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Speaker 1: Bloomberg Audio Studios, podcasts, radio news. Bloomberg Tech is alive

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

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Speaker 1: and Ed Lovelow in Sent Francisco.

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Speaker 2: This is Bloomberg Tech coming up.

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Speaker 3: US auto safety regulators probe Tesla over issues with door

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Speaker 3: handles on certain vehicles following a Bloomberg report.

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Speaker 4: Plus, Google will invest close to seven billion dollars over

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Speaker 4: two years in the UK to help build its AI economy, and.

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Speaker 3: Service now expands its presence in Florida with a new

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Speaker 3: regional hub. We speak with the CEO and with the

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Speaker 3: developer of the.

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Speaker 4: Site, but first we check out what's happening in the markets.

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Speaker 5: We are so close to ten.

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Speaker 4: Straight days of gains on the NASA one hundred. There's

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Speaker 4: a blip. We pull just slightly into the negative territory.

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Speaker 4: And then as that one hundred only slightly ed, what

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Speaker 4: is it? Thirteen points? Much anxiety as we go into

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Speaker 4: the federal reserve policy. The decision comes tomorrow, will we

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Speaker 4: see a cut? But what about the future direction? As

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Speaker 4: those retail sales look pretty buoyant, can they be as

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Speaker 4: dubvish in the longer term? But Ed, you're looking at

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Speaker 4: perhaps what moves the markets on.

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Speaker 5: This exact day.

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Speaker 2: Yeah, let's go to our top story.

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Speaker 3: US auto safety regulators opened up an investigation into whether

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Speaker 3: some Tesla vehicle doors are defective. This comes days after

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Speaker 3: a Bloomberg investigation uncovered a series of incidents in which

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Speaker 3: people were injured or died after they were unable to

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Speaker 3: open doors when Tesla's lost power, particularly after crashes. I

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Speaker 3: would note the stock is higher in this Tuesday session,

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Speaker 3: up almost two percent. Bloomberg's Global Auto's editor Craig Trudell

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Speaker 3: joins us from London. Let's start with the investigation, which

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Speaker 3: is a Nitzer investigation. Craig explain the parameters of what

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Speaker 3: Nitza's looking at and the scope of what they're looking at.

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Speaker 6: Yeah, it's interesting, you know, the sort of headline information

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Speaker 6: at the top of this document that it's an issue

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Speaker 6: today refers to a pretty narrow, narrow set of vehicles.

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Speaker 6: This is the twenty twenty one model Y. It's about

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Speaker 6: one hundred and seventy thousand cars. But the issue here

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Speaker 6: has the potential to be much broader because what NITSA

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Speaker 6: is looking at is Tesla's approach to its door design

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Speaker 6: and the fact that its doors are reliant on.

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Speaker 2: Electrical power in order to work.

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Speaker 6: That is something that applies to all Tesla's going back

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Speaker 6: to the model S that's been in production since twenty twelve.

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Speaker 6: So while Tesla is you know, on the surface, it

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Speaker 6: looks like this is a single model, a single model year,

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Speaker 6: this has the potential to be something much broader. You

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Speaker 6: think back to, you know, a precedent of an autopilot

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Speaker 6: investigation where they were narrowly looking at how that system

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Speaker 6: handled you know, certain parameters like how they werenavigating emergency

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Speaker 6: vehicles and you know, running into say, fire trucks or

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Speaker 6: police cars. That didn't just stayed narrowly focused on that

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Speaker 6: one issue. They had to recall autopilot.

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Speaker 7: You know.

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Speaker 6: Overall, right, it affected their vehicles in a much broader way.

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Speaker 6: It has there is some potential for the same to

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Speaker 6: play out here with this model.

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Speaker 2: Why why investigation.

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Speaker 4: Craig China, top regulators there have been looking at these

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Speaker 4: concealed handles before. Already Europe has been thinking a lot

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Speaker 4: about accidents in such cases.

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Speaker 5: Is it just a Tesler design?

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Speaker 4: And more broadly, how are we thinking about the US

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Speaker 4: tackling it versus other regions?

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Speaker 6: I think it's interesting because this is a design that,

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Speaker 6: for all of its potential flaws, at least to some degree,

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Speaker 6: has been embraced and sort of copied by other manufacturers.

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Speaker 2: And that's something that we included in our.

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Speaker 6: Report last week that a lot of electric vehicle you know,

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Speaker 6: rivals or would be rivals to Tesla that have come

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Speaker 6: onto the market over the years have kind of embraced

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Speaker 6: this you know, flush door handle design, essentially kind of

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Speaker 6: innovating a door handle that maybe didn't need to be innovated,

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Speaker 6: and that is something that will be you know, very

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Speaker 6: interesting for us to watch here because we also included

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Speaker 6: in last week's report mentioned of the fact that we've

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Speaker 6: already seen recalls related to the safety of door handles

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Speaker 6: in for instance, the Mustang Machie, the Ford SUV that

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Speaker 6: is taking on the Model Y. So this has the

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Speaker 6: potential to be not only a broader investigation for Tesla,

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Speaker 6: but also something that knits A takes a closer look

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Speaker 6: at across all manufacturers that have taken after Tesla from

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Speaker 6: this design perspective.

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Speaker 3: After NITSA confirmed its investigation this morning, Tesla has not

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Speaker 3: responded to request a comment from Bloomberg, but We just

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Speaker 3: showed Craig while you were speaking the comments of Tesla's

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Speaker 3: board chair Robin Denholm, which will remember Karen and I

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Speaker 3: are posed too after our original report has been in

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Speaker 3: vers Cray Trudell out of London.

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Speaker 2: Thank you very much.

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Speaker 3: Going back to the UK, Google will invest five billion

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Speaker 3: dollars that's six point five billion pounds storry, that's six

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Speaker 3: point eight billion dollars over two years into the UK

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Speaker 3: to help build an AI economy in the country. The

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Speaker 3: tech giant disclosed the plan just as President Trump is

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Speaker 3: set to announce billions of dollars of economic deals during

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Speaker 3: his visit to the UK this week. He's expected to

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Speaker 3: travel with several US tech leaders, including in Nvidio CEO

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Speaker 3: Jensen Wang and open Ai CEO Sam Altman. Bloomberg's UK

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Speaker 3: correspondent Lizzie Burden joins us and Lizzie give us the

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Speaker 3: need to know on this alphabet deal and what else

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Speaker 3: we're looking forward to.

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Speaker 8: Well, as you both know, this alphabet deal is a

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Speaker 8: drop in the ocean in terms of the capex of alphabets,

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Speaker 8: but it's a big deal for the UK. It's something

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Speaker 8: that's been long in the making. The UK tech Secretary

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Speaker 8: is the former one. Peter Kyle is now the UK

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Speaker 8: Business and Trade Secretary, perhaps as a sign of just

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Speaker 8: how important tech is to the business landscape here in

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Speaker 8: the UK.

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Speaker 5: But as you say, it's part of a broader suite.

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Speaker 8: Of economic deals that we're expecting the President to announce

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Speaker 8: here on his visit to Britain. We're expecting ten billion

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Speaker 8: pounds worth of deals to be announced, including a defense

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Speaker 8: tech cooperation agreement, also partnership on nuclear also bringing together

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Speaker 8: the economic hubs on both sides of the Atlantics. There's

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Speaker 8: a lot of stake here for Keir Starmer. It's an

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Speaker 8: unprecedented second state visit for Donald Trump here in Windsor

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Speaker 8: this eleventh century castle behind me. But I have to

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Speaker 8: say this is the worst possible timing for Keir Starmer.

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Speaker 8: He's just lost his UK Ambassador to the US, Peter Mandelson,

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Speaker 8: over his links to Jeffrey Epstein. Epstein of course links

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Speaker 8: to the King himself via his brother Prince Andrew, and

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Speaker 8: to Donald Trump. So there are going to be some

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Speaker 8: very very awkward moments, not least at the press conference

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Speaker 8: at the end of the trip. For the UK, the

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Speaker 8: point will be to not look like we're appeasing the President,

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Speaker 8: but also to make sure that something substantive comes out

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Speaker 8: from this visit, because ultimately the UK is playing its

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Speaker 8: age by deploying the King.

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Speaker 4: Bloomberg's Lizzie Burden from Windsor Castle. We appreciated. Let's return

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Speaker 4: to the tech deals that we're expecting to come out

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Speaker 4: of that visit and the focus on AI with Leeds Hue,

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Speaker 4: chief Investment Officer for Thematic Innovation Equities and Alliance Burnsteam

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Speaker 4: and more.

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Speaker 5: This fits into the whole.

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Speaker 4: Array of conversation we keep having about the need for

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Speaker 4: investment in air. We just think back to Oracle's numbers

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Speaker 4: last week and how much they were showing that they've

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Speaker 4: got this backlog building. We've got all the hyperscalers trying

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Speaker 4: to build out, Alphabet's looking to build a data center

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Speaker 4: in the UK. Are we seeing that continuing to go

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Speaker 4: up into the right at the speed that we see

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Speaker 4: at the moment, Well.

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Speaker 9: I think all we're seeing is actually we're hitting an

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Speaker 9: inflection point in inferencing. So you look, it's just broadly speaking,

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Speaker 9: not just those big numbers that you quoted, but also

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Speaker 9: if you look the AI trend and the adoption and

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Speaker 9: where we're seeing the step function and numbers is broadening out,

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Speaker 9: so it's a broader set of companies that are starting

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Speaker 9: to benefit, whether it's the networking companies or we're seeing

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Speaker 9: it in memory pricing, in storage, in hardware. So those

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Speaker 9: are all signs that you know, in terms of the

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Speaker 9: AI adoption, the inferencing at the edge, things are actually happening,

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Speaker 9: and to me, this is a very positive sign. That

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Speaker 9: means the real adoption which will drive continued build So

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Speaker 9: we think about it tech innovation generally, we take step functions, right,

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Speaker 9: We kind of chuck along and then all of a

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Speaker 9: sudden there's an inflection point and things really start to

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Speaker 9: take off. And I really think we are still in

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Speaker 9: the early innings of that happening, and supported by all

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Speaker 9: the evidence that we have seen at the micro level

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Speaker 9: from the company as well as these mega trends that

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Speaker 9: you're seeing at you know, the big macro level.

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Speaker 4: The step function has already been shown in the valuations

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Speaker 4: of companies. We just want to bring you some sound

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Speaker 4: actually from a key investor who manages money for Peter

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Speaker 4: til no Less. We've been talking about how we've been

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Speaker 4: looking at maybe a bubble growing an ai.

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Speaker 5: Just take a listen.

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Speaker 10: The AI bubble is real, and I don't take enough

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Speaker 10: people talk about it. And if you were able to

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Speaker 10: be an early investor in open ai, then congratulations, that's

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Speaker 10: a great place to be. If you're coming and investing

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Speaker 10: at open ai at a five hundred million dollar valuation,

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Speaker 10: I honestly.

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Speaker 2: Don't know about that.

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Speaker 10: So I think that is the more dominant topic that

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Speaker 10: is going on, at least within Silicon Valley circles. It

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Speaker 10: doesn't get talked about enough. And how it chicks out,

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Speaker 10: it's going to be fascinating because if you got in early, fantastic.

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Speaker 10: If you're getting in today, I'm not assured.

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Speaker 4: Long time sort of managing director for the private wealth

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Speaker 4: of Peter Teel, but also with AZVC founder Jack Selby,

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Speaker 4: there are you worried about any exuberance already reflecting evaluations

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Speaker 4: even though we are at this inflection point.

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Speaker 9: I think that brings it interesting point. Valuation is important,

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Speaker 9: and we always said valuation is important, but it's only

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Speaker 9: related to interestal customer revisions. So not all companies are

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Speaker 9: going to succeed. There will be a lot of company

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Speaker 9: that simply put the name in their press release, and

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Speaker 9: those are the ones that we say, oh, that's AI too.

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Speaker 9: So it actually brings back to we have to do

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Speaker 9: our due diligence. Some of them will succeed, many of

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Speaker 9: them will fail. Even if you look back to the

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Speaker 9: web one dot right, there were so thousands of companies,

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Speaker 9: but really a few survived and those are the leaders today.

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Speaker 9: And as we look forward, I would say AI is transformative.

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Speaker 9: We are early and leadership is being redefined. And that's

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Speaker 9: why all the companies are rushing out to spend because

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Speaker 9: it's as defensive as it is offensive. But we will

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Speaker 9: find new leaders but in the meantime we'll also have

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Speaker 9: to be prudent. Not all of them are going to succeed.

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Speaker 9: And in fact, when you redefine the future of leadership,

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Speaker 9: when there's a paradigm change, some of the things that

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Speaker 9: we use to think that work may not work. So

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Speaker 9: what is perceived to be cheap could also be more

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Speaker 9: expensive than you expect it. So again brings back to

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Speaker 9: we've got to do our homework. It's easy to call

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Speaker 9: everything a bubble, but underneath that, actually there are opportunities,

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Speaker 9: but they are also you know, prudence is absolutely important.

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Speaker 3: Lay the other counterpoint to a bubble argument is that

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Speaker 3: different geographies are moving at different speeds. This week exemplifies that.

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Speaker 3: Does it not that you see earlier announcements for a

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Speaker 3: buildout of infrastructure in the United Kingdom given that we

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Speaker 3: haven't seen the same level of activity in Western Europe

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Speaker 3: the United Kingdom? Does the Lions burnsteam change its attitude

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Speaker 3: towards British equities, UK equities, European equities in that AI

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Speaker 3: infrastructure supply chain.

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Speaker 9: I think AI is a global phenomenon, but it's more

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Speaker 9: so just tech. Innovation has become a crucial element in

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Speaker 9: national success. So it is something that we watch closely.

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Speaker 9: And I think in terms of each country the adoption

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Speaker 9: of AI, it reflects the readiness of the infrastructure, the

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Speaker 9: readiness of the government, But oftentimes it ultimately comes down

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Speaker 9: to a private public together initiative, and there will be opportunities.

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Speaker 9: We've seen sovereign being a big driver for spend and

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Speaker 9: I expect to see that continue going forward. And I

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Speaker 9: also think each country will take a very different approach

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Speaker 9: because the budget is different, the willingness is different.

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Speaker 3: Lay very quickly, how close are you tracking private markets

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Speaker 3: and private companies that are active here?

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Speaker 9: It's very very important for us because a big part

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Speaker 9: of the AI adoptions is happening in the private market.

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Speaker 2: And now to.

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Speaker 9: Mention, if you look at these hundreds of billions of

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Speaker 9: dollars they need to be financed. A big part of

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Speaker 9: the financing is being done on the private side, monitoring

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Speaker 9: that trend very closely, both on the demand side and

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Speaker 9: in terms of financing which support the supply side.

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Speaker 3: Late of alien spurn seen. Great to have you back

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Speaker 3: on the program, Thank you very much. Now coming up,

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Speaker 3: the CEO of Service Now and developer Related Ross joins

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Speaker 3: us to discuss efforts to turn West Palm Beach into

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Speaker 3: an AI hub.

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Speaker 2: Carry what are you looking at?

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Speaker 4: I'm actually still looking at those valuations on the publicly

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Speaker 4: traded side. Oracle, I mean key player when it comes

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Speaker 4: to AI infrastructure cours up one and a half percent.

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Speaker 4: This is on the back of its earnings last week,

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Speaker 4: but also as the narrative around TikTok continues to unfold.

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Speaker 4: Will they remain a key cloud provider, an infrastructure provider?

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Speaker 4: Could they even take a necty stake for at one

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Speaker 4: point se percent? This is Broomberg Tech.

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Speaker 3: Service Now is expanding its presence in Florida with a

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Speaker 3: new regional innovation hub, an AI Institute in West Palm Beach.

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Speaker 3: The developer of the site is Related Ross, run by

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Speaker 3: Stephen Ross. He's known for the Hudson Yards redevelopment project

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Speaker 3: and of course ownership of the Miami Dolphins. Stephen Ross

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Speaker 3: and Service Now CEO Bill McDermott join us now, gentlemen,

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Speaker 3: Good morning. Thank you for joining us here on Bloombo Tech. Bill,

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Speaker 3: it's great to have you back on. Start with the

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Speaker 3: Service Now piece. You know, in this environment, Bill, where

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Speaker 3: there's such a micro focus on the talent in AI

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Speaker 3: and where companies are spending resources, why does this position

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Speaker 3: Service Now better to have this footprint in Florida.

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Speaker 11: Well, there's no artificial intelligence without human intelligence, said, and

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Speaker 11: there's no leader that can develop a project and a

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Speaker 11: dream are better than Stephen Ross. And you mentioned the

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Speaker 11: Hudson Yards, but he also did the Time Warner Center.

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Speaker 11: And we've been friends for a long time. And I

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Speaker 11: always felt the trust was the ultimate human currency and

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Speaker 11: it's still is. And I believed in his dream and

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Speaker 11: what I see happening here is we're building an AI institute,

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Speaker 11: and in this institute, we're going to have the most

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Speaker 11: innovative engineers in the world. We're going to be able

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Speaker 11: to prototype solutions for the public and private sector at

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Speaker 11: record pace, and then we're going to move those solutions

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Speaker 11: out into the market. We're also creating knowledge university, and

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Speaker 11: we're going to put the flag right here in West

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Speaker 11: Palm Beach to rise up three million people in our

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Speaker 11: economy to the AI world so they can get the

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Speaker 11: better paying jobs, the creative jobs where only humans can

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Speaker 11: really excel. And I underscore we really believe it's all

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Speaker 11: about putting AI to work for people, because we're a

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Speaker 11: job creator and we believe that AI has to be

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Speaker 11: in service to people, and right in West Palm Beach

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Speaker 11: we're role modeling that.

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Speaker 3: Mister Ross, you have a vision that West Palm Beach

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Speaker 3: becomes an AI hub more than just service. Now, how

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Speaker 3: difficult is it to vince the technology industry of your vision?

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Speaker 2: And why West Palm Beach, Well.

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Speaker 12: I mean West Palm Beach is really because of Florida

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Speaker 12: being the great business state it is, and knowing that

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Speaker 12: South Florida is different than the rest of Florida and

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Speaker 12: it's really poised to growth and attract jobs. It's never

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Speaker 12: done that before. It's always been second homes, you know,

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Speaker 12: the second home to all South America, if you will.

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Speaker 12: But right now, the resources of Florida, there's not a

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Speaker 12: better business state. And when you look and see where

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Speaker 12: people are going in the change that's occurring in this country,

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Speaker 12: there's no place better positioned. So we had to really

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Speaker 12: put it together to bring those things that Florida didn't

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Speaker 12: have to attract business. And that's what we've been concentrating on.

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Speaker 12: And fortunately now I mean Bill and his vision which

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Speaker 12: is second to none. Really saw, at least in our opinion,

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Speaker 12: and I'll take that most people's opinion, but saw the

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Speaker 12: possibilities and how South Florida was really different than any

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Speaker 12: other place in the country. There's not a better business

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Speaker 12: state in Florida to start with. So we're very fortunate.

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Speaker 4: Bill eight hundred and fifty jobs over the next five years,

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Speaker 4: talking about one point eight billion dollars in economic impact.

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Speaker 4: You're big on training and training people with service now.

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Speaker 5: But will some of your employees move over? How much

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Speaker 5: are they wanting to come to the Gold Coast?

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Speaker 11: I would say we'll have a twenty percent of our

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Speaker 11: workforce likely relocate. The demand to do that has been unbelievable.

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Speaker 11: And I keep reminding people the office gets completed in

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Speaker 11: twenty twenty seven, so just relax. But the demand is there.

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Speaker 11: I think it'll be eighty percent net new job.

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Speaker 2: So you look at.

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Speaker 11: Florida, amazing universities across Florida, look at our veterans. We're

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Speaker 11: going to cross train our veterans on our open AI

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Speaker 11: opportunity and they're going to get excited and this is

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Speaker 11: going to be a great place for them to grow

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Speaker 11: and prosper people that want to switch jobs and go

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Speaker 11: into this industry because it's flourishing. You know, the jobs

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Speaker 11: are going to get created in tech companies like service Now,

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Speaker 11: and we keep hiring, We're growing, we're hiring, we're prospering

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Speaker 11: because the innovation is second to none. And you know

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Speaker 11: something you know that's very well Carolina and ed. This

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Speaker 11: platform connects to every cloud, it connects to every learning

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Speaker 11: and every AI model, and it connects.

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Speaker 2: To every data source.

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Speaker 11: So this will be the AI platform for business transformation.

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Speaker 11: And the opportunity has never been greater than it is

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Speaker 11: right now. And I'm excited to do this with my

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Speaker 11: great friend Steve and really really grow the company, especially

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Speaker 11: in West Palm Beach for the great state of Florida,

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Speaker 11: and I want to say Governor DeSantis, Mayor James Stephen Ross,

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Speaker 11: all of us work very hard behind the scenes to

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Speaker 11: make this moment a reality.

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Speaker 4: Stephen, that reality is mixed use residential, retail, office properties

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Speaker 4: in this particular focus.

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Speaker 5: What about data centers?

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Speaker 4: Are you thinking about the future of Florida there? I

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Speaker 4: know very much West Palm Beach is a place to

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Speaker 4: live and to thrive. But where will your opportunities go

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Speaker 4: next when it comes to technology.

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Speaker 12: Well, first of all, all we're just starting and really

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Speaker 12: had to really develop the base for them to see

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Speaker 12: the opportunities here. So we really concentrated on bringing great

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Speaker 12: universities like Vanderbilt that are coming here with their business engineering,

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Speaker 12: tech with schools, and then we had to bring in

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Speaker 12: a hospital. We have Cleveland Clinic, and so we're bringing

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Speaker 12: all those things that are necessary K through twelve education

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Speaker 12: to attract companies. And that's what we've been concentrating on

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Speaker 12: and working with the city and the county and the

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Speaker 12: state that will really make this a place where companies

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Speaker 12: really want to relocate because they can attract the best talent.

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Speaker 3: Mister Ross, thank you for that Bill, I think a

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Speaker 3: very reasonable question that your employees are going to have

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Speaker 3: is whether the you yourself are going to make the

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Speaker 3: move to Florida and other members of leadership will make

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Speaker 3: the move if you believe so much in this vision

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Speaker 3: of the future for West Palm Beach.

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Speaker 11: Well, you have to remember we have a very large

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Speaker 11: commitment to the state of California where we started the

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Speaker 11: company in both San Diego and Santa Clara, California, which

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Speaker 11: is where I'm based. But we will have executive leaders

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Speaker 11: on the top management team that will be domicile here

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Speaker 11: in West Palm Beach and will be part of this

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Speaker 11: amazing revolution. And I will spend a lot of time

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Speaker 11: the time, the discretionary time that I can here because

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Speaker 11: I really want people to know we planted a flag today.

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Speaker 11: This is a flag of opportunity, a flag of growth,

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Speaker 11: and leadership starts at the top. And I've always believed

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Speaker 11: that the true measure of a leader is not what

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Speaker 11: you take from this world, is what you give it.

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Speaker 11: And today's service now gave it a lot. We came

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Speaker 11: in here and Kelly, who runs Palm Beach County Business Development,

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Speaker 11: set on stage. This is the biggest corporate move into

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Speaker 11: this area in Palm Beach County in the last thirty years.

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Speaker 11: I'm super proud of that, and i want to make

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Speaker 11: this a stunning success. So I'll be where I need

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Speaker 11: to be, the leadership team will be where they need

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Speaker 11: to be. But the main thing is to build a

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Speaker 11: masterpiece of flywheel of growth and innovation.

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Speaker 2: I've already received several techs.

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Speaker 11: Today on this announcement from other tech companies and systems

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Speaker 11: integrators that are like, Wow, what are you doing there?

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Speaker 2: What's going on in West Palm.

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Speaker 4: Bill, We'll see who comes on to say they're moving next.

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Speaker 4: Bill McDermott, CEO of Service Now Stephen Ross, CEO related Ross.

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Speaker 5: Great to have you both. It's time now for talking tech.

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Speaker 4: First up, Amazon satellite internet venture project Kaiper, expected to

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Speaker 4: offer service in five countries, including the US by early

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Speaker 4: twenty twenty six. The names to compete with Musk Starlink,

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Speaker 4: and has already reached an agreement to provide on board

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Speaker 4: Wi Fi for Jet Blue plus Google Well it considered

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Speaker 4: selling off parts of its ad tech business to resolve

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Speaker 4: monopoly charges.

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Speaker 5: It's going into a lawyer for the company now.

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Speaker 4: The Justice Department, however, is seeking a full divestiture of

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Speaker 4: Google Google's advertising exchange.

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Speaker 5: Two sides meet in a hearing next week.

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Speaker 3: Welcome back to Bloomberg Tech. I'm saying here, look at

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Speaker 3: the chip sector. The Philadelphia Semiconductor Index or socks were

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Speaker 3: mildly soft, down a few tens five percent, but early

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Speaker 3: in the session we opened higher, and if we close

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Speaker 3: in the green, that would put us on track for

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Speaker 3: the ninth straight day of gains on the socks, which

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Speaker 3: is the longest streak since twenty seventeen.

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Speaker 2: Stories there, I've put Micron in a video.

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Speaker 3: Okay, video is down almost a percent in the moment,

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Speaker 3: but year to date, big drivers have gained. Micron reports

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Speaker 3: earning September twenty third in video. Under pressure right now,

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Speaker 3: but recent momentum and the idea carr as you know,

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Speaker 3: is that maybe in videos at the center of the

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Speaker 3: discussions between the United States and China right now, will

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Speaker 3: it come off on that phone call between the President

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Speaker 3: and Jijing thing on Friday?

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Speaker 2: That's the question the market's answer askame it is.

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Speaker 4: Meanwhile, the market's also looking at what President Trump is

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Speaker 4: doing in terms of filing a fifteen billion dollar defamation

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Speaker 4: lawsuit against the new York Times, that's greater in the

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Speaker 4: newspaper's market cap A so you can currently see the

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Speaker 4: President is accusing The Times of serving as a.

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Speaker 5: Quote mouthpiece for the Democrats.

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Speaker 4: The New York Times send in a statement that the

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Speaker 4: lawsuit quote has no merit and is an attempt to

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Speaker 4: stifle and discourage independent reporting. That's bringing lead focus for

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Speaker 4: Bloomberg's media and entertainment coverage Chris pal Mary, Chris, when

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Speaker 4: you're editing stories like this, when you're thinking about driving

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Speaker 4: forward the news, we have the context that is this

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Speaker 4: isn't the first time President Trump has sued a reporting network.

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Speaker 13: Right, I mean, in terms of our work, I mean,

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Speaker 13: we always try to be tough but fair to everybody.

440
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Speaker 13: And so this has been a tactic Trump's used for

441
00:23:56,320 --> 00:23:58,960
Speaker 13: years and until he became president. Really the second time

442
00:23:59,000 --> 00:24:03,320
Speaker 13: he's not been successful ensuing the media, but more recently

443
00:24:03,400 --> 00:24:07,760
Speaker 13: he has been getting settlements out of ABC and CBS, Facebook,

444
00:24:07,800 --> 00:24:11,359
Speaker 13: And so he's tying this in a way to his

445
00:24:12,600 --> 00:24:17,040
Speaker 13: power as president to say, get the FCC to approve

446
00:24:17,400 --> 00:24:21,040
Speaker 13: Paramount's merger with guidance, which happened just a week or

447
00:24:21,080 --> 00:24:24,000
Speaker 13: so after they settled the CBS suit with him so

448
00:24:24,320 --> 00:24:26,160
Speaker 13: you know, he's using this.

449
00:24:26,359 --> 00:24:27,639
Speaker 2: It scores with his base.

450
00:24:27,720 --> 00:24:29,680
Speaker 13: If you see what his truth social posts have said.

451
00:24:29,680 --> 00:24:33,400
Speaker 13: It's really about, hey, they're attacking me, your president, and

452
00:24:33,640 --> 00:24:37,120
Speaker 13: it's a revenue generator for his Presidential Library foundation.

453
00:24:37,880 --> 00:24:39,240
Speaker 2: And lastly, he.

454
00:24:39,320 --> 00:24:43,520
Speaker 13: Hopes whether that's successful not not clear at all. Is stifling,

455
00:24:43,880 --> 00:24:46,520
Speaker 13: as The New York Times said, trying to get reporters

456
00:24:46,560 --> 00:24:48,200
Speaker 13: not to write nasty stories about him.

457
00:24:48,920 --> 00:24:53,000
Speaker 3: Chris, what is it specifically that the president is claiming

458
00:24:53,080 --> 00:24:55,800
Speaker 3: in this suit? We say it's a fifteen billion dollar lawsuit,

459
00:24:55,800 --> 00:24:58,080
Speaker 3: But what is it that he is accusing the New

460
00:24:58,200 --> 00:25:00,280
Speaker 3: York Times of You.

461
00:25:00,200 --> 00:25:03,359
Speaker 13: Know, it's interesting compared to the ABC and CVS suits,

462
00:25:03,400 --> 00:25:07,880
Speaker 13: which were really specific incidences, this is much broader. It's

463
00:25:07,880 --> 00:25:14,000
Speaker 13: sort of just a whole agenda he argues against him

464
00:25:12,880 --> 00:25:18,040
Speaker 13: and for Kamala Harris in the last election. You know much,

465
00:25:18,480 --> 00:25:22,720
Speaker 13: you know, harder when there's no specific allegation of journalistic

466
00:25:23,040 --> 00:25:23,840
Speaker 13: wrongdoing here.

467
00:25:25,000 --> 00:25:27,040
Speaker 3: The New York Times said in a statement, the lawsuit

468
00:25:27,040 --> 00:25:29,320
Speaker 3: has no merit and is an attempt to cipher and

469
00:25:29,359 --> 00:25:33,640
Speaker 3: discourage independent reporting. Bloomberg's entertainment editor, Chris Palm Mary, thank

470
00:25:33,640 --> 00:25:36,800
Speaker 3: you very much, President Trump says, he'll speak with Chinese

471
00:25:36,880 --> 00:25:40,600
Speaker 3: leaders Jijingping on Friday, as US and Chinese officials reached

472
00:25:40,800 --> 00:25:44,760
Speaker 3: a framework deal on keeping the TikTok app running in

473
00:25:44,800 --> 00:25:45,679
Speaker 3: the United States.

474
00:25:45,720 --> 00:25:46,199
Speaker 2: Listen to this.

475
00:25:47,440 --> 00:25:48,920
Speaker 11: We have a deal on TikTok.

476
00:25:49,000 --> 00:25:50,320
Speaker 7: I've reached a deal with China.

477
00:25:50,359 --> 00:25:51,400
Speaker 14: I'm going to stick to.

478
00:25:51,520 --> 00:25:54,840
Speaker 15: Presidency on Friday to confirm everything up.

479
00:25:54,880 --> 00:25:57,080
Speaker 3: We made a very good, great deal, and I hope

480
00:25:57,119 --> 00:25:59,960
Speaker 3: good for both cutches, but a very different deal.

481
00:26:00,200 --> 00:26:03,560
Speaker 7: Made in the best.

482
00:26:03,960 --> 00:26:05,920
Speaker 9: We'll be announcing that we have a group of very

483
00:26:05,920 --> 00:26:07,000
Speaker 9: big companies.

484
00:26:06,600 --> 00:26:07,280
Speaker 6: That want to buy it.

485
00:26:08,320 --> 00:26:10,760
Speaker 3: That's the President speaking ahead of traveling to the United

486
00:26:10,840 --> 00:26:13,520
Speaker 3: Kingdom in summary, saying a lot of big technology companies

487
00:26:13,560 --> 00:26:16,520
Speaker 3: want to buy us TikTok and that there is a deal.

488
00:26:16,520 --> 00:26:17,640
Speaker 2: We'll learn more later in the week.

489
00:26:17,720 --> 00:26:21,480
Speaker 3: Sarahkrep's, director of the Tech Policy Institute at Cornell University,

490
00:26:21,800 --> 00:26:25,360
Speaker 3: joins us now and Sarah, you know, newsflow is one thing,

491
00:26:25,440 --> 00:26:29,440
Speaker 3: but it looks like we're proceeding to a situation where

492
00:26:29,480 --> 00:26:34,960
Speaker 3: a coalition of American technology companies and others will be

493
00:26:35,080 --> 00:26:38,320
Speaker 3: able to keep TikTok going in the United States. But

494
00:26:38,359 --> 00:26:41,640
Speaker 3: there's a big phone call on Friday, and in your analysis,

495
00:26:41,640 --> 00:26:45,040
Speaker 3: and expertise of the relationship between the United States and

496
00:26:45,119 --> 00:26:48,200
Speaker 3: China and the tech domain. How central is the success

497
00:26:48,240 --> 00:26:50,200
Speaker 3: of that phone call to this happening.

498
00:26:52,040 --> 00:26:55,000
Speaker 16: I don't think that the phone call itself is going

499
00:26:55,040 --> 00:26:57,840
Speaker 16: to be what this deal hinges on. My sense is

500
00:26:57,840 --> 00:27:01,560
Speaker 16: that they've already established a framework through which which the

501
00:27:01,680 --> 00:27:04,840
Speaker 16: US part of TikTok will divest from the Chinese parent

502
00:27:04,880 --> 00:27:08,520
Speaker 16: company Byte Dance, and I think Friday's call is really

503
00:27:08,640 --> 00:27:11,159
Speaker 16: just to seal that deal and make an announcement.

504
00:27:12,560 --> 00:27:15,879
Speaker 3: We cover this based in the United States, right, and

505
00:27:15,920 --> 00:27:18,919
Speaker 3: work for an American news organization, but we always come

506
00:27:18,960 --> 00:27:21,479
Speaker 3: at this from the US point to the negotiating table.

507
00:27:22,600 --> 00:27:26,280
Speaker 3: How do you evaluate how China feels about TikTok being

508
00:27:26,280 --> 00:27:29,240
Speaker 3: able to get to continue in the US but some

509
00:27:29,280 --> 00:27:33,560
Speaker 3: concessions being made that would impact China and byte.

510
00:27:33,400 --> 00:27:36,240
Speaker 5: Dance, right, I think this is well.

511
00:27:36,560 --> 00:27:39,560
Speaker 16: I think first and foremost they would be the Chinese

512
00:27:40,080 --> 00:27:42,080
Speaker 16: have made it pretty clear they do not want to

513
00:27:42,160 --> 00:27:46,520
Speaker 16: sell the algorithm, that they want to separate the platform

514
00:27:46,600 --> 00:27:49,120
Speaker 16: from the algorithm, because it's the algorithm that is really

515
00:27:49,119 --> 00:27:53,320
Speaker 16: the secret sauce here for the whole thing, and so

516
00:27:53,480 --> 00:27:56,879
Speaker 16: trying to tease those two things out. The algorithm from

517
00:27:57,040 --> 00:28:00,760
Speaker 16: TikTok Usa, I think is really important to them. But

518
00:28:00,840 --> 00:28:03,760
Speaker 16: then there is a lot of issue linkage going on here.

519
00:28:03,840 --> 00:28:06,439
Speaker 16: There are so many aspects. So TikTok I think is

520
00:28:06,520 --> 00:28:10,919
Speaker 16: part of a broader set of discussions on trade between

521
00:28:10,960 --> 00:28:12,679
Speaker 16: the US and China, and so I think this is

522
00:28:12,720 --> 00:28:16,280
Speaker 16: really an important part of that, but emblematic of I

523
00:28:16,359 --> 00:28:18,640
Speaker 16: think what it seems Trump is trying to do, which

524
00:28:18,680 --> 00:28:22,359
Speaker 16: is harmonize a little bit that relationship between the US

525
00:28:22,400 --> 00:28:25,679
Speaker 16: and China.

526
00:28:24,200 --> 00:28:28,159
Speaker 4: In terms of data. How safe or at least from

527
00:28:28,160 --> 00:28:32,320
Speaker 4: a national security perspective, how able is US data to

528
00:28:32,359 --> 00:28:35,720
Speaker 4: be now protected in some way from flowover to China,

529
00:28:35,800 --> 00:28:37,360
Speaker 4: as Congress hopes.

530
00:28:38,280 --> 00:28:41,040
Speaker 16: Right, that was the important thing for Congress, which is well,

531
00:28:41,120 --> 00:28:44,120
Speaker 16: there were two aspects for Congress, which was one was

532
00:28:44,120 --> 00:28:48,440
Speaker 16: the algorithm, which was the ability to manipulate through the algorithm,

533
00:28:48,760 --> 00:28:51,040
Speaker 16: But there was always the question of data. And even

534
00:28:51,080 --> 00:28:54,200
Speaker 16: without the algorithm, the data is still very powerful. As

535
00:28:54,400 --> 00:28:58,760
Speaker 16: you probably remember, Cambridge Analytica never touched Facebook's algorithm, but

536
00:28:58,960 --> 00:29:01,440
Speaker 16: with the raw data that they had, they built profiles

537
00:29:01,440 --> 00:29:04,720
Speaker 16: of individual users, tested messages, and then micro targeted them.

538
00:29:04,960 --> 00:29:07,960
Speaker 16: And the TikTok data is even more revealing than that.

539
00:29:08,120 --> 00:29:12,800
Speaker 16: So it just not just posts and likes, but watch times, rewatches, pauses, shares,

540
00:29:13,280 --> 00:29:19,040
Speaker 16: all those signals are an exposure of attention span, emotional triggers,

541
00:29:19,080 --> 00:29:19,880
Speaker 16: hidden interests.

542
00:29:20,200 --> 00:29:20,960
Speaker 11: So the.

543
00:29:22,480 --> 00:29:26,480
Speaker 16: You know whatever foreign entity would perhaps still have a

544
00:29:26,520 --> 00:29:30,040
Speaker 16: backdoor to that data, and so far I haven't seen

545
00:29:30,120 --> 00:29:33,240
Speaker 16: anything on the technical side about how the US what

546
00:29:33,400 --> 00:29:36,680
Speaker 16: part of the deal would address that possible back door

547
00:29:37,320 --> 00:29:39,400
Speaker 16: access to power the powerful data.

548
00:29:40,160 --> 00:29:42,560
Speaker 4: Sarah, It's so interesting because all of this comes in

549
00:29:42,680 --> 00:29:45,800
Speaker 4: the broader view of US China relations and you sit

550
00:29:45,880 --> 00:29:50,480
Speaker 4: at that intersection technology, geopolitics, national security is TikTok the

551
00:29:50,520 --> 00:29:52,440
Speaker 4: thing that we should be that worried about when we're

552
00:29:52,480 --> 00:29:54,320
Speaker 4: also looking about AI relationships.

553
00:29:56,000 --> 00:29:58,840
Speaker 16: Well, it's an interesting question because you know, and I've

554
00:29:58,960 --> 00:30:02,560
Speaker 16: puzzled over why Congress, which passed this law and it

555
00:30:02,640 --> 00:30:06,200
Speaker 16: was signed into law, has not really pushed back on

556
00:30:06,560 --> 00:30:11,800
Speaker 16: these constant extensions, because if this was such a national

557
00:30:11,800 --> 00:30:13,960
Speaker 16: security threat, you would think it was a threat a

558
00:30:14,040 --> 00:30:17,400
Speaker 16: year ago, and the ninety day extensions are just kind

559
00:30:17,400 --> 00:30:20,440
Speaker 16: of perpetuating that threat. And I think part of the

560
00:30:20,760 --> 00:30:24,160
Speaker 16: implicit realization is that we've you know, even if you

561
00:30:24,200 --> 00:30:27,240
Speaker 16: address TikTok is really the tip of the iceberg, and

562
00:30:27,360 --> 00:30:32,479
Speaker 16: all these other national security tech issues, including the AI question,

563
00:30:32,560 --> 00:30:35,479
Speaker 16: which I think is just in some ways looms even larger.

564
00:30:36,080 --> 00:30:39,680
Speaker 4: Sarah Creps of Cornell University come back to talk about

565
00:30:40,240 --> 00:30:42,160
Speaker 4: the AI looming still coming up.

566
00:30:42,240 --> 00:30:45,200
Speaker 5: Jack Ma returns to add to Baba with some conventions.

567
00:30:45,320 --> 00:30:46,760
Speaker 5: I'm going to discuss that next. This is a blue

568
00:30:46,800 --> 00:30:47,200
Speaker 5: bag tech.

569
00:30:55,920 --> 00:30:58,719
Speaker 4: Jack Ma is back after banishing from public eye at

570
00:30:58,720 --> 00:31:01,440
Speaker 4: the outset of an anti trust investgation in late twenty twenty.

571
00:31:01,680 --> 00:31:05,160
Speaker 4: Sources say China's most recognizable entrepreneur is back on Ali

572
00:31:05,160 --> 00:31:08,120
Speaker 4: Baba's campuses, and he's more directly involved than he's been

573
00:31:08,160 --> 00:31:08,920
Speaker 4: in half a decade.

574
00:31:09,080 --> 00:31:10,760
Speaker 5: Bromberg's Global Tech editor.

575
00:31:10,560 --> 00:31:14,400
Speaker 4: Peter Elstrom joins us, Now, how is his hand being felt?

576
00:31:15,680 --> 00:31:19,120
Speaker 15: Yeah, so Jack is back on the Ali Baba campuses.

577
00:31:20,000 --> 00:31:23,200
Speaker 15: We've spoken with people who have seen him on the campus.

578
00:31:23,240 --> 00:31:26,080
Speaker 15: He's wearing his badge around. He's more actively involved in

579
00:31:26,160 --> 00:31:28,760
Speaker 15: the operations of the company than he has been really

580
00:31:28,800 --> 00:31:32,080
Speaker 15: since twenty nineteen when he stepped down as chairman. In particular,

581
00:31:32,120 --> 00:31:35,520
Speaker 15: he's been quite involved in AI, their AI initiatives, which

582
00:31:35,560 --> 00:31:38,120
Speaker 15: are going quite well at Ali Baba, and he's been

583
00:31:38,240 --> 00:31:41,280
Speaker 15: very involved in this e commerce fight that the company

584
00:31:41,320 --> 00:31:44,440
Speaker 15: has been having with JD dot Com and Mayitwan, the

585
00:31:44,440 --> 00:31:47,520
Speaker 15: biggest delivery company there. Jack is used to the days

586
00:31:47,520 --> 00:31:51,200
Speaker 15: when Ali Baba commanded the tech landscape within China, when

587
00:31:51,240 --> 00:31:53,080
Speaker 15: they had something like eighty five percent of the e

588
00:31:53,120 --> 00:31:56,040
Speaker 15: commerce market, and now the competition is much more severe.

589
00:31:56,080 --> 00:31:59,160
Speaker 15: So in this latest clash where these companies are really

590
00:32:00,080 --> 00:32:03,680
Speaker 15: fighting with each other over fast deliveries, deliveries within an hour,

591
00:32:03,840 --> 00:32:06,840
Speaker 15: he's been encouraging them to spend lots of money fifty

592
00:32:06,880 --> 00:32:09,560
Speaker 15: billion New Want or about seven billion dollars on these

593
00:32:09,600 --> 00:32:13,240
Speaker 15: fast delivery competitions. So he's there, he's involved in strategy,

594
00:32:13,320 --> 00:32:16,040
Speaker 15: he's taking part in these discussions, and he's quite active,

595
00:32:16,120 --> 00:32:17,800
Speaker 15: and he's an inspiration for employee.

596
00:32:17,800 --> 00:32:18,520
Speaker 2: He's on campus.

597
00:32:19,280 --> 00:32:22,600
Speaker 3: That was part of the reporting that I found most interesting.

598
00:32:22,640 --> 00:32:26,560
Speaker 3: Sources basically telling us that Jack is back, but other

599
00:32:26,680 --> 00:32:29,480
Speaker 3: officials at the company are trying to explain to him

600
00:32:30,040 --> 00:32:32,760
Speaker 3: that it's not the Ali Barba that he knew from

601
00:32:32,800 --> 00:32:35,760
Speaker 3: a market competitiveness standpoint. Do we know anything about how

602
00:32:36,000 --> 00:32:39,360
Speaker 3: Jack Mars reacted to that, you know, the new realities

603
00:32:39,360 --> 00:32:40,760
Speaker 3: that he finds himself in.

604
00:32:42,080 --> 00:32:42,320
Speaker 2: Right.

605
00:32:42,360 --> 00:32:44,920
Speaker 15: He certainly is used to the days when Ali Baba

606
00:32:45,040 --> 00:32:48,560
Speaker 15: was the biggest, most valuable tech company within China, and

607
00:32:48,600 --> 00:32:50,640
Speaker 15: now the landscape has changed quite a bit. Even in

608
00:32:50,720 --> 00:32:54,160
Speaker 15: e commerce, they face very very serious competition and food

609
00:32:54,200 --> 00:32:56,560
Speaker 15: delivery May Twine is much bigger than they are now

610
00:32:56,600 --> 00:32:59,320
Speaker 15: ten Cent is much more valuable than they are. Ali

611
00:32:59,400 --> 00:33:01,720
Speaker 15: Baba's stock has come back quite a bit this year.

612
00:33:01,760 --> 00:33:04,360
Speaker 15: It's up about eighty percent, but it's still far far

613
00:33:04,400 --> 00:33:07,680
Speaker 15: below its peak back in twenty twenty. It's down more

614
00:33:07,720 --> 00:33:10,200
Speaker 15: than fifty percent from that level, and for good reason.

615
00:33:10,280 --> 00:33:12,960
Speaker 15: The company ran into a bunch of regulatory problems. Jack

616
00:33:13,000 --> 00:33:16,520
Speaker 15: Moss spoke out against the regulators at the time. That

617
00:33:16,600 --> 00:33:18,800
Speaker 15: was part of the reason that the company ran into trouble.

618
00:33:18,960 --> 00:33:21,800
Speaker 15: They were planning on taking their finance affiliate and group

619
00:33:21,840 --> 00:33:24,360
Speaker 15: public at that point, and they had to pull that IPO.

620
00:33:24,760 --> 00:33:27,280
Speaker 15: It still isn't public even at this point. But now

621
00:33:27,320 --> 00:33:30,840
Speaker 15: he's sort of come back. He's revived his reputation and

622
00:33:30,880 --> 00:33:33,720
Speaker 15: met with Shi Jimping earlier this year, So now he's

623
00:33:34,120 --> 00:33:37,320
Speaker 15: given more freedom and he's participating in campus and he's

624
00:33:37,360 --> 00:33:39,800
Speaker 15: more than just another executive at the company. He really

625
00:33:39,840 --> 00:33:42,400
Speaker 15: is an inspiration for a lot of the employees. Many

626
00:33:42,440 --> 00:33:44,520
Speaker 15: of these employees never worked with him, and they've been

627
00:33:44,560 --> 00:33:47,920
Speaker 15: there a short enough period of time that they haven't

628
00:33:47,960 --> 00:33:49,880
Speaker 15: really seen what he's been able to do, and they're

629
00:33:49,920 --> 00:33:51,880
Speaker 15: looking forward to him coming back. But as you say,

630
00:33:51,920 --> 00:33:54,560
Speaker 15: the business is very different. AI is much more important.

631
00:33:54,680 --> 00:33:57,360
Speaker 15: E commerce is very much a different game. They're participating

632
00:33:57,360 --> 00:33:59,160
Speaker 15: in cloud computing, so there's a lot that he has

633
00:33:59,200 --> 00:33:59,800
Speaker 15: to learn too.

634
00:34:00,800 --> 00:34:03,720
Speaker 3: Bloomberg's Peter Elstrom on a really important piece of Bloomberg

635
00:34:03,720 --> 00:34:07,280
Speaker 3: reporting about Ali Baba, Thank you Now. AI is coming

636
00:34:07,320 --> 00:34:11,280
Speaker 3: for the Owl due lingo is facing risks from multiple angles.

637
00:34:11,360 --> 00:34:14,600
Speaker 3: Is investors reassess the impact of AI on the language

638
00:34:14,680 --> 00:34:18,440
Speaker 3: learning platform. One of them AI powered live translation services.

639
00:34:18,480 --> 00:34:22,120
Speaker 3: Bloomberg's Tech equity reporter for Ian Vaselka has the reporting,

640
00:34:22,480 --> 00:34:24,840
Speaker 3: this takes me back to Apple iPhone day in the

641
00:34:24,920 --> 00:34:28,640
Speaker 3: market move when Airport's pro had simultaneous translation.

642
00:34:29,040 --> 00:34:32,279
Speaker 2: You've looked at the stock, what's going on? Hey, thanks

643
00:34:32,280 --> 00:34:32,799
Speaker 2: for having me.

644
00:34:32,960 --> 00:34:35,920
Speaker 13: So we've seen a number of AI companies and services

645
00:34:35,960 --> 00:34:39,000
Speaker 13: come out with live translation features, which is seen as

646
00:34:39,040 --> 00:34:42,520
Speaker 13: a kind of competition for dual lingo. Are people going

647
00:34:42,560 --> 00:34:44,960
Speaker 13: to be paying to keep learning languages. When you can

648
00:34:45,000 --> 00:34:49,439
Speaker 13: have AI automatically translate everything for you right away, that's

649
00:34:49,480 --> 00:34:52,600
Speaker 13: a big concern. Now the company has its own AI

650
00:34:52,680 --> 00:34:56,200
Speaker 13: first strategy, but this is an example where we have

651
00:34:56,239 --> 00:34:59,320
Speaker 13: seen a real consumer backlash against this. Now the company

652
00:34:59,320 --> 00:35:02,399
Speaker 13: says it's not impacting their financials yet, but we've seen

653
00:35:02,440 --> 00:35:05,239
Speaker 13: some analysts come out and talk about how this sort

654
00:35:05,280 --> 00:35:09,880
Speaker 13: of consumer aversion to AI could ultimately lead to weaker

655
00:35:10,000 --> 00:35:13,080
Speaker 13: user growth or other kinds of financial churn. So this

656
00:35:13,160 --> 00:35:14,759
Speaker 13: is a company that is getting it kind of on

657
00:35:14,800 --> 00:35:18,280
Speaker 13: both sides, both a backlash and competition from AI.

658
00:35:19,040 --> 00:35:22,560
Speaker 4: In our household, it's all about chess, bloemegs round Ustelica,

659
00:35:22,880 --> 00:35:23,600
Speaker 4: thank you very much.

660
00:35:23,640 --> 00:35:32,719
Speaker 5: Indeed, YouTube's Made on YouTube event is Underwear in New York,

661
00:35:32,760 --> 00:35:33,040
Speaker 5: with the.

662
00:35:33,000 --> 00:35:36,319
Speaker 4: Company unveiling new tools, of course, including plenty of aipowd

663
00:35:36,360 --> 00:35:38,600
Speaker 4: ones to help video creators. We've got one of them,

664
00:35:38,640 --> 00:35:41,240
Speaker 4: one of the most successful ones, Mark Rover, former NASA

665
00:35:41,280 --> 00:35:45,279
Speaker 4: engineer turned hugely popular YouTuber. And you are one of

666
00:35:45,360 --> 00:35:47,360
Speaker 4: the key creators at the event. You are in an

667
00:35:47,360 --> 00:35:49,880
Speaker 4: Apple product design as well. But you flipped your attention

668
00:35:49,920 --> 00:35:53,400
Speaker 4: back in twenty eleven to basically virality on YouTube and

669
00:35:53,640 --> 00:35:57,120
Speaker 4: education around science in particular, how much are you adopting

670
00:35:57,120 --> 00:35:59,279
Speaker 4: the AI tools, how much your team adopting it and

671
00:35:59,280 --> 00:36:00,480
Speaker 4: making your life a lot easier.

672
00:36:01,440 --> 00:36:03,360
Speaker 14: We've definitely got our pulse on it. We're using it

673
00:36:03,360 --> 00:36:06,560
Speaker 14: a lot for like ideation and like thumbnails. I'd say

674
00:36:06,680 --> 00:36:09,719
Speaker 14: is like the main like ide eating what thumbnails are.

675
00:36:09,760 --> 00:36:12,440
Speaker 14: But it's like, it will be really interesting to see

676
00:36:12,520 --> 00:36:15,799
Speaker 14: how consumers feel about this, right because some people do

677
00:36:15,840 --> 00:36:18,440
Speaker 14: feel like it's taking you know, the creator out of

678
00:36:18,440 --> 00:36:20,160
Speaker 14: the loop. But I think YouTube has been very clear

679
00:36:20,160 --> 00:36:23,239
Speaker 14: today they want to creator in the loop is what matter.

680
00:36:23,280 --> 00:36:26,440
Speaker 14: They don't want aislop either, So it kind of remains

681
00:36:26,480 --> 00:36:28,840
Speaker 14: if you've seen how the consumer feels out about it.

682
00:36:28,680 --> 00:36:33,160
Speaker 4: Interesting because for you, it's maybe about ab testing titles basically,

683
00:36:33,239 --> 00:36:35,759
Speaker 4: maybe there's dubbing that really helps the reach when you

684
00:36:35,840 --> 00:36:38,719
Speaker 4: go more global mark But when you think of VO

685
00:36:38,719 --> 00:36:41,440
Speaker 4: three and the use just not even of view as

686
00:36:41,440 --> 00:36:44,560
Speaker 4: a person, what do you want to put in place

687
00:36:44,600 --> 00:36:46,960
Speaker 4: by YouTube to ensure that slop isn't created?

688
00:36:48,760 --> 00:36:50,799
Speaker 7: I think I just trust that they're going to do

689
00:36:50,840 --> 00:36:51,680
Speaker 7: this responsibly.

690
00:36:51,719 --> 00:36:54,400
Speaker 14: But even for me, like there's an opportunity here, right,

691
00:36:54,480 --> 00:36:57,920
Speaker 14: Like I want to get people stoked about science and education,

692
00:36:58,040 --> 00:37:01,919
Speaker 14: and there's only you know, twenty four hours in a day,

693
00:37:02,320 --> 00:37:04,440
Speaker 14: so even for me, there's you know, there's an opportunity

694
00:37:04,440 --> 00:37:08,400
Speaker 14: for me to scale myself and to you know, teach

695
00:37:09,000 --> 00:37:10,280
Speaker 14: more topics deeper.

696
00:37:11,400 --> 00:37:13,440
Speaker 7: So you know, we're keeping a pulse on it.

697
00:37:13,480 --> 00:37:15,600
Speaker 14: I think YouTube will do a very good job of

698
00:37:15,600 --> 00:37:18,480
Speaker 14: making sure it's it's high quality and it's additive and

699
00:37:18,520 --> 00:37:21,760
Speaker 14: your feed isn't just filled with slot. That's terrible business

700
00:37:21,840 --> 00:37:23,439
Speaker 14: for them, right, They don't want that to happen. People

701
00:37:23,440 --> 00:37:25,960
Speaker 14: would stop using the platform.

702
00:37:26,200 --> 00:37:26,399
Speaker 9: Mark.

703
00:37:26,440 --> 00:37:28,800
Speaker 3: I spent a bit of time watching the Team Water

704
00:37:29,480 --> 00:37:32,000
Speaker 3: video that you did the collab we missed the Beast right,

705
00:37:32,080 --> 00:37:34,359
Speaker 3: and you know, hearing from some of the execs at

706
00:37:34,520 --> 00:37:37,640
Speaker 3: today's event, there's lots of awesome AI stuff with VO three,

707
00:37:38,000 --> 00:37:41,560
Speaker 3: but you describe how you'd use it. The Team Water

708
00:37:41,600 --> 00:37:45,239
Speaker 3: projects like real video. Does it result the AI tool

709
00:37:45,280 --> 00:37:48,960
Speaker 3: in just less real material circulating on the platform?

710
00:37:49,280 --> 00:37:51,359
Speaker 14: I think it depends on the type of content, right,

711
00:37:51,400 --> 00:37:55,040
Speaker 14: for like just telling stories and like fiction. You know,

712
00:37:55,200 --> 00:37:57,680
Speaker 14: I think you're gonna see a lot more AI adoption

713
00:37:57,840 --> 00:38:00,320
Speaker 14: and people being okay with that. You know, at the

714
00:38:00,400 --> 00:38:02,520
Speaker 14: end of the day, if you know, mister bist and

715
00:38:02,560 --> 00:38:05,200
Speaker 14: I we go to Kenya to visit a village. If

716
00:38:05,200 --> 00:38:08,319
Speaker 14: that's AI, like, I got to imagine people aren't going

717
00:38:08,360 --> 00:38:10,960
Speaker 14: to love that, right, So there's definitely going to be

718
00:38:11,000 --> 00:38:14,440
Speaker 14: a spot for like real content that is actual connecting

719
00:38:14,520 --> 00:38:17,040
Speaker 14: with real humans, right. And then there's a spot where

720
00:38:17,040 --> 00:38:19,320
Speaker 14: I think it's going to really help with storytelling, and

721
00:38:19,480 --> 00:38:21,560
Speaker 14: so I think I think we'll see how that kind

722
00:38:21,600 --> 00:38:23,280
Speaker 14: of settled out settles out over time.

723
00:38:24,920 --> 00:38:27,279
Speaker 3: Mark, what are the main challenges that you face on

724
00:38:27,360 --> 00:38:31,080
Speaker 3: YouTube that were not addressed by by these great generative

725
00:38:31,120 --> 00:38:32,840
Speaker 3: AI tools that will put out today?

726
00:38:33,920 --> 00:38:36,280
Speaker 14: I mean, for the challenges that I face, I feel

727
00:38:36,280 --> 00:38:39,360
Speaker 14: like it's actually they've given me more tools than I

728
00:38:39,400 --> 00:38:42,120
Speaker 14: would even use out of the gate, right, So I

729
00:38:42,160 --> 00:38:44,680
Speaker 14: think they're doing a good job of getting out in

730
00:38:44,719 --> 00:38:47,520
Speaker 14: front of it and giving creators the tools.

731
00:38:47,600 --> 00:38:48,840
Speaker 7: And that's what YouTube.

732
00:38:48,440 --> 00:38:50,840
Speaker 14: Does, right, That's kind of their advantage over like a Netflix.

733
00:38:51,040 --> 00:38:53,520
Speaker 14: They don't have to pick the winners. They make the tools,

734
00:38:53,560 --> 00:38:56,319
Speaker 14: they create the platform and lo and behold over time,

735
00:38:56,360 --> 00:38:59,000
Speaker 14: the winners, you know, emerge, and then that's.

736
00:38:58,840 --> 00:39:01,720
Speaker 7: Who YouTube pays right through addsets and stuff.

737
00:39:02,000 --> 00:39:04,040
Speaker 14: So I think they're just following the same playbook that

738
00:39:04,080 --> 00:39:06,560
Speaker 14: they've done so far that's made them so successful. Create

739
00:39:06,600 --> 00:39:08,719
Speaker 14: the tools, create the platform. The end of the day,

740
00:39:08,719 --> 00:39:10,320
Speaker 14: it's all about the creators.

741
00:39:10,200 --> 00:39:11,719
Speaker 5: And it's about authentic creators.

742
00:39:11,840 --> 00:39:14,560
Speaker 4: And that's what helped, for example, crunch Labs with the

743
00:39:14,600 --> 00:39:17,160
Speaker 4: success of getting real products into real people's hands because

744
00:39:17,160 --> 00:39:19,840
Speaker 4: people trust you and therefore you can help sell products.

745
00:39:19,880 --> 00:39:21,920
Speaker 5: You can do the stem toys, you can think.

746
00:39:22,000 --> 00:39:25,200
Speaker 4: Not only about viral videos, but about curriculum, about content,

747
00:39:25,280 --> 00:39:29,000
Speaker 4: about media projects that you're thinking mark will in the end,

748
00:39:29,120 --> 00:39:32,080
Speaker 4: authenticity be the thing that lends you even more success

749
00:39:32,200 --> 00:39:34,799
Speaker 4: versus the sudden wall of creation that we're going to

750
00:39:34,800 --> 00:39:35,600
Speaker 4: see that isn't real.

751
00:39:36,360 --> 00:39:40,200
Speaker 14: Yeah, I mean, especially on YouTube, historically, authenticity is the currency.

752
00:39:40,239 --> 00:39:42,080
Speaker 14: And that's kind of like what's helped me in by

753
00:39:42,160 --> 00:39:45,000
Speaker 14: background at NASA and Apple. I'm an actual mechanical engineer.

754
00:39:46,000 --> 00:39:48,960
Speaker 14: And you know, if a TV show like Discovery Channel

755
00:39:48,960 --> 00:39:51,719
Speaker 14: puts a TV show on YouTube, it doesn't do very

756
00:39:51,719 --> 00:39:56,040
Speaker 14: well because people want that authentic connection. So I think

757
00:39:56,080 --> 00:39:58,399
Speaker 14: there's probably going to be ways though, to even using

758
00:39:58,440 --> 00:40:02,200
Speaker 14: AI create that connection with your audience that feels authentic

759
00:40:02,280 --> 00:40:04,680
Speaker 14: and it all remained. You know, we're going to see

760
00:40:04,680 --> 00:40:07,160
Speaker 14: how that kind of pans out. But the tool is

761
00:40:07,200 --> 00:40:09,279
Speaker 14: just so powerful. You can do so much with it.

762
00:40:10,120 --> 00:40:14,160
Speaker 14: You know, clearly there's going to be some fairly seismic shift.

763
00:40:14,560 --> 00:40:16,640
Speaker 14: The key is kind of observing it and kind of

764
00:40:16,680 --> 00:40:19,160
Speaker 14: staying out in front, using it as a tool to

765
00:40:19,280 --> 00:40:22,640
Speaker 14: further authentically, you know, connect with your audience.

766
00:40:23,200 --> 00:40:25,879
Speaker 4: Marve your story is so fascinating. The fact that, yeah,

767
00:40:25,880 --> 00:40:28,160
Speaker 4: you've done all this philanthropic work of late and we

768
00:40:28,200 --> 00:40:30,319
Speaker 4: saw that with mister Beeste, But the fact that you

769
00:40:30,320 --> 00:40:30,719
Speaker 4: were an.

770
00:40:30,600 --> 00:40:32,800
Speaker 5: Assa engineer, the fact that you were working at Apple.

771
00:40:33,360 --> 00:40:35,640
Speaker 4: I mean we're all talking about generals to AI and

772
00:40:35,680 --> 00:40:37,520
Speaker 4: Apple being behind the curve. What do your products you

773
00:40:37,560 --> 00:40:40,520
Speaker 4: want from them?

774
00:40:40,880 --> 00:40:41,120
Speaker 7: Yeah?

775
00:40:41,160 --> 00:40:44,960
Speaker 14: I would want an iPhone that you know, actually Siri

776
00:40:45,040 --> 00:40:47,440
Speaker 14: that can actually answer a question or dictate.

777
00:40:47,520 --> 00:40:48,800
Speaker 7: Well, you know that Google.

778
00:40:48,920 --> 00:40:51,960
Speaker 14: It's really funny actually, you know it used to be

779
00:40:52,280 --> 00:40:54,600
Speaker 14: the Apple events are exciting. Google's were kind of boring

780
00:40:54,640 --> 00:40:56,279
Speaker 14: with like hardware and phones, and now it's sort of

781
00:40:56,320 --> 00:40:58,759
Speaker 14: switch where it's like, oh, what's Google doing, because you

782
00:40:58,760 --> 00:41:00,719
Speaker 14: know they are, you know, head of the curve at

783
00:41:00,760 --> 00:41:03,600
Speaker 14: least with AI and Gemini versus Apple got some catching

784
00:41:03,680 --> 00:41:07,600
Speaker 14: up to do. So regardless, it's a very exciting time

785
00:41:07,640 --> 00:41:10,040
Speaker 14: to be alive, right, you know, I think the way

786
00:41:10,120 --> 00:41:13,200
Speaker 14: we can definitely agree is that things will be changing

787
00:41:13,200 --> 00:41:17,319
Speaker 14: a lot in the next three, five, ten years and

788
00:41:17,600 --> 00:41:19,920
Speaker 14: we just get to you know, sit by an a watch.

789
00:41:20,040 --> 00:41:22,759
Speaker 14: But there's others of us, you know, myself, even you

790
00:41:22,800 --> 00:41:25,359
Speaker 14: know you guys included. We get to be part of

791
00:41:25,440 --> 00:41:27,480
Speaker 14: like shaping what it will be and how it will

792
00:41:27,520 --> 00:41:27,920
Speaker 14: turn out.

793
00:41:29,120 --> 00:41:29,480
Speaker 2: Market.

794
00:41:29,560 --> 00:41:32,799
Speaker 3: It looks like TikTok in the United States will be

795
00:41:32,840 --> 00:41:35,759
Speaker 3: able to continue. We'll find out more this week. You know,

796
00:41:35,840 --> 00:41:38,640
Speaker 3: in your career as a content creator focus on YouTube.

797
00:41:38,640 --> 00:41:41,400
Speaker 3: How do you view that? You know, your industry faces

798
00:41:41,480 --> 00:41:43,719
Speaker 3: choice right on the platforms that they can go to.

799
00:41:45,560 --> 00:41:47,520
Speaker 7: I think it's great. I think competition's great.

800
00:41:47,560 --> 00:41:51,480
Speaker 14: Honestly, I will say most creators, if you actually ask them,

801
00:41:51,840 --> 00:41:54,680
Speaker 14: want to move to YouTube, Like if you're big on TikTok,

802
00:41:55,160 --> 00:41:57,640
Speaker 14: if you're big on Instagram, like, they want to shift

803
00:41:57,680 --> 00:42:00,440
Speaker 14: to YouTube because they watch out for creators most they

804
00:42:00,440 --> 00:42:02,160
Speaker 14: pay the most. I'm not getting paid to say that.

805
00:42:02,239 --> 00:42:04,279
Speaker 14: I'm just one of them, and I see this right,

806
00:42:05,400 --> 00:42:08,400
Speaker 14: So and generally, you know, when TikTok had their short

807
00:42:08,400 --> 00:42:11,600
Speaker 14: form now YouTube as YouTube shorts. So generally, if there's

808
00:42:11,719 --> 00:42:15,360
Speaker 14: a type of content that really becomes sticky, right. You know,

809
00:42:15,440 --> 00:42:18,600
Speaker 14: YouTube adapts, and you know this AI is a great

810
00:42:18,600 --> 00:42:21,239
Speaker 14: example of this, Right. I think they're staying ahead of

811
00:42:21,280 --> 00:42:23,400
Speaker 14: the curve and skating to where the puck is and

812
00:42:23,440 --> 00:42:25,719
Speaker 14: saying like, hey, we need to make these tools available

813
00:42:26,120 --> 00:42:29,400
Speaker 14: so that we don't become obsolete, which, honestly, you know,

814
00:42:29,480 --> 00:42:31,960
Speaker 14: YouTube is where I have seventy one million subscribers.

815
00:42:32,000 --> 00:42:35,200
Speaker 7: So I'm really glad that they are having that kind.

816
00:42:35,040 --> 00:42:37,400
Speaker 14: Of attitude so that it doesn't become a tool or

817
00:42:37,520 --> 00:42:39,160
Speaker 14: in a platform that people don't want to use.

818
00:42:39,239 --> 00:42:39,399
Speaker 2: Right.

819
00:42:40,600 --> 00:42:43,399
Speaker 3: Mark Rover, YouTube Create, a founder of crunch Labs. Really

820
00:42:43,440 --> 00:42:45,520
Speaker 3: great to have you here on Bloomberg Tech. Thank you

821
00:42:45,640 --> 00:42:48,400
Speaker 3: very much. That does it for this edition of Bloomberg

822
00:42:48,480 --> 00:42:49,000
Speaker 3: Tech CARC.

823
00:42:49,560 --> 00:42:52,080
Speaker 4: Do not forget to check out some of our other

824
00:42:52,160 --> 00:42:54,560
Speaker 4: areas on digital podcasts, for example, you can find it

825
00:42:54,600 --> 00:42:56,719
Speaker 4: on the terminal as well as online on Apples, Spotify, and.

826
00:42:56,800 --> 00:42:59,880
Speaker 5: iHeart from New York from San Francisco. This is bet

827
00:43:00,080 --> 00:43:00,480
Speaker 5: back Tack.

828
00:43:03,000 --> 00:43:03,239
Speaker 11: Yeah,