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

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Speaker 1: live from Coast to Coast with Caroline Hide in New

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Speaker 1: York and Eva low in sentrances go.

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Speaker 2: This is Bloomberg Tech coming up.

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Speaker 3: Open Ai becomes the world's largest startup with a five

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Speaker 3: hundred billion dollar valuation following an employee share sale.

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Speaker 4: Plus Tesla's vehicle sales jumped to a worldwide record in

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Speaker 4: the third quarter, a surprise increase after several quarters of

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Speaker 4: sales slumps. How much did the ev tax credit exploration.

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Speaker 3: Helped, and how Microsoft aims to cope with a shortage

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Speaker 3: of AI data center capacity, striking deals with so called

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Speaker 3: neo clouds.

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Speaker 4: So first we check in on these publicly traded markets

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Speaker 4: that were at record highs clinging to them as we speak.

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Speaker 4: The NASAK one hundred is up but five points now. Notably,

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Speaker 4: we've got a wall of worry coming towards the markets

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Speaker 4: at the moment. But there have been this desire to

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Speaker 4: buy into chip stocks, in particular the open ai valuation

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Speaker 4: that we'll dig into, the idea of the contracts that

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Speaker 4: they're building with sk Heinex, with Samsung, all of that

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Speaker 4: had really helped lift the socks. I'm looking at that

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Speaker 4: at one point thirty percent, but really there's other stocks

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Speaker 4: that are dragging the overall benchmarks a little bit lower.

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Speaker 5: Edd.

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Speaker 3: Yeah, the part of the argument is that it's Tesla

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Speaker 3: that's doing that.

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Speaker 2: Right.

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Speaker 3: We had been higher pre market when the delivery numbers broke.

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Speaker 3: Four hundred and ninety seven ninety nine evs delivered in

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Speaker 3: the third quarter, an astonishing turnaround, a huge beat against consensus.

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Speaker 3: But as we've been talking about for a while now,

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Speaker 3: they started advertising in the quarter. They started emailing on

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Speaker 3: a daily basis, saying, by the way the federal tax

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Speaker 3: credit runs out, how big a fact was that that

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Speaker 3: it's an isolated quarter of an elevated proportion of sales.

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Speaker 2: Let's go to private markets.

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Speaker 3: Big piece of reporting from Bloomberg Shering Gafari open AI

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Speaker 3: five hundred billion dollar valuation based on employee share sale

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Speaker 3: to a really intro seen group of investors. Remember Sharen

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Speaker 3: broke this story first on August the sixth, But now

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Speaker 3: it's done and there's actually a lot of interesting data

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Speaker 3: in the report Caro about who opted to or not

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Speaker 3: to participate. If you're an employee that had two years

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Speaker 3: of holding the.

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Speaker 4: Shares and let's get straight to sharm Gafari extraordinary scoop

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Speaker 4: that first came in August. Now we get the real

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Speaker 4: details and perhaps those current employees and former employees not

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Speaker 4: setting as much as they could have done.

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Speaker 2: That's right.

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Speaker 6: So you know, again, this is a record valuation for

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Speaker 6: Open Eye and for just startups right now, surpassing SpaceX

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Speaker 6: as the most highly valued startup. That being said, there

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Speaker 6: was more. There could have been more units sold, is

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Speaker 6: what we're told. And actually employees shows not to take

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Speaker 6: up all of that potential share sale, so you know,

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Speaker 6: it could indicate that employees are feeling, you know, the

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Speaker 6: optimistic about the future of the company and that the

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Speaker 6: valuation could go even higher. But of course this is

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Speaker 6: an ongoing story and there are still a lot of

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Speaker 6: uncertainties as well in opening Ice future, including its ability

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Speaker 6: to go forward with the restructure.

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Speaker 3: When there is a tender or a secondary or any

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Speaker 3: kind of financial transaction. Sharene there's always a data room,

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Speaker 3: just take my word for it. And so I find

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Speaker 3: the group of investors here really interesting third parties that

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Speaker 3: were able to buy those shares from employees. Just run

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Speaker 3: us through the list and any that caught your eye.

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Speaker 6: That's right, so many of them were expected. We have Thrive,

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Speaker 6: also a former large investor, as well as SoftBank, another

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Speaker 6: major partner. We also have Abu, Abu, Dhab, MGX, Dragonear,

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Speaker 6: and t Row And you know, MGX is an interesting

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Speaker 6: one given we're seeing more money coming in from overseas,

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Speaker 6: from the Middle East into AI companies. And you know,

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Speaker 6: this is just an ongoing as I find an AI.

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Speaker 6: Once one investment closes, it's the beginning of another one.

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Speaker 6: So we can expect these sizes to just get bigger

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Speaker 6: and bigger in terms of funds going in and sales

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Speaker 6: being shares being seld.

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Speaker 4: I mean, that's what's extraordinary is the fact that they

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Speaker 4: raised money fresh money from SoftBank back in March, and

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Speaker 4: the valuation is just spiraled even since then, staring even

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Speaker 4: as remind us of the data and the fundamentals. The

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Speaker 4: company remains unprofitable and at the moment, revenue is tiny

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Speaker 4: in comparison to say a Netflix, which is also worth

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Speaker 4: about five hundred billion dollars.

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Speaker 2: That's right.

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Speaker 6: So while we're seeing the revenue increase rapidly, they have

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Speaker 6: something like seven hundred million users. At the same time,

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Speaker 6: the company is also unprofitable, and that's because of the

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Speaker 6: large cost to fuel basically the development of AI. There's

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Speaker 6: huge data compute costs. Here are these unprecedented data centers

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Speaker 6: that they're building out, there are researchers.

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Speaker 5: All of that takes a lot of money.

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Speaker 6: So it's still a highly capital intensive, an unprofitable business,

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Speaker 6: even though the revenue is growing at a very fast rate.

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Speaker 3: Bembo Sharen Gafari, It's Dev Dave Open Ai Monday, and

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Speaker 3: I think we're going to be able to pose questions

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Speaker 3: that might give us some of the answers to what's

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Speaker 3: really going on top and bottom line at open Ai.

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Speaker 3: Let's pivot from the private market side to the public

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Speaker 3: public side because open AI's story is driving US equities

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Speaker 3: to fresh highs. We've seen some pullback since the show started,

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Speaker 3: but generally the idea was that the open ai valuation

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Speaker 3: signaled a lot of optimism for AI across those public names.

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Speaker 3: Nancy Tengler, CEO and CIO of Lafetengla Investments, joins us

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Speaker 3: now for more. There's a lot of life in secondary markets.

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Speaker 3: Right sharm was running us through tro price participating in

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Speaker 3: that round. I know that this might not be your domain.

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Speaker 3: But what did you make of the open ai valuation?

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Speaker 3: And if someone came to you and said, Hey, Nancy,

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Speaker 3: I'm putting together an SPV or something like that, would

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Speaker 3: you try and get in on open ai at this

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Speaker 3: private level.

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Speaker 7: Yes, we would, yes, and we're actually in the process

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Speaker 7: of working with a firm to do just that. But

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Speaker 7: we're also interested in you know, SpaceX and XAI and

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Speaker 7: many of the other names that are still private, and

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Speaker 7: I think for retail investors it's an opportunity and then

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Speaker 7: of course for the insiders it provides liquidity at least

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Speaker 7: through the provider.

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Speaker 5: We're working with one.

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Speaker 3: One sec Marguerite, bring up the chart there it is okay,

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Speaker 3: so open ai five hundred billion dollar valuation, SpaceX number two,

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Speaker 3: four hundred billion, and then I don't see XAI in there,

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Speaker 3: but I reported that XAI is raising money at a

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Speaker 3: two hundred million dollar valuation. Of those three, what's your

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Speaker 3: top priority?

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Speaker 7: SpaceX is my greatest interest. I think we know the

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Speaker 7: AI game and there's a lot of ways to play it.

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Speaker 5: It's not a game, but the.

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Speaker 7: Opportunity and I really want to get more exposure to space.

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Speaker 7: So we just launched a fund a strategy that is

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Speaker 7: focused on all of the above quantum space, nuclear robotics,

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Speaker 7: and spaces of particular interest to us.

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Speaker 4: Fascinating that you're looking at basically these valuations in the

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Speaker 4: private side, as well as, of course all the exposure

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Speaker 4: that you build and the public side. Nancy, what draws you?

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Speaker 4: Is it just too hard to ignore when you're seeing

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Speaker 4: companies staying private for so much longer?

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Speaker 7: Yeah, well right, I mean, Caroline, we used to have

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Speaker 7: the Wilshire five thousand, and now it's the Wilshair thirty

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Speaker 7: five hundred. I think, you know, as an investor, my

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Speaker 7: job is to look around and try to figure out

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Speaker 7: ways to make money for my clients. When you're going

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Speaker 7: through a transformative technological revolution like we are, you get

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Speaker 7: these concentrations, you get higher than normal valuations. But that

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Speaker 7: is not to say this cannot continue for some time.

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Speaker 7: And as you know, I've drawn the analogy to the

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Speaker 7: nineteen nineties. I think the technologies we are seeing now

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Speaker 7: are much more robust than just eyeballs on a screen,

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Speaker 7: which was what we were measuring in the nineties. So

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Speaker 7: I'm excited about all the opportunity and really working hard

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Speaker 7: to try to figure out ways to gain exposure. Because

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Speaker 7: the private markets are open to a very lead group

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Speaker 7: of investors, certainly we want to open it up to

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Speaker 7: our clients as well.

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Speaker 4: Nazie, talk about the fundamentals that you like within these companies,

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Speaker 4: because yes, you're saying valuations can continue up into the

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Speaker 4: right for foreseeable future. You think it's underlying technology that

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Speaker 4: gets us there rather than the market being a rational

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Speaker 4: lesson in some sort of hype cycle.

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Speaker 7: Absolutely, so, just think back as far as Amazon. I mean,

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Speaker 7: that was a valuable lesson for me as a as

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Speaker 7: a value investor trained as a you know, buy when

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Speaker 7: things go down valuation matters. I could never figure out

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Speaker 7: how the company couldn't report earnings and continue to drive forward.

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Speaker 7: I think that, and so ultimately we became we participated

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Speaker 7: in the name and learned a lesson that during certain

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Speaker 7: periods of time, that's what you're going to see, and

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Speaker 7: you have to depend on management. You have to be

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Speaker 7: focused on the underlying fundamentals. And that's that's our job,

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Speaker 7: and that's why we have a team of analysts that

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Speaker 7: support me and the other portfolio managers at the firm.

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Speaker 7: So we're primarily focused on catalyst forout performance in the

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Speaker 7: soft site, we look at all the numbers that everybody

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Speaker 7: else looks at on the quantitative side, but qualitatively, we're

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Speaker 7: looking for catalyst for out performance and strong management teams,

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Speaker 7: and you can measure those over time. It's obviously a

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Speaker 7: subjective decision, but we spend a lot.

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Speaker 5: Of time on it.

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Speaker 3: Nancy, We're going to go very, very deep on Tesla

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Speaker 3: in the next segment. But actually, as a team, when

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Speaker 3: we were talking about today's show yesterday, your name came up, right,

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Speaker 3: you join us all the time. Four hundred and ninety

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Speaker 3: seven ninety nine vehicles delivered in the third quarter, a record.

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Speaker 3: The stock rose and now it's down almost two percent.

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Speaker 3: Just your reaction and to what extent you see the

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Speaker 3: expiry of the federal tax credit being the principal factor.

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Speaker 5: Well, I do think it's a principal factor.

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Speaker 7: And I mean I think there was some strength seen

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Speaker 7: in China which was good or at least less deterioration.

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Speaker 7: So I think that that is a rebound that we're

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Speaker 7: going to be watching and continuing to watch closely. But

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Speaker 7: for us, and I've said this to you, historically, we're

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Speaker 7: interested in the name because of the energy business, which

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Speaker 7: we've been talking about for two years, and I think

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Speaker 7: now people are sort of, you know, excited about that business.

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Speaker 7: We're interested, obviously, as everyone else is in FSD. They

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Speaker 7: seem to be seeing really robust improvements. It may not

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Speaker 7: be a linear acceleration. It may just be at one

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Speaker 7: point we see that FSD is at the levels we need,

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Speaker 7: and then they've got seven billion miles traveled and that

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Speaker 7: Dwarf's Weimo. I live in Weimo Land. You know, you

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Speaker 7: can't stop at a stoplight in Arizona without seeing four

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Speaker 7: or five of them. And Tesla's way ahead on that.

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Speaker 7: So they just need to catch up on the technology

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Speaker 7: and they will because they have the data. So we're

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Speaker 7: very excited about the new model Robotaxi, all of the others,

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Speaker 7: and then of course Optimists, which I'm counting on as

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Speaker 7: my home health care solution.

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Speaker 4: My kids asking me yesterday when we're going to be

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Speaker 4: getting a robot in the home, Nanci and I can

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Speaker 4: see that we're all waiting on tent to hoax. But

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Speaker 4: so too is the comp package for your musk. It's

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Speaker 4: tied to real delivereralies of Optimus of Robotaxes twenty million

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Speaker 4: evs on the roads.

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Speaker 2: Are you going to be voting in favor of that?

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Speaker 3: Oh?

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Speaker 7: Yes, absolutely, and the Ai you know, the XAI fundraise.

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Speaker 7: We would love to see the companies melt together and

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Speaker 7: get access to SpaceX and XAI. We'll see. I mean

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Speaker 7: that's me talking, not Elon, but we will definitely be

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Speaker 7: voting in favor. I love when incentives for the management

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Speaker 7: team or the visionary CEO are lined up with me

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Speaker 7: and my shareholders. So we're very excited about the future

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Speaker 7: of Tesla. And remember it doesn't go straight up. It's

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Speaker 7: a volatile name. We were buying at two forty in

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Speaker 7: the spring during the tariff tantrum. We will we will

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Speaker 7: buy again when stock dips down. But it's a six

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Speaker 7: percent holding in our strategy, which is the macrocycle opportunities,

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Speaker 7: and then in our growth strategy it's four and a

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Speaker 7: half percent holding. So we're committed to the name, and

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Speaker 7: you know, we believe, we believe in Elon. Maybe I'll

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Speaker 7: get a T shirt made well when the space fun

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Speaker 7: goes live.

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Speaker 4: When you've got the money coming in for the private

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Speaker 4: funds as well, do join us. I mean you're always

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Speaker 4: joining us, and we love it and that's a Tangler

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Speaker 4: CEO C that's Tangler Investments. Stay well. Meanwhile, coming up,

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Speaker 4: we're diving for into Tesla, into the vehicle sales that

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Speaker 4: jump to a worldwide record and third quarter. I'm going

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Speaker 4: to be going into what's behind this, whether it's sustainable.

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Speaker 4: Stay with us. This is Bloomberg Tech.

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Speaker 3: US customers help drive Tesla's third quarter sales to a

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Speaker 3: record high as buyers rush to take advantage of federal

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Speaker 3: tax credits before they expire. I want to get out

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Speaker 3: to London and Bloomberg's Automotive.

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Speaker 2: Zar Craigtrude out.

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Speaker 3: Data is really important here, Okay, third quarter four hundred

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Speaker 3: and ninety seven ninety nine vehicles. The expectation was we'd

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Speaker 3: see a drop year on year, even if it was

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Speaker 3: a sequential improvement. This this is an anomaly. This is

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Speaker 3: like something happened in the quarter. Just explain it.

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Speaker 8: Yeah, you know, I think this is a surprise if

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Speaker 8: you're looking at the consensus and yet if you sort

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Speaker 8: of were watching closely to where an estimates were coming in.

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Speaker 8: Towards the very end of the month of September, a

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Speaker 8: lot of sales side analysts were saying, we think these

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Speaker 8: deliveries are going to be much higher than that. I

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Speaker 8: think even having said that, you know, this is a

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Speaker 8: surprise even for those who are you know, bullish going

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Speaker 8: into this print. And you know, you do have to

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Speaker 8: hand it to this company to have delivered more vehicles

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Speaker 8: than they ever have, even if there are some real

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Speaker 8: questions about whether there's some staying power to these numbers.

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Speaker 8: Without the seventy five hundred dollars tax credit in the US,

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Speaker 8: that's going to be you know, the I guess fourner

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Speaker 8: and twenty dollars question on the earnings.

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Speaker 4: Call in a few weeks for twenty Craig. I'm interested though,

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Speaker 4: like you are, sat in the heart of the UK,

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Speaker 4: and indeed Europe has been against Tesla's basically we've seen

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Speaker 4: sales destruction over there in large part people blaming the

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Speaker 4: politics of Elon Musk. Is that still the sentiment that

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Speaker 4: you're seeing. Are you getting any other granular data that

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Speaker 4: shows that maybe other regions in the world have liked

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Speaker 4: the model wise and the upgrades.

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Speaker 8: Of late Yeah, I mean, I think in terms of

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Speaker 8: the way things have been trending in Europe, it's been

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Speaker 8: very consistent. There's maybe some you know, kind of marginal

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Speaker 8: narrowing of the declines over here in Europe, but still

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Speaker 8: substantially down in a market that is up substantially, and

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Speaker 8: in China you've seen, you know, at best, shipments move

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Speaker 8: sideways flat, you know, down by small percentages in a

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Speaker 8: market where you know, BYD and Jawmi and you know,

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Speaker 8: domestic players really are making a lot of noise. We did,

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Speaker 8: you know, see just recently some loss of momentum on

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Speaker 8: BYD's part, but that's from a standpoint of really just

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Speaker 8: dominating their local markets. So sort of by process of elimination,

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Speaker 8: we really, you know, can can sort of come to

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Speaker 8: this conclusion that the US is really what drove.

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Speaker 2: This result for Tesla. We'll see to what extent.

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Speaker 8: You know, Elon Musk is willing to sort of get

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Speaker 8: into that, but I think we've already heard from him

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Speaker 8: during the last earnings call that you know, this this

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Speaker 8: could be a company that's in for a few rough

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Speaker 8: quarters as a result of this pullback of support from

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Speaker 8: the US government.

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Speaker 4: Really most crowdu down. Thank you as always for the

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Speaker 4: thorough analysis. Let's stick with Tesla sales. Bring in Stephanie

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Speaker 4: Valdez Street. She is the director of Industry insights of

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Speaker 4: Coxa Automotive and just the larger picture in the US.

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Speaker 4: For Stephanie, it was but earlier in the week that

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Speaker 4: we saw Jim Farley, CEO of Ford saying the EV

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Speaker 4: market in the US is going to slump by half

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Speaker 4: because of the policy is currently being enacted here. And

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Speaker 4: meanwhile we see Tesla jump but because of that EV

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Speaker 4: tax credit expire, potentially, what is the forward looking analysis

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Speaker 4: of yours for US EV sales for Tesla?

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Speaker 9: Yeah, definitely, we knew Q three was going to be

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Speaker 9: a record quarter, right driven by policy. Right, everyone created

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Speaker 9: a sense of urgency, whether it was dealers, OEMs, and

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Speaker 9: so consumers reacted. So we're probably going to reach about

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Speaker 9: four hundred and ten thousand, probably ten percent market share

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Speaker 9: in the US market, and Tesla has definitely taken advantage

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Speaker 9: of that, but once again, that was policy driven. Moving

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Speaker 9: into Q four, we're going to see a slowdown. However,

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Speaker 9: I've already seen and you've probably seen some of the

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Speaker 9: manufacturers are going to continue a seventy five hundred dollars

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Speaker 9: credit going into Q four. On leasing, Hyundai mentioned they're

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Speaker 9: going to reduce their Ionic five by you know, ninety

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Speaker 9: eight hundreds and twenty six model and continue to offer

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Speaker 9: the seventy five hundred.

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Speaker 3: So just very specifically, Stephanie, in this quarter that's just

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Speaker 3: been reported. In the Tesla's case, specifically, you see evidence

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Speaker 3: that the consumer knew that the federal tax credit was

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Speaker 3: running out and so took advantage of that to make

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Speaker 3: a decision and either purchase or lease a vehicle.

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Speaker 9: Oh definitely, Yeah, Like, I think the consumers became very

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Speaker 9: aware of this incentive. If you went to any online

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Speaker 9: search website, you saw that, you know, the tax credit

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Speaker 9: was there, it was winding down, And I think definitely

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Speaker 9: this sense of urgency created consumer reaction, and we're seeing

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Speaker 9: that in the data. The numbers are still coming in

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Speaker 9: for September in the US, but definitely going to be

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Speaker 9: a record quarter and you know, highest market share to date.

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Speaker 3: Go There's so many things that I want to poke

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Speaker 3: around at. Like what sources inside Tesla told me in

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Speaker 3: recent weeks was like, hey, have you been noticing the

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Speaker 3: advertising we've been doing on YouTube and Instagram, something that

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Speaker 3: Elon Musk historically is completely against. But I'm also like,

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Speaker 3: almost five hundred thousand vehicles in the quarter. Do you

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Speaker 3: see that as just being a one time thing like

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Speaker 3: would this be replicated because it has to if he's

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Speaker 3: going to deliver twenty million vehicles over a ten year period.

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Speaker 3: That's the math five hundred thousand a quarter.

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Speaker 9: Yeah, I think it's going to be challenging, right because

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Speaker 9: I think just I think a lot of consumers that

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Speaker 9: were considering buying a vehicle EV specifically pulled ahead bought

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Speaker 9: it in Q three because of the incentives, and so

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Speaker 9: I think just we're going to see that slowdown coming

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Speaker 9: Q four and we'll start to see the market stabilize.

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Speaker 9: What's that natural demand for evs? And I think it's

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Speaker 9: going to be dependent on for Tesla, right once again

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Speaker 9: having some product, new product that's going to resonate with consumers.

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Speaker 9: And then I think the other challenge for Tesla is

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Speaker 9: navigating the changes in the regulatary policy. You know that

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Speaker 9: revenue that've gotten from carbon credit will soon disappear, and

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Speaker 9: so how do they navigate that? And once again, I

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Speaker 9: think they do have some opportunities with energy storage. They

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Speaker 9: have their AI ROBOTAXI, so they have stuff in play,

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Speaker 9: but it's navigating the short term when demand goes down

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Speaker 9: and have I not the product available, new product that

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Speaker 9: resonates with customers.

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Speaker 4: It's definite go global because we can with you. And

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Speaker 4: what's so interesting is while the EV market is getting

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Speaker 4: smaller here in the US as a policy, China is

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Speaker 4: going up into the right. Europe it's expanding. But Tesla's

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Speaker 4: foothold has not been Can they turn that around?

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Speaker 9: I think they can if they continue. I mean the

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Speaker 9: model why. I think the sixth three row or the

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Speaker 9: sixty model why is really doing well in China now.

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Speaker 9: I think if they continue to, you know, once again

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Speaker 9: have new product. But I think the Chinese OEMs, you

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Speaker 9: have voids shell me that are really gaining market share,

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Speaker 9: and I think Tesla has stiff competition. So I think

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Speaker 9: it's going to come down to having product and being

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Speaker 9: able to resonate that with the consumer.

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Speaker 2: There definitely.

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Speaker 3: Voudez Tred, director of Industry in Sitess Auto Motive, we

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Speaker 3: really appreciate having you.

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Speaker 2: On the show. CARO like check me on this.

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Speaker 3: When we spoke to Robin Denholms, she was crystal clear

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Speaker 3: like the twenty million EV sales targets there for a

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Speaker 3: reason I went onto the Tesla I our website. All

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Speaker 3: of their factories around the world are capable of building

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Speaker 3: two million vehicles a year, so he's going to have

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Speaker 3: to hit five hundred thousand every quarter.

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Speaker 2: Like, am I understanding that? Right?

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Speaker 4: Delivery is what I'm interested? Is production pulled back a

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Speaker 4: bit as well? And tell us is that about the

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Speaker 4: change in the way that they're moving to different vehicles

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Speaker 4: and they thinks about increasing improving model wise and model threes.

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Speaker 3: The data not in this press release on quarterly deliveries

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Speaker 3: is inventory and inventory days and you know, look at that.

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Speaker 3: Actually you can you can kind of work out using

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Speaker 3: satellite imagery how many vehicles are really hot on a

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Speaker 3: lot exactly. But yeah, and then the sheer reaction is

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Speaker 3: kind of weird, right, you know. I guess people are

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Speaker 3: saying this was a one time thing because of the

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Speaker 3: tax credit.

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Speaker 4: And the shares have done rather well. We maybe have

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Speaker 4: a little bit of a profit taking moment. It's time

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Speaker 4: now for talking tech and first up AI language platform

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Speaker 4: deep l It is said to be exploring in potential

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Speaker 4: us ipo now. According to sources, the Google Translate rival

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Speaker 4: based in Europe, has held preliminary discussions with advisors on

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Speaker 4: the listing. The possibility of share sales taking place as

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Speaker 4: soon as next year. Plus a notorious ransomware group have

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Speaker 4: claimed to install in data from a suite of Oracle apps.

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Speaker 10: Now.

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Speaker 4: The hackers claimed to have reached Oracle's e business suite,

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Speaker 4: giving them access to finances, supply chains, and customer relationships.

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Speaker 4: In one case, the group has demanded a ransom after

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Speaker 4: fifty million dollars and then Musk and X they have

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Speaker 4: settled with three former senior Twitter executives who said that

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Speaker 4: they were wrongly denied fifty three million dollars worth in

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Speaker 4: severance after the takeover. Now the deal comes six weeks

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Speaker 4: after Musk and X moved to settle a separate class

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Speaker 4: action alleging six thousand laid off workers will own as

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Speaker 4: much as five hundred million dollars at least in severance

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Speaker 4: ed okay.

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Speaker 3: Coming up on the program, Microsoft copes with data center

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Speaker 3: shortages through a thirty three billion dollar deal with Nebus Group.

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Speaker 3: The idea is that if you can't do it with

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Speaker 3: your own gear looked. The Neo Cloud stock down one

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Speaker 3: point six percent in the market. Nebuus is up higher.

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Speaker 3: But there's also a bigger picture story at play in

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Speaker 3: the market today about how optimistic or not we are

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Speaker 3: about AI. This is Bloomberg Tech. Welcome back to Bloomberg Tech.

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Speaker 3: I'm going to take another look at Tesla. Look, we're

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Speaker 3: down when the numbers hit in pre market. We were

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Speaker 3: up significantly almost five hundred thousand vehicles delivered in the

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Speaker 3: third quarter. But it's a one time anomaly and it's

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Speaker 3: driven by consumers, particularly in the United States, flocking to

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Speaker 3: Tesla vehicles because of the expiring of a federal tax credit.

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Speaker 3: It's also stocked that was up twelve percent year to date,

437
00:22:43,400 --> 00:22:45,960
Speaker 3: had a sort of a rebound from April lows, and

438
00:22:46,000 --> 00:22:48,160
Speaker 3: maybe there's a bit of pulling back here. I don't

439
00:22:48,200 --> 00:22:50,879
Speaker 3: really know, but the consensus seems to be this was

440
00:22:50,880 --> 00:22:52,960
Speaker 3: a one time deal and what was a record corder

441
00:22:53,040 --> 00:22:55,320
Speaker 3: for deliveries, and the future isn't even about.

442
00:22:55,040 --> 00:22:57,000
Speaker 2: Cars, is it. I'm also looking at Microsoft.

443
00:22:57,080 --> 00:22:59,960
Speaker 3: This is kind of interesting because there's some newsflow about Microsoft.

444
00:23:00,000 --> 00:23:02,320
Speaker 3: We're about to get to it, but the early part

445
00:23:02,320 --> 00:23:05,800
Speaker 3: of trading in the session was actually about open AI's

446
00:23:05,880 --> 00:23:09,399
Speaker 3: valuation five hundred billion dollars per Bloomberg reporting in a

447
00:23:09,440 --> 00:23:12,679
Speaker 3: secondary and the simple logic that it's a signal of

448
00:23:12,720 --> 00:23:15,560
Speaker 3: optimism for AI broadly, and it carries a lot of

449
00:23:15,600 --> 00:23:18,080
Speaker 3: names with it, we're now down one point six percent Carroc.

450
00:23:18,440 --> 00:23:20,680
Speaker 3: There's also the neocloud deals and.

451
00:23:20,640 --> 00:23:22,720
Speaker 4: We've got to dig into that because it's a fascinating

452
00:23:22,760 --> 00:23:26,200
Speaker 4: perspective of just the rampant demand for AI compute right

453
00:23:26,240 --> 00:23:29,000
Speaker 4: now across the world. And to break that the story down,

454
00:23:29,000 --> 00:23:32,160
Speaker 4: it's Bloomberg's Brodie Ford who is articulated and found out

455
00:23:32,800 --> 00:23:35,800
Speaker 4: that basically there's been thirty three billion dollars spent by

456
00:23:35,960 --> 00:23:40,720
Speaker 4: Microsoft on neo clouds. You're talking European players like n Scale, Nebeus.

457
00:23:40,720 --> 00:23:44,160
Speaker 4: There's also local player core Weave. Why would the AI

458
00:23:44,280 --> 00:23:48,960
Speaker 4: data center like render outer of that we all know

459
00:23:49,040 --> 00:23:50,719
Speaker 4: for asu're be turning to others.

460
00:23:51,080 --> 00:23:52,840
Speaker 10: Yeah, it's kind of funky, right, It's like if I

461
00:23:52,880 --> 00:23:54,920
Speaker 10: was paying somebody to write stories and I was still

462
00:23:54,960 --> 00:23:58,760
Speaker 10: writing stories. I mean, it's like, essentially, because we have

463
00:23:58,920 --> 00:24:02,640
Speaker 10: huge capacity strains, right, Microsoft needs to get as many

464
00:24:02,720 --> 00:24:06,440
Speaker 10: chips online as it can, both for its customers itself

465
00:24:06,640 --> 00:24:09,560
Speaker 10: and open AI, and it's needing to kind of pull

466
00:24:09,600 --> 00:24:12,200
Speaker 10: every single lever it can, and so it's emerged as

467
00:24:12,240 --> 00:24:14,800
Speaker 10: a major customer for all of these names like the

468
00:24:14,800 --> 00:24:17,879
Speaker 10: core weaves and the nebuuses which have become you know,

469
00:24:18,080 --> 00:24:19,760
Speaker 10: very newsy in recent months.

470
00:24:20,440 --> 00:24:24,000
Speaker 3: It's like managing assets, right, and you know the point

471
00:24:24,040 --> 00:24:27,600
Speaker 3: of a neocloud is it's dedicated to AI, either training

472
00:24:27,680 --> 00:24:31,040
Speaker 3: or influence and you know storage running other software.

473
00:24:31,160 --> 00:24:32,120
Speaker 2: You know, that's a different thing.

474
00:24:32,359 --> 00:24:34,760
Speaker 3: Talls me about the figure of thirty three billion dollars though, like,

475
00:24:34,880 --> 00:24:37,160
Speaker 3: is that news? Is it something that we were able

476
00:24:37,160 --> 00:24:40,280
Speaker 3: to work out? Because Microsoft doesn't disclose it in like

477
00:24:40,359 --> 00:24:41,800
Speaker 3: quarterly earnings or something like that.

478
00:24:41,920 --> 00:24:45,040
Speaker 10: So Microsoft has just kind of disclosed it in piecemeal ways,

479
00:24:45,160 --> 00:24:47,560
Speaker 10: and likely it is going to be much higher than

480
00:24:47,560 --> 00:24:50,560
Speaker 10: that thirty three. What we have been able to discover

481
00:24:50,800 --> 00:24:53,760
Speaker 10: is what this capacity is actually being used for. And

482
00:24:53,840 --> 00:24:56,600
Speaker 10: in many cases it's for Microsoft to build their own

483
00:24:56,680 --> 00:25:00,600
Speaker 10: AI models. And that's surprising because it's there's a larger

484
00:25:00,600 --> 00:25:03,640
Speaker 10: amount of investment in their own internal AI teams than

485
00:25:03,680 --> 00:25:07,080
Speaker 10: many had realized. And the points to them saying, man,

486
00:25:07,119 --> 00:25:09,800
Speaker 10: we better catch up with the open eyes and anthropics

487
00:25:09,800 --> 00:25:11,639
Speaker 10: and have our own models on hand, and we're going

488
00:25:11,640 --> 00:25:13,000
Speaker 10: to use the neo clouds to do it.

489
00:25:13,040 --> 00:25:15,800
Speaker 4: And Mostphah Sulliman, who came from deep Mind, went to

490
00:25:15,840 --> 00:25:20,000
Speaker 4: Microsoft with an inflection being bought in this rather odd way.

491
00:25:20,359 --> 00:25:23,480
Speaker 4: He's the man behind the consumer AI offering. He's I mean,

492
00:25:23,520 --> 00:25:26,200
Speaker 4: you've found out that basically the first larger language model

493
00:25:26,240 --> 00:25:29,760
Speaker 4: they're building internally under him been using care Weave's assets

494
00:25:29,800 --> 00:25:30,640
Speaker 4: over in Oregon.

495
00:25:30,680 --> 00:25:32,960
Speaker 3: I think it is, which is another way of saying

496
00:25:33,000 --> 00:25:35,160
Speaker 3: that're using Nvidia Gear to do it.

497
00:25:35,280 --> 00:25:39,600
Speaker 4: Yeah, using basically via core Weave. But also what's interesting

498
00:25:39,680 --> 00:25:42,920
Speaker 4: is the numbers that you have to orientate yourself around,

499
00:25:42,960 --> 00:25:45,800
Speaker 4: because basically it allows Amy Hood not to have to

500
00:25:45,800 --> 00:25:46,920
Speaker 4: write this all as KPEX.

501
00:25:47,280 --> 00:25:49,600
Speaker 10: That's a really important point, right If you buy a

502
00:25:49,640 --> 00:25:53,040
Speaker 10: bunch of servers, now you have to appreciate them. Now

503
00:25:53,080 --> 00:25:56,720
Speaker 10: it's on your capital expenditures, not you're operating, and investors

504
00:25:56,760 --> 00:25:58,760
Speaker 10: want to see a good balance there. And you know,

505
00:25:58,840 --> 00:26:01,800
Speaker 10: Microsoft's then able to one's surrending from neal clouds to

506
00:26:01,880 --> 00:26:04,840
Speaker 10: say if in five years we actually don't really need

507
00:26:04,880 --> 00:26:07,800
Speaker 10: that many GB three hundreds, would rather use more Vera Rubins,

508
00:26:08,480 --> 00:26:10,359
Speaker 10: bye bye, We don't need a deal with all these

509
00:26:10,400 --> 00:26:13,040
Speaker 10: servers or you don't have necessarily a use for That's

510
00:26:13,080 --> 00:26:14,600
Speaker 10: what it allows them to do.

511
00:26:14,880 --> 00:26:19,000
Speaker 3: Potentially, Brody thrown around your GB three hundreds if there

512
00:26:18,840 --> 00:26:21,760
Speaker 3: are rubebins appreciate the reforming.

513
00:26:21,440 --> 00:26:23,600
Speaker 4: At has he bench pressed them, though that is a

514
00:26:23,720 --> 00:26:24,760
Speaker 4: question for.

515
00:26:24,760 --> 00:26:28,000
Speaker 3: Those uninitiated in video. Once, let me pick up an

516
00:26:28,160 --> 00:26:30,560
Speaker 3: h A DGX, which is an eighty pound We'll get

517
00:26:30,560 --> 00:26:33,160
Speaker 3: to it another time. Let's talk about the investor perspective

518
00:26:33,160 --> 00:26:36,560
Speaker 3: of Brian Kirshman, GQG Partner's portfolio manager joins us Now.

519
00:26:36,680 --> 00:26:41,720
Speaker 3: Gkg's portfolios have recently turned significantly underweight Tech on concerns

520
00:26:42,119 --> 00:26:45,600
Speaker 3: of deteriorating fundamentals, and a part of what Brody was discussing, right.

521
00:26:45,640 --> 00:26:48,120
Speaker 3: I know that we can talk about Microsoft here because

522
00:26:48,119 --> 00:26:51,719
Speaker 3: there's some exposure in the funds, but the idea that

523
00:26:51,760 --> 00:26:54,080
Speaker 3: you rely on the neo clouds so it doesn't show

524
00:26:54,160 --> 00:26:56,760
Speaker 3: up on the balance sheet in the capex. What was

525
00:26:56,800 --> 00:26:58,520
Speaker 3: your sort of reaction to hearing that?

526
00:27:00,160 --> 00:27:02,440
Speaker 11: So, I think what it speaks to from a Microsoft

527
00:27:02,480 --> 00:27:05,760
Speaker 11: perspective is sort of that Capex sort of notion where

528
00:27:05,840 --> 00:27:08,280
Speaker 11: you don't necessarily want to spend all of your capacs

529
00:27:08,320 --> 00:27:10,880
Speaker 11: on sort of an asset that could depreciator. It may

530
00:27:11,000 --> 00:27:12,960
Speaker 11: not necessarily be as advantageous for you on a go

531
00:27:13,000 --> 00:27:15,080
Speaker 11: forward basis. There's a lot of things that are evolving

532
00:27:15,560 --> 00:27:18,840
Speaker 11: really quickly when it comes down to these things, but

533
00:27:18,880 --> 00:27:20,520
Speaker 11: if I were to take a step back and you

534
00:27:20,560 --> 00:27:22,680
Speaker 11: had mentioned sort of we've become a little bit more

535
00:27:22,960 --> 00:27:26,640
Speaker 11: as cautious, so to speak, on sort of these names

536
00:27:26,640 --> 00:27:29,000
Speaker 11: in general and from an AI perspective, And I think

537
00:27:29,000 --> 00:27:30,920
Speaker 11: one of the reasons for that is there's been a

538
00:27:31,000 --> 00:27:33,080
Speaker 11: whole lot of spending on the capack side of things,

539
00:27:33,119 --> 00:27:35,600
Speaker 11: six hundred billion dollars in spending in CAPEX, and really,

540
00:27:35,600 --> 00:27:37,960
Speaker 11: if you take out the infrastructure spending side of this,

541
00:27:38,320 --> 00:27:40,639
Speaker 11: there's only been about thirty billion dollars in revenue that

542
00:27:40,640 --> 00:27:43,520
Speaker 11: have been generated off of this. So our issue here

543
00:27:43,640 --> 00:27:45,359
Speaker 11: is that there is a lack of headroom sort of

544
00:27:45,440 --> 00:27:47,640
Speaker 11: returns that are coming through on a lot of these

545
00:27:47,640 --> 00:27:50,119
Speaker 11: types of businesses over the course of time. Now, Microsoft,

546
00:27:50,160 --> 00:27:52,920
Speaker 11: to its credit, has a software business. They have sort

547
00:27:52,920 --> 00:27:54,720
Speaker 11: of steady earnings. They have been able to deliver some

548
00:27:54,880 --> 00:27:57,280
Speaker 11: decent results over the course of time, But we are

549
00:27:57,320 --> 00:27:59,600
Speaker 11: becoming more skeptical about sort of a lot of things

550
00:27:59,640 --> 00:28:02,200
Speaker 11: on the A side where these returns coming from you,

551
00:28:02,359 --> 00:28:03,480
Speaker 11: the open AI in particular.

552
00:28:03,560 --> 00:28:05,600
Speaker 4: Yeah, I'm sorry, I mean, Brian, we're looking at a

553
00:28:05,640 --> 00:28:08,359
Speaker 4: note that your team put out September the eleventh. You

554
00:28:08,440 --> 00:28:11,240
Speaker 4: rang that alarm bell basically saying, we believe that the

555
00:28:11,240 --> 00:28:15,280
Speaker 4: sector has a significant inflection point and everyone's making a

556
00:28:15,280 --> 00:28:17,680
Speaker 4: one way better as you see it on ai Mania,

557
00:28:18,320 --> 00:28:21,280
Speaker 4: and they're ignoring the alarming fundamentals. For you, the alarming

558
00:28:21,320 --> 00:28:24,520
Speaker 4: fundamentals are that there is a lack of revenue today,

559
00:28:24,680 --> 00:28:27,239
Speaker 4: is it not? Therefore, can you not just make that

560
00:28:27,240 --> 00:28:30,760
Speaker 4: bet that eventually open ai will make three hundred billion

561
00:28:30,840 --> 00:28:33,480
Speaker 4: dollars worth in revenue by twenty thirty. That vindicates the

562
00:28:33,480 --> 00:28:35,480
Speaker 4: amount that they have to spend on all this compute.

563
00:28:36,040 --> 00:28:38,160
Speaker 11: So I think it becomes hard because if you actually

564
00:28:38,200 --> 00:28:40,680
Speaker 11: look at the data behind the set, look at open ai,

565
00:28:40,800 --> 00:28:42,920
Speaker 11: and they have about a two percent conversion rate in

566
00:28:43,040 --> 00:28:45,080
Speaker 11: terms of people that actually want to pay for the service.

567
00:28:45,160 --> 00:28:47,440
Speaker 11: That means ninety eight percent of people that use open

568
00:28:47,480 --> 00:28:50,200
Speaker 11: ai aren't actually paying for it. So now they have

569
00:28:50,280 --> 00:28:53,680
Speaker 11: seven hundred million users globally, about half of those are

570
00:28:53,680 --> 00:28:56,280
Speaker 11: coming from the emerging markets. And what's interesting there if

571
00:28:56,320 --> 00:28:58,800
Speaker 11: you think about the unit economics of sort of cloud

572
00:28:59,120 --> 00:29:01,280
Speaker 11: and I'm sorry, sort of the ai sort of side

573
00:29:01,320 --> 00:29:04,920
Speaker 11: of things, is that this isn't like SaaS. So this

574
00:29:04,960 --> 00:29:07,360
Speaker 11: isn't like a CRM business where you add additional users

575
00:29:07,360 --> 00:29:09,240
Speaker 11: and it all sort of that revenue drops to the

576
00:29:09,240 --> 00:29:11,800
Speaker 11: bottom line. There is a high cost to compute that

577
00:29:11,800 --> 00:29:13,840
Speaker 11: comes along with this, So you need to generate some

578
00:29:13,880 --> 00:29:16,520
Speaker 11: sort of revenues off of each one of these users. Now,

579
00:29:16,560 --> 00:29:19,760
Speaker 11: with half of that user base coming from the emerging markets,

580
00:29:19,760 --> 00:29:22,880
Speaker 11: a significant chunk coming from India. For example, if I

581
00:29:22,880 --> 00:29:26,120
Speaker 11: can get a five G telephone plan within India for

582
00:29:26,240 --> 00:29:28,040
Speaker 11: less than ten dollars a month, do I really think

583
00:29:28,080 --> 00:29:30,000
Speaker 11: that folks are going to pay twenty dollars a month

584
00:29:30,040 --> 00:29:32,080
Speaker 11: for a subscription to chagbt?

585
00:29:32,240 --> 00:29:33,040
Speaker 2: Okay, here we go.

586
00:29:33,200 --> 00:29:35,440
Speaker 3: I like this because we're I think we're looking at

587
00:29:35,440 --> 00:29:38,320
Speaker 3: the same data sets. So the top story today is

588
00:29:38,400 --> 00:29:41,120
Speaker 3: open ai being valued at five hundred billion dollars on

589
00:29:41,400 --> 00:29:45,480
Speaker 3: the latest secondary round. But the big question here is

590
00:29:45,480 --> 00:29:48,800
Speaker 3: is where the future for open ai lays on subscriptions

591
00:29:48,880 --> 00:29:51,280
Speaker 3: or on enterprise. The data point that I look at

592
00:29:51,360 --> 00:29:52,880
Speaker 3: is that it has a user base. You know, it's

593
00:29:52,920 --> 00:29:55,520
Speaker 3: like seven hundred million a monthly, right, Caro, how much

594
00:29:55,560 --> 00:29:59,640
Speaker 3: of that user base is free and then converted to

595
00:29:59,680 --> 00:30:02,200
Speaker 3: being a paying subscribe Because that kind of answers all

596
00:30:02,200 --> 00:30:02,920
Speaker 3: your questions.

597
00:30:03,960 --> 00:30:06,320
Speaker 11: Yeah, So that's exactly the stat that I was referring

598
00:30:06,360 --> 00:30:08,680
Speaker 11: to from what we've seen, only about two percent of

599
00:30:08,720 --> 00:30:12,520
Speaker 11: those folks actually convert over to being paying users, which

600
00:30:12,560 --> 00:30:15,560
Speaker 11: means two percent yes, And so that means that ninety

601
00:30:15,600 --> 00:30:17,560
Speaker 11: eight percent of folks that are using this actually don't

602
00:30:17,600 --> 00:30:21,280
Speaker 11: find enough value to actually sort of spend money on this. Now,

603
00:30:21,320 --> 00:30:23,040
Speaker 11: going back to that India data point that I was

604
00:30:23,080 --> 00:30:25,760
Speaker 11: referencing earlier, if you think about those folks and you

605
00:30:25,840 --> 00:30:27,840
Speaker 11: need to sort of charge call it twenty dollars a

606
00:30:27,840 --> 00:30:30,320
Speaker 11: month for some sort of subscription to make this break

607
00:30:30,360 --> 00:30:34,200
Speaker 11: even profitability or even come close to that. In India,

608
00:30:34,440 --> 00:30:36,440
Speaker 11: you have you know, Barthi Airtel that has a deal

609
00:30:36,440 --> 00:30:39,600
Speaker 11: with Perplexity that offers this service for free across parties.

610
00:30:40,000 --> 00:30:42,600
Speaker 11: So it becomes really hard to see where the monetization

611
00:30:42,800 --> 00:30:45,120
Speaker 11: path comes on a lot of these things over the

612
00:30:45,120 --> 00:30:47,320
Speaker 11: course of time. Now, the other side of this is

613
00:30:47,360 --> 00:30:50,040
Speaker 11: on the enterprise side. So a lot of people say, okay, well,

614
00:30:50,040 --> 00:30:52,200
Speaker 11: maybe it's more of a B to B sales. And

615
00:30:52,240 --> 00:30:54,240
Speaker 11: there's a lot of things that people are investigating or

616
00:30:54,280 --> 00:30:56,280
Speaker 11: looking at from the enterprise side in terms of I

617
00:30:56,280 --> 00:31:00,600
Speaker 11: can use AI to get efficiencies and things like that study.

618
00:31:00,680 --> 00:31:02,880
Speaker 11: I think we all know that by now being quoted

619
00:31:02,920 --> 00:31:04,840
Speaker 11: in terms of the lack of sort of effectiveness, and

620
00:31:04,880 --> 00:31:07,720
Speaker 11: a lot of those We've talked to other tech consultants recently.

621
00:31:07,800 --> 00:31:10,200
Speaker 11: In fact, one one of the big three consultant firms,

622
00:31:10,480 --> 00:31:12,680
Speaker 11: so that eighty five percent of the projects that they're

623
00:31:12,720 --> 00:31:15,120
Speaker 11: working on, so the four hundred projects they've been done

624
00:31:15,160 --> 00:31:16,840
Speaker 11: on a year to day basis, eighty five percent of

625
00:31:16,880 --> 00:31:18,800
Speaker 11: those projects were absolutely useless.

626
00:31:18,800 --> 00:31:21,160
Speaker 5: I said, fifteen percent generates some sort of benefit.

627
00:31:21,320 --> 00:31:25,600
Speaker 4: You're literally sort of echoing exactly the conversation that we

628
00:31:25,760 --> 00:31:30,640
Speaker 4: had with Synthesia's CEO founder yesterday, saying basically, only about

629
00:31:30,640 --> 00:31:33,360
Speaker 4: fifteen percent or even vainly working, and only five percent

630
00:31:33,400 --> 00:31:36,840
Speaker 4: actually working well. But Brian, can you not think that

631
00:31:37,000 --> 00:31:40,520
Speaker 4: eventually they will work? And that's actually more to implementation

632
00:31:40,680 --> 00:31:44,400
Speaker 4: issues rather than actually the fact that they're not adding value.

633
00:31:45,440 --> 00:31:47,440
Speaker 11: So I think you have to show me sort of

634
00:31:47,480 --> 00:31:50,240
Speaker 11: the math and the monetization and then the pathway for

635
00:31:50,280 --> 00:31:53,040
Speaker 11: that working. There's a lot of data organization that needs

636
00:31:53,040 --> 00:31:54,680
Speaker 11: to happen. There's a lot of things that need to

637
00:31:54,680 --> 00:31:57,040
Speaker 11: happen to get to that point. And what we're seeing

638
00:31:57,040 --> 00:31:59,120
Speaker 11: in terms of large language models is we're kind of

639
00:31:59,120 --> 00:32:01,360
Speaker 11: peeking out in terms of what the capabilities are, and

640
00:32:01,480 --> 00:32:04,160
Speaker 11: you saw that sort of transitioning from GPT four to

641
00:32:04,240 --> 00:32:08,280
Speaker 11: GPT five. It's not simply you throw more compute at

642
00:32:08,320 --> 00:32:10,920
Speaker 11: the problem and you solve bigger and more complex large

643
00:32:11,000 --> 00:32:13,720
Speaker 11: language models. There's more post training types of things that

644
00:32:13,760 --> 00:32:15,640
Speaker 11: are coming through, and you're seeing that the models are

645
00:32:15,680 --> 00:32:18,400
Speaker 11: actually peeking out in terms of their effectiveness. And at

646
00:32:18,440 --> 00:32:22,000
Speaker 11: the end of the day, these are extrapolators, so you're

647
00:32:22,080 --> 00:32:23,960
Speaker 11: guessing what the next letter is, what the next word

648
00:32:24,040 --> 00:32:26,240
Speaker 11: is based on a large training set. I can't think

649
00:32:26,320 --> 00:32:28,440
Speaker 11: for you, and it can't sort of, you know, make

650
00:32:28,480 --> 00:32:30,680
Speaker 11: those decisions for you. And I think you're starting to

651
00:32:30,680 --> 00:32:33,000
Speaker 11: see that within the enterprise side of things. Now to

652
00:32:33,040 --> 00:32:36,320
Speaker 11: pivot to an even bigger question here is where has

653
00:32:36,400 --> 00:32:39,440
Speaker 11: this spending actually come through and where are we actually

654
00:32:39,440 --> 00:32:41,800
Speaker 11: seeing the money spent. And that is actually more on

655
00:32:41,840 --> 00:32:44,680
Speaker 11: the hyperscaler side of things, so actually providing the cloud

656
00:32:44,760 --> 00:32:47,880
Speaker 11: services where the data is coming through and where you're

657
00:32:47,880 --> 00:32:50,000
Speaker 11: paying for it on the cloud side of things, and

658
00:32:50,040 --> 00:32:51,760
Speaker 11: this is also fairly concerned.

659
00:32:51,840 --> 00:32:54,160
Speaker 3: I'm sorry to jump in because we'll run out of time.

660
00:32:54,440 --> 00:32:57,280
Speaker 3: That linked to that, including the top line growth discussion,

661
00:32:57,520 --> 00:33:00,960
Speaker 3: what we've asked private Market and public MARKETATIST Week is

662
00:33:01,000 --> 00:33:03,840
Speaker 3: their assessment of the role debt is playing in all

663
00:33:03,880 --> 00:33:06,920
Speaker 3: of these infrastructure projects and how worried or not one

664
00:33:06,960 --> 00:33:07,920
Speaker 3: should be about that.

665
00:33:09,360 --> 00:33:10,920
Speaker 5: Yeah, so debt or nodebt.

666
00:33:11,480 --> 00:33:13,120
Speaker 11: One of the points that I was trying to make

667
00:33:13,160 --> 00:33:15,840
Speaker 11: earlier was that if you look at the pricing dynamics

668
00:33:15,840 --> 00:33:18,600
Speaker 11: within cloud, they're coming under a lot of pressure and

669
00:33:18,640 --> 00:33:21,120
Speaker 11: there's a lot of increased competition that's coming through, and

670
00:33:21,120 --> 00:33:23,040
Speaker 11: I think that's where we're really struggling on a lot

671
00:33:23,040 --> 00:33:25,440
Speaker 11: of these things. Or you have Oracle coming in and

672
00:33:25,600 --> 00:33:28,840
Speaker 11: undercutting price by forty to seventy percent on a lot

673
00:33:28,880 --> 00:33:31,680
Speaker 11: of these enterprise deals, and you're seeing that dragging down

674
00:33:31,680 --> 00:33:33,440
Speaker 11: in terms of the pricing a lot of across a

675
00:33:33,440 --> 00:33:35,760
Speaker 11: lot of the cloud players, including like an AWS and

676
00:33:35,800 --> 00:33:38,640
Speaker 11: things like that. So it becomes a less profitable venture.

677
00:33:39,240 --> 00:33:41,760
Speaker 11: The switching costs are becoming a little bit lower, and

678
00:33:41,960 --> 00:33:44,440
Speaker 11: the economics aren't quite as good. It's becoming more commoditized,

679
00:33:44,480 --> 00:33:46,400
Speaker 11: and that's where we really struggle because there's a whole

680
00:33:46,440 --> 00:33:49,000
Speaker 11: host of investments that's happening in this area and it's

681
00:33:49,040 --> 00:33:52,160
Speaker 11: becoming increasingly commoditized. Similar to the fiber build out, so

682
00:33:52,200 --> 00:33:55,120
Speaker 11: to speak back in the dot com boom and bus cycle.

683
00:33:55,000 --> 00:33:59,440
Speaker 4: The commoditized element of concern, What about the circularity argument

684
00:33:59,600 --> 00:34:02,040
Speaker 4: that we can and that feeds into the debt question

685
00:34:02,120 --> 00:34:02,560
Speaker 4: in many.

686
00:34:02,440 --> 00:34:04,440
Speaker 5: Ways absolutely so.

687
00:34:04,480 --> 00:34:06,560
Speaker 11: Then the other question to ask is, if this is

688
00:34:06,600 --> 00:34:09,239
Speaker 11: such a fantastic investment on a go forward basis, why

689
00:34:09,320 --> 00:34:12,840
Speaker 11: do you have participants in the ecosystem that are actually

690
00:34:13,040 --> 00:34:15,440
Speaker 11: funding their customers and then those cash flows are then

691
00:34:15,440 --> 00:34:18,359
Speaker 11: coming back to them. So in a lot of the

692
00:34:18,440 --> 00:34:20,640
Speaker 11: sort of obscure sort of arrangements and deals as well

693
00:34:20,680 --> 00:34:24,239
Speaker 11: in terms of special purpose vehicles JV structures, where are

694
00:34:24,280 --> 00:34:26,880
Speaker 11: you putting some of these assets into other sort of

695
00:34:26,880 --> 00:34:29,759
Speaker 11: places where you can depreciate the debt or you can

696
00:34:29,800 --> 00:34:32,880
Speaker 11: depreciate the assets within those other vehicles and it's not

697
00:34:32,920 --> 00:34:36,560
Speaker 11: sitting directly on your balance sheet. So this tends to

698
00:34:36,600 --> 00:34:38,600
Speaker 11: happen later in a cycle where you start to see

699
00:34:38,640 --> 00:34:41,440
Speaker 11: a little bit more aggressive accounting coming through, and you

700
00:34:41,480 --> 00:34:43,319
Speaker 11: start to see some of these things that are starting

701
00:34:43,320 --> 00:34:45,120
Speaker 11: to become a little bit more obscure. That has us

702
00:34:45,200 --> 00:34:48,080
Speaker 11: concern that we can't see a true sort of trajectory

703
00:34:48,200 --> 00:34:50,000
Speaker 11: where the economics are coming through.

704
00:34:50,920 --> 00:34:52,680
Speaker 5: That's what has this concern right now and.

705
00:34:52,640 --> 00:34:55,000
Speaker 4: Why you've gone under way. Brian Kirshman. Great to have

706
00:34:55,080 --> 00:34:57,759
Speaker 4: you come back soon. GQG Partners, We thank you for

707
00:34:57,800 --> 00:35:00,359
Speaker 4: coming up. Apple hits pauls on read I think it's

708
00:35:00,400 --> 00:35:03,560
Speaker 4: Vision Pro headsets. We discussed the rivalry with Meta as

709
00:35:03,560 --> 00:35:04,520
Speaker 4: a Bloomberg.

710
00:35:04,120 --> 00:35:08,880
Speaker 3: Tech Apple is said to be ditching plans to revap

711
00:35:08,960 --> 00:35:11,799
Speaker 3: its Vision pro headsets. Instead, the iPhone maker is said

712
00:35:11,800 --> 00:35:14,880
Speaker 3: to be looking to fast track and develop smart glasses

713
00:35:15,160 --> 00:35:16,600
Speaker 3: to rival metas ray bands.

714
00:35:16,640 --> 00:35:17,560
Speaker 2: That's the reporting.

715
00:35:17,800 --> 00:35:20,400
Speaker 3: Let's get to the analysis of Apple's entry into the

716
00:35:20,440 --> 00:35:24,720
Speaker 3: smart glass glasses category of anaag Rana Bloomberg Intelligence senior

717
00:35:24,760 --> 00:35:26,799
Speaker 3: tech analysts. They have a lot on their plate right

718
00:35:26,800 --> 00:35:29,879
Speaker 3: now to shift a new generation of handset of smartphone.

719
00:35:30,280 --> 00:35:32,960
Speaker 3: But have you modeled for the idea that they enter

720
00:35:33,000 --> 00:35:36,560
Speaker 3: a new category, the smart glass, away from augmented in VR.

721
00:35:37,840 --> 00:35:40,040
Speaker 12: No, not yet, Danil. We have to see what it is.

722
00:35:40,239 --> 00:35:42,359
Speaker 12: We have to see what kind of potential reception it's

723
00:35:42,400 --> 00:35:45,000
Speaker 12: going to be. I think Meta has a massive lead here,

724
00:35:45,280 --> 00:35:47,359
Speaker 12: so you know, you just can't sign off just because

725
00:35:47,400 --> 00:35:49,399
Speaker 12: it's an Apple product that it's going to do well.

726
00:35:50,040 --> 00:35:52,080
Speaker 12: I think it's going to have to see the details

727
00:35:52,120 --> 00:35:54,560
Speaker 12: and before we start to model any you know, kind

728
00:35:54,560 --> 00:35:55,040
Speaker 12: of shipment.

729
00:35:55,440 --> 00:35:56,760
Speaker 2: Should they be fast tracking?

730
00:35:58,520 --> 00:36:00,399
Speaker 12: I mean it is, but at the end of the day,

731
00:36:00,440 --> 00:36:03,000
Speaker 12: a lot depends on the models that go into it.

732
00:36:03,040 --> 00:36:05,480
Speaker 12: So AI is a very big on device. AI is

733
00:36:05,480 --> 00:36:08,520
Speaker 12: a very big part of any of these edge products,

734
00:36:08,560 --> 00:36:10,879
Speaker 12: and I think, as we know, Apple has to get

735
00:36:10,960 --> 00:36:13,799
Speaker 12: that thing first right before they can move on to

736
00:36:13,920 --> 00:36:14,880
Speaker 12: some of those features.

737
00:36:14,960 --> 00:36:18,719
Speaker 3: Anarag, I've been reading your latest research wait times, inventory

738
00:36:18,880 --> 00:36:20,960
Speaker 3: handsets of the IFN seventeen generation.

739
00:36:21,360 --> 00:36:23,439
Speaker 2: Your conclusion, yeah, I see.

740
00:36:23,440 --> 00:36:25,960
Speaker 12: I think that's a good part is the base model's

741
00:36:26,000 --> 00:36:28,319
Speaker 12: doing very well, the pro is doing very well, but

742
00:36:28,400 --> 00:36:30,720
Speaker 12: iPhone Air is not at all doing well. And frankly,

743
00:36:30,760 --> 00:36:33,960
Speaker 12: that was the one model we thought could get some traction.

744
00:36:34,160 --> 00:36:36,600
Speaker 12: But it seems like the battery life is an issue there.

745
00:36:36,760 --> 00:36:38,920
Speaker 12: And the second piece could be it's not available in

746
00:36:39,040 --> 00:36:41,520
Speaker 12: China right now and that could be another driving factor.

747
00:36:42,040 --> 00:36:45,799
Speaker 4: Must read always Bloomberg Intelligence. Anna Ragrana, thanks so much

748
00:36:45,800 --> 00:36:49,040
Speaker 4: for spending time with us. Meanwhile, Peloton shares, let's talk

749
00:36:49,080 --> 00:36:52,600
Speaker 4: about half they've performed after yesterday. They continued to be

750
00:36:52,640 --> 00:36:55,920
Speaker 4: on the downside after unveiling revamped hardware software along with

751
00:36:56,000 --> 00:36:59,120
Speaker 4: new higher prices for its equipment and subscriptions. We spoke

752
00:36:59,160 --> 00:37:02,440
Speaker 4: with Peter Stern to CEO yesterday about the new features.

753
00:37:03,160 --> 00:37:06,600
Speaker 13: We are focused both on existing members as well as

754
00:37:06,960 --> 00:37:10,280
Speaker 13: non members. For existing members, they're getting so much today.

755
00:37:10,560 --> 00:37:13,719
Speaker 13: We are introducing for everyone, regardless of when you bought

756
00:37:13,719 --> 00:37:16,000
Speaker 13: your equipment, the benefits of peloton Iq, and that's just

757
00:37:16,080 --> 00:37:21,239
Speaker 13: included in your membership. We are now including a new

758
00:37:21,280 --> 00:37:23,920
Speaker 13: acquisition that we did a company called breath Work, because

759
00:37:23,920 --> 00:37:26,279
Speaker 13: we know the power of breathing and how it can

760
00:37:26,320 --> 00:37:29,280
Speaker 13: help people with stress and anxiety and depression and improve

761
00:37:29,280 --> 00:37:33,520
Speaker 13: heart rate variability and improve blood pressure. So everyone's getting that.

762
00:37:34,680 --> 00:37:37,200
Speaker 13: Major partnerships, for example, one with the Hospital for Special

763
00:37:37,239 --> 00:37:40,840
Speaker 13: Surgery to focus on injury prevention and rehabilitation. All of

764
00:37:40,880 --> 00:37:43,640
Speaker 13: these things happen for existing members, but if you're not

765
00:37:43,680 --> 00:37:46,600
Speaker 13: an existing member, there has never been a better time

766
00:37:46,640 --> 00:37:49,600
Speaker 13: to become one. With the launch of this all new

767
00:37:49,600 --> 00:37:53,200
Speaker 13: equipment lineup the Cross Training Series. Now we're delivering the

768
00:37:53,200 --> 00:37:57,480
Speaker 13: benefits of both cardio and strength because we know that

769
00:37:57,520 --> 00:38:00,560
Speaker 13: adults should be doing a couple of hours at a

770
00:38:00,600 --> 00:38:04,040
Speaker 13: week of cardio and two days of strength training every week.

771
00:38:04,200 --> 00:38:06,000
Speaker 13: You can do that now, all with one piece of

772
00:38:06,040 --> 00:38:07,640
Speaker 13: equipment that makes it super easy.

773
00:38:08,239 --> 00:38:11,880
Speaker 4: It's almost in many ways like cross training is the

774
00:38:11,880 --> 00:38:14,120
Speaker 4: way that which you're sort of identifying it. But if

775
00:38:14,160 --> 00:38:15,920
Speaker 4: I look at the analyst notes and maybe the reaction

776
00:38:15,960 --> 00:38:17,080
Speaker 4: from the stock is because a lot.

777
00:38:17,040 --> 00:38:17,880
Speaker 2: Of this have been maked in.

778
00:38:18,040 --> 00:38:20,399
Speaker 4: You've already given us full year forecasts that in many

779
00:38:20,440 --> 00:38:23,760
Speaker 4: way talk about what churn you're expecting, but what subscriber growth,

780
00:38:23,960 --> 00:38:26,080
Speaker 4: what do you think this will spur in terms of support.

781
00:38:26,520 --> 00:38:29,719
Speaker 13: So we knew, of course as we went into this

782
00:38:29,800 --> 00:38:31,279
Speaker 13: year what we were going to be launching, and we

783
00:38:31,280 --> 00:38:33,319
Speaker 13: were able, as you point out, Caroline, to bake all

784
00:38:33,320 --> 00:38:36,520
Speaker 13: of that into our guidance for the year. But we

785
00:38:36,600 --> 00:38:40,080
Speaker 13: also included in our guidance that as the year progresses,

786
00:38:40,400 --> 00:38:43,320
Speaker 13: we will be inflecting back toward growth. And that's a big,

787
00:38:43,560 --> 00:38:47,440
Speaker 13: big step for us as a company. We had a

788
00:38:47,520 --> 00:38:49,520
Speaker 13: couple of years where we've been down as we have

789
00:38:50,880 --> 00:38:53,800
Speaker 13: regrouped after the pandemic, and we are now in such

790
00:38:53,800 --> 00:38:57,200
Speaker 13: a good place where you see us having reignited our

791
00:38:57,280 --> 00:39:01,440
Speaker 13: innovation engine. Of course, our customer love has never left us.

792
00:39:01,760 --> 00:39:06,600
Speaker 13: Customers really just appreciate what Peloton does for them and

793
00:39:06,640 --> 00:39:09,520
Speaker 13: in particular have their deep connection with our instructors. So

794
00:39:09,560 --> 00:39:12,120
Speaker 13: we're building on that foundation and now feel even more

795
00:39:12,120 --> 00:39:13,880
Speaker 13: confident about our future than ever before.

796
00:39:14,800 --> 00:39:17,799
Speaker 3: That was Peloton's CEO Peter Stern speaking to Caro in

797
00:39:17,800 --> 00:39:18,759
Speaker 3: a big conversation.

798
00:39:25,000 --> 00:39:27,760
Speaker 4: Who will be the next CEO of Disney? The searches

799
00:39:27,760 --> 00:39:29,520
Speaker 4: on and right now the board has focused on four

800
00:39:29,560 --> 00:39:34,759
Speaker 4: internal candidates, including Josh Damarrow, Banna Walden, Alan Bergman, and

801
00:39:34,840 --> 00:39:37,440
Speaker 4: Jimmy and Pataro. Now this is the company is getting

802
00:39:37,480 --> 00:39:39,680
Speaker 4: ready to name a new CEO early next year, but

803
00:39:40,239 --> 00:39:43,239
Speaker 4: it sounds though conversations are starting to steer towards one

804
00:39:43,280 --> 00:39:48,200
Speaker 4: particular name. Lucas Shaw has the details. Why after Bob Chapek,

805
00:39:48,320 --> 00:39:50,920
Speaker 4: would it be deemed that the person in charge of

806
00:39:51,000 --> 00:39:52,879
Speaker 4: experiences and parks is the right pick?

807
00:39:52,960 --> 00:39:57,320
Speaker 14: Lucas well, Look, it's both about personality and the future

808
00:39:57,360 --> 00:39:59,239
Speaker 14: of Disney. You look at where Disney's putting all of

809
00:39:59,280 --> 00:40:02,040
Speaker 14: its money going forward, it's into that parts and experience.

810
00:40:02,040 --> 00:40:02,560
Speaker 5: This division.

811
00:40:02,640 --> 00:40:04,000
Speaker 2: Most of the capex over the.

812
00:40:03,960 --> 00:40:07,800
Speaker 14: Next decade is going there, whether expanding existing parks or

813
00:40:07,880 --> 00:40:11,200
Speaker 14: building new parks. And Josh is also a very different

814
00:40:11,239 --> 00:40:15,000
Speaker 14: personality than Bob Shapek, right, he seems to have more

815
00:40:15,040 --> 00:40:17,720
Speaker 14: facility with other parts of the business. He frankly looks

816
00:40:17,760 --> 00:40:19,799
Speaker 14: like a Disney CEO, as weird as that may be

817
00:40:19,960 --> 00:40:23,480
Speaker 14: to sound, or as weird as that may sound, And

818
00:40:23,680 --> 00:40:28,080
Speaker 14: he is just seen as very well qualified relative to

819
00:40:28,200 --> 00:40:30,720
Speaker 14: the other candidates in the business and a Disney lifer,

820
00:40:31,520 --> 00:40:34,520
Speaker 14: which matters at a company that has a very distinct culture.

821
00:40:35,239 --> 00:40:37,680
Speaker 3: He was around and hanging out in some valley in

822
00:40:37,760 --> 00:40:41,400
Speaker 3: July saw him. The screen Time team gave a detailed

823
00:40:41,400 --> 00:40:44,399
Speaker 3: report about a breakfast that took place Lucas, I think

824
00:40:44,400 --> 00:40:48,600
Speaker 3: it's worth you explaining to the audience what happened, why

825
00:40:48,640 --> 00:40:49,440
Speaker 3: it's significant.

826
00:40:50,239 --> 00:40:53,759
Speaker 14: Well, Bob Iger, the current CEO of Disney, who's been

827
00:40:53,800 --> 00:40:56,399
Speaker 14: at the company for more than two decades, was having

828
00:40:56,440 --> 00:41:01,040
Speaker 14: breakfast with someone who said what many in Hollywood are

829
00:41:01,120 --> 00:41:03,640
Speaker 14: already thinking and saying, which is Josh is going to

830
00:41:03,640 --> 00:41:06,920
Speaker 14: have the job, and said something positive about how he

831
00:41:06,920 --> 00:41:10,880
Speaker 14: would do in it, and Bob reacted very negatively, insisting

832
00:41:10,960 --> 00:41:14,040
Speaker 14: that the board has not made a decision. And there's

833
00:41:14,040 --> 00:41:17,359
Speaker 14: two important things to know about this. One is that

834
00:41:17,719 --> 00:41:20,360
Speaker 14: Disney is a company. Even though everyone in Hollywood believes

835
00:41:20,600 --> 00:41:23,320
Speaker 14: that Josh is now the clear front runner, the company

836
00:41:23,360 --> 00:41:25,440
Speaker 14: is insisting and has made no decisions, and it's not

837
00:41:25,480 --> 00:41:27,879
Speaker 14: going to make any news about this until early next year.

838
00:41:28,640 --> 00:41:31,440
Speaker 14: The other is that Bob Iger, who has been pretty

839
00:41:31,480 --> 00:41:34,200
Speaker 14: involved in succession the last few times, which have not

840
00:41:34,520 --> 00:41:37,759
Speaker 14: processes that have not gone well, is said to be

841
00:41:37,880 --> 00:41:40,400
Speaker 14: more marginalized this time because the board knows they need

842
00:41:40,480 --> 00:41:41,880
Speaker 14: to get it right, and one way to get it

843
00:41:41,960 --> 00:41:44,760
Speaker 14: right is to not have the current CEO as involved

844
00:41:44,760 --> 00:41:46,560
Speaker 14: as he has been. And so I think this is

845
00:41:46,600 --> 00:41:48,840
Speaker 14: just a source of great frustration for Bob, who doesn't

846
00:41:48,840 --> 00:41:50,479
Speaker 14: want to be seen as a lame duck, but also

847
00:41:50,560 --> 00:41:52,640
Speaker 14: doesn't have as much control over this as he has.

848
00:41:53,760 --> 00:41:56,240
Speaker 4: Briefly, Lucas, I just want to switch Gears to Netflix.

849
00:41:56,239 --> 00:41:58,880
Speaker 4: It's down for four straight days now. There is growing

850
00:41:58,920 --> 00:42:01,799
Speaker 4: anxiety about what happening over an X Andino Musk.

851
00:42:04,480 --> 00:42:07,440
Speaker 14: I mean maybe growing anxiety among a few investors. I

852
00:42:07,480 --> 00:42:10,920
Speaker 14: am not detecting that with my sources at the company,

853
00:42:12,280 --> 00:42:14,040
Speaker 14: most of whom would point out that it's a little

854
00:42:14,080 --> 00:42:16,920
Speaker 14: bit ironic for someone who's been a free speech warrior

855
00:42:17,040 --> 00:42:19,640
Speaker 14: to browbeat them for a television show that was released

856
00:42:19,880 --> 00:42:21,239
Speaker 14: like three to five years ago.

857
00:42:22,080 --> 00:42:24,880
Speaker 3: Bloombergs Lucashaw, who leads the screen time team, Thank you

858
00:42:24,960 --> 00:42:27,959
Speaker 3: so much. That does it for this edition of Bloomberg Tech.

859
00:42:28,280 --> 00:42:32,440
Speaker 3: But screen Time returns next week live from Los Angeles.

860
00:42:32,760 --> 00:42:35,279
Speaker 3: You got a tune in conversations with the best of

861
00:42:35,320 --> 00:42:40,000
Speaker 3: the entertainment industry, including Jimmy Kimmel, Caroline Yeah.

862
00:42:40,400 --> 00:42:42,600
Speaker 4: I cannot wait to go. Cannot wait to hear the

863
00:42:42,600 --> 00:42:45,279
Speaker 4: conversations Lucas is going to conduct to many others do not.

864
00:42:45,360 --> 00:42:48,279
Speaker 4: In the meantime, forget to check out our podcast. Find

865
00:42:48,320 --> 00:42:51,040
Speaker 4: it on the terminal as well as online on Apple, Spotify,

866
00:42:51,280 --> 00:42:54,439
Speaker 4: and iHeart. This is Bloomberg Tech from New York.