but some

0:17:33.840 --> 0:17:35.359
<v Speaker 12>of the emerging markets as well.

0:17:35.600 --> 0:17:38.399
<v Speaker 3>Meanwhile, one of the biggest feedback I often get with

0:17:38.440 --> 0:17:42.040
<v Speaker 3>my social is about the lack of BYD or Chinese

0:17:42.080 --> 0:17:43.680
<v Speaker 3>offerings here in the United States.

0:17:43.840 --> 0:17:44.960
<v Speaker 4>Is that ever going to come.

0:17:44.880 --> 0:17:46.560
<v Speaker 3>To bat or they're just forever going to be shut

0:17:46.600 --> 0:17:49.879
<v Speaker 3>out because it's really bets on TESLA and also pushing

0:17:49.880 --> 0:17:51.399
<v Speaker 3>away against evs more broadly.

0:17:52.520 --> 0:17:54.200
<v Speaker 12>Yeah, you know, I think if you look at the US,

0:17:54.280 --> 0:17:56.760
<v Speaker 12>that's one thing I think both political parties can agree

0:17:56.800 --> 0:17:58.960
<v Speaker 12>on is to keep China out. And so I think

0:17:59.000 --> 0:18:01.400
<v Speaker 12>that's kind of where we're at now. Out in the future,

0:18:01.520 --> 0:18:03.760
<v Speaker 12>you know, maybe we could see something that similar happened

0:18:03.760 --> 0:18:06.560
<v Speaker 12>to the Japanese and the Koreans. They come, they build

0:18:06.600 --> 0:18:09.920
<v Speaker 12>a partner and they build manufacturing plants. But for now

0:18:10.000 --> 0:18:12.400
<v Speaker 12>the near term, we're not going to have those other

0:18:12.440 --> 0:18:14.720
<v Speaker 12>than the ones that we already have under Geele, which

0:18:14.760 --> 0:18:17.720
<v Speaker 12>is the Vulgo and pole Star. But definitely, I think

0:18:18.280 --> 0:18:21.840
<v Speaker 12>consumers are seeing evs when they travel abroad and getting

0:18:21.920 --> 0:18:25.400
<v Speaker 12>the experience of writing in a Chinese ozem and discovering

0:18:25.440 --> 0:18:29.200
<v Speaker 12>how good quality high tech, and so I think that

0:18:29.240 --> 0:18:31.320
<v Speaker 12>it would resonate with US consumers at the right.

0:18:31.200 --> 0:18:32.840
<v Speaker 5>Price, Stephanie.

0:18:32.920 --> 0:18:36.720
<v Speaker 2>Last week at CS Nvidia outlined a full stack hardware

0:18:36.800 --> 0:18:40.320
<v Speaker 2>software solution for autonomous driving, and it very quickly raised

0:18:40.400 --> 0:18:41.359
<v Speaker 2>questions about Tesla.

0:18:41.840 --> 0:18:43.919
<v Speaker 5>So I asked Jensen Wong about it. Listen to this.

0:18:44.680 --> 0:18:47.640
<v Speaker 13>I think the Tesla stack is the most advanced AV

0:18:47.760 --> 0:18:52.360
<v Speaker 13>stack in the world, and I think the Tesla AV

0:18:52.480 --> 0:18:55.680
<v Speaker 13>operations is the most advanced in the world, and I'm

0:18:56.440 --> 0:19:02.000
<v Speaker 13>I'm fairly certain that they were already using them to

0:19:02.160 --> 0:19:02.800
<v Speaker 13>end AI.

0:19:04.040 --> 0:19:04.720
<v Speaker 5>So here's the thing.

0:19:05.000 --> 0:19:08.440
<v Speaker 2>Mercedes will ship a vehicle this quarter capable of point

0:19:08.480 --> 0:19:12.520
<v Speaker 2>to point hands free using in video technology. Does Tesla

0:19:12.600 --> 0:19:15.080
<v Speaker 2>finally have something real in the market to worry about?

0:19:16.320 --> 0:19:17.040
<v Speaker 7>I think they do.

0:19:17.119 --> 0:19:19.520
<v Speaker 12>You think about some of the even Rivian's another player,

0:19:19.600 --> 0:19:21.880
<v Speaker 12>right that they at their aidea they announce their plan.

0:19:22.000 --> 0:19:24.639
<v Speaker 12>I think definitely there's a lot of competition, and I

0:19:24.640 --> 0:19:27.439
<v Speaker 12>still think, you know, we're making some tremendous progress, but

0:19:27.480 --> 0:19:31.400
<v Speaker 12>I think one of the challenges continues to be regulation safety.

0:19:31.440 --> 0:19:34.920
<v Speaker 12>But I think in a video announcement with that technology

0:19:34.960 --> 0:19:38.480
<v Speaker 12>to really identify those edge cases which will help with

0:19:38.680 --> 0:19:43.360
<v Speaker 12>regulations more credibility. So definitely Tesla has some challenges out

0:19:43.359 --> 0:19:43.920
<v Speaker 12>there for sure.

0:19:44.600 --> 0:19:46.359
<v Speaker 2>The reason I find it fascinating is that if you

0:19:46.400 --> 0:19:48.480
<v Speaker 2>are a Tesla owner, you know, you know all about

0:19:48.480 --> 0:19:51.040
<v Speaker 2>full self driving FSD. It's a part of the pitch

0:19:51.080 --> 0:19:54.280
<v Speaker 2>from Tesla, But the vast majority of the auto market,

0:19:54.280 --> 0:19:57.000
<v Speaker 2>at least in America, maybe they don't think about, Okay,

0:19:57.040 --> 0:19:59.200
<v Speaker 2>I'm going to buy a vehicle based on its ability

0:19:59.240 --> 0:20:01.640
<v Speaker 2>to do this. Do you think that changes from here

0:20:01.680 --> 0:20:02.000
<v Speaker 2>on in?

0:20:03.359 --> 0:20:05.879
<v Speaker 12>I think I think more from consumer, it's more about

0:20:06.240 --> 0:20:09.600
<v Speaker 12>the in car experience. So we keep hearing this software

0:20:09.600 --> 0:20:11.959
<v Speaker 12>defined vehicle, So I don't think they're going into like

0:20:12.000 --> 0:20:15.040
<v Speaker 12>I want this autonomous or full self driving. It's more

0:20:15.080 --> 0:20:18.600
<v Speaker 12>about what kind of consumer experience can I have with

0:20:18.720 --> 0:20:22.720
<v Speaker 12>technology in the vehicle, So in vehicle experience, So maybe

0:20:22.760 --> 0:20:25.480
<v Speaker 12>it's the ability to have some of that ADA as technology,

0:20:25.480 --> 0:20:27.080
<v Speaker 12>but I don't think that's the main driver, it's more

0:20:27.080 --> 0:20:29.200
<v Speaker 12>about what's that experience going to be and what other

0:20:29.240 --> 0:20:30.840
<v Speaker 12>options that vehicle provide for me.

0:20:31.560 --> 0:20:33.720
<v Speaker 3>In many ways, it's about marketing, getting people in the

0:20:33.760 --> 0:20:36.200
<v Speaker 3>cars to understand what it feels like, and then sort

0:20:36.200 --> 0:20:39.200
<v Speaker 3>of perpetuate that demand for wanting more and more and more.

0:20:39.440 --> 0:20:43.040
<v Speaker 3>From your perspective, is the consumer mindset there from a

0:20:43.040 --> 0:20:47.560
<v Speaker 3>safety perspective? Is the regulation there from that perspective as well?

0:20:48.440 --> 0:20:48.640
<v Speaker 7>Yeah?

0:20:48.680 --> 0:20:50.280
<v Speaker 12>I think so. I think that's the one thing if

0:20:50.320 --> 0:20:52.920
<v Speaker 12>you think about you know, I think when you think

0:20:52.920 --> 0:20:55.080
<v Speaker 12>about Robotechi's right, we're starting to see a lot of

0:20:55.080 --> 0:20:58.160
<v Speaker 12>that with wai Mo and Zook, some other companies, Tesla

0:20:58.480 --> 0:21:01.560
<v Speaker 12>getting consumers into those taxi atonos, So they're getting to

0:21:01.640 --> 0:21:04.520
<v Speaker 12>finally experience that. But I still think, you know, it's

0:21:04.520 --> 0:21:07.200
<v Speaker 12>been hard to get consumers to trans you know, kind

0:21:07.200 --> 0:21:10.920
<v Speaker 12>of consider electric vehicles to get into an autonomous vehicle

0:21:11.000 --> 0:21:12.600
<v Speaker 12>is in more so. So, I think there's still a

0:21:12.640 --> 0:21:14.920
<v Speaker 12>lot of work to be done in terms of credibility

0:21:15.000 --> 0:21:19.080
<v Speaker 12>and safety perceptions for autonomous vehicles from a consumer perspective.

0:21:20.119 --> 0:21:23.960
<v Speaker 2>Stephanie, look forward to twenty twenty six for US, What

0:21:24.080 --> 0:21:27.199
<v Speaker 2>is it you expect to have in United States? In

0:21:27.280 --> 0:21:31.199
<v Speaker 2>particular in electric vehicles and any growth that may or

0:21:31.200 --> 0:21:32.440
<v Speaker 2>may not come to your mind.

0:21:33.400 --> 0:21:36.520
<v Speaker 12>Yeah, you know, twenty twenty five it ended exactly where

0:21:36.560 --> 0:21:38.760
<v Speaker 12>we thought it would. Our report comes out tomorrow, but

0:21:38.840 --> 0:21:41.359
<v Speaker 12>we're going to be about two percent down your year

0:21:41.720 --> 0:21:45.000
<v Speaker 12>round up to one point three million vehicles. But going

0:21:45.040 --> 0:21:46.480
<v Speaker 12>into twenty twenty six, right.

0:21:46.400 --> 0:21:48.200
<v Speaker 7>We got rid of the characteristic.

0:21:48.359 --> 0:21:52.280
<v Speaker 12>We no longer have the IRA tax intetive, the corporate

0:21:52.320 --> 0:21:57.080
<v Speaker 12>average fuel economy standards have been less stringent, the Calvern waiver.

0:21:57.640 --> 0:22:00.560
<v Speaker 12>But given all that, we still have twenty plus new

0:22:00.600 --> 0:22:03.880
<v Speaker 12>EV's launching in twenty twenty six, so I think we're

0:22:03.880 --> 0:22:06.000
<v Speaker 12>still going to see momentum. It's going to be hard,

0:22:06.080 --> 0:22:07.440
<v Speaker 12>but I think consumers.

0:22:06.960 --> 0:22:08.080
<v Speaker 4>Are going to have more product.

0:22:08.760 --> 0:22:10.840
<v Speaker 12>But I think the one thing which we've talked about

0:22:10.840 --> 0:22:13.600
<v Speaker 12>before in the past is the affordability. If you look

0:22:13.640 --> 0:22:17.960
<v Speaker 12>at the current product lineupsues that are offered over sixty

0:22:17.960 --> 0:22:20.720
<v Speaker 12>percent for over sixty five thousand dollars.

0:22:20.960 --> 0:22:22.280
<v Speaker 5>So that's definitely about is Treat.

0:22:23.640 --> 0:22:25.679
<v Speaker 2>It's definitely about it is Treated, Director of Industry in

0:22:25.680 --> 0:22:28.200
<v Speaker 2>Size Cox Automotive, thank you so much for coming up.

0:22:28.280 --> 0:22:30.680
<v Speaker 2>We'll speak with LUTs Capital co founder Peter Herbert about

0:22:30.720 --> 0:22:35.200
<v Speaker 2>the firm's latest fund, its biggest fund. Silicon Valley meets DC.

0:22:35.640 --> 0:22:47.560
<v Speaker 2>This is Bloomberg Tech. Welcome back to Bloomberg Tech. There's

0:22:47.560 --> 0:22:49.119
<v Speaker 2>a story we're going to go deeper on later in

0:22:49.119 --> 0:22:52.840
<v Speaker 2>the program, the President saying that if credit card companies

0:22:52.880 --> 0:22:56.359
<v Speaker 2>don't respect an interest cap with ten percent in the year,

0:22:57.040 --> 0:22:58.920
<v Speaker 2>they will be facing uh.

0:23:00.359 --> 0:23:01.639
<v Speaker 5>Illegal activity claims.

0:23:01.680 --> 0:23:03.800
<v Speaker 2>Basically, these are two of the more tech focus names

0:23:03.840 --> 0:23:06.240
<v Speaker 2>Klana a firm, both down on the news. I would

0:23:06.240 --> 0:23:09.280
<v Speaker 2>note American Express is also down as an example significantly.

0:23:09.320 --> 0:23:10.960
<v Speaker 2>We're going to get to that later in the program.

0:23:11.160 --> 0:23:13.639
<v Speaker 2>Back to one of the top stories, we've had confirmation

0:23:14.080 --> 0:23:16.640
<v Speaker 2>from Google that it is entered into a multi year

0:23:16.680 --> 0:23:20.679
<v Speaker 2>agreement with Apple for Gemini to be the underpinnings of

0:23:20.760 --> 0:23:22.040
<v Speaker 2>the next gen AI SERI.

0:23:22.480 --> 0:23:23.400
<v Speaker 5>You see, when the.

0:23:23.359 --> 0:23:26.280
<v Speaker 2>News broke just before the program about ten thirty East

0:23:26.320 --> 0:23:28.440
<v Speaker 2>in time, a big jump in alphabet shares that sent

0:23:28.520 --> 0:23:30.240
<v Speaker 2>market cap through four trillion.

0:23:30.280 --> 0:23:31.000
<v Speaker 5>They then faded.

0:23:31.040 --> 0:23:33.879
<v Speaker 2>And I'd remind you as well that Bloomberg did report

0:23:33.880 --> 0:23:36.639
<v Speaker 2>in November that a deal was close for Apple to

0:23:36.680 --> 0:23:39.120
<v Speaker 2>pay Google about a billion dollars a year for use

0:23:39.359 --> 0:23:42.720
<v Speaker 2>of that very large one point two trillion parameter model,

0:23:43.080 --> 0:23:43.760
<v Speaker 2>Carol what else.

0:23:44.200 --> 0:23:46.840
<v Speaker 3>Well, let's dig in on Alphabet and it's recent moves,

0:23:46.840 --> 0:23:49.280
<v Speaker 3>but also where it stands versus the rest of the market.

0:23:49.280 --> 0:23:52.200
<v Speaker 3>Bluembog equity reporter comen Ryanikey has been really digging in

0:23:52.240 --> 0:23:54.280
<v Speaker 3>to the idea that maybe we're broadening out.

0:23:54.520 --> 0:23:57.320
<v Speaker 4>Maybe MAG seven isn't just a sure far bet. Alphabet

0:23:57.400 --> 0:23:58.840
<v Speaker 4>was a sure far bet last year.

0:23:59.040 --> 0:24:00.880
<v Speaker 3>Tell us about the discern that was starting to see

0:24:00.880 --> 0:24:02.480
<v Speaker 3>among these key megacaps.

0:24:02.760 --> 0:24:05.359
<v Speaker 14>Yeah, I mean what we saw last year is continuing

0:24:05.400 --> 0:24:07.160
<v Speaker 14>at least in the first few weeks of this year.

0:24:07.200 --> 0:24:10.679
<v Speaker 14>Where the winners and losers are really important. So Alphabet

0:24:10.720 --> 0:24:13.120
<v Speaker 14>was a winner last year. It was the biggest outperformer

0:24:13.160 --> 0:24:15.240
<v Speaker 14>and one of only two stocks in the MAG seven

0:24:15.240 --> 0:24:17.760
<v Speaker 14>group that outperforms the broader market, the other one being

0:24:17.760 --> 0:24:21.479
<v Speaker 14>in Nvidia. So it's really established itself as dominant in

0:24:21.520 --> 0:24:25.480
<v Speaker 14>the AI trend, and you know, maintaining that momentum going

0:24:25.480 --> 0:24:29.080
<v Speaker 14>forward is really important, especially considering that we're starting to

0:24:29.160 --> 0:24:31.520
<v Speaker 14>see some of these other names lag a little bit.

0:24:31.600 --> 0:24:33.960
<v Speaker 14>You know, they're just slowing down in terms of overall

0:24:34.000 --> 0:24:36.960
<v Speaker 14>growth and heading into earning season, some of those things

0:24:36.960 --> 0:24:39.920
<v Speaker 14>are expected to continue, right we're just we're hitting the

0:24:40.359 --> 0:24:43.320
<v Speaker 14>law of large numbers. Growth is expected to slow, and

0:24:43.400 --> 0:24:46.200
<v Speaker 14>so that might translate, you know, into stock games as well.

0:24:47.280 --> 0:24:50.199
<v Speaker 2>Been an interesting morning for Alphabet and Apple and the

0:24:50.240 --> 0:24:55.040
<v Speaker 2>news flow around the deal to improve Siri, and I

0:24:55.119 --> 0:24:59.080
<v Speaker 2>was reflecting on literally just the ticker, right, you know,

0:24:59.240 --> 0:25:02.600
<v Speaker 2>Alphabet saw and breaches four trillion dollars market cap then

0:25:02.720 --> 0:25:04.560
<v Speaker 2>kind of fade straight away. What did you see in

0:25:04.600 --> 0:25:08.120
<v Speaker 2>the markets this morning in terms of how people reacted.

0:25:08.480 --> 0:25:11.160
<v Speaker 14>Yeah, so we saw that big spike for both Google

0:25:11.240 --> 0:25:14.560
<v Speaker 14>and Alpha or sorry, Google and Apple shares. It did

0:25:14.600 --> 0:25:17.480
<v Speaker 14>push Google over four trillion in market cap. It's also

0:25:17.680 --> 0:25:21.640
<v Speaker 14>surpassed Apple recently, so it's the second largest company in

0:25:21.680 --> 0:25:23.560
<v Speaker 14>the s and P five hundred million in the market

0:25:23.800 --> 0:25:26.840
<v Speaker 14>other than in Nvidia. And it's interesting because you know,

0:25:26.880 --> 0:25:29.520
<v Speaker 14>we did see those those gains fade a little bit.

0:25:29.560 --> 0:25:32.000
<v Speaker 14>They're up now. I think both stocks are trading in

0:25:32.040 --> 0:25:34.800
<v Speaker 14>positive territory. But the overall market, I think we are

0:25:34.880 --> 0:25:37.879
<v Speaker 14>still seeing a lot of macro news weigh on this.

0:25:38.040 --> 0:25:40.080
<v Speaker 14>It's been a little bit all over the place today.

0:25:40.200 --> 0:25:43.679
<v Speaker 14>So big tech is obviously still super important. These stocks

0:25:43.680 --> 0:25:46.720
<v Speaker 14>are really important. They're so large they add a lot

0:25:46.760 --> 0:25:49.000
<v Speaker 14>and can weigh a lot on the broader index. But

0:25:49.200 --> 0:25:51.159
<v Speaker 14>we also are seeing that there is a broadening out.

0:25:51.200 --> 0:25:54.600
<v Speaker 14>People are looking at other sectors, and you know, it's

0:25:54.640 --> 0:25:57.240
<v Speaker 14>not just big tech that's always driving the gains and

0:25:57.320 --> 0:25:58.240
<v Speaker 14>losses in the market.

0:25:58.920 --> 0:26:01.360
<v Speaker 5>Bloombe's common. Ryan, Thank you very much.

0:26:01.400 --> 0:26:04.880
<v Speaker 2>Let's go from the public markets private markets, where interest

0:26:04.920 --> 0:26:08.360
<v Speaker 2>in frontier tech is incredibly high. Lux Capital is raised

0:26:08.400 --> 0:26:11.000
<v Speaker 2>one point five billion dollars for its ninth fund, the

0:26:11.119 --> 0:26:14.680
<v Speaker 2>largest in the venture firms more than twenty year history.

0:26:14.880 --> 0:26:17.240
<v Speaker 2>Peter Abair, partner and co founder of Lots Capitals with

0:26:17.320 --> 0:26:18.280
<v Speaker 2>us here in San Francisco.

0:26:18.520 --> 0:26:19.320
<v Speaker 5>Thank you for having me.

0:26:19.440 --> 0:26:22.480
<v Speaker 2>It's exciting news, right the ninth fund that the largest ever.

0:26:22.560 --> 0:26:25.240
<v Speaker 2>You turned away about a billion dollars of capital. What's

0:26:25.320 --> 0:26:28.240
<v Speaker 2>very interesting about it, though, is the consistency. The themes

0:26:28.240 --> 0:26:30.520
<v Speaker 2>are the same, the focus is the same. What do

0:26:30.560 --> 0:26:31.600
<v Speaker 2>you want to do with this fund?

0:26:32.000 --> 0:26:34.800
<v Speaker 15>So we will be doing more of the same, but

0:26:35.000 --> 0:26:37.680
<v Speaker 15>just accelerating that piece. And so we've been investing now

0:26:37.760 --> 0:26:42.400
<v Speaker 15>for more than twenty five years in physical, computational life sciences,

0:26:42.680 --> 0:26:44.960
<v Speaker 15>but really at the cutting edge and the frontier of

0:26:45.000 --> 0:26:48.120
<v Speaker 15>all these different scientific disciplines, and so as we say

0:26:48.280 --> 0:26:50.960
<v Speaker 15>science doesn't scale itself, and so that's where we're going

0:26:51.000 --> 0:26:52.520
<v Speaker 15>to be put in the thrust of our investment.

0:26:52.960 --> 0:26:55.879
<v Speaker 2>Peter, we enjoy having you on the program. The firm you,

0:26:56.480 --> 0:26:58.800
<v Speaker 2>Josh Dino when they cut when all of you come on.

0:26:59.320 --> 0:27:03.240
<v Speaker 2>But it seems very disciplined, very calm. Check sizes one

0:27:03.320 --> 0:27:07.639
<v Speaker 2>hundred thousand. This is exciting though. These are some of

0:27:07.680 --> 0:27:10.840
<v Speaker 2>the domains that are moving the fastest, and actually, would

0:27:10.840 --> 0:27:14.800
<v Speaker 2>you reflect that this administration has allowed you to do that?

0:27:15.480 --> 0:27:18.840
<v Speaker 2>The areas of defense, other areas adjacent to AI is

0:27:18.880 --> 0:27:21.920
<v Speaker 2>something that the Trump administration has moved quickly to support.

0:27:22.520 --> 0:27:26.840
<v Speaker 15>So certainly in areas like defense, kind of broadly reindustrialization

0:27:26.960 --> 0:27:29.280
<v Speaker 15>a lot of the things that we do. It's certainly

0:27:29.560 --> 0:27:33.159
<v Speaker 15>having a moment, and that's really reflected one from the

0:27:33.200 --> 0:27:36.400
<v Speaker 15>technological waves that are happening. One of the things that

0:27:36.880 --> 0:27:40.119
<v Speaker 15>is top of everyone's mind right now is physical AI.

0:27:41.119 --> 0:27:44.000
<v Speaker 15>Right now, there's also the JP Morgan healthcare event happening

0:27:44.040 --> 0:27:48.080
<v Speaker 15>in San Francisco. You're seeing huge breakthroughs in medical robotics

0:27:48.560 --> 0:27:52.280
<v Speaker 15>and in computational drug discovery. But absolutely, if you look

0:27:52.320 --> 0:27:56.360
<v Speaker 15>at the world, it's an uncertain place, and defense technology

0:27:56.520 --> 0:28:00.760
<v Speaker 15>has been really soaring as Large Nations state its rearm

0:28:00.840 --> 0:28:03.720
<v Speaker 15>and focus under Terrens Peter Andreill.

0:28:03.760 --> 0:28:05.360
<v Speaker 4>Of course, one of the key bets you made and.

0:28:05.320 --> 0:28:08.040
<v Speaker 3>We had Parmalucky on the show last week. From ces

0:28:08.920 --> 0:28:12.280
<v Speaker 3>of this fund, how much will be to double down

0:28:12.520 --> 0:28:15.160
<v Speaker 3>on prior bets or how much will be to take

0:28:15.200 --> 0:28:18.240
<v Speaker 3>out totally new bets on new companies coming to your inbox.

0:28:19.200 --> 0:28:21.480
<v Speaker 15>So the spirit of this fund is really thinking about

0:28:21.520 --> 0:28:25.000
<v Speaker 15>as a blank slate, starting with the portfolio of probably

0:28:25.040 --> 0:28:29.879
<v Speaker 15>forty to fifty core positions. Historically we've had companies that

0:28:29.960 --> 0:28:33.080
<v Speaker 15>have gone from one fund to another cross fund investing,

0:28:33.119 --> 0:28:36.040
<v Speaker 15>but it's generally not the focus and philosophy of each

0:28:36.119 --> 0:28:37.560
<v Speaker 15>new core fund that we.

0:28:37.600 --> 0:28:40.800
<v Speaker 3>Raise one hundred thousand dollars to one hundred million, that's

0:28:40.840 --> 0:28:44.400
<v Speaker 3>a huge breadth that you're giving yourselves. Where do you

0:28:44.440 --> 0:28:48.000
<v Speaker 3>think you will be excited to deploy? Have the foundational

0:28:48.040 --> 0:28:50.720
<v Speaker 3>models moved forward? Are we seeing more interesting areas of

0:28:50.800 --> 0:28:55.280
<v Speaker 3>more specific niche parts of the building the llms or

0:28:55.320 --> 0:28:57.800
<v Speaker 3>is it more about application? Where are you thinking about

0:28:57.920 --> 0:28:58.840
<v Speaker 3>getting excited for?

0:29:00.000 --> 0:29:02.360
<v Speaker 15>So our mental model and framework really is what we

0:29:02.440 --> 0:29:05.960
<v Speaker 15>describe as moving from two D two dimensional AI to

0:29:06.200 --> 0:29:10.360
<v Speaker 15>three D and that's really areas of robotics and automation

0:29:10.520 --> 0:29:14.360
<v Speaker 15>and biology, but it's seeing AI for the first time

0:29:14.480 --> 0:29:17.960
<v Speaker 15>coming out of the digital world into the physical And

0:29:18.120 --> 0:29:21.240
<v Speaker 15>just one example of that is really just the momentous

0:29:21.280 --> 0:29:26.920
<v Speaker 15>opportunity here. Approximately ninety percent of us GDP is not

0:29:27.080 --> 0:29:30.560
<v Speaker 15>digitally native. It is in the physical world. It's construction,

0:29:30.720 --> 0:29:34.160
<v Speaker 15>it's heavy industry, and that's thirty trillion dollars of total

0:29:34.320 --> 0:29:38.920
<v Speaker 15>us GDP. So the opportunity really exist for technology investors

0:29:39.640 --> 0:29:43.960
<v Speaker 15>focused on software, data other very specific areas that now

0:29:44.040 --> 0:29:49.040
<v Speaker 15>have the opportunity basically ten x total addressable market.

0:29:49.760 --> 0:29:52.080
<v Speaker 5>Peter, you're co founder of this firm.

0:29:52.240 --> 0:29:56.000
<v Speaker 2>Has the composition of the LP's changed from fund one

0:29:56.080 --> 0:29:58.880
<v Speaker 2>through to fund nine, and where the interests in you

0:29:59.000 --> 0:30:00.480
<v Speaker 2>is coming from?

0:30:00.760 --> 0:30:05.080
<v Speaker 15>Earliest a believer in LUX was a gentleman, Bill Conway,

0:30:05.080 --> 0:30:07.200
<v Speaker 15>one of the founders of the Carlisle Law, and so

0:30:07.240 --> 0:30:12.200
<v Speaker 15>he was LUX Venture is one. Today we manage seven

0:30:12.200 --> 0:30:16.680
<v Speaker 15>billion dollars on behalf of endowments and foundations and state pensions.

0:30:17.000 --> 0:30:21.760
<v Speaker 15>So obviously going from an initial individual albeit a quasi institution,

0:30:22.320 --> 0:30:25.240
<v Speaker 15>to now serving some of the world's most elite institutions.

0:30:25.480 --> 0:30:28.120
<v Speaker 2>I'm really interested in the core competencies you're looking for

0:30:28.240 --> 0:30:30.680
<v Speaker 2>later in the program. We have one X, the humanoid

0:30:30.760 --> 0:30:34.240
<v Speaker 2>robotics company on right, and they're out with their own

0:30:34.280 --> 0:30:37.600
<v Speaker 2>world model. But the problem right now is that in Nvidia,

0:30:37.720 --> 0:30:39.959
<v Speaker 2>as was made very plain last week, basically come out

0:30:40.000 --> 0:30:41.560
<v Speaker 2>and say we'll do it all for you on the

0:30:41.600 --> 0:30:45.760
<v Speaker 2>hardware and software side. If you're a humanoid robots company

0:30:46.000 --> 0:30:49.200
<v Speaker 2>or a different physical AI offering, what's left to look

0:30:49.280 --> 0:30:51.080
<v Speaker 2>for in that regard.

0:30:50.880 --> 0:30:51.800
<v Speaker 5>Believe in it or not.

0:30:52.680 --> 0:30:56.080
<v Speaker 15>There will not just be one company that rules all others,

0:30:56.080 --> 0:30:58.280
<v Speaker 15>and so there are a number of different opportunities. And

0:30:58.320 --> 0:31:01.719
<v Speaker 15>even with Nvidia, as prominas they are, there are other

0:31:01.840 --> 0:31:04.680
<v Speaker 15>up and comers on the silicon side, certainly on the

0:31:04.720 --> 0:31:08.760
<v Speaker 15>software side training there are a number of different companies

0:31:08.800 --> 0:31:13.760
<v Speaker 15>that are attacking again physical implementations of AI, from physical

0:31:13.760 --> 0:31:17.760
<v Speaker 15>intelligence that's here in San Francisco to Applied Intuition, which

0:31:17.800 --> 0:31:20.000
<v Speaker 15>is a lux portfolio company which is really creating an

0:31:20.040 --> 0:31:24.920
<v Speaker 15>operating system in mobility. So there is abundant opportunity.

0:31:24.680 --> 0:31:26.880
<v Speaker 3>And is that global Peter in terms of not just

0:31:27.040 --> 0:31:30.280
<v Speaker 3>the consumer base, but where these companies are getting birthed.

0:31:30.320 --> 0:31:31.200
<v Speaker 4>How broad do you go?

0:31:32.560 --> 0:31:36.160
<v Speaker 15>Well, one X not an American company. There are many

0:31:36.280 --> 0:31:41.120
<v Speaker 15>global competitors in this marketplace, even in AI. Right now,

0:31:41.120 --> 0:31:44.000
<v Speaker 15>we're an investor in a company called Sikana Ai based

0:31:44.000 --> 0:31:47.080
<v Speaker 15>in Japan. We've made probably about a dozen or so

0:31:47.200 --> 0:31:52.120
<v Speaker 15>investments across Europe in the last fund. So technology is global,

0:31:52.160 --> 0:31:56.720
<v Speaker 15>it's broadly distributed. San Francisco remains the epicenter, but you

0:31:56.760 --> 0:31:59.520
<v Speaker 15>will see it popping up coming out of a lot

0:31:59.560 --> 0:32:01.880
<v Speaker 15>of large research institutions across the globe.

0:32:02.560 --> 0:32:05.720
<v Speaker 3>Fascinating p DA Bere We thank you, partner co founder

0:32:05.800 --> 0:32:09.000
<v Speaker 3>lux Capital. On the latest fun announcement coming up, we

0:32:09.040 --> 0:32:11.640
<v Speaker 3>talk about that company one X, the maker of Neo.

0:32:12.120 --> 0:32:14.080
<v Speaker 3>It says this new AI model will give its home

0:32:14.240 --> 0:32:16.880
<v Speaker 3>robot the ability to learn new tasks from scratch.

0:32:17.240 --> 0:32:19.920
<v Speaker 4>I'll talk to the CEO. This has been their tech.

0:32:29.400 --> 0:32:31.680
<v Speaker 5>We've got news for you from the world of robotics.

0:32:31.800 --> 0:32:34.960
<v Speaker 2>One X Technologies, the maker of the humanoid robot Neo,

0:32:35.560 --> 0:32:37.959
<v Speaker 2>has an update for its one Ex World model, an

0:32:37.960 --> 0:32:41.600
<v Speaker 2>AI video model grounded in physics. According to the company,

0:32:41.600 --> 0:32:44.840
<v Speaker 2>the update will make Neo capable of executing on new

0:32:44.880 --> 0:32:48.160
<v Speaker 2>AI abilities with a simple text or voice prompt. That's

0:32:48.280 --> 0:32:51.720
<v Speaker 2>even if the robot has zero experience of doing the

0:32:51.800 --> 0:32:54.719
<v Speaker 2>task before joining us is one X Technology CEO and

0:32:54.800 --> 0:32:56.280
<v Speaker 2>CTO Bernt Bernick.

0:32:56.520 --> 0:32:57.760
<v Speaker 5>Welcome back to bloombog Tech.

0:32:58.120 --> 0:32:58.520
<v Speaker 10>Thank you.

0:32:58.720 --> 0:33:00.480
<v Speaker 7>I want to keep this really simple to start.

0:33:00.760 --> 0:33:03.600
<v Speaker 2>What is an example of a task that the update

0:33:03.640 --> 0:33:06.440
<v Speaker 2>to the model allows for NEO to do that it

0:33:06.480 --> 0:33:10.200
<v Speaker 2>couldn't have done for the first time without the update.

0:33:12.080 --> 0:33:14.720
<v Speaker 16>So I mean to me, it's all about like things

0:33:14.840 --> 0:33:20.760
<v Speaker 16>just being anything that you don't have in your data set,

0:33:20.880 --> 0:33:23.000
<v Speaker 16>but still being able to have a sensible approach.

0:33:23.440 --> 0:33:25.800
<v Speaker 10>So like the first time I really kind of.

0:33:25.760 --> 0:33:28.040
<v Speaker 16>Like saw this and it was a simple question, just

0:33:28.080 --> 0:33:30.560
<v Speaker 16>asking the robot, hey, can you can you pick the

0:33:31.200 --> 0:33:33.360
<v Speaker 16>post it note down from the board and read it?

0:33:33.400 --> 0:33:35.280
<v Speaker 16>But it might never have seen a post and it's like,

0:33:35.320 --> 0:33:37.719
<v Speaker 16>of course, we don't have any training data on us

0:33:37.800 --> 0:33:39.640
<v Speaker 16>using robots to like pick post it notes off a

0:33:39.680 --> 0:33:41.480
<v Speaker 16>board and like look at it and read what's on it.

0:33:42.000 --> 0:33:44.440
<v Speaker 10>But it can actually do it really well, and it's

0:33:44.480 --> 0:33:45.480
<v Speaker 10>not aji yet.

0:33:45.840 --> 0:33:49.720
<v Speaker 16>There are examples where it fails, But what it does

0:33:49.840 --> 0:33:53.800
<v Speaker 16>is the ability to have this very sensible approach to anything,

0:33:54.400 --> 0:33:56.960
<v Speaker 16>which is a cornerstone of learning, because now all you

0:33:57.040 --> 0:33:59.160
<v Speaker 16>need is the robots teaching themselves how to do all

0:33:59.200 --> 0:34:01.680
<v Speaker 16>these tasks by actually experimenting and doing this in the

0:34:01.800 --> 0:34:02.200
<v Speaker 16>real world.

0:34:03.120 --> 0:34:06.160
<v Speaker 5>This model, how good is it? You know?

0:34:06.240 --> 0:34:10.800
<v Speaker 2>Last week CS and Video extol the virtues of using

0:34:10.840 --> 0:34:14.560
<v Speaker 2>their open models, and inside Neo, the brain of Neo

0:34:15.160 --> 0:34:18.800
<v Speaker 2>is an Nvidia inferenced chip, right, so why not just

0:34:18.920 --> 0:34:20.800
<v Speaker 2>using Vidia's model too.

0:34:22.160 --> 0:34:24.120
<v Speaker 16>We have a very deep collaboration made in VideA and

0:34:24.160 --> 0:34:26.320
<v Speaker 16>we do use a lot of their technology in the stack.

0:34:28.480 --> 0:34:32.040
<v Speaker 16>I think to us also, it's very much about the

0:34:32.080 --> 0:34:35.600
<v Speaker 16>embodiment and the husband designed really over the last decade

0:34:35.640 --> 0:34:38.600
<v Speaker 16>to be as close to a human as possible. Because

0:34:38.640 --> 0:34:40.440
<v Speaker 16>if you take all of the knowledge that we have

0:34:40.480 --> 0:34:42.360
<v Speaker 16>in the world, like everything you can see on YouTube

0:34:42.440 --> 0:34:44.719
<v Speaker 16>or any kind of video content, and you train a

0:34:44.800 --> 0:34:47.279
<v Speaker 16>model on this and now you want to pick up

0:34:47.320 --> 0:34:51.360
<v Speaker 16>the cup or open the door, if your robot is

0:34:51.360 --> 0:34:54.680
<v Speaker 16>actually not similar enough to a human, this doesn't work

0:34:54.719 --> 0:34:56.880
<v Speaker 16>anymore because you wouldn't do the task in the same manner.

0:34:57.280 --> 0:34:59.399
<v Speaker 16>And this is quite unique to one because I think

0:34:59.520 --> 0:35:01.920
<v Speaker 16>there's there's a couple of things that really puts us apart,

0:35:02.200 --> 0:35:05.080
<v Speaker 16>and it's that we have robots that are so close

0:35:05.120 --> 0:35:07.719
<v Speaker 16>to humans in how they interact with the world, but

0:35:07.800 --> 0:35:10.600
<v Speaker 16>also that they're safe so they can actually try to

0:35:10.640 --> 0:35:13.279
<v Speaker 16>do something and if they fail, then the world is

0:35:13.280 --> 0:35:16.000
<v Speaker 16>still okay. You don't want your like I don't know,

0:35:16.040 --> 0:35:17.719
<v Speaker 16>you don't want your door to be scratched because there

0:35:17.760 --> 0:35:21.279
<v Speaker 16>was a robot trying to open it. And this puts

0:35:21.360 --> 0:35:23.719
<v Speaker 16>us in a category where our approach today it is

0:35:23.719 --> 0:35:26.120
<v Speaker 16>probably a bit different, like what the standard is now

0:35:26.160 --> 0:35:29.879
<v Speaker 16>and also why we're so we're very excited about these

0:35:29.880 --> 0:35:33.400
<v Speaker 16>world models where finally we see robotic scaling following the

0:35:33.400 --> 0:35:36.279
<v Speaker 16>same scaling laws as for example, video pre training from

0:35:36.320 --> 0:35:40.000
<v Speaker 16>the big video models, like so our video from our competitors,

0:35:40.040 --> 0:35:41.480
<v Speaker 16>and go in on.

0:35:41.440 --> 0:35:44.240
<v Speaker 3>The safety a little bit more because you're talking about

0:35:44.440 --> 0:35:47.600
<v Speaker 3>how it stops the door getting scratched, but for many

0:35:47.640 --> 0:35:51.040
<v Speaker 3>it's about well, when robots start learning to do things themselves,

0:35:51.320 --> 0:35:53.040
<v Speaker 3>therein lies the safety issue.

0:35:53.200 --> 0:35:54.600
<v Speaker 4>What god rails do you have in place?

0:35:56.280 --> 0:35:59.239
<v Speaker 16>So we have some exciting work on that that will

0:35:59.239 --> 0:35:59.879
<v Speaker 16>come out soon.

0:36:00.719 --> 0:36:02.000
<v Speaker 10>We are doing.

0:36:03.280 --> 0:36:05.640
<v Speaker 16>The proper things on the safety side with respect to

0:36:05.680 --> 0:36:09.319
<v Speaker 16>following the standards, helping develop some of the standards, but

0:36:09.360 --> 0:36:13.399
<v Speaker 16>also ensuring that we, for example, have externally audited work

0:36:13.440 --> 0:36:17.080
<v Speaker 16>of our safety work by an independent by independent third party,

0:36:17.080 --> 0:36:20.520
<v Speaker 16>of course, But to me, safety has many layers. You

0:36:20.600 --> 0:36:23.479
<v Speaker 16>have what we call like the passive intrinsic safety, where

0:36:23.600 --> 0:36:26.200
<v Speaker 16>humans are actually very safe in the sense that we have.

0:36:26.200 --> 0:36:28.640
<v Speaker 10>To actively work to hurt each other.

0:36:29.000 --> 0:36:31.840
<v Speaker 16>We don't hurt each other by accident usually, and this

0:36:31.920 --> 0:36:33.960
<v Speaker 16>is something we build into the machine the same kind

0:36:33.960 --> 0:36:37.640
<v Speaker 16>of just you have to be soft, compliant, lightweight, low energy,

0:36:37.880 --> 0:36:40.960
<v Speaker 16>so you can be safe in among people and in

0:36:41.000 --> 0:36:43.760
<v Speaker 16>the environment. And then of course you have the AI alignment,

0:36:43.960 --> 0:36:46.200
<v Speaker 16>which is equally important, and how do you ensure that

0:36:46.440 --> 0:36:49.719
<v Speaker 16>you can always take the safest leads to risky path

0:36:49.800 --> 0:36:52.239
<v Speaker 16>for whatever task you want to achieve. And this is

0:36:52.280 --> 0:36:55.759
<v Speaker 16>also something that's incredibly exciting about these world models that

0:36:56.120 --> 0:36:58.640
<v Speaker 16>they understand the world so well and also how the

0:36:58.640 --> 0:37:01.680
<v Speaker 16>physical world works, that you can not only ask for

0:37:01.800 --> 0:37:04.080
<v Speaker 16>how am I going to do this task, but how

0:37:04.120 --> 0:37:05.680
<v Speaker 16>am I going to do this task in a manner

0:37:05.760 --> 0:37:06.960
<v Speaker 16>that is as safe as possible?

0:37:07.120 --> 0:37:10.040
<v Speaker 10>What are the things that could possibly be wrong go wrong?

0:37:10.320 --> 0:37:11.760
<v Speaker 10>And then the model actively.

0:37:11.400 --> 0:37:13.200
<v Speaker 16>Reasons about like, hey, here are the things that I

0:37:13.239 --> 0:37:15.480
<v Speaker 16>can visualize going wrong here, So I'm going to take

0:37:15.480 --> 0:37:17.040
<v Speaker 16>this path here, which is the safest path.

0:37:17.600 --> 0:37:21.280
<v Speaker 2>The problem being sold for other than ultimately accelerating deployment

0:37:21.320 --> 0:37:23.640
<v Speaker 2>of NEO in the real world. Is the burden of

0:37:23.680 --> 0:37:27.279
<v Speaker 2>real world data gathering and a lot of focus right

0:37:27.280 --> 0:37:31.319
<v Speaker 2>now on simulation and synthetic data. Just talk a little

0:37:31.320 --> 0:37:33.760
<v Speaker 2>bit about that. Some of our audiences is our industry,

0:37:33.840 --> 0:37:35.920
<v Speaker 2>they're more technical and they'll want to know how you

0:37:35.960 --> 0:37:37.640
<v Speaker 2>did it with this particular model.

0:37:38.480 --> 0:37:41.719
<v Speaker 16>Yeah, so I think really, if you boil it down

0:37:41.800 --> 0:37:45.799
<v Speaker 16>to the simplest parts, it is if your embodiment, if

0:37:45.840 --> 0:37:48.799
<v Speaker 16>your robot is close enough to a human, then all

0:37:48.840 --> 0:37:52.560
<v Speaker 16>of these learnings that they have from video they actually

0:37:52.560 --> 0:37:56.160
<v Speaker 16>transfer pretty well. And once you can do that, and

0:37:56.200 --> 0:37:58.719
<v Speaker 16>your robot can now approach almost any task as long

0:37:58.719 --> 0:37:59.040
<v Speaker 16>as you.

0:37:58.960 --> 0:37:59.600
<v Speaker 10>Can ask for it.

0:38:01.800 --> 0:38:05.400
<v Speaker 16>Your intelligence doesn't scale with the amount of data you

0:38:05.400 --> 0:38:06.920
<v Speaker 16>can collect with humans anymore.

0:38:07.080 --> 0:38:09.080
<v Speaker 10>It actually scales with the number of robots.

0:38:08.760 --> 0:38:12.400
<v Speaker 16>You've deployed, because now you just need enough robots actually

0:38:12.480 --> 0:38:14.640
<v Speaker 16>trying to do all these things, and trying to do

0:38:14.680 --> 0:38:18.040
<v Speaker 16>these things are useful, right, so you also produce useful work.

0:38:18.080 --> 0:38:20.280
<v Speaker 16>But in the process, the robot learns and it quickly

0:38:20.280 --> 0:38:23.040
<v Speaker 16>gets better, and now you just want enough robots across

0:38:23.040 --> 0:38:26.480
<v Speaker 16>society and doing enough different tasks so that you get

0:38:26.480 --> 0:38:29.880
<v Speaker 16>a very large data coverage and then you're progressing very

0:38:29.680 --> 0:38:33.719
<v Speaker 16>well on your scaling laws towards general intelligence. But it's

0:38:33.719 --> 0:38:38.000
<v Speaker 16>now independent of actually having to use humans to gather

0:38:38.040 --> 0:38:38.680
<v Speaker 16>the data to a.

0:38:38.680 --> 0:38:42.080
<v Speaker 2>Tel operations sideration exactly, burn x CEO and c to

0:38:42.280 --> 0:38:44.120
<v Speaker 2>one X. Is great to have you back here on

0:38:44.200 --> 0:38:46.560
<v Speaker 2>boomby Tech. Thank you very much. Carry plenty of other

0:38:46.600 --> 0:38:47.200
<v Speaker 2>news headlines.

0:38:47.320 --> 0:38:49.560
<v Speaker 3>Yeah, and it's time now for talking tech and first start.

0:38:49.680 --> 0:38:52.800
<v Speaker 3>Mon Meta has appointed a formatop advisor to President Trump

0:38:52.840 --> 0:38:56.160
<v Speaker 3>to a newly created senior management role. Done Power McCormick

0:38:56.400 --> 0:38:59.600
<v Speaker 3>will guide the company's aim structure efforts, including securing future

0:38:59.600 --> 0:39:03.719
<v Speaker 3>funding from governments and investors for massive data center projects.

0:39:04.000 --> 0:39:06.879
<v Speaker 3>Plus Meta also says it has shut down almost five

0:39:06.960 --> 0:39:10.239
<v Speaker 3>hundred and fifty thousand accounts in Australia to comply with

0:39:10.320 --> 0:39:13.600
<v Speaker 3>the country's new social media ban for kids Now. The law,

0:39:13.640 --> 0:39:16.160
<v Speaker 3>which came into effect last year, mandates that services like

0:39:16.200 --> 0:39:19.040
<v Speaker 3>Facebook and Instagram block under sixteen year olds from having

0:39:19.040 --> 0:39:21.360
<v Speaker 3>accounts or face fines ab up to thirty three million

0:39:21.400 --> 0:39:25.280
<v Speaker 3>dollars and anthropic. While it's making a push into healthcare

0:39:25.360 --> 0:39:28.280
<v Speaker 3>with tools that allow patients and doctors to access medical

0:39:28.320 --> 0:39:29.800
<v Speaker 3>information on its AI chatbot.

0:39:29.960 --> 0:39:30.120
<v Speaker 5>Now.

0:39:30.120 --> 0:39:31.840
<v Speaker 4>The new offering is compliant with.

0:39:31.960 --> 0:39:35.720
<v Speaker 3>US medical privacy regulations, allowing providers and consumers to field

0:39:35.760 --> 0:39:36.880
<v Speaker 3>protected health.

0:39:36.680 --> 0:39:39.400
<v Speaker 5>Data ed okay, coming up.

0:39:39.440 --> 0:39:42.359
<v Speaker 2>Credit card issuers are on edge as President Trump calls

0:39:42.400 --> 0:39:45.440
<v Speaker 2>for a ten percent interest rate cap on credit cards

0:39:45.600 --> 0:39:46.200
<v Speaker 2>for one year.

0:39:46.239 --> 0:39:48.399
<v Speaker 5>We had the details. Next, this is Bloomberg Tech.

0:39:56.960 --> 0:39:59.759
<v Speaker 2>Allmark is partnering with alphabet to offer Ali and hands

0:39:59.760 --> 0:40:02.880
<v Speaker 2>show being on Google Gemini's platform part of the retailer's

0:40:02.960 --> 0:40:06.400
<v Speaker 2>race to apply the technology across its operations, from apparel

0:40:06.520 --> 0:40:09.960
<v Speaker 2>and consumables to entertainment and food products. Customers will be

0:40:10.000 --> 0:40:13.600
<v Speaker 2>able to purchase items on Gemini's browser or mobile app

0:40:13.719 --> 0:40:14.520
<v Speaker 2>in the coming months.

0:40:14.600 --> 0:40:16.640
<v Speaker 3>Carot, let's talk a bit more about the consumer and

0:40:17.120 --> 0:40:19.800
<v Speaker 3>tech and payments. For example, because President Trump is pushing

0:40:19.920 --> 0:40:22.160
<v Speaker 3>for a one year cap on credit card interest rates

0:40:22.239 --> 0:40:24.279
<v Speaker 3>at ten percent, it's a move that could end the

0:40:24.320 --> 0:40:27.120
<v Speaker 3>credit card industry and also ripple through major buy now,

0:40:27.160 --> 0:40:30.520
<v Speaker 3>pay later providers. Newberg's page Smith, who covers consumer finance,

0:40:30.800 --> 0:40:35.600
<v Speaker 3>is right here. Look, is this going to send shock

0:40:35.640 --> 0:40:39.280
<v Speaker 3>waves and people towards alternative forms of financing? If, for example,

0:40:39.320 --> 0:40:42.080
<v Speaker 3>these credit cards just can't serve the broad consumer that

0:40:42.120 --> 0:40:42.600
<v Speaker 3>they used to.

0:40:42.600 --> 0:40:45.200
<v Speaker 4>If ten percent is the cap, that's a really good question.

0:40:45.400 --> 0:40:48.919
<v Speaker 17>I think we are a bit early to exactly see

0:40:48.920 --> 0:40:52.560
<v Speaker 17>how consumers are responding to this, because it's still early days.

0:40:52.680 --> 0:40:55.840
<v Speaker 17>Just to be clear, President Trump's statement on Friday evening

0:40:55.840 --> 0:40:59.240
<v Speaker 17>and then again last night was really just saying that

0:40:59.080 --> 0:41:03.240
<v Speaker 17>that credit card companies, essentially issuers and big banks should

0:41:03.320 --> 0:41:06.480
<v Speaker 17>be doing this. The legal levers that he can actually

0:41:06.480 --> 0:41:10.760
<v Speaker 17>pull to implement such a proposal would are still very unclear.

0:41:10.920 --> 0:41:13.759
<v Speaker 17>We haven't seen any sort of formal proposals. So to

0:41:13.840 --> 0:41:17.000
<v Speaker 17>sort of say that there would be fintech, you know,

0:41:17.040 --> 0:41:20.719
<v Speaker 17>maybe fintech alternatives, sort of folks along the lines of

0:41:21.040 --> 0:41:24.600
<v Speaker 17>so Fi or a firm or Klarna actually stepping into

0:41:24.640 --> 0:41:28.319
<v Speaker 17>the void is a bit premature. But although shares have

0:41:28.440 --> 0:41:31.960
<v Speaker 17>sort of seemed to react and seem to be identifying

0:41:31.960 --> 0:41:33.680
<v Speaker 17>some potential opportunities along those.

0:41:33.560 --> 0:41:37.399
<v Speaker 2>Lines, Paige, the president's claim is that some credit card

0:41:37.520 --> 0:41:40.759
<v Speaker 2>providers are charging twenty eight up to thirty percent, as

0:41:40.760 --> 0:41:43.560
<v Speaker 2>he put it, but also that the consumer might not

0:41:43.640 --> 0:41:46.200
<v Speaker 2>even realize that they're being charge interest at a rate

0:41:46.239 --> 0:41:49.640
<v Speaker 2>of thirty percent. In our reporting and in evidence, do

0:41:49.719 --> 0:41:52.880
<v Speaker 2>we know that to be true among some credit card providers.

0:41:53.320 --> 0:41:55.120
<v Speaker 17>I mean, I'll speak for myself. I think it would

0:41:55.160 --> 0:41:57.440
<v Speaker 17>be fair to say that it was a good reminder

0:41:57.520 --> 0:41:59.640
<v Speaker 17>this morning and over the weekend to be checking interest

0:41:59.719 --> 0:42:02.799
<v Speaker 17>rates on credit cards, as every consumer should be. So

0:42:03.040 --> 0:42:06.000
<v Speaker 17>I think it is fair that it's not a widely

0:42:06.120 --> 0:42:10.640
<v Speaker 17>known fact of exactly how much it costs consumers to

0:42:10.800 --> 0:42:14.359
<v Speaker 17>be swiping, tapping using their credit cards across the board.

0:42:14.880 --> 0:42:16.719
<v Speaker 3>You do a great job, but reminding us that this

0:42:16.800 --> 0:42:18.880
<v Speaker 3>is still at these stages and enacting any sort of

0:42:18.920 --> 0:42:21.719
<v Speaker 3>proposed cap would take, I believe, in act to congress,

0:42:22.800 --> 0:42:25.640
<v Speaker 3>but push us forward to what some of the key

0:42:25.680 --> 0:42:29.719
<v Speaker 3>executives have said in response to this potential move.

0:42:29.960 --> 0:42:32.680
<v Speaker 17>Most definitely a quote that stood out to me just

0:42:32.719 --> 0:42:34.759
<v Speaker 17>before I came on air as I saw that the

0:42:35.160 --> 0:42:39.440
<v Speaker 17>Sofi CEO, Anthony Noto. I believe the quote was giddy

0:42:39.520 --> 0:42:43.280
<v Speaker 17>up in terms of the opportunities for Sofi. Sofi actually

0:42:43.520 --> 0:42:46.439
<v Speaker 17>does offer credit card to its consumers, but it's really

0:42:46.520 --> 0:42:48.839
<v Speaker 17>a firm that's kind of best known for student loan

0:42:48.880 --> 0:42:52.719
<v Speaker 17>refinancing and also personal loans for consumers. So that's kind

0:42:52.719 --> 0:42:57.360
<v Speaker 17>of a flavor of the tones some executives are striking,

0:42:57.400 --> 0:43:00.600
<v Speaker 17>while others are maybe kind of hanging back and seeing

0:43:00.640 --> 0:43:03.920
<v Speaker 17>substantively what impact this could have or what opportunities it

0:43:03.960 --> 0:43:05.320
<v Speaker 17>could present for their businesses.

0:43:06.320 --> 0:43:09.239
<v Speaker 2>Bloomberg's page fith thank you very much. That does it

0:43:09.280 --> 0:43:11.799
<v Speaker 2>for this edition of Bloomberg Tech carry.

0:43:11.800 --> 0:43:14.319
<v Speaker 3>So much already as we kick off this week, don't

0:43:14.360 --> 0:43:15.960
<v Speaker 3>forget to check out our podcasts. You can find out

0:43:16.000 --> 0:43:19.080
<v Speaker 3>on the Terminal, sells online on Apple, Spotify, and iHeart.

0:43:19.840 --> 0:43:22.520
<v Speaker 4>Back in San Francisco and New York. No longer in Vegas.

0:43:22.640 --> 0:43:23.600
<v Speaker 4>This is Bloomberg Tech