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Speaker 1: Bloomberg Audio Studios, Podcasts, radio news. Bloomberg Tech is live

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Speaker 1: from coast to coast with Caroline Hide in New York

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Speaker 1: and vow into San Francisco.

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Speaker 2: This is Bloomberg Tech Coming up.

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Speaker 3: We sit down with the Care We've CEO Michael and

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Speaker 3: Trader to discuss the company's earnings as it.

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Speaker 2: Builds out data center capacity.

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Speaker 3: Plus, we break down the jobs report and the impact

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Speaker 3: of AI on today's workforce with Clara Schai from the

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Speaker 3: New Work Foundation, and we bring down more earnings with

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Speaker 3: LIFT CEO David Risher. As a company spends on international expansion,

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Speaker 3: but first we check in on these markets that are

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Speaker 3: moving on an international basis. Looks we still have eyes

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Speaker 3: towards some sort of peace still being broken between the

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Speaker 3: US and Iran, but the focus is also on optimism

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Speaker 3: round jobs. Data coming in stronger for the first back

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Speaker 3: to back gain we've had at least a year in

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Speaker 3: terms of month and month non f perils. But tech

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Speaker 3: I'm afraid down for sixty straight months in terms of

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Speaker 3: jobs in the information technology area. We're at one point

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Speaker 3: seven percent though, even as consumer confidence lags and it's

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Speaker 3: about the AI trade is about big tech, but there

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Speaker 3: is a lagged out there, and I just want to

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Speaker 3: shine light and what's happening with Core.

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Speaker 2: We've ropt by twelve percent.

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Speaker 3: The context is this company was up, let's say, ninety

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Speaker 3: percent year to date. In the run up to these earnings,

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Speaker 3: we see profit taking. We also see some anxiety as

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Speaker 3: we see the forecast perhaps sort of living up to

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Speaker 3: some of the higher expectations. CEO Michael and Trader joins

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Speaker 3: us now in the studio. Michael, earnings are always tough

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Speaker 3: when the market has built up a lot of optimism

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Speaker 3: around the business.

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Speaker 2: So why do you think they're.

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Speaker 3: A little bit concerned about the full looking guidance when

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Speaker 3: it comes to revenue, when it comes to operating profit.

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Speaker 4: So look, I think this was, and I said this

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Speaker 4: in the earnings call, a transformational and extraordinary earnings for us.

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Speaker 4: You know, the company really hit on all cylinders. We

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Speaker 4: you know, we beat on our revenue. You know, we

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Speaker 4: reafforted our annual revenue targets from a nominal perspective, we

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Speaker 4: reaffirmed our twenty twenty six ar are operating margin targets.

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Speaker 5: Really a great.

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Speaker 4: Quarter for us by the numbers, but also you know,

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Speaker 4: extending our product you know, we can't keep up with

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Speaker 4: demand from existing customers, which are you know, historically been

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Speaker 4: AI labs and AI native and cloud. Now they're expanding, yeah,

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Speaker 4: and we're just being overwhelmed by new verticals that are

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Speaker 4: coming in and integrating AI at scale into their workflows.

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Speaker 5: Right. And so you know, you heard me talk.

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Speaker 4: A little bit about some of the the trading and

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Speaker 4: finance companies like Jane Street and Hudson River Trading. You

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Speaker 4: know that's adding to you know, JP Morgan and Morgan

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Speaker 4: Stanley who are already clients. You know, you heard me

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Speaker 4: talk a little bit about some of the physical AI

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Speaker 4: into the robotics space, you know, where where you know,

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Speaker 4: great new clients coming on to our infrastructure. It's really exciting.

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Speaker 4: You know, Stock's going to bounce around. You know, we

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Speaker 4: understand that. But but you know, one of the you know,

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Speaker 4: one of the best things about being a founder and

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Speaker 4: a CEO, and one of the best things about and

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Speaker 4: one of the hardest things about being a founder and

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Speaker 4: CEO is you know, I try to keep my eye

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Speaker 4: on the parts of the business that are succeeding and

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Speaker 4: growing and expanding. And you know, we're winning the day, right.

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Speaker 4: We drove down our cost of capital, We expanded our

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Speaker 4: backlog by forty billion dollars. We we did all the

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Speaker 4: things that we needed to do. So I'm thrilled with

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Speaker 4: the quarter. I think was fantastic. You know, seemingly there's

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Speaker 4: a little bit of trepidation around next quarters revenue?

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Speaker 3: Do you Yeah, how do you get next quot And

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Speaker 3: indeed the second half people are optimistic that you're saying,

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Speaker 3: I'm optimistic the profitability will.

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Speaker 2: Ramp up in the second half. How does that happen?

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Speaker 5: Oh?

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Speaker 4: So, you know, I mean, look, we're we it's almost

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Speaker 4: mathematical at some point, right like where you know you're

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Speaker 4: building infrastructure, that infrastructure takes time to bring online.

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Speaker 5: We are going through a massive build out across the

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Speaker 5: company right now.

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Speaker 4: It's why the the operating margins have compressed this because

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Speaker 4: we're going through this enormous scaling exercise. As you push

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Speaker 4: through that, all of that infrastructure comes onto billing. And

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Speaker 4: once it comes on to billing, you are going to

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Speaker 4: see a sequential expansion of the operating margins until we

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Speaker 4: go from you know, one percent in Q one all

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Speaker 4: the way up through low double digits by Q four.

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Speaker 4: And you know that's sort of baked in because of

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Speaker 4: the infrastructure coming online, the software capacity to deliver that infrastructure.

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Speaker 4: You know, we're highly confident we're going to hit those numbers.

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Speaker 3: There was anxiety about another company a kind not hitting

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Speaker 3: internal numbers, and I'm talking about open And Look, Sarahphry

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Speaker 3: has come on and spoken to colleagues here at breoing

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Speaker 3: revenues and pushed back against that, saying they're seeing a

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Speaker 3: wall of demand. But how confident are you that your

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Speaker 3: clients are seeing that demand and are good for the

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Speaker 3: money for the buildout.

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Speaker 5: Yeah.

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Speaker 4: So one of the things I talked about yesterday during

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Speaker 4: Ernix call is that.

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Speaker 5: The demand for our.

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Speaker 4: Paper in the debt markets has been nothing shy of astounding.

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Speaker 4: You know, we did a one of our delayed draw

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Speaker 4: facilities closed two days ago. The clients in it were

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Speaker 4: cohere and open Ai exclusively, and the two things happened. One,

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Speaker 4: it was five x oversubscribed, which is enormous. It also

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Speaker 4: closed fifty basis points below the marketed range, and that

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Speaker 4: is a clear indication of enormous buying interest for financing the.

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Speaker 5: Paper with regards to paying.

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Speaker 4: Look, you know, open Ai is extraordinary company, right, One

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Speaker 4: in ten people on the planet use their product.

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Speaker 5: Every year.

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Speaker 4: But you know, and we think that they're in a

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Speaker 4: wonderful position. But we've also built an incredibly diversified portfolio

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Speaker 4: of companies that use our infrastructure.

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Speaker 5: This this quarter.

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Speaker 4: We announced Anthropic, We announced a massive deal twenty one

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Speaker 4: billion dollars with Meta. We announced, you know, a six

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Speaker 4: billion dollar deal with Jane Street. You know, like the

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Speaker 4: number of clients that are using our infrastructure are expanding,

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Speaker 4: you know, the diversification is expanding.

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Speaker 5: Open Ai is an important client, but one of many.

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Speaker 3: Let's talk about an important partner and in your supply chain,

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Speaker 3: and that's in Video. How confident you are with the

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Speaker 3: strength of your relationship there and videos made deals with you,

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Speaker 3: invested in you, but also doing that with shall I say,

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Speaker 3: even competitors in the space.

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Speaker 2: Is that ever an anxiety?

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Speaker 4: No, I take that as an incredible affirmation of the

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Speaker 4: fact that the world needs more of this infrastructure. And

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Speaker 4: the demand and for the infrastructure and the product that

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Speaker 4: we deliver is you know, overwhelming. And you know, at

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Speaker 4: the end of the day, you know, in Video has

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Speaker 4: got to do what it's got to do for its business.

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Speaker 4: I really focus on my clients and my clients are

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Speaker 4: coming back to us and they are saying again and again,

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Speaker 4: you deliver the best product the way that your software

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Speaker 4: stack enables our engineers to use it most efficiently, that

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Speaker 4: most cost effectively, and most successfully, and therefore we want

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Speaker 4: to buy more. And so the problem that I've got

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Speaker 4: is how do I bring on enough infrastructure to sate

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Speaker 4: and to deliver the infrastructure that my clients are clamoring.

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Speaker 3: Dig into the problems because there have been delays at

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Speaker 3: times with certain of them coming online. And that's to

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Speaker 3: do with a partnership. What is the biggest chokol for

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Speaker 3: you the matter?

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Speaker 4: So you know, Core is becoming a massive player in

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Speaker 4: the space, and you know we are currently approaching fifty

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Speaker 4: data centers that were delivering infrastructure from There is no

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Speaker 4: single data center provider that represents more than seventeen percent

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Speaker 4: of our infrastructure. We have a massive effort internal to

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Speaker 4: the company to go through self builds so that we

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Speaker 4: have greater operational control over the delivery of data center capacity.

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Speaker 4: You know, we're doing all the right things by diversifying

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Speaker 4: to ensure that no single data center can materially impact

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Speaker 4: the trajectory of the company.

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Speaker 5: That is further.

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Speaker 4: Reinforced by just the size and scale of the installed capacity. Right,

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Speaker 4: So you know, if you have a gigawatt worth of

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Speaker 4: capacity and a data hall represents you know, fifty megawats,

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Speaker 4: you know, you know, and you're bringing a fifty megawat

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Speaker 4: the impact of a week delay on fifty megawats in

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Speaker 4: a gigawatt environment is very different than earlier on when

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Speaker 4: you're bringing on fifty megawats and you only have fifty

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Speaker 4: megawats online. A week delay rattles your entire ability to

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Speaker 4: project where you're going.

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Speaker 5: And we no longer have that problem.

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Speaker 4: We have achieved escape velocity, both in terms of our

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Speaker 4: data center capacity as well as our revenue, as well

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Speaker 4: as our ability to provide guidance into the back half

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Speaker 4: of this year.

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Speaker 5: We're super excited about that.

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Speaker 3: We'll wait for the investors maybe to just react to

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Speaker 3: some of your longer term perspective, Michael Intrader.

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Speaker 2: They're the CEO of Courwave on the back of theirnvembers.

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Speaker 3: Now we're also watching shares a cloud flare after their

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Speaker 3: own planning's report. Look, they're saying they're going to slash jobs.

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Speaker 3: About a fifth of all jobs are going to go

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Speaker 3: they're giving a forecast for revenue that fell short of

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Speaker 3: analyst expectations. This is again and lean into AI, but

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Speaker 3: it comes sadly at the expense of people and the

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Speaker 3: workforce for them. We'll currently see the shares of twenty

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Speaker 3: four percent as the really the revenue and the forecast

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Speaker 3: is what is concerning people at the moment.

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Speaker 2: Coming up, we'll.

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Speaker 3: Discuss further that issue of AI, of tech, of jobs,

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Speaker 3: of unemployment on the back of the jobs report and

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Speaker 3: indeed of the likes of cloud Flare. Clara Shies with

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Speaker 3: Us New Work Foundation doesn't blum beg tech. US payrolls

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Speaker 3: beat most expectations in April was actually the first back

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Speaker 3: to back game for payrolls in a year, but tech

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Speaker 3: jobs have fallen for sixteenth straight month and that's in

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Speaker 3: many ways being blamed on AI. Let's talk about the

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Speaker 3: AI story here because learning artificial intelligence is becoming more

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Speaker 3: and more crucial for workers to get hired. Forty two

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Speaker 3: percent of recent grads are still underemployed. Tara Shies with

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Speaker 3: Us found our CEO of New Work Foundation, former head of.

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Speaker 2: Business at Meta.

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Speaker 3: Your CV stands out and look, you're saying you want

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Speaker 3: AI to be profitable not just for businesses, but everyone,

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Speaker 3: including the millions of twenty five year olds currently unde

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Speaker 3: employed or unemployed. Kara, you've founded this what's happening with

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Speaker 3: the labor market right now.

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Speaker 6: Thank you, Carolyne. Great to see you, gen Z. American

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Speaker 6: workers are graduating in the worst job market in thirty

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Speaker 6: seven years. As you said, forty two percent are underemployed,

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Speaker 6: so they're bartending, they're working gig jobs and taking other

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Speaker 6: work that don't require their degree. And it's because traditional

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Speaker 6: pathways are drying up, and today's young Americans are graduating

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Speaker 6: without the skills, tools and information they need to get

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Speaker 6: hired in this AI economy.

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Speaker 2: So the skills the tools they need.

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Speaker 3: You're bringing that to bear, how because there is a

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Speaker 3: sudden anxiety that people need to realign themselves for the

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Speaker 3: future of work.

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Speaker 6: Well, absolutely, And I look at the colleges in America

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Speaker 6: and CA to twelve education. There is rightful caution around

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Speaker 6: using AI, but many of these young people are actively

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Speaker 6: being discouraged from using AI and learning AI while they're

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Speaker 6: in school, and so they're graduating not knowing how to

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Speaker 6: direct these systems, not knowing how to properly set up

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Speaker 6: context engineering and how to apply these AI workflows in

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Speaker 6: transformational ways, whether they're applying for a mar marketing job,

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Speaker 6: software engineering, or accounting accounting.

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Speaker 3: I think of just an industry that is being shaken

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Speaker 3: up significantly by new AI products. This isn't just gen

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Speaker 3: Z that are suffering. And the moment we see yet

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Speaker 3: more and more layoffs being announced cloud Flair. Today we've

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Speaker 3: had Block coming out with its numbers and showing the

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Speaker 3: rewards it's gaining from having left almost half of its

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Speaker 3: entire employee based coenbase this week.

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Speaker 2: You think they just keep on building.

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Speaker 3: Thirty three thousand tank jobs have been cut in April.

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Speaker 3: What do you think the tech sector is going to

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Speaker 3: look like in the future, Clo, It's.

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Speaker 6: Really hard to say, but I think what we're trending

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Speaker 6: right now is really much more usage of AI and

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Speaker 6: specifically AI agents to do a lot of the work

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Speaker 6: that traditionally entry level workers did. And again that's why

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Speaker 6: it is so important that we equip our young graduates

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Speaker 6: with a tool and information they need and the experience

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Speaker 6: they need to get hired.

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Speaker 2: Is there a backlash?

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Speaker 3: I mean, I've thought of how you and I've sat

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Speaker 3: down over the years, and you've talked about the tools

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Speaker 3: you're using, the way you're leaning into a gender KI

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Speaker 3: or just generator writ large.

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Speaker 2: You then see the response to a Reese Witherspoon.

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Speaker 3: Trying to say that maybe people who look like you

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Speaker 3: and me, women in particular, should start using AI a

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Speaker 3: little bit more. The people are worried about the cost

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Speaker 3: of the environment, the cost of creativity and royalties and payouts.

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Speaker 3: How do you navigate that amongst gen z who maybe

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Speaker 3: coming to AI kicking and screaming yes.

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Speaker 6: And as we've done this work with a New Work Foundation,

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Speaker 6: one of my co founders Samantha, she is part of

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Speaker 6: gen Z, and what I've heard from her and her

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Speaker 6: friends is a lot of young people today do have

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Speaker 6: these moral objections and concerns around AI. And so what

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Speaker 6: I would say is these are the exact people we

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Speaker 6: want being part of building the solutions, so that we

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Speaker 6: can capture their concerns and creatively build the right path

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Speaker 6: forward that addresses what they want but also doesn't leave

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Speaker 6: them behind in this new economy.

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Speaker 3: You've got this initial set of free AI tools. Job Claw,

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Speaker 3: you've got one of them, Field Report. I want to

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Speaker 3: go into they really do, but there is a lot

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Speaker 3: of free tools out there. IBM has them, Amazon has them. Look,

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Speaker 3: if you wanted to lean into understanding and building your

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Speaker 3: own repertoire of AI talent, you can do it. So

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Speaker 3: why did you have to design something different?

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Speaker 6: Well, I think we have to address the legitimate moral

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Speaker 6: questions that gen Z has, just like we said, but

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Speaker 6: then also beyond that, it's almost overwhelming how much information

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Speaker 6: is out there about AI. There are hundreds of thousands

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Speaker 6: of hours of AI courses, certifications, some of them free,

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Speaker 6: but some of them very expensive, and it's very hard

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Speaker 6: for anyone of any age actually to navigate this. And

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Speaker 6: so what we wanted to do is NEWWAAR Foundation is

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Speaker 6: going job by job, going across the most common entry

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Speaker 6: level white collar roles that young people are applying for,

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Speaker 6: and we're breaking down exactly what it takes to become

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Speaker 6: AI native in doing that job. So whether it's marketing,

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Speaker 6: whether it's software, whether it's investment banking, whether it's legal,

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Speaker 6: whether it's it's some other role. We're talking to hiring

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Speaker 6: managers that are using AI, asking them to describe in

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Speaker 6: clear terms how what they're looking for has changed in

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Speaker 6: the last twelve months. As a result, of AI and agents.

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Speaker 6: And we're also interviewing other gen Z workers who had

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Speaker 6: been struggling to find work but have recently found a

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Speaker 6: job in that particular role, so that they can share

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Speaker 6: their tips and.

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Speaker 2: Tricks our shy.

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Speaker 3: I'm sure music to many A person's there, if they're listening,

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Speaker 3: if they are among that gen Z cohort New Work Foundation.

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Speaker 3: We appreciate your time today, taking a look now at

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Speaker 3: your day's big number. Six billion dollars. That's what SoftBank

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Speaker 3: is now targeting for a loan backed by its open

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Speaker 3: Ai stake, after facing some hesitation from creditors. It's all

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Speaker 3: according to people familiar with the matter. It's down from

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Speaker 3: an initial target of ten billion dollars that it was

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Speaker 3: originally planning. Part of the investor concerns deal with the

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Speaker 3: difficulty of reaching a valuation for an unlisted company like

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Speaker 3: open Ai, which has been reported as facing some challenges

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Speaker 3: and meeting some internal targets and internal goals, a point

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Speaker 3: that Sarah Fryer has pushed back on when joining our

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Speaker 3: colleagues on Bloomberg News. Let's talk about SpaceX now rival,

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Speaker 3: though its rival is ast Space Mobile, and it's searched

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Speaker 3: to roughly twenty five billion dollar market cap despite generating

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Speaker 3: just seventy one million dollars an annual revenue. It's fueled

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Speaker 3: in large part by devoted retail investor community known as

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Speaker 3: the space Mob.

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Speaker 2: For more his Sana Frashanka.

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Speaker 3: With today's Big Tay, it is one of the most

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Speaker 3: red stories across our platform today. Sarah, so tell us

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Speaker 3: a little bit of what's happening. Who are these people

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Speaker 3: who are loving AST?

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Speaker 7: Yeah, so, AST has thousands of retail investors. As you mentioned,

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Speaker 7: the space Mob, and you know, there are a little

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Speaker 7: reminiscent of the crowds that used to rally around Munstock

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Speaker 7: side game stop in AMC. Except the space mob really

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Speaker 7: believes in AST Space Mobile. They think it's going to

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Speaker 7: become the next trillion dollar company. And they're not in

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Speaker 7: it to make a quick hit. They really believe in

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Speaker 7: the technology. AST is pioneering directed device technology, which are

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Speaker 7: satellites that beam cellar section directly to your mobile phone,

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Speaker 7: which is something that satellites traditionally have not done. And

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Speaker 7: so they have, you know, rallied around the stock. They

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Speaker 7: fixate on every shred of corporate intel from the company.

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Speaker 7: They track their regulatory filings. You know, the planes that

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Speaker 7: ship the company satellites. So they're about as devoted as

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Speaker 7: a fan base to a company as you can get.

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Speaker 3: And that devotion means the stock is out nearly six

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Speaker 3: percent over a twenty two month period. We're looking at

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Speaker 3: it on a one year basis right now. Talk to

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Speaker 3: us about some leadership amongst the Space Mob.

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Speaker 2: Cock who is Kuck?

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Speaker 7: So the quuk is a He's a California based private investor.

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Speaker 7: He wants to remain anonymous, but he has just a

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Speaker 7: ton of money in as space Mobile. His family's money's

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Speaker 7: in it, you know, for his kid's money, everything, And

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Speaker 7: so he really leads the space Mob. He is one

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Speaker 7: of the most prominent figures around the Space Mob. And

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Speaker 7: you know, if you follow his ex post, he's very

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Speaker 7: emotionally invested in it, and you know, you can track

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Speaker 7: his mood based on how the stock is doing. And

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Speaker 7: so he's really a zany character that you know a

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Speaker 7: lot of the other Space mobbers follow and watch four

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Speaker 7: signs of his emotional mood and sometimes you can see

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Speaker 7: that reflected in the stock price as well.

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Speaker 3: And he's bottom apparently, Tanna Ottaway, I mean, an extraordinary character.

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Speaker 3: Shine light on his life savings into ast stock. Sana Fashanka,

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Speaker 3: go read this story. Thank you for joining us on it.

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Speaker 3: We appreciate you coming on now. Intel shares would largely

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Speaker 3: flat for months after CEO Libhutan took the helm in

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Speaker 3: March of last year, but have since climbed as you

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Speaker 3: can see, to record highs as he built ties with

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Speaker 3: some of the biggest technique is Anacle's President Trump still

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Speaker 3: core challenges persist for the chip maker. Bloomberg's Big Tech

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Speaker 3: reporter Sarah Fry joins us now because what's so interesting

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Speaker 3: about this story is we've got this conversation to sit

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Speaker 3: down with Lipbutan and one of people making of his

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Speaker 3: leadership styles.

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Speaker 8: Sarah well Ian King talked to many current informer employees

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Speaker 8: and got the picture of that. While Liputan has succeeded

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Speaker 8: in rallying this optimism around Intel's future from the likes

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Speaker 8: of Donald Trump, Elon Musk, we have that potential customer

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Speaker 8: deal with Apple and others, there still has to be

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Speaker 8: a major change in how the company thinks about its products,

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Speaker 8: how it develops them to be high quality, the quality

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Speaker 8: of its factories, all of the work internally still needs

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Speaker 8: to be done to really deliver on that optimism going forward.

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Speaker 8: And so Intel, you know, we have these record highs,

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Speaker 8: we have wall streets backing. Now we need Liputan to

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Speaker 8: look inward and rally the company around a vision for that.

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Speaker 3: And he's trying to look in his first interview, CEO

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Speaker 3: telling inking, you got the technology, We've got the talent,

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Speaker 3: we've got the scale to lead again, what leadership has

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Speaker 3: earned through execution? Is he on site enough for that execution?

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Speaker 3: That seems to be a bit of a concern amongst

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Speaker 3: those that I interviewed.

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Speaker 8: Yes Ian found that really he's spending or has spent

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Speaker 8: at least a lot more time with customers than he

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Speaker 8: has internally at Intel. And when he does spend time

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Speaker 8: at Intel, he doesn't really go into the details with people.

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Speaker 8: He's not a micromanager by any sense of the imagination.

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Speaker 8: He is much more of a high level strategy thinker.

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Speaker 8: When he hears somebody's strategy, he sort of quizzes them

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Speaker 8: on the industry from a broad sense, and then if

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Speaker 8: he likes how they think, he backs them and he

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Speaker 8: undoes roadblocks for them and supports them, sort of like

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Speaker 8: his role as a venture capital investor and board member. Right,

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Speaker 8: But at Intel. The details really do matter because when

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Speaker 8: you're you're thinking about the efficiency of these chips, about

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Speaker 8: the ability for a customer to spend to make a

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Speaker 8: bet on using one of your one of your factories,

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Speaker 8: it has to go right. It has to be.

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Speaker 3: Effective, particularly when the yield rates are only about sixty

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Speaker 3: five percent versus eighty percent over at t SMC, Sarah

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Speaker 3: Fryar brilliant editing on a really crucial story.

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Speaker 2: Thanks for joining on it. Welcome back to Bloomberg Tech.

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Speaker 3: It's another day, another new record high for then as

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Speaker 3: that one hundred, we continue to power on. Maybe the

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Speaker 3: jobless claims a rosier look on the labor market, even

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Speaker 3: though it's not a rosier look for tech jobs. Sixteen

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Speaker 3: months of declines for the tech industry and jobless claims,

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Speaker 3: but I mean not in jobless claims, in non vom payrolls,

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Speaker 3: but consumer sentiment also low. Nevertheless, we're looking at earnings

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Speaker 3: that have been thriving in certain parts of the business,

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Speaker 3: and I want to dial into some of those earnings

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Speaker 3: that we got overnight and in the morning, I'm looking

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Speaker 3: at three point three percent games for Airbnb. Look, they're

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Speaker 3: dialing up the growth expectations of the investor base right

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Speaker 3: now because they're seeing good growth in the United States.

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Speaker 3: They're even reinvesting, of course, putting money to work to.

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Speaker 2: Diversify the business.

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Speaker 3: We're seeing block well liked up six percent as they

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Speaker 3: just announced forty percent more than job cuts. Well, that's

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Speaker 3: already because AI is making such a difference to the

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Speaker 3: coding within the business and the software stack within also

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Speaker 3: the ability to serve clients, and we're seeing profitability being

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Speaker 3: guided higher at that particular company, Coinbase, though they're also

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Speaker 3: announced layoffs earlier this week and revenue sinking. Clearly the

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Speaker 3: turbulance in the crypto market is still hitting summer. Coinbas's

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Speaker 3: metrics are off by more than a percentage point. DraftKings

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Speaker 3: up two point eight percent. There was some relief in

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Speaker 3: the numbers as they see revenue coming in some seventeen

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Speaker 3: percent higher and some signs of growth when it comes

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Speaker 3: to the predictions market. But let's stick with earnings more broadly.

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Speaker 2: And shares.

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Speaker 3: A right hailing company, well Lift, we're currently up two

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Speaker 3: point one percent. That's called it after the company reported

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Speaker 3: first called a profit. Actually, so there's some anxiety among

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Speaker 3: Wall Street about the expectations, but it was all being

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Speaker 3: ramped up by spending on international expansion. Maybe that's what

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Speaker 3: was hitting in the near term, the profitability metrics. I've

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Speaker 3: got to talk to the person who knows all Lift CEO,

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Speaker 3: David Risher. Look, we've had a volatile trading day for Lift.

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Speaker 3: There was some pressure as people worried about well, the

440
00:23:08,200 --> 00:23:10,320
Speaker 3: amount that you're spending to grow, But you're managing to

441
00:23:10,320 --> 00:23:12,560
Speaker 3: push back on that. You see to investor base that

442
00:23:12,640 --> 00:23:14,120
Speaker 3: this is the right use of capital.

443
00:23:15,200 --> 00:23:16,040
Speaker 9: I really think it is.

444
00:23:16,280 --> 00:23:16,600
Speaker 5: Yeah.

445
00:23:16,760 --> 00:23:18,520
Speaker 9: I mean, look, we had a record quarter, which is

446
00:23:18,520 --> 00:23:22,320
Speaker 9: always wonderful, almost five billion in bookings. You bit up

447
00:23:22,600 --> 00:23:25,160
Speaker 9: thirty seven percent year on year, one point one billion

448
00:23:25,240 --> 00:23:26,359
Speaker 9: dollars of free cash flow.

449
00:23:26,440 --> 00:23:27,200
Speaker 5: So that's great.

450
00:23:27,400 --> 00:23:29,520
Speaker 9: So when you're in a position like that, that allows

451
00:23:29,520 --> 00:23:32,000
Speaker 9: you to grow and grow even more. And as you noted,

452
00:23:32,040 --> 00:23:35,080
Speaker 9: we've done some international acquisitions just in fact, one announced

453
00:23:35,119 --> 00:23:38,080
Speaker 9: a couple of days ago get in the UK. Look,

454
00:23:38,080 --> 00:23:39,560
Speaker 9: I think it's a great time to be frankly, the

455
00:23:39,640 --> 00:23:41,760
Speaker 9: rights your business because we're a really important part of

456
00:23:41,760 --> 00:23:44,520
Speaker 9: a lot of people's lives and we're growing.

457
00:23:44,280 --> 00:23:49,080
Speaker 3: Like a weed, growing like a weed. Mandy Blueberg Intelligent

458
00:23:49,160 --> 00:23:52,080
Speaker 3: Sort of saying that supply growth for lift perhaps is likely.

459
00:23:51,960 --> 00:23:53,160
Speaker 2: To trail some larger peers.

460
00:23:53,160 --> 00:23:54,680
Speaker 3: I mean, I talked to us about the adoption rate,

461
00:23:54,680 --> 00:23:56,919
Speaker 3: the adoption rate of your offerings, but the adoption rate

462
00:23:56,960 --> 00:23:59,760
Speaker 3: in particular of autonomous vehicles that you're starting to dabble in.

463
00:24:00,560 --> 00:24:00,879
Speaker 5: Yeah.

464
00:24:01,160 --> 00:24:03,280
Speaker 9: So look, I think if you zoom, weigh in, you

465
00:24:03,280 --> 00:24:06,360
Speaker 9: can always find little things, right. So we delivered about

466
00:24:06,359 --> 00:24:08,680
Speaker 9: two hundred and thirty seven million rides this last quarter.

467
00:24:08,840 --> 00:24:10,960
Speaker 9: That's a lot of rides, a lot of commuting rides,

468
00:24:10,960 --> 00:24:12,639
Speaker 9: a lot of rides to the airport and so forth.

469
00:24:12,840 --> 00:24:14,160
Speaker 5: Now, the quarter started.

470
00:24:13,920 --> 00:24:16,480
Speaker 9: Off a little bit slow. There's some really intense storms,

471
00:24:16,480 --> 00:24:19,080
Speaker 9: particularly in New York City where you live. As you know,

472
00:24:19,160 --> 00:24:21,160
Speaker 9: that brought you ride share and beg share to.

473
00:24:21,119 --> 00:24:21,680
Speaker 5: Sort of zero.

474
00:24:21,760 --> 00:24:23,840
Speaker 9: So that was an early, you know, kind of headwind.

475
00:24:23,880 --> 00:24:27,840
Speaker 9: But look, Valentine's Day, Saint Patrick's Day, Super Bowl, these

476
00:24:27,840 --> 00:24:30,040
Speaker 9: were all all time highs. And then we had our

477
00:24:30,080 --> 00:24:32,960
Speaker 9: highest ride month ever in March. So I think that

478
00:24:33,000 --> 00:24:35,000
Speaker 9: there's a lot of reason to believe that there's still

479
00:24:35,000 --> 00:24:37,000
Speaker 9: a huge, huge amount of growth here. And then, as

480
00:24:37,000 --> 00:24:39,440
Speaker 9: you say, autonomous vehicles, that's a great product and that's

481
00:24:39,480 --> 00:24:40,879
Speaker 9: going to be one of the next big kind of

482
00:24:40,920 --> 00:24:41,719
Speaker 9: growth vectors up.

483
00:24:42,240 --> 00:24:45,120
Speaker 3: Mart Mahine over Evercore really liking the fact that you've

484
00:24:45,119 --> 00:24:47,720
Speaker 3: got a record six straight quarter in.

485
00:24:47,760 --> 00:24:48,840
Speaker 2: Terms of active riders.

486
00:24:49,200 --> 00:24:51,160
Speaker 3: But I think what he's liking to see is maybe

487
00:24:51,200 --> 00:24:53,439
Speaker 3: consumer incentives to just moderate a little bit.

488
00:24:53,480 --> 00:24:55,200
Speaker 2: Are you being able to do that, David.

489
00:24:55,800 --> 00:24:56,480
Speaker 5: Yeah, we are.

490
00:24:56,520 --> 00:24:58,080
Speaker 9: We've gotten a lot of you know, we think of

491
00:24:58,040 --> 00:25:00,000
Speaker 9: it as a sort of leverage off of consumer incentive.

492
00:25:00,560 --> 00:25:02,639
Speaker 9: And I'll tell you a particular thing that I'm starting

493
00:25:02,640 --> 00:25:05,879
Speaker 9: to see more. I think if it is rewards maxing. Okay,

494
00:25:05,920 --> 00:25:08,919
Speaker 9: so oh no, you've got right there, you go, there,

495
00:25:08,960 --> 00:25:10,560
Speaker 9: you go. Be careful about where we're going to go

496
00:25:10,560 --> 00:25:12,920
Speaker 9: with this one. So anyway, No, but look, we've got

497
00:25:12,920 --> 00:25:15,600
Speaker 9: to deal with United right, which allows people to both

498
00:25:15,640 --> 00:25:18,240
Speaker 9: earn points and also spend points on left. We have

499
00:25:18,240 --> 00:25:22,000
Speaker 9: a deal with Hilton, we have an arrangement with alask Airlines.

500
00:25:22,000 --> 00:25:24,160
Speaker 9: We have an arrangement with door Dash are super super

501
00:25:24,160 --> 00:25:27,720
Speaker 9: important program there that just expanded to Canada. And so

502
00:25:27,840 --> 00:25:30,240
Speaker 9: what we're seeing people do is they're you know, they're

503
00:25:30,280 --> 00:25:33,359
Speaker 9: they're taking lift rides, they're earning points and they're spending

504
00:25:33,400 --> 00:25:36,240
Speaker 9: them elsewhere, or they're even spending them back on our platform.

505
00:25:36,520 --> 00:25:37,760
Speaker 5: And yeah, I think it's.

506
00:25:37,600 --> 00:25:38,639
Speaker 9: Going to be a thing, and I think it's one

507
00:25:38,640 --> 00:25:40,560
Speaker 9: of the reasons why we're seeing high margins sort of

508
00:25:40,600 --> 00:25:44,600
Speaker 9: like black and luxury rides rise. Even with some consumer concerns.

509
00:25:44,800 --> 00:25:47,320
Speaker 9: Still this rewards maxing thing, I think is working for people.

510
00:25:48,000 --> 00:25:50,879
Speaker 3: Rewards maxing, of course is a play on all the

511
00:25:50,920 --> 00:25:53,560
Speaker 3: maxing that we have. We looks maxing, all the tons

512
00:25:53,560 --> 00:25:54,800
Speaker 3: of phrase that gen Z use.

513
00:25:56,000 --> 00:25:59,040
Speaker 2: Is it gens? I mean, I mean, how much do

514
00:25:59,119 --> 00:25:59,480
Speaker 2: you see?

515
00:25:59,560 --> 00:26:02,720
Speaker 3: How much you seeing the idea of different age groups

516
00:26:02,760 --> 00:26:05,320
Speaker 3: responding to your new offerings, because in many ways I

517
00:26:05,359 --> 00:26:07,600
Speaker 3: see the more premium offerings coming to a to an

518
00:26:07,600 --> 00:26:10,680
Speaker 3: older cohort, a more obviously a wealthier cohort, in many ways,

519
00:26:10,680 --> 00:26:11,520
Speaker 3: a corporate cohort.

520
00:26:12,600 --> 00:26:12,800
Speaker 5: You know.

521
00:26:13,000 --> 00:26:15,440
Speaker 9: I think that's something that's changing over time. I think,

522
00:26:15,600 --> 00:26:17,479
Speaker 9: you know, back when I was, you know, early in

523
00:26:17,520 --> 00:26:20,320
Speaker 9: my career, you know, you didn't have an Amex you know,

524
00:26:21,000 --> 00:26:24,280
Speaker 9: platinum card or Chase Sapphire Reserve card until you're you.

525
00:26:24,280 --> 00:26:26,920
Speaker 5: Know, old like me now. But no, it turns out.

526
00:26:26,840 --> 00:26:28,439
Speaker 9: Actually a lot of kids, a lot of sort of

527
00:26:28,480 --> 00:26:31,399
Speaker 9: gen Y gen Z folks are early in that ecosystem

528
00:26:31,400 --> 00:26:33,399
Speaker 9: because they realize that there's a lot of value to

529
00:26:33,440 --> 00:26:35,199
Speaker 9: be unlocked if they kind of play the game. And

530
00:26:35,240 --> 00:26:36,480
Speaker 9: I think a lot of them think of it a

531
00:26:36,520 --> 00:26:38,199
Speaker 9: bit of as almost to play in the game, like

532
00:26:38,200 --> 00:26:40,520
Speaker 9: how can I how can I do this rewards maximine

533
00:26:40,560 --> 00:26:43,680
Speaker 9: thing to be able to afford a lift black even

534
00:26:43,720 --> 00:26:45,240
Speaker 9: when I'm in my in my twenties.

535
00:26:45,920 --> 00:26:48,840
Speaker 3: Savvy is what they are, and I'm interested, David, and

536
00:26:49,119 --> 00:26:51,080
Speaker 3: how savvy you are about the landscape for M and A.

537
00:26:51,200 --> 00:26:51,479
Speaker 2: Right now?

538
00:26:51,480 --> 00:26:54,520
Speaker 3: You've made acquisitions, this is where you've been spending your money.

539
00:26:54,600 --> 00:26:55,320
Speaker 2: Is there more to come?

540
00:26:57,080 --> 00:26:59,280
Speaker 9: You know, you never say never about these things. It's always,

541
00:26:59,680 --> 00:27:01,720
Speaker 9: you know, fool's game to predict M and A. But

542
00:27:01,800 --> 00:27:04,680
Speaker 9: I will say that it's a part of our strategy. Now.

543
00:27:04,720 --> 00:27:07,080
Speaker 5: We were not a very inquisitive company for a long time.

544
00:27:07,359 --> 00:27:10,000
Speaker 9: But now that we've got you know, the fastest pickup times,

545
00:27:10,080 --> 00:27:13,160
Speaker 9: great pricing, great service levels all around, we're really thinking

546
00:27:13,200 --> 00:27:15,399
Speaker 9: of bringing that abroad. And that's really where our M

547
00:27:15,400 --> 00:27:17,160
Speaker 9: and A focus has been is overseas.

548
00:27:17,320 --> 00:27:19,040
Speaker 2: Any warries about the consumer right now?

549
00:27:20,160 --> 00:27:23,040
Speaker 9: No, no, And I know that sounds glib. Of course,

550
00:27:23,080 --> 00:27:25,520
Speaker 9: people are feeling some pain. Our drivers feel a lot

551
00:27:25,520 --> 00:27:27,159
Speaker 9: of pain at the pump, and so that's why we

552
00:27:27,160 --> 00:27:29,280
Speaker 9: were the first to get out there with a nice

553
00:27:29,320 --> 00:27:32,040
Speaker 9: cash back program at the pump saves about a dollar

554
00:27:32,040 --> 00:27:34,240
Speaker 9: a gallon. So you know, there are reasons, I think,

555
00:27:34,280 --> 00:27:36,280
Speaker 9: of course, are to be concerned, but when we look

556
00:27:36,320 --> 00:27:38,520
Speaker 9: at the data, you know, we're not seeing that play out.

557
00:27:39,840 --> 00:27:42,200
Speaker 3: It's been a week where I feel that you haven't

558
00:27:42,200 --> 00:27:44,960
Speaker 3: actually mentioned AI yet much. I mean, autonomous vehicles is

559
00:27:45,000 --> 00:27:48,080
Speaker 3: inherently AI. How much there were your workforce using it,

560
00:27:48,160 --> 00:27:50,679
Speaker 3: how much your workforce responding to having to use it?

561
00:27:50,760 --> 00:27:53,560
Speaker 3: And is there any stretch at which point you are

562
00:27:53,600 --> 00:27:55,840
Speaker 3: able to reduce your headcount or hiring on the back

563
00:27:55,880 --> 00:27:56,160
Speaker 3: of it.

564
00:27:57,160 --> 00:27:58,920
Speaker 9: You know, I love this question, and I think it's

565
00:27:58,960 --> 00:28:01,080
Speaker 9: really important for people to sort of get their arms

566
00:28:01,119 --> 00:28:04,360
Speaker 9: around this. Absolutely, are something like eighty six percent now

567
00:28:04,359 --> 00:28:08,399
Speaker 9: of our developers, our software engineers are using actively, like

568
00:28:08,440 --> 00:28:11,040
Speaker 9: every single day, using AI to write code for them.

569
00:28:11,119 --> 00:28:13,200
Speaker 9: We're also using it in customer care. We're using all

570
00:28:13,200 --> 00:28:15,200
Speaker 9: over the place. But I think there's a way of

571
00:28:15,240 --> 00:28:17,480
Speaker 9: thinking about it which is not so much about cost

572
00:28:17,480 --> 00:28:22,080
Speaker 9: reduction but about velocity increase and capacity building. You know,

573
00:28:22,200 --> 00:28:25,159
Speaker 9: our imaginations are huge and we're a customer obsessed company,

574
00:28:25,200 --> 00:28:27,560
Speaker 9: so we have no shortage of great ideas to innovate

575
00:28:27,600 --> 00:28:30,000
Speaker 9: on behalf of customers. I think that's really where AI

576
00:28:30,080 --> 00:28:31,320
Speaker 9: is going to give us a big edge.

577
00:28:31,440 --> 00:28:33,160
Speaker 2: Not so much on this sort I mean cost.

578
00:28:33,240 --> 00:28:34,960
Speaker 9: Sure, we can maybe save a little bit money, but

579
00:28:35,000 --> 00:28:36,800
Speaker 9: there's so much more value if we can figure out

580
00:28:37,000 --> 00:28:40,240
Speaker 9: new great ways for riders and drivers to use our platform.

581
00:28:40,640 --> 00:28:44,240
Speaker 3: Is it a more competitive backdrop right now? To say

582
00:28:44,240 --> 00:28:46,920
Speaker 3: one more time, is it a more competitive backdrop right now?

583
00:28:47,760 --> 00:28:50,560
Speaker 9: Well, it is, you know, but only in the following sense.

584
00:28:50,640 --> 00:28:50,840
Speaker 2: You know.

585
00:28:51,080 --> 00:28:53,240
Speaker 9: Remember there one hundred and sixty billion rides that people

586
00:28:53,280 --> 00:28:55,960
Speaker 9: take in their private car every single year, and I

587
00:28:56,000 --> 00:28:58,760
Speaker 9: think that's ultimately going to be the real competition for us. Look,

588
00:28:58,840 --> 00:29:01,360
Speaker 9: it's fifty thousand dollars to buy a car eight hundred

589
00:29:01,360 --> 00:29:04,440
Speaker 9: bucks a month plus insurance, plus gas, plus maintenance, whereas

590
00:29:04,440 --> 00:29:06,520
Speaker 9: lift is you know, twenty bucks a ride. So in

591
00:29:06,560 --> 00:29:08,600
Speaker 9: a funny way, I think the competition is going to

592
00:29:08,640 --> 00:29:10,960
Speaker 9: shift a little away from the other guys and a

593
00:29:11,000 --> 00:29:12,840
Speaker 9: little bit more towards what are good ways for you

594
00:29:12,880 --> 00:29:14,760
Speaker 9: to spend your money and how can you live your best.

595
00:29:14,600 --> 00:29:16,400
Speaker 2: Life and rewards?

596
00:29:16,440 --> 00:29:20,000
Speaker 9: Max and rewards. Max exactly, I'm glad you picked up on.

597
00:29:20,000 --> 00:29:23,560
Speaker 2: That I shouldn't have done. David H. We love having

598
00:29:23,600 --> 00:29:24,960
Speaker 2: you on the show. Thank you very much.

599
00:29:24,960 --> 00:29:28,320
Speaker 3: Indeed, the CEO of Lyft coming up, we take a

600
00:29:28,360 --> 00:29:31,640
Speaker 3: look at Enhanced. There's a Pewter teil back to elite

601
00:29:31,680 --> 00:29:33,880
Speaker 3: sports competition and performance products company.

602
00:29:34,160 --> 00:29:35,120
Speaker 2: It's gone public today.

603
00:29:35,640 --> 00:29:45,080
Speaker 3: More Next, this is a Blue Beg Tech, an Olympic

604
00:29:45,200 --> 00:29:49,520
Speaker 3: style sports event that welcomes performance enhancing drugs, set for.

605
00:29:49,520 --> 00:29:50,760
Speaker 2: Later this month in Las Vegas.

606
00:29:50,840 --> 00:29:53,600
Speaker 3: Today, the company behind that endeavor went public in a

607
00:29:53,640 --> 00:29:56,400
Speaker 3: merger with a blank check company with Enhanced now as

608
00:29:56,440 --> 00:29:58,920
Speaker 3: you see, trading up eight point eight percent following the transaction.

609
00:30:00,000 --> 00:30:02,160
Speaker 3: One point two billion dollars in this back and has

610
00:30:02,200 --> 00:30:05,000
Speaker 3: backing from like Sir Peter Tiill and former coinbased CTO

611
00:30:05,320 --> 00:30:06,360
Speaker 3: Large Shunavessan.

612
00:30:06,600 --> 00:30:07,880
Speaker 2: Now the company CEO now.

613
00:30:07,880 --> 00:30:10,320
Speaker 3: Joins us Maximilian Martin from the Flora of the New

614
00:30:10,400 --> 00:30:11,200
Speaker 3: York Stock Exchange.

615
00:30:11,240 --> 00:30:15,240
Speaker 2: So go on public? Why why need it?

616
00:30:15,720 --> 00:30:17,560
Speaker 10: First of all, hello and thank you to having me

617
00:30:17,600 --> 00:30:19,600
Speaker 10: on the show today. We're going public because Enhanced there

618
00:30:19,640 --> 00:30:21,600
Speaker 10: is a movement and we want the people in that

619
00:30:21,680 --> 00:30:23,680
Speaker 10: movement not just to be part of it by watching

620
00:30:23,680 --> 00:30:27,120
Speaker 10: the sports or buying enhancement products through a live enhanced platform,

621
00:30:27,160 --> 00:30:28,960
Speaker 10: but by owning a piece of it too. This is

622
00:30:28,960 --> 00:30:32,000
Speaker 10: why we've decided to go public and which we're very

623
00:30:32,000 --> 00:30:34,720
Speaker 10: excited about having done and concluded the transaction today.

624
00:30:34,920 --> 00:30:37,840
Speaker 2: So there's a is it a retail investment play? Here?

625
00:30:37,880 --> 00:30:40,000
Speaker 3: More broadly, Maximilian, is it the people that you want

626
00:30:40,040 --> 00:30:43,600
Speaker 3: to purchase not only the products so called longevity products

627
00:30:43,640 --> 00:30:45,840
Speaker 3: maybe they're peptides, but also those who are then going

628
00:30:45,880 --> 00:30:47,800
Speaker 3: to come and watch the enhanced games?

629
00:30:49,440 --> 00:30:51,560
Speaker 10: Sorry, can you repeat the question? I didn't catch that fully.

630
00:30:51,640 --> 00:30:54,040
Speaker 3: Is it a retail investor that you're most focused on?

631
00:30:55,240 --> 00:30:55,400
Speaker 2: Ah?

632
00:30:55,480 --> 00:30:58,719
Speaker 10: Yes, yes, so I think enhanced there's a stock opportunity

633
00:30:58,800 --> 00:31:01,040
Speaker 10: is really for everyone, but I think particularly exciting for

634
00:31:01,120 --> 00:31:05,720
Speaker 10: retail too, because sports traditionally isn't as investable for retail

635
00:31:05,760 --> 00:31:08,240
Speaker 10: as it is for, for example, more institutional like players.

636
00:31:08,400 --> 00:31:11,800
Speaker 10: This is why we're very excited about retail particularly getting

637
00:31:11,800 --> 00:31:13,880
Speaker 10: focused on the opportunity that's ahead of them now with

638
00:31:13,960 --> 00:31:15,320
Speaker 10: us listed on the exchange here.

639
00:31:15,800 --> 00:31:19,560
Speaker 3: If you look at past media attention on the games,

640
00:31:19,600 --> 00:31:24,200
Speaker 3: in particular people who sort of called it Olympics on steroids,

641
00:31:24,400 --> 00:31:27,560
Speaker 3: Why is it not that from your perspective, Maximilian.

642
00:31:28,360 --> 00:31:31,480
Speaker 10: Yeah, because steroids is a term that has very many

643
00:31:31,560 --> 00:31:34,680
Speaker 10: negative associations with it. Many people associated with it to

644
00:31:34,720 --> 00:31:37,240
Speaker 10: be also illegal, and that is not true for the

645
00:31:37,280 --> 00:31:39,760
Speaker 10: setup that's been created at the Enhanced Games. What the

646
00:31:39,800 --> 00:31:42,880
Speaker 10: athletes can actually take at the Enhanced Games are FDA

647
00:31:42,960 --> 00:31:46,560
Speaker 10: proof substances under a doctor's supervision. And they also all

648
00:31:46,680 --> 00:31:49,280
Speaker 10: independent of them enhancing or not, need to pass medical

649
00:31:49,280 --> 00:31:51,880
Speaker 10: screenings that we do with them over time to determine

650
00:31:51,880 --> 00:31:55,120
Speaker 10: whether they're ahealthy and be safe to compete. So steroids

651
00:31:55,160 --> 00:31:57,960
Speaker 10: is really for people thinking about happening in the garage,

652
00:31:58,000 --> 00:32:01,000
Speaker 10: in the backdoor locker room of a gym, etc. But

653
00:32:01,080 --> 00:32:03,040
Speaker 10: that's not it. This is out all in the open

654
00:32:03,760 --> 00:32:08,880
Speaker 10: with pleregulation around it that makes enhancements for the athletes,

655
00:32:08,920 --> 00:32:11,600
Speaker 10: but then also the consumers that we offer it to safe.

656
00:32:13,640 --> 00:32:14,280
Speaker 2: Fascinating.

657
00:32:14,440 --> 00:32:18,760
Speaker 3: Your aim is to evolve mankind into a new super humanity.

658
00:32:19,160 --> 00:32:21,040
Speaker 3: We'll have you back, Maximian Martin, thank you very much

659
00:32:21,040 --> 00:32:25,040
Speaker 3: for joining us today. The CEO of Enhanced Now stable coins.

660
00:32:25,120 --> 00:32:28,720
Speaker 3: They promised to make cross border payments cheaper and nearly instantaneous,

661
00:32:28,760 --> 00:32:30,680
Speaker 3: but it remains a tiny part of the global payment

662
00:32:30,720 --> 00:32:33,760
Speaker 3: system today, the Genius Act set to take effect and

663
00:32:33,920 --> 00:32:36,680
Speaker 3: banks eyeing the space. The Wall Street Week team to

664
00:32:36,720 --> 00:32:38,920
Speaker 3: a deep dive into whether the use of the blockchain

665
00:32:38,960 --> 00:32:41,040
Speaker 3: technology is truly starting to scale.

666
00:32:41,920 --> 00:32:45,080
Speaker 11: So you'll hear in the media the trillions of dollars

667
00:32:45,120 --> 00:32:48,880
Speaker 11: of stable coin payments today. Ninety nine percent of that

668
00:32:49,120 --> 00:32:52,800
Speaker 11: is crypto related, not the sort of payments we think about,

669
00:32:52,880 --> 00:32:56,640
Speaker 11: which is company to company or even paying remittances person

670
00:32:56,680 --> 00:32:59,320
Speaker 11: to person. And so we look at this situation today

671
00:32:59,360 --> 00:33:02,440
Speaker 11: and say how much real payments volume is there out there,

672
00:33:02,920 --> 00:33:04,920
Speaker 11: and we think it's probably the order of a billion

673
00:33:05,000 --> 00:33:08,440
Speaker 11: or two a day, which is tiny. The late assessments

674
00:33:08,440 --> 00:33:12,080
Speaker 11: we have are three hundred and ninety billion dollars in

675
00:33:12,120 --> 00:33:16,440
Speaker 11: the total year, and that compares with several trillion dollars

676
00:33:16,680 --> 00:33:18,360
Speaker 11: of regular payments per day.

677
00:33:18,600 --> 00:33:20,880
Speaker 9: So a SMaL mart right now, how does it compare

678
00:33:20,960 --> 00:33:23,960
Speaker 9: with last year, and how does it compare with forecast

679
00:33:24,000 --> 00:33:24,760
Speaker 9: for next year.

680
00:33:25,200 --> 00:33:29,000
Speaker 11: The data shows that the volume of real payment transactions

681
00:33:29,080 --> 00:33:32,960
Speaker 11: using stable coins probably doubled over the last year. When

682
00:33:33,000 --> 00:33:35,400
Speaker 11: you look at the volume of stable coins in circulation,

683
00:33:35,560 --> 00:33:38,280
Speaker 11: that went from around one hundred and fifty billion dollars

684
00:33:38,320 --> 00:33:41,880
Speaker 11: to three hundred billion dollars today it's doubling, which by

685
00:33:41,920 --> 00:33:44,600
Speaker 11: any measure is substantial in terms of growth.

686
00:33:44,960 --> 00:33:48,000
Speaker 5: How much of that is cross border international? Essentially? How

687
00:33:48,040 --> 00:33:49,400
Speaker 5: much of it is domestic?

688
00:33:49,840 --> 00:33:52,960
Speaker 11: The vast majority is cross border. It's interesting. We've been

689
00:33:53,000 --> 00:33:56,760
Speaker 11: looking at the geographic source of those payments with our

690
00:33:56,960 --> 00:34:01,560
Speaker 11: research partner, Artemis Analytics. What they founders about sixty percent

691
00:34:01,760 --> 00:34:04,840
Speaker 11: originates from Asia, and that surprises a little bit because

692
00:34:04,880 --> 00:34:06,960
Speaker 11: a lot of the talk has been in North America

693
00:34:07,040 --> 00:34:09,120
Speaker 11: or Europe about the potential of stable coins.

694
00:34:09,400 --> 00:34:11,759
Speaker 3: March the full Wall Street Week episode later today at

695
00:34:11,800 --> 00:34:16,080
Speaker 3: six pm Eastern three pm Pacific time. Now, cybersecurity fears

696
00:34:16,080 --> 00:34:19,480
Speaker 3: are sweeping through global campuses after hackers disrupted a portal

697
00:34:19,600 --> 00:34:22,360
Speaker 3: used by thousands of colleges, including Harvin Princeton.

698
00:34:22,680 --> 00:34:24,080
Speaker 2: Look Infrastructure, which.

699
00:34:23,960 --> 00:34:27,360
Speaker 3: Runs the Canvas service used by students, was forced to

700
00:34:27,400 --> 00:34:30,560
Speaker 3: suspend the system, sparking warnings that sensitive student data our

701
00:34:30,600 --> 00:34:33,919
Speaker 3: messages may have been stolen for extortion. Earlier this hour,

702
00:34:33,920 --> 00:34:36,960
Speaker 3: we understood that Cornell University said its own Canvas access

703
00:34:37,200 --> 00:34:46,160
Speaker 3: has been fully restored. Three Mile Island, the site of

704
00:34:46,160 --> 00:34:49,719
Speaker 3: the most famous US nuclear accident, is coming back online

705
00:34:49,800 --> 00:34:52,120
Speaker 3: as soon as mid twenty twenty seven that's powered by

706
00:34:52,120 --> 00:34:55,799
Speaker 3: a long term deal by Microsoft and Constellation Energy to power. Yes,

707
00:34:55,800 --> 00:34:58,160
Speaker 3: you've guessed it, AI applications, chatbots, much more.

708
00:34:58,160 --> 00:34:58,680
Speaker 2: Bloombergs.

709
00:34:58,680 --> 00:35:02,160
Speaker 3: Wild Wade is here with any extraordinary deep dive into

710
00:35:02,239 --> 00:35:06,239
Speaker 3: what has now been rebranded unsurprisingly, but remind those what

711
00:35:06,320 --> 00:35:08,319
Speaker 3: three Mile Island means to many and why it's so

712
00:35:08,320 --> 00:35:09,600
Speaker 3: important that comes back online.

713
00:35:09,680 --> 00:35:14,000
Speaker 12: Okay, to many, it means nuclear disaster. Nineteen seventy nine,

714
00:35:14,360 --> 00:35:17,440
Speaker 12: it was the site of the worst nuclear accident in

715
00:35:17,600 --> 00:35:20,319
Speaker 12: US history. But let's keep in mind nineteen seventy nine

716
00:35:20,360 --> 00:35:21,480
Speaker 12: was like a long time ago.

717
00:35:21,719 --> 00:35:22,480
Speaker 2: No, last night.

718
00:35:22,520 --> 00:35:24,359
Speaker 12: I actually told my son, Hey, I have this big

719
00:35:24,360 --> 00:35:26,120
Speaker 12: story coming out on Three Mile Island.

720
00:35:26,120 --> 00:35:26,799
Speaker 2: He's like, what's that?

721
00:35:27,600 --> 00:35:30,000
Speaker 12: So for a lot of us it has a lot

722
00:35:30,000 --> 00:35:32,919
Speaker 12: of meaning, but for younger people it has no meaning

723
00:35:32,920 --> 00:35:33,200
Speaker 12: at all.

724
00:35:33,880 --> 00:35:36,080
Speaker 2: Well, you don't talk about your job nearly enough at home.

725
00:35:36,160 --> 00:35:39,120
Speaker 3: Quite clearly, it's a nuclear reporter reporting on the sector.

726
00:35:39,120 --> 00:35:41,880
Speaker 3: Sin's twenty nineteen, when initially it was all about closures,

727
00:35:41,920 --> 00:35:44,480
Speaker 3: You're now into this area where it's about reopenings.

728
00:35:44,800 --> 00:35:46,200
Speaker 2: Yeah, nuclear renaissance.

729
00:35:46,239 --> 00:35:47,880
Speaker 3: What did you learn by going into what is the

730
00:35:47,920 --> 00:35:50,080
Speaker 3: rebranded crane Clean Energy Center.

731
00:35:50,200 --> 00:35:51,440
Speaker 5: You know what's really fascinating.

732
00:35:51,480 --> 00:35:53,319
Speaker 12: And if you see the pictures on the story.

733
00:35:53,160 --> 00:35:55,040
Speaker 2: Yeah it looks old, it doesn't.

734
00:35:55,080 --> 00:35:58,160
Speaker 12: It looks really old schools because it is because it

735
00:35:58,200 --> 00:36:01,560
Speaker 12: was like designed and built like the sixties and seventies,

736
00:36:01,600 --> 00:36:05,279
Speaker 12: and so much of the US nuclear power plants date

737
00:36:05,360 --> 00:36:08,960
Speaker 12: back to, you know, the last century, because we really

738
00:36:09,040 --> 00:36:11,920
Speaker 12: haven't built very many of them at all. But right

739
00:36:11,960 --> 00:36:16,000
Speaker 12: now there's just this insatiable demand for electricity from the

740
00:36:16,040 --> 00:36:19,320
Speaker 12: big tech companies. It's for AI. It's all for AI.

741
00:36:19,960 --> 00:36:22,400
Speaker 12: You know, a while ago they're like, we want nuclear

742
00:36:22,440 --> 00:36:24,680
Speaker 12: because it's clean, it's going to help us save the

743
00:36:24,719 --> 00:36:27,719
Speaker 12: world from climate change, and that sort of was a

744
00:36:27,800 --> 00:36:31,200
Speaker 12: little bit of a motivation. But really the motivation now

745
00:36:31,200 --> 00:36:34,960
Speaker 12: it's from tech, it's from AI. It's because there's money involved.

746
00:36:34,840 --> 00:36:35,520
Speaker 2: A lot of money.

747
00:36:35,520 --> 00:36:37,719
Speaker 3: I think thirty billion has been invested in nuclear since

748
00:36:37,800 --> 00:36:41,359
Speaker 3: twenty twenty. But what about the waste, Like, what how

749
00:36:41,360 --> 00:36:43,920
Speaker 3: has that changed since nineteen seventy nine, Well, that hasn't

750
00:36:44,000 --> 00:36:45,360
Speaker 3: changed at all, So what are they going to do

751
00:36:45,440 --> 00:36:49,040
Speaker 3: with it? They're going to do what they've always seen energy.

752
00:36:49,400 --> 00:36:51,440
Speaker 12: If you go to any nuclear power plant, if you

753
00:36:51,480 --> 00:36:54,399
Speaker 12: go out back, there's these giant casks where they store

754
00:36:54,440 --> 00:36:58,839
Speaker 12: the waste. They've always been there, and there's been talk

755
00:36:58,960 --> 00:37:02,319
Speaker 12: of creating a central repository in the US. It's been

756
00:37:02,400 --> 00:37:06,520
Speaker 12: stalled for political reasons. So that's just not happening.

757
00:37:06,640 --> 00:37:09,520
Speaker 3: So isn't it funny that the very edge of innovation

758
00:37:10,480 --> 00:37:12,520
Speaker 3: is sort of being fueled by something that doesn't seem

759
00:37:12,560 --> 00:37:14,279
Speaker 3: to be innovating for very much at tool we're relying

760
00:37:14,280 --> 00:37:18,400
Speaker 3: on a nineteen seventy nine building. How is it innovating?

761
00:37:18,440 --> 00:37:20,680
Speaker 3: How are we seeing SMRs come into play? Will we

762
00:37:20,760 --> 00:37:22,480
Speaker 3: get a new type of nuclear offering?

763
00:37:22,680 --> 00:37:22,879
Speaker 2: Yeah?

764
00:37:22,920 --> 00:37:25,040
Speaker 12: See, that's a good question. There is a lot of

765
00:37:25,080 --> 00:37:29,040
Speaker 12: innovation in the nuclear space. There's companies developing all kinds

766
00:37:29,080 --> 00:37:32,319
Speaker 12: of new reactor designs. There's new big ones, there's new

767
00:37:32,360 --> 00:37:35,279
Speaker 12: small ones. There's new really really small ones. They want

768
00:37:35,360 --> 00:37:38,319
Speaker 12: to put them on a shipping container and deliver them

769
00:37:38,360 --> 00:37:41,040
Speaker 12: to military bases in the middle of nowhere. There's a

770
00:37:41,080 --> 00:37:44,839
Speaker 12: lot of innovation. It's not here yet. I really do

771
00:37:44,880 --> 00:37:48,399
Speaker 12: think it's coming. There's just so much motivation to make

772
00:37:48,440 --> 00:37:52,760
Speaker 12: this happen. So what are we twenty twenty six, twenty thirty,

773
00:37:52,880 --> 00:37:56,040
Speaker 12: twenty thirty, mid twenty thirties. I think we'll see some,

774
00:37:56,239 --> 00:37:58,560
Speaker 12: but not for the next several years.

775
00:37:58,760 --> 00:38:01,160
Speaker 3: It's wholly world of uranium in Richmond, and you've got

776
00:38:01,200 --> 00:38:04,040
Speaker 3: so many amazing stories to tell about it. We'll wade

777
00:38:04,120 --> 00:38:05,759
Speaker 3: here with us on the latest. You've got to go

778
00:38:05,760 --> 00:38:09,200
Speaker 3: and read it the Big Take today. Now we're going

779
00:38:09,280 --> 00:38:11,440
Speaker 3: to move on and talk about a key company behind

780
00:38:11,480 --> 00:38:13,960
Speaker 3: Thailand's national AI effort, now.

781
00:38:13,760 --> 00:38:15,160
Speaker 2: Called Obon Corp.

782
00:38:15,600 --> 00:38:19,040
Speaker 3: It's suspected, though, of helping to smuggle servers containing advanced

783
00:38:19,040 --> 00:38:21,560
Speaker 3: and video chips to China. That's according to sources who

784
00:38:21,600 --> 00:38:23,760
Speaker 3: say some of the two and a half billion dollars

785
00:38:23,800 --> 00:38:28,200
Speaker 3: worth of service sold by Obon obo n allegedly went

786
00:38:28,239 --> 00:38:31,920
Speaker 3: to Chinese AI leader Ali Bubba. This comes as US

787
00:38:31,960 --> 00:38:34,279
Speaker 3: officials are walking a pretty delicate line when it comes

788
00:38:34,280 --> 00:38:37,200
Speaker 3: to the Trump administration's approach to Beijing. Earlier this year,

789
00:38:37,200 --> 00:38:40,160
Speaker 3: the Pentagon added Ali, Baba and Baidu to a list

790
00:38:40,160 --> 00:38:43,080
Speaker 3: of companies that aid the Chinese military, and then promptly

791
00:38:43,080 --> 00:38:46,000
Speaker 3: declared the list unpublished. So Wilimag's tech editor in DC,

792
00:38:46,160 --> 00:38:50,279
Speaker 3: Michael Shepherd, joins us now with this previously unreported details

793
00:38:50,520 --> 00:38:53,760
Speaker 3: of what is happening with this so called blacklist.

794
00:38:54,200 --> 00:38:57,000
Speaker 13: Well, Caro let's turn the clock back to that day

795
00:38:57,040 --> 00:39:00,319
Speaker 13: in February. It was Friday the thirteenth. Then you and

796
00:39:00,440 --> 00:39:03,320
Speaker 13: I on this program. We're trying to pick our jaws

797
00:39:03,400 --> 00:39:06,440
Speaker 13: up off the floor, figuring out not only the import

798
00:39:06,520 --> 00:39:09,680
Speaker 13: of this list being published, but the mystery behind why

799
00:39:09,800 --> 00:39:12,120
Speaker 13: it was abruptly withdrawn minutes later.

800
00:39:12,440 --> 00:39:13,279
Speaker 5: What was going on?

801
00:39:13,480 --> 00:39:16,080
Speaker 13: What would that say about China policy. Well, our colleague

802
00:39:16,120 --> 00:39:18,879
Speaker 13: Cato Keef here in Washington set out to find out

803
00:39:18,920 --> 00:39:22,279
Speaker 13: the backstory, and it's revealing. It turns out that the

804
00:39:22,320 --> 00:39:25,759
Speaker 13: Pentagon had withdrawn two names from the list. Dropped two

805
00:39:25,880 --> 00:39:30,520
Speaker 13: names from the list Chinese chip makers YMTC and CXMT.

806
00:39:31,480 --> 00:39:34,760
Speaker 13: They're producers of memory products that are really in demand

807
00:39:34,840 --> 00:39:37,640
Speaker 13: these days, of course, as we know, and the White

808
00:39:37,640 --> 00:39:39,680
Speaker 13: House of one of them kept on when the list

809
00:39:39,760 --> 00:39:43,040
Speaker 13: was published, the names weren't there. The White House was furious.

810
00:39:43,280 --> 00:39:46,560
Speaker 13: The Pentagon quickly moved to pull it back in. Since then,

811
00:39:46,600 --> 00:39:50,080
Speaker 13: we have not seen this list republished, and in part

812
00:39:50,120 --> 00:39:52,880
Speaker 13: because we are in such a delicate moment in this

813
00:39:53,040 --> 00:39:56,239
Speaker 13: trade truce between Washington and Beijing. That's the one that

814
00:39:56,280 --> 00:40:00,600
Speaker 13: President Donald Trump announced with Shi Jimping in Lei October

815
00:40:00,680 --> 00:40:03,120
Speaker 13: after their meeting and of course they have a meeting

816
00:40:03,200 --> 00:40:05,399
Speaker 13: coming up next week, and this is just the kind

817
00:40:05,440 --> 00:40:08,960
Speaker 13: of misstep that really can upset the apple cart heading

818
00:40:09,000 --> 00:40:12,360
Speaker 13: into such a high stakes encounter between leaders of the

819
00:40:12,360 --> 00:40:14,000
Speaker 13: world's two largest economies.

820
00:40:14,239 --> 00:40:17,400
Speaker 3: So let's think about next week, because there is talk

821
00:40:17,480 --> 00:40:20,880
Speaker 3: that maybe even future rules of generative AI and the

822
00:40:20,960 --> 00:40:25,000
Speaker 3: latest greatest LLM might be something's discussed by Treasures actually

823
00:40:25,040 --> 00:40:27,800
Speaker 3: beston and others as reporting around that mind, how interested as.

824
00:40:27,640 --> 00:40:29,160
Speaker 2: To what you think will be achieved and.

825
00:40:29,120 --> 00:40:32,439
Speaker 3: What names will be announced or working together or working

826
00:40:32,480 --> 00:40:33,319
Speaker 3: apart from each other?

827
00:40:33,719 --> 00:40:36,600
Speaker 13: Well, it's a great question, Carol. And the war in

828
00:40:36,640 --> 00:40:40,440
Speaker 13: Iran really has overshadowed any of the other initiatives that

829
00:40:40,640 --> 00:40:45,160
Speaker 13: might be put on the table between presidents She and

830
00:40:45,280 --> 00:40:48,360
Speaker 13: Trump as they sit down to talk. You know, absent

831
00:40:48,440 --> 00:40:51,440
Speaker 13: the war, we might have seen more talk about access

832
00:40:51,560 --> 00:40:56,160
Speaker 13: to American design chips, like from Nvidia and AMD. The

833
00:40:56,200 --> 00:40:59,600
Speaker 13: President and his team have cleared the release of the

834
00:40:59,719 --> 00:41:03,239
Speaker 13: H hundreds from Nvidia and comparable products from A and

835
00:41:03,360 --> 00:41:07,440
Speaker 13: D for sales to China. But the big asterisk is

836
00:41:07,480 --> 00:41:10,160
Speaker 13: that Beijing so far is really not letting too many

837
00:41:10,239 --> 00:41:13,000
Speaker 13: of those products in and we haven't seen very many

838
00:41:13,239 --> 00:41:16,840
Speaker 13: licenses issued from the US side either, so there is

839
00:41:16,920 --> 00:41:19,680
Speaker 13: clearly some sort of a log jam and perhaps they

840
00:41:19,760 --> 00:41:22,440
Speaker 13: could get to the bottom of that. Iran, of course,

841
00:41:22,480 --> 00:41:24,279
Speaker 13: could stand in the way. And then there are the

842
00:41:24,320 --> 00:41:29,080
Speaker 13: complaints from American AI developers Open Ai, Anthropic and Google

843
00:41:29,400 --> 00:41:34,160
Speaker 13: that Chinese rivals have been distilling unfairly the results of

844
00:41:34,280 --> 00:41:38,400
Speaker 13: their models to produce rival chatbots at a fraction of

845
00:41:38,440 --> 00:41:41,320
Speaker 13: the cost. And this is prompted and outcry on Capitol

846
00:41:41,360 --> 00:41:44,640
Speaker 13: Hill and also steps from the White House to try

847
00:41:44,640 --> 00:41:46,879
Speaker 13: to rein in and address that practice. So we could

848
00:41:46,920 --> 00:41:49,520
Speaker 13: also see that come up as well. And then of

849
00:41:49,520 --> 00:41:52,760
Speaker 13: course there is the question of rarer scro which really

850
00:41:52,800 --> 00:41:55,080
Speaker 13: lies at the heart of the conflict between the US

851
00:41:55,120 --> 00:41:55,560
Speaker 13: and China.

852
00:41:55,760 --> 00:41:58,440
Speaker 3: Well said most Mutch Sheppard a feeling we might be

853
00:41:58,480 --> 00:42:01,480
Speaker 3: retricing some of those talks as we look ahead to

854
00:42:01,560 --> 00:42:02,200
Speaker 3: next week too.

855
00:42:02,200 --> 00:42:02,440
Speaker 2: With you.

856
00:42:02,640 --> 00:42:04,520
Speaker 3: That does it for this edition of Boomberg Tech. Don't

857
00:42:04,520 --> 00:42:05,960
Speaker 3: forget to check out our podcasts. You can find it

858
00:42:06,000 --> 00:42:08,560
Speaker 3: on the terminal as well as online Apple, Spotify, iHeart

859
00:42:09,040 --> 00:42:09,560
Speaker 3: wishing you.

860
00:42:09,520 --> 00:42:12,239
Speaker 2: All a very wonderful weekend. See you Monday. This is

861
00:42:12,239 --> 00:42:12,919
Speaker 2: Boomberg Tech