WEBVTT - Memory Prices Hit Cisco, Apple Faces Siri Snags

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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 Hyde in New York

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

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<v Speaker 2>This is Bloomberg Tech coming up. Memory chip prices strike again,

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<v Speaker 2>this time taking a toll on Cisco, even as AI

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<v Speaker 2>demand surges will break it down.

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<v Speaker 3>Plus, Apple's revamp of its Siri voice assistant hits new

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<v Speaker 3>snags that could delay the release of some features.

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<v Speaker 2>An Altruist launched AI tax planning tool, and within ours

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<v Speaker 2>wealth management stocks tumbled. The CEO of Outist joins us

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<v Speaker 2>to discuss.

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<v Speaker 3>First we check in on these markets that in many

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<v Speaker 3>ways are still digesting AI disruption. We focus in on

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<v Speaker 3>Cisco that I know you'll go to. We're off by

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<v Speaker 3>one percent on the Nastak one hundred. That anxiety of costs,

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<v Speaker 3>of memory costs really building into the benchmark. But more broadly,

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<v Speaker 3>we're all eyes on costs for consumers. CPI print coming

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<v Speaker 3>later in the market. Just a little bit nervous ahead

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<v Speaker 3>of that. Bitcoin down another day of five percentage point

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<v Speaker 3>sixty seven thousand is where we trade for this particular

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<v Speaker 3>risk asset ed What.

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<v Speaker 2>Are you looking at there's a lot of pieces of

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<v Speaker 2>consecutive red on the screens we've been putting up. Cisco

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<v Speaker 2>no exception, down eleven percent, on track for its biggest

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<v Speaker 2>drop since May twenty twenty two, and prior to today's session

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<v Speaker 2>it was up eleven percent and had momentum. Outlook is

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<v Speaker 2>strong on sales for the current period. AI demands there,

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<v Speaker 2>but there's margin compression memory chip prices. Let's get more

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<v Speaker 2>with Bloomberg Intelligence senior hardware and network analysts Wou jin Ho.

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<v Speaker 2>It's actually probably a good time to remind us what

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<v Speaker 2>Cisco is and what Cisco does. But the memory issue

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<v Speaker 2>is factoring in to servers, and right now you are

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<v Speaker 2>leading with your REACT piece on the Bloomberg terminal with

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<v Speaker 2>the memory chip issue. What do we need to know.

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<v Speaker 4>So really quickly with Cisco, is is the leading global

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<v Speaker 4>provider of a networking equipment for corporate as well as

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<v Speaker 4>for data centers, and they've actually had a foray into

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<v Speaker 4>cloud data centers to help power some of the AI workloads. Now,

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<v Speaker 4>what happened last quarter? They got the AI orders, you know,

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<v Speaker 4>momentum and drove a lot of the upside on sales,

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<v Speaker 4>but the gross margin issue especially given from the dram,

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<v Speaker 4>pricing is a lot bigger than we had thought.

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<v Speaker 3>Chuck Robins, though, was trying to say that, like, if

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<v Speaker 3>anyone's going to navigate this, they're going to navigate it.

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<v Speaker 3>They're already going to their suppliers. They're already thinking about

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<v Speaker 3>increasing prices. How well can they handle it?

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<v Speaker 4>Yeah, So we did the math for the third quarter,

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<v Speaker 4>there's about two hundred basis point product derosion on gross margin.

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<v Speaker 4>But when we look at the fourth quarter, you know

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<v Speaker 4>they're able to stabilize that. Now, if we think about

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<v Speaker 4>twenty twenty seven, they actually have a fairly sizable software business,

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<v Speaker 4>and if software really starts wrapping up, we could start

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<v Speaker 4>seeing some gross mogstability in twenty twenty seven.

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<v Speaker 3>W Jino Blomberg Intelligence. There we have your p Cisco's

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<v Speaker 3>results outlook pinched by memory price spike. Look, all of

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<v Speaker 3>this is as Cisco's numbers. They highlight the heavy infrastructure

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<v Speaker 3>build out, but have investors really questioning what happens next

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<v Speaker 3>for the implications to software too, joining us now to

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<v Speaker 3>go across the whole gamut. As Tony one portfolio manager

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<v Speaker 3>tro Price Science and Technology Fund in his latest thoughts,

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<v Speaker 3>he says that the recent software sell off is more

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<v Speaker 3>of a valuation reset and that companies that successfully embed

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<v Speaker 3>AI into workflows could drive stronger productivity and margins over time.

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<v Speaker 3>And Tony, what's so great about having your voice on this?

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<v Speaker 3>Shows you time and time again have been like the

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<v Speaker 3>proof point the ROI is going to be productivity gains.

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<v Speaker 3>Suddenly we've got the productivity gains. Saw a shining a

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<v Speaker 3>light that we're actually worried it's going to really hit valuations.

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<v Speaker 3>How do you weigh where we are in terms of

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<v Speaker 3>the selloff and if it's overdone?

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<v Speaker 5>Yeah, well, I think it's the key question the market

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<v Speaker 5>is wrestling with bright now. And so when I think

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<v Speaker 5>about it, it's it's really just what is on the

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<v Speaker 5>right side of change, I think, and what is the

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<v Speaker 5>inevitability here? And I think what you're seeing with plod

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<v Speaker 5>cowork is that these agents are becoming more autonomous and

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<v Speaker 5>they can actually execute things on their own, do more

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<v Speaker 5>than just like you have to prompt something like chat

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<v Speaker 5>to be team, you know, for for your your own

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<v Speaker 5>personal chat bete. But so what it's it's exciting is

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<v Speaker 5>that these enterprise agents, I think, are going to be

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<v Speaker 5>more more of a force here and as we're starting

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<v Speaker 5>to see that really pay off. And when we think

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<v Speaker 5>about it, like I think the why the markets reacting

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<v Speaker 5>to the way it is because if you think about

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<v Speaker 5>it in the in the future, like, there are wide

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<v Speaker 5>sweeping implications for what modes mean, like in terms of

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<v Speaker 5>software as well as information services. So it's definitely a

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<v Speaker 5>disruptive potential force here.

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<v Speaker 3>Disruptive to some of those in your portfolio. I'm looking

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<v Speaker 3>you are exposed to salesforce, you are exposed to accenture,

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<v Speaker 3>which people have been worrying about the consultants side of

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<v Speaker 3>the equation. Even Shopify and delimit strong numbers got beaten

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<v Speaker 3>up yesterday. How are you being discerning at this moment

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<v Speaker 3>of where you actually buy into on a dip because

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<v Speaker 3>you do think that they'll manage to ride the software disruption.

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<v Speaker 5>Yeah, so I think that you know there it's more

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<v Speaker 5>important that you are the platform and not just a feature.

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<v Speaker 5>Because you're a feature than AI agents can encode software

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<v Speaker 5>so easily and coustiously that you essentially can be embedded

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<v Speaker 5>in a bigger platform. And so I think that increasingly

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<v Speaker 5>you want to make sure that you're the layer that

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<v Speaker 5>all these agents need to coalesce around, and I think

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<v Speaker 5>that there's going to be a lot of change here

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<v Speaker 5>in terms of and we honestly don't know. And so

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<v Speaker 5>I think the market is in a sell first and

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<v Speaker 5>ask questions later mode, and so it's important to kind

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<v Speaker 5>of stay on the right side and manage these these

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<v Speaker 5>changes in the market.

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<v Speaker 2>Tiny Nvidia CEO agents one has this line that software

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<v Speaker 2>where is now worth paying for? The example he would

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<v Speaker 2>give is Cursor. But I guess what we're trying to

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<v Speaker 2>do with you is define what software is that is

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<v Speaker 2>worth paying for. You just brought up Salesforce, right, so

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<v Speaker 2>in the most recent quarter they had like more than

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<v Speaker 2>a billion dollars of arr directly from AI and they

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<v Speaker 2>talk about all the almost nineteen thousand agent force deals

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<v Speaker 2>that they have, yet they're still subject to this same

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<v Speaker 2>AI is going to eat software's lunch chat that's going

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<v Speaker 2>on right now. Why do people not believe the traction

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<v Speaker 2>that they have as an example that it's worth paying for.

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<v Speaker 6>Yeah, So I think.

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<v Speaker 2>There's two things that I think about.

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<v Speaker 5>One is that there's just so much competition when you

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<v Speaker 5>think about all these AI neted startups and they're pricing

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<v Speaker 5>in a way that is really compelling and to drive

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<v Speaker 5>ad option essentially, So you think about like image generation, right,

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<v Speaker 5>like you pay twenty dollars at chat to bet you

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<v Speaker 5>can generate unloaded images, whereas on Adobe or Firefly you

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<v Speaker 5>have to pay per image generation. But you know, you

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<v Speaker 5>can think about you know, cloud cowords in a similar

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<v Speaker 5>way in terms of what they're pricing versus the value

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<v Speaker 5>that they're delivering is really compelling. And so I think,

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<v Speaker 5>what you just have a lot of price inflation, and

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<v Speaker 5>that's why I think a lot of these you know,

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<v Speaker 5>software companies are looking to drive adoption. You know, the

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<v Speaker 5>economics aren't as good as the seat based model, and

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<v Speaker 5>we're going from like a sea based model to outcomes

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<v Speaker 5>and agents, which is a very different, different version.

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<v Speaker 2>Just for reference to audience. And as that one hundred

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<v Speaker 2>near session low is now down one and a quarter percent.

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<v Speaker 2>This story started in Europe in August. I was there

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<v Speaker 2>in London. I remember the day all the European software

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<v Speaker 2>that was sold off. Earlier today we spoke to the

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<v Speaker 2>ceman CEO. Let's get his take.

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<v Speaker 7>We know that AI has the potential to disrupt some

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<v Speaker 7>of the software businesses. I mean, if you talk about software,

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<v Speaker 7>it runs on call centers and the like. I mean,

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<v Speaker 7>that's fully on the block. But if you go on

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<v Speaker 7>the other end on industrial software, simulation software, physics, space software,

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<v Speaker 7>let's we don't see that at all. We rather see

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<v Speaker 7>an enrichment of the software which allows more and more

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<v Speaker 7>customers to use it.

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<v Speaker 2>Another software CEO whose fate is very closely tied to

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<v Speaker 2>a relationship with Nvideo, and I think it's important to

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<v Speaker 2>point that out. But his argument is that actually specialized

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<v Speaker 2>software is getting better because of AI. You buy that.

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<v Speaker 5>I think so, And I think that most I think

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<v Speaker 5>a lot of the economics that we've made and the

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<v Speaker 5>specialization of the niches, so you know, domain specific knowledge

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<v Speaker 5>will always be very important, and so you know, I

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<v Speaker 5>think just general knowledge is probably going to be not

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<v Speaker 5>take the economics, and so what really matters is like

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<v Speaker 5>being able to put this into ROI now. At the

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<v Speaker 5>same time, it doesn't mean that if you have a

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<v Speaker 5>stronger model, that doesn't mean it doesn't create more competition

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<v Speaker 5>for existing comments. So I don't think the battle is

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<v Speaker 5>one or loss for these companies, and I think it's

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<v Speaker 5>just important that they stay you know, front footed and

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<v Speaker 5>incorporating the latest technology trends into their.

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<v Speaker 3>Platform and your science Technology fund has all the trends.

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<v Speaker 3>You're in hardware, you're in software, you're number one holding

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<v Speaker 3>is alphabet at the moment, then in video. But going

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<v Speaker 3>back full circle to Cisco who exposure there? What do

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<v Speaker 3>you think about the memory price implications and how you

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<v Speaker 3>can weather who are the winners and loses in that situation?

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<v Speaker 2>How long for?

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<v Speaker 5>Yeah, So I think that you know, memory is fascinating

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<v Speaker 5>industry because one is secular trends and AI is now

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<v Speaker 5>this new tam and then we've also gone through multiple

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<v Speaker 5>years of under investment because memory has been a downturn.

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<v Speaker 6>So I think one it.

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<v Speaker 5>Is that they're secular, but there's also cyclcal elements a bit.

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<v Speaker 5>So you know, in terms of our portfolio, we definitely

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<v Speaker 5>own a lot of the bottlenecks where the economic value

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<v Speaker 5>capture is in such as memory. At the same time,

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<v Speaker 5>I think that you know, Cisco networking and this is

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<v Speaker 5>also going to be part of in AI. I think

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<v Speaker 5>that the implications of the memory a shortage is actually

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<v Speaker 5>becoming more widespread and having implications that a.

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<v Speaker 2>Lot of times the market didn't think about.

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<v Speaker 5>So you know, it is fascinating, But I do think

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<v Speaker 5>Cisco continue to be a really impeign company that's driving

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<v Speaker 5>a lot on this AI adoption tourny one.

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<v Speaker 2>Duro price great heavy back on Bloomberg Tech. Really appreciate it.

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<v Speaker 2>Now coming up, Apple's new Sery runs into more snags

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<v Speaker 2>during testing. What's delaying the AI up grade? We have

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<v Speaker 2>the Bloomberg recording next, This is Bloomberg Tech. Apple's revamp

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<v Speaker 2>of its Siri voice assistant has hit new challenges that

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<v Speaker 2>could delay the release of some features, according to sources,

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<v Speaker 2>Bloombo's Mark German, as always, has the details. Let's get

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<v Speaker 2>into the details. What do we need to know? What

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<v Speaker 2>you what are you hearing from inside the company about

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<v Speaker 2>the latest snag with artificial intelligence powered Sery.

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<v Speaker 8>So Apple has been planning to launch the new Seri.

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<v Speaker 9>This is an AI revamp that initially introduced in June

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<v Speaker 9>twenty twenty four at its Developers conference, and I'm going

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<v Speaker 9>to tap into features like your personal data to fulfill

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<v Speaker 9>queries onstream content and precise control of apps. It was

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<v Speaker 9>supposed to launch next month in March. Is part of

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<v Speaker 9>an update called iOS twenty six point four. This had

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<v Speaker 9>been the plan for several months. It's actually been the

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<v Speaker 9>plan for well over a year at this point. Now

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<v Speaker 9>that is being delayed and staggered potentially right now. The

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<v Speaker 9>delay is moving many of the serie capabilities to iOS

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<v Speaker 9>twenty six dot five that's scheduled for some time in

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<v Speaker 9>May June, so about a couple month delay. But some

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<v Speaker 9>of the features, including the personal context features, those are

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<v Speaker 9>likely not to launch until September as part of iOS

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<v Speaker 9>twenty seven, so a bit of a delay there, you know. Altogether,

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<v Speaker 9>it's possible that these new features are not going to

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<v Speaker 9>launch until two years after they were initially introduced. The

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<v Speaker 9>setback for Apple here is not necessarily in bone sales.

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<v Speaker 9>People are still buying iPhones. You saw the eighty five

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<v Speaker 9>billion dollars worth of sales, which could have even been

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<v Speaker 9>more if not for some manufacturing challenges. But the challenge

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<v Speaker 9>is where is OpenAI whereas anthropic? Where are Google going

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<v Speaker 9>to be at the end of this year? Right, They're

0:12:25.080 --> 0:12:27.520
<v Speaker 9>likely to be well ahead where they are today. So

0:12:27.840 --> 0:12:29.600
<v Speaker 9>that's really what we have to pay attention to.

0:12:30.840 --> 0:12:34.760
<v Speaker 3>Mett's talk Mark about how therefore the Google introgation is going,

0:12:34.880 --> 0:12:37.559
<v Speaker 3>because in many ways it just fits into the overall

0:12:37.600 --> 0:12:40.320
<v Speaker 3>Apple intelligence stop start and how they're going to be

0:12:40.320 --> 0:12:41.319
<v Speaker 3>building out from within.

0:12:43.559 --> 0:12:45.880
<v Speaker 9>My belief is the only reason they're going to be

0:12:45.960 --> 0:12:48.680
<v Speaker 9>able to get this done this year, which I still

0:12:48.679 --> 0:12:51.560
<v Speaker 9>believe they're going to do despite these latest snags during testing,

0:12:52.000 --> 0:12:54.839
<v Speaker 9>is because their models are being improved by the Google

0:12:54.880 --> 0:12:58.439
<v Speaker 9>Gemini team as part of that collaboration between the research

0:12:58.640 --> 0:13:01.680
<v Speaker 9>labs at both Apple and Google. So that is going

0:13:01.720 --> 0:13:04.560
<v Speaker 9>to be a major boon for them. I do expect

0:13:04.640 --> 0:13:08.040
<v Speaker 9>this big serie chatbot revamp in iOS twenty seven coming

0:13:08.040 --> 0:13:10.920
<v Speaker 9>out with the iPhones in the fall to be pretty

0:13:10.960 --> 0:13:13.120
<v Speaker 9>nifty and pretty cool, a new way to control your

0:13:13.120 --> 0:13:16.000
<v Speaker 9>phone with AI. They just need to pull it off,

0:13:16.080 --> 0:13:18.920
<v Speaker 9>and I think they will. But the big question is

0:13:18.960 --> 0:13:22.200
<v Speaker 9>how impressive is it going to be in September compared

0:13:22.200 --> 0:13:25.160
<v Speaker 9>to whatever Open AI in Gemini has for their own

0:13:25.200 --> 0:13:28.600
<v Speaker 9>customers and bropias with Quad in six months from now.

0:13:30.280 --> 0:13:34.040
<v Speaker 3>Bloomberg's Mark German, we appreciate you on all things latest

0:13:34.040 --> 0:13:36.840
<v Speaker 3>with Apple. Meanwhile, let's turn our attention to social media now,

0:13:36.920 --> 0:13:39.920
<v Speaker 3>because Instagram boss Adam Massari testified in a landmark case

0:13:40.080 --> 0:13:43.200
<v Speaker 3>they're like in social media to digital casinos. Masari told

0:13:43.240 --> 0:13:46.120
<v Speaker 3>the jury he doesn't consider problematic use of platforms like

0:13:46.200 --> 0:13:49.880
<v Speaker 3>meta to be the same as quote critical addiction. Blom

0:13:49.920 --> 0:13:52.600
<v Speaker 3>Meg's legal reporter Madlyn Mackelberg is with us. You were

0:13:52.640 --> 0:13:56.600
<v Speaker 3>there in the hearing, NLA, and so the push on

0:13:56.679 --> 0:13:59.719
<v Speaker 3>Adam Massari anything different. We've heard on other occasions that

0:13:59.800 --> 0:14:00.520
<v Speaker 3>he's testified.

0:14:02.360 --> 0:14:04.680
<v Speaker 10>So he covered a lot of similar ground to things

0:14:04.679 --> 0:14:08.160
<v Speaker 10>that we've heard before in congressional testimony and other public

0:14:08.240 --> 0:14:12.800
<v Speaker 10>remarks about this issue of social media addiction. Obviously, what's

0:14:12.880 --> 0:14:15.840
<v Speaker 10>unique here is the context in which he was giving

0:14:15.880 --> 0:14:19.760
<v Speaker 10>this testimony, which is this landmark case that's testing whether

0:14:19.880 --> 0:14:23.520
<v Speaker 10>juries will respond to claims that these companies knowingly designed

0:14:23.560 --> 0:14:26.560
<v Speaker 10>their platforms to addict young users. But we heard him

0:14:26.560 --> 0:14:29.080
<v Speaker 10>cover a lot of different ground. As you noted, he

0:14:29.200 --> 0:14:33.160
<v Speaker 10>talked about this issue of clinical addiction versus problematic use,

0:14:33.200 --> 0:14:35.800
<v Speaker 10>which is something that we hear a lot from social

0:14:35.840 --> 0:14:39.200
<v Speaker 10>media companies, referring to people who use the platforms more

0:14:39.240 --> 0:14:42.200
<v Speaker 10>than maybe they feel good about. We also heard him

0:14:42.240 --> 0:14:45.360
<v Speaker 10>talk about some internal emails in the company when he

0:14:45.440 --> 0:14:48.200
<v Speaker 10>was asked about them by the lawyer about decisions they

0:14:48.200 --> 0:14:51.800
<v Speaker 10>were weighing about certain features on the platform related to

0:14:51.880 --> 0:14:53.600
<v Speaker 10>photo filters on Instagram.

0:14:54.720 --> 0:14:58.640
<v Speaker 2>Mad this is a process, right, both sides present arguments

0:14:58.760 --> 0:15:01.280
<v Speaker 2>of plaintiffs, what do we need to know about what

0:15:01.320 --> 0:15:06.320
<v Speaker 2>happens next, who else might testify, and what is under

0:15:06.320 --> 0:15:11.480
<v Speaker 2>consideration at the cort of the trial. That's right.

0:15:11.560 --> 0:15:14.840
<v Speaker 10>So we're in week one of what's expected to be

0:15:14.960 --> 0:15:18.600
<v Speaker 10>an eight week trial. Adam Asseri was the first executive

0:15:18.640 --> 0:15:20.640
<v Speaker 10>to be called to the stand, but he will certainly

0:15:20.640 --> 0:15:22.800
<v Speaker 10>not be the last. As you said, this is the

0:15:22.800 --> 0:15:25.160
<v Speaker 10>plaintiff's case. They kind of get the first chunk of

0:15:25.160 --> 0:15:28.040
<v Speaker 10>time at the trial, and then the defendants in this case,

0:15:28.200 --> 0:15:30.600
<v Speaker 10>Meta in Google, they're going to get a chance to respond.

0:15:31.080 --> 0:15:34.800
<v Speaker 10>We're also expecting to hear from Mark Zuckerberg of Meta,

0:15:34.960 --> 0:15:38.240
<v Speaker 10>We're expecting to hear from YouTube CEO Neil Mohan at

0:15:38.240 --> 0:15:41.080
<v Speaker 10>some point, and we're also we kind of got a

0:15:41.080 --> 0:15:42.640
<v Speaker 10>little bit of a preview that we're going to be

0:15:42.680 --> 0:15:45.240
<v Speaker 10>hearing from executives a little bit further down the food

0:15:45.320 --> 0:15:48.080
<v Speaker 10>chain who maybe we're weighing in on some of these decisions.

0:15:48.560 --> 0:15:51.360
<v Speaker 10>But the heart of this case is about this question

0:15:51.520 --> 0:15:55.280
<v Speaker 10>of addiction and whether or not these platforms knowingly designed

0:15:55.320 --> 0:15:59.560
<v Speaker 10>these tools to hook young users resulting in mental health struggles.

0:16:00.000 --> 0:16:03.080
<v Speaker 10>This case, of course, centers on one individual, a young

0:16:03.120 --> 0:16:07.320
<v Speaker 10>woman from California and her specific allegations, but it represents

0:16:07.360 --> 0:16:09.720
<v Speaker 10>thousands of other cases that have been filed. So there's

0:16:09.720 --> 0:16:12.280
<v Speaker 10>a lot of attention on the outcome here because it's

0:16:12.280 --> 0:16:14.920
<v Speaker 10>going to dictate how the rest of these cases are decided.

0:16:16.000 --> 0:16:19.200
<v Speaker 2>Bloomberg's Madeline Meckeberg, thank you very much. Now coming up,

0:16:19.360 --> 0:16:23.720
<v Speaker 2>Altruist introduces a new AI way to plan your taxes.

0:16:23.800 --> 0:16:27.360
<v Speaker 2>We speak with Jason wenk Voucheris's CEO. Next, this is

0:16:27.360 --> 0:16:28.360
<v Speaker 2>Bloomberg Tech.

0:16:40.200 --> 0:16:40.640
<v Speaker 11>AI.

0:16:41.120 --> 0:16:43.880
<v Speaker 3>It's added again and it's been a wonkey, worrying few

0:16:43.920 --> 0:16:46.560
<v Speaker 3>days for wealth managers and those who had shares in

0:16:46.600 --> 0:16:50.200
<v Speaker 3>it considering the technology's impact. It's all started Tuesday, a

0:16:50.240 --> 0:16:53.680
<v Speaker 3>startup called Altruist added a tax planning tool to its

0:16:53.680 --> 0:16:57.560
<v Speaker 3>AI model Hazel. Within hours, wealth management stocks had tumbled.

0:16:57.640 --> 0:17:01.720
<v Speaker 3>Charles schwab lpl Woymond James, as you see significantly, and

0:17:01.800 --> 0:17:03.080
<v Speaker 3>that's as investors really.

0:17:02.880 --> 0:17:03.960
<v Speaker 11>Feared AI disruption.

0:17:04.080 --> 0:17:07.600
<v Speaker 3>The CEO of the company that kicked all of this off, Altruists,

0:17:07.680 --> 0:17:09.920
<v Speaker 3>Jason Wank Jason, did this citate you?

0:17:10.000 --> 0:17:10.479
<v Speaker 11>I surprise?

0:17:11.119 --> 0:17:14.040
<v Speaker 12>Yeah. I think, to be incredibly honest, I don't think

0:17:14.040 --> 0:17:17.440
<v Speaker 12>anybody could have possibly thought that you know, somewhere between

0:17:17.800 --> 0:17:20.000
<v Speaker 12>you know, tens of billions and maybe one hundred billion

0:17:20.040 --> 0:17:21.680
<v Speaker 12>of market cap would be wiped out in a week.

0:17:22.000 --> 0:17:26.520
<v Speaker 12>AI is very powerful and certainly the market you know

0:17:26.600 --> 0:17:30.240
<v Speaker 12>reaction tells me that there's a lot of people voting

0:17:30.240 --> 0:17:32.280
<v Speaker 12>with their dollars in the potential disruption.

0:17:32.920 --> 0:17:37.520
<v Speaker 3>Jason, all of this is about enabling well wealth managers

0:17:37.520 --> 0:17:40.199
<v Speaker 3>individual wealth managers. From your part, just remind us what

0:17:40.280 --> 0:17:43.160
<v Speaker 3>altruist does and what this new development in terms of

0:17:43.320 --> 0:17:47.159
<v Speaker 3>building in a tax tool does to help them.

0:17:47.240 --> 0:17:48.119
<v Speaker 8>Yeah, absolutely so.

0:17:48.160 --> 0:17:49.760
<v Speaker 12>I think the nail on the head, like the most

0:17:49.800 --> 0:17:53.120
<v Speaker 12>important thing is that we're not trying to displace financial

0:17:53.119 --> 0:17:54.600
<v Speaker 12>advisors or wealth managers.

0:17:54.880 --> 0:17:56.760
<v Speaker 8>It's not AI taking those jobs away.

0:17:56.800 --> 0:17:59.840
<v Speaker 12>It's AI to help empower them to do better work

0:17:59.840 --> 0:18:03.480
<v Speaker 12>for their clients. And in many ways, when people think

0:18:03.520 --> 0:18:08.200
<v Speaker 12>about wealth management, you know, there's there's deservedly a lot

0:18:08.240 --> 0:18:11.159
<v Speaker 12>of critique. It could be things like why is it

0:18:11.240 --> 0:18:14.360
<v Speaker 12>so hard to get access? Like the minimums are really high,

0:18:14.400 --> 0:18:17.480
<v Speaker 12>Why are the costs very high? Why are the results

0:18:17.480 --> 0:18:21.080
<v Speaker 12>sometimes inconsistent? And a lot of that is, you know,

0:18:21.119 --> 0:18:24.480
<v Speaker 12>because of how much manual process and human labors involved.

0:18:24.480 --> 0:18:26.160
<v Speaker 8>You just have a lot of limiting factors.

0:18:26.800 --> 0:18:31.639
<v Speaker 12>AI very much is an incredible equalizer, you know, effectively

0:18:31.800 --> 0:18:34.879
<v Speaker 12>with a tool like Hazel what used to take you know,

0:18:35.040 --> 0:18:38.359
<v Speaker 12>teams that were you know, ten or more people working

0:18:38.480 --> 0:18:41.720
<v Speaker 12>hundreds of hours and costing many tens of thousands of dollars,

0:18:42.320 --> 0:18:44.399
<v Speaker 12>It can be done in like two to three minutes.

0:18:45.200 --> 0:18:47.960
<v Speaker 12>And you know, users, the advisor users in our case

0:18:47.960 --> 0:18:49.879
<v Speaker 12>are paying one hundred is dollars per month, right, so

0:18:50.320 --> 0:18:51.920
<v Speaker 12>much more affordable, much more accessible.

0:18:52.080 --> 0:18:53.680
<v Speaker 8>And tax is just the start.

0:18:53.720 --> 0:18:55.760
<v Speaker 12>We launched tax first for what it's worth, because it's

0:18:55.800 --> 0:18:57.840
<v Speaker 12>tax season in the US. We wanted that to be

0:18:57.880 --> 0:18:59.399
<v Speaker 12>our first agent, you know, to kind of get out

0:18:59.440 --> 0:19:02.479
<v Speaker 12>there in the hands wealth managers and advisors. But this

0:19:02.520 --> 0:19:04.720
<v Speaker 12>is a pretty good harbinger of the things that will come.

0:19:04.760 --> 0:19:07.840
<v Speaker 12>There'll be more agents doing more work that will continue

0:19:07.840 --> 0:19:10.600
<v Speaker 12>to make advice better, more affordable, and more accessible.

0:19:11.960 --> 0:19:14.399
<v Speaker 2>Jason, you will have noticed that some of the CEOs

0:19:14.440 --> 0:19:17.000
<v Speaker 2>of those wealth managers appeared on television in the days

0:19:17.000 --> 0:19:19.840
<v Speaker 2>that followed the selloff. His child swab listened to what

0:19:19.840 --> 0:19:20.520
<v Speaker 2>they had to say.

0:19:21.080 --> 0:19:23.440
<v Speaker 13>AI is a real accelerant. So it was puzzling to

0:19:23.480 --> 0:19:26.680
<v Speaker 13>see our stock sell off related AI because we're benefiting

0:19:26.680 --> 0:19:28.879
<v Speaker 13>it from it in multiple ways and bringing it to

0:19:28.920 --> 0:19:29.600
<v Speaker 13>our clients.

0:19:29.680 --> 0:19:31.719
<v Speaker 2>It's allowing us to reach new clients.

0:19:31.720 --> 0:19:34.280
<v Speaker 13>And I think that's why you won't see the population

0:19:34.680 --> 0:19:37.879
<v Speaker 13>of advisor's shrink, is that AI will be useful in

0:19:38.000 --> 0:19:39.800
<v Speaker 13>reaching new clients that we couldn't before.

0:19:41.200 --> 0:19:44.560
<v Speaker 2>Has mister West or any other leader in that field

0:19:44.640 --> 0:19:47.720
<v Speaker 2>phoned you since Tuesday and would you be open to

0:19:47.840 --> 0:19:53.480
<v Speaker 2>working with these companies literally jointly. Yes.

0:19:53.760 --> 0:19:57.359
<v Speaker 12>So no, I haven't heard directly from mister Worcester, but

0:19:58.160 --> 0:20:01.520
<v Speaker 12>we already actually work with any dependent financial advisor. One

0:20:01.520 --> 0:20:04.119
<v Speaker 12>of the reasons why we stood up Hazel as a

0:20:04.160 --> 0:20:08.000
<v Speaker 12>separate entity altruist of course as a direct competitor to Schwab, Fidelity,

0:20:08.160 --> 0:20:11.600
<v Speaker 12>LPL and others. But we wanted Hazel to be something

0:20:11.640 --> 0:20:14.159
<v Speaker 12>that any advisor could use to help any client, and

0:20:14.200 --> 0:20:16.760
<v Speaker 12>we didn't want them to be forced into using a

0:20:16.800 --> 0:20:21.600
<v Speaker 12>single custodian. So there are already thousands of advisors who

0:20:21.840 --> 0:20:24.960
<v Speaker 12>use Schwab, for example, as a custodian that are leveraging

0:20:25.000 --> 0:20:28.400
<v Speaker 12>Hazel and doing so to drive better outcomes for their

0:20:28.400 --> 0:20:32.560
<v Speaker 12>clients and a lot more operational efficiency for themselves. And

0:20:33.160 --> 0:20:35.680
<v Speaker 12>we have i'd say, in the last forty eight hours.

0:20:36.320 --> 0:20:39.919
<v Speaker 12>It's in the hundreds of very large, significant, you know,

0:20:40.000 --> 0:20:44.160
<v Speaker 12>wealth management companies around the world reaching out to see

0:20:44.160 --> 0:20:45.879
<v Speaker 12>if there's a way that we can partner. So definitely

0:20:45.880 --> 0:20:48.600
<v Speaker 12>looking forward to, you know, putting this tool in as

0:20:48.680 --> 0:20:51.440
<v Speaker 12>many hands of as many capable advisors in the US

0:20:51.480 --> 0:20:52.040
<v Speaker 12>as possible.

0:20:53.680 --> 0:20:55.679
<v Speaker 2>Let's talk about the tool and the technology. You know,

0:20:56.040 --> 0:20:58.480
<v Speaker 2>what are the data sets that the underlying model was

0:20:58.480 --> 0:21:02.720
<v Speaker 2>trained on. What is your coal competence that if there

0:21:02.800 --> 0:21:06.600
<v Speaker 2>is concern from the legacy industry of wealth management, what

0:21:06.680 --> 0:21:09.000
<v Speaker 2>is it they should be concerned about, And what is

0:21:09.000 --> 0:21:10.640
<v Speaker 2>it that makes this model powerful?

0:21:12.160 --> 0:21:14.480
<v Speaker 12>Well, so kind there's two parts that I'll try to

0:21:14.480 --> 0:21:16.840
<v Speaker 12>be succinct. But the first is I think what causes

0:21:16.920 --> 0:21:19.480
<v Speaker 12>concern is not so much just the AI. It's the

0:21:19.520 --> 0:21:22.879
<v Speaker 12>fact that we also have built a very modern infrastructure

0:21:23.040 --> 0:21:25.679
<v Speaker 12>for our wealth business. So the things you can do

0:21:25.720 --> 0:21:29.040
<v Speaker 12>on altruists you just can't do anywhere else in terms

0:21:29.080 --> 0:21:32.040
<v Speaker 12>of the speed of opening accounts and funding accounts and

0:21:32.280 --> 0:21:35.520
<v Speaker 12>managing of assets. If you take AI and you put

0:21:35.560 --> 0:21:39.840
<v Speaker 12>it on top of bad, antiquated infrastructure, you're not going

0:21:39.880 --> 0:21:41.560
<v Speaker 12>to get a ton of value. It's you know, kind

0:21:41.600 --> 0:21:44.199
<v Speaker 12>of akin to putting like a you know, self driving

0:21:44.240 --> 0:21:46.159
<v Speaker 12>on a horse and buggy or something like that, Like

0:21:46.240 --> 0:21:49.560
<v Speaker 12>you need to have like an entire vertically integrated ecosystem.

0:21:50.440 --> 0:21:52.399
<v Speaker 12>I think, if anything, that's maybe where some of the

0:21:52.440 --> 0:21:56.080
<v Speaker 12>market concern is is that what happens if something like

0:21:56.800 --> 0:21:59.320
<v Speaker 12>you know is digital and it's twenty or thirty percent better,

0:21:59.640 --> 0:22:02.240
<v Speaker 12>you add AI and multiple agents, it becomes two or

0:22:02.240 --> 0:22:05.159
<v Speaker 12>three hundred percent better. Now advisors could very much have

0:22:05.200 --> 0:22:07.680
<v Speaker 12>a shift in where they decide to custoy their assets.

0:22:07.800 --> 0:22:11.359
<v Speaker 12>That could be pretty monumentally difficult to overcome for some

0:22:11.400 --> 0:22:12.280
<v Speaker 12>of the big incumbents.

0:22:12.760 --> 0:22:14.359
<v Speaker 8>As far as what makes the model unique.

0:22:14.560 --> 0:22:17.600
<v Speaker 12>The way that we built Hazel's we rely, like most

0:22:17.680 --> 0:22:21.680
<v Speaker 12>AI companies, on having really clean data.

0:22:21.760 --> 0:22:23.160
<v Speaker 8>So data is a huge advantage.

0:22:23.160 --> 0:22:26.280
<v Speaker 12>I think, you know, mister Worcester was right in saying

0:22:26.320 --> 0:22:30.000
<v Speaker 12>that data is very critical. In the case of the custodian.

0:22:30.040 --> 0:22:33.080
<v Speaker 12>You have the ultimate system of record meeting, right. We

0:22:33.119 --> 0:22:36.440
<v Speaker 12>have all of this data on clients transactions. That makes

0:22:36.480 --> 0:22:40.320
<v Speaker 12>it a lot easier to give personalized analysis and feedback

0:22:40.359 --> 0:22:41.200
<v Speaker 12>back to the users.

0:22:42.080 --> 0:22:44.639
<v Speaker 2>Jason Mike Vouchers, Sorry, we're out of time. Grateful for

0:22:44.680 --> 0:22:47.280
<v Speaker 2>the conversation coming out. We look at way moo. We'll

0:22:47.280 --> 0:22:48.920
<v Speaker 2>be right back. This is blue bag attack.

0:23:00.440 --> 0:23:02.480
<v Speaker 3>Welcome back to Bloomberg Tech. A lot of action in

0:23:02.520 --> 0:23:04.320
<v Speaker 3>the markets today, let's just go through it. In terms

0:23:04.320 --> 0:23:06.480
<v Speaker 3>of the NASDA benchmark currently off by one point eight percent,

0:23:06.480 --> 0:23:09.160
<v Speaker 3>we're at session lows. This is as we worry about

0:23:09.200 --> 0:23:11.879
<v Speaker 3>earnings and how they're implicated by prices. Prices and Memory

0:23:11.960 --> 0:23:14.639
<v Speaker 3>Cisco in particular down significantly. I want to shine a

0:23:14.720 --> 0:23:16.760
<v Speaker 3>night and off by eleven percent. So we've got that

0:23:16.840 --> 0:23:20.240
<v Speaker 3>anxiety about whether AI is really helping these businesses or

0:23:20.240 --> 0:23:22.680
<v Speaker 3>whether pricing pressure is hurting them. Remember the macro pictures

0:23:22.720 --> 0:23:25.080
<v Speaker 3>are about get CPI data, so pricing pressure for the

0:23:25.119 --> 0:23:27.399
<v Speaker 3>consumer too. As we build up to that, the market's

0:23:27.480 --> 0:23:30.240
<v Speaker 3>just a little bit jittery. Add Ian over in European

0:23:30.240 --> 0:23:32.679
<v Speaker 3>trading check it out by twenty percent. This is the

0:23:32.680 --> 0:23:36.000
<v Speaker 3>payments company Fintech, which is being hit by consumer.

0:23:35.640 --> 0:23:37.000
<v Speaker 11>Sentiment being on the downside.

0:23:37.000 --> 0:23:39.040
<v Speaker 3>Also a week of dollar hit them as well in

0:23:39.119 --> 0:23:42.480
<v Speaker 3>terms of payments, revenue and their earnings outline, just really

0:23:42.520 --> 0:23:44.600
<v Speaker 3>not living up to expectations. We move on and have

0:23:44.640 --> 0:23:47.119
<v Speaker 3>a think about what's happening when you've got exposure to

0:23:47.160 --> 0:23:50.760
<v Speaker 3>the private sector now many are saying, I'm talking BTIG

0:23:50.880 --> 0:23:53.320
<v Speaker 3>in particular, saying that soft bank is like the way

0:23:53.359 --> 0:23:56.200
<v Speaker 3>to play open Ai exposure as well, because they've already

0:23:56.200 --> 0:23:58.840
<v Speaker 3>put thirty six billion dollars in. They're looking to increase

0:23:58.880 --> 0:24:00.600
<v Speaker 3>that maybe up to the tune of thirds thirty billionaire.

0:24:00.600 --> 0:24:02.639
<v Speaker 3>They have an eleven percent stake in the business, and

0:24:02.680 --> 0:24:05.160
<v Speaker 3>actually they managed to post a profit, the fourth quarterly

0:24:05.160 --> 0:24:07.560
<v Speaker 3>profit in a row, not seen since twenty twenty one,

0:24:07.680 --> 0:24:10.159
<v Speaker 3>as their investment stake in open Ai goes up and

0:24:10.200 --> 0:24:13.480
<v Speaker 3>to the right, helping offset some other losses. But the

0:24:13.520 --> 0:24:16.160
<v Speaker 3>stock traded in the US if you're looking at depository

0:24:16.160 --> 0:24:17.560
<v Speaker 3>receipts currently up by thirty percent.

0:24:17.600 --> 0:24:19.000
<v Speaker 11>So we'll dig into that a little bit more.

0:24:19.080 --> 0:24:19.159
<v Speaker 9>End.

0:24:19.240 --> 0:24:21.240
<v Speaker 3>But it's interesting what's happening in terms of a soft

0:24:21.240 --> 0:24:21.800
<v Speaker 3>bank story.

0:24:22.960 --> 0:24:25.320
<v Speaker 2>It's a little bit like shuffling the deck and like

0:24:25.560 --> 0:24:27.760
<v Speaker 2>you know, you have to sell at certain holdings to

0:24:27.840 --> 0:24:31.600
<v Speaker 2>fund investment deeper into the names that you're most interested in.

0:24:31.760 --> 0:24:34.280
<v Speaker 2>Like it's not rocket science at the end of the day.

0:24:34.320 --> 0:24:36.920
<v Speaker 2>Carry one quick question to ask is like how wide

0:24:36.960 --> 0:24:40.040
<v Speaker 2>soft banks is exposed beyond one single name like open Ai,

0:24:40.640 --> 0:24:43.280
<v Speaker 2>Given how ferocious the lab battle is right now.

0:24:43.440 --> 0:24:46.080
<v Speaker 3>Yeah, opening either in on Remember they've been going into

0:24:46.320 --> 0:24:49.720
<v Speaker 3>chip design companies like I'm peer, they've been looking real

0:24:49.760 --> 0:24:51.800
<v Speaker 3>exposure to ARM but they've been coming back on their

0:24:51.800 --> 0:24:54.359
<v Speaker 3>T mobile exposure to be able to get more into

0:24:54.359 --> 0:24:58.320
<v Speaker 3>these privately held businesses. Also been buying private equity companies

0:24:58.400 --> 0:25:00.359
<v Speaker 3>right because they want the exposure to day to center.

0:25:01.280 --> 0:25:03.200
<v Speaker 2>Yeah, I'm glad the team got that up. I mean,

0:25:03.560 --> 0:25:07.000
<v Speaker 2>you know, far right column says everything. Let's get to

0:25:07.119 --> 0:25:09.120
<v Speaker 2>another story in the private markets that we've been trying

0:25:09.119 --> 0:25:12.800
<v Speaker 2>to update you on regularly. Anthropic is close to locking

0:25:12.840 --> 0:25:14.920
<v Speaker 2>in a deal to raise more than twenty billion dollars

0:25:14.960 --> 0:25:18.120
<v Speaker 2>in a funding round co led by investors including Pieter

0:25:18.240 --> 0:25:22.280
<v Speaker 2>Teal's founder's fund, The Shore and DRAGONEA that's, according to

0:25:22.280 --> 0:25:25.920
<v Speaker 2>Bloomberg's sources, one of the largest startup funding rounds ever.

0:25:26.200 --> 0:25:29.680
<v Speaker 2>And who's been across at Bloomberg's VC reporter Natasha mascarinus

0:25:29.880 --> 0:25:33.359
<v Speaker 2>important detail, Actually, Like some of those names are are interesting.

0:25:34.160 --> 0:25:36.159
<v Speaker 2>You know, dragone has come up a lot recently. Weimo

0:25:36.720 --> 0:25:38.760
<v Speaker 2>was something we reported a couple of weeks ago. What

0:25:38.800 --> 0:25:40.400
<v Speaker 2>do we need to know? Like how close is this

0:25:40.520 --> 0:25:42.320
<v Speaker 2>and who's leading? Yeah, listen.

0:25:42.359 --> 0:25:44.800
<v Speaker 14>On Monday, we were discussing where are the crossover funds

0:25:45.119 --> 0:25:48.000
<v Speaker 14>in this round? Now we have some examples with d Shah,

0:25:48.080 --> 0:25:52.400
<v Speaker 14>with DRAGONEIR. We also have a continuing list of traditional

0:25:52.480 --> 0:25:54.919
<v Speaker 14>venture capitalists in the round. What I'm really paying attention

0:25:55.000 --> 0:25:57.520
<v Speaker 14>to is the addition of Founder's Fund to the cap table.

0:25:57.600 --> 0:26:00.800
<v Speaker 14>That's an early open AI investor and founder just Want

0:26:00.840 --> 0:26:03.080
<v Speaker 14>is known for concentrated bets, So it is interesting to

0:26:03.119 --> 0:26:05.359
<v Speaker 14>see an early open AI investor go ahead and be

0:26:05.400 --> 0:26:07.960
<v Speaker 14>a major investor in this anthropic ground. And Founder's Want

0:26:08.000 --> 0:26:11.359
<v Speaker 14>is not alone. We're seeing Sequoia as well in the round,

0:26:11.920 --> 0:26:12.680
<v Speaker 14>and the list grows.

0:26:13.800 --> 0:26:14.480
<v Speaker 11>It's interesting.

0:26:14.840 --> 0:26:18.440
<v Speaker 3>I know another VEC that makes concentrated bets and doesn't

0:26:18.480 --> 0:26:22.159
<v Speaker 3>go in to other companies that seem to directly compete.

0:26:22.280 --> 0:26:25.200
<v Speaker 3>So how much of a taboo is it that vcs

0:26:25.680 --> 0:26:28.600
<v Speaker 3>back to horses, almost like having some sub option here.

0:26:29.880 --> 0:26:31.920
<v Speaker 14>Yeah, I mean it used to be a huge taboo

0:26:32.160 --> 0:26:35.399
<v Speaker 14>because of concerns about information leakage or how do you

0:26:35.440 --> 0:26:37.080
<v Speaker 14>really take that out of your head when you're in

0:26:37.119 --> 0:26:40.720
<v Speaker 14>a partner meeting and discussing you know two different roadmaps

0:26:40.720 --> 0:26:43.040
<v Speaker 14>that are you know, both in this case going towards

0:26:43.080 --> 0:26:46.320
<v Speaker 14>a version of AGI. What I would say and what

0:26:46.359 --> 0:26:50.520
<v Speaker 14>we are reporting is that certain investors get certain information rights.

0:26:50.520 --> 0:26:52.440
<v Speaker 14>In the case of open AI, sources are telling us

0:26:52.480 --> 0:26:55.560
<v Speaker 14>that if you have a certain amount of ownership in

0:26:55.600 --> 0:26:58.679
<v Speaker 14>the company, that comes with its own information. And so

0:26:58.760 --> 0:27:01.840
<v Speaker 14>what we're really wondering is who's taking big checks in

0:27:01.880 --> 0:27:03.679
<v Speaker 14>these rounds, because they are the ones that will have

0:27:03.720 --> 0:27:06.280
<v Speaker 14>to answer the questions of how are we keeping the

0:27:06.320 --> 0:27:07.840
<v Speaker 14>information separate?

0:27:08.160 --> 0:27:11.479
<v Speaker 2>Bloombergs and Sasha Mascarinas, thank you very much. Now, Waimo

0:27:12.040 --> 0:27:14.600
<v Speaker 2>is aiming to have a big year, adding new US

0:27:14.600 --> 0:27:18.840
<v Speaker 2>and international markets. The robotax firm also recently raised sixteen

0:27:18.880 --> 0:27:22.880
<v Speaker 2>billion dollars from parent Alphabet and other outside investors. Co

0:27:22.960 --> 0:27:26.040
<v Speaker 2>CEO Taqijra Maracana sat down with us and discuss the

0:27:26.040 --> 0:27:30.159
<v Speaker 2>company's plans, including whether it's considering an IPO. Listen to this.

0:27:31.000 --> 0:27:34.439
<v Speaker 15>We are just laser focused on execution, you know, building

0:27:34.480 --> 0:27:38.879
<v Speaker 15>weimo to be financially responsible, operationally excellent, and then make

0:27:38.920 --> 0:27:42.160
<v Speaker 15>sure we maintain the safety culture. Like that's what we're

0:27:42.200 --> 0:27:45.480
<v Speaker 15>really focused on. Having this vote of confidence, as you said,

0:27:45.520 --> 0:27:48.960
<v Speaker 15>not only from Alphabet, but from our three colleagues. From

0:27:48.960 --> 0:27:52.000
<v Speaker 15>this round and from all of the new investors who

0:27:52.080 --> 0:27:55.000
<v Speaker 15>decided to join our cap table and the existing ones

0:27:55.200 --> 0:27:57.439
<v Speaker 15>who doubled down on their belief that this is the

0:27:57.520 --> 0:28:02.240
<v Speaker 15>right opportunity to fund, and we just feel humbled, but

0:28:02.280 --> 0:28:05.280
<v Speaker 15>also there's a lot to do, so we're really focused

0:28:05.320 --> 0:28:07.840
<v Speaker 15>on making sure that we can scale, focusing on our

0:28:07.880 --> 0:28:12.000
<v Speaker 15>two first international launches, you know, London and Tokyo, and

0:28:12.200 --> 0:28:13.880
<v Speaker 15>scaling across the United States.

0:28:14.200 --> 0:28:16.840
<v Speaker 2>We do not yet have, although there has been progress

0:28:16.880 --> 0:28:21.560
<v Speaker 2>towards just this week, a federal level framework set of rules.

0:28:23.119 --> 0:28:26.520
<v Speaker 2>What do you think the direction of travel is with that?

0:28:26.760 --> 0:28:29.280
<v Speaker 2>And you know, clearly if you had to deal with

0:28:29.280 --> 0:28:31.120
<v Speaker 2>one set of rules and not a city by city,

0:28:31.200 --> 0:28:35.199
<v Speaker 2>let alone state by state basis or case, you'd be

0:28:35.280 --> 0:28:37.480
<v Speaker 2>making a bit more progress. I suppose.

0:28:37.920 --> 0:28:40.360
<v Speaker 15>Yeah, we think it's really important that there is a

0:28:40.400 --> 0:28:45.200
<v Speaker 15>federal av standard. We've been advocating for sort of a

0:28:45.240 --> 0:28:49.440
<v Speaker 15>safety case based approach because the technologies are different and

0:28:49.480 --> 0:28:51.680
<v Speaker 15>we think that the burdens should be on companies to

0:28:51.760 --> 0:28:54.880
<v Speaker 15>demonstrate why you believe your technology is safe enough. We

0:28:54.920 --> 0:28:58.200
<v Speaker 15>also think there should be transparency requirements. You know, people

0:28:58.200 --> 0:29:00.640
<v Speaker 15>should have to demonstrate how many trips.

0:29:00.240 --> 0:29:01.040
<v Speaker 16>Are you providing?

0:29:01.240 --> 0:29:02.920
<v Speaker 15>You know, I don't right now.

0:29:03.120 --> 0:29:04.400
<v Speaker 2>The balance isn't quite there.

0:29:04.440 --> 0:29:07.280
<v Speaker 15>I mean, some states require a lot of reporting, some

0:29:07.360 --> 0:29:10.520
<v Speaker 15>don't require as much reporting. I think the United States

0:29:10.560 --> 0:29:14.160
<v Speaker 15>has an opportunity with this technology to lead globally, and

0:29:14.160 --> 0:29:16.719
<v Speaker 15>I don't think you can lead globally if it's a

0:29:16.760 --> 0:29:20.920
<v Speaker 15>framework that's governed by multiple jurisdictions across the states. And

0:29:21.000 --> 0:29:23.600
<v Speaker 15>it's a way to slow down the adoption of this

0:29:23.720 --> 0:29:26.880
<v Speaker 15>technology not only in the US, but in other markets.

0:29:27.760 --> 0:29:31.400
<v Speaker 2>New York City, New York City, not necessarily New York State.

0:29:31.920 --> 0:29:34.880
<v Speaker 2>A lot of people want to know what's the roadblock

0:29:34.920 --> 0:29:39.520
<v Speaker 2>there upon the expression and what's the timeline. You know,

0:29:40.120 --> 0:29:43.960
<v Speaker 2>you work closely with the authorities, but that is a

0:29:43.960 --> 0:29:45.240
<v Speaker 2>big potential market.

0:29:45.640 --> 0:29:47.760
<v Speaker 15>Yeah, that's a market where you know, we're just going

0:29:47.840 --> 0:29:51.160
<v Speaker 15>to have to do the work and demonstrate our safety

0:29:51.200 --> 0:29:54.840
<v Speaker 15>outcomes and earn the trust and shizzle away at it

0:29:54.920 --> 0:29:55.360
<v Speaker 15>over time.

0:29:55.400 --> 0:29:57.160
<v Speaker 2>Do they have the rules for you to follow?

0:29:57.560 --> 0:30:01.240
<v Speaker 15>They do not have rules that allow the human operator

0:30:01.320 --> 0:30:03.520
<v Speaker 15>to be removed from vehicle entirely.

0:30:03.280 --> 0:30:05.760
<v Speaker 2>And until that changes, and until that changes.

0:30:05.880 --> 0:30:08.520
<v Speaker 15>But you know, there is an interest in doing this

0:30:08.640 --> 0:30:11.000
<v Speaker 15>in the state, even outside of the city, and that

0:30:11.040 --> 0:30:14.440
<v Speaker 15>gives us an opportunity to grow more fans, and fans

0:30:14.560 --> 0:30:18.000
<v Speaker 15>actually are calling for this in cities where our technology

0:30:18.040 --> 0:30:21.760
<v Speaker 15>can't be deployed. We are seeing organic campaigns spring up

0:30:22.080 --> 0:30:24.000
<v Speaker 15>saying I want WEIMO in my town.

0:30:24.000 --> 0:30:28.520
<v Speaker 2>San Francisco. The Bay Area is my home. London's where

0:30:28.520 --> 0:30:31.040
<v Speaker 2>I grew up. And I was studying the map of

0:30:31.080 --> 0:30:35.880
<v Speaker 2>the burros that you propose to launch in and you

0:30:35.920 --> 0:30:38.120
<v Speaker 2>correct me if my math is wrong, but just based

0:30:38.160 --> 0:30:41.120
<v Speaker 2>on those burroughs at launch, this seems to be the

0:30:41.160 --> 0:30:45.520
<v Speaker 2>biggest citywide deployment from the start that you guys will

0:30:45.560 --> 0:30:47.360
<v Speaker 2>have done. Is that correct?

0:30:49.360 --> 0:30:49.440
<v Speaker 17>It?

0:30:49.600 --> 0:30:50.880
<v Speaker 2>Possibly, it's correct.

0:30:50.880 --> 0:30:53.360
<v Speaker 15>I mean, we're in the phases of figuring out the

0:30:53.440 --> 0:30:57.120
<v Speaker 15>specifics around the launch and figuring out the actual framework

0:30:57.200 --> 0:30:59.200
<v Speaker 15>around the launch, and so I don't want to speak

0:30:59.240 --> 0:31:01.600
<v Speaker 15>to definitive word about what we're going to do. But

0:31:01.840 --> 0:31:05.880
<v Speaker 15>what you're speaking to is we're not gated by the technology, right,

0:31:06.000 --> 0:31:08.640
<v Speaker 15>and we have the appetite to scale, and we want

0:31:08.640 --> 0:31:11.080
<v Speaker 15>to partner and do so safely, and we want to

0:31:11.120 --> 0:31:13.680
<v Speaker 15>earn trust. So that's like there's a lot of levers

0:31:13.720 --> 0:31:16.240
<v Speaker 15>there that we have to figure out how to strike

0:31:16.280 --> 0:31:18.120
<v Speaker 15>the right balance and how to make sure that we're

0:31:18.160 --> 0:31:21.080
<v Speaker 15>introducing it to the community both to meet the demand

0:31:21.120 --> 0:31:21.840
<v Speaker 15>and a grow I.

0:31:21.840 --> 0:31:24.920
<v Speaker 2>Asked, because of those twenty cities to come, London is one, yes,

0:31:25.440 --> 0:31:28.440
<v Speaker 2>and London is now outside of the European Union, but

0:31:28.480 --> 0:31:30.800
<v Speaker 2>it's you know, it's kind of your europe launch. Yes,

0:31:31.280 --> 0:31:34.880
<v Speaker 2>what was that experience like? Within London's regulatory framework and

0:31:35.200 --> 0:31:37.520
<v Speaker 2>the UK's regulatory framework.

0:31:37.160 --> 0:31:41.640
<v Speaker 15>They've been extremely forward leaning and interested in seeing how

0:31:41.680 --> 0:31:44.560
<v Speaker 15>this technology could actually improve safety.

0:31:44.120 --> 0:31:44.960
<v Speaker 11>On their roadways.

0:31:45.240 --> 0:31:47.040
<v Speaker 15>And that's where I think, you know, we find a

0:31:47.080 --> 0:31:52.240
<v Speaker 15>sweet spot when people are less sort of complacent about

0:31:52.240 --> 0:31:52.960
<v Speaker 15>the status quo.

0:31:53.520 --> 0:31:57.840
<v Speaker 3>Weimo co CEO to Keedra Mawakana ed. I mean, we've

0:31:57.880 --> 0:31:59.880
<v Speaker 3>got to check out the full interview. It's on Bloomberg

0:32:00.720 --> 0:32:03.440
<v Speaker 3>or as a special edition of Bloomberg Tech Podcast. But

0:32:04.040 --> 0:32:07.440
<v Speaker 3>really your conversation is about this extrawnay expansion into London

0:32:07.600 --> 0:32:11.960
<v Speaker 3>and just what pace of growth, what signals you discerning

0:32:12.040 --> 0:32:13.320
<v Speaker 3>as to how big it can be there.

0:32:14.040 --> 0:32:15.960
<v Speaker 2>Now you and I have both called London home, right

0:32:16.000 --> 0:32:18.520
<v Speaker 2>and we've taken the bus and the tube and gone

0:32:18.560 --> 0:32:21.520
<v Speaker 2>on bikes, and so how do they get past what's

0:32:21.520 --> 0:32:24.720
<v Speaker 2>a really established transit network and right now there are

0:32:24.880 --> 0:32:29.080
<v Speaker 2>several dozen Waymo vehicles testing in London. They are doing

0:32:29.120 --> 0:32:31.960
<v Speaker 2>that in more than thirty of the sixty London boroughs,

0:32:32.280 --> 0:32:34.600
<v Speaker 2>you know, like sixty percent of the city's already covered.

0:32:34.720 --> 0:32:37.600
<v Speaker 2>That's way beyond what, for example, Tesla's doing in Austin

0:32:37.720 --> 0:32:40.440
<v Speaker 2>right even the Bay Area here in terms of their

0:32:40.480 --> 0:32:43.760
<v Speaker 2>scale on footprint. So there's a big expectation that if

0:32:44.000 --> 0:32:47.800
<v Speaker 2>this labor government is doing okay and passes the rules,

0:32:48.200 --> 0:32:50.400
<v Speaker 2>then they can do this for real this year, no

0:32:50.560 --> 0:32:53.720
<v Speaker 2>safety driver or supervisor and have a commercial service at

0:32:53.760 --> 0:32:56.960
<v Speaker 2>scale that they haven't done that quickly in the United States.

0:32:57.080 --> 0:33:00.520
<v Speaker 3>Look, this is about disruption of transport, and it looks

0:33:00.560 --> 0:33:02.840
<v Speaker 3>as though transport and logistics is in the either storm

0:33:02.880 --> 0:33:04.560
<v Speaker 3>in terms of disruption today as well. If you're looking

0:33:04.600 --> 0:33:06.320
<v Speaker 3>at the markets now, you and I have just been

0:33:06.320 --> 0:33:09.000
<v Speaker 3>pouring over some of these market moves extraordinary for c H.

0:33:09.080 --> 0:33:11.560
<v Speaker 3>Robinson down by twenty one percent, but you're actually seeing

0:33:11.560 --> 0:33:14.560
<v Speaker 3>the Dow Transports the index having its worst day since

0:33:14.600 --> 0:33:17.880
<v Speaker 3>April of twenty twenty five, currently down by five percent.

0:33:18.240 --> 0:33:21.800
<v Speaker 3>Now traders are telling Bloomberg Kuneneagel, for example, which is

0:33:21.840 --> 0:33:26.400
<v Speaker 3>another European logistics company, traders are citing an announcement coming

0:33:26.400 --> 0:33:27.800
<v Speaker 3>from Algorithm Now.

0:33:27.840 --> 0:33:29.640
<v Speaker 11>Algorithm is a.

0:33:29.360 --> 0:33:32.280
<v Speaker 3>US traded company and they've announced that as a leading

0:33:32.280 --> 0:33:35.840
<v Speaker 3>AI technology company. They've published a new white paper demonstrating

0:33:35.880 --> 0:33:40.160
<v Speaker 3>its semi cab platform reduces empty freight miles by more

0:33:40.200 --> 0:33:42.920
<v Speaker 3>than seventy percent across active customer networks. Is this the

0:33:43.000 --> 0:33:44.640
<v Speaker 3>next aishooter drop ed?

0:33:45.520 --> 0:33:47.520
<v Speaker 2>It was a severe sharp drop and we got to

0:33:47.600 --> 0:33:49.920
<v Speaker 2>keep looking into it. Coming up from the program Back

0:33:49.960 --> 0:33:53.280
<v Speaker 2>to Ai similarly secures one hundred million dollars in new

0:33:53.280 --> 0:33:59.480
<v Speaker 2>funding as it looks to scale predictive AI mimics human behavior.

0:34:00.000 --> 0:34:02.480
<v Speaker 2>We have more on that next. This is Bloomberg Tech.

0:34:14.160 --> 0:34:17.640
<v Speaker 2>AIS Startups similarly has raised one hundred million dollars in

0:34:17.680 --> 0:34:20.319
<v Speaker 2>a new funding round led by Index Ventures. Similarly as

0:34:20.320 --> 0:34:24.600
<v Speaker 2>an AI lab, the wantes to help companies predict human behavior,

0:34:24.880 --> 0:34:27.720
<v Speaker 2>in fact a chain of human behaviors for more. June

0:34:27.760 --> 0:34:30.440
<v Speaker 2>Park similarly CEO and one of the founding group is

0:34:30.480 --> 0:34:33.720
<v Speaker 2>with us in San Francisco. This is very interesting because

0:34:33.760 --> 0:34:37.759
<v Speaker 2>the field has tried to develop a model that is

0:34:38.040 --> 0:34:42.240
<v Speaker 2>a behavior model, and it has had mixed success some failure.

0:34:43.239 --> 0:34:46.799
<v Speaker 2>Let's start by talking about the data sets that the

0:34:46.800 --> 0:34:50.040
<v Speaker 2>model's trained on. How did you develop what you think

0:34:50.080 --> 0:34:53.120
<v Speaker 2>is a model that does give you an insight or

0:34:53.120 --> 0:34:56.560
<v Speaker 2>a prediction of how a human might behave? Absolutely, thank

0:34:56.600 --> 0:34:58.080
<v Speaker 2>you for having me. Glad to be here.

0:34:58.520 --> 0:35:00.920
<v Speaker 17>So similarly is a company that are spinning out of

0:35:00.960 --> 0:35:05.000
<v Speaker 17>Stanford where we led frontier research on creating agents and

0:35:05.080 --> 0:35:08.920
<v Speaker 17>simulations that leverages generate to BAI technology. So today we

0:35:09.080 --> 0:35:12.359
<v Speaker 17>partner with millions of real people and combine our data

0:35:12.400 --> 0:35:16.440
<v Speaker 17>collection strategy with our modeling strategy to create agents that

0:35:16.480 --> 0:35:20.120
<v Speaker 17>can actually behave in a much more generalizable context. So

0:35:20.280 --> 0:35:23.799
<v Speaker 17>data here we might leverage include interview data that's unstructured,

0:35:23.960 --> 0:35:25.799
<v Speaker 17>which is the kind of data in the past was

0:35:25.920 --> 0:35:26.600
<v Speaker 17>very hard to.

0:35:26.600 --> 0:35:29.879
<v Speaker 2>Leverage literally people telling you their life stories. That's exactly right.

0:35:30.239 --> 0:35:33.520
<v Speaker 17>So we actually create ai interviewer that can go talk

0:35:33.520 --> 0:35:36.240
<v Speaker 17>to people one on one, voice to voice and actually

0:35:36.239 --> 0:35:39.680
<v Speaker 17>get life stories and their preferences around different policies and

0:35:39.719 --> 0:35:41.160
<v Speaker 17>so forth with their consent.

0:35:42.440 --> 0:35:45.920
<v Speaker 3>And to what end I mean to build simulations that

0:35:45.960 --> 0:35:51.560
<v Speaker 3>are one hundred percent accurate to then populate with agents tune.

0:35:51.719 --> 0:35:53.120
<v Speaker 11>How do you see this work?

0:35:53.200 --> 0:35:58.680
<v Speaker 3>You've done proving more disruption to the market right now, right.

0:35:58.920 --> 0:36:02.480
<v Speaker 17>So today we work Fortune ten companies in retailer businesses,

0:36:02.760 --> 0:36:07.759
<v Speaker 17>to personal finance, to CpG companies and even to polling companies.

0:36:07.920 --> 0:36:11.680
<v Speaker 17>And today our customers use our technology to do concept testing. So,

0:36:11.719 --> 0:36:13.840
<v Speaker 17>for instance, CBS has been a close partner for the

0:36:13.880 --> 0:36:17.160
<v Speaker 17>past five months where CBS has now created hundreds of

0:36:17.200 --> 0:36:20.719
<v Speaker 17>thousands of similis or quote unquote agents that represent their

0:36:20.760 --> 0:36:24.360
<v Speaker 17>real customers, so they can actually do simulated focus groups

0:36:24.600 --> 0:36:27.040
<v Speaker 17>to understand better and there's in their pain points and

0:36:27.040 --> 0:36:30.520
<v Speaker 17>their use cases, but also to do story layout designs

0:36:30.600 --> 0:36:34.200
<v Speaker 17>and so forth. Galop, another polling company that's highly well

0:36:34.280 --> 0:36:37.120
<v Speaker 17>established and respected, is now working with similar to create

0:36:37.200 --> 0:36:41.399
<v Speaker 17>digital panel of their agents or their simulated human panels. Now,

0:36:41.440 --> 0:36:44.239
<v Speaker 17>one last example that's interesting is, of course many of

0:36:44.280 --> 0:36:47.759
<v Speaker 17>our customers are Fortune five hundred companies that regularly have

0:36:47.920 --> 0:36:51.400
<v Speaker 17>earnings call, so use case there might actually be creating

0:36:51.440 --> 0:36:54.120
<v Speaker 17>simulation of their earnings call. So this is an ass

0:36:54.239 --> 0:36:57.480
<v Speaker 17>that we get frequently. So in the recent earnings call

0:36:57.520 --> 0:37:00.319
<v Speaker 17>we simulated we actually can predict eight out of ten

0:37:00.440 --> 0:37:02.520
<v Speaker 17>questions that are actually asked.

0:37:02.200 --> 0:37:02.719
<v Speaker 2>In this court.

0:37:02.800 --> 0:37:07.600
<v Speaker 3>Sorry, June, you're saying the analysts almost don't need to

0:37:07.600 --> 0:37:10.880
<v Speaker 3>be asking that question. You can predict with eighty seventy

0:37:11.719 --> 0:37:14.760
<v Speaker 3>what analysts are going to ask CEO CFOs on earning course.

0:37:15.680 --> 0:37:16.600
<v Speaker 2>That's exactly right.

0:37:16.760 --> 0:37:19.880
<v Speaker 17>In fact, I actually before our conversation today, I had

0:37:19.880 --> 0:37:22.399
<v Speaker 17>a chance to simulate the questions that twelve you might ask.

0:37:22.719 --> 0:37:24.640
<v Speaker 17>And these are some other questions that actually have come

0:37:24.719 --> 0:37:25.600
<v Speaker 17>up in our assimilation.

0:37:26.040 --> 0:37:30.719
<v Speaker 2>Oh so you seem well prepared. Look, there's a degree

0:37:30.719 --> 0:37:35.200
<v Speaker 2>of skepticism about Similarly, to be fair, the founding members

0:37:35.200 --> 0:37:37.960
<v Speaker 2>four of you are are largely academics at Stamford. You

0:37:38.360 --> 0:37:40.839
<v Speaker 2>founded the company officially a year ago, but you've only

0:37:40.880 --> 0:37:43.799
<v Speaker 2>been training the model for seven months. You say you

0:37:43.840 --> 0:37:46.719
<v Speaker 2>have five months of commercial deals. How have you done

0:37:46.760 --> 0:37:49.000
<v Speaker 2>that so quickly? So similarly, it is a.

0:37:48.960 --> 0:37:53.279
<v Speaker 17>Real combination of amazing front your researchers that lasers the

0:37:53.320 --> 0:37:56.400
<v Speaker 17>ceiling of what the models are capable of today, but

0:37:56.560 --> 0:37:59.600
<v Speaker 17>also amazing product and engineers.

0:38:00.080 --> 0:38:01.600
<v Speaker 2>So here on the product.

0:38:01.280 --> 0:38:03.840
<v Speaker 17>Side, we have people like Laney Allen and Mikha Kapor

0:38:04.040 --> 0:38:07.160
<v Speaker 17>who have been product and engineering leader in the space

0:38:07.400 --> 0:38:11.760
<v Speaker 17>of companies such as Figma and Heavier, and that combined

0:38:11.760 --> 0:38:13.840
<v Speaker 17>with the rest of the engineering team and the research

0:38:13.920 --> 0:38:17.440
<v Speaker 17>talent our neighbors, us to create frontier technology that actually

0:38:17.480 --> 0:38:18.960
<v Speaker 17>gets routed directly.

0:38:18.680 --> 0:38:23.160
<v Speaker 3>To product June Park, who has preempted all of our

0:38:23.239 --> 0:38:26.880
<v Speaker 3>questions through his own products of Civilly. We so appreciate

0:38:26.920 --> 0:38:29.440
<v Speaker 3>your time, Thank you very much. Indeed, let's just take

0:38:29.480 --> 0:38:32.400
<v Speaker 3>a look elsewhere in AI model world, because Alphabet currently

0:38:32.440 --> 0:38:35.719
<v Speaker 3>spiking higher, up almost a percentage point. This is they've

0:38:35.800 --> 0:38:39.480
<v Speaker 3>updated a release to Gemini three Gemini three Deep Thinking

0:38:39.520 --> 0:38:42.279
<v Speaker 3>Reasoning Model. It's an update and they say that the

0:38:42.320 --> 0:38:46.080
<v Speaker 3>mode hasn't been updated to solve modern science research challenges

0:38:46.120 --> 0:38:46.640
<v Speaker 3>in particular.

0:38:46.840 --> 0:38:46.920
<v Speaker 6>Ed.

0:38:47.080 --> 0:38:49.480
<v Speaker 3>Look, Alphabet has been on a tear because of the

0:38:49.560 --> 0:38:52.399
<v Speaker 3>idea that it's generative. AI is managing to leap frog

0:38:52.480 --> 0:38:54.160
<v Speaker 3>or at least push ahead some of the rivals.

0:38:55.440 --> 0:38:57.080
<v Speaker 2>Yeah, it has, and look at the spike in the

0:38:57.120 --> 0:39:00.000
<v Speaker 2>session on those headlines are coming up Coinbase releases earning

0:39:00.120 --> 0:39:02.840
<v Speaker 2>after the closing bell, We're going to preview what to expect.

0:39:02.920 --> 0:39:20.280
<v Speaker 2>This is Blomberg Tech, Asian delivery firm GRAB missed analysts

0:39:20.360 --> 0:39:23.480
<v Speaker 2>expectations on its full year forecast to sign that weaker

0:39:23.600 --> 0:39:27.000
<v Speaker 2>consumer sentiment is weighing on the company. Earlier, we spoke

0:39:27.040 --> 0:39:29.560
<v Speaker 2>with GRAB CFO Peter Owe. Listen to this.

0:39:30.440 --> 0:39:33.120
<v Speaker 18>It was an amazing year for us. We achieved some

0:39:33.239 --> 0:39:36.400
<v Speaker 18>new mastones in the business. We have now fifty million

0:39:36.440 --> 0:39:40.680
<v Speaker 18>monthly transacting users using our app constantly on a monthly basis.

0:39:40.719 --> 0:39:43.840
<v Speaker 6>We also showed great profitability.

0:39:43.200 --> 0:39:46.120
<v Speaker 18>In the business to over five hundred million dollars in

0:39:46.120 --> 0:39:48.440
<v Speaker 18>the Justicey you be done, but also our first YEARNIT

0:39:48.560 --> 0:39:51.480
<v Speaker 18>profit in the business. As we look at twenty twenty six,

0:39:51.880 --> 0:39:54.520
<v Speaker 18>we're firing on aus cylinders and we are seeing good

0:39:54.600 --> 0:39:57.680
<v Speaker 18>growth across all the platforms, across all the different products

0:39:57.680 --> 0:40:00.680
<v Speaker 18>that we have today. We are confident going into twenty

0:40:00.719 --> 0:40:03.960
<v Speaker 18>twenty six in terms of delivering that new guide that

0:40:04.000 --> 0:40:06.279
<v Speaker 18>we gave up for twenty twenty six, but also we

0:40:06.320 --> 0:40:08.719
<v Speaker 18>also gave a three year guidance at the same time

0:40:08.880 --> 0:40:11.680
<v Speaker 18>of twenty percent revenue growth from twenty twenty five through

0:40:11.719 --> 0:40:12.520
<v Speaker 18>twenty twenty eight.

0:40:13.040 --> 0:40:14.640
<v Speaker 11>So really long term perspective here.

0:40:14.760 --> 0:40:17.399
<v Speaker 3>Just dialing in on the profitability side, because you're right

0:40:17.840 --> 0:40:20.400
<v Speaker 3>many loving the fact that you surprised you delivered this

0:40:20.440 --> 0:40:23.719
<v Speaker 3>full year profit. What now to really drive up that

0:40:23.760 --> 0:40:27.160
<v Speaker 3>return on equity? Our Bloomberg Intelligence analyst talking about maybe

0:40:27.239 --> 0:40:29.200
<v Speaker 3>it's the net profit.

0:40:28.920 --> 0:40:29.960
<v Speaker 11>To really be driven higher.

0:40:30.040 --> 0:40:32.120
<v Speaker 3>Needs even more leaning into the fintech side of the

0:40:32.120 --> 0:40:33.760
<v Speaker 3>business or some cost cuts.

0:40:33.800 --> 0:40:34.520
<v Speaker 11>Where do you pull.

0:40:36.120 --> 0:40:38.040
<v Speaker 18>Yeah, there's really three big pillars when you look at

0:40:38.080 --> 0:40:40.759
<v Speaker 18>the business today. One is continuing the growth momentum in

0:40:40.800 --> 0:40:43.880
<v Speaker 18>our rights business as well as our deliveries business. And

0:40:43.880 --> 0:40:47.799
<v Speaker 18>our deliveries also now we have other products and services up.

0:40:47.840 --> 0:40:50.040
<v Speaker 18>One example at grocery delivery continues to be one of

0:40:50.120 --> 0:40:53.440
<v Speaker 18>our fastest growing it's actually growing one point seven times faster.

0:40:53.640 --> 0:40:55.120
<v Speaker 6>Than our food business today.

0:40:55.400 --> 0:40:58.560
<v Speaker 18>We also have dining in which is another unique set

0:40:58.560 --> 0:41:00.759
<v Speaker 18>of product features that brings people the restaurants.

0:41:00.760 --> 0:41:03.279
<v Speaker 6>Also, at the same time, financial service is.

0:41:03.280 --> 0:41:06.680
<v Speaker 18>Also condused to be our fastest growing segment about business today.

0:41:06.840 --> 0:41:09.120
<v Speaker 18>The loan box size that we have today, we've clicked

0:41:09.160 --> 0:41:12.040
<v Speaker 18>over a billion dollars in loan portfolio and we expect

0:41:12.040 --> 0:41:14.480
<v Speaker 18>to double that is we finish the year twenty twenty six.

0:41:14.560 --> 0:41:17.400
<v Speaker 18>So we've got all the different products working together to

0:41:17.480 --> 0:41:20.080
<v Speaker 18>really drive the growth in the missus but also margin

0:41:20.200 --> 0:41:21.480
<v Speaker 18>expansion at the same.

0:41:21.320 --> 0:41:25.080
<v Speaker 3>Time, delivery to fintech grabs CFO Peter Ue there talking

0:41:25.120 --> 0:41:27.880
<v Speaker 3>of fintech. Coinbase was about to report earnings after the

0:41:27.880 --> 0:41:30.280
<v Speaker 3>bell and this comes in the context of a deepening

0:41:30.320 --> 0:41:33.000
<v Speaker 3>crypto route which has seen the value of bitcoin in particular,

0:41:33.080 --> 0:41:36.000
<v Speaker 3>plunge look more than forty five percent from its peak,

0:41:36.160 --> 0:41:39.240
<v Speaker 3>and with that, expectations of coinbases revenue are not looking

0:41:39.239 --> 0:41:41.920
<v Speaker 3>pretty Bloomberg Senior crypto reporter Olga Caraff.

0:41:42.000 --> 0:41:42.880
<v Speaker 11>Joins us now.

0:41:43.160 --> 0:41:45.480
<v Speaker 3>And it's all about volumes, right, and they're going to

0:41:45.520 --> 0:41:48.080
<v Speaker 3>pull back, so inherently revenues must have been hit.

0:41:49.280 --> 0:41:55.359
<v Speaker 19>Absolutely, So what happens when prices drop continuously? A lot

0:41:55.360 --> 0:41:59.080
<v Speaker 19>of the retail traders stay on the sidelines, and of

0:41:59.120 --> 0:42:03.239
<v Speaker 19>course crypto exchanges they make a huge portion of their

0:42:03.239 --> 0:42:06.640
<v Speaker 19>revenues from transaction fees, so they see a huge drop

0:42:06.680 --> 0:42:07.000
<v Speaker 19>on that.

0:42:08.680 --> 0:42:11.719
<v Speaker 2>What I understand or I get the volumes concerned, But

0:42:11.880 --> 0:42:16.160
<v Speaker 2>I've always understood that like coinbase others that it competes with,

0:42:16.440 --> 0:42:20.080
<v Speaker 2>they benefit from volatility, right because volatility you have to

0:42:20.080 --> 0:42:23.080
<v Speaker 2>trade in one direction or another. Why is that not

0:42:23.600 --> 0:42:25.600
<v Speaker 2>a good moment for them?

0:42:26.120 --> 0:42:30.680
<v Speaker 19>So you're absolutely right, when there is high volatility, they

0:42:30.719 --> 0:42:34.680
<v Speaker 19>do benefit. But typically what happens is that you have

0:42:34.920 --> 0:42:39.560
<v Speaker 19>say several days of very high volatility, such as sort

0:42:39.560 --> 0:42:44.920
<v Speaker 19>of in October when bitcoin dropped a lot, or in

0:42:45.160 --> 0:42:48.520
<v Speaker 19>early February when again it dropped a lot. So you

0:42:48.600 --> 0:42:50.920
<v Speaker 19>can have a lot of volatility, a lot of trading

0:42:51.000 --> 0:42:54.399
<v Speaker 19>during those days, but then you can have a sort

0:42:54.440 --> 0:42:58.600
<v Speaker 19>of slower activity, lower activity in the days kind of

0:42:58.640 --> 0:43:03.399
<v Speaker 19>in between those very high volatility days, and that can

0:43:03.440 --> 0:43:08.840
<v Speaker 19>impact exchanges like for instance, we've already seen Robinhood report.

0:43:08.560 --> 0:43:11.960
<v Speaker 16>That is a fourth quarter crypto revenue.

0:43:11.560 --> 0:43:15.240
<v Speaker 19>Was down thirty percent, So things are not looking good

0:43:15.360 --> 0:43:19.239
<v Speaker 19>for crypto trading providers.

0:43:19.480 --> 0:43:23.279
<v Speaker 3>Briefly, Coinbase has tried to diversify ahead of this. They're

0:43:23.320 --> 0:43:26.520
<v Speaker 3>looking whether or not it's predictions markets, whether it's equity

0:43:26.560 --> 0:43:27.200
<v Speaker 3>trading alga.

0:43:27.280 --> 0:43:27.839
<v Speaker 11>Is that enough?

0:43:29.840 --> 0:43:34.600
<v Speaker 19>So Coinbase has been trying to diversify for many years

0:43:34.640 --> 0:43:38.839
<v Speaker 19>and these are really good initiatives that could really help

0:43:39.320 --> 0:43:42.600
<v Speaker 19>in the years ahead. But right now, for instance, they

0:43:42.760 --> 0:43:45.320
<v Speaker 19>just launched prediction markets, so it's a very.

0:43:45.239 --> 0:43:47.120
<v Speaker 16>Very small revenue driver.

0:43:47.440 --> 0:43:52.440
<v Speaker 19>They do have stable coin revenue coming from their revenue

0:43:52.440 --> 0:43:57.120
<v Speaker 19>share with Circle that is helping to stabilize revenues quite

0:43:57.160 --> 0:43:59.319
<v Speaker 19>a bit, but a.

0:43:59.280 --> 0:44:01.839
<v Speaker 16>Lot of the the revenue portions are.

0:44:01.719 --> 0:44:05.400
<v Speaker 2>Still all Bloomberg's ald creed. Thank you very much. That

0:44:05.520 --> 0:44:07.959
<v Speaker 2>does it carry for this edition of Bloomberg Tech