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

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

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Speaker 1: and Va Low in San Francisco.

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Speaker 2: This is Bloomberg Tech coming up. Open ai is close

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Speaker 2: to finalizing the first phase of a new funding round

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Speaker 2: that could bring in more than one hundred billion dollars plus.

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Speaker 2: Mark Zuckerberg testified in a landmark social media trial and

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Speaker 2: said it is quote very difficult to enforce Instagram's age limits,

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Speaker 2: and the DOJ is taking a closer look at the

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Speaker 2: potential impact of a sale of Warner Brothers Discovery on

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Speaker 2: theater chains. We'll get the reaction from Netflix co CEO

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Speaker 2: Ted Sarandos at twelve thirty pm Eastern right here on Bloomberg.

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Speaker 3: Okay, let's get to the top story.

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Speaker 2: Open ai is close to finalize the first phase of

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Speaker 2: new funding that could bring in more than one hundred

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Speaker 2: billion dollars, according to sources, that could boost its valuation

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Speaker 2: to eight hundred and fifty billion dollars post money. The

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Speaker 2: first round of strategic investors include AI heavy hitters Amazon, SoftBank, Nvidia,

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Speaker 2: and Microsoft and Overnight. When we broke this story in Japan, trading,

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Speaker 2: SoftBank jumps as much as four percent end the up

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Speaker 2: closing down up sorry, two point six percent. I think

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Speaker 2: the usadrs are actually a little softer team effort that

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Speaker 2: led the way by Bloomberg, Surrey and Gafari, who's been

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Speaker 2: tracking this story for a little while. Now, I think

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Speaker 2: let's get into the details, right. It isn't that straightforward

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Speaker 2: to understand, so let's call it phase one, the strategic investors.

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Speaker 3: What do we need to know?

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Speaker 4: So phase one are the major companies that are going

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Speaker 4: to be partners investors in open AI. So names like Amazon,

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Speaker 4: which as we've reported, could invest up to fifty billion,

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Speaker 4: SoftBank up to thirty You also have Microsoft in Nvidia

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Speaker 4: and others. So that is the first kind of part

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Speaker 4: of this round, securing those allocations, and that could come

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Speaker 4: as soon as the end of this month. Then they'll

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Speaker 4: move on to the vcs, sovereign wealth funds and other

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Speaker 4: financial investors.

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Speaker 2: Yeah, I think you know the sources that I've been

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Speaker 2: speaking to in that next bucket, the sovereigns. The bench

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Speaker 2: CAFEUS is probably a line around the corner, so to speak,

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Speaker 2: of people who want an allocation. Here, there's some interesting

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Speaker 2: detail that I want to get to with you. So

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Speaker 2: like Amazon, for example, a first time investment at that

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Speaker 2: scale super interesting. But also there's some kind of technology

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Speaker 2: agreement as part of this, right.

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Speaker 3: That's right.

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Speaker 4: So part of the deal, as we reported, is that

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Speaker 4: this will involve an expansion of Opening Eyes partnership with

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Speaker 4: Amazon on using their cloud compute to run Opening Eyes products,

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Speaker 4: as well as the chips Amazon Trainingum chips to be

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Speaker 4: used in Opening Eyes development.

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Speaker 2: I think it's also important to be sort of transparent

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Speaker 2: with the audience. These numbers have moved around a little bit, right,

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Speaker 2: and so particularly like some of our reporting on what

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Speaker 2: the pre money valuation would be, how we're kind of

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Speaker 2: getting to that post money valuation of eight hundred and

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Speaker 2: fifty billion dollars. Again, just give us the specifics that

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Speaker 2: we need to know.

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Speaker 4: Sure, there's been a lot of numbers out there, and

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Speaker 4: of course with a deal this big that's been in

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Speaker 4: talks for months, right, things kind of can shift. But

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Speaker 4: you might have heard the seven hundred and thirty billion

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Speaker 4: number in terms of open AI's potential valuation in this round,

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Speaker 4: that is still the you know, as far as we

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Speaker 4: know it today. The pre money valuation being discussed for

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Speaker 4: open a eye. But with around this big once you

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Speaker 4: add in that money, obviously the post money valuation could

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Speaker 4: go up significantly. So what we're hearing is now that

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Speaker 4: once you add up all the you know, strategics, which

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Speaker 4: could easily top one hundred if things go well, and

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Speaker 4: then you have the financial investors, you could get to

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Speaker 4: that eight fifty post money valuation.

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Speaker 2: I just want to point out to the audience that

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Speaker 2: all of the companies we've mentioned either declined to comment

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Speaker 2: or didn't respond to our request for comment. And for

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Speaker 2: what it's worstren Overnight Bloomberg Seslan that Amin spoke to

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Speaker 2: Chris Lahane and put it to him our reporting about

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Speaker 2: this round, and he didn't answer the question. Frankly, what

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Speaker 2: is consistent is the broader context. Open ai has said

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Speaker 2: for a little while it's compute constrained, and in other words,

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Speaker 2: you know, if it had more access to compute, we

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Speaker 2: know about its ambitions to build more infrastructure, it could

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Speaker 2: do more things, It could release more products, it could

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Speaker 2: broaden API access, et cetera. Paint a little bit more

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Speaker 2: of a picture for us in that respect.

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Speaker 4: Yeah, if you think about it, open ai has hardware ambitions.

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Speaker 4: They have to build out all these data centers that

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Speaker 4: they promised with stargate. They have to go and train

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Speaker 4: these models that become bigger and bigger in terms of

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Speaker 4: the amount of compute needed to get to what they

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Speaker 4: want to you know, call it agi right, So I

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Speaker 4: think that there's there's obviously a lot of room for

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Speaker 4: them to expand and go beyond just chat GPT into

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Speaker 4: other business lines. With this as well as just this,

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Speaker 4: there's this fierce horse race to make the next big model.

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Speaker 5: They have the anthropic Google Xai.

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Speaker 4: Everyone is going after the same price here, so they

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Speaker 4: need to be constantly investing in the best development to

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Speaker 4: get a had and stay ahead.

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Speaker 2: Bloombag Shrien Gafari, thank you very much. Sticking with open ai,

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Speaker 2: the Chat GBT maker is partnering with Tata Group and

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Speaker 2: its tech services arm Tata Consultancy Services on a massive

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Speaker 2: deal that could then could speed up open AI's enterprises option.

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Speaker 2: As part of the deal, TCS will develop a one

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Speaker 2: hundred megawatt data center that may be expanded to one gigawa.

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Speaker 3: Tata would also.

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Speaker 2: Infuse Ai throughout its operations, and the pair will work

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Speaker 2: together to build agentic solutions for specific industries. The deal

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Speaker 2: was announced while Open AI CEO Sam Altman was in

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Speaker 2: New Delhi for the India AI Summit, where he told

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Speaker 2: the crowd early visions and versions of artificial general intelligence

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Speaker 2: may not be far off.

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Speaker 6: India's largest democracy is well positioned to lead an AI,

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Speaker 6: not just to build it, but to shape it and

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Speaker 6: decide what our future is going to look like. And

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Speaker 6: it's important to move quickly on our current trajectory. We

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Speaker 6: believe we may be only a couple of years away

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Speaker 6: from early versions of true superintelligence.

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Speaker 2: Altman wasn't the only tech leader making that kind of prediction.

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Speaker 2: Demisa Sabis, head of Google Deep Mind, said AGI could

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Speaker 2: be five years away. And if having all these AI

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Speaker 2: leaders in one place singing the praises of the technology

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Speaker 2: was giving you the impression of unity, think again. There

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Speaker 2: was this moment when former colleagues turned rivals Sam Altman

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Speaker 2: and Anthropic CEO Dario Amoday awkwardly refuse to clasp.

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Speaker 3: One another's hands.

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Speaker 2: It happened during a photo op orchestrated by India's Prime

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Speaker 2: Minister Neurendromodi.

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Speaker 3: Okay.

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Speaker 2: As trees race to keep pace with the AI boom,

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Speaker 2: investors are increasingly turning to energy as the next big opportunity.

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Speaker 2: Tortures Capital Senior portfolio manager Rob Dummel joins us now,

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Speaker 2: and actually, you know, let's go back to the top story.

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Speaker 2: You know, a one hundred billion dollar or more rounds

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Speaker 2: from open AI where the lead investors are Amazon, SoftBank,

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Speaker 2: Microsoft and Nvidia. You know where that capital is going

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Speaker 2: to go, right in terms of infrastructure as somebody that

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Speaker 2: is trying to seize the opportunity in the energy sector

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Speaker 2: supporting that build out.

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Speaker 3: Your reaction to the reporting, Yeah.

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Speaker 5: Thanks for having me.

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Speaker 7: So when we look at that at Tortoise, and we've

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Speaker 7: been focused on infrastructure for a long time, and when

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Speaker 7: we see more capital going into AI, you know who

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Speaker 7: who's going to win out of that? Well, AI fundamentally

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Speaker 7: it's two things. It's data and it's and it's energy.

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Speaker 7: And so so we created an AI Infrastructure Fund here

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Speaker 7: at Tortoise. It's an active ETF that focus is on

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Speaker 7: the data infrastructure. So, so who's going to win from perspective?

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Speaker 7: You need more data storage, right, you need you need

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Speaker 7: more cabling, you need more liquid cooling. So the companies

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Speaker 7: that provide that to the data centers, and you're gonna

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Speaker 7: need more data centers as you highlight them, and you're

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Speaker 7: gonna build more of those. Those are the companies that

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Speaker 7: are gonna going to benefit from from this hundred billion

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Speaker 7: dollars of spend. Now, you also need energy, you need electricity, right,

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Speaker 7: and so's that's where the electrification infrastructure is going to

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Speaker 7: be really important. And so companies that have electric generation

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Speaker 7: in the areas where these data centers are going to

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Speaker 7: be built are going to win as well.

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Speaker 3: Rob.

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Speaker 2: Earlier this week, I had an extended conversation with Mary Daily,

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Speaker 2: president of the Federal Reserve Bank of San Francisco, very

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Speaker 2: focused on I guess the inflationary impact of what's happening

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Speaker 2: in the data center build out, the argument that the

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Speaker 2: hyperscale is PG and E right. The utility in Northern

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Speaker 2: California argue is it will lower electricity prices at the

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Speaker 2: wholesale level because those those mega cap tech names take

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Speaker 2: on the capital burden of modernizing the grid, but also

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Speaker 2: you know, paying up front.

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Speaker 3: Could you just weigh in on that.

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Speaker 7: Yeah, No, I think it's an absolutely valid point. Is

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Speaker 7: something we all need to keep our eye on. And

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Speaker 7: Mary has some great points, and you have some great

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Speaker 7: points as well. There's some really innovative solutions that are happening.

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Speaker 7: And right now, you know, we're investing in a company

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Speaker 7: like Williams Companies, who owns the largest natural gas pipeline

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Speaker 7: network in the US. They're actually helping to try to

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Speaker 7: reduce retail electricity prices by building electric generation to support

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Speaker 7: AI data center buildouts. But the contracts that they have

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Speaker 7: are between Williams, who's going to build electric generation, and

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Speaker 7: the Hyperscalers basically ultimately. And so why does that matter?

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Speaker 7: It matters because that from a cost perspective, the cost

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Speaker 7: of that electricity generation to develop AI is going to

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Speaker 7: be put upon the Hyperscalers, not the retail consumer, not

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Speaker 7: the retail electricity provider, whether you're in California or Texas

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Speaker 7: or where I am in Kansas City. And so you're

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Speaker 7: seeing a lot of those innovative solutions start to happen

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Speaker 7: and that but the goal is to not have this

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Speaker 7: AI build out and to win the AI race, We're

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Speaker 7: going to need a lot of electricity, but not have

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Speaker 7: that be paid for by the retail consumer and as

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Speaker 7: a result, have inflation rise because of that. The goal

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Speaker 7: is to have the Hyperscalers pay for that, and there's

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Speaker 7: multiple innovative solutions that are resulting in.

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Speaker 2: That Open ai raising more than one hundred billion dollars,

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Speaker 2: are going to go back to it with this kind

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Speaker 2: of bigger goal of a trillion dollars of commitments. Right,

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Speaker 2: you know if you try and top them all up,

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Speaker 2: how much of a risk is it that the center

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Speaker 2: of what's happening there is just this sort of single entity.

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Speaker 2: I'm not necessarily talking about circular financing. I'm talking about

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Speaker 2: the build out. The main tenant of that being one

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Speaker 2: single company. And of course you know Amthropic and an

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Speaker 2: xai and Google will factor into that, but increasingly it's

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Speaker 2: open AI and everything.

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Speaker 7: Yeah, I think we're going to world at autonomous everything, right,

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Speaker 7: and so and and and we'll see where that where

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Speaker 7: that ends up. Look, I have a lot of confidence

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Speaker 7: and you know, you you give the tech tools to

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Speaker 7: to the tech experts and what can they do? And

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Speaker 7: we've already seen it's been incredible in terms of the

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Speaker 7: opportunities in AI. And we're if you think about it,

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Speaker 7: we're just getting started. I mean as far as what

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Speaker 7: what opportunities there are for agenic AI and and and

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Speaker 7: other ways, Right, whether it's healthcare or or education or

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Speaker 7: just every area in our lives is going to be

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Speaker 7: impacted over the next several decades. And and so the

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Speaker 7: technology is there, we just need to get the energy there,

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Speaker 7: and we need to get the electricity consistent.

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Speaker 2: So how great is the risk that the supply of

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Speaker 2: energy will not catch up with where demand is currently

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Speaker 2: and where it will be.

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Speaker 7: Well, Look, I've been investing in the energy sector for

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Speaker 7: thirty years, and you know, you give these energy sectors,

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Speaker 7: this sector a challenge, and it always steps up to

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Speaker 7: the to the plate. And and I do think that

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Speaker 7: the sector will and and so so there are plans

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Speaker 7: in plays to continue to expand the US electricity grid.

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Speaker 7: And if you do that you mentioned earlier your discussion yesterday,

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Speaker 7: you can you can make the grid more reliable and

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Speaker 7: so so we I don't think there's gonna be a

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Speaker 7: big risk of that.

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Speaker 2: Actually, let me ask you just really quickly, Elon Musk

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Speaker 2: has this target of one hundred gig or what's of

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Speaker 2: solar capacity in this country?

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Speaker 3: Is that achievable?

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Speaker 7: Rob Well, I think you're gonna need all of the

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Speaker 7: above approach to meet that. So you're gonna need solar,

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Speaker 7: You're gonna need win. You're gonna need hydro, we're gonna

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Speaker 7: need nuclear. Obviously, we're gonna need more natural gas. And

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Speaker 7: so we've got to the US has got an advantage

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Speaker 7: and it's gonna win this global AI race because it

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Speaker 7: can provide low cost electricity. It's going to do that

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Speaker 7: by this all of the above approach that includes solar, wind, nuclear,

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Speaker 7: natural gas, and and and frankly, probably a little bit

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Speaker 7: of call as well.

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Speaker 2: Rob bunld Sours's Capital. Great to have you back on

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Speaker 2: the show, Thank you very much. Now coming up, door

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Speaker 2: Dash serves up a first quarter growth forecast. We break

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Speaker 2: down the food delivery giants latest earnings.

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Speaker 3: Next, this is Bloomberg Tech.

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Speaker 2: New York Governor Kathi HOCl has pulled a proposal that

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Speaker 2: would have allowed for commercial robo taxi services outside New

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Speaker 2: York City. This comes as a blow to Alphabet's Weimo,

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Speaker 2: which is looking to aggressively expand its driverless fleet this year.

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Speaker 2: A Waymos spokesperson said the company will work with the

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Speaker 2: state legislature to advance the issue and bring its service

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Speaker 2: to New York. That story was broken by our Consumer

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Speaker 2: Apps and Gig Economy reporter Natalie Lung, who joins us

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Speaker 2: now to break down some of the other earnings on

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Speaker 2: her beat, and you've been busy. I'm looking at shares

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Speaker 2: with door Dash up around six percent or five percent

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Speaker 2: right now. They had been as high as seven percent,

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Speaker 2: on track for their best day since April last year.

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Speaker 2: Company issuing a first quarter order growth forecast that tops estimates.

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Speaker 2: The food delivery platform beat estimates on gross order volume.

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Speaker 2: In the fourth quarter, earnings and revenues missed expectations. I

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Speaker 2: guess the way look at actually, if you take the

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Speaker 2: lid off the food type ofware in the delivery bag,

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Speaker 2: what's the story with door Dash here?

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Speaker 8: So the demand for on demand delivery is very strong,

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Speaker 8: as evidenced by Dordash's strong growth order forecast for the

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Speaker 8: first quarter, and then follows sort of the strong demand

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Speaker 8: out of that uber head earlier this month. But the

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Speaker 8: bigger story here for DoorDash is their investments into some

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Speaker 8: of the new products, including the UK business they acquired,

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Speaker 8: as well as like a back end system upgrade that

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Speaker 8: they're talking about to reconcile all of these new businesses

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Speaker 8: they've been building and acquired.

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Speaker 2: So the back end system upgrade is really interesting. Whenever

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Speaker 2: executives from the company come on the show. They always

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Speaker 2: talk about how good they are at software, in particular,

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Speaker 2: what is it that they're rebuilding here.

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Speaker 8: Yeah, so last year they went on this you know,

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Speaker 8: multi billion acquisition spree, including UK's Delivery, and earlier a

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Speaker 8: few years ago they acquired the Eastern Eastern European delivery

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Speaker 8: business Volte. And so now they have these three different

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Speaker 8: apps DoorDash, Volte and Delivery, and they all worked on

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Speaker 8: different systems, and so the CEO, Tony su wants all

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Speaker 8: these systems to work on the same platform so that

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Speaker 8: engineers can work on the same projects and analytics teams

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Speaker 8: can look at the same common data sets. And so

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Speaker 8: he says this is a painful but necessary exercise to

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Speaker 8: conduct this year, and they are having to invest a

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Speaker 8: lot into it that could weigh on profits.

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Speaker 2: You've also been looking at booking holdings stock down, you know,

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Speaker 2: relatively significantly. I don't know if some analysts are saying,

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Speaker 2: like global travel seems strong, that's supporting them. Others are

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Speaker 2: debating and questioning their growth forecast to interpret that.

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Speaker 3: What do you see?

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Speaker 8: So it's actually a similar story there in bookings. They

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Speaker 8: are it's going to be a big year for reinvestments

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Speaker 8: for them. Last year they talked about this transformation program

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Speaker 8: where they had to cut a few jobs and reorganize

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Speaker 8: some of their businesses, and now they're investing those savings

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Speaker 8: back into the company for AI. And they talked about

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Speaker 8: how customer service has been improved with AI, and so

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Speaker 8: there's always, you know, concerns or skepticism on how that

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Speaker 8: would play out for them.

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Speaker 2: Bloomberg's Natalie Lung terrific reporting all morning long. Thank you

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Speaker 2: very much. I just want to look at shares of Figma.

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Speaker 2: The company gave an annual revenue outlook that topped estimates

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Speaker 2: and it kind of eased Wall Streets anxiety over AI

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Speaker 2: threats to its own business.

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Speaker 3: It's up around seven percent, but.

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Speaker 2: Also, like I think, showed a lot of what it's

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Speaker 2: doing in the field of AI. Bloomberg's brody Ford is

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Speaker 2: on the other side of town from me, where it's

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Speaker 2: raining heavily. I've learned a lot this morning through your

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Speaker 2: reporting about what, on the face of its heres a

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Speaker 2: pretty boring term net dollar retention rate, but actually, like

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Speaker 2: if you kind of dig into it, it basically shows

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Speaker 2: Figma had a lot of existing customers it launched new products,

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Speaker 2: those existing customers were willing to pay for those new

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Speaker 2: products on top of what they already have.

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Speaker 9: That's exactly right, Yeah, and that's true that investors wanted

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Speaker 9: to see. I mean, Figma is one of these names

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Speaker 9: that's gotten caught up in the SaaS apocalypse, you know,

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Speaker 9: the fear that as it gets easier to build software,

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Speaker 9: these application leaders aren't going to have the pricing power

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Speaker 9: they once did. But Figma showed us they did because

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Speaker 9: on average, if I gave them a dollar last year,

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Speaker 9: I'm giving them a dollar thirty five this year. And

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Speaker 9: so that clearly shows that the amount of products customers

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Speaker 9: are buying is expanding.

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Speaker 2: We kind of zeroed in on by the way we're

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Speaker 2: showing the shares kind of over a longer time period

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Speaker 2: since the IPO in July of last year, down twenty

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Speaker 2: two percent. Basically, Pigma Make they basically said, like, here's

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Speaker 2: an AI tool that we have.

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Speaker 3: It is growing. What do we need to know?

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Speaker 8: Right?

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Speaker 9: Pigma Make is essentially the you type in a prompt

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Speaker 9: and it kind of gives you a pretty good app right.

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Speaker 9: I mean, it's in the vibe coding realm, and that

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Speaker 9: matters because there's a lot of these startups like Bolt

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Speaker 9: or Replet that problems to be able to vibe coaps

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Speaker 9: pretty well. And so it was really up to fig

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Speaker 9: O to show that, no, we are the incumbent here

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Speaker 9: and we're going to out innovate our peers. And you know,

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Speaker 9: at least last night they took a step towards convincing

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Speaker 9: the market of.

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Speaker 2: That doing those brody Ford terrific reporting. Thank you, Thank

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Speaker 2: you very much. A lot more coming up. Bike Dant

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Speaker 2: seems to compete with the world's leading US based AI

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Speaker 2: companies literally on their own turf. We have more on

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Speaker 2: that next. This is Bloomberg Tech. It's time for Talking

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Speaker 2: tech and first Start. The UK has proposed rules requiring

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Speaker 2: tech companies to remove abusive images within forty eight hours

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Speaker 2: all face fines of up to ten percent of global

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Speaker 2: revenue or even a UK service van. The move comes

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Speaker 2: amid investigations in Ireland, Spain and other countries over nonconsensual

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Speaker 2: undressed images created by Ex's AI Chatbotrock Plus Morgan Stanley's

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Speaker 2: cutting fees in half for clients trading private company shares

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Speaker 2: on its newly acquired equity Zen platform, charges for buyers

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Speaker 2: and sellers will be lowered to two point five percent

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Speaker 2: from five percent on most transactions, undercutting competitors as it

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Speaker 2: looks to take advantage of an expanding market. And finally,

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Speaker 2: Amazon has officially overtaken Walmart as the world's largest company

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Speaker 2: by revenue. The online retail giant posted seven hundred and

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Speaker 2: seventeen billion dollars in sales for twenty twenty five, edging

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Speaker 2: past Walmart's seven hundred and thirteen. A big driver of

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Speaker 2: that growth Amazon's cloud computing business AWS, and we.

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Speaker 3: Stripped that out. It's not quite apples to apples.

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Speaker 2: Another story, Chinese tech giant bike Dance is hiring in

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Speaker 2: the US for nearly one hundred open roles within its

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Speaker 2: Ai division. The push comes after it announced the deal

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Speaker 2: to sell parts of its US TikTok business to non

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Speaker 2: Chinese owners to address US national security concerns. Bloomberg's social

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Speaker 2: media report Alex Lavine has the story, let's stop cis like,

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Speaker 2: what are these roles?

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Speaker 3: Where are these roles?

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Speaker 10: The roles are mainly in California and Washington. We have

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Speaker 10: them across Los Angeles, San Jose, and Seattle, which are

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Speaker 10: all cities that TikTok also has offices in and I

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Speaker 10: think what's so fascinating about these AI roles is really

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Speaker 10: just how much they run the gamut. You've got roles

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Speaker 10: that are focused on producing international data to feed to.

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Speaker 11: Buy dances llms.

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Speaker 10: You've got roles doing research to make AI more human like.

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Speaker 10: And you've also got these really interesting roles building science

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Speaker 10: science models that are really looking for talent in biology, chemistry,

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Speaker 10: and physics. And these are more roles focused on helping

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Speaker 10: buy dance pursue drug discovery and development.

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Speaker 2: So the reason this is a notable story, right, you

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Speaker 2: just said that these roles will be in proximity to

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Speaker 2: or in US TikTok's offices, right, But the broader thing is,

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Speaker 2: you know, Chinese parent hiring for roles in the field

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Speaker 2: of AI in the UNI States national security competition take

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Speaker 2: us there.

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Speaker 10: To clarify, these not necessarily in the same as the

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Speaker 10: TikTok offices, but they are in the same cities where

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Speaker 10: TikTok has a large footprint. And as you just mentioned,

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Speaker 10: these are also cities where some of the leading American

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Speaker 10: AI companies also have a lot of a lot of

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Speaker 10: talent and their own footprint. I think what's so interesting

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Speaker 10: is that to this point in the US, we've really

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Speaker 10: thought about byte Dance as a social media company. It

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Speaker 10: is also a dominant AI company, and it really seems

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Speaker 10: that that has been a bit lost on the US

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Speaker 10: until now. And I think the turning point has really

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Speaker 10: been over the last week since by Dance unveiled some

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Speaker 10: new AI models for video generation for example, an image

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Speaker 10: generation that has really caught on and raised concern especially

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Speaker 10: from Hollywood.

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Speaker 11: In a very big way.

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Speaker 2: All right, Bloomberg z AlCH Slovine, it's a must read

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Speaker 2: report on the Bloomberg about byte Dance building out AI

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Speaker 2: teams in the US.

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Speaker 3: Coming up, we're going.

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Speaker 2: To discuss what Mark Zuckerberg had to say about teen

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Speaker 2: social media use when the metase A CEO testified in

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Speaker 2: a landmark trial. We have those details coming up next.

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Speaker 2: This is Bloomberg Tech.

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Speaker 3: Welcome back to Bloomberg Tech.

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Speaker 2: We're just going to take a quick look at where

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Speaker 2: financial markets are right now. We had a lot of

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Speaker 2: economic data to pass through the morning. Our market's team

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Speaker 2: on the Bloomberg terminal and on dot com are really

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Speaker 2: emphasizing the geopolitical risk that's out there, also ongoing concerns

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Speaker 2: about inflation then as that one hundred very tech heavy,

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Speaker 2: modestly lower down three tenths of a percent, chip stocks

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Speaker 2: taking a breather, down eight tenths of a percent, and

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Speaker 2: then Bitcoin now further blows sixty seven US thousand dollars

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Speaker 2: to can remember it's a shorter week in the United States.

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Speaker 2: It was a holiday on Monday, but bitcoin trades twenty

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Speaker 2: four to seven, and we came back from that holiday

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Speaker 2: weekend with Bitcoin under pressure. One headline, by the way,

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Speaker 2: Goldman Sat CEO David Solomon saying he owns a very

440
00:22:59,600 --> 00:23:02,359
Speaker 2: modest amount of bitcoin, but remember he's long been a

441
00:23:02,359 --> 00:23:05,679
Speaker 2: cryptoskeptic and that's not doing much to support the asset

442
00:23:05,760 --> 00:23:08,480
Speaker 2: either way. We'll keep you posted. Another top story today,

443
00:23:08,520 --> 00:23:11,520
Speaker 2: Meta CEO Mark Zuckerberg took to the stand in the

444
00:23:11,600 --> 00:23:15,439
Speaker 2: Landmark social media addiction trial. Bloomberg's Riley Griffin was in

445
00:23:15,480 --> 00:23:18,760
Speaker 2: the courtroom for that testimony. And look, we were building

446
00:23:18,840 --> 00:23:22,520
Speaker 2: up to this on the program throughout the week. Take

447
00:23:22,600 --> 00:23:25,280
Speaker 2: us through the lines of questioning, and I guess the

448
00:23:25,280 --> 00:23:28,040
Speaker 2: top line of what mister Zuckerberg had to say in

449
00:23:28,080 --> 00:23:29,400
Speaker 2: response to those questions.

450
00:23:30,960 --> 00:23:32,040
Speaker 5: Yeah, ed, great question.

451
00:23:32,119 --> 00:23:34,879
Speaker 12: It was an intense day here in Los Angeles, and

452
00:23:34,960 --> 00:23:38,320
Speaker 12: yesterday we saw Mark Zuckerberg testify to a number of things.

453
00:23:39,600 --> 00:23:44,160
Speaker 12: Questions about company documents that showed that Meta had been

454
00:23:44,240 --> 00:23:49,320
Speaker 12: focused on increasing time spent among young users. Questions about

455
00:23:49,480 --> 00:23:53,359
Speaker 12: the under thirteen demographic on the platform. Despite policies that

456
00:23:53,400 --> 00:23:56,280
Speaker 12: suggest they're not allowed to be, there still millions of

457
00:23:56,320 --> 00:24:00,639
Speaker 12: Americans under that age on the platform. Questions about decisions

458
00:24:00,680 --> 00:24:04,240
Speaker 12: he personally made regarding beauty filters. All of this came

459
00:24:04,280 --> 00:24:07,119
Speaker 12: to a head with him on the stand at times

460
00:24:07,200 --> 00:24:12,240
Speaker 12: rather uncomfortable, very subdued. He did score a couple of

461
00:24:12,280 --> 00:24:16,000
Speaker 12: wins here and there, but overall the picture was painted

462
00:24:16,080 --> 00:24:18,480
Speaker 12: of a company that made deliberate.

463
00:24:21,400 --> 00:24:25,199
Speaker 5: Could be user of health the youngest users.

464
00:24:26,040 --> 00:24:26,240
Speaker 3: Right.

465
00:24:26,720 --> 00:24:30,280
Speaker 2: You know, Instagram does have age limits and other tools

466
00:24:30,280 --> 00:24:33,840
Speaker 2: that already exist, and mister Zuckerberg basically splained it was

467
00:24:33,920 --> 00:24:36,440
Speaker 2: very difficult to enforce them. Did he go a step

468
00:24:36,480 --> 00:24:39,120
Speaker 2: for over and explain why it's difficult to enforce them.

469
00:24:39,400 --> 00:24:41,120
Speaker 2: I think he also talked a little bit about other

470
00:24:41,160 --> 00:24:43,919
Speaker 2: tools that they are being let's say proactive on.

471
00:24:45,600 --> 00:24:45,879
Speaker 3: Yeah.

472
00:24:45,920 --> 00:24:48,919
Speaker 12: So one of the cases that mister Zuckerberg made was

473
00:24:48,960 --> 00:24:52,720
Speaker 12: to say that for the youngest users, particularly those without

474
00:24:52,840 --> 00:24:56,480
Speaker 12: driver's license, it's really hard to verify age. He took

475
00:24:56,480 --> 00:24:58,560
Speaker 12: a line that has come up a lot these days,

476
00:24:58,600 --> 00:25:02,120
Speaker 12: particularly in lobbying afforts, which is to say that phonemakers

477
00:25:02,200 --> 00:25:04,840
Speaker 12: like Apple should do a little bit more to help.

478
00:25:04,680 --> 00:25:06,600
Speaker 5: With that age verification process.

479
00:25:07,480 --> 00:25:12,119
Speaker 12: In fact, an email was brought forth by Meta's defense

480
00:25:12,880 --> 00:25:14,800
Speaker 12: to show that he had made efforts to reach out

481
00:25:14,840 --> 00:25:17,720
Speaker 12: to Tim Cook in the past to look for efforts

482
00:25:18,119 --> 00:25:22,000
Speaker 12: that where they could collaborate on improving team safety.

483
00:25:22,119 --> 00:25:25,159
Speaker 5: So he said, it's an open secret.

484
00:25:25,240 --> 00:25:28,640
Speaker 12: They all know that many users are lying about their age.

485
00:25:29,440 --> 00:25:32,560
Speaker 12: The plaintiff's attorneys suggested that that Meta had not done

486
00:25:32,680 --> 00:25:35,520
Speaker 12: enough to enforce that, and there were some documents that

487
00:25:35,600 --> 00:25:38,439
Speaker 12: showed that Nick Klegg, for example, a former policy chief,

488
00:25:38,800 --> 00:25:42,560
Speaker 12: had said these policies were basically unenforceable and showed that

489
00:25:42,960 --> 00:25:45,919
Speaker 12: they weren't doing all that they could. So we saw

490
00:25:46,320 --> 00:25:48,840
Speaker 12: it go back and forth. But Mark Zuckerberg's take here

491
00:25:49,040 --> 00:25:53,600
Speaker 12: was that it's a really difficult challenge even as they

492
00:25:53,640 --> 00:25:58,160
Speaker 12: create proactive tools to remove under thirteen users and NICs.

493
00:25:58,240 --> 00:26:00,800
Speaker 2: Roddy Griffin, who is on the ground and will continue

494
00:26:00,840 --> 00:26:03,040
Speaker 2: to cover the trial, thank you very much. Let's discuss

495
00:26:03,320 --> 00:26:06,720
Speaker 2: the broader legal invocations of the case with Mary Anne Franks.

496
00:26:06,840 --> 00:26:10,200
Speaker 2: She's a professor at George Washington University Law School in

497
00:26:10,200 --> 00:26:14,120
Speaker 2: Intellectual Property, technology and Civil rights. And a moment ago,

498
00:26:14,200 --> 00:26:18,359
Speaker 2: the team was showing the data around what else is

499
00:26:18,400 --> 00:26:22,000
Speaker 2: happening in parallel with this specific trial? Right there are

500
00:26:22,040 --> 00:26:26,639
Speaker 2: three thousand such suits running in parallel. You also have

501
00:26:26,760 --> 00:26:31,720
Speaker 2: states attorneys general forty plus looking at this issue. But

502
00:26:31,840 --> 00:26:35,200
Speaker 2: in the here and now, with this specific legal proceeding,

503
00:26:36,000 --> 00:26:38,880
Speaker 2: could you just help us understand what is it question here?

504
00:26:39,520 --> 00:26:39,879
Speaker 3: Please?

505
00:26:41,920 --> 00:26:44,919
Speaker 13: The primary question that they're trying to address here is

506
00:26:45,280 --> 00:26:48,679
Speaker 13: are the harms that are being experienced by these plaintiffs?

507
00:26:48,680 --> 00:26:51,760
Speaker 13: And those are some really extensive and really serious ones,

508
00:26:51,840 --> 00:26:57,800
Speaker 13: including in some cases suicide, but depression, body anxiety, body dysmorphia.

509
00:26:58,080 --> 00:27:01,920
Speaker 13: Are these things attributable to the design of certain platforms

510
00:27:01,960 --> 00:27:05,480
Speaker 13: in particular things like Instagram and Facebook? And so really

511
00:27:05,480 --> 00:27:08,840
Speaker 13: the question is who is causing this harm? What is responsible?

512
00:27:09,240 --> 00:27:12,720
Speaker 13: Is it the content that these kids are seeking out

513
00:27:13,119 --> 00:27:15,480
Speaker 13: or is it the way that these platforms have designed

514
00:27:15,520 --> 00:27:19,119
Speaker 13: their tools and services to entice really vulnerable users to

515
00:27:19,160 --> 00:27:22,080
Speaker 13: stay on the platform for longer and longer periods of time.

516
00:27:23,720 --> 00:27:27,239
Speaker 2: It was mister Zuckerberg, who was giving testimony, and you know,

517
00:27:27,359 --> 00:27:31,199
Speaker 2: the I suppose top line of that testimony was that

518
00:27:31,280 --> 00:27:36,200
Speaker 2: it is difficult for Meta, in particular through the Instagram app,

519
00:27:36,600 --> 00:27:40,879
Speaker 2: to enforce what are existing rules. You know, how do

520
00:27:40,960 --> 00:27:45,359
Speaker 2: you feel that that argument will carry from him?

521
00:27:46,119 --> 00:27:49,040
Speaker 13: It's not really clear how well that's going to serve

522
00:27:49,160 --> 00:27:53,080
Speaker 13: I think the defense, because really what Zuckerberg seemed to

523
00:27:53,119 --> 00:27:55,760
Speaker 13: be reiterating was, well, we have all of these really

524
00:27:55,840 --> 00:27:58,760
Speaker 13: dangerous tools that we know can cause harm, and you know,

525
00:27:58,760 --> 00:28:00,359
Speaker 13: it's just really hard for us to keep them out

526
00:28:00,400 --> 00:28:02,320
Speaker 13: of the hands of certain individuals.

527
00:28:02,400 --> 00:28:04,640
Speaker 11: But that's just sort of accepting.

528
00:28:04,160 --> 00:28:06,920
Speaker 13: The premise that these kinds of products and services should

529
00:28:06,960 --> 00:28:10,600
Speaker 13: exist at all, and that it's just an intractable problem

530
00:28:10,640 --> 00:28:13,360
Speaker 13: about who's going to access them, when the question really

531
00:28:13,359 --> 00:28:15,480
Speaker 13: should be, you know, why are you creating these types

532
00:28:15,520 --> 00:28:18,320
Speaker 13: of features? What's the actual use of something like a

533
00:28:18,359 --> 00:28:20,440
Speaker 13: beauty filter that you know is going to be really

534
00:28:20,440 --> 00:28:23,119
Speaker 13: attractive to nine and ten year old girls. So I

535
00:28:23,160 --> 00:28:25,560
Speaker 13: think that he's very much trying to say, well, if

536
00:28:25,560 --> 00:28:27,719
Speaker 13: you assume a world where all of these things have

537
00:28:27,800 --> 00:28:30,480
Speaker 13: to exist, then it's really hard for us to control access.

538
00:28:30,600 --> 00:28:33,040
Speaker 13: That's true enough, but why do these things actually have

539
00:28:33,080 --> 00:28:34,040
Speaker 13: to exist.

540
00:28:34,320 --> 00:28:38,920
Speaker 2: We're showing a February eleventh statement from metas specifically tied

541
00:28:38,960 --> 00:28:41,800
Speaker 2: to this trial, and the back half of it says,

542
00:28:41,840 --> 00:28:46,240
Speaker 2: the evidence will show she a plaintiff, faced many significant

543
00:28:46,240 --> 00:28:50,120
Speaker 2: difficult challenges well before she ever used social media. I'm

544
00:28:50,120 --> 00:28:53,320
Speaker 2: just putting that that is Meta's statement. Prior to that

545
00:28:53,400 --> 00:28:56,440
Speaker 2: in November, you know, they had said they strongly disagree

546
00:28:56,440 --> 00:28:59,880
Speaker 2: with these allegations and confident the evidence will show our

547
00:29:00,040 --> 00:29:03,520
Speaker 2: longstanding commitment to supporting young people. I'm going to ask

548
00:29:03,600 --> 00:29:05,240
Speaker 2: the same question again in a slightly different way that

549
00:29:05,280 --> 00:29:08,560
Speaker 2: you have the CEO of the company defending what our

550
00:29:08,680 --> 00:29:12,960
Speaker 2: existing policies and practices, but explaining how difficult it.

551
00:29:12,960 --> 00:29:14,120
Speaker 3: Is to enforce them.

552
00:29:14,840 --> 00:29:19,160
Speaker 2: Would you just help us understand, you know, what pressure

553
00:29:19,160 --> 00:29:21,600
Speaker 2: will be put on him as the CEO of that company,

554
00:29:22,160 --> 00:29:25,200
Speaker 2: or what changes or what outcome the court could affect

555
00:29:25,760 --> 00:29:27,320
Speaker 2: how that company does business.

556
00:29:29,400 --> 00:29:31,800
Speaker 11: Yes, so a lot of things could happen at this point.

557
00:29:31,840 --> 00:29:35,120
Speaker 13: Because this isn't just about whether liability is found in

558
00:29:35,160 --> 00:29:38,840
Speaker 13: these particular cases. This is also the first moment that

559
00:29:38,880 --> 00:29:41,920
Speaker 13: we're really seeing the general public get a look at

560
00:29:41,960 --> 00:29:44,640
Speaker 13: what did Mark Zuckerberg know and when did he know it?

561
00:29:45,000 --> 00:29:47,800
Speaker 13: And so even if an individual cases, it's an uphill

562
00:29:47,880 --> 00:29:51,480
Speaker 13: battle to show absolute causation for these injuries. Now we've

563
00:29:51,480 --> 00:29:53,720
Speaker 13: got information in the hands of the public, in the

564
00:29:53,760 --> 00:29:57,040
Speaker 13: hands of regulators, in the hands of policymakers, and you've

565
00:29:57,080 --> 00:29:59,480
Speaker 13: already seen that this kind of attention is causing these

566
00:29:59,520 --> 00:30:02,680
Speaker 13: companies change some of their practices. So they've been giving

567
00:30:02,720 --> 00:30:05,520
Speaker 13: the kind of pr propaganda about how well we're doing

568
00:30:05,520 --> 00:30:06,040
Speaker 13: our best.

569
00:30:06,080 --> 00:30:07,280
Speaker 11: But it's really challenging.

570
00:30:07,720 --> 00:30:11,400
Speaker 13: But every time there's serious consequences that might loom over

571
00:30:11,560 --> 00:30:15,120
Speaker 13: these platforms, they do start making some changes, although usually

572
00:30:15,120 --> 00:30:16,680
Speaker 13: they're a little too little, too late.

573
00:30:18,280 --> 00:30:20,760
Speaker 2: We put in writing that this trial will run through

574
00:30:20,800 --> 00:30:23,120
Speaker 2: the end of March, and again it's in parallel with

575
00:30:23,160 --> 00:30:26,080
Speaker 2: a number of other legal proceedings that involve other parties.

576
00:30:26,960 --> 00:30:29,680
Speaker 2: How much does one trial influence all the others that

577
00:30:29,760 --> 00:30:31,720
Speaker 2: may happen after very quickly.

578
00:30:32,960 --> 00:30:35,160
Speaker 13: Quite a bit these This is a Bellweather trial, and

579
00:30:35,200 --> 00:30:37,400
Speaker 13: the entire reason why it's been chosen is because it's

580
00:30:37,440 --> 00:30:39,800
Speaker 13: supposed to give both parties a sense of how this

581
00:30:39,840 --> 00:30:41,800
Speaker 13: is going to play out. And so if it looks

582
00:30:41,800 --> 00:30:43,880
Speaker 13: as though things are going badly for the defense, that

583
00:30:43,920 --> 00:30:46,880
Speaker 13: could really have an effect on settlements and possibly agreements

584
00:30:46,920 --> 00:30:49,120
Speaker 13: going forward to have safer products and platforms.

585
00:30:49,960 --> 00:30:52,600
Speaker 2: Mary Anne Franks from George Washington University Law School, thank

586
00:30:52,600 --> 00:30:55,520
Speaker 2: you very much. What about the business impact? MINDA Smiley

587
00:30:55,640 --> 00:30:58,400
Speaker 2: c the analyst that eMarketer has been looking into teen

588
00:30:58,520 --> 00:31:01,080
Speaker 2: social media use and enjoy us now and again, going

589
00:31:01,120 --> 00:31:04,600
Speaker 2: back to mister Zuckerberg's testimony, his argument was that this

590
00:31:05,480 --> 00:31:10,200
Speaker 2: category or demographic is a small part of the Instagram business.

591
00:31:10,440 --> 00:31:12,440
Speaker 3: Does your research support that?

592
00:31:14,240 --> 00:31:15,920
Speaker 14: Yeah, I mean I think the reality is a little

593
00:31:15,960 --> 00:31:18,000
Speaker 14: bit murkier than that, right, I mean, I do think

594
00:31:18,040 --> 00:31:20,880
Speaker 14: he maybe has some points when he says they're not

595
00:31:20,960 --> 00:31:24,440
Speaker 14: a demographic is majorly monetized, and that they maybe don't

596
00:31:24,440 --> 00:31:26,400
Speaker 14: bring in a ton of ad revenue, but that does

597
00:31:26,400 --> 00:31:27,560
Speaker 14: not mean they're not significant.

598
00:31:27,600 --> 00:31:30,400
Speaker 5: I mean, when you look at our a Marketer data, we.

599
00:31:30,320 --> 00:31:33,440
Speaker 14: See that in the US at least about eleven percent

600
00:31:33,640 --> 00:31:36,680
Speaker 14: of Instagram users are under the age of eighteen, and

601
00:31:36,760 --> 00:31:40,760
Speaker 14: so again not a huge majority, but that's a significant percentage.

602
00:31:40,800 --> 00:31:43,640
Speaker 14: And also, I think, you know, the numbers tell one story,

603
00:31:43,640 --> 00:31:46,040
Speaker 14: but the reality is these platforms gain a lot by

604
00:31:46,120 --> 00:31:49,080
Speaker 14: you know, essentially hooking these users young because the younger

605
00:31:49,120 --> 00:31:50,840
Speaker 14: that they get on these platforms, the more likely they

606
00:31:50,880 --> 00:31:52,479
Speaker 14: are to continue using them in the future.

607
00:31:52,680 --> 00:31:54,960
Speaker 5: So again you can look at the numbers.

608
00:31:54,960 --> 00:31:56,600
Speaker 14: You can look at maybe how much they how much

609
00:31:56,640 --> 00:31:59,479
Speaker 14: revenue they're generating from teens per year, but really it's

610
00:31:59,480 --> 00:32:02,880
Speaker 14: about setting these behaviors early and benefiting in the long term.

611
00:32:03,840 --> 00:32:08,800
Speaker 2: Mister Zuckerberg stated that teams equate to one percent of revenue,

612
00:32:08,800 --> 00:32:13,720
Speaker 2: which I thought was an interesting data point. This question

613
00:32:14,360 --> 00:32:16,920
Speaker 2: about the future of Instagram in particular, but you know,

614
00:32:17,120 --> 00:32:20,280
Speaker 2: the other meta family of apps is well, what would

615
00:32:20,280 --> 00:32:22,960
Speaker 2: they change? You know, And part of the discussion in

616
00:32:23,000 --> 00:32:26,680
Speaker 2: the testimony was the tension on the rules they have

617
00:32:26,760 --> 00:32:29,640
Speaker 2: in place and the privacy of the individuals that are

618
00:32:29,680 --> 00:32:33,680
Speaker 2: signing up for them. Does that tension have any pairing

619
00:32:33,680 --> 00:32:35,280
Speaker 2: on how they do business going forward?

620
00:32:36,760 --> 00:32:39,400
Speaker 14: Yeah, I mean I think it's still really early to say,

621
00:32:39,480 --> 00:32:41,560
Speaker 14: but I mean, for sure, I think depending on how

622
00:32:41,560 --> 00:32:43,479
Speaker 14: these lawsuits play out, if they end up having to

623
00:32:43,560 --> 00:32:47,719
Speaker 14: fundamentally change how their platforms work, whether it's whether it's

624
00:32:47,760 --> 00:32:50,920
Speaker 14: the algorithms or AutoPlay and infinite scroll, whatever it might be,

625
00:32:51,280 --> 00:32:53,400
Speaker 14: that will in turn have an impact on how teenagers

626
00:32:53,520 --> 00:32:56,040
Speaker 14: use these platforms. And something we've noticed is that, you know,

627
00:32:56,360 --> 00:32:58,360
Speaker 14: it was interesting to see him really kind of downplay

628
00:32:58,400 --> 00:33:01,680
Speaker 14: to what extent meta is really prioritized time spent as

629
00:33:01,680 --> 00:33:04,000
Speaker 14: a metric when our numbers show and just you know,

630
00:33:04,240 --> 00:33:06,720
Speaker 14: paying attention to the company in general, and we know

631
00:33:06,760 --> 00:33:10,200
Speaker 14: that time spent is definitely a crucial metric for formata

632
00:33:10,240 --> 00:33:12,800
Speaker 14: and all social networks. And we have seen time spent

633
00:33:12,920 --> 00:33:17,000
Speaker 14: among teenagers specifically rise year over year on Instagram, and

634
00:33:17,040 --> 00:33:20,560
Speaker 14: so we do see that, you know, anything that would

635
00:33:20,600 --> 00:33:22,520
Speaker 14: kind of hi away that time spent if they would

636
00:33:22,520 --> 00:33:24,200
Speaker 14: have to make changes to the platform, what would have

637
00:33:24,200 --> 00:33:25,160
Speaker 14: an impact.

638
00:33:25,520 --> 00:33:29,080
Speaker 2: But your research shows that teams are spending significantly more

639
00:33:29,080 --> 00:33:32,760
Speaker 2: time on TikTok than on Instagram. I think I'm correct

640
00:33:32,800 --> 00:33:34,800
Speaker 2: in saying right. I just want to point out that

641
00:33:35,520 --> 00:33:39,600
Speaker 2: with this trial, TikTok and also Snap and not parties

642
00:33:39,640 --> 00:33:42,560
Speaker 2: to the case because they had settlements prior to it.

643
00:33:43,360 --> 00:33:46,680
Speaker 2: But if we look bigger picture at the industry, how

644
00:33:46,720 --> 00:33:49,320
Speaker 2: will these other players be looking at this trial, do

645
00:33:49,360 --> 00:33:49,720
Speaker 2: you think?

646
00:33:51,120 --> 00:33:51,320
Speaker 3: Yeah?

647
00:33:51,360 --> 00:33:53,520
Speaker 14: I mean I think they're all probably looking at it

648
00:33:53,600 --> 00:33:56,360
Speaker 14: through through a similar lens. I know YouTube is trying

649
00:33:56,400 --> 00:33:58,960
Speaker 14: to really make the case that it operates very differently

650
00:33:58,960 --> 00:34:01,720
Speaker 14: than than a meta than a TikTok than a snapchat,

651
00:34:01,800 --> 00:34:06,360
Speaker 14: and so I think, you know, that could potentially see see.

652
00:34:06,200 --> 00:34:07,640
Speaker 5: YouTube play out a little bit differently.

653
00:34:07,680 --> 00:34:11,240
Speaker 14: But I think in general, yes, especially a company like TikTok,

654
00:34:11,280 --> 00:34:14,200
Speaker 14: which is kind of you know, it's really equated with

655
00:34:14,280 --> 00:34:16,839
Speaker 14: teenage use. Right, A large part of why it became

656
00:34:16,880 --> 00:34:19,000
Speaker 14: so popular in the US in the first place was

657
00:34:19,040 --> 00:34:21,319
Speaker 14: because of young people, because of teenagers.

658
00:34:21,360 --> 00:34:23,799
Speaker 5: So and like as you said, yes, our figures do.

659
00:34:23,840 --> 00:34:26,920
Speaker 14: Show that teenagers spend a ton of time on TikTok,

660
00:34:26,960 --> 00:34:29,760
Speaker 14: definitely more than Instagram. Although we are see that seeing

661
00:34:29,760 --> 00:34:31,960
Speaker 14: that time spent you know, come down a little bit

662
00:34:32,000 --> 00:34:35,200
Speaker 14: year every year, which kind of suggests that TikTok isn't

663
00:34:35,239 --> 00:34:37,399
Speaker 14: maybe the shiny new object it was, you know, five

664
00:34:37,480 --> 00:34:38,200
Speaker 14: six years ago.

665
00:34:39,920 --> 00:34:43,399
Speaker 2: The difficult question, I mean, there's is what happens next, right,

666
00:34:43,440 --> 00:34:47,239
Speaker 2: and your your research others point to law makers, you know,

667
00:34:47,400 --> 00:34:50,880
Speaker 2: putting out a new set of rules. Is their momentum

668
00:34:50,960 --> 00:34:52,360
Speaker 2: behind that pathway?

669
00:34:54,080 --> 00:34:57,880
Speaker 14: So yes, and no, I think there is momentum at

670
00:34:57,880 --> 00:35:00,920
Speaker 14: the state and the federal level. We are seeing lawmakers

671
00:35:00,960 --> 00:35:04,360
Speaker 14: and regulators try try to address a lot of these concerns.

672
00:35:04,560 --> 00:35:08,719
Speaker 14: Independent of this lawsuit, These lawsuits. That being said, they're

673
00:35:08,760 --> 00:35:11,440
Speaker 14: running up, running up against a lot of challenges.

674
00:35:12,160 --> 00:35:13,680
Speaker 5: For one is big tech lobbying.

675
00:35:13,719 --> 00:35:16,000
Speaker 14: I mean, these companies are lobbying against a lot of

676
00:35:16,040 --> 00:35:17,600
Speaker 14: these bills and laws.

677
00:35:18,239 --> 00:35:20,440
Speaker 5: There's challenges happening in court, and.

678
00:35:20,400 --> 00:35:22,640
Speaker 14: Then even you know, generally this tends to be a

679
00:35:22,640 --> 00:35:25,680
Speaker 14: bipartisan issue. I mean, we see lawmakers on both sides

680
00:35:25,680 --> 00:35:27,600
Speaker 14: of the aisle want to kind of reign in the

681
00:35:27,640 --> 00:35:30,760
Speaker 14: power of these platforms and reign in what they perceive

682
00:35:30,880 --> 00:35:31,520
Speaker 14: to be harms.

683
00:35:31,920 --> 00:35:34,239
Speaker 5: But the way they want to go about.

684
00:35:33,960 --> 00:35:37,440
Speaker 14: It often differs, and so that's another challenge. Enforcement is

685
00:35:37,440 --> 00:35:39,480
Speaker 14: a challenge. We're seeing that play out in Australia with

686
00:35:39,520 --> 00:35:42,400
Speaker 14: the ban under sixteens. You know, they're having a lot

687
00:35:42,400 --> 00:35:44,200
Speaker 14: of success in some ways, but they are having some

688
00:35:44,320 --> 00:35:47,520
Speaker 14: enforcement challenges and actually getting people under sixteen to completely

689
00:35:47,560 --> 00:35:50,600
Speaker 14: say off these platforms, and so it's a messy area

690
00:35:50,640 --> 00:35:51,160
Speaker 14: to regulate.

691
00:35:52,680 --> 00:35:55,080
Speaker 3: Mind Smiley emocs to senior analysts. Thank you.

692
00:35:55,120 --> 00:35:57,600
Speaker 2: Now, coming up, we're going to hear from Microsoft president

693
00:35:57,680 --> 00:36:01,240
Speaker 2: Brad Smith on the company's relationship with open AI.

694
00:36:01,480 --> 00:36:03,520
Speaker 3: That's next. This is Bloomberg Tech.

695
00:36:11,840 --> 00:36:14,680
Speaker 2: Microsoft president Brad Smith says the company is on track

696
00:36:14,760 --> 00:36:18,280
Speaker 2: to spend fifty billion dollars by twenty thirty to expand

697
00:36:18,280 --> 00:36:21,400
Speaker 2: AI infrastructure to the global South. He sat down with

698
00:36:21,440 --> 00:36:24,640
Speaker 2: Bloomberg's has Linda Ahmin on the sidelines of India's AI

699
00:36:24,680 --> 00:36:27,000
Speaker 2: Impact Summit. He also weighed in on the state of

700
00:36:27,080 --> 00:36:29,839
Speaker 2: Microsoft's partnership with open ai Take a listen.

701
00:36:30,840 --> 00:36:35,080
Speaker 15: I think it remains a critically important partnership for Microsoft.

702
00:36:35,160 --> 00:36:39,480
Speaker 15: We bet on each other, but it's not as exclusive

703
00:36:39,920 --> 00:36:43,680
Speaker 15: as it was, say a few years ago. OpenAI uses

704
00:36:43,760 --> 00:36:46,640
Speaker 15: our compute, they train models in our data centers, but

705
00:36:46,680 --> 00:36:50,799
Speaker 15: they work with other companies as well. We critically rely

706
00:36:50,960 --> 00:36:55,320
Speaker 15: on open AI's frontier models. They are among the best,

707
00:36:55,560 --> 00:36:58,120
Speaker 15: and many days they are the best in the world.

708
00:36:58,480 --> 00:37:01,200
Speaker 15: But we have a relationship with him thropic. We use

709
00:37:01,239 --> 00:37:04,759
Speaker 15: open source models, We're developing our own models, so on

710
00:37:04,920 --> 00:37:09,279
Speaker 15: both sides we work with more partners. But I think

711
00:37:09,320 --> 00:37:12,600
Speaker 15: the partnership between the two of us remains an imperative.

712
00:37:12,640 --> 00:37:15,080
Speaker 15: It's a huge priority for us at Microsoft.

713
00:37:15,160 --> 00:37:17,319
Speaker 16: The question is why is it a hedge, is it

714
00:37:17,360 --> 00:37:21,360
Speaker 16: a strategic pivot? How would you describe that move looking

715
00:37:21,400 --> 00:37:23,280
Speaker 16: at alternative partners.

716
00:37:23,080 --> 00:37:26,080
Speaker 15: Well, look, if you want to think about the partnership

717
00:37:26,160 --> 00:37:28,560
Speaker 15: between open AI and Microsoft. All you have to do

718
00:37:28,640 --> 00:37:32,960
Speaker 15: is ask one question, would any of this generative AI

719
00:37:33,120 --> 00:37:36,480
Speaker 15: sector even exist if the two of us had not

720
00:37:36,640 --> 00:37:40,920
Speaker 15: come together. Open Ai created something that no one else

721
00:37:41,040 --> 00:37:46,400
Speaker 15: even understood was possible when they launched chat GPT, and

722
00:37:46,520 --> 00:37:51,120
Speaker 15: open Ai could never have created that without Microsoft's compute

723
00:37:51,480 --> 00:37:55,719
Speaker 15: and really frontier data centers on which to train that.

724
00:37:56,080 --> 00:38:00,520
Speaker 15: We built something special. We'll each do special things on

725
00:38:00,560 --> 00:38:03,560
Speaker 15: our own. Will each do special things with other companies?

726
00:38:04,120 --> 00:38:08,080
Speaker 15: Will each do I think, very special things with each other.

727
00:38:08,800 --> 00:38:11,560
Speaker 16: Just one funnel question, because we're running out of time, apparently,

728
00:38:12,000 --> 00:38:13,840
Speaker 16: copilot is it losing traction?

729
00:38:14,239 --> 00:38:17,600
Speaker 15: I don't think so. It's gaining ground. It's getting better

730
00:38:17,680 --> 00:38:20,359
Speaker 15: every week, it's getting better every month. I say this

731
00:38:20,520 --> 00:38:24,680
Speaker 15: as a user, not just a M three sixty five copilot,

732
00:38:24,680 --> 00:38:28,360
Speaker 15: but our consumer copilot, our researcher agent, our other agents.

733
00:38:29,040 --> 00:38:34,520
Speaker 15: We're seeing usage grow. We will continue to add features

734
00:38:34,560 --> 00:38:38,640
Speaker 15: and functionality. I personally think it is an important part

735
00:38:38,800 --> 00:38:41,840
Speaker 15: not just a Microsoft's past and present. It is a

736
00:38:42,040 --> 00:38:44,799
Speaker 15: key part of our future. It is a key part

737
00:38:44,840 --> 00:38:49,839
Speaker 15: of I think making everyone more creative, more productive. I

738
00:38:49,880 --> 00:38:52,399
Speaker 15: certainly find that in my own work each and every

739
00:38:52,480 --> 00:38:53,799
Speaker 15: day that.

740
00:38:53,840 --> 00:38:57,160
Speaker 2: Was Microsoft fvicechair and President Brad Smith, along with Bloomberg's

741
00:38:57,360 --> 00:39:00,440
Speaker 2: has end Amen. In other news out of the Summitcrosoft

742
00:39:00,440 --> 00:39:03,400
Speaker 2: co founder Bill Gates backed out of a keynote address

743
00:39:03,840 --> 00:39:07,160
Speaker 2: just hours before he was due to speak, replaced instead

744
00:39:07,440 --> 00:39:10,680
Speaker 2: by the president of the Gates Foundations Africa and India offices.

745
00:39:10,719 --> 00:39:14,120
Speaker 2: The Foundation explained the decision as an effort to ensure

746
00:39:14,160 --> 00:39:18,200
Speaker 2: the focus remains on the conference, without elaborating. The withdrawal

747
00:39:18,200 --> 00:39:22,400
Speaker 2: follows criticism of gates relationship with convicted sex offender Jeffrey

748
00:39:22,400 --> 00:39:27,080
Speaker 2: Epstein and speculation about whether that link could overshadow the

749
00:39:27,120 --> 00:39:32,000
Speaker 2: Foundation's broader mission. Coming up, there is more drama around

750
00:39:32,040 --> 00:39:35,320
Speaker 2: the sale of Warner Brothers Discovery. We'll discover that next.

751
00:39:35,680 --> 00:39:48,360
Speaker 2: This is Bloomberg Tech. Hollywood is no stranger to a

752
00:39:48,440 --> 00:39:51,160
Speaker 2: plot twist. Take the latest development in the saga to

753
00:39:51,200 --> 00:39:55,560
Speaker 2: purchase Warner Brothers Discovery. According to sources, the Justice Department

754
00:39:55,560 --> 00:39:58,799
Speaker 2: has summoned some of the country's largest theater chains to

755
00:39:58,880 --> 00:40:01,840
Speaker 2: discuss the potential impact active a sale to either Netflix

756
00:40:01,920 --> 00:40:04,719
Speaker 2: or Paramount Skuydance. This coming on the heels of Warner

757
00:40:04,719 --> 00:40:08,520
Speaker 2: Brothers reopening deal talks with Paramount. Now all this drama

758
00:40:08,680 --> 00:40:12,120
Speaker 2: should be seen as one twist too many for Netflix,

759
00:40:12,400 --> 00:40:15,520
Speaker 2: according to Bloomberg Intelligence, Let's bring in the aufer of

760
00:40:15,520 --> 00:40:16,440
Speaker 2: that research b I.

761
00:40:16,520 --> 00:40:18,359
Speaker 3: Seen around this. KEITHA. Angerath and.

762
00:40:20,080 --> 00:40:23,080
Speaker 2: Investors have voiced this, right there is this idea that

763
00:40:23,160 --> 00:40:25,520
Speaker 2: now might be the time for Netflix to walk away

764
00:40:25,840 --> 00:40:28,360
Speaker 2: from some corners of the market. I think last weekend

765
00:40:28,400 --> 00:40:31,719
Speaker 2: Korra came out in favor of that. But you at

766
00:40:31,760 --> 00:40:35,440
Speaker 2: BI have some pretty clear reasons why you think Netflix

767
00:40:35,440 --> 00:40:36,160
Speaker 2: should walk away.

768
00:40:36,239 --> 00:40:37,439
Speaker 3: Just outline them for us.

769
00:40:38,480 --> 00:40:39,279
Speaker 11: Yeah, absolutely.

770
00:40:39,280 --> 00:40:42,759
Speaker 17: I mean this has been a major distraction ed now

771
00:40:42,840 --> 00:40:44,960
Speaker 17: for you know, over a couple of months right now,

772
00:40:44,960 --> 00:40:46,560
Speaker 17: and we've seen that even you know, as a reflection

773
00:40:46,600 --> 00:40:48,759
Speaker 17: in the stock price. But they're really you know, it

774
00:40:48,880 --> 00:40:51,719
Speaker 17: just kind of really muddies a really clean narrative for

775
00:40:51,840 --> 00:40:54,960
Speaker 17: the company. And I think from our perspective, yes, we

776
00:40:55,040 --> 00:40:57,279
Speaker 17: do see that. You know, Netflix obviously has a lot

777
00:40:57,280 --> 00:41:01,080
Speaker 17: of financial firepower. They are an absolute cash flow machine.

778
00:41:01,200 --> 00:41:03,160
Speaker 17: They're probably going to generate about eleven billion in free

779
00:41:03,160 --> 00:41:04,360
Speaker 17: cash flow this year, there's.

780
00:41:04,200 --> 00:41:05,000
Speaker 11: No doubt about that.

781
00:41:05,560 --> 00:41:07,800
Speaker 17: But there is going to be the question of leverage.

782
00:41:07,840 --> 00:41:09,880
Speaker 17: So if they do take up their offer, it's currently

783
00:41:09,920 --> 00:41:12,640
Speaker 17: about twenty seven dollars and seventy five cents their risk,

784
00:41:12,719 --> 00:41:15,440
Speaker 17: pushing close to almost four times leverage. As they go

785
00:41:15,600 --> 00:41:18,520
Speaker 17: up to maybe thirty dollars thirty two dollars, we don't

786
00:41:18,520 --> 00:41:20,960
Speaker 17: know what that final number is going to be. And

787
00:41:21,000 --> 00:41:23,400
Speaker 17: then you know you're going to deal with how do

788
00:41:23,440 --> 00:41:26,600
Speaker 17: you reduce debt, So it just becomes a big problem there.

789
00:41:26,600 --> 00:41:28,680
Speaker 17: And then of course you just have the general concerns

790
00:41:28,719 --> 00:41:33,359
Speaker 17: with integration risk, execution risk. And remember with this, you know,

791
00:41:33,400 --> 00:41:36,200
Speaker 17: Netflix is really acquiring a business that they always wanted

792
00:41:36,200 --> 00:41:39,520
Speaker 17: to stay away from. They're acquiring a traditional Yes, they

793
00:41:39,520 --> 00:41:43,600
Speaker 17: do get the library, the fantastic IP, the HBO library,

794
00:41:43,600 --> 00:41:45,000
Speaker 17: which is one of a kind when it comes to

795
00:41:45,040 --> 00:41:48,960
Speaker 17: scripted you know, dramas, But then you also really are

796
00:41:49,120 --> 00:41:51,719
Speaker 17: increasing your dependence on Hollywood. And the whole reason that

797
00:41:51,760 --> 00:41:55,000
Speaker 17: Netflix has done so well ed is because they have

798
00:41:55,160 --> 00:41:58,359
Speaker 17: been a global powerhouse. They have not just depended on

799
00:41:58,440 --> 00:42:01,720
Speaker 17: Hollywood for content. They have gone to so many different

800
00:42:01,800 --> 00:42:05,919
Speaker 17: local markets. International has been such a big deal for them.

801
00:42:06,760 --> 00:42:09,040
Speaker 17: But you know, as we kind of see the union

802
00:42:09,080 --> 00:42:11,319
Speaker 17: contracts kind of coming up, you know, we think that

803
00:42:11,440 --> 00:42:14,319
Speaker 17: increasing the dependence on Hollywood is actually more of a

804
00:42:14,360 --> 00:42:16,239
Speaker 17: negative than a positive for Netflix and.

805
00:42:16,320 --> 00:42:19,800
Speaker 2: Just very quickly getha the stocks down more than thirty

806
00:42:19,840 --> 00:42:23,400
Speaker 2: percent since this started. Is that a signal or is

807
00:42:23,440 --> 00:42:24,920
Speaker 2: it real pressure on management?

808
00:42:26,280 --> 00:42:27,759
Speaker 17: So a couple of different things. I think a lot

809
00:42:27,760 --> 00:42:29,719
Speaker 17: of it hinges on what the outcome of this whole

810
00:42:29,760 --> 00:42:31,840
Speaker 17: Warner Brothers Discovery deal is going to be. But then

811
00:42:31,920 --> 00:42:34,560
Speaker 17: Netflix also has some problems. They have shown that they

812
00:42:34,560 --> 00:42:36,960
Speaker 17: haven't really been able to grow engagement and a lot

813
00:42:36,960 --> 00:42:39,080
Speaker 17: of people have argued that maybe that is why that

814
00:42:39,120 --> 00:42:42,200
Speaker 17: they're pursuing Warner Brothers Discovery in the first place. So,

815
00:42:42,440 --> 00:42:44,440
Speaker 17: you know, they have a couple of things to do

816
00:42:44,520 --> 00:42:47,200
Speaker 17: in terms of increasing their operating margin in terms of

817
00:42:47,400 --> 00:42:50,200
Speaker 17: boosting engagement, and if they do that, then I think

818
00:42:50,400 --> 00:42:53,000
Speaker 17: management has a pretty good story why they don't need

819
00:42:53,040 --> 00:42:54,120
Speaker 17: Warner Brothers Discovery.

820
00:42:54,719 --> 00:42:57,480
Speaker 2: Keither rang enough from Bloomberg Intelligence. Thank you very much,

821
00:42:57,520 --> 00:43:01,320
Speaker 2: and we will be speaking with Netflix coc Ted Surundos

822
00:43:01,440 --> 00:43:04,319
Speaker 2: is in about thirty minutes time, so stick around. That

823
00:43:04,400 --> 00:43:07,359
Speaker 2: does it for this edition of Bloomberg Tech Recap. What

824
00:43:07,600 --> 00:43:11,160
Speaker 2: was an incredible news show on the podcast you know

825
00:43:11,200 --> 00:43:13,120
Speaker 2: where to find it. This is Bloomberg Tech