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Speaker 1: Bloomberg Audio Studios, podcasts, radio news from the heart of

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Speaker 1: where innovation, money and power collide in Silicon Valley and beyond.

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Speaker 1: This is Bloomberg Technology with Caroline Hyde and Ed Lovelow.

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Speaker 2: Live from New York. I'm Caroline Hyde.

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Speaker 3: And I'm Mike Sheppard in San Francisco. This is Bloomberg Technology.

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Speaker 4: Coming up asml fights back Deep Seak concerns and surges

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Speaker 4: the most since twenty twenty as stronger chip equipment orders,

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Speaker 4: Impress plus, did Deep Seek improperly use open ai data?

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Speaker 4: Microsoft and open Ai investigate? We have the latest and

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Speaker 4: we sit down with T Mobile CEO on the heels

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Speaker 4: of the company's standout fourth quarter.

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Speaker 2: But first we check in on these markets.

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Speaker 4: Remember, folks, it is fed day where we get a

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Speaker 4: pause that comes later today.

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Speaker 2: But we're off by four tens percent.

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Speaker 4: Now's that on the downside, we're being dragged down by

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Speaker 4: the like some video Microsoft in the red. Let's move

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Speaker 4: on and see what earnings we have coming off after

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Speaker 4: the bell because it is thick and fast. Not only

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Speaker 4: are we reading from deep Seek, but we've got to.

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Speaker 2: Digest the real numbers.

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Speaker 4: Microsoft, Meta, Tesla, Apple a little bit later, but tonight,

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Speaker 4: we keep an eye on these front three and then

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Speaker 4: we think about what we've already had out of the

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Speaker 4: bell in Europe and is ASML the chip equipment maker

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Speaker 4: managing to fight back some of those anxieties around deep

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Speaker 4: seek cheap AA models? Ultimately does it matter for chips?

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Speaker 4: For chip equipment ASML surging currently we see up five

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Speaker 4: percent in US trading. It was up the most that's

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Speaker 4: twenty twenty earlier, Mike, and this was on the back

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Speaker 4: of very strong orders.

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Speaker 3: And we're staying on ASML and their big earnings. Be

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Speaker 3: joining us to discuss this is Bloomberg's Chan coach in Amsterdam.

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Speaker 5: Chan.

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Speaker 3: There were a surgeon orders in the last quarter for ASML,

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Speaker 3: far more than expected. But all of that was before

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Speaker 3: the deep Seek revelations. How did the CEO of ASML

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Speaker 3: message this to investors today?

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Speaker 6: All right?

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Speaker 7: CHRISTOSML CEO doubled down on AI. Basically, he thinks Deep

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Speaker 7: Seek will be good news for ASML, and his thinking

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Speaker 7: is that anyone that lowers cost lowers barriers to entry,

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Speaker 7: so lower cost means AI can be used in more applications.

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Speaker 7: More applications mean more chips, and more chips would mean

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Speaker 7: ASML can sell more machines to chip makers, and they

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Speaker 7: think deep sea can lead to democratization of AI, which

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Speaker 7: will then create more customers for them charm.

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Speaker 3: When we talk about chips, we can't get away from geopolitics.

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Speaker 3: How did some of the US restrictions on sales of

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Speaker 3: sensitive equipment to China play in the results that we

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Speaker 3: saw today?

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Speaker 7: Will China accounted for twenty seven percent of ASML sales

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Speaker 7: in the fourth quarter, which was down from nearly half

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Speaker 7: of its sales in the third quarter. The company expects

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Speaker 7: China sales to follow up one fifth of its total

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Speaker 7: revenue this year, and they think that their sales in

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Speaker 7: China are taking a hit from the prospect of more

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Speaker 7: US restrictions under Donald Trump's administration, as well as a

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Speaker 7: broader weakness in the chip sector.

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Speaker 5: Bloomberg's John Coach, thank you so much, Caro.

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Speaker 4: We booke a plenty more earnings and other socks we're

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Speaker 4: watching this morning.

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Speaker 2: Apple t Mobile.

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Speaker 4: In particular, two companies that have been working secretly together.

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Speaker 4: We understand ad support for SpaceX is Starling network in

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Speaker 4: a surprise release. The tech is now being supported with

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Speaker 4: an installation of the iPhone's latest software update on Monday,

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Speaker 4: but more on T Mobile because.

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Speaker 2: The company, of course is out with this fourth quarter.

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Speaker 4: Results beating analyst expectations. The telecom providers saw continued growth

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Speaker 4: in wireless subscribers and home internet customers. Get this, adding

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Speaker 4: nine hundred and three thousand monthly phone customers and guiding

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Speaker 4: from continued strong growth. Joining us now might see that

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Speaker 4: his Tmobile CEO. And what's interesting is descend. But you said,

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Speaker 4: be cautious about our fourth quarter.

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Speaker 2: What changed?

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Speaker 8: Well, the only thing I was pointing out back then,

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Speaker 8: which maybe was misunderstood, is that it's a seasonal quarter,

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Speaker 8: and you know, the last couple of weeks are important.

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Speaker 8: But you know, we just are firing on all cylinders.

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Speaker 8: We just finished our strongest growth year ever, and we

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Speaker 8: finished it strong with a monster Q four that exceeded

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Speaker 8: a lot of people's expectations.

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Speaker 4: And you're guiding for postpaid net customers to be adding

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Speaker 4: up to six million in twenty twenty five. That's a

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Speaker 4: big ramp. Where are those customers coming to?

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Speaker 8: You know, this is the strongest beginning of year guide

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Speaker 8: on new subscribers we've ever given, and.

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Speaker 9: It's really simple.

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Speaker 8: Our consumer business is firing on all cylinders in the

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Speaker 8: top one hundred markets, also smaller markets in rural areas.

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Speaker 8: But now our business sector is starting to rise as well.

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Speaker 8: And so you look across all the segments. People are

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Speaker 8: flocking to.

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Speaker 4: T Mobile, governments to New York one of them that

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Speaker 4: you've added. But I'm interested that the other competitors out there,

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Speaker 4: at and T Verizon they added to where are these

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Speaker 4: customers coming from?

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Speaker 9: Look this is I like to think about this.

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Speaker 8: You know, we're the best house in a great neighborhood.

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Speaker 8: I don't need for our competitors to fail in order

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Speaker 8: for us to succeed. We are taking share. But also

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Speaker 8: the market is vibrant and growing, and people are, you know,

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Speaker 8: getting more value out of rate plans. They're buying up

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Speaker 8: our rate card. You know, our average revenues per customer

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Speaker 8: per month are rising, not because of rising prices, but

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Speaker 8: because they're self selecting up our rate card, and that

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Speaker 8: allows revenues to rise where nobody else is the loser.

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Speaker 4: People need more data. They're going to need more data

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Speaker 4: for Generator of AI. Is that become a choke point for.

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Speaker 2: You in some way?

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Speaker 8: It's going to be a way for us to showcase

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Speaker 8: our differentiation you know, both Oukla and Open Signal have

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Speaker 8: once again said we ran the gamut in terms of

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Speaker 8: network awards and we have the.

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Speaker 9: Most capacity by far.

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Speaker 8: And so as the demand for our network on AI

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Speaker 8: based applications starts to grow, it'll only showcase t mobiles differentiation.

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Speaker 8: I think consumers will really be able to see the difference.

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Speaker 4: Will consumers care about when they're out without any signal

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Speaker 4: and now they're able potentially to tap in to Starlin

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Speaker 4: easing team Mobile.

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Speaker 8: When we first announced this partnership in twenty twenty two,

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Speaker 8: it was the single most covered thing we've ever talked about.

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Speaker 8: And that's saying something because our uncarrier moves are big deals.

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Speaker 8: This is the biggest one because it speaks to a

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Speaker 8: universal pain point in this industry. This is a big

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Speaker 8: country and there are five hundred thousand square miles that

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Speaker 8: none of the carriers cover. And so now there's our

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Speaker 8: vision is so simple. If you can see the sky,

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Speaker 8: you're connected and you don't.

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Speaker 4: Have to point your phone at it anymore, which is

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Speaker 4: what you had to do with an Apple previously. Why

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Speaker 4: did you sort of roll it out so secretly? Why

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Speaker 4: did it feel like suddenly we woke up and quietly

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Speaker 4: you could get onto your T mobile iPhone device when

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Speaker 4: we wouldn't have thought it already.

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Speaker 8: Honestly, we've been a little self conscious than that. We

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Speaker 8: announced this a long time ago, and so it's been

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Speaker 8: a couple of years and we didn't want to keep

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Speaker 8: crowing about something until it was ready.

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Speaker 9: So we made a big.

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Speaker 8: Deal out of it when we struck the partnership and

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Speaker 8: we said, look, let's just stay quiet until it's time

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Speaker 8: to hand people this service. About two weeks ago we

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Speaker 8: quietly started letting people into our beta program. We now

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Speaker 8: have thousands of users and we're about to throw the

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Speaker 8: doors wide open on our beta. It's going to be

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Speaker 8: a big moment and then commercial service this year.

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Speaker 2: So it's performing well in beta.

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Speaker 8: Absolutely, and right now the launches are happening really rapidly.

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Speaker 8: So there's well over four hundred satellites. They're low Earth

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Speaker 8: orbit satellites, so they're very performant. You mentioned some of

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Speaker 8: the differences versus higher level satellites, and people are getting

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Speaker 8: a great experience.

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Speaker 6: You know.

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Speaker 9: Our goal is to.

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Speaker 8: Start with text messaging so that you can get your

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Speaker 8: texts out regardless of where you are, but it'll very

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Speaker 8: quickly move to picture messaging, MMS, data and voice.

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Speaker 4: I hate to try and find any clouds when you're

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Speaker 4: pointing to silver linings throughout, But when you signal that

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Speaker 4: caution in December, Yes, about sort of the cyclicality, but

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Speaker 4: ultimately you've had stellar growth after sellar growth. How much

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Speaker 4: can you keep on ramping, keep on bringing on more consumers?

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Speaker 4: How strong is the consumer sentiment out there?

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Speaker 8: It's steady and consistent. I think that's what you want

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Speaker 8: from us. You know, one of the things that differentiates

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Speaker 8: us is we set out a set of outlooks and

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Speaker 8: then we consistently meet or beat them. And what we

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Speaker 8: put out today was a strong guide, but it wasn't

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Speaker 8: expecting much from our business that we haven't done in

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Speaker 8: the past. And so you can rely on the things

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Speaker 8: that we say because we look at the trends underneath it.

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Speaker 8: And you know, the bottom line is we offer a

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Speaker 8: stronger network value proposition, and we offer it at a

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Speaker 8: lower price, and at the end of the day, that's

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Speaker 8: going to cause people across segments to continue choosing T Mobile.

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Speaker 4: What is it that investors in particular a needing at

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Speaker 4: this moment to hear from you? I mean you've got

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Speaker 4: twenty two buys, only nine holds and only two cells.

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Speaker 4: But where are you hearing the questions of caution coming

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Speaker 4: from an investor base right?

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Speaker 8: Well, they want to know what our next act is,

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Speaker 8: you know, And so that's a big piece of what

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Speaker 8: we focused on in our Capital Markets day last fall.

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Speaker 8: So talk about what comes be on the next couple

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Speaker 8: of years, and you know, AI is a big piece

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Speaker 8: of it. We're transforming our business operations to be able

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Speaker 8: to think about how do we serve customers in the

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Speaker 8: era of AI in new ways? And this industry has

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Speaker 8: always treated everybody exactly the same, and it's so analogue.

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Speaker 8: You go in and spend a Saturday of your life

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Speaker 8: in one of our retail stores trying to upgrade your

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Speaker 8: family to new phones.

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Speaker 9: We know we can do.

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Speaker 8: Better, and our Tea Life app that's now in the

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Speaker 8: hands of fifty million people can give you an experience

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Speaker 8: of T Mobile that's different than somebody else in terms

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Speaker 8: of the offers. You may see, the prioritization, the upgrades,

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Speaker 8: et cetera. And so it's an exciting moment for us

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Speaker 8: to rethink how we serve customers and give each customer

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Speaker 8: a fantastic journey with T Mobile.

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Speaker 4: What could the phone make has been doing better at

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Speaker 4: the moment because ultimately we see Apple getting another downgrade.

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Speaker 4: Many worries about China, but we aren't upgrading our phones

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Speaker 4: as much as we used to do. You have to

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Speaker 4: capitalize on giving the add ons in this moment because

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Speaker 4: Samsung and Apple just they're not presenting as new a

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Speaker 4: use cases as they used to.

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Speaker 9: Well, it works for our business model. I mean, I

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Speaker 9: can't speak for them.

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Speaker 8: One thing that's happening is upgrade rates have slowed down,

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Speaker 8: but they're pretty steady. Prices have risen, so the OEMs

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Speaker 8: have made up for it. That way, customers are keeping

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Speaker 8: their phones longer. But what you saw with T Mobile

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Speaker 8: this time is our upgrade rates did tick up a

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Speaker 8: little bit. With the lowest upgrade rates in the industry.

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Speaker 8: That's good for our financials. But they started to normalize,

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Speaker 8: so they ticked up. I signaled earlier in the quarter

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Speaker 8: that our iPhone sales were very strong, and they were,

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Speaker 8: and you saw it in our numbers.

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Speaker 2: Mike, so great to have you.

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Speaker 4: Great to see you again in the back of your earnings.

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Speaker 4: Come back soon. Mike's even is a T Mobile CEO,

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Speaker 4: Microsoft and open Ai are investigating where the deep seek

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Speaker 4: used data output from open AI's technology if it was

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Speaker 4: obtained in an unauthorized manner by a group linked to

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Speaker 4: the Chinese AI startups, all according to sources. Now, Deep

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Speaker 4: Seek and the High Flyer Hedge fund where deep Seak

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Speaker 4: was started, have not commented on there's so far, so

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Speaker 4: let's discuss it and the data privacy concerns around deep

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Speaker 4: seat with Alex Staemosi's chief mentioned security officer at Centinel

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Speaker 4: One and former chief security officer at Facebook. Look Alex

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Speaker 4: is open ai and indeed other AI labs at the moment.

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Speaker 4: Are they right to be concerned about their ip here?

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Speaker 9: I think they are.

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Speaker 10: There's a lot of people who doubt the claim that

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Speaker 10: deepsek was able to build such a incredibly capable model

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Speaker 10: with such a little compute and such as little cost

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Speaker 10: as they claim. Now there are some great breakthroughs here.

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Speaker 10: Deep Seek published at paper that demonstrated great breakthroughs in

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Speaker 10: both training cost and inference costs. So inference is what

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Speaker 10: you do when you're actually running the model for people

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Speaker 10: to use later, and they have some legitimate breakthroughs. So those

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Speaker 10: are breakthroughs that to their credit, they have documentary that

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Speaker 10: other people are going to be able to use now.

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Speaker 10: But there's a lot of people who believe that they

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Speaker 10: utilized both open AI's model probably running up in Microsoft's

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Speaker 10: Azure service, as well as metas open source models to

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Speaker 10: build upon to build Deepseek, And that's what's being investigated.

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Speaker 3: Right now, Alex Is there anything that Microsoft and other

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Speaker 3: open and open ai and other providers can do to

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Speaker 3: perhaps prevent this from happening again? If not deep Seek,

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Speaker 3: then perhaps another competitor from China.

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Speaker 10: Well, this is the challenge that they're going to have

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Speaker 10: that Microsoft's business model is that you can go to

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Speaker 10: Microsoft Azure and you can throw down a credit card,

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Speaker 10: you can open up an account, and you can ask

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Speaker 10: them to create a private copy of open AI's models

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Speaker 10: for you that you can use for your own purposes.

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Speaker 10: This is how Microsoft plans on monetizing their multi billion

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Speaker 10: dollar investment in open Ai. That is a great thing

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Speaker 10: for them, that's a great thing in theory for both

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Speaker 10: open Ai and the customers that you can have a

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Speaker 10: version of open Ai that in theory does not expose

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Speaker 10: their model weights to the customer and does not expose

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Speaker 10: the customer's private enterprise data to open AI.

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Speaker 9: But what has happened is that people have figured.

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Speaker 10: Out ways that you can ask a model many many

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Speaker 10: millions or billions of questions to suck all of the

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Speaker 10: data out of it. So imagine you have an ancient

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Speaker 10: wise professor, and you're able to ask that wise professor many, many,

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Speaker 10: many questions and then effectively become a.

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Speaker 9: Copy of that professor.

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Speaker 10: That's exactly what can happen here, except at machine speed.

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Speaker 10: You can do that over days, weeks, or months, and

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Speaker 10: that is the business model that Microsoft is operating here.

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Speaker 10: So detecting that kind of behavior might be theoretically possible,

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Speaker 10: but that's also exactly what they're selling. And so I think, yes,

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Speaker 10: they're going to look into what Deepseat did here, but

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Speaker 10: it will only be a cat and mouse game to

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Speaker 10: try to determine whether somebody is actually utilizing the models

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Speaker 10: in the way Microsoft wants them to and wants to

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Speaker 10: get paid for, and whether or not they're trying to

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Speaker 10: actually copy those models.

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Speaker 4: Is we want to ask you a little bit more

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Speaker 4: about the detail of concerns anxieties privacy. Teresa Peyton joined US.

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Speaker 4: She's former CEO for the White House. Here's what she

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Speaker 4: had to say about worries on using deep Seat.

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Speaker 11: This is an untested app. I would caution people not

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Speaker 11: to put too much proprietary company information into it, and

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Speaker 11: until there's been an opportunity to actually do something called

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Speaker 11: ethical hacking or red teaming pen testing of the actual

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Speaker 11: app and learning more about how is your data treated,

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Speaker 11: where is it stored, how do the algorithms work. It

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Speaker 11: is open source, but things do still need to be

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Speaker 11: put through their paces.

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Speaker 4: Of course, deep Seat was the number one app downloaded

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Speaker 4: on Apple. We've also now got Ali Baba announcing its

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Speaker 4: latest powerful AI model. Should similar reticence be used by

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Speaker 4: US companies?

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Speaker 2: By US people? Adds?

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Speaker 10: Okay, So this is where it gets complicated and we

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Speaker 10: got to be really careful here to separate out two

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Speaker 10: different things. There is the deep Seak app that people

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Speaker 10: are downloading on their phones. That app, that data goes

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Speaker 10: straight to China. Right, So if you're downloading deep Seek

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Speaker 10: on your phone, or if you're going to deep Seak's

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Speaker 10: website and you're typing in query that app, that data

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Speaker 10: goes straight to China. That's available to that Chinese company,

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Speaker 10: that is probably available to the Chinese government without any problem.

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Speaker 10: So yes, absolutely, companies should not be allowing their employees

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Speaker 10: to download the deep Seap app onto their phones. If

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Speaker 10: you're a company and you download the open source model weights,

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Speaker 10: that data does not go back to China. Now there

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Speaker 10: are some potential risks right now.

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Speaker 9: Those risks are pretty much theoretical. The deep seek model

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Speaker 9: weights do have an ideological.

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Speaker 10: Twist towards the CCP, so if you asked you about

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Speaker 10: Tineman square, it won't answer. It will not create, for example,

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Speaker 10: a Winnie the Pooh story about Shishan Pin.

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Speaker 9: So it corresponds to the.

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Speaker 10: Rules the Chinese government has created about the ideological consistency

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Speaker 10: of AI, but that is not a security risk. That

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Speaker 10: being said, there are some interesting theoretical ideas people have

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Speaker 10: come up with about backdooring AI when it's used for

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Speaker 10: security sensitive uses, but right now that is not as

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Speaker 10: big of a deal. I think a more interesting question

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Speaker 10: for enterprises that are looking to use the deep Seak

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Speaker 10: model WAKES is the legal issues. If it turns out

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Speaker 10: that deep seek was trained off of metas and open

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Speaker 10: AIS models, what does that mean for the legality of

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Speaker 10: using deep seeks models. Deep Seak has open source theirs,

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Speaker 10: but they do not have the ability to get rid

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Speaker 10: of any legal issues that are caused by open AI.

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Speaker 10: Of course, open ai is being sued for their use

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Speaker 10: of training data that's open that. This is one of

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Speaker 10: the issues with AI. The intellectual property issues have not

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Speaker 10: been solved. We're dealing with eighteen, nineteenth and early twentieth

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Speaker 10: century copyright ideas and we're trying to apply it to

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Speaker 10: these twenty first century problems. And it's a real legal

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Speaker 10: mess that the legal system is years behind what the

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Speaker 10: cutting edges in technology.

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Speaker 3: Alex Stamos, Sentinel One Chief Information Security Officer, Thank you.

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Speaker 3: Coming up, we'll cover deep Seek's impact on the chip

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Speaker 3: world with Andrew Feldman from Sarah Bras.

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Speaker 5: This is Bloomberg.

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Speaker 3: Not all hardware providers are worried about deep seek advantas.

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Speaker 3: The partner of Nvidia that sells chip testing equipment just

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Speaker 3: lifted its full year forecast almost forty percent in anticipation

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Speaker 3: of elevated spending around AI, and it downplayed the impact

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Speaker 3: of deep Seek's big debut. Now let's bring in someone

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Speaker 3: else in the field. Andrew Feldman, CEO Sarah Brus, a

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Speaker 3: company building computer systems for complex AI deep learning applications. Andrew,

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Speaker 3: your company is trying to go toe to toe with

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Speaker 3: a big competitor and that is Nvidia. What do you

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Speaker 3: draw in terms of an underdog story from what we

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Speaker 3: saw the other day with deep Seek?

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Speaker 12: Okay, I think this is an enormously exciting moment for

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Speaker 12: the community. I think it sends multiple powerful messages. Clearly,

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Speaker 12: they used less compute, they used fewer people and produced

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Speaker 12: something quite impressive. Now, I think that's a reminder that

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Speaker 12: those of us who are underdogs and are competing against

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Speaker 12: the eight hundred pound gorillas in the industry, small teams

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Speaker 12: of hardworking people with big ideas can produce industry changing results.

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Speaker 12: And that's what we do at Cerebras.

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Speaker 4: Yeah, Andrew, they used you, they used Cerebras inference offering.

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Speaker 2: What did you see?

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Speaker 4: What have you taken on in terms of the amount

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Speaker 4: of share necessity they need in this moment?

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Speaker 12: Sure, So we are now in beta with our deep

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Speaker 12: Seak offering. And as your last guest said, there are

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Speaker 12: two ways to use deep Seek. You can use it

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Speaker 12: through their app, and I think he's absolutely correct that

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Speaker 12: that that data you can assume goes right to China.

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Speaker 12: Or you can use it through a company like us

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Speaker 12: or Perplexity or collection of others that are offering the model,

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Speaker 12: and we of course have all sorts of protections for

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Speaker 12: your data such that you can be assured it will

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Speaker 12: go nowhere. There is tremendous demand for this type of model.

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Speaker 12: One of the things that separated this model from previous

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Speaker 12: models was that its ability to reason and to do logic,

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Speaker 12: and those type of models in particular outperform the other

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Speaker 12: forms of models, and they do that by using more

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Speaker 12: compute during inference. And this is something that the whole

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Speaker 12: industry has been grappling with and we are today the

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Speaker 12: fastest of this and what that means for you, the

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Speaker 12: user is a better user experience, quicker answers, less waiting,

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Speaker 12: and that's what's really moving the customers right now.

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Speaker 3: Andrew Cerebras had been planning an IPO, do you have

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Speaker 3: an update on that? And we also understand and that

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Speaker 3: an interagency panel in Washington known as SIPIUS has been

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Speaker 3: reviewing all of this.

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Speaker 5: Do you have an update there? I don't, But I.

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Speaker 12: Think the deep Seek model was put out right around

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Speaker 12: Trump's inauguration.

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Speaker 6: I don't think that was an accident.

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Speaker 12: I think this was an effort to communicate at the

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Speaker 12: geopolitical level to the US that the previous administration's regulations

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Speaker 12: hadn't worked, that the Chinese engineer was capable of doing

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Speaker 12: extraordinary things even in the face of the regulations imposed

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Speaker 12: by the previous administration's commerce team.

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Speaker 4: What's so interesting about this You talk about the geopolitics

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Speaker 4: and perhaps all that sort of timing use with Huawei

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Speaker 4: and its innovations, But briefly, many and perhaps worried Siphius

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Speaker 4: maybe have anxiety around your relationship with G forty two

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Speaker 4: and it's ultimate relationship with Chines, your overseas locations. How

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Speaker 4: do you tackle that in this environment?

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Speaker 12: Look, I think we have a strategic partnership with G

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Speaker 12: forty two. They are the national champion AI company for

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Speaker 12: United Arab Emirates, and they are one of the US's

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Speaker 12: staunchest allies in the Middle East and have a long

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Speaker 12: track record of supporting US interests and being good allies.

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Speaker 12: I think one of the things that Deep Seek has

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Speaker 12: taught us is that.

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Speaker 9: We will need the community and we will need our allies.

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Speaker 12: That we thought perhaps that the US could run this alone,

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Speaker 12: that we had the computer companies like Cerebras, like Nvidia

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Speaker 12: and a m D and we had the open eyes

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Speaker 12: of the world. But I think what we're learning here

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Speaker 12: is that we will need the entire US ecosystem in

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Speaker 12: this AI battle.

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Speaker 2: Andrew Feldman, thanks so much for joining us.

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Speaker 4: CEO Cerebras.

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Speaker 2: Come back when you do. You have a bit more

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Speaker 2: news on the IPO potentially coming up.

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Speaker 4: Activist investor Kristin Hull joins us to discuss what she'll

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Speaker 4: be looking for when Tesla releases its results later today.

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Speaker 4: I remember an activist investor what she makes of Elon

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Speaker 4: Musk's involvement in government, in the German government. This is

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Speaker 4: bloue Meg Technology. Welcome back to Blue Meg Technology. I'm

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Speaker 4: Caroline Hide in New York.

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Speaker 5: And I'm Mike Shepard in San Francisco.

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Speaker 4: Check on these markets, Mike, because we've got some anxiety

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Speaker 4: ahead of the FED, of course, and indeed ahead of earnings.

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Speaker 4: We've got Microsoft Meta Tesla after well, nasdak off by

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Speaker 4: four ten percent. The bitcoin though, is getting a bit

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Speaker 4: of a risk on trade where at one and a

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Speaker 4: half percent, maybe because of what Trump Media has just

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Speaker 4: announced a pairing into financial services. They're launching a fintech

442
00:22:56,600 --> 00:23:00,480
Speaker 4: brand name Truthfi. In collaborations with Charles Schwab up eight

443
00:23:00,520 --> 00:23:04,159
Speaker 4: and a half percent Sally Bakewell here to discuss what

444
00:23:04,160 --> 00:23:07,119
Speaker 4: are we expecting this sort of a move from an

445
00:23:07,240 --> 00:23:08,439
Speaker 4: entity related to the president.

446
00:23:09,000 --> 00:23:10,399
Speaker 2: I think we could have expected it.

447
00:23:10,480 --> 00:23:13,840
Speaker 13: I mean, Trump has just launched his trump coin, he

448
00:23:13,880 --> 00:23:18,040
Speaker 13: has already declared himself a huge supporter of cryptocurrencies.

449
00:23:18,080 --> 00:23:19,280
Speaker 2: He's the crypto president.

450
00:23:19,560 --> 00:23:21,439
Speaker 13: So I don't think it's a huge surprise that Trump

451
00:23:21,440 --> 00:23:26,840
Speaker 13: Media is delving into the financial services world with this investment.

452
00:23:27,080 --> 00:23:27,240
Speaker 9: Now.

453
00:23:27,240 --> 00:23:31,080
Speaker 13: It's notable, though, that Donald Trump he actually transferred his

454
00:23:31,200 --> 00:23:34,359
Speaker 13: shares in Trump Media last month to a trust which

455
00:23:34,440 --> 00:23:37,240
Speaker 13: is controlled by his eldest son, so he no longer

456
00:23:37,280 --> 00:23:39,800
Speaker 13: directly owns any of Trump Media, but he is the

457
00:23:39,800 --> 00:23:43,199
Speaker 13: sole beneficiary of that trust. So I think this is

458
00:23:43,280 --> 00:23:46,679
Speaker 13: just an example of how the Trump Empire is deepening

459
00:23:46,800 --> 00:23:50,640
Speaker 13: its push into crypto and fintech. And it's interestingly timed

460
00:23:50,720 --> 00:23:54,600
Speaker 13: because just last week Trump made comments about, you know,

461
00:23:54,680 --> 00:23:57,800
Speaker 13: traditional banks and how he said that they were effectively

462
00:23:57,880 --> 00:24:01,640
Speaker 13: debanking the Conservatives. He's sort of made a barber Bank

463
00:24:01,680 --> 00:24:04,520
Speaker 13: of America CEO Brian moynihan, as well as JP Morgan

464
00:24:04,760 --> 00:24:07,399
Speaker 13: chief Jamie Diamond, so he's a big fan of the

465
00:24:07,480 --> 00:24:09,040
Speaker 13: crypto the fintech world.

466
00:24:09,080 --> 00:24:09,720
Speaker 2: I think it is fair to.

467
00:24:09,720 --> 00:24:15,840
Speaker 3: Say Sally in effector is the Trump Media group trying

468
00:24:15,880 --> 00:24:19,040
Speaker 3: to create something that Elon Musk has dreamed about for

469
00:24:19,080 --> 00:24:22,919
Speaker 3: all these years, that is a one stop social platform

470
00:24:23,000 --> 00:24:26,040
Speaker 3: with everything, messaging, finance, you name it.

471
00:24:26,600 --> 00:24:27,760
Speaker 2: Well, so far, what do we know?

472
00:24:27,920 --> 00:24:30,080
Speaker 13: We know that Trump Media is investing two hundred and

473
00:24:30,160 --> 00:24:33,280
Speaker 13: fifty million in this effort, and that money actually is

474
00:24:33,280 --> 00:24:35,560
Speaker 13: going to be custodied by Charles Schwab, which is also

475
00:24:35,600 --> 00:24:38,640
Speaker 13: going to advise it on its investments and its strategy.

476
00:24:38,640 --> 00:24:43,159
Speaker 13: It's going to offer separately managed accounts ETFs, and other bitcoin,

477
00:24:43,240 --> 00:24:47,240
Speaker 13: crypto and bitcoin related products. Now, getting into the financial

478
00:24:47,320 --> 00:24:50,320
Speaker 13: services space is something that a lot of companies have done.

479
00:24:50,480 --> 00:24:54,000
Speaker 13: Just yesterday, social media platform x announced that it was

480
00:24:54,080 --> 00:24:57,280
Speaker 13: partnering with Visa on its digital wallet in order to

481
00:24:57,320 --> 00:25:00,840
Speaker 13: be this everything app that Musk has lo talked about.

482
00:25:00,840 --> 00:25:01,560
Speaker 2: And we've seen the.

483
00:25:01,600 --> 00:25:05,960
Speaker 13: Likes of Amazon creeps only into financial services, as has

484
00:25:06,040 --> 00:25:09,960
Speaker 13: Apple with the wallet. So it's a difficult world to

485
00:25:10,080 --> 00:25:12,200
Speaker 13: enter in many ways. There are a lot of incumbents

486
00:25:12,359 --> 00:25:17,159
Speaker 13: such as zell and Venmo, which holds substantial portions of

487
00:25:17,200 --> 00:25:19,640
Speaker 13: the market. But equally, a lot of these companies also

488
00:25:19,680 --> 00:25:22,200
Speaker 13: want to diversify their revenue, and this is one place

489
00:25:22,240 --> 00:25:22,879
Speaker 13: that they can do that.

490
00:25:23,960 --> 00:25:28,160
Speaker 3: Bloomberg Sally big, Well, thank you so much. Tesla releases

491
00:25:28,200 --> 00:25:31,360
Speaker 3: its fourth quarter earnings later today, and investors are going

492
00:25:31,400 --> 00:25:34,600
Speaker 3: to be closely watching for information on new products and

493
00:25:34,720 --> 00:25:37,640
Speaker 3: sales volume, and they also want to know how CEO

494
00:25:37,760 --> 00:25:41,639
Speaker 3: Elon Musk's new role in the Trump administration is impacting

495
00:25:41,680 --> 00:25:43,000
Speaker 3: the electric vehicle maker.

496
00:25:43,320 --> 00:25:44,600
Speaker 5: Let's bring in Kristen Hall.

497
00:25:44,760 --> 00:25:47,879
Speaker 3: She's the founder and chief investment officer at NIA Impact

498
00:25:47,960 --> 00:25:52,040
Speaker 3: Capital and somebody who follows Tesla very closely, Nia, this

499
00:25:52,119 --> 00:25:53,879
Speaker 3: is a real moment for you.

500
00:25:53,920 --> 00:25:56,120
Speaker 5: If somebody watches this company very closely.

501
00:25:56,880 --> 00:26:00,800
Speaker 3: Tough sales numbers earlier this month from the company, we

502
00:26:00,840 --> 00:26:04,040
Speaker 3: see the new president pulling away the EV subsidies and

503
00:26:04,119 --> 00:26:08,600
Speaker 3: the CEO of Tesla himself quite distracted by politics. These

504
00:26:08,640 --> 00:26:12,320
Speaker 3: are choppy waters for any company. How is Tesla going

505
00:26:12,359 --> 00:26:13,320
Speaker 3: to navigate them?

506
00:26:13,760 --> 00:26:15,280
Speaker 2: Hey, Mike, thanks for having me today.

507
00:26:15,560 --> 00:26:17,879
Speaker 14: This is a tricky company and all investors are going

508
00:26:17,920 --> 00:26:20,600
Speaker 14: to be watching for these earnings today. We want to

509
00:26:20,680 --> 00:26:23,359
Speaker 14: see that there's a commitment to growth and that there's

510
00:26:24,160 --> 00:26:27,000
Speaker 14: an ability for execution, and of course we have questions

511
00:26:27,520 --> 00:26:30,439
Speaker 14: can the CEO execute on these and do we have

512
00:26:30,480 --> 00:26:32,320
Speaker 14: a board that's going to support all of the growth

513
00:26:32,320 --> 00:26:33,800
Speaker 14: that we need to see from this company.

514
00:26:34,320 --> 00:26:35,320
Speaker 5: What are you looking.

515
00:26:35,119 --> 00:26:39,040
Speaker 3: For in particular when it comes to the business including

516
00:26:39,119 --> 00:26:42,960
Speaker 3: self driving and perhaps some of the other businesses that

517
00:26:43,000 --> 00:26:46,760
Speaker 3: have emerged for Tesla, including AI and robotics.

518
00:26:47,240 --> 00:26:50,080
Speaker 14: Yeah, so that's a good question, right because as investors,

519
00:26:50,080 --> 00:26:51,920
Speaker 14: we want to see growth, and we want to see

520
00:26:51,960 --> 00:26:55,280
Speaker 14: a plan, and we want to see guidance. And what

521
00:26:55,359 --> 00:26:57,760
Speaker 14: we know from these earnings reports from the past is

522
00:26:57,920 --> 00:27:01,680
Speaker 14: consistently there will be surprises. We can expect that we

523
00:27:01,720 --> 00:27:04,400
Speaker 14: want to see that there are sales growth in their

524
00:27:04,440 --> 00:27:08,520
Speaker 14: main revenue source, which is automobiles, right, and yet Europe

525
00:27:09,160 --> 00:27:13,960
Speaker 14: dropping in popularity. Actually worldwide, Tesla has been dropping popularity,

526
00:27:14,000 --> 00:27:16,639
Speaker 14: and so we have competition coming up in the market,

527
00:27:16,680 --> 00:27:20,480
Speaker 14: both with regular automobile makers as well as some of

528
00:27:20,480 --> 00:27:22,320
Speaker 14: the Chinese that are coming in and so it's a

529
00:27:22,400 --> 00:27:26,159
Speaker 14: complicated terrain for Tesla right now to navigate, and so

530
00:27:26,200 --> 00:27:27,960
Speaker 14: we're going to want to see that there's a CEO

531
00:27:28,040 --> 00:27:29,359
Speaker 14: in control with a plan.

532
00:27:30,280 --> 00:27:33,040
Speaker 4: You are so important in terms of a voice because

533
00:27:33,080 --> 00:27:38,080
Speaker 4: you're an activist investor, and ultimately you're questioning often the

534
00:27:38,200 --> 00:27:41,000
Speaker 4: role of elo Musk, the way of policies he.

535
00:27:41,040 --> 00:27:42,840
Speaker 2: Invokes, the way he acts.

536
00:27:43,119 --> 00:27:45,560
Speaker 4: But notably at the moment, Tesla doesn't seem to be

537
00:27:45,720 --> 00:27:48,480
Speaker 4: particularly related to fundamentals. We point out that their shares

538
00:27:48,480 --> 00:27:50,640
Speaker 4: are nearly doubled since the last time we got earnings,

539
00:27:51,000 --> 00:27:52,879
Speaker 4: and the numbers haven't been that great since then if

540
00:27:52,880 --> 00:27:55,280
Speaker 4: you think about the deliveries numbers instead, this is a

541
00:27:55,320 --> 00:28:00,640
Speaker 4: proxy on Elon's closeness to politics. How do you distinguish

542
00:28:00,680 --> 00:28:02,120
Speaker 4: that for yourself as an investor?

543
00:28:02,560 --> 00:28:05,640
Speaker 14: So, Caroline, thanks for the question. This is a complicated company,

544
00:28:05,840 --> 00:28:08,919
Speaker 14: particularly when the CEO is as involved with the federal

545
00:28:08,960 --> 00:28:13,080
Speaker 14: government as is. Oftentimes you would see if there's a

546
00:28:13,160 --> 00:28:15,679
Speaker 14: role granted from the federal government that you would drop

547
00:28:15,760 --> 00:28:18,680
Speaker 14: your current day job, and yet we're not seeing that happening.

548
00:28:18,840 --> 00:28:19,919
Speaker 2: So we do.

549
00:28:19,840 --> 00:28:22,919
Speaker 14: Believe that every company deserves a full time CEO, and

550
00:28:22,960 --> 00:28:25,560
Speaker 14: so we have lots of questions there. We also have

551
00:28:25,720 --> 00:28:29,480
Speaker 14: questions about human capital management and how is Tesla going

552
00:28:29,520 --> 00:28:34,200
Speaker 14: to be able to attract, retain, promote top talent, because,

553
00:28:34,400 --> 00:28:37,000
Speaker 14: as we know, this is an innovation company, and innovation

554
00:28:37,200 --> 00:28:42,680
Speaker 14: does derive itself from really loyal client base, both on

555
00:28:42,720 --> 00:28:44,760
Speaker 14: the client side and then also on the employee base,

556
00:28:44,960 --> 00:28:47,480
Speaker 14: and so we're looking to see how is the company

557
00:28:47,520 --> 00:28:48,280
Speaker 14: going to manage this.

558
00:28:49,040 --> 00:28:52,680
Speaker 4: For years, though, since you first bought into Tesla, you've

559
00:28:52,680 --> 00:28:55,280
Speaker 4: been trying to communicate with the company and pushing against

560
00:28:55,320 --> 00:28:57,520
Speaker 4: some of the activities that we've seen, whether it be

561
00:28:57,560 --> 00:29:01,120
Speaker 4: consents around on to DEI, whether it be certain perceived

562
00:29:01,160 --> 00:29:03,760
Speaker 4: anti Semitic compents coming from Elo Musk in the past

563
00:29:03,760 --> 00:29:04,800
Speaker 4: that I know you've written about.

564
00:29:04,960 --> 00:29:06,760
Speaker 2: There's also, though, of course, the latest.

565
00:29:06,440 --> 00:29:08,880
Speaker 4: When we come to the concerns around gestures recently made

566
00:29:08,880 --> 00:29:11,520
Speaker 4: around the inauguration of Trump made by Elo Musk and

567
00:29:11,560 --> 00:29:14,840
Speaker 4: indeed his support of IFD, which is deemed a right

568
00:29:14,880 --> 00:29:19,440
Speaker 4: wing group in Germany. Nothing seems the matter when you're

569
00:29:19,480 --> 00:29:21,640
Speaker 4: putting this to ultimately a share price that goes up

570
00:29:21,640 --> 00:29:22,160
Speaker 4: into the right.

571
00:29:23,040 --> 00:29:26,200
Speaker 14: So you bring up some really interesting points. This company

572
00:29:26,280 --> 00:29:29,040
Speaker 14: does seem to stand alone as far as its meanness,

573
00:29:29,080 --> 00:29:32,520
Speaker 14: and that it's continued to grow. Other companies would not

574
00:29:33,120 --> 00:29:35,840
Speaker 14: get the same reactions with that type of CEO and

575
00:29:35,880 --> 00:29:39,000
Speaker 14: those types of behaviors. We as investors are really looking

576
00:29:39,040 --> 00:29:41,920
Speaker 14: for the long term possibilities here, and when you have

577
00:29:42,040 --> 00:29:45,800
Speaker 14: such a controversial CEO, we are seeing, as you point out,

578
00:29:45,840 --> 00:29:50,360
Speaker 14: sales are dropping, popularity is dropping, the brand has been damaged,

579
00:29:50,680 --> 00:29:53,560
Speaker 14: and so how is the board and the rest of

580
00:29:53,600 --> 00:29:55,400
Speaker 14: Tesla going to step in and see how are we

581
00:29:55,440 --> 00:29:58,600
Speaker 14: going to see sales growing when we are having a

582
00:29:58,640 --> 00:30:01,720
Speaker 14: lot of controversial issues. As I pointed out earlier, we're

583
00:30:01,760 --> 00:30:04,720
Speaker 14: also seeing not only two clients at where I live

584
00:30:04,760 --> 00:30:08,080
Speaker 14: in California, many many are switching to Rivian and other

585
00:30:08,160 --> 00:30:11,640
Speaker 14: EV brands specifically based on the brand and some of

586
00:30:11,680 --> 00:30:13,440
Speaker 14: the issues that they see that they don't want to

587
00:30:13,480 --> 00:30:16,760
Speaker 14: be associated with. And we're also seeing that for employees,

588
00:30:17,160 --> 00:30:19,280
Speaker 14: who's going to want to work for Tesla in such

589
00:30:19,280 --> 00:30:22,040
Speaker 14: a volatile environment. These are questions that investors have.

590
00:30:22,360 --> 00:30:26,280
Speaker 3: Kristin, It's been a year since Tesla dropped diversity and

591
00:30:26,320 --> 00:30:29,520
Speaker 3: inclusion language from its ten K, and we've seen since

592
00:30:29,560 --> 00:30:33,040
Speaker 3: then other companies and even the federal government following suit

593
00:30:33,120 --> 00:30:35,600
Speaker 3: in some fashion or another. Do you see this tide

594
00:30:35,760 --> 00:30:38,320
Speaker 3: changing at all? And what sort of pressure will you

595
00:30:38,440 --> 00:30:42,479
Speaker 3: be able to apply to Tesla at upcoming meetings?

596
00:30:43,040 --> 00:30:45,040
Speaker 14: So for all of our companies, we really want to

597
00:30:45,080 --> 00:30:48,240
Speaker 14: see strong human capital management. And so whether you call

598
00:30:48,320 --> 00:30:51,920
Speaker 14: it DEI or whether you call it supporting your employee base,

599
00:30:51,960 --> 00:30:54,920
Speaker 14: we really want to see Tesla and other companies hold

600
00:30:54,960 --> 00:30:57,560
Speaker 14: their employees on the asset side of the balance sheet

601
00:30:57,800 --> 00:31:00,560
Speaker 14: as opposed to on the expense side. We want to

602
00:31:00,600 --> 00:31:03,840
Speaker 14: see that Tesla is showing that they will invest in

603
00:31:03,880 --> 00:31:06,680
Speaker 14: their employee base because we know that again, to execute

604
00:31:06,720 --> 00:31:08,920
Speaker 14: on all of the innovation that they promised, they're going

605
00:31:08,960 --> 00:31:11,880
Speaker 14: to need to have strong, loyal employees and that's going

606
00:31:11,880 --> 00:31:15,400
Speaker 14: to mean strong programs and so again, whether it's called diversity,

607
00:31:15,440 --> 00:31:18,400
Speaker 14: equity inclusion, whether it's merit based hiring, we want to

608
00:31:18,400 --> 00:31:21,160
Speaker 14: see that investment and we need to see the transparency

609
00:31:21,200 --> 00:31:24,479
Speaker 14: around that. So with Tesla, we and NIA have been

610
00:31:24,520 --> 00:31:28,760
Speaker 14: asking them to remove forced arbitration from employee contracts because

611
00:31:28,800 --> 00:31:31,680
Speaker 14: that does conceal a lot of what's going on, both

612
00:31:31,680 --> 00:31:35,000
Speaker 14: for managers and for investors as well as for other employees.

613
00:31:35,760 --> 00:31:39,600
Speaker 4: Kristin how, chief investment Officer for NIA Impact Capital, thanks

614
00:31:39,640 --> 00:31:41,560
Speaker 4: so much for joining us today and do not forget

615
00:31:41,600 --> 00:31:45,560
Speaker 4: to check out the elon Ink Podcasts FINGO card for

616
00:31:45,720 --> 00:31:47,160
Speaker 4: this round of Tesla's earnings.

617
00:31:47,200 --> 00:31:47,840
Speaker 2: You can find it on the.

618
00:31:47,880 --> 00:31:51,440
Speaker 4: Terminal Online Work out what words are used, how many times,

619
00:31:51,720 --> 00:31:54,200
Speaker 4: and if they're in line with that card coming up.

620
00:31:54,400 --> 00:31:56,880
Speaker 4: TikTok still needs a US buyer to avoid a bad

621
00:31:56,920 --> 00:31:57,560
Speaker 4: in the States.

622
00:31:57,760 --> 00:31:59,320
Speaker 2: Seventy five day extension.

623
00:31:58,960 --> 00:32:01,600
Speaker 4: Signed by President Trump run out in April. We'll talk

624
00:32:01,640 --> 00:32:04,480
Speaker 4: to Jesse Tinsley about the old cash bid he's put

625
00:32:04,520 --> 00:32:06,440
Speaker 4: together with none of them, the mister Beast. This is

626
00:32:06,440 --> 00:32:07,320
Speaker 4: bringing back technology.

627
00:32:17,360 --> 00:32:20,760
Speaker 3: Could a widely popular influencer become an owner in a

628
00:32:20,840 --> 00:32:23,280
Speaker 3: hugely popular social media platform.

629
00:32:23,520 --> 00:32:25,400
Speaker 5: Mister Beast is reported.

630
00:32:24,960 --> 00:32:28,720
Speaker 3: To be speaking with multiple groups of investors about buying TikTok.

631
00:32:29,040 --> 00:32:30,400
Speaker 5: One of those groups is led.

632
00:32:30,280 --> 00:32:34,120
Speaker 3: By Jesse Tinsley, the CEO of Employer dot Com. Jesse

633
00:32:34,240 --> 00:32:37,440
Speaker 3: Tinsley joins us now. Jesse, thank you for being here.

634
00:32:37,680 --> 00:32:41,560
Speaker 3: Let's get right to it. How involved is mister Beast

635
00:32:41,800 --> 00:32:45,400
Speaker 3: with your group's bid? Has he fully committed to joining

636
00:32:45,400 --> 00:32:46,040
Speaker 3: your team here?

637
00:32:46,560 --> 00:32:48,680
Speaker 15: I think mister Beast, as we said last week, I

638
00:32:48,680 --> 00:32:51,080
Speaker 15: think we hope that he joins as many bus as

639
00:32:51,120 --> 00:32:51,600
Speaker 15: as possible.

640
00:32:51,640 --> 00:32:53,120
Speaker 6: He's positive influence.

641
00:32:52,760 --> 00:32:55,320
Speaker 15: For young people and people ever read globally, and so

642
00:32:55,920 --> 00:32:59,640
Speaker 15: we're excited to have him in his group backing our

643
00:32:59,680 --> 00:33:01,040
Speaker 15: bid among others as well.

644
00:33:02,040 --> 00:33:04,200
Speaker 4: So he's not formally signed on to your bid. He's

645
00:33:04,240 --> 00:33:06,640
Speaker 4: just seeing whoever wins contacts.

646
00:33:06,640 --> 00:33:08,320
Speaker 15: So I think there's some some articles that came out

647
00:33:08,400 --> 00:33:12,560
Speaker 15: last week and mister Beast and his group are definitely

648
00:33:13,200 --> 00:33:15,920
Speaker 15: signed on with our group and it's but it's non exclusive,

649
00:33:16,000 --> 00:33:17,960
Speaker 15: so we hope he can work with as many groups

650
00:33:17,960 --> 00:33:18,480
Speaker 15: as possible.

651
00:33:19,240 --> 00:33:20,440
Speaker 2: And what about your bid?

652
00:33:20,920 --> 00:33:25,160
Speaker 4: Who else is involved other than yourself and potentially mister Beaste.

653
00:33:25,360 --> 00:33:26,760
Speaker 6: Yeah, yeah, it's a great question.

654
00:33:26,840 --> 00:33:29,760
Speaker 15: I think we were We were not obviously a very

655
00:33:30,080 --> 00:33:31,520
Speaker 15: large bid by by any means.

656
00:33:31,600 --> 00:33:31,719
Speaker 9: Right.

657
00:33:31,760 --> 00:33:35,480
Speaker 15: We're a bunch of technologists and founders and there's folks

658
00:33:35,560 --> 00:33:39,360
Speaker 15: like David Bazouki from the CEO and co founder of

659
00:33:39,560 --> 00:33:42,400
Speaker 15: rope Blocks, as well as Nathan Coley, co founder and

660
00:33:42,480 --> 00:33:45,800
Speaker 15: CEO of Anchorage, among a bunch of other technologists and

661
00:33:45,800 --> 00:33:49,400
Speaker 15: folks that I think can stabilize, you know, TikTok can

662
00:33:49,400 --> 00:33:51,760
Speaker 15: put in a really good place for users and data

663
00:33:51,800 --> 00:33:56,160
Speaker 15: integrity across you know, across the US based population.

664
00:33:56,840 --> 00:33:58,200
Speaker 6: We're We're excited with the group we have.

665
00:33:58,360 --> 00:34:01,000
Speaker 15: We have as almost a great effort as opposed to

666
00:34:01,040 --> 00:34:02,160
Speaker 15: some of these larger bids.

667
00:34:01,920 --> 00:34:04,440
Speaker 6: And I think we have folks that can come in

668
00:34:04,480 --> 00:34:06,880
Speaker 6: and make a huge impact. We're really excited with the

669
00:34:06,880 --> 00:34:07,320
Speaker 6: group that we.

670
00:34:07,280 --> 00:34:10,760
Speaker 3: A Jesse, what have you heard back from BYT Dance

671
00:34:10,840 --> 00:34:13,840
Speaker 3: and who at the company are you dealing with specifically.

672
00:34:14,280 --> 00:34:16,200
Speaker 6: Yeah, that's a good question. We have heard back from

673
00:34:16,200 --> 00:34:17,000
Speaker 6: BI Dance directly.

674
00:34:17,560 --> 00:34:20,160
Speaker 15: It's been a bit of radio silence on their side,

675
00:34:20,200 --> 00:34:22,200
Speaker 15: but we're looking forward to chatting with them the next

676
00:34:22,200 --> 00:34:24,360
Speaker 15: couple of weeks. It sounds like there's some movement with

677
00:34:24,400 --> 00:34:28,080
Speaker 15: different conversations we've been having across a bunch of different parties,

678
00:34:28,160 --> 00:34:32,080
Speaker 15: and I think it's right now. We're scared with the

679
00:34:32,120 --> 00:34:36,200
Speaker 15: way things are trending. And yeah, so no direct contact

680
00:34:36,200 --> 00:34:36,680
Speaker 15: with by Dance.

681
00:34:36,719 --> 00:34:37,920
Speaker 6: Thom's farm.

682
00:34:38,160 --> 00:34:43,120
Speaker 4: Really fascinating about who's alongside you Roadblocks. I totally get

683
00:34:43,320 --> 00:34:45,480
Speaker 4: the idea that you want to therefore be aligned with

684
00:34:45,520 --> 00:34:48,600
Speaker 4: social media and with discussion and groups and interaction of

685
00:34:48,640 --> 00:34:51,400
Speaker 4: young people. But Jesse, you have made your name in

686
00:34:51,760 --> 00:34:55,040
Speaker 4: human capital. Why are you interested in this asset?

687
00:34:55,080 --> 00:34:56,319
Speaker 2: What change do you want to make?

688
00:34:56,680 --> 00:35:00,920
Speaker 6: Yeah, the fantastic question. I think. Obviously data's background.

689
00:35:01,680 --> 00:35:05,080
Speaker 15: Roadblocks directly seeks the lines a lot with the same

690
00:35:05,160 --> 00:35:06,400
Speaker 15: values that I shared. It's one of the reasons that

691
00:35:06,400 --> 00:35:10,800
Speaker 15: we added him directly is I have two young daughters

692
00:35:11,320 --> 00:35:14,160
Speaker 15: who will soon be on on social media and hopefully

693
00:35:14,440 --> 00:35:17,880
Speaker 15: my goal and whoever whoever wins roadblocks, whether it's myself

694
00:35:17,960 --> 00:35:20,359
Speaker 15: or another group, I hope that you know that it's

695
00:35:20,480 --> 00:35:22,480
Speaker 15: safe enough for the where I feel comfortable with my

696
00:35:22,560 --> 00:35:24,160
Speaker 15: young daughters going on.

697
00:35:24,040 --> 00:35:25,839
Speaker 6: TikTok for the next six ft full months.

698
00:35:25,840 --> 00:35:28,959
Speaker 15: And I think right now, the way the algorithm is set,

699
00:35:29,040 --> 00:35:31,439
Speaker 15: where the data is, how the data is being used,

700
00:35:32,520 --> 00:35:35,000
Speaker 15: I would not feel that comfortable doing that thus far.

701
00:35:35,120 --> 00:35:36,600
Speaker 15: So I think that that's kind of my goal and

702
00:35:37,960 --> 00:35:40,880
Speaker 15: the values that I see an ndidate for for US.

703
00:35:40,920 --> 00:35:42,720
Speaker 6: Stone after this stood correctly.

704
00:35:42,719 --> 00:35:47,960
Speaker 3: Jesse, President Donald Trump has made selling TikTok to US

705
00:35:48,040 --> 00:35:50,480
Speaker 3: buyers or reaching a deal a priority.

706
00:35:50,520 --> 00:35:52,600
Speaker 5: What kind of contact have you had with the White

707
00:35:52,640 --> 00:35:53,359
Speaker 5: House and what.

708
00:35:53,400 --> 00:35:56,719
Speaker 3: Sort of support are you getting from Trump administration officials

709
00:35:56,719 --> 00:35:57,200
Speaker 3: on your bid.

710
00:35:57,640 --> 00:36:00,719
Speaker 15: Yeah, we've done ongoing dialogue with the Trump illustration, and

711
00:36:01,760 --> 00:36:04,200
Speaker 15: we feel very comfortable with our bid in terms of

712
00:36:04,239 --> 00:36:06,399
Speaker 15: how we've actually set it up. We have a bunch

713
00:36:06,400 --> 00:36:09,040
Speaker 15: of we've already preset a lot of the team in

714
00:36:09,200 --> 00:36:12,520
Speaker 15: terms of board of directors and board sub committees with

715
00:36:12,560 --> 00:36:15,319
Speaker 15: around finance, technology and everything else.

716
00:36:15,360 --> 00:36:16,480
Speaker 6: So we feel really really good.

717
00:36:16,520 --> 00:36:20,560
Speaker 15: We have an all us back vaccine with all of

718
00:36:20,560 --> 00:36:22,879
Speaker 15: the data and servers and technology moving here.

719
00:36:22,920 --> 00:36:25,600
Speaker 6: So definitely gonna be a challenge to move TikTok.

720
00:36:25,280 --> 00:36:30,360
Speaker 15: But over from byte Dance and there's so many servers

721
00:36:30,480 --> 00:36:31,440
Speaker 15: and move it here.

722
00:36:31,480 --> 00:36:33,800
Speaker 6: But we feel really comfortable with our bid correctly.

723
00:36:34,360 --> 00:36:39,080
Speaker 4: Ultimately, it sounds like you're making one just for the

724
00:36:39,120 --> 00:36:41,120
Speaker 4: good of humanity, for the good of your kids.

725
00:36:41,320 --> 00:36:41,799
Speaker 2: I mean you.

726
00:36:41,800 --> 00:36:44,839
Speaker 4: Said, I think accidentally said you were making whoever wins

727
00:36:44,840 --> 00:36:46,839
Speaker 4: out on roadblocks, and you might say whoever wins out

728
00:36:47,160 --> 00:36:47,920
Speaker 4: on TikTok.

729
00:36:48,360 --> 00:36:51,360
Speaker 2: But help us take this really seriously.

730
00:36:51,480 --> 00:36:54,040
Speaker 4: You've already named some really significant people who are in

731
00:36:54,080 --> 00:36:58,120
Speaker 4: this with yourself are a significant entrepreneur and founder. But

732
00:36:58,760 --> 00:37:01,520
Speaker 4: help us understand how serious the nature it is of

733
00:37:01,560 --> 00:37:03,320
Speaker 4: this bid and how much money you've got behind it.

734
00:37:03,440 --> 00:37:08,960
Speaker 15: Jesse, Yeah, so definitely definitely a very large bit, I

735
00:37:09,000 --> 00:37:12,279
Speaker 15: think Bell I'll measures we basically have I think the

736
00:37:12,520 --> 00:37:15,400
Speaker 15: other public number fit that's been floated as a twenty

737
00:37:15,400 --> 00:37:20,000
Speaker 15: big billion by another group essentially ours and significantly higher

738
00:37:20,600 --> 00:37:23,160
Speaker 15: that offer ends today got.

739
00:37:23,000 --> 00:37:25,360
Speaker 4: The money behind at Jesse Tinsley, He tells our CEO

740
00:37:25,360 --> 00:37:34,600
Speaker 4: of employer dot com thanks so much for joining us.

741
00:37:36,400 --> 00:37:39,880
Speaker 3: Microsoft and Meta reporting after market closed today. All this

742
00:37:39,960 --> 00:37:44,680
Speaker 3: admits concerns around artificial intelligence spending. Let's bring in Bloomberg's

743
00:37:44,719 --> 00:37:45,880
Speaker 3: Ryan Blestelica.

744
00:37:46,120 --> 00:37:49,720
Speaker 5: Ryan. Meta and Microsoft are two very different stories.

745
00:37:49,760 --> 00:37:52,400
Speaker 3: When it comes to capex, Meta seems to be getting

746
00:37:52,400 --> 00:37:53,640
Speaker 3: a little bit more of a pass.

747
00:37:53,719 --> 00:37:56,160
Speaker 16: Why is that, Hey, thanks for having me on. Yeah,

748
00:37:56,160 --> 00:37:58,319
Speaker 16: it's a great question. So last week they came out

749
00:37:58,360 --> 00:38:01,560
Speaker 16: gave a new cappex target that was significantly above what

750
00:38:01,600 --> 00:38:02,640
Speaker 16: people were expecting.

751
00:38:03,000 --> 00:38:04,280
Speaker 9: And while a lot.

752
00:38:04,160 --> 00:38:07,000
Speaker 16: Of AI spending has come under scrutiny lately, the stock

753
00:38:07,120 --> 00:38:10,960
Speaker 16: actually rallied. It seems like the overall takeaway was people

754
00:38:11,040 --> 00:38:13,799
Speaker 16: view them as investing from a place's strength. And then

755
00:38:13,840 --> 00:38:17,640
Speaker 16: earlier this week, amid all the sell off and volatility

756
00:38:17,680 --> 00:38:20,680
Speaker 16: related to Deep Seek out of China, Meta also rose again.

757
00:38:21,000 --> 00:38:22,879
Speaker 16: That was sort of seen as a validation of its

758
00:38:22,920 --> 00:38:25,840
Speaker 16: own AI model Lama, which is open source, getting a

759
00:38:25,840 --> 00:38:28,000
Speaker 16: little bit of a bid from deep Seek, which is

760
00:38:28,000 --> 00:38:30,239
Speaker 16: another open source model, So it's sort of a validation

761
00:38:30,320 --> 00:38:31,439
Speaker 16: of their strategy there.

762
00:38:32,080 --> 00:38:35,399
Speaker 4: Meanwhile, Microsoft expecting eleven percent increase in revenue, but they've

763
00:38:35,400 --> 00:38:37,600
Speaker 4: got to vindicate their spending and indeed where the open

764
00:38:37,640 --> 00:38:41,320
Speaker 4: AI is is valuable without Since the deep Seek news.

765
00:38:42,040 --> 00:38:43,640
Speaker 9: Yeah, absolutely so that's this company.

766
00:38:43,719 --> 00:38:45,960
Speaker 16: They've disappointed the past couple of quarters, just based on

767
00:38:46,000 --> 00:38:49,680
Speaker 16: their share price reaction. Some concerns about the strength of

768
00:38:49,680 --> 00:38:52,040
Speaker 16: their cloud business. Is it growing fast enough for people

769
00:38:52,040 --> 00:38:55,760
Speaker 16: to justify paying the high multiple that Microsoft has, especially

770
00:38:55,800 --> 00:38:56,680
Speaker 16: relative to Meta.

771
00:38:56,760 --> 00:38:58,399
Speaker 9: That's going to be a real focus here.

772
00:38:58,440 --> 00:39:00,239
Speaker 16: And obviously that was the name that a I saw

773
00:39:00,280 --> 00:39:02,080
Speaker 16: a lot of weakness earlier this week on the deep

774
00:39:02,080 --> 00:39:02,720
Speaker 16: seek news.

775
00:39:02,960 --> 00:39:04,760
Speaker 9: A lot of implications.

776
00:39:04,080 --> 00:39:06,879
Speaker 16: For you know, how much money is being cloud into AI,

777
00:39:06,920 --> 00:39:09,879
Speaker 16: at least based on the traditional sort of architecture. Now,

778
00:39:09,920 --> 00:39:11,279
Speaker 16: if deep seek is able to do this in a

779
00:39:11,320 --> 00:39:14,000
Speaker 16: more efficient and cost effective manner, that really kind of

780
00:39:14,080 --> 00:39:16,640
Speaker 16: changes the economics behind some of the spinning that they've

781
00:39:16,680 --> 00:39:17,080
Speaker 16: been doing.

782
00:39:17,400 --> 00:39:20,080
Speaker 4: I'm les Delca. Got to be busy, thank you. Moving

783
00:39:20,120 --> 00:39:22,600
Speaker 4: on to two other companies also reporting after the Bell Service.

784
00:39:22,640 --> 00:39:24,160
Speaker 4: Now in IBM, let's get to it.

785
00:39:24,200 --> 00:39:25,520
Speaker 2: Boombergs Brodie Ford and.

786
00:39:25,680 --> 00:39:28,319
Speaker 4: Software is having its moment because of deep Seek. What

787
00:39:28,360 --> 00:39:29,320
Speaker 4: do we expect from IBM?

788
00:39:29,719 --> 00:39:33,959
Speaker 17: Absolutely so with IBM, their method of AI monetization thus

789
00:39:33,960 --> 00:39:37,120
Speaker 17: far as argument in their consulting business. Everyone's watching their

790
00:39:37,120 --> 00:39:40,840
Speaker 17: bookings around AI as it relates to consulting because that's

791
00:39:40,880 --> 00:39:42,319
Speaker 17: kind of a good place to be in with the

792
00:39:42,320 --> 00:39:45,280
Speaker 17: picks and shovels question because you know, no matter what happens,

793
00:39:45,320 --> 00:39:47,239
Speaker 17: even if the customers don't actually end up buying it,

794
00:39:47,560 --> 00:39:49,319
Speaker 17: ib able to help you set it up right. So

795
00:39:49,320 --> 00:39:52,120
Speaker 17: that's a good setup for Jeni at this moment. See

796
00:39:52,160 --> 00:39:54,799
Speaker 17: how folks are watching for that as well as their

797
00:39:54,840 --> 00:39:56,920
Speaker 17: own software business largely.

798
00:39:57,840 --> 00:40:00,960
Speaker 3: And Brodie on Service now Generative AI is also a

799
00:40:01,000 --> 00:40:03,520
Speaker 3: big part of their story. Tell us what you're looking

800
00:40:03,560 --> 00:40:06,520
Speaker 3: for this afternoon when they drop the application.

801
00:40:06,719 --> 00:40:10,160
Speaker 17: Software vendors were struggling a little while as it relates

802
00:40:10,160 --> 00:40:12,680
Speaker 17: to AI, but right now with the agent moment, there's

803
00:40:12,719 --> 00:40:16,759
Speaker 17: a lot more optimism, especially with deep seek. People say, hey,

804
00:40:16,920 --> 00:40:20,720
Speaker 17: are models getting cheaper. Maybe that's scary if you're in Nvidia,

805
00:40:20,840 --> 00:40:22,879
Speaker 17: but if you're a company that's going to buy those

806
00:40:22,960 --> 00:40:26,200
Speaker 17: models and then deliver them to your customers, that's actually

807
00:40:26,360 --> 00:40:26,880
Speaker 17: very good.

808
00:40:27,000 --> 00:40:27,640
Speaker 2: We see that the.

809
00:40:27,600 --> 00:40:30,040
Speaker 17: Service now is at about an all time high right now,

810
00:40:30,080 --> 00:40:32,479
Speaker 17: and you know, folks are whole. It's down a little

811
00:40:32,480 --> 00:40:35,319
Speaker 17: bit today, but yesterday they close that an all time high,

812
00:40:35,400 --> 00:40:38,920
Speaker 17: so investors are excited about the potential for the application

813
00:40:39,040 --> 00:40:41,520
Speaker 17: layer to really kind of start having its moment With Jennai.

814
00:40:42,280 --> 00:40:44,640
Speaker 4: Both of these stocks had their moment in twenty twenty

815
00:40:44,640 --> 00:40:48,360
Speaker 4: four though. Yes, IBM up thirty percent more than bestince

816
00:40:48,400 --> 00:40:50,719
Speaker 4: two thousand and I service now and its best year

817
00:40:50,800 --> 00:40:54,240
Speaker 4: up fifty percent. So is it all about just talking

818
00:40:54,320 --> 00:40:55,800
Speaker 4: up the AI narrative as much.

819
00:40:55,600 --> 00:40:56,120
Speaker 2: As they can.

820
00:40:56,440 --> 00:40:58,840
Speaker 17: That's a huge part of it. IBM had such a

821
00:40:58,840 --> 00:41:00,719
Speaker 17: great year last year because they were one of the

822
00:41:00,920 --> 00:41:03,919
Speaker 17: rare reacceleration stories with software. I mean, you could poke

823
00:41:03,960 --> 00:41:05,759
Speaker 17: at their growth right and say, oh man, it's only

824
00:41:05,840 --> 00:41:10,040
Speaker 17: two percent this and that, but their software business is accelerating.

825
00:41:10,040 --> 00:41:12,719
Speaker 17: I mean, the idea that IBM would become a serious

826
00:41:12,760 --> 00:41:16,480
Speaker 17: software contender, you know, five six years ago wasn't the

827
00:41:16,520 --> 00:41:19,200
Speaker 17: most popular take, but today we've seen that it really

828
00:41:19,239 --> 00:41:20,160
Speaker 17: has played out.

829
00:41:21,640 --> 00:41:24,799
Speaker 3: Bertie, Is there any weak spot in either of these

830
00:41:24,800 --> 00:41:28,239
Speaker 3: companies as they're heading into this afternoon that investors are

831
00:41:28,239 --> 00:41:29,680
Speaker 3: going to be concerned about?

832
00:41:29,680 --> 00:41:30,320
Speaker 5: In particular?

833
00:41:30,520 --> 00:41:33,520
Speaker 17: One X factor is that they are both pretty big

834
00:41:33,560 --> 00:41:37,840
Speaker 17: government you know, vendors, and obviously what doge right, I mean,

835
00:41:37,880 --> 00:41:40,080
Speaker 17: if the whole promise is that we're going to cut off,

836
00:41:40,840 --> 00:41:43,000
Speaker 17: you know, spending on unnecessary things.

837
00:41:43,120 --> 00:41:43,319
Speaker 12: Right.

838
00:41:43,719 --> 00:41:47,960
Speaker 17: Elon famously doesn't love to pay software bills at his

839
00:41:48,000 --> 00:41:50,759
Speaker 17: own companies, right, And so some investors have said, man,

840
00:41:50,880 --> 00:41:52,680
Speaker 17: is this going to be a concern when it comes

841
00:41:52,719 --> 00:41:55,920
Speaker 17: time to you know, a company like service now Is

842
00:41:55,960 --> 00:41:58,000
Speaker 17: sells so much into the federal government.

843
00:41:58,960 --> 00:42:01,839
Speaker 4: I correct myself, seve Now up fifty in twenty twenty four,

844
00:42:01,920 --> 00:42:04,760
Speaker 4: is actually up eighty one percent in age twenty three.

845
00:42:04,960 --> 00:42:07,360
Speaker 4: We'll see what it delivers tonight, Brady Ford. Great to

846
00:42:07,360 --> 00:42:09,680
Speaker 4: have him across both of the earnings. And that does

847
00:42:09,719 --> 00:42:12,440
Speaker 4: it for this edition of Bloomberg Technology. Don't forget to

848
00:42:12,520 --> 00:42:14,200
Speaker 4: check in on all of the earnings after the bell,

849
00:42:14,280 --> 00:42:16,000
Speaker 4: but also check out our podcast. You can find it

850
00:42:16,040 --> 00:42:18,240
Speaker 4: on the terminal as well as online on Apples, Spotify,

851
00:42:18,280 --> 00:42:21,440
Speaker 4: and iHeart from New York from San Francisco. This is

852
00:42:21,440 --> 00:42:22,880
Speaker 4: Bloomberg Technology.