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

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

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Speaker 1: and Ed Lovelow in sent Francesco.

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Speaker 2: This is Bloomberg Tech coming up. Spotify added a record

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Speaker 2: number of users last quarter thanks to its end of

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Speaker 2: year wrapped campaign, shares search plus.

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Speaker 3: Paramount enhances its bid for Warner Brothers Discovery, offering billions

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Speaker 3: to cover termination debt, refinancing and ticking fees.

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Speaker 4: Details this hour.

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Speaker 2: And Runway CEO Chris thebau Valezuela joins us to talk

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Speaker 2: about the new funding round that values the company at

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Speaker 2: five point three billion dollars.

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Speaker 3: From private markets to the public market. Look on the benchmarks,

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Speaker 3: nothing that exciting.

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Speaker 4: We're holding on too.

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Speaker 3: Gains just eking out twenty three points in the green

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Speaker 3: and the NASTAQ one hundred. But you go underneath a

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Speaker 3: herd ed and rotation continues. But this time is the

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Speaker 3: hardware that gets sold off.

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Speaker 4: The software is being bought for a third straight day.

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Speaker 3: Software really up about nine percent as we buy back

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Speaker 3: into that beaten up sector. But we're looking also to

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Speaker 3: what the macro picture is painting. We have got retail

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Speaker 3: sales that come in less than have been expected. What

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Speaker 3: does that mean for a FED cut? What does it

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Speaker 3: mean for equities? What does mean for crypto? Because let's

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Speaker 3: face it, that is where the movement's happening today. Bigoin

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Speaker 3: not by one point six percent, look at Eth down

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Speaker 3: almost another five percent. As we still question what's sort

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Speaker 3: of an asset? This really is what are you looking at?

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Speaker 2: I'm looking at Spotify and shares are absolutely surging. A

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Speaker 2: record number of subscribers added last quarter, taking the total

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Speaker 2: to seven hundred and fifty one million dollars. Later in

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Speaker 2: the show, we'll get to it where Bloomberg's actually Carmen.

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Speaker 2: But it was all about the end of year rat

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Speaker 2: and I know as a team we all exchanged our raps.

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Speaker 2: The stock was on track for its best day over

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Speaker 2: up almost twenty percent, now on track for its figures

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Speaker 2: jumping about seven years. But that is a big response

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Speaker 2: to strength when it comes to music streaming.

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Speaker 4: Character It certainly is tell you else's strength. The bond market.

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Speaker 3: We're not looking at shares of Alphabet, but really I

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Speaker 3: want you to focus on its debt because it's bond

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Speaker 3: offerings keep coming and after the US dollar debt sale,

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Speaker 3: raised twenty billion dollars yesterday, it was upsized.

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Speaker 4: The company is now selling over eleven.

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Speaker 3: Billion more in Sterling and Swiss frank denominated bonds. And

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Speaker 3: that's super rare one hundred year note we told you

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Speaker 3: about yesterday while it was oversubscribed and then some almost

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Speaker 3: ten times according to sources. Let's talk about it with

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Speaker 3: Robert Schiffman from Blue Meg Intelligence. In less than twenty

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Speaker 3: four hours, they've raised thirty two billion dollars basically on

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Speaker 3: the debt markets. Let's just focus in on what that

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Speaker 3: one hundred year debt signals about the confidence people have

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Speaker 3: in this company.

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Speaker 5: Well, I think what the bond market is telling us

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Speaker 5: is that AI bubble talks are so twenty twenty five.

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Speaker 5: But the concerns that, at least from the creditors perspective,

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Speaker 5: is not anything near what it is from inequity standpoint.

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Speaker 5: The reality, though, is what is the benefit of a

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Speaker 5: one hundred year bond? To me, it's just a trophy.

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Speaker 5: It's going to be put on the shelf of pension

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Speaker 5: funds and insurance companies. They're going to hold it to maturity.

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Speaker 5: And let me tell you something, if anyone's really worried,

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Speaker 5: if that bond does not pay off in one hundred years.

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Speaker 5: Come and look me up at Bloomberg. I'm going to

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Speaker 5: be upstairs in my office eating free.

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Speaker 6: Snacks, Robert.

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Speaker 2: The macro point is that they're doing interesting things with capital,

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Speaker 2: the bigger picture, to fund CAPEX, right, to grow AI

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Speaker 2: infrastructure at scale. I always read your memo every morning,

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Speaker 2: and you revise constantly the kind of trajectory. What are

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Speaker 2: the latest numbers that you see going over the next decade.

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Speaker 5: Yeah, you know, it sort of becomes monopoly money, the

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Speaker 5: type of spending that we're seeing. I mean, we're now

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Speaker 5: projecting over four trillion dollars of cumulative hyperscaler spend through

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Speaker 5: twenty thirty. You can afford a lot of that from

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Speaker 5: operating cash flow. However, how do you supplement it? You

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Speaker 5: supplement it with really cheap bonds. And the way that

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Speaker 5: you can do that is you start off with balance

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Speaker 5: sheets that are in phenomenal shape. You know, if you

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Speaker 5: look at Alphabet's DOAA plus credit rating, SMP came out

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Speaker 5: yesterday and said in order to breach their downgrade trigger,

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Speaker 5: they would have to issue more than one hundred and

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Speaker 5: eighty billion dollars of incremental net debt. So what I

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Speaker 5: would argue is, hey, if they wanted to be a

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Speaker 5: triple bname, would they have to issue a trillion dollars

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Speaker 5: of bonds? There is so much capacity. Why not take

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Speaker 5: the money down, borrow long dated paper at five and

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Speaker 5: a half five point seven percent, put it to work

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Speaker 5: today and grow your future cash flows for another decade,

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Speaker 5: if not one hundred years.

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Speaker 3: There is some pushback in the market that yes, it's

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Speaker 3: a trophy on a pension fund's desk, maybe it's a

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Speaker 3: trophy on Alphabet's CFO and treasurer's desk if they sell

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Speaker 3: one hundred year bonds, but also signals at the top

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Speaker 3: of the market. Look, we go back to when the

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Speaker 3: last time a tech company did this, it was Motroller

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Speaker 3: back in the nineties, and people are trying to make

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Speaker 3: this serchon that may be Motrola was at the peak

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Speaker 3: of its game then and where is it now? What

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Speaker 3: do you say, so this is a question marks about

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Speaker 3: one hundred a to tech.

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Speaker 5: Yeah, listen, I think you know what's going to be

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Speaker 5: the top. We can never call the top. Let me

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Speaker 5: tell you something though, I think there's more bonds to come.

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Speaker 5: We still have Microsoft, we still have Meta, we still

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Speaker 5: probably have Amazon.

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Speaker 4: But would they do one hundred Yeah, you know what.

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Speaker 5: They might, and they also might do a lot of

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Speaker 5: other incremental currencies like we talked about yesterday. I'm actually

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Speaker 5: surprised they stayed out of the euromarket. I think there's

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Speaker 5: a big, deep demand there is. Every portfolio manager that

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Speaker 5: we are talking to is talking about having excess cash

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Speaker 5: on hand, and everyone is looking at the same compressed yields.

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Speaker 5: There is a bid for a yield. It is not

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Speaker 5: going away anytime soon. So if we hit the top

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Speaker 5: of the market, I don't think it's today. Maybe it's

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Speaker 5: next week, Maybe it's going to be in three weeks,

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Speaker 5: but I don't think it's yet. I listen, I've never

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Speaker 5: been as bullish on tech as I am today. I

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Speaker 5: don't think these companies have ever been better positioned. I

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Speaker 5: don't think their balance sheets have ever been better positioned.

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Speaker 5: And I actually think the confidence levels that we see

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Speaker 5: across the bond market far supersede what I think even

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Speaker 5: Bloomberg News starking belt.

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Speaker 2: Robert Schiffman from Bloomberg Intelligence bonds are fun, thank you

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Speaker 2: very much. The software sector may have a chance to

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Speaker 2: rebound we're so closely tracking what's happening in software right now.

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Speaker 2: According to JP Morgan Strategists, fears of AI disruption may

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Speaker 2: be overblown and the current bearish sentiment is a quote

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Speaker 2: overshoot at this time. That views echoed by Lauren Webster,

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Speaker 2: Managing Director of Investment Banking for Technology at Piper Sandler.

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Speaker 2: She writes, while there is merit that AI will be

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Speaker 2: a death sentence to certain sectors of software, the notion

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Speaker 2: of software's broad obsolescence is overstated.

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Speaker 6: Delighted to say that, she.

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Speaker 2: Joins us, Now, I mean this is a day by

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Speaker 2: day thing. Looking at some of the trading and action

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Speaker 2: in the moment, I see a lot of green in

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Speaker 2: the software space. But I say every day, one market

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Speaker 2: session a market does not make just go a bit

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Speaker 2: deeper on your thesis and why you're a bit more

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Speaker 2: calm here.

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Speaker 7: Absolutely, So, I think where we are is in sort

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Speaker 7: of this phase of forming, storming, norming in the market

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Speaker 7: and the give and take between AI innovation and software stocks,

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Speaker 7: and so you're seeing a lot of volatility disruption each

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Speaker 7: time there is a new product release from an AI innovator.

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Speaker 7: Yet this broader realization that enterprise software is here for good.

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Speaker 7: You can't rip it out tomorrow, and this is a

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Speaker 7: longer term trend. As we figure out how to embed

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Speaker 7: AI into enterprise solutions, what is actually going to be disrupted.

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Speaker 2: We are canvassing a wide and diverse range of views

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Speaker 2: and what's happening in software. Earlier today, we spoke to

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Speaker 2: the Golden and Sax CEO David Solomon.

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Speaker 6: Here's what he thinks.

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Speaker 8: We have software exposure, but I'd say it's insignificant the

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Speaker 8: scale of our overall platform, but it's certainly something that

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Speaker 8: we're monitoring. I think the narrative over the last week

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Speaker 8: has been a little bit too broad and will be

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Speaker 8: as losers and plenty of companies pilot do just find.

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Speaker 6: Sell off too broad.

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Speaker 2: It sounds like you and mister Solomon agree that maybe

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Speaker 2: what we've seen in the last seven to ten days

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Speaker 2: a little overdone.

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Speaker 7: Certainly, with that said, though, I would if I was

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Speaker 7: running a business in the software sector today, I would

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Speaker 7: be taking a hard look, spending time with customers understanding

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Speaker 7: how they're using AI in place of the products that

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Speaker 7: I offer, where I should be embedding it, and certainly

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Speaker 7: planning for the next decade. Will transition towards more AI

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Speaker 7: infrastructure tooling. But yes, as I said, nothing is getting

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Speaker 7: ripped out tomorrow, and this is a much longer transition period.

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Speaker 7: And the good news in that is that it gives

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Speaker 7: software companies time to catch up figure out how they

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Speaker 7: can play this opportunity.

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Speaker 3: Lauren, what data do you look to as to what

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Speaker 3: might be being ripped out? What is a point of

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Speaker 3: offering rather than a platform that's into more deeply within

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Speaker 3: a business.

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Speaker 7: Yeah, certainly looking at those that have been disrupted most

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Speaker 7: by recent product launches from whether it be anthropic or others.

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Speaker 7: Workflow tooling is a place at risk. Certainly, there are

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Speaker 7: elements within the legal sector that some of the newer

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Speaker 7: announcements are starting to displace. There are, however, bright spots

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Speaker 7: like cybersecurities one where I spend a lot of time

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Speaker 7: and certainly you need cybersecurity capabilities to even implement some

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Speaker 7: of that AI enterprise infrastructure. So there will be pockets

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Speaker 7: of opportunity in the software sector, and then certainly in

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Speaker 7: the picks and shovels around AI infrastructure.

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Speaker 3: Go there a little bit more, because that was clearly

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Speaker 3: the read across from some of this capital expenditure spend

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Speaker 3: that we saw last week and now so I mean

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Speaker 3: extraordinary numbers coming from the hyperscalers, and then of course

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Speaker 3: people thought, well, time to be long, energy, time to

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Speaker 3: be long the chips that go inside these data centers.

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Speaker 4: Is that still the right play, feelin.

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Speaker 7: Absolutely?

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Speaker 9: So.

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Speaker 7: The money is not pulling out of the market and

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Speaker 7: sitting on the sidelines. It truly is going into a

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Speaker 7: lot of the infrastructure opportunity what is often called the

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Speaker 7: physical AI play, where it is energy networking. I mean,

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Speaker 7: we're even seeing physical security around data centers getting another lock,

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Speaker 7: and so there's a significant opportunity in that infrastructure and

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Speaker 7: elsewhere that is, you know, irl are in the physical world.

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Speaker 2: What I'm trying to understand is why the story has

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Speaker 2: changed for lots of investors.

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Speaker 6: You know, if you.

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Speaker 2: Think back to when we started closing closely tracking capital expenditures,

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Speaker 2: people wanted to see the software revenues. On the other side,

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Speaker 2: they wanted to see revenue top line growth that directly

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Speaker 2: resulted from AI investment. Right think about the core to

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Speaker 2: gone a name like Salesforce. They posted really good numbers,

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Speaker 2: but the anxiet is still there despite the evidence. It's

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Speaker 2: backward looking that people are willing to pay for.

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Speaker 6: That AI era of software. Why is that?

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Speaker 7: Look, there's a broad realization that you're going to have

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Speaker 7: to invest ahead of ahead of the real realization of

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Speaker 7: the opportunity, the real realization of the profits. And so

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Speaker 7: that's why you're seeing a lot of these hyperscalers poor

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Speaker 7: tremendous capital, hundreds of billions into their capex infrastructure associated

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Speaker 7: with AI. And there will be support for others across

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Speaker 7: the software ecosystem as long as there is also that

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Speaker 7: customer enterprise customer journey narrative going with it as well.

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Speaker 2: Yeah, that enterprise evidence is right is what we're looking for.

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Speaker 2: I can to ask you one of my favorite questions,

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Speaker 2: given with still early in the year, what happens in

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Speaker 2: the rest of twenty twenty six with a software sector.

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Speaker 7: Yeah, I'm going to go back to where I started,

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Speaker 7: which is really this forming norming storming. You have a

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Speaker 7: lot of AI forming right now, and I will tell

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Speaker 7: you we are not we are not at the end

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Speaker 7: of that formation. There are going to be gives and takes,

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Speaker 7: and then that's storming with traditional software. The winner there

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Speaker 7: is going to be those that are really spending time

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Speaker 7: understanding the evolution of their technology with their customers and

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Speaker 7: how those customers are applying AI to their solutions, and

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Speaker 7: then you'll have this normalization and it could be a

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Speaker 7: few years out where there's a balance between you know,

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Speaker 7: AI infrastructure leaders and those software innovators enterprise SaaS who

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Speaker 7: have really seized the opportunity to embed AI for their

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Speaker 7: customer benefit.

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Speaker 3: Non Webster wait to have you back on the show.

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Speaker 4: Thank you very much. Indeed, Pype Sandler, we appreciate it.

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Speaker 4: Coming up.

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Speaker 3: Spotify reporting record user growth in its fourth quarter. What's

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Speaker 3: to discuss next? We're in these earnings, but what are

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Speaker 3: you looking at?

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Speaker 2: Just a very quick look at TSMC's US listed shares

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Speaker 2: there are almost two percent one point percent, but trading

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Speaker 2: at a record high. The shares in Taiwan overnight traded

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Speaker 2: at record highs. The revenue jump thirty seven percent in January.

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Speaker 2: Same story, AI spending marches on. TSMC dominates the market

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Speaker 2: for chip manufacturing.

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Speaker 6: This is bloomboag tech.

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Speaker 3: It's checking on a Spotify shares having a strong day

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Speaker 3: up fifteen percent at one point, having their biggest move

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Speaker 3: on record after the company reported well record use a

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Speaker 3: growth in that fiscal fourth quarter. And eight hundred and

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Speaker 3: thirty five million dollars in operating income. Let's turn to

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Speaker 3: Bloombo's Ashley Carmen, who broke down the numbers and look,

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Speaker 3: the mighty have fallen a lot coming into this number, Ashley,

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Speaker 3: So the bounce back is perhaps not surprising when they're

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Speaker 3: able to give some sort of like ease to the

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Speaker 3: investor base.

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Speaker 10: Yeah, and I think that was a lot of what

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Speaker 10: this call was today is just addressing concerns that AI,

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Speaker 10: specifically AI music startups might I mean these are supposed

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Speaker 10: launch this year, so people are concerned they are people

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Speaker 10: going to start using AI degenerate songs and then listen

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Speaker 10: to those songs on other platforms, or are they going

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Speaker 10: to keep coming to Spotify? And today the co CEOs

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Speaker 10: were saying, we think they'll keep coming to Spotify.

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Speaker 2: So the stock at one point was up on track

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Speaker 2: for its bigges jump. Ever it's now up fifteen and

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Speaker 2: a half percent, I think, contract for its biggest jump

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Speaker 2: in seven almost eight years. You write about in the

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Speaker 2: report the impact of Rapped for those although I don't

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Speaker 2: imagine there's many that don't know what that is, Ashley,

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Speaker 2: just explain it. But like, why was that such a

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Speaker 2: big factor.

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Speaker 10: So Rapped is their annual interactive viral marketing campaign where

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Speaker 10: people share their music and podcasts that they listen to

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Speaker 10: the most this year and every year. It is just

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Speaker 10: a moment on the Internet. People tend to activate their

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Speaker 10: service to participate in RAP, so they always expect to

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Speaker 10: see a boost. But I believe on the call today

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Speaker 10: they said this was their biggest Rapped ever, So we

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Speaker 10: can really see the results of that marketing campaign.

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Speaker 4: But are people advertising more with Spotify?

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Speaker 3: Are they able to drive revenues not just by having

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Speaker 3: more of us tune in and unearth our Spotify account

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Speaker 3: every end of year.

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Speaker 10: So this is the one part of the earnings today

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Speaker 10: that was a little bit gloomy. The ad supported revenue

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Speaker 10: actually dropped year over year, and this has been a

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Speaker 10: part of the business that people are really wondering, when

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Speaker 10: are we going to see you start making more money

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Speaker 10: from advertising, Which is also an important question because when

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Speaker 10: we're talking about them adding users, these are ad supported users.

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Speaker 10: Subscribers grew as well, but if you're going to keep

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Speaker 10: adding ad supported users, you also.

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Speaker 4: Want to see the revenue in that department go up

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Speaker 4: as well.

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Speaker 2: Bloomberg's actually coming on Spotify, Thank you very much. Power

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Speaker 2: Amount is trying to sweeten it's Warner Brothers bid the

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Speaker 2: media giants, saying it will cover a two point eight

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Speaker 2: billion dollar termination fee that Warner Bros. Would pay Netflix

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Speaker 2: if it terminates and already agreed upon deal. Bloombok's Lucashaw,

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Speaker 2: who leads the screen Time team, it's with us. This

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Speaker 2: was interesting, right, So the headline's here and it's a

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Speaker 2: wheatner an improvement on their deal. But actually the specifics

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Speaker 2: are very interesting. They're not just they're not boosting the

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Speaker 2: offer price. Go into detail, explain how we unpick this.

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Speaker 11: Yeah, so they are addressing and they being Paramount. Two

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Speaker 11: of the concerns that Warner Brothers has had about their deal.

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Speaker 11: One is this question of the breakup thee Right, So,

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Speaker 11: Warner Brothers has been had been debating between two main

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Speaker 11: offers between Netflix and Paramount. They pick Netflix, but if

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Speaker 11: they walk away from Netflix to you know, re engage

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Speaker 11: with Paramount, they have to pay Netflix a bunch of money.

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Speaker 11: Paramount had is now offering to cover that, and Warner

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Speaker 11: Brothers had been very worried about it because they said

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Speaker 11: that one of the reasons that the deals weren't equivalent.

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Speaker 11: Was Paramount wasn't kind of covering Warner Brothers downside on that,

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Speaker 11: which would have come out of the money that they get.

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Speaker 11: The other thing here is Warner Brothers have been really

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Speaker 11: concerned about their ability to refinance their debt going forward.

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Speaker 11: Paramount has now or David Ellison both first in swallowing

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Speaker 11: Paramount and now try follow. Warner Brothers has a history

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Speaker 11: of trying to impose really onerous kind of covenants on

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Speaker 11: what the company he's acquiring can do, which would have

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Speaker 11: limited Warner Brothers in that respect, and now Paramount is

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Speaker 11: saying basically, we'll cover you on whatever costs are related

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Speaker 11: to that debt financing.

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Speaker 6: To your point, they still haven't.

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Speaker 11: Actually raised the thirty dollars a share offer. This does

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Speaker 11: increase the total net value of the bid, and so

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Speaker 11: we're waiting to see what the Warner Brothers board has

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Speaker 11: to say about it.

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Speaker 3: What credence to investors give at the moment. Lucas to

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Speaker 3: that this would pass through regulators more easily. This whole

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Speaker 3: ticking fee the idea that if it goes past the

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Speaker 3: quarter expected, they get a chunk of change in return.

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Speaker 3: If it's delayed, I mean that really just speaks to

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Speaker 3: the bravado here.

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Speaker 6: Yeah.

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Speaker 11: Well, Paramount has been adamant all along that it stands

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Speaker 11: a better chance of getting its deal approved, which on

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Speaker 11: its face makes some sense. Netflix is a much larger company,

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Speaker 11: a more powerful company. It's the number one player in streaming.

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Speaker 11: Netflix of course has countered that, you know, they're very

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Speaker 11: confident in getting their deal approved and raised issues with

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Speaker 11: with Paramounts offer because Paramount plus Warner Brothers Discovery combined

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Speaker 11: would account for technically a larger share of television viewing

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Speaker 11: than Netflix would under the deal. But both sides are

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Speaker 11: trying to plead their case. Paramount obviously is sort of

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Speaker 11: coming from behind here, and what they are trying to

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Speaker 11: do is inject enough doubt in the minds of shareholders

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Speaker 11: that they will not vote for the Netflix deal next month.

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Speaker 2: Lucas both sides trying to plead their case. There's been

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Speaker 2: a lot of recent reporting from US and what's also

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Speaker 2: happening kind of in the background. There's obviously been an

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Speaker 2: interest from Washington DC. What else do we need to

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Speaker 2: know about how this is going from a regulatory perspective,

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Speaker 2: or at least interest from government as well.

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Speaker 6: I don't know.

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Speaker 11: Right we've had Paramount shareholders or we've had kind of

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Speaker 11: Paramount and David Allison lobbying people in DC and Europe.

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Speaker 11: We've had Netflix going ahead of the Senate last week.

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Speaker 11: President Trump had said he'll be involved, and he said

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Speaker 11: he's not involved. What we do know, just as a

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Speaker 11: as a kind of basic set of facts, is that

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Speaker 11: the DOJ is looking into both cases and has yet

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Speaker 11: to say whether or not it's going to challenge either

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Speaker 11: of them.

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Speaker 3: In terms of timing, Is there anything pressuring? Is there

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Speaker 3: any date, any number, any any time frame that we

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Speaker 3: look to for the.

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Speaker 11: Next Yeah, the next big one is the shareholder vote. Really,

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Speaker 11: we're expecting Warner Brothers to arrange a vote of its

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Speaker 11: shareholders sometime probably in mid to late March, kind of

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Speaker 11: at the latest early April. That's something of a deadline

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Speaker 11: for Paramount because they need to convince a bunch of

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Speaker 11: shareholders before then to change their mind. Otherwise then they're

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Speaker 11: really up to the whims of regulators, because if it

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Speaker 11: gets to shareholders and shareholders do approve that Netflix deal,

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Speaker 11: there's not much Paramount can do besides hope that the

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Speaker 11: government in the US or Europe blocks the.

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Speaker 3: Deal for sure, we appreciate you on the story. Meanwhile,

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Speaker 3: coming up, we're going to talk about how storied VC

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Speaker 3: firm and recent Prowitz is helping drive the Trump administration's

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Speaker 3: AI approach us.

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Speaker 4: Next, this is brettly bed Tech.

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Speaker 3: It's time now for Talking tech and first up Stripe.

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Speaker 3: It's arranging a tender offer that would value the company

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Speaker 3: at one hundred and forty billion dollars now. According to sources,

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Speaker 3: that marks a roughly thirty billion dollar increase from the

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Speaker 3: most recent valuation in last year. The move is being

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Speaker 3: seen as a sign that the mighty fintech may continue

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Speaker 3: to delay.

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Speaker 4: As initial public offerings.

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Speaker 3: Plus, Cadence Design Systems is introducing a new AI tool

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Speaker 3: designed to speed up semiconductor development. Now the company's new

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Speaker 3: Chipstack AI.

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Speaker 4: Superagent, and it will act as as a system to.

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Speaker 3: Engineers helping with design debugging blueprint generation look. The move

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Speaker 3: comes as a tech industry really grapples with the surgeon

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Speaker 3: chip demand and ongoing labor shortages and Ali Baba. While

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Speaker 3: it's pushing further into robotics. The company has debuted a

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Speaker 3: new AI model called Rinbrain, designed to give robots in

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Speaker 3: more advanced understanding of their surroundings. With the release Ali

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Speaker 3: Baba takes on AI leaders such as Google and Nvidia

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Speaker 3: and what have you got?

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Speaker 2: Okay, So Andrews and Horowitz has become one of the

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Speaker 2: most influential voices shaping the Trump administration's AI policies. Sources

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Speaker 2: say the venture firm is often the first outside call

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Speaker 2: the top White House officials and senior Republican congressional aids

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Speaker 2: make when weighing moves that could affect tech companies AI plans.

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Speaker 6: And like a lot of this.

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Speaker 2: Reporting CARO is coming from current and former White House officials.

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Speaker 2: There are things that are clearly in plain sight, right.

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Speaker 2: So Shriram Krishnan, who is a senior AI policy advisor

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Speaker 2: to the President, is a former and recent Horowitz partner,

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Speaker 2: but he was in London, and there's reporting in there

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Speaker 2: about you know, David Sachs, who is from the world

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Speaker 2: of bench capital in Silicon Valley, is close to the

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Speaker 2: president and wants to hear out industry.

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Speaker 6: And Injurcent has.

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Speaker 3: Scale, has scale, it has money to put into super PACs.

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Speaker 3: We see what they did with the crypto fair Shake

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Speaker 3: in the way that they've then retargeted in the AI spectrum.

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Speaker 3: But what's also interesting is one of the lines in

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Speaker 3: the story says they de facto have a veto really

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Speaker 3: over certain AI policies.

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Speaker 4: Now they push back on that.

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Speaker 3: In particular, the named lobbyist for A sixteen Z says, Look,

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Speaker 3: the only person who's got AI veto is President Trump himself.

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Speaker 6: Yeah.

442
00:22:21,520 --> 00:22:24,320
Speaker 2: Yeah, the President makes policy back. You know, as we've reported,

443
00:22:24,600 --> 00:22:26,960
Speaker 2: he often gets handed the docs, reads them himself and

444
00:22:27,000 --> 00:22:30,000
Speaker 2: says good call. Coming up on the program, Runway CEO

445
00:22:30,080 --> 00:22:32,560
Speaker 2: Chris abou Venezuela will be with us to talk about

446
00:22:32,560 --> 00:22:35,720
Speaker 2: the startup's latest funding round at a five point three

447
00:22:35,800 --> 00:22:39,000
Speaker 2: billion dollar valuation. It is halftime in that conversation is

448
00:22:39,000 --> 00:22:39,680
Speaker 2: coming up next.

449
00:22:39,960 --> 00:22:40,920
Speaker 6: This is Bloomberg Tech.

450
00:22:47,800 --> 00:22:49,440
Speaker 3: Welcome back to bloom bed Tech. Let's check in on

451
00:22:49,480 --> 00:22:51,400
Speaker 3: the markets that actually giving away some of their gains

452
00:22:51,480 --> 00:22:54,119
Speaker 3: we had earlier in the session. We're now unchanged on

453
00:22:54,160 --> 00:22:56,880
Speaker 3: the NASAK one hundred. We're trying to digest the retail

454
00:22:56,960 --> 00:22:58,800
Speaker 3: data that we got which was weaker than expected. But

455
00:22:58,800 --> 00:23:00,119
Speaker 3: what does that mean in terms of the FED and

456
00:23:00,160 --> 00:23:03,160
Speaker 3: its ability to cut rates more broadly? But also where

457
00:23:03,240 --> 00:23:05,760
Speaker 3: are we buying back into? Is software still loved at

458
00:23:05,760 --> 00:23:07,919
Speaker 3: the moment, having been so beaten up last week, and

459
00:23:07,960 --> 00:23:10,000
Speaker 3: the hardware sol off is just a little bit crimping

460
00:23:10,040 --> 00:23:12,560
Speaker 3: some of that risk feeling of the day. I'm looking

461
00:23:12,600 --> 00:23:14,919
Speaker 3: at a risk off feeling in crypto Bitcoin not by

462
00:23:14,920 --> 00:23:17,360
Speaker 3: one point four percent. We're still at sixty nine thousand,

463
00:23:17,480 --> 00:23:20,000
Speaker 3: so well off the lows of last week, but it's

464
00:23:20,000 --> 00:23:22,560
Speaker 3: still the moon music not strong. Particularly in eth We're

465
00:23:22,560 --> 00:23:25,879
Speaker 3: off by four point six percent, So still looking for

466
00:23:25,920 --> 00:23:29,440
Speaker 3: a direction and really where the asset class buying comes

467
00:23:29,520 --> 00:23:32,399
Speaker 3: and steps back in. Move on to what's happening underneath

468
00:23:32,480 --> 00:23:35,879
Speaker 3: hoad of the benchmarks, because look, we are seeing significant.

469
00:23:35,359 --> 00:23:36,160
Speaker 4: Games of Spotify.

470
00:23:36,240 --> 00:23:38,679
Speaker 3: I might add it has been crushed leading up to

471
00:23:38,720 --> 00:23:41,199
Speaker 3: these numbers, so we're still down on the ear In

472
00:23:41,320 --> 00:23:43,399
Speaker 3: terms of a one year basis, We're up fifteen percent,

473
00:23:43,480 --> 00:23:47,240
Speaker 3: almost a record move on their shares after their addition

474
00:23:47,280 --> 00:23:51,240
Speaker 3: to monthly average users. Really eclipsed expectations. Snap gets an

475
00:23:51,359 --> 00:23:54,000
Speaker 3: upgrade EREC. It's really seeing that you could be buying

476
00:23:54,040 --> 00:23:57,160
Speaker 3: into the strength of subscriptions for this company. Data dog

477
00:23:57,359 --> 00:23:59,800
Speaker 3: check that out up sixteen percent against software was beaten up,

478
00:23:59,800 --> 00:24:03,199
Speaker 3: but it's still giving an earnings report that studded some

479
00:24:03,240 --> 00:24:05,760
Speaker 3: of those nerves at joining.

480
00:24:05,520 --> 00:24:08,600
Speaker 2: Us now is Bloomberg Aquities reporter Rhyme Vasselica, who I

481
00:24:08,600 --> 00:24:10,439
Speaker 2: don't know how he does it, but he's across the

482
00:24:10,600 --> 00:24:13,240
Speaker 2: entire lot. Let's start with that with the earnings part,

483
00:24:13,280 --> 00:24:15,720
Speaker 2: because that's probably more common to some of the bigger

484
00:24:15,800 --> 00:24:19,440
Speaker 2: movers right across the markets this morning, Spotify, Data Dog,

485
00:24:19,840 --> 00:24:21,760
Speaker 2: what are the trends we're seeing and what's the action

486
00:24:21,840 --> 00:24:22,919
Speaker 2: in the moment telling.

487
00:24:22,680 --> 00:24:25,440
Speaker 12: You, hey, good morning, thanks for having me. So a

488
00:24:25,480 --> 00:24:28,600
Speaker 12: lot of these companies have gotten beaten down, as you mentioned,

489
00:24:28,760 --> 00:24:31,080
Speaker 12: but they did a lot to reassure investors about some

490
00:24:31,119 --> 00:24:33,240
Speaker 12: of the bigger concerns that are facing them. So in

491
00:24:33,320 --> 00:24:36,280
Speaker 12: Spotify's case, they give a very strong outlook for their

492
00:24:36,400 --> 00:24:38,960
Speaker 12: user growth. They gave a very strong outlook for their margins,

493
00:24:38,960 --> 00:24:41,520
Speaker 12: both of which helped to address key concern that people

494
00:24:41,560 --> 00:24:45,680
Speaker 12: have been having. Spotify, I think us up by biggest day.

495
00:24:45,720 --> 00:24:47,720
Speaker 12: I think you in several years by now, So certainly

496
00:24:47,760 --> 00:24:51,040
Speaker 12: a relief rally there. Data Dog another company that has

497
00:24:51,040 --> 00:24:54,200
Speaker 12: been really beaten down as part of the ongoing route

498
00:24:54,200 --> 00:24:57,400
Speaker 12: in software stocks. Strong revenue forecasts there in the full

499
00:24:57,480 --> 00:24:59,920
Speaker 12: year revenue forecast I think was a little bit under expected,

500
00:25:00,359 --> 00:25:02,679
Speaker 12: But at the same time, analyst said, this looks like

501
00:25:02,720 --> 00:25:05,879
Speaker 12: it could be conservative, really helping to ease concerns about

502
00:25:06,080 --> 00:25:08,440
Speaker 12: what is the impact that some of these software companies

503
00:25:08,480 --> 00:25:11,240
Speaker 12: are going to see from AI related services.

504
00:25:11,680 --> 00:25:14,800
Speaker 3: That's it, isn't it. That's the read across it's how

505
00:25:14,880 --> 00:25:16,800
Speaker 3: much is AI going to be eating any of these

506
00:25:16,800 --> 00:25:20,359
Speaker 3: companies launches? And absolutely it must be the desire of

507
00:25:20,400 --> 00:25:22,720
Speaker 3: the executives right now to push back and to show

508
00:25:23,080 --> 00:25:26,240
Speaker 3: real operating margin growth and in particular real revenue. I

509
00:25:26,240 --> 00:25:28,320
Speaker 3: mean Data Dog was up twenty nine percent for their

510
00:25:28,400 --> 00:25:29,520
Speaker 3: last quarter, just gone.

511
00:25:30,000 --> 00:25:30,760
Speaker 6: Yeah. Absolutely.

512
00:25:30,840 --> 00:25:33,040
Speaker 12: Now I will say that the not all of the

513
00:25:33,080 --> 00:25:35,359
Speaker 12: results have been strong. So yesterday we got results from

514
00:25:35,400 --> 00:25:38,879
Speaker 12: the company called Monday dot Com that's not fell twenty percent.

515
00:25:38,920 --> 00:25:41,720
Speaker 12: I think that one wasn't strong enough to help ease

516
00:25:41,720 --> 00:25:43,960
Speaker 12: some of these concerns how to persisted around it. But

517
00:25:44,040 --> 00:25:45,520
Speaker 12: Data Dog is the one that I feel like you

518
00:25:45,560 --> 00:25:47,840
Speaker 12: hear a lot of people talking about when you look

519
00:25:47,840 --> 00:25:50,199
Speaker 12: at the overall software weakness, this is one name that

520
00:25:50,240 --> 00:25:52,679
Speaker 12: gets singled out repeatedly as one that was sort of

521
00:25:52,720 --> 00:25:55,640
Speaker 12: thrown out with the bathwater. So maybe overdone selling there.

522
00:25:55,920 --> 00:25:57,800
Speaker 12: Certainly the results here are giving the bowl.

523
00:25:57,880 --> 00:26:01,520
Speaker 2: Something to cheer about, bost Ryan for Stelika, thank you

524
00:26:01,640 --> 00:26:03,560
Speaker 2: very much. Just go to the private markets. In the

525
00:26:03,560 --> 00:26:06,680
Speaker 2: world of startups, AI start at Runway hit a five

526
00:26:06,720 --> 00:26:09,480
Speaker 2: point three billion dollar valuation after the company ciniched a

527
00:26:09,480 --> 00:26:12,560
Speaker 2: new round of funding, raising three hundred and fifteen million dollars.

528
00:26:13,119 --> 00:26:16,320
Speaker 2: Here to discuss Runway CEO christ Valezuela. You know, I

529
00:26:16,359 --> 00:26:19,840
Speaker 2: was reading all of the different reports about this this round,

530
00:26:19,840 --> 00:26:22,040
Speaker 2: and we'll get to the money part, but I think

531
00:26:22,320 --> 00:26:24,280
Speaker 2: what's jumping out at me Christ about it's great to

532
00:26:24,320 --> 00:26:26,479
Speaker 2: have you back on the program, By the way, is

533
00:26:26,960 --> 00:26:32,040
Speaker 2: the need to make models that are more useful, that

534
00:26:32,119 --> 00:26:34,199
Speaker 2: can do more. Do you think that's a that's a

535
00:26:34,240 --> 00:26:35,320
Speaker 2: fair place to start.

536
00:26:36,680 --> 00:26:39,760
Speaker 6: It is I'm thinking for and having me hear it is.

537
00:26:39,800 --> 00:26:42,760
Speaker 13: I think it's a reality of where the thegnologies heading

538
00:26:42,840 --> 00:26:46,359
Speaker 13: or where the models are. We've sent There's a little

539
00:26:46,359 --> 00:26:49,720
Speaker 13: bit with language models, but now I think world models

540
00:26:49,720 --> 00:26:53,040
Speaker 13: are basically eating research and eating AI. It's kind of

541
00:26:53,040 --> 00:26:55,880
Speaker 13: clear that the next round tier of what we expect

542
00:26:55,920 --> 00:26:58,560
Speaker 13: to see progress and all more valities will come from

543
00:26:58,600 --> 00:27:00,560
Speaker 13: video and from models that are going to understand and

544
00:27:00,600 --> 00:27:01,440
Speaker 13: simulate the world.

545
00:27:01,920 --> 00:27:03,560
Speaker 6: And so a lot of what we're doing with this new.

546
00:27:03,400 --> 00:27:05,639
Speaker 13: Funding is to basically double down on that vision and

547
00:27:05,640 --> 00:27:08,159
Speaker 13: that mission, which I think we've been first to market

548
00:27:08,160 --> 00:27:11,399
Speaker 13: and many other parts of AI, including of course video generation.

549
00:27:12,000 --> 00:27:14,240
Speaker 13: But now it feels like more present than ever. Then

550
00:27:14,320 --> 00:27:17,480
Speaker 13: world models will start really unlocking the next stage of

551
00:27:17,480 --> 00:27:18,280
Speaker 13: AI progress.

552
00:27:19,240 --> 00:27:21,080
Speaker 2: You may be a little beaten down by by this

553
00:27:21,160 --> 00:27:24,440
Speaker 2: story and line of questioning the capital is for compute,

554
00:27:24,760 --> 00:27:27,040
Speaker 2: or it's for talent, or it's for both, and give

555
00:27:27,119 --> 00:27:29,359
Speaker 2: us a sense of what that environment is right now.

556
00:27:30,200 --> 00:27:31,680
Speaker 6: Yeah, it's true for both.

557
00:27:31,720 --> 00:27:33,960
Speaker 13: I mean, the growth of the company seems from how

558
00:27:34,000 --> 00:27:37,800
Speaker 13: we allocate these resources effectively. And look, we've been very

559
00:27:37,840 --> 00:27:43,240
Speaker 13: focused and very efficient company, spending what we've raised in

560
00:27:43,320 --> 00:27:46,120
Speaker 13: putting it into compute, into training some of the world

561
00:27:46,280 --> 00:27:49,520
Speaker 13: best data models out there, and hiring we're for the

562
00:27:49,600 --> 00:27:51,280
Speaker 13: impact that we've had as a company and for the

563
00:27:51,320 --> 00:27:55,120
Speaker 13: kind of customers and enterprises that we serve. Very small team,

564
00:27:55,200 --> 00:27:57,600
Speaker 13: and so right now we are scaling that we are

565
00:27:57,920 --> 00:28:02,280
Speaker 13: hiring across the board, more researchers, more great talent, and

566
00:28:02,359 --> 00:28:05,040
Speaker 13: of course double down on compute, which is fundamental if

567
00:28:05,040 --> 00:28:06,439
Speaker 13: you really want to get to the next stage of

568
00:28:06,480 --> 00:28:07,440
Speaker 13: what we think will.

569
00:28:07,240 --> 00:28:09,480
Speaker 3: Come the kind of customers you serve?

570
00:28:10,119 --> 00:28:12,000
Speaker 4: Christ about who is that? Then?

571
00:28:12,280 --> 00:28:17,080
Speaker 3: As we still typecast you as an AI video generation company,

572
00:28:17,119 --> 00:28:19,960
Speaker 3: but you're not. You're a robotics company, you're an avatar company,

573
00:28:20,040 --> 00:28:20,959
Speaker 3: you're a world company.

574
00:28:21,000 --> 00:28:21,840
Speaker 4: So who do you serve?

575
00:28:22,800 --> 00:28:24,000
Speaker 6: Yeah, of course that's a good question.

576
00:28:24,040 --> 00:28:27,120
Speaker 13: So look, I think it's important to understand how AI

577
00:28:27,160 --> 00:28:31,480
Speaker 13: has progressed and language models are basically describing reality. World

578
00:28:31,480 --> 00:28:34,480
Speaker 13: models are simulating the world. And when you stimulate the world,

579
00:28:34,560 --> 00:28:37,359
Speaker 13: you can start tackling many different kind of industries.

580
00:28:37,440 --> 00:28:38,640
Speaker 6: So the question of.

581
00:28:38,600 --> 00:28:42,280
Speaker 13: Like, wo AI models will help advertising, marketing, Hollywood media,

582
00:28:42,680 --> 00:28:44,760
Speaker 13: I think the question is answered and the answer is yes.

583
00:28:45,080 --> 00:28:48,400
Speaker 13: It's kind of a pretty obvious yes to these days.

584
00:28:48,560 --> 00:28:51,040
Speaker 13: And so we're the best company and the best kind

585
00:28:51,080 --> 00:28:55,600
Speaker 13: of like solution for marketers, media, Hollywood entertainment. We've been

586
00:28:55,680 --> 00:28:58,240
Speaker 13: doing this for quite some time and so I think

587
00:28:58,240 --> 00:28:59,960
Speaker 13: we're won there and going to continue to grow.

588
00:29:00,040 --> 00:29:01,600
Speaker 6: There's a lot of expansion that we have to do

589
00:29:01,600 --> 00:29:02,520
Speaker 6: in the industry there.

590
00:29:02,800 --> 00:29:05,360
Speaker 13: Now the models can simulate the world, So we started

591
00:29:05,360 --> 00:29:08,040
Speaker 13: to simulate not only media and entertainment, but we started

592
00:29:08,040 --> 00:29:10,920
Speaker 13: to simulate how the world works, and that is effectively

593
00:29:11,080 --> 00:29:13,840
Speaker 13: very valuable for robotics, for physically a I for ave

594
00:29:14,600 --> 00:29:17,080
Speaker 13: and so another way of thinking about it is we

595
00:29:17,120 --> 00:29:19,280
Speaker 13: have some of the best tools to create media and

596
00:29:19,400 --> 00:29:22,200
Speaker 13: videos for humans to watch. We now started to create

597
00:29:22,280 --> 00:29:25,440
Speaker 13: videos and media for robots to watch, and that for

598
00:29:25,520 --> 00:29:28,440
Speaker 13: those robots to learn from that data, which is fascinating.

599
00:29:28,840 --> 00:29:31,960
Speaker 3: It is fascinating. It also has different impacts on different people,

600
00:29:32,120 --> 00:29:34,600
Speaker 3: and when you say it helps an industry, that's kind

601
00:29:34,600 --> 00:29:36,960
Speaker 3: of in the eye of the beholder. Chris Well, talk

602
00:29:37,000 --> 00:29:39,440
Speaker 3: to us about how you think about as a leader

603
00:29:39,440 --> 00:29:42,480
Speaker 3: of your business, the implications this has for the labor market,

604
00:29:42,640 --> 00:29:46,320
Speaker 3: for what it means more broadly for humans watching content

605
00:29:46,440 --> 00:29:49,720
Speaker 3: that wasn't made by people and the reality of them.

606
00:29:50,720 --> 00:29:50,920
Speaker 6: Yeah.

607
00:29:51,160 --> 00:29:54,560
Speaker 13: Look, that's a question that we've tried to grapple for

608
00:29:54,600 --> 00:29:56,360
Speaker 13: a long time in terms of how do we make

609
00:29:56,400 --> 00:29:59,800
Speaker 13: sure that companies and industries react accordingly to what's coming

610
00:30:00,000 --> 00:30:02,920
Speaker 13: that's happening. And I think my take, after seeing the

611
00:30:02,960 --> 00:30:05,000
Speaker 13: industry for quite some times, I think the industry's are

612
00:30:05,040 --> 00:30:07,160
Speaker 13: acting pretty well. To be honest, if you look at

613
00:30:07,200 --> 00:30:10,400
Speaker 13: advertising agencies, if you look at Hollywood, it's pretty obvious

614
00:30:10,440 --> 00:30:13,240
Speaker 13: these days is that every studio has an AI department,

615
00:30:13,280 --> 00:30:17,120
Speaker 13: an AI can function and ichi forth, and the organization

616
00:30:17,200 --> 00:30:20,440
Speaker 13: has started to rethink themselves in an AI for native world,

617
00:30:20,920 --> 00:30:24,320
Speaker 13: and that has allowed themselves to really find new jobs,

618
00:30:24,400 --> 00:30:26,400
Speaker 13: new types of things that they weren't able to do before.

619
00:30:26,480 --> 00:30:29,840
Speaker 13: So in a way, that's taking some of the tasks

620
00:30:29,920 --> 00:30:31,960
Speaker 13: and things we've seen in the past, and that will

621
00:30:32,000 --> 00:30:33,200
Speaker 13: go away, and that's natural.

622
00:30:33,240 --> 00:30:35,760
Speaker 6: I think that we've solely realized that that's the case.

623
00:30:36,200 --> 00:30:38,880
Speaker 13: At the same time, we've seen more jobs being put

624
00:30:38,880 --> 00:30:41,320
Speaker 13: out there with new descriptions on things that even a

625
00:30:41,400 --> 00:30:43,920
Speaker 13: year ago would have been unthinkable of. And I think

626
00:30:43,960 --> 00:30:47,160
Speaker 13: that reaction is now becoming obvious, notably for media, for Hollywood,

627
00:30:47,320 --> 00:30:49,880
Speaker 13: for for gaming companies, and for many other industries.

628
00:30:49,920 --> 00:30:52,160
Speaker 6: Even for software engineers. I think it's kind of pretty obviously.

629
00:30:52,240 --> 00:30:54,120
Speaker 13: Day is where you start to see that you can

630
00:30:54,160 --> 00:30:57,280
Speaker 13: automate and simplify a lot of the entry like level

631
00:30:57,360 --> 00:30:59,480
Speaker 13: tasks and jobs, and so that's where I think we

632
00:30:59,480 --> 00:31:01,440
Speaker 13: will continue to see growth industry wise.

633
00:31:02,040 --> 00:31:05,040
Speaker 6: Meet and Entertainment Chris about.

634
00:31:04,960 --> 00:31:07,000
Speaker 2: We find that that there's a lot of interest in

635
00:31:07,080 --> 00:31:09,960
Speaker 2: Runway right as a company, how the models are being

636
00:31:09,960 --> 00:31:14,600
Speaker 2: deployed and used commercialization. This was a big round. The

637
00:31:14,680 --> 00:31:17,320
Speaker 2: valuation is interesting. A lot of the questions we get

638
00:31:17,360 --> 00:31:19,960
Speaker 2: for you about your future and whether you plan to

639
00:31:20,000 --> 00:31:22,280
Speaker 2: go public, So I'd ask you to kind of be

640
00:31:22,400 --> 00:31:27,120
Speaker 2: candid about that, the benefits and negatives of being a

641
00:31:27,160 --> 00:31:30,800
Speaker 2: public company, and why you might consider doing that.

642
00:31:32,760 --> 00:31:35,960
Speaker 13: It's not something we're not consider at some point. I

643
00:31:35,960 --> 00:31:40,520
Speaker 13: think right now, given the breath and research innovation that

644
00:31:40,560 --> 00:31:42,480
Speaker 13: we conduct at the company, I think we're in a

645
00:31:42,560 --> 00:31:45,280
Speaker 13: much better position thinking about being private for a bit

646
00:31:45,320 --> 00:31:48,000
Speaker 13: more time. I think there's tradeoffs as being a public

647
00:31:48,040 --> 00:31:50,480
Speaker 13: company in terms of how you report, how you think

648
00:31:50,480 --> 00:31:52,320
Speaker 13: about your growth, the kind of things that you need

649
00:31:52,360 --> 00:31:55,160
Speaker 13: to focus on right now. For me, this is an

650
00:31:55,200 --> 00:31:58,920
Speaker 13: area of unique from tiear research, and being a private

651
00:31:58,920 --> 00:32:00,960
Speaker 13: company allows you to do that frontier research in a

652
00:32:01,040 --> 00:32:04,720
Speaker 13: much more with much for freedom, and so it's something

653
00:32:04,720 --> 00:32:07,840
Speaker 13: we wouldn't necessarily not consider, but right now, given the

654
00:32:07,840 --> 00:32:10,440
Speaker 13: growth that we see, will probably remain a private company

655
00:32:10,440 --> 00:32:12,640
Speaker 13: for quite some time to retain their independence.

656
00:32:13,400 --> 00:32:16,440
Speaker 3: Chase Well, briefly, I so of asked you about whether

657
00:32:16,640 --> 00:32:19,480
Speaker 3: the employee base in companies already. Am I as a

658
00:32:19,560 --> 00:32:23,000
Speaker 3: human ready to digest the wall of AI made content

659
00:32:23,040 --> 00:32:24,480
Speaker 3: and discern what's real and what's not.

660
00:32:25,840 --> 00:32:30,040
Speaker 6: Yeah, you know, that's that's an interesting question. I actually

661
00:32:30,080 --> 00:32:33,120
Speaker 6: will I actually will kind of flip the assumption there.

662
00:32:33,320 --> 00:32:36,080
Speaker 13: I would start to assume when I will suggest everyone

663
00:32:36,120 --> 00:32:38,880
Speaker 13: probably starts to assume that most of the content that

664
00:32:38,920 --> 00:32:41,640
Speaker 13: you see how is going to be generated, and in

665
00:32:41,680 --> 00:32:43,560
Speaker 13: that case, what we should be kind of water marketing

666
00:32:43,600 --> 00:32:47,040
Speaker 13: and protecting isn't necessarily the generated content is the real content.

667
00:32:47,080 --> 00:32:49,080
Speaker 13: It's the content that we've seen and we've recorded from

668
00:32:49,080 --> 00:32:51,280
Speaker 13: a camera. And then inverts a little bit of the

669
00:32:51,280 --> 00:32:55,320
Speaker 13: problem because yes, more content will start becoming the norm.

670
00:32:55,440 --> 00:32:57,560
Speaker 13: More AI content will start becoming the norm of the

671
00:32:57,600 --> 00:33:00,400
Speaker 13: content we interact with, specifically when you can also doing

672
00:33:00,480 --> 00:33:02,440
Speaker 13: in real time, which is going to be a fascinating

673
00:33:02,480 --> 00:33:05,320
Speaker 13: new avenue of like gaming and nonlinear experiences.

674
00:33:06,600 --> 00:33:08,360
Speaker 6: I think the world is adjusting to that.

675
00:33:08,400 --> 00:33:12,080
Speaker 13: There's definitely a culture on social adjustment, period, but from

676
00:33:12,080 --> 00:33:15,120
Speaker 13: what I've seen, I think it's happening faster there before,

677
00:33:15,200 --> 00:33:17,320
Speaker 13: and just to be period because it's going to get

678
00:33:17,360 --> 00:33:18,320
Speaker 13: even even more crezy.

679
00:33:18,800 --> 00:33:22,160
Speaker 3: Christopher Valenzuela Runway CEO, it's great to have you back.

680
00:33:22,280 --> 00:33:23,800
Speaker 6: We appreciate it, of course, thank you.

681
00:33:23,840 --> 00:33:27,840
Speaker 3: Grayce coming up ahead of a landmark addiction trial. Meta

682
00:33:28,120 --> 00:33:31,120
Speaker 3: run thousands of commercials to promote its safety work with teens.

683
00:33:31,280 --> 00:33:33,440
Speaker 4: Details on that. Next, this is a blue neg.

684
00:33:33,360 --> 00:33:41,840
Speaker 6: Tech Instagram owner.

685
00:33:41,920 --> 00:33:46,000
Speaker 2: Meta paid for thousands of TV commercials that promoted its

686
00:33:46,040 --> 00:33:50,240
Speaker 2: safety with teens, all ahead of a landmark case examining

687
00:33:50,240 --> 00:33:55,480
Speaker 2: whether the company intentionally designed products to hook children. Bloombers

688
00:33:55,520 --> 00:33:57,840
Speaker 2: Kirk Wagner, who leads our coverage of matters here with us.

689
00:33:58,200 --> 00:34:01,840
Speaker 2: This is about timing and proximity to two events.

690
00:34:01,880 --> 00:34:04,120
Speaker 6: But what do we need to know in our reporting?

691
00:34:04,280 --> 00:34:06,600
Speaker 14: Yeah, so the trial is sort of the backdrop of

692
00:34:06,600 --> 00:34:09,600
Speaker 14: this whole thing that started yesterday in Los Angeles.

693
00:34:09,760 --> 00:34:10,920
Speaker 6: As you point out, the.

694
00:34:11,880 --> 00:34:15,040
Speaker 14: Allegations here are that Meta and YouTube and others have

695
00:34:15,120 --> 00:34:17,759
Speaker 14: created these products to addict young people, you know, the

696
00:34:17,800 --> 00:34:20,879
Speaker 14: infinite scrolling, the algorithms, things like that. And so these

697
00:34:21,040 --> 00:34:23,719
Speaker 14: advertisements that Meta has been running for a while, but

698
00:34:23,840 --> 00:34:28,279
Speaker 14: really in earnest since November, promote their team accounts and

699
00:34:28,360 --> 00:34:30,160
Speaker 14: all of the stuff they're doing to try and help

700
00:34:30,760 --> 00:34:34,080
Speaker 14: and combat this issue with teenagers. And so again timing

701
00:34:34,160 --> 00:34:35,920
Speaker 14: is interesting here. They're trying to sort of set this

702
00:34:36,040 --> 00:34:38,879
Speaker 14: narrative about themselves with the backdrop of this trial. Going

703
00:34:38,880 --> 00:34:40,040
Speaker 14: on at the same time.

704
00:34:40,120 --> 00:34:42,960
Speaker 3: Now in the story talks of tech Oversite Project executive

705
00:34:42,960 --> 00:34:46,399
Speaker 3: director Sasha Howeth really talking about this as being an

706
00:34:46,480 --> 00:34:49,480
Speaker 3: influence play, but in many ways, to take the other side,

707
00:34:49,640 --> 00:34:50,160
Speaker 3: it's meant to.

708
00:34:50,120 --> 00:34:52,279
Speaker 4: Be an influence play for parents.

709
00:34:51,960 --> 00:34:54,920
Speaker 3: For kids to understand that these tools are there for

710
00:34:54,960 --> 00:34:56,120
Speaker 3: them to use, right.

711
00:34:57,680 --> 00:34:58,200
Speaker 6: Exactly.

712
00:34:58,280 --> 00:35:00,400
Speaker 14: And you know, you think about if you're Meta and

713
00:35:00,400 --> 00:35:02,400
Speaker 14: you're sitting here going, Okay, there's going to be this

714
00:35:02,480 --> 00:35:04,520
Speaker 14: landmark trial, and in fact, there's going to be trials

715
00:35:04,719 --> 00:35:07,520
Speaker 14: for Meta around child safety and tea and safety throughout

716
00:35:07,520 --> 00:35:09,640
Speaker 14: the year. And so if you think about there's this

717
00:35:09,719 --> 00:35:13,920
Speaker 14: steady drumbeat of headlines and news and coverage about that issue,

718
00:35:14,040 --> 00:35:16,320
Speaker 14: you certainly want to have your viewpoint.

719
00:35:15,800 --> 00:35:16,480
Speaker 6: Out there as well.

720
00:35:16,520 --> 00:35:18,719
Speaker 14: And so I think that's why we see them promoting

721
00:35:18,760 --> 00:35:21,640
Speaker 14: these teen accounts, which they were all about about two

722
00:35:21,719 --> 00:35:25,600
Speaker 14: years ago, and really trying, to your point, Caroline, show

723
00:35:25,719 --> 00:35:28,040
Speaker 14: parents that, hey, all these things you're reading in the press,

724
00:35:28,080 --> 00:35:32,440
Speaker 14: like we are addressing them with these safety settings that

725
00:35:32,480 --> 00:35:33,760
Speaker 14: we've put in place as well.

726
00:35:33,840 --> 00:35:35,839
Speaker 4: And most Kurt Wagner, we thank you.

727
00:35:36,000 --> 00:35:37,879
Speaker 3: We're going to talk more about that story in a moment,

728
00:35:37,880 --> 00:35:39,560
Speaker 3: but first then you've got some breaking news.

729
00:35:40,080 --> 00:35:40,400
Speaker 6: Yeah.

730
00:35:40,520 --> 00:35:45,520
Speaker 2: My understanding is that Tesla has promoted Joe Ward, who

731
00:35:45,560 --> 00:35:49,360
Speaker 2: is the vice president leading the emir Region operations, to

732
00:35:49,480 --> 00:35:53,720
Speaker 2: basically run sales, service and delivery globally. All those teams

733
00:35:53,719 --> 00:35:56,239
Speaker 2: around the world are now reporting into him. We don't

734
00:35:56,239 --> 00:35:58,600
Speaker 2: know that much about Joe Ward. I think he started

735
00:35:58,600 --> 00:36:01,319
Speaker 2: at Tesla as an intern and quite a long time ago,

736
00:36:01,719 --> 00:36:04,359
Speaker 2: has kind of closed climbed up the ranks and been

737
00:36:04,360 --> 00:36:07,839
Speaker 2: based in Europe. You'll remember yesterday Bloomberg had reported that

738
00:36:07,960 --> 00:36:10,520
Speaker 2: Raj Jigg and Nathan had left Tesla and he had

739
00:36:10,560 --> 00:36:13,799
Speaker 2: been running the sales org. And you know, we try

740
00:36:13,840 --> 00:36:15,920
Speaker 2: and track this because of how it runs with everything

741
00:36:16,000 --> 00:36:19,000
Speaker 2: kind of filtering into Elon Musk. Ultimately we'll keep tracking

742
00:36:19,000 --> 00:36:19,480
Speaker 2: it a carrot.

743
00:36:19,560 --> 00:36:22,319
Speaker 3: Yeah, yeah, AA sales they've been tough of late. Now

744
00:36:22,400 --> 00:36:25,600
Speaker 3: let's just return to our original conversation, because, as mentioned,

745
00:36:25,760 --> 00:36:28,920
Speaker 3: it's not just Meta that's currently under scrutiny over safety,

746
00:36:28,960 --> 00:36:32,040
Speaker 3: particularly for teens. Other tech giants think Google when it's

747
00:36:32,080 --> 00:36:34,800
Speaker 3: YouTube of facing lawsuits as well over the addictive nature

748
00:36:34,800 --> 00:36:35,840
Speaker 3: of social media.

749
00:36:36,000 --> 00:36:36,920
Speaker 4: Let's get more on all of this.

750
00:36:37,080 --> 00:36:39,560
Speaker 3: Eric Goldman, he's a law professor at Santa Clara University

751
00:36:39,560 --> 00:36:41,279
Speaker 3: School of Law and co director of the school at

752
00:36:41,360 --> 00:36:45,200
Speaker 3: Center for High Tech Law. Eric, as I mentioned, it's Meta,

753
00:36:45,320 --> 00:36:50,280
Speaker 3: it's Google, it's also Snap and TikTok facing legal focus

754
00:36:50,360 --> 00:36:51,040
Speaker 3: throughout the year.

755
00:36:51,120 --> 00:36:51,920
Speaker 4: Correct.

756
00:36:52,920 --> 00:36:55,080
Speaker 15: Yeah, there's a trial taking place right now in Los

757
00:36:55,120 --> 00:36:58,840
Speaker 15: Angeles putting all four of them on trial. There's also

758
00:36:58,960 --> 00:37:02,480
Speaker 15: a federal key since putting them on trial in June,

759
00:37:03,280 --> 00:37:06,080
Speaker 15: and there are lawsuits against all of them throughout the country.

760
00:37:06,200 --> 00:37:07,080
Speaker 15: In parallel with that.

761
00:37:08,120 --> 00:37:12,239
Speaker 3: The argument at its core from some of these so

762
00:37:12,360 --> 00:37:17,040
Speaker 3: called victims are that these tools and these platforms were

763
00:37:17,040 --> 00:37:20,560
Speaker 3: designed to hook teams young brains in particular, and keep

764
00:37:20,600 --> 00:37:23,400
Speaker 3: them coming back for more. Eric, is that the understanding

765
00:37:23,440 --> 00:37:25,719
Speaker 3: you have, what legal credence? What fight do they have

766
00:37:25,760 --> 00:37:26,319
Speaker 3: to fight here?

767
00:37:27,480 --> 00:37:30,280
Speaker 15: So the basic argument for the planet is, as you described,

768
00:37:30,320 --> 00:37:34,400
Speaker 15: that the sites were designed to intentionally addict users, and

769
00:37:34,400 --> 00:37:37,000
Speaker 15: that the services are therefore liable for the harms that

770
00:37:37,120 --> 00:37:40,920
Speaker 15: resulted from that addiction. There's a lot of questions about that.

771
00:37:41,360 --> 00:37:44,440
Speaker 15: For example, we have to ask what does it even

772
00:37:44,440 --> 00:37:47,520
Speaker 15: mean to be quote addicted to a social media service.

773
00:37:47,600 --> 00:37:50,840
Speaker 15: There aren't medical or psychological definitions of that. But I

774
00:37:50,920 --> 00:37:53,439
Speaker 15: just have to talk about whether or not the services

775
00:37:53,440 --> 00:37:56,600
Speaker 15: caused the harms that the victims has suffered. There are

776
00:37:56,640 --> 00:38:00,600
Speaker 15: many causes of harms in people's lives, and so that

777
00:38:00,719 --> 00:38:04,560
Speaker 15: causation is going to be tricky for the playoffs as well.

778
00:38:04,640 --> 00:38:07,799
Speaker 2: Let's get Meta's response to these lawsuits in questions, right,

779
00:38:07,840 --> 00:38:11,640
Speaker 2: the company says that they don't reflect reality. The evidence

780
00:38:11,680 --> 00:38:15,799
Speaker 2: will show a company deeply and responsibly confronting tough questions

781
00:38:16,520 --> 00:38:20,360
Speaker 2: concerning research, listening to parents, academics and safety experts, etc.

782
00:38:21,200 --> 00:38:24,440
Speaker 2: That's the company's reaction. Actually, what's happening in response to

783
00:38:24,480 --> 00:38:29,520
Speaker 2: the wider issue is you see state by state, different

784
00:38:29,640 --> 00:38:34,480
Speaker 2: laws being enacted that are consistent with the complaints of

785
00:38:34,520 --> 00:38:39,279
Speaker 2: the plaintiffs. That's my read of it. Professor Goldman, is

786
00:38:39,320 --> 00:38:42,279
Speaker 2: that a sort of useful strategy towards a solution here?

787
00:38:43,960 --> 00:38:45,960
Speaker 15: I think you need to be careful about using the

788
00:38:46,000 --> 00:38:48,279
Speaker 15: term solution because in order for us to talk about that,

789
00:38:48,280 --> 00:38:50,440
Speaker 15: we have to be very precise about exactly what problem

790
00:38:50,440 --> 00:38:52,840
Speaker 15: we're trying to fix. There are a lot of problems

791
00:38:52,840 --> 00:38:55,759
Speaker 15: in our society, a lot of problems plaguing kids, and

792
00:38:55,920 --> 00:38:59,800
Speaker 15: there are also problems of over responding to the content

793
00:38:59,800 --> 00:39:02,600
Speaker 15: on line that looks a lot like censorship, and so

794
00:39:02,960 --> 00:39:05,399
Speaker 15: when we talk about solutions, we can't do that without

795
00:39:05,400 --> 00:39:08,160
Speaker 15: talking about the problems. Having said that, I think that

796
00:39:08,640 --> 00:39:11,400
Speaker 15: we're going to see a battle of experts in these trials,

797
00:39:11,680 --> 00:39:14,239
Speaker 15: where both sides are going to bring in the best

798
00:39:14,320 --> 00:39:16,759
Speaker 15: and brightest minds to tell their case to the jury.

799
00:39:16,800 --> 00:39:20,560
Speaker 15: We're going to hear from average Americans, essentially plucked off

800
00:39:20,600 --> 00:39:22,799
Speaker 15: the streets, who are going to weigh that evidence and

801
00:39:22,840 --> 00:39:24,640
Speaker 15: try and tell us whether or not they think there's

802
00:39:24,640 --> 00:39:26,280
Speaker 15: a problem here that needs to be addressed.

803
00:39:27,840 --> 00:39:28,280
Speaker 6: Professor.

804
00:39:28,520 --> 00:39:33,160
Speaker 2: In the course of proceedings throughout the trials, those that

805
00:39:33,600 --> 00:39:36,960
Speaker 2: are kind of trying to come to a decision in them,

806
00:39:37,320 --> 00:39:41,000
Speaker 2: those presiding over the case, to what degree do they

807
00:39:41,000 --> 00:39:44,439
Speaker 2: have expertise in the technicalities behind this?

808
00:39:45,800 --> 00:39:49,960
Speaker 15: So ideally the jury doesn't have any direct expertise they're

809
00:39:49,960 --> 00:39:52,200
Speaker 15: bringing in. The idea is that that's not what they're

810
00:39:53,600 --> 00:39:55,799
Speaker 15: being asked to do. They're going to be presented with

811
00:39:55,840 --> 00:39:59,000
Speaker 15: evidence from experts that have been chosen by the parties,

812
00:39:59,239 --> 00:40:03,400
Speaker 15: and they're supposed to to sift through that evidence, discuss it, evaluated,

813
00:40:03,560 --> 00:40:06,480
Speaker 15: and try to say which they find more convincing. So

814
00:40:06,760 --> 00:40:08,960
Speaker 15: in that sense, I think it's even better for us

815
00:40:09,000 --> 00:40:11,520
Speaker 15: that it's not a panel of express training side. It's

816
00:40:11,600 --> 00:40:14,280
Speaker 15: really a bunch of what we hope are well meaning

817
00:40:14,320 --> 00:40:18,000
Speaker 15: Americans who are there to just tell us. I'm not

818
00:40:18,040 --> 00:40:19,759
Speaker 15: going to respond to the hype. I'm not going to

819
00:40:19,840 --> 00:40:22,200
Speaker 15: listen to the critics and the media, or the playoffs

820
00:40:22,239 --> 00:40:25,320
Speaker 15: lawyers and the politicians per se. I'm going to listen

821
00:40:25,320 --> 00:40:26,000
Speaker 15: to the evidence.

822
00:40:28,000 --> 00:40:30,879
Speaker 2: Eric Goldman of Santa Clara University School of Law, thank

823
00:40:30,920 --> 00:40:32,680
Speaker 2: you very much for your time. Now coming up on

824
00:40:32,719 --> 00:40:35,480
Speaker 2: the show, Lift's earnings are out later today, We're going

825
00:40:35,520 --> 00:40:38,239
Speaker 2: to preview see what to expect that's next.

826
00:40:38,239 --> 00:40:39,320
Speaker 6: This is Boomberg Tech.

827
00:40:52,000 --> 00:40:54,719
Speaker 3: Lift earnings. They're out after the bell today and less

828
00:40:54,719 --> 00:40:57,520
Speaker 3: than a week after rival Uber kind of disappointed investors

829
00:40:57,560 --> 00:40:59,400
Speaker 3: with its profit outlook. Let's talk about what we can

830
00:40:59,440 --> 00:41:02,480
Speaker 3: expect from with bluem Meg's gig economy reports and Natalie Land,

831
00:41:02,760 --> 00:41:05,840
Speaker 3: we are expecting pretty healthy growth bookings right for the

832
00:41:05,840 --> 00:41:06,600
Speaker 3: fiscal court.

833
00:41:06,440 --> 00:41:10,120
Speaker 9: To just gone yes. If Uber's earning towards any guide.

834
00:41:10,640 --> 00:41:13,279
Speaker 9: They posted pretty strong for Q and Lyft is also

835
00:41:13,360 --> 00:41:17,040
Speaker 9: expected to post pretty strong growth there, one of the

836
00:41:17,080 --> 00:41:19,520
Speaker 9: strongest growths we've seen in nearly two years.

837
00:41:20,680 --> 00:41:24,360
Speaker 2: Natalie Uber used its earnings to position itself structurally and

838
00:41:24,400 --> 00:41:27,880
Speaker 2: from a personnel perspective for its robotaxi era. You know,

839
00:41:27,920 --> 00:41:30,040
Speaker 2: we've spent a lot of time with Lyft, who plan

840
00:41:30,160 --> 00:41:32,359
Speaker 2: to do the same. Right, what do we expect them

841
00:41:32,400 --> 00:41:34,520
Speaker 2: to communicate in earnings in that respect?

842
00:41:35,719 --> 00:41:38,480
Speaker 9: Lyft is going to row out avs in a couple

843
00:41:38,520 --> 00:41:41,919
Speaker 9: of cities this year, as they announced last year. Those

844
00:41:41,960 --> 00:41:46,319
Speaker 9: are Dallas in Nashville. So we might hear some of

845
00:41:46,360 --> 00:41:50,359
Speaker 9: their royal plans today and also hear them talk about

846
00:41:50,400 --> 00:41:55,359
Speaker 9: how their you know, fleet operations units subsidiary flags Drive

847
00:41:55,719 --> 00:41:56,440
Speaker 9: might help with that.

848
00:41:57,239 --> 00:41:59,960
Speaker 3: And Dave Richard and the team of late have really

849
00:42:00,080 --> 00:42:02,000
Speaker 3: got the memo that they need to go global. They've

850
00:42:02,000 --> 00:42:04,239
Speaker 3: been making m and a. How is that speaking to

851
00:42:04,239 --> 00:42:05,399
Speaker 3: the growth opportunity here?

852
00:42:05,920 --> 00:42:08,080
Speaker 9: So the fourth quarter would be the first full quarter

853
00:42:08,120 --> 00:42:10,759
Speaker 9: where they take into account the European business Free Now,

854
00:42:10,760 --> 00:42:13,200
Speaker 9: which is the taxi app in Europe that they acquired

855
00:42:13,239 --> 00:42:15,759
Speaker 9: last year, so they might get a boost there. And

856
00:42:15,840 --> 00:42:18,600
Speaker 9: they've also acquired this chauffeuring business which is like this

857
00:42:18,760 --> 00:42:21,719
Speaker 9: high end rides type which could also vote well for

858
00:42:21,760 --> 00:42:22,680
Speaker 9: the bottom line.

859
00:42:23,760 --> 00:42:25,640
Speaker 2: Did Lift to actually do anything in the Court of

860
00:42:25,680 --> 00:42:27,320
Speaker 2: Natalie that you kind of think might give them a

861
00:42:27,320 --> 00:42:29,080
Speaker 2: little bit of a boost. Is there anything that they've

862
00:42:29,160 --> 00:42:32,160
Speaker 2: already announced so we think they'll show traction on So.

863
00:42:32,239 --> 00:42:35,000
Speaker 9: Last year was a big year for their silver product,

864
00:42:35,040 --> 00:42:39,640
Speaker 9: which is aimed at elderly users. They simplified their app

865
00:42:40,080 --> 00:42:42,719
Speaker 9: interface for users, so there could be a boost in

866
00:42:42,880 --> 00:42:46,279
Speaker 9: rider base there. There also boosts a lot of their partnerships.

867
00:42:46,320 --> 00:42:49,840
Speaker 9: In November, they announced a partnership with United Air letting

868
00:42:49,840 --> 00:42:52,800
Speaker 9: people earn miles if they'd connect their accounts with Lift,

869
00:42:53,000 --> 00:42:57,239
Speaker 9: so that might attract more businesses there on airport rides too.

870
00:42:58,239 --> 00:43:00,839
Speaker 3: How are they in terms of scale versus I mean,

871
00:43:00,880 --> 00:43:03,480
Speaker 3: at the moment analysts really like the stop fifteen of

872
00:43:03,520 --> 00:43:06,719
Speaker 3: them say by only two say sell? But is it

873
00:43:07,000 --> 00:43:09,320
Speaker 3: a lightful like comparison here? Are they always going to

874
00:43:09,360 --> 00:43:10,040
Speaker 3: be the second film?

875
00:43:10,600 --> 00:43:14,800
Speaker 9: Yeah? Like lifts business is you know thirty or twenty

876
00:43:14,800 --> 00:43:18,120
Speaker 9: to thirty percent market share in the US, and they

877
00:43:19,080 --> 00:43:21,799
Speaker 9: they're just starting with their global expansion compared to Uber,

878
00:43:21,840 --> 00:43:24,000
Speaker 9: which is already in more than you know, thirty countries,

879
00:43:24,440 --> 00:43:26,440
Speaker 9: and so there's still a lot of catch up there.

880
00:43:26,680 --> 00:43:29,560
Speaker 9: But we know Lyft is on track with their three

881
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Speaker 9: year targets too.

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Speaker 6: Bloomberg's natally lunk thank you very much.

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Speaker 2: I mean the earnings in the moment carries Spotify on

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Speaker 2: track for their best day in about seven years. Thirty

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Speaker 2: eight million subscribers added called it gone seven hundred and

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Speaker 2: fifty one million total. It was all about the unwrapped

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Speaker 2: my average age thirty seven year old listener.

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Speaker 3: Apparently, I think I pipped you to the post with

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Speaker 3: a thirty two year old listener, but I thank my

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Speaker 3: kids for that.

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Speaker 4: That does it for this edition of Bloomberg Tech.

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Speaker 2: Check out the pod. You know where to find it.

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Speaker 6: This is Bloomberg