WEBVTT - Bloomberg Tech Screentime Special

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<v Speaker 1>Bloomberg Audio Studios.

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<v Speaker 2>Podcasts.

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<v Speaker 3>Radio. News.

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<v Speaker 4>Bloomberg Tech is live from the heart of Silicon Valley

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<v Speaker 4>with Ed Ludlow in San Francisco.

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<v Speaker 2>Welcome to a special edition of Bloomberg Tech, live from

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<v Speaker 2>Bloomberg Screen Time in Los Angeles. Coming up this hour,

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<v Speaker 2>we'll bring you conversations with some of the biggest names

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<v Speaker 2>in the entertainment industry. And of course, AI is front

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<v Speaker 2>and center. We'll be speaking with entrepreneurs and leaders across

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<v Speaker 2>a changing tech and media landscape. I want to get

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<v Speaker 2>to the big entertainment story today, which is Paramount's $ 110

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<v Speaker 2>billion Warner Bros.

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<v Speaker 5>Deal.

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<v Speaker 2>It is cleared to move forward. A federal judge has

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<v Speaker 2>approved a settlement with a dozen states, and the companies

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<v Speaker 2>now expect the merger to close October 6th.

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<v Speaker 6>Timely.

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<v Speaker 2>Bloomberg's Lucas Shaw leads our media and entertainment coverage, leads

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<v Speaker 2>the Screen Time team, and we're here at Screen Time,

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<v Speaker 2>but that was a big headline. Let's start with, this

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<v Speaker 2>is cleared.

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<v Speaker 3>It's going to close.

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<v Speaker 7>Yeah, we knew it was going to close as soon

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<v Speaker 7>as the state AGs and the Writers Guild of America

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<v Speaker 7>settled their lawsuit saying, you know, we feel like you

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<v Speaker 7>have agreed to certain conditions that make us satisfied. And

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<v Speaker 7>David Ellison, the chairman and CEO of Paramount Skydance, who

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<v Speaker 7>will be the chairman and CEO of the combined company,

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<v Speaker 7>is wasting no time making changes with staffing and leadership,

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<v Speaker 7>and I expect we'll just see news pretty much every

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<v Speaker 7>day over the next couple weeks.

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<v Speaker 2>There are also sort of details coming out now about

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<v Speaker 2>what that new company looks like. What does it look

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<v Speaker 2>like on paper?

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<v Speaker 6>Well, we know a couple things.

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<v Speaker 7>One is that Cindy Holland, who's been the head of

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<v Speaker 7>streaming for Paramount Skydance and who had previously been a

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<v Speaker 7>top executive at Netflix.

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<v Speaker 3>has left.

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<v Speaker 7>And everybody believes that that means that Casey Bloys, who

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<v Speaker 7>will be speaking at this conference later today, will be

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<v Speaker 7>in charge of streaming. That is something that we have

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<v Speaker 7>reported and something that I think others have reported as well.

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<v Speaker 3>The big news also.

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<v Speaker 7>Yesterday was that they announced Enon Kreitz, who has been

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<v Speaker 7>the CEO of Mattel, is joining as the co-CEO of

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<v Speaker 7>the combined company. A little weird because David Ellison is

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<v Speaker 7>the CEO, but you can think of Enon as the

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<v Speaker 7>person who's going to come in and really run things

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<v Speaker 7>day to day cut a lot of cost restructure like

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<v Speaker 7>all the nasty stuff that david ellison doesn't want to

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<v Speaker 7>be kind of stuck with is enon's job.

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<v Speaker 2>Okay so last night we kicked things off here in

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<v Speaker 2>in hollywood with a conversation with netflix co-ceo ted sarandos

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<v Speaker 2>and obviously it's in the past now but the opportunity

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<v Speaker 2>that netflix had seen with warner brothers discovery you talked

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<v Speaker 2>about that quite a lot let's just listen to a

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<v Speaker 2>little bit.

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<v Speaker 8>Of it.

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<v Speaker 9>The plan was solid um i think we we and

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<v Speaker 9>we won the deal at some point, so we priced

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<v Speaker 9>it right. At our scale, that was the top price

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<v Speaker 9>point where I thought we could return value to our

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<v Speaker 9>shareholders with that asset. Any more than that, I thought

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<v Speaker 9>we'd be taking it into negative territory.

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<v Speaker 2>I think macro point, now that it is Paramount Skydance

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<v Speaker 2>and Warner Brothers Discovery, the landscape's shifting a bit. And

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<v Speaker 2>Ted Sarandos and you talked about how Netflix kind of

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<v Speaker 2>is going to respond, how they're going to get growth

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<v Speaker 2>in the future.

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<v Speaker 6>It's tricky for him because... I think prior.

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<v Speaker 7>To Netflix going after that deal, they were seen as

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<v Speaker 7>the biggest entertainment company on the block and just all

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<v Speaker 7>things were going very well, it seemed for them. And

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<v Speaker 7>their pursuit of Warner Brothers Discovery, rightly or wrongly, triggered

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<v Speaker 7>a lot of skepticism because people started to wonder, why

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<v Speaker 7>are they doing this? Ted talked about it last night.

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<v Speaker 7>It sort of changed the narrative for the company. And

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<v Speaker 7>he says he's okay with that. It was a deal

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<v Speaker 7>that was worth going for, but it.

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<v Speaker 6>Has hurt them.

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<v Speaker 7>And their response right now is basically, we don't need

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<v Speaker 7>to do anything dramatic. We were in a good position

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<v Speaker 7>before that, and that has not satisfied investors.

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<v Speaker 2>It's a huge agenda today here in Hollywood. Preview some

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<v Speaker 2>of it. And the big question is, this industry is

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<v Speaker 2>genuinely debating while we're all gathered.

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<v Speaker 7>Well, look, the Paramount Warner Brothers deal, even though we

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<v Speaker 7>know it's going to happen, is still top of mind

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<v Speaker 7>for everyone because they're wondering what it's going to look like.

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<v Speaker 7>So we have Casey Bloys, as I mentioned. We also

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<v Speaker 7>have Jerry Cardinale, who is David Ellison's deal guy, one

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<v Speaker 7>of the largest shareholders in Paramount Skydance. I'm excited for

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<v Speaker 7>both of those conversations. We have Dana Walden, who's the

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<v Speaker 7>number two at the Walt Disney Company. We have not

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<v Speaker 7>had Disney at this event before, so I'm excited for that. Obviously,

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<v Speaker 7>a company of great interest. AI is a topic, as

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<v Speaker 7>you mentioned, at the top of the show that's big.

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<v Speaker 7>I think you're going to have Mikey Schulman, the.

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<v Speaker 6>CEO of Suno, on the show.

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<v Speaker 7>I'll be interviewing him with our colleague Ashley Carmen this afternoon.

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<v Speaker 4>So that should be fun.

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<v Speaker 2>Bloomberg's Lucas Shaw, leader of our Screen Time team and

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<v Speaker 2>this annual event. Thank you very much, dude. I just

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<v Speaker 2>want to stay with Netflix. Ted Sarandos says the streaming

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<v Speaker 2>giant needs to move faster. And when Lucas sat down

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<v Speaker 2>with the Netflix co-CEO to talk about engagement, the push

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<v Speaker 2>into live programming and the company's strategy for growth, he

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<v Speaker 2>was pretty strong. Listen to this.

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<v Speaker 9>We are growing engagement. So we're growing on 200 billion

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<v Speaker 9>hours of watching. We grew 2%. in our last announcement.

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<v Speaker 7>But 2% is not what people are hoping for out

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<v Speaker 7>of you, right? They're used to double-digit growth, at least

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<v Speaker 7>certainly in revenue, and to some extent even in viewership,

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<v Speaker 7>they'd expect more.

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<v Speaker 9>This is my point about the growth in general. Yes, overall,

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<v Speaker 9>we're not growing as fast as I want us to,

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<v Speaker 9>and we're working on making that move faster. We are, though,

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<v Speaker 9>also doing things that create a lot of headwind to

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<v Speaker 9>that number, meaning when we do live programming on Netflix,

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<v Speaker 9>which is a relatively new thing, we spend about 5%

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<v Speaker 9>of our content budget on live events. They generate about 1%

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<v Speaker 9>of our watching. But they do a very different job.

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<v Speaker 6>They generate a lot of sign-ups. They're really effective for advertising.

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<v Speaker 9>Sign-up, retention, advertising, all those things that they do. But

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<v Speaker 9>it creates engagement headwind in how you invest against it.

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<v Speaker 9>And remember, when I say we grew 2%, it's an

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<v Speaker 9>easy number to sneeze at. But it's through all the

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<v Speaker 9>growth of Live. It's through incredible headwinds from things like

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<v Speaker 9>the World Cup and World Sports and all those things

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<v Speaker 9>that are going on, too. So we are growing the business.

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<v Speaker 9>We want to keep growing it faster. This past quarter,

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<v Speaker 9>we did double-digit revenue growth in every.

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<v Speaker 3>Region of the world.

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<v Speaker 9>So the business is great and growing fine. I mean,

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<v Speaker 9>if you asked me if we were growing at 20%,

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<v Speaker 9>I'd be telling you I wish we were growing faster.

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<v Speaker 8>Right.

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<v Speaker 7>But when you said you wish you were growing faster

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<v Speaker 7>and we're working on it, what are the things that

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<v Speaker 7>you are working on to kind of reaccelerate that growth?

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<v Speaker 9>Well, some of the things are in the expansion of

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<v Speaker 9>what we do. So Live was an expansion of what

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<v Speaker 9>we did that didn't necessarily bring more gross engagement, but

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<v Speaker 9>it brings very valuable engagement. So it's not... a mystery

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<v Speaker 9>that all engagement is not equal because you probably are

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<v Speaker 9>not surprised to know that an hour of Judge Judy

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<v Speaker 9>in the middle of the day does not generate as

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<v Speaker 9>much revenue as an hour of NFL football.

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<v Speaker 7>Or I saw some CPM chart recently that showed what

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<v Speaker 7>you make per view versus what YouTube makes per view.

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<v Speaker 3>And yours is higher.

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<v Speaker 9>Yeah, we monetize better. Our programming monetizes better. Now, we're

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<v Speaker 9>looking constantly at how do we do things to bring

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<v Speaker 9>more value to the members, more things to watch, more

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<v Speaker 9>ways to watch all those things. So that is some

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<v Speaker 9>of these things that are, and I don't want to

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<v Speaker 9>over-characterize things like podcasts and those things because they're very

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<v Speaker 9>small investment and very small addition to what we're doing.

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<v Speaker 9>The vast majority of what we spend on is professionally

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<v Speaker 9>made movies and television series and games.

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<v Speaker 4>Would you ever buy one of the big studios, take two?

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<v Speaker 3>Microsoft seems to be.

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<v Speaker 6>Unhappy with that.

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<v Speaker 9>Well, as you know, we're not, we have not been

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<v Speaker 9>traditionally big buyers. The Warner Brothers notwithstanding. that we've not

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<v Speaker 9>really been builders from scratch. So I do think we've

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<v Speaker 9>looked at, we have built some, worked with some of

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<v Speaker 9>the smaller studios and programmers and developers, and there's a

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<v Speaker 9>likeliness of those things come. The big problem with when

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<v Speaker 9>you do these deals, and the reason why I go back,

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<v Speaker 9>why the Warner Brothers was attractive, even though I said

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<v Speaker 9>we were not going to do that, is it's very

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<v Speaker 9>rare that this kind of asset was so clean. You're

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<v Speaker 9>just buying just the things we wanted to buy. And

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<v Speaker 9>so we were able to very easily look at this

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<v Speaker 9>and say, how will this add value to Netflix and

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<v Speaker 9>not destroy value in other ways? How do you take

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<v Speaker 9>this growth engine and have it supercharge our growth engine?

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<v Speaker 9>And for us, the ability to do that made that

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<v Speaker 9>deal super unique. We're not looking for the next opportunity

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<v Speaker 9>to backfill that deal because our plans and how we're

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<v Speaker 9>going to grow is primarily organic, and we'll look for

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<v Speaker 9>opportunities that complement the business as we go. That's for games, too.

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<v Speaker 2>That was Netflix co-CEO Ted Sarandos speaking with Lucas Shaw.

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<v Speaker 2>That's how we kicked off Bloomberg Screen Time 2026. Coming

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<v Speaker 2>up on this show, we're going to discuss how AI

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<v Speaker 2>is changing the way music gets made with Suno CEO

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<v Speaker 2>Mikey Shulman. That's next. This is Bloomberg Tech. We go

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<v Speaker 2>live to SpaceX, Space Launch Complex 40, Cape Canaveral, Florida,

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<v Speaker 2>Crew Dragon 13. You have four astronauts, two Americans, one Canadian,

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<v Speaker 2>one Russian cosmonaut. in the next 30 seconds heading to

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<v Speaker 2>the International Space Station. SpaceX in coordination with NASA. As

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<v Speaker 2>it stands, everything nominal. This mission looks like it's a go.

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<v Speaker 2>Let's listen in to the countdown from Cape Canaveral, Florida.

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<v Speaker 2>T-minus 10, 9, 8, 7, 6, 5, 4, 3, 2, 1, ignition.

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<v Speaker 5>And liftoff.

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<v Speaker 6>Go Falcon, go Dragon, and go Crew-13.

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<v Speaker 10>Liftoff of Crew-13 carried by Dragon Brace to the International

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<v Speaker 10>Space Station.

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<v Speaker 7>All nine Merlin engines on the first stage at maximum

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<v Speaker 7>thrust of 1.7 million pounds.

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<v Speaker 2>We heard a good call.

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<v Speaker 6>The propulsion is nominal or as expected.

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<v Speaker 11>The spacecraft will also begin to pitch downrange, meaning it's

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<v Speaker 11>turning slightly horizontally from what you saw.

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<v Speaker 6>At liftoff to help build speed.

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<v Speaker 12>E plus 40 seconds. T-plus 40 seconds into Crew 13's

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<v Speaker 12>mission on board.

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<v Speaker 2>Stage one throttle down.

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<v Speaker 12>Of Dragon and Falcon 9. And we did hear that

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<v Speaker 12>call out for stage one throttle down. That is in

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<v Speaker 12>preparation for Max Q coming up here in.

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<v Speaker 1>A few seconds.

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<v Speaker 2>Okay, there are four astronauts heading on Falcon 9 inside

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<v Speaker 2>a Dragon capsule towards the International Space Station, just hitting

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<v Speaker 2>the moment of Max Q, where the air is most

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<v Speaker 2>dense as the craft passes through Earth's atmosphere. The maximum

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<v Speaker 2>moment of aerodynamic pressure.

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<v Speaker 8>Those.

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<v Speaker 2>astronauts feeling three to four g's on the way up

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<v Speaker 2>this has kind of become routine um but it's an

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<v Speaker 2>important mission for spacex nonetheless with the future of the

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<v Speaker 2>falcon as the launch system program under question dragon as

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<v Speaker 2>well i want to bring in bloomberg space correspondent lauren

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<v Speaker 2>grush um you know you and i talk about this

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<v Speaker 2>all the time right lauren this is kind of somewhat

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<v Speaker 2>routine but give us the context and why this this

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<v Speaker 2>mission to service iss is important Right.

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<v Speaker 11>Well, as you see, it's the 13th mission that SpaceX

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<v Speaker 11>has done. So we really are getting into the rhythm

0:11:19.200 --> 0:11:22.040
<v Speaker 11>of things. But it does come at an interesting time,

0:11:22.120 --> 0:11:25.240
<v Speaker 11>which you said, which is that the future of the

0:11:25.280 --> 0:11:28.110
<v Speaker 11>Crew Dragon that the crew is flying in is kind

0:11:28.140 --> 0:11:30.290
<v Speaker 11>of in question at the moment. There's a lot of

0:11:30.370 --> 0:11:33.990
<v Speaker 11>speculation that SpaceX is going to retire the Crew Dragon

0:11:34.450 --> 0:11:36.770
<v Speaker 11>as soon as the ISS program ends. We don't have

0:11:36.809 --> 0:11:39.790
<v Speaker 11>a clear answer on that. But this could be one

0:11:39.830 --> 0:11:42.720
<v Speaker 11>of the few remaining Crew Dragon missions that we actually

0:11:42.770 --> 0:11:45.840
<v Speaker 11>see them do for NASA. They have four more scheduled

0:11:45.960 --> 0:11:47.900
<v Speaker 11>for crew rotation missions going forward.

0:11:48.320 --> 0:11:48.940
<v Speaker 2>So we should.

0:11:48.780 --> 0:11:51.420
<v Speaker 11>Definitely keep an eye on those. But yeah, it's an

0:11:51.490 --> 0:11:53.370
<v Speaker 11>interesting time for these launches to occur.

0:11:56.030 --> 0:11:59.030
<v Speaker 2>Okay, we're waiting for Miko main engine cutoff where the

0:11:59.050 --> 0:12:03.069
<v Speaker 2>first stage engine shuts down. Then we should get stage separations,

0:12:03.090 --> 0:12:06.330
<v Speaker 2>a pretty nice visual that we get any moment now.

0:12:07.070 --> 0:12:10.709
<v Speaker 2>Three first-time flyers, Lauren, on this mission, and there you

0:12:10.730 --> 0:12:12.829
<v Speaker 2>have it, that stage separation I was talking about a

0:12:12.860 --> 0:12:15.240
<v Speaker 2>second ago. Just give us a bit more of the

0:12:15.260 --> 0:12:18.160
<v Speaker 2>mission overview and the reality of what it takes for

0:12:18.179 --> 0:12:19.840
<v Speaker 2>Dragon to get to the ISS.

0:12:20.780 --> 0:12:21.700
<v Speaker 1>Yeah, absolutely.

0:12:21.780 --> 0:12:25.660
<v Speaker 11>So these are pretty routine missions, if you can call

0:12:25.710 --> 0:12:29.050
<v Speaker 11>them routine. You know, space flight is never routine. But

0:12:29.130 --> 0:12:30.150
<v Speaker 11>in order to keep the.

0:12:30.190 --> 0:12:32.270
<v Speaker 1>ISS fully staffed.

0:12:32.370 --> 0:12:36.790
<v Speaker 11>They send crews every six months to the International Space Station.

0:12:37.170 --> 0:12:40.179
<v Speaker 11>So this crew is heading to the ISS. They'll stay

0:12:40.200 --> 0:12:43.470
<v Speaker 11>there for roughly a week and greet the crew that's

0:12:43.500 --> 0:12:44.270
<v Speaker 11>already on board.

0:12:44.630 --> 0:12:45.030
<v Speaker 2>And then the.

0:12:44.990 --> 0:12:48.550
<v Speaker 11>Previous crew, Crew 12, another four-person crew, is slated to

0:12:48.590 --> 0:12:51.349
<v Speaker 11>come home once they do that handover mission. And so

0:12:51.610 --> 0:12:57.680
<v Speaker 11>it's a pretty periodic schedule that SpaceX has helped NASA maintain,

0:12:57.860 --> 0:13:03.020
<v Speaker 11>you know, regular schedule. crew, um, appointments to the ISS.

0:13:03.040 --> 0:13:05.800
<v Speaker 11>So it's, it's, um, you know, like I said, hate

0:13:05.820 --> 0:13:08.880
<v Speaker 11>to call it standard, but it is a standard mission.

0:13:08.620 --> 0:13:13.560
<v Speaker 2>For NASA and SpaceX. Okay, Bloomers, Lauren Grush, thank you

0:13:13.580 --> 0:13:15.980
<v Speaker 2>very much. You can keep watching the full launch on

0:13:16.000 --> 0:13:20.140
<v Speaker 2>the terminal at Live Go. Let's go from space back

0:13:20.179 --> 0:13:22.540
<v Speaker 2>down to earth here in Hollywood and back to entertainment.

0:13:22.960 --> 0:13:26.000
<v Speaker 2>And look at the collision of AI and creativity, specifically

0:13:26.040 --> 0:13:29.770
<v Speaker 2>in music. Suno has brought AI-generated music to more than

0:13:29.770 --> 0:13:33.730
<v Speaker 2>100 million users. and is now partnering with some of

0:13:33.750 --> 0:13:36.650
<v Speaker 2>the industry's biggest players. Joining us is Suno co-founder and CEO,

0:13:37.070 --> 0:13:38.790
<v Speaker 2>Mikey Shulman. I think a really good place to start is,

0:13:39.050 --> 0:13:41.250
<v Speaker 2>for those that just aren't familiar with Suno, what it

0:13:41.330 --> 0:13:42.720
<v Speaker 2>is and what you can actually do with it.

0:13:43.150 --> 0:13:44.000
<v Speaker 3>Yeah, great to be here.

0:13:45.059 --> 0:13:47.900
<v Speaker 13>For the uninitiated, Suno is a way for everybody to

0:13:48.040 --> 0:13:52.280
<v Speaker 13>enjoy making music, whether you're a Grammy-winning producer tweaking something,

0:13:52.300 --> 0:13:54.500
<v Speaker 13>getting that last little bit out of it, or a

0:13:54.540 --> 0:13:58.480
<v Speaker 13>grandmother just making music for fun. And the thing about

0:13:59.020 --> 0:14:02.780
<v Speaker 13>music is... Everybody is creative, but not only is everybody creative,

0:14:02.880 --> 0:14:04.290
<v Speaker 13>everybody enjoys being creative.

0:14:04.309 --> 0:14:06.470
<v Speaker 2>You're talking about humans being creative.

0:14:06.490 --> 0:14:09.730
<v Speaker 13>Yes, everybody is creative. And so forget the tooling that

0:14:09.770 --> 0:14:13.570
<v Speaker 13>you use. When you spend 30 minutes making music or

0:14:13.590 --> 0:14:15.750
<v Speaker 13>making anything, you just feel so much better than the

0:14:15.790 --> 0:14:18.310
<v Speaker 13>way we're entertained today of just consuming stuff. And we

0:14:18.350 --> 0:14:21.010
<v Speaker 13>think in the future, everybody will be entertained creatively.

0:14:21.650 --> 0:14:24.400
<v Speaker 2>That 100 million number is a big number. Kind of

0:14:24.420 --> 0:14:27.510
<v Speaker 2>surprised me a little bit. Who are those people? What

0:14:27.550 --> 0:14:30.290
<v Speaker 2>types of people? What are the demographics? What are the

0:14:30.330 --> 0:14:32.730
<v Speaker 2>profiles of people that are engaging with the technology?

0:14:32.910 --> 0:14:35.310
<v Speaker 3>It's so interesting. It is so varied.

0:14:35.390 --> 0:14:37.510
<v Speaker 13>It's like I said, we know tons and tons of

0:14:37.590 --> 0:14:40.850
<v Speaker 13>industry professionals using this in their day-to-day workflows, falling in

0:14:40.890 --> 0:14:42.670
<v Speaker 13>love with new ways of making music professionally.

0:14:43.110 --> 0:14:44.730
<v Speaker 3>But it is the whole world.

0:14:44.890 --> 0:14:48.200
<v Speaker 13>It's every gender, every race, every country. We work in

0:14:48.250 --> 0:14:51.240
<v Speaker 13>every language. Music is so universal. So it's not surprising

0:14:51.300 --> 0:14:52.760
<v Speaker 13>to us that we see this.

0:14:52.880 --> 0:14:53.400
<v Speaker 3>All over the world.

0:14:53.740 --> 0:14:57.140
<v Speaker 2>This is... I think the third edition of Bloomberg Screen Time.

0:14:57.340 --> 0:15:01.300
<v Speaker 2>And over those three years, we've been talking about the

0:15:01.370 --> 0:15:05.030
<v Speaker 2>use of AI in generating music, but content generally. The

0:15:06.030 --> 0:15:10.050
<v Speaker 2>music industry, I would say, was initially pretty hostile to

0:15:10.070 --> 0:15:13.570
<v Speaker 2>the technology, what it would mean for them, for their content,

0:15:13.710 --> 0:15:14.730
<v Speaker 2>their IP.

0:15:15.330 --> 0:15:16.170
<v Speaker 6>Where are we at now?

0:15:17.620 --> 0:15:21.240
<v Speaker 13>I think we found ourselves in a really interesting, complex time.

0:15:21.380 --> 0:15:24.470
<v Speaker 13>The entire industry of music is moving very quickly, and

0:15:24.490 --> 0:15:27.890
<v Speaker 13>actually the entire industry of AI is moving extremely quickly.

0:15:27.930 --> 0:15:31.260
<v Speaker 13>And so things are shifting in a very complex way.

0:15:31.560 --> 0:15:32.000
<v Speaker 4>That said.

0:15:32.620 --> 0:15:35.310
<v Speaker 13>It's a really exciting time because as the technologies progress,

0:15:35.330 --> 0:15:37.030
<v Speaker 13>we are able to do so much more with our

0:15:37.070 --> 0:15:37.770
<v Speaker 13>industry partners.

0:15:37.990 --> 0:15:39.730
<v Speaker 3>We're able to push things forward a lot more.

0:15:40.070 --> 0:15:43.620
<v Speaker 13>I think slowly we see people actually excited to speak

0:15:43.660 --> 0:15:47.520
<v Speaker 13>a little bit about how they use these tools, about how...

0:15:47.820 --> 0:15:50.840
<v Speaker 13>It is helping them amplify their creativity about how there's

0:15:50.900 --> 0:15:54.370
<v Speaker 13>actually a human behind everything. And so I'm really, really

0:15:54.410 --> 0:15:55.229
<v Speaker 13>excited for the next year.

0:15:55.570 --> 0:15:58.490
<v Speaker 2>Let's talk about where Suna has got commercially. You have

0:15:58.550 --> 0:16:02.850
<v Speaker 2>partnerships with Warner, BMG, for example. What is it that

0:16:02.870 --> 0:16:06.000
<v Speaker 2>you actually do with or for them? What's the output

0:16:06.400 --> 0:16:06.920
<v Speaker 2>for Suno?

0:16:07.080 --> 0:16:07.860
<v Speaker 3>It's a great question.

0:16:08.080 --> 0:16:12.020
<v Speaker 13>I think that we think of these partnerships as really long-term,

0:16:12.330 --> 0:16:14.870
<v Speaker 13>and it's because where we are today is a particular

0:16:14.910 --> 0:16:17.090
<v Speaker 13>moment in time, but what the future of music can

0:16:17.130 --> 0:16:19.590
<v Speaker 13>be is actually still unknown. And the thing we're most

0:16:19.650 --> 0:16:22.870
<v Speaker 13>excited about these partnerships is building products that could never

0:16:22.910 --> 0:16:25.530
<v Speaker 13>have been built before without bringing the best technology and

0:16:25.550 --> 0:16:26.050
<v Speaker 13>the biggest.

0:16:25.870 --> 0:16:26.430
<v Speaker 3>Music companies together.

0:16:26.450 --> 0:16:29.260
<v Speaker 2>When you say building products, you mean building tracks? What

0:16:29.300 --> 0:16:30.640
<v Speaker 2>is it that they pay you for?

0:16:30.800 --> 0:16:32.920
<v Speaker 3>So imagine you can take.

0:16:33.400 --> 0:16:35.700
<v Speaker 13>the music of one of your favorite artists and start

0:16:35.740 --> 0:16:38.720
<v Speaker 13>to play with it and remix it or cover it

0:16:38.780 --> 0:16:40.880
<v Speaker 13>or mash it up with something else or otherwise change

0:16:40.920 --> 0:16:43.040
<v Speaker 13>it in a way that has you feeling like you

0:16:43.090 --> 0:16:44.710
<v Speaker 13>are co-creating with your favorite artist.

0:16:44.750 --> 0:16:46.730
<v Speaker 3>This is an entirely new product.

0:16:47.010 --> 0:16:49.810
<v Speaker 13>Digital music today has become very, very passive and to

0:16:49.850 --> 0:16:52.110
<v Speaker 13>pull people in, get them to engage in new ways,

0:16:52.150 --> 0:16:54.310
<v Speaker 13>this is how we actually grow The music business.

0:16:54.950 --> 0:16:57.890
<v Speaker 2>Mikey, let's go to the underlying technology, the core competence

0:16:57.950 --> 0:17:00.480
<v Speaker 2>that you and the team at Sonar have. Is it

0:17:00.620 --> 0:17:04.740
<v Speaker 2>in AI? Are you model builders, a model lab, or

0:17:04.760 --> 0:17:08.480
<v Speaker 2>do you harness? Harness is a very specific term. Do

0:17:08.500 --> 0:17:10.240
<v Speaker 2>you make use of other people's technology?

0:17:10.800 --> 0:17:13.760
<v Speaker 13>We build all of our technology in-house. When we started

0:17:13.780 --> 0:17:16.700
<v Speaker 13>this company, there was nothing. in this space, and so

0:17:16.770 --> 0:17:18.290
<v Speaker 13>we really had to be the tip of the spear.

0:17:18.630 --> 0:17:21.090
<v Speaker 13>That said, I really think of us as a music company,

0:17:21.130 --> 0:17:24.300
<v Speaker 13>as a product company. We are building technology, not just

0:17:24.320 --> 0:17:26.700
<v Speaker 13>for the sake of building technology, but actually for the

0:17:26.740 --> 0:17:27.920
<v Speaker 13>sake of delighting our users.

0:17:28.400 --> 0:17:30.980
<v Speaker 3>And you cover a lot of AI stuff. There's so

0:17:31.030 --> 0:17:31.950
<v Speaker 3>much focus.

0:17:31.869 --> 0:17:36.590
<v Speaker 13>On on utility, on the enterprise, and there's not enough

0:17:36.609 --> 0:17:38.750
<v Speaker 13>focus on what I think is a fundamental part of

0:17:38.770 --> 0:17:42.810
<v Speaker 13>being a human, which is fulfillment, creativity, fun, entertainment. And

0:17:43.130 --> 0:17:45.140
<v Speaker 13>I think this is to everybody's detriment to just think

0:17:45.200 --> 0:17:47.800
<v Speaker 13>about everything through the technological lens and not enough through

0:17:47.820 --> 0:17:48.380
<v Speaker 13>the human lens.

0:17:49.260 --> 0:17:52.400
<v Speaker 2>How important is it? So, you know, we're talking about

0:17:52.420 --> 0:17:55.399
<v Speaker 2>the medium of audio, but how do you sort of

0:17:55.520 --> 0:17:57.880
<v Speaker 2>make it clear to the world this is a piece

0:17:57.920 --> 0:18:00.310
<v Speaker 2>of AI-generated audio content?

0:18:00.330 --> 0:18:00.409
<v Speaker 8>Yeah.

0:18:01.220 --> 0:18:03.139
<v Speaker 2>And this is not. Do you need to? Is it

0:18:03.180 --> 0:18:06.219
<v Speaker 2>incumbent on you to say, make that distinction?

0:18:06.960 --> 0:18:09.619
<v Speaker 3>This is a really interesting issue. Just my opinion.

0:18:10.040 --> 0:18:12.139
<v Speaker 13>I think when we think about what is AI music,

0:18:12.160 --> 0:18:14.320
<v Speaker 13>what does that really mean? This is such a broad

0:18:14.359 --> 0:18:16.920
<v Speaker 13>spectrum of things, whether it's somebody typed a few words

0:18:16.960 --> 0:18:19.440
<v Speaker 13>into a text box or a professional using it just

0:18:19.510 --> 0:18:22.590
<v Speaker 13>in bits and pieces at that final step. And in

0:18:22.650 --> 0:18:25.070
<v Speaker 13>my opinion, we don't want any single party, whether it's

0:18:25.090 --> 0:18:28.570
<v Speaker 13>an AI platform or a media platform, a set of

0:18:28.630 --> 0:18:29.149
<v Speaker 13>rights holders.

0:18:29.190 --> 0:18:31.389
<v Speaker 3>We actually want to make these decisions together.

0:18:32.090 --> 0:18:34.649
<v Speaker 13>And to add more complexity to this, actually, this is

0:18:34.690 --> 0:18:38.060
<v Speaker 13>kind of a shifting landscape as the technology itself changes,

0:18:38.180 --> 0:18:39.880
<v Speaker 13>as the way in which we use AI in music

0:18:39.920 --> 0:18:42.800
<v Speaker 13>production changes. And so it's actually good that we don't

0:18:42.840 --> 0:18:44.140
<v Speaker 13>have firm rules of the road just yet.

0:18:45.000 --> 0:18:47.530
<v Speaker 2>Let's use the case study of a vocal artist. It

0:18:47.590 --> 0:18:50.390
<v Speaker 2>could be anyone, right? There are those that have concerns, right?

0:18:50.750 --> 0:18:53.030
<v Speaker 2>But there are also people that see opportunity. They could

0:18:53.109 --> 0:18:56.530
<v Speaker 2>license their voice. Essentially, they could make it available. They

0:18:56.550 --> 0:19:00.480
<v Speaker 2>could open source it, I suppose. What do you see

0:19:00.520 --> 0:19:04.200
<v Speaker 2>in that space? You know, that is basically the idea

0:19:04.220 --> 0:19:07.700
<v Speaker 2>of making a piece of content attractive because a known

0:19:08.000 --> 0:19:11.169
<v Speaker 2>entity's name is against it, even if it was AI generated.

0:19:11.820 --> 0:19:13.220
<v Speaker 3>There is so much opportunity here.

0:19:13.300 --> 0:19:16.770
<v Speaker 13>So everything you said about can you license somebody's voice

0:19:16.810 --> 0:19:19.510
<v Speaker 13>or likeness, there's so much opportunity to build.

0:19:19.310 --> 0:19:21.130
<v Speaker 3>New things around all of this.

0:19:21.210 --> 0:19:23.910
<v Speaker 13>And so that's the stuff that we're really excited about

0:19:24.790 --> 0:19:27.290
<v Speaker 13>working with our partners to build. The amazing thing is, again,

0:19:27.530 --> 0:19:32.119
<v Speaker 13>there is finally the ability to build differentiated products in

0:19:32.200 --> 0:19:34.159
<v Speaker 13>a world of music that has had a little bit

0:19:34.180 --> 0:19:35.420
<v Speaker 13>of stagnation actually today.

0:19:36.020 --> 0:19:38.159
<v Speaker 2>You go to the entrance to Bloomberg Screen Time, it

0:19:38.220 --> 0:19:41.920
<v Speaker 2>says where entertainment meets capital. So let's talk a little

0:19:41.960 --> 0:19:46.730
<v Speaker 2>bit about money. How are you building the business? And

0:19:46.730 --> 0:19:48.750
<v Speaker 2>what are your kind of capital needs? Are you kind

0:19:48.750 --> 0:19:50.689
<v Speaker 2>of in in growth mode or is is there is

0:19:50.730 --> 0:19:53.639
<v Speaker 2>now some top line traction that you've been able.

0:19:53.500 --> 0:19:56.760
<v Speaker 13>To get There's been a fair amount of traction, and

0:19:56.780 --> 0:19:59.100
<v Speaker 13>you said 100 million users have used it. The last

0:19:59.760 --> 0:20:03.179
<v Speaker 13>stats that we released were 2 million subscribers.

0:20:03.180 --> 0:20:04.440
<v Speaker 3>$ 300 million in revenue.

0:20:04.480 --> 0:20:06.780
<v Speaker 13>We are far beyond that by now, and so there is.

0:20:06.720 --> 0:20:07.440
<v Speaker 3>Quite a lot of traction.

0:20:07.460 --> 0:20:08.260
<v Speaker 2>Far beyond those two numbers.

0:20:08.280 --> 0:20:09.060
<v Speaker 3>Yes, we are.

0:20:09.460 --> 0:20:12.240
<v Speaker 13>And I think, just thinking about investors, we have amazing

0:20:12.280 --> 0:20:16.160
<v Speaker 13>investors and partners for building this business, but a lot

0:20:16.200 --> 0:20:18.189
<v Speaker 13>of people think of music as a small business and

0:20:18.350 --> 0:20:20.109
<v Speaker 13>one that they don't necessarily want to get into, and

0:20:20.150 --> 0:20:22.840
<v Speaker 13>I think We've shown the world, actually, that music is

0:20:22.880 --> 0:20:24.600
<v Speaker 13>a big business. Music is a really big part of

0:20:24.640 --> 0:20:27.160
<v Speaker 13>people's lives, and there's immense potential for growth.

0:20:28.740 --> 0:20:32.149
<v Speaker 2>How do you manage usage, right? Because you must have

0:20:32.170 --> 0:20:35.379
<v Speaker 2>compute costs. and then there's what you charge. How do

0:20:35.420 --> 0:20:36.040
<v Speaker 2>you balance that?

0:20:36.560 --> 0:20:39.220
<v Speaker 3>Yeah, we're kind of in the middle here.

0:20:39.240 --> 0:20:42.780
<v Speaker 13>You know, we're not in the regime of, let's say, streaming,

0:20:42.859 --> 0:20:45.560
<v Speaker 13>where the marginal cost of serving our stuff is so small.

0:20:45.900 --> 0:20:49.250
<v Speaker 13>But we're also not in the business of general intelligence,

0:20:49.270 --> 0:20:51.290
<v Speaker 13>where we just need to throw as much compute as

0:20:51.350 --> 0:20:53.150
<v Speaker 13>possible at our problems, and they'll all get solved.

0:20:53.230 --> 0:20:55.410
<v Speaker 3>Music is art. Music doesn't have right answers.

0:20:55.450 --> 0:20:58.010
<v Speaker 13>Music is not something that you can just scale, and

0:20:58.030 --> 0:20:59.250
<v Speaker 13>you'll get to where you want to go. And so

0:20:59.270 --> 0:21:01.239
<v Speaker 13>we kind of sit in this in-between, and I think

0:21:01.260 --> 0:21:02.520
<v Speaker 13>we're doing okay from that perspective.

0:21:03.190 --> 0:21:05.210
<v Speaker 2>Suno CEO, Mikey Shulman, it's been great to have you

0:21:05.250 --> 0:21:07.570
<v Speaker 2>here with us on Bloomberg Tech. Thank you very much indeed.

0:21:07.830 --> 0:21:09.330
<v Speaker 2>Let's get to some news in the world of AI.

0:21:09.530 --> 0:21:13.810
<v Speaker 2>OpenAI is accusing Chinese rival Moonshot AI of trying to

0:21:13.869 --> 0:21:16.790
<v Speaker 2>extract proprietary data from its models. The company says users

0:21:17.070 --> 0:21:19.990
<v Speaker 2>tied to Moonshot made thousands of attempts to uncover how

0:21:20.050 --> 0:21:23.390
<v Speaker 2>its models reason through problems. Bloomberg Senior Tech Editor Mike

0:21:23.410 --> 0:21:28.219
<v Speaker 2>Shepard joins us now. This was a big story yesterday

0:21:28.240 --> 0:21:30.959
<v Speaker 2>that came just after the show. Explain the accusation.

0:21:32.000 --> 0:21:36.280
<v Speaker 8>Well, the claims are that Moonshot had been working with

0:21:36.359 --> 0:21:40.750
<v Speaker 8>or had actors that were associated with the company seeking

0:21:40.790 --> 0:21:44.650
<v Speaker 8>to extract data en masse from OpenAI in a way

0:21:44.710 --> 0:21:48.310
<v Speaker 8>that would evade OpenAI's attempts to hide some of the

0:21:48.410 --> 0:21:51.770
<v Speaker 8>reasoning of its models. Companies like OpenAI and Anthropic have

0:21:51.790 --> 0:21:55.070
<v Speaker 8>been trying to put up defenses against this practice of

0:21:55.150 --> 0:21:59.270
<v Speaker 8>distillation where data is is extracted en masse and used

0:21:59.310 --> 0:22:02.729
<v Speaker 8>to build new chatbots. And normally in the AI industry,

0:22:02.780 --> 0:22:05.520
<v Speaker 8>this practice is acceptable. But when it's carried out on

0:22:05.560 --> 0:22:09.520
<v Speaker 8>an industrial scale, that's where these companies get concerned. And

0:22:09.560 --> 0:22:13.560
<v Speaker 8>we've heard anthropic and open AI level accusations against their

0:22:13.600 --> 0:22:17.930
<v Speaker 8>Chinese competitors of unfair play in using distillation. And in fact,

0:22:17.950 --> 0:22:21.610
<v Speaker 8>the Trump administration has even warned of sanctions on the

0:22:21.770 --> 0:22:24.290
<v Speaker 8>practice against companies that have been carrying it out. And

0:22:24.310 --> 0:22:27.469
<v Speaker 8>we've also seen Anthropic issue its own set of claims

0:22:27.530 --> 0:22:32.600
<v Speaker 8>against Alibaba and also Moonshot for similar versions of this ad.

0:22:32.920 --> 0:22:36.119
<v Speaker 8>So it highlights how both the attempts of the companies

0:22:36.619 --> 0:22:39.379
<v Speaker 8>to try to put up defenses are being evaded and

0:22:39.440 --> 0:22:43.090
<v Speaker 8>that the practice is still under is still being continued.

0:22:45.910 --> 0:22:49.280
<v Speaker 2>Shep, there's another major story out there that we'd be

0:22:49.300 --> 0:22:53.460
<v Speaker 2>grateful for some reporting on, how the world and America

0:22:53.520 --> 0:22:56.210
<v Speaker 2>feels about guardrails, some whole data. Tell me about it.

0:22:57.340 --> 0:23:00.879
<v Speaker 8>Well, yesterday, and this was a day after President Donald

0:23:00.900 --> 0:23:05.520
<v Speaker 8>Trump held that high-profile lunch with Silicon Valley leaders, Quinnipiac

0:23:05.600 --> 0:23:10.679
<v Speaker 8>University in Connecticut released findings that showed 91% of Americans

0:23:10.790 --> 0:23:16.060
<v Speaker 8>favor putting some guardrails on artificial intelligence. and 81% support

0:23:16.340 --> 0:23:21.870
<v Speaker 8>safety over innovation when it comes to actually pursuing AI development. Now,

0:23:21.990 --> 0:23:24.489
<v Speaker 8>that really stands in contrast with what we heard from

0:23:24.510 --> 0:23:28.590
<v Speaker 8>the president on Tuesday, The industry should police itself that

0:23:29.030 --> 0:23:31.930
<v Speaker 8>in this agreement that they unveiled a few hours after

0:23:32.570 --> 0:23:35.290
<v Speaker 8>this lunch at the White House, that the industry would

0:23:35.410 --> 0:23:38.990
<v Speaker 8>take care of running its own tests on its models,

0:23:39.230 --> 0:23:41.810
<v Speaker 8>but that the government would take and continue to take

0:23:42.150 --> 0:23:46.760
<v Speaker 8>this hands-off approach. And what was interesting also in these findings, Zeb,

0:23:46.780 --> 0:23:51.399
<v Speaker 8>was how people view the technology industry itself. 74% of

0:23:51.440 --> 0:23:54.800
<v Speaker 8>those surveyed said that they don't trust AI leaders. And

0:23:54.840 --> 0:23:58.949
<v Speaker 8>that also reflects a broader distrust of the technology itself, Ed.

0:23:59.310 --> 0:24:03.450
<v Speaker 8>We saw in the survey findings that 53% of Americans

0:24:03.550 --> 0:24:07.010
<v Speaker 8>said that they see AI causing more harm.

0:24:06.810 --> 0:24:08.649
<v Speaker 3>Than good in their daily lives.

0:24:08.710 --> 0:24:12.409
<v Speaker 8>Now, AI leaders, including Sam Altman, whom you spoke about

0:24:13.250 --> 0:24:16.649
<v Speaker 8>this very issue with during your interview with him a

0:24:16.710 --> 0:24:19.670
<v Speaker 8>few weeks back, they see it as a messaging problem

0:24:19.790 --> 0:24:22.300
<v Speaker 8>and a branding problem. President Donald Trump has tried to

0:24:22.340 --> 0:24:25.820
<v Speaker 8>address it, of course, by renaming it superintelligence. And yet

0:24:25.840 --> 0:24:28.880
<v Speaker 8>we're seeing in these results that the American public has

0:24:28.980 --> 0:24:32.440
<v Speaker 8>deep misgivings about the technology, its impact, and its safety.

0:24:35.480 --> 0:24:39.560
<v Speaker 2>Bloomberg's Mike Sheppard out of D.C. Thank you very much indeed. Okay,

0:24:39.600 --> 0:24:41.139
<v Speaker 2>back to Hollywood and coming up, we're going to be

0:24:41.580 --> 0:24:45.200
<v Speaker 2>joined by George Stompoulos from Promise to talk about the

0:24:45.260 --> 0:24:49.000
<v Speaker 2>need to redefine what a studio looks like in the

0:24:49.140 --> 0:24:52.280
<v Speaker 2>AI age. Let's also talk a little bit about what's

0:24:52.300 --> 0:24:56.680
<v Speaker 2>happening above our heads. Dragon now in orbit, traveling 17,500

0:24:56.680 --> 0:25:00.050
<v Speaker 2>miles an hour. Next, the nose cone opens. It exposes

0:25:00.109 --> 0:25:03.070
<v Speaker 2>the systems that Dragon needs to rendezvous and dock with

0:25:03.109 --> 0:25:07.369
<v Speaker 2>the ISS. From there, spacecraft performs a series of carefully

0:25:07.390 --> 0:25:10.969
<v Speaker 2>timed burns, catches up with ISS. That journey is going

0:25:10.990 --> 0:25:14.490
<v Speaker 2>to take that crew of four, three first-time flyers aboard

0:25:14.730 --> 0:25:19.650
<v Speaker 2>Falcon 9 Dragon to the International Space Station before Dragon

0:25:19.670 --> 0:25:23.980
<v Speaker 2>essentially lines itself up and autonomously docks with the International

0:25:24.020 --> 0:25:27.900
<v Speaker 2>Space Station. It's a long-duration mission in orbit for that

0:25:28.160 --> 0:25:33.040
<v Speaker 2>four-person crew. But as they say, everything nominal so far.

0:25:41.450 --> 0:25:43.490
<v Speaker 2>Welcome back to a special edition of Bloomberg Tech. We're

0:25:43.520 --> 0:25:46.540
<v Speaker 2>live from Bloomberg Screen Time in Los Angeles. AI is

0:25:46.600 --> 0:25:49.560
<v Speaker 2>moving deeper into Hollywood, not just as a tool, but

0:25:49.619 --> 0:25:52.080
<v Speaker 2>as the foundation for an entirely new kind of studio.

0:25:52.540 --> 0:25:55.760
<v Speaker 2>Promise is an AI native studio, betting that the tech

0:25:55.960 --> 0:25:59.840
<v Speaker 2>can fundamentally reshape how entertainment gets made. And its CEO

0:26:00.080 --> 0:26:04.240
<v Speaker 2>and co-founder, George Trompoulos, joins us now. What is an

0:26:04.280 --> 0:26:06.920
<v Speaker 2>AI native studio, George? Let's start with the basics.

0:26:07.080 --> 0:26:07.879
<v Speaker 6>Great question, Ed.

0:26:08.080 --> 0:26:11.959
<v Speaker 10>So, you know, the advent of generative AI has enabled

0:26:12.020 --> 0:26:15.369
<v Speaker 10>creators to have 10X superpowers. And we sought out to

0:26:15.510 --> 0:26:18.970
<v Speaker 10>build a company around these new types of creators. They

0:26:19.190 --> 0:26:22.929
<v Speaker 10>are leveraging all the best models to produce original films

0:26:22.990 --> 0:26:25.670
<v Speaker 10>and series at a fraction of the traditional cost and timeline.

0:26:25.760 --> 0:26:27.760
<v Speaker 2>You know, I think back just even maybe last year,

0:26:27.780 --> 0:26:31.930
<v Speaker 2>but three years ago, discussing the basic premise of And

0:26:32.090 --> 0:26:35.449
<v Speaker 2>for lots of people, the dream was the prompt results

0:26:35.510 --> 0:26:38.370
<v Speaker 2>in a feature film coming out the other side. Is

0:26:38.430 --> 0:26:43.480
<v Speaker 2>that a reality now? We're talking about something very specific.

0:26:43.560 --> 0:26:45.480
<v Speaker 6>You know, this is an artist-led process.

0:26:46.280 --> 0:26:49.060
<v Speaker 10>You know, of course, when you open up an AI model,

0:26:49.080 --> 0:26:50.780
<v Speaker 10>you can prompt something and get a result.

0:26:51.240 --> 0:26:52.520
<v Speaker 6>Models are good for shots.

0:26:53.000 --> 0:26:55.629
<v Speaker 10>Studios are good for producing films and series.

0:26:55.770 --> 0:26:57.290
<v Speaker 6>And it's a collaborative process.

0:26:57.730 --> 0:27:01.890
<v Speaker 10>It brings together artistry from character designers to environmental designers

0:27:01.990 --> 0:27:05.530
<v Speaker 10>to visual effects artists and of course great storytellers. So

0:27:05.570 --> 0:27:07.470
<v Speaker 10>a lot of the roles you would see in traditional

0:27:07.490 --> 0:27:10.629
<v Speaker 10>filmmaking process are still there. But what's possible now is

0:27:10.670 --> 0:27:12.680
<v Speaker 10>for smaller teams to do high impact work.

0:27:12.980 --> 0:27:15.480
<v Speaker 2>I guess another way of pushing you on it, George,

0:27:15.520 --> 0:27:17.840
<v Speaker 2>is to ask what is it that you do differently

0:27:18.180 --> 0:27:21.600
<v Speaker 2>to a traditional Hollywood studio? How is the setup different?

0:27:21.859 --> 0:27:22.880
<v Speaker 6>You know, if you look back at the.

0:27:22.859 --> 0:27:25.940
<v Speaker 10>History of entertainment, there have been these technological shifts that

0:27:25.960 --> 0:27:28.350
<v Speaker 10>have changed how the business works. We think there's no

0:27:28.390 --> 0:27:31.109
<v Speaker 10>doubt that the advent of generative AI will be another

0:27:31.170 --> 0:27:33.909
<v Speaker 10>one of them. So we are really rethinking the business

0:27:33.930 --> 0:27:37.199
<v Speaker 10>from first principles, from how ideas are shaped, developed and

0:27:37.240 --> 0:27:41.600
<v Speaker 10>tested all the way through to production, post-production and even

0:27:41.660 --> 0:27:42.740
<v Speaker 10>how they're brought to audiences.

0:27:42.760 --> 0:27:44.580
<v Speaker 2>But is it like, you know, somebody has a script.

0:27:44.680 --> 0:27:46.790
<v Speaker 2>That's how this town works, right? Somebody has a script.

0:27:47.180 --> 0:27:50.050
<v Speaker 2>They come to you and they say, here you go.

0:27:51.010 --> 0:27:56.090
<v Speaker 10>You know, we do collaborate with incredible writers in Hollywood,

0:27:56.230 --> 0:28:00.870
<v Speaker 10>as well as storytellers who haven't had their moment yet.

0:28:01.410 --> 0:28:03.450
<v Speaker 10>And one thing that we do that's quite different, Ed,

0:28:03.710 --> 0:28:06.250
<v Speaker 10>is we make the last thing first.

0:28:06.390 --> 0:28:07.350
<v Speaker 6>Here's what I mean by that.

0:28:07.690 --> 0:28:10.119
<v Speaker 10>Typically, if you're making a film, one of the last

0:28:10.150 --> 0:28:11.689
<v Speaker 10>things you do is produce the trailer.

0:28:12.200 --> 0:28:14.220
<v Speaker 6>In our world, once we have the story, the.

0:28:14.180 --> 0:28:17.320
<v Speaker 10>Script, the idea developed, we actually go straight to a

0:28:17.380 --> 0:28:19.899
<v Speaker 10>trailer or a proof of concept. So we can see

0:28:19.940 --> 0:28:21.780
<v Speaker 10>the story leap off the page. You can get a

0:28:21.850 --> 0:28:23.730
<v Speaker 10>sense of how it's going to look, feel, and sound.

0:28:23.810 --> 0:28:26.590
<v Speaker 2>Let's take that trailer. Let's say it's three minutes long,

0:28:26.590 --> 0:28:31.750
<v Speaker 2>90 seconds. How much of that product is AI generated?

0:28:32.130 --> 0:28:34.290
<v Speaker 2>How much of it is not? That's the bit that

0:28:34.310 --> 0:28:35.870
<v Speaker 2>I think people are trying to understand.

0:28:36.210 --> 0:28:39.570
<v Speaker 10>In our case, we leverage generative media for a large

0:28:39.630 --> 0:28:42.010
<v Speaker 10>portion of the process. It sort of depends on what

0:28:42.070 --> 0:28:44.850
<v Speaker 10>type of project you're talking about. At Promise, we're focused

0:28:44.910 --> 0:28:48.630
<v Speaker 10>on animation. We're also focused on what's called hybrid. Hybrid

0:28:48.710 --> 0:28:52.780
<v Speaker 10>is human performance in synthetic environments. And what that does

0:28:52.900 --> 0:28:55.500
<v Speaker 10>is it serves to bring down the cost of visual

0:28:55.540 --> 0:28:59.460
<v Speaker 10>effects and allowing smaller films to have great scope and scale.

0:28:59.580 --> 0:29:01.640
<v Speaker 2>Okay, that's where I wanted to go. So you talked about,

0:29:01.720 --> 0:29:04.380
<v Speaker 2>you know, when there is a technological shift, it changes

0:29:04.440 --> 0:29:09.030
<v Speaker 2>an industry. Let's get to the economic change. Is this

0:29:09.690 --> 0:29:14.440
<v Speaker 2>the case that the production process of a feature film

0:29:14.720 --> 0:29:18.620
<v Speaker 2>or a television series is lowered through how you set

0:29:18.660 --> 0:29:20.090
<v Speaker 2>yourselves up through the technology?

0:29:20.270 --> 0:29:23.810
<v Speaker 10>Yeah, this is actually about a reduction in cost and timeline.

0:29:24.210 --> 0:29:27.090
<v Speaker 10>In the animated side, we're seeing cost reductions in the 50%

0:29:27.090 --> 0:29:27.470
<v Speaker 10>plus range.

0:29:28.730 --> 0:29:29.680
<v Speaker 6>For certain productions.

0:29:29.820 --> 0:29:32.400
<v Speaker 10>Now that's not to say every animated project needs to

0:29:32.820 --> 0:29:35.260
<v Speaker 10>follow this methodology, but in our case we see that

0:29:35.320 --> 0:29:37.330
<v Speaker 10>as an opportunity to bring new stories to life that

0:29:37.350 --> 0:29:38.250
<v Speaker 10>weren't possible before.

0:29:39.540 --> 0:29:42.060
<v Speaker 2>That's a saving for the industry. How does that manifest

0:29:42.140 --> 0:29:46.400
<v Speaker 2>as business for you? What makes working with you, George, attractive?

0:29:46.720 --> 0:29:49.860
<v Speaker 10>We think that it creates a new opportunity to shift

0:29:49.900 --> 0:29:50.460
<v Speaker 10>the paradigm.

0:29:51.870 --> 0:29:53.510
<v Speaker 6>If we were setting.

0:29:53.310 --> 0:29:55.840
<v Speaker 10>Out to produce an animated feature in the past, that

0:29:55.860 --> 0:29:58.320
<v Speaker 10>would cost hundreds of millions of dollars and take years

0:29:58.380 --> 0:30:01.500
<v Speaker 10>and years and years. Now, with the reduced cost, we

0:30:01.550 --> 0:30:03.850
<v Speaker 10>can produce that ourselves. We can own that and we

0:30:03.890 --> 0:30:06.790
<v Speaker 10>can seek the distribution that we need for such projects.

0:30:06.850 --> 0:30:09.250
<v Speaker 10>So many stories that weren't told before are now going.

0:30:09.090 --> 0:30:09.709
<v Speaker 6>To be unlocked.

0:30:10.060 --> 0:30:15.220
<v Speaker 2>I'm super interested in the backstory, backing from Andreessen Horowitz,

0:30:15.660 --> 0:30:20.860
<v Speaker 2>Google's AI Futures Fund, kind of incubated by Disney. You're

0:30:20.880 --> 0:30:22.980
<v Speaker 2>growing a startup? Is that fair?

0:30:23.310 --> 0:30:26.610
<v Speaker 10>Yeah, this is absolutely a startup. We're a two-year-old company.

0:30:27.310 --> 0:30:30.510
<v Speaker 10>We've been deep in R &amp; D, building the structure

0:30:30.530 --> 0:30:32.270
<v Speaker 10>of what we think a studio should look like in

0:30:32.310 --> 0:30:34.770
<v Speaker 10>the modern era. We've been fortunate to bring on great

0:30:34.790 --> 0:30:38.330
<v Speaker 10>partners that you've mentioned. We participated in the Disney Accelerator,

0:30:38.370 --> 0:30:40.850
<v Speaker 10>which is how they engage with new innovative companies. They've

0:30:40.870 --> 0:30:45.130
<v Speaker 10>been a tremendous partner. Really excited about collaborating with them. And,

0:30:45.310 --> 0:30:47.890
<v Speaker 10>you know, we're now entering into the production phase. So

0:30:47.910 --> 0:30:51.330
<v Speaker 10>we're in production this week on a hybrid. horror series

0:30:51.690 --> 0:30:54.120
<v Speaker 10>which is uh has the scope and scale of a

0:30:54.150 --> 0:30:57.960
<v Speaker 10>massive budget uh series but is actually done again at

0:30:57.980 --> 0:31:00.400
<v Speaker 10>a fraction of the cost and timeline with an incredible

0:31:00.440 --> 0:31:03.980
<v Speaker 10>crew of artists as well as ai artists that help

0:31:04.020 --> 0:31:05.060
<v Speaker 10>bring the story to life.

0:31:05.950 --> 0:31:08.960
<v Speaker 2>George Trompolo, CEO, founder of Promise. It's been great to

0:31:08.980 --> 0:31:09.680
<v Speaker 2>have you here on the show.

0:31:09.720 --> 0:31:09.959
<v Speaker 8>Thank you.

0:31:10.000 --> 0:31:13.580
<v Speaker 2>Thank you very much indeed. Coming up, could AI actually

0:31:13.620 --> 0:31:17.400
<v Speaker 2>help bring production back to Los Angeles? We'll discuss with

0:31:17.680 --> 0:31:20.280
<v Speaker 2>Caroline Ingborn from Luma AI. I actually came up last

0:31:20.360 --> 0:31:24.360
<v Speaker 2>night with Netflix's Ted Sarandos as well. As networks tighten

0:31:24.380 --> 0:31:28.400
<v Speaker 2>their budgets, Conan O'Brien told Bloomberg's Ashley Carman that while

0:31:28.460 --> 0:31:30.700
<v Speaker 2>this is a real problem for comedians, both good and

0:31:30.780 --> 0:31:32.440
<v Speaker 2>bad can come out of it.

0:31:32.880 --> 0:31:33.580
<v Speaker 3>Just like AI.

0:31:34.020 --> 0:31:34.800
<v Speaker 2>This is Bloomberg Tech.

0:31:36.080 --> 0:31:37.640
<v Speaker 3>Things are changing.

0:31:37.660 --> 0:31:40.510
<v Speaker 14>The way I see it is that it's like the

0:31:40.550 --> 0:31:45.190
<v Speaker 14>discussions about AI. There will be amazing benefits, and then

0:31:45.210 --> 0:31:49.810
<v Speaker 14>there will be some horrible unintended consequences, and that is

0:31:50.370 --> 0:31:52.290
<v Speaker 14>the case with anything that's new.

0:31:52.770 --> 0:31:53.170
<v Speaker 3>Anything.

0:32:04.620 --> 0:32:08.450
<v Speaker 15>When I worry about AI... I worry about my kids

0:32:08.510 --> 0:32:12.750
<v Speaker 15>in school. I worry about the 30% rise in the

0:32:12.790 --> 0:32:14.910
<v Speaker 15>number of A's given out at colleges over the last

0:32:14.950 --> 0:32:15.430
<v Speaker 15>three years.

0:32:15.530 --> 0:32:16.850
<v Speaker 4>I worry about learned helplessness.

0:32:17.430 --> 0:32:22.650
<v Speaker 15>I worry about responsible use. I don't worry about Skynet,

0:32:22.790 --> 0:32:25.310
<v Speaker 15>and I don't think that it's going to take over

0:32:25.370 --> 0:32:28.090
<v Speaker 15>this business in any meaningful way. I think it's going

0:32:28.110 --> 0:32:28.670
<v Speaker 15>to be additive.

0:32:33.230 --> 0:32:35.810
<v Speaker 2>That was actor and producer Ben Affleck, who thinks AI

0:32:35.850 --> 0:32:39.020
<v Speaker 2>will actually be an added benefit to the filmmaking industry.

0:32:39.400 --> 0:32:42.220
<v Speaker 2>In the same vein, AI startup Luma AI says the

0:32:42.260 --> 0:32:45.800
<v Speaker 2>technology could actually help bring production back to Los Angeles

0:32:45.860 --> 0:32:50.140
<v Speaker 2>by lowering costs and making ambitious projects faster and easier

0:32:50.180 --> 0:32:54.610
<v Speaker 2>to produce without sacrificing creative control. Luma AI COO Caroline

0:32:54.690 --> 0:32:58.510
<v Speaker 2>Ingerborn joins us now. You and I were listening to Mr.

0:32:58.550 --> 0:33:03.590
<v Speaker 2>Affleck together last night. His view on AI's role in

0:33:03.610 --> 0:33:08.730
<v Speaker 2>the filmmaking process or the creative process. Obviously, Luma believes

0:33:08.810 --> 0:33:11.650
<v Speaker 2>AI has a role. Just explain what Luma does and

0:33:12.530 --> 0:33:14.130
<v Speaker 2>how you make a role in Hollywood.

0:33:17.220 --> 0:33:20.000
<v Speaker 5>So Luma started out as a frontier research lab.

0:33:20.300 --> 0:33:20.760
<v Speaker 12>That's right.

0:33:21.940 --> 0:33:23.700
<v Speaker 1>What we are today is a full stack company.

0:33:23.920 --> 0:33:28.400
<v Speaker 5>So what that means is that we do research on

0:33:29.270 --> 0:33:30.790
<v Speaker 5>multimodal AI models.

0:33:32.020 --> 0:33:34.320
<v Speaker 1>But then where our product.

0:33:34.060 --> 0:33:36.970
<v Speaker 5>Is and how we go to market is focused on

0:33:36.990 --> 0:33:38.130
<v Speaker 5>AI for creative work.

0:33:40.130 --> 0:33:41.070
<v Speaker 1>And so if you.

0:33:41.010 --> 0:33:44.850
<v Speaker 5>Look at this of how the industry has evolved, it

0:33:44.930 --> 0:33:49.220
<v Speaker 5>is first like you need these models to be able

0:33:49.260 --> 0:33:53.400
<v Speaker 5>to do anything, right? But if you only use the models,

0:33:53.440 --> 0:33:56.100
<v Speaker 5>they are very unruly. And you saw this in the

0:33:56.220 --> 0:33:59.220
<v Speaker 5>early user behavior. So the second layer of this is

0:33:59.300 --> 0:34:03.969
<v Speaker 5>building products for creative professionals so that they can access

0:34:03.990 --> 0:34:09.790
<v Speaker 5>the models, but also retain control. And the third layer

0:34:10.190 --> 0:34:16.280
<v Speaker 5>is having forward-deployed creatives and engineers so that adoption really

0:34:16.860 --> 0:34:17.840
<v Speaker 5>actually takes place.

0:34:18.080 --> 0:34:21.060
<v Speaker 2>Yeah, we're familiar with the concept of the forward-deployed engineer

0:34:21.120 --> 0:34:25.140
<v Speaker 2>generally in the field of AI. In my conversation with

0:34:25.180 --> 0:34:28.820
<v Speaker 2>George Strompolos just a minute ago, I kind of outlined

0:34:28.900 --> 0:34:32.040
<v Speaker 2>what the original vision was, but the prompt and the

0:34:32.140 --> 0:34:36.370
<v Speaker 2>output is a full feature length film. That's not the reality, right?

0:34:36.410 --> 0:34:39.090
<v Speaker 5>No, that is not the reality. And I would say

0:34:39.130 --> 0:34:40.050
<v Speaker 5>that's not the goal.

0:34:42.030 --> 0:34:42.609
<v Speaker 2>What is the goal?

0:34:42.750 --> 0:34:43.430
<v Speaker 1>The goal is.

0:34:43.390 --> 0:34:47.090
<v Speaker 5>Not to have a prompt input. This is a tool

0:34:47.330 --> 0:34:51.070
<v Speaker 5>at the end of the day. And what I'm seeing

0:34:51.130 --> 0:34:52.930
<v Speaker 5>that is so exciting is when.

0:34:54.250 --> 0:34:54.989
<v Speaker 1>Can I take this out?

0:34:55.030 --> 0:34:55.630
<v Speaker 3>Please pull it out.

0:34:55.650 --> 0:34:56.230
<v Speaker 2>Don't worry about it.

0:34:56.510 --> 0:34:56.740
<v Speaker 1>Thank you.

0:34:58.190 --> 0:35:01.690
<v Speaker 5>What I'm seeing that is so exciting is this is

0:35:01.770 --> 0:35:04.310
<v Speaker 5>a tool as all other tools that we have seen.

0:35:04.350 --> 0:35:07.690
<v Speaker 5>And Hollywood is like built on technology shifts.

0:35:08.360 --> 0:35:09.960
<v Speaker 1>This is a new technology shift.

0:35:11.290 --> 0:35:14.029
<v Speaker 5>So far, I haven't seen any technology shift having as

0:35:14.130 --> 0:35:14.740
<v Speaker 5>a goal to.

0:35:14.890 --> 0:35:16.400
<v Speaker 1>It's a collaborative process.

0:35:16.420 --> 0:35:18.780
<v Speaker 2>Well, on that collaboration, so I find the Luma agent

0:35:18.880 --> 0:35:21.960
<v Speaker 2>interesting because you start as a frontier lab, right? But

0:35:22.040 --> 0:35:25.529
<v Speaker 2>really what the agent does is direct the project to

0:35:25.570 --> 0:35:28.810
<v Speaker 2>the best underlying model for that project. And it could

0:35:28.870 --> 0:35:31.630
<v Speaker 2>come from OpenAI. It could come from another partner.

0:35:31.730 --> 0:35:31.930
<v Speaker 3>Yes.

0:35:32.170 --> 0:35:33.790
<v Speaker 2>Explain why that's important.

0:35:34.110 --> 0:35:35.490
<v Speaker 1>It's very important because.

0:35:36.300 --> 0:35:39.880
<v Speaker 5>In the creative field today, and I would argue in

0:35:39.920 --> 0:35:43.480
<v Speaker 5>many fields today, there is no model to rule them all.

0:35:43.940 --> 0:35:44.940
<v Speaker 1>There is no model.

0:35:44.739 --> 0:35:47.540
<v Speaker 5>That can make a movie, even though I don't think

0:35:47.640 --> 0:35:50.300
<v Speaker 5>any video AI company has that as a goal.

0:35:50.320 --> 0:35:52.299
<v Speaker 2>Sweet Lord of the Rings reference, by the way.

0:35:53.680 --> 0:35:55.000
<v Speaker 1>There is no one to rule them all.

0:35:55.100 --> 0:35:58.029
<v Speaker 5>And so what that means is that as the creative professional,

0:35:58.510 --> 0:36:02.990
<v Speaker 5>as our user, we serve them. And so we want

0:36:03.210 --> 0:36:07.779
<v Speaker 5>our creative agent is... trained to give you as the

0:36:07.820 --> 0:36:12.690
<v Speaker 5>creative professional access to the best model for what you

0:36:12.770 --> 0:36:15.850
<v Speaker 5>are trying to solve for and so sometimes that means

0:36:15.870 --> 0:36:19.750
<v Speaker 5>like yes you should go to the absolutely latest video

0:36:19.770 --> 0:36:23.750
<v Speaker 5>model to get the highest quality output but if you're

0:36:23.790 --> 0:36:27.770
<v Speaker 5>in the ideation phase and you want to generate a

0:36:28.070 --> 0:36:32.730
<v Speaker 5>lot of content you don't need to pay for that Highest,

0:36:32.790 --> 0:36:35.590
<v Speaker 5>most prestige. You want to be able to generate a

0:36:35.660 --> 0:36:36.800
<v Speaker 5>lot and quite fast.

0:36:36.820 --> 0:36:37.940
<v Speaker 2>We're still talking about tokens.

0:36:38.280 --> 0:36:40.100
<v Speaker 1>Yes, we're still talking about tokens.

0:36:40.320 --> 0:36:45.500
<v Speaker 2>Last night, the Netflix co-CEO Ted Sarandos talked about filmmaking

0:36:45.540 --> 0:36:49.920
<v Speaker 2>in America, content creation in America, and in particular Los Angeles.

0:36:49.960 --> 0:36:53.150
<v Speaker 2>And he talked about three specific projects, $ 400 million worth

0:36:53.190 --> 0:37:00.080
<v Speaker 2>of production spend. Luma also has this argument that AI brings... energy,

0:37:00.420 --> 0:37:03.330
<v Speaker 2>activity back to LA. What is that about? What is

0:37:03.370 --> 0:37:04.049
<v Speaker 2>your point of view?

0:37:04.070 --> 0:37:09.430
<v Speaker 5>I think there's like two very clear cases here. One

0:37:09.530 --> 0:37:12.940
<v Speaker 5>is like if you are in LA today and you

0:37:12.960 --> 0:37:17.830
<v Speaker 5>spend time in the community, It's fantastic. There are so

0:37:17.930 --> 0:37:23.259
<v Speaker 5>many people that have dived into this new technology, and

0:37:23.280 --> 0:37:26.720
<v Speaker 5>they're collaborating, they're supporting each other, they're making more content,

0:37:26.739 --> 0:37:30.819
<v Speaker 5>they're sharing. The internet is filled with people just sharing, like, hey,

0:37:30.900 --> 0:37:32.739
<v Speaker 5>I found out how to do this, I found out

0:37:32.800 --> 0:37:36.910
<v Speaker 5>how to control this. It's a very generous, excited, and

0:37:37.030 --> 0:37:38.240
<v Speaker 5>curious community.

0:37:38.260 --> 0:37:39.169
<v Speaker 2>Generous token spend?

0:37:39.190 --> 0:37:39.260
<v Speaker 8>Yes.

0:37:40.550 --> 0:37:44.330
<v Speaker 5>It's a generous token spend, but ultimately they're also finding

0:37:44.370 --> 0:37:47.120
<v Speaker 5>a bunch of hacks of how to optimize the token

0:37:47.140 --> 0:37:50.560
<v Speaker 5>spend and get the most out of your token spend.

0:37:51.880 --> 0:37:54.219
<v Speaker 5>The other one, which is a very clear example, is

0:37:54.320 --> 0:37:56.060
<v Speaker 5>our collaboration with John Irvin.

0:37:56.430 --> 0:37:56.620
<v Speaker 1>Yes.

0:37:57.489 --> 0:37:57.609
<v Speaker 8>And.

0:37:58.239 --> 0:38:00.620
<v Speaker 1>So what he has shown.

0:38:00.340 --> 0:38:05.209
<v Speaker 5>With a project called a TV show at Amazon called

0:38:05.510 --> 0:38:08.109
<v Speaker 5>Moses is that what he was able to do, so

0:38:08.170 --> 0:38:12.670
<v Speaker 5>he spent years making TV shows abroad because that's how

0:38:12.730 --> 0:38:15.549
<v Speaker 5>he could get the most out of the investments that

0:38:15.969 --> 0:38:18.790
<v Speaker 5>he was doing and to tell his story. And that's

0:38:18.810 --> 0:38:21.750
<v Speaker 5>like the constraint that you see if you're like at the,

0:38:22.800 --> 0:38:25.000
<v Speaker 5>you know, the biggest director in the world, or if

0:38:25.060 --> 0:38:27.810
<v Speaker 5>you're a YouTuber starting out, at the end of the day,

0:38:28.270 --> 0:38:30.930
<v Speaker 5>you want to be able to tell your story. And

0:38:31.010 --> 0:38:34.960
<v Speaker 5>so capital comes into that storytelling. But what John was

0:38:35.060 --> 0:38:39.390
<v Speaker 5>able to do with Moses is... In Manhattan Beach, on

0:38:39.450 --> 0:38:43.680
<v Speaker 5>a stage, hundreds of people working together to make Moses happen.

0:38:44.040 --> 0:38:48.500
<v Speaker 5>And he was able to do that by hybrid filmmaking.

0:38:48.820 --> 0:38:51.280
<v Speaker 1>So is it AI? Is it not AI?

0:38:51.340 --> 0:38:52.080
<v Speaker 3>No, it's hybrid.

0:38:52.460 --> 0:38:56.069
<v Speaker 5>And so they're real actors. There is a bunch of

0:38:56.110 --> 0:39:01.210
<v Speaker 5>people using AI to move these actors from the stage

0:39:01.930 --> 0:39:05.319
<v Speaker 5>in Manhattan Beach into any environment that you want. And

0:39:05.450 --> 0:39:08.310
<v Speaker 5>this retains the actor's performance.

0:39:08.750 --> 0:39:09.630
<v Speaker 1>It enhances it.

0:39:10.210 --> 0:39:12.250
<v Speaker 5>If you speak to the actors, it's a lot more

0:39:12.330 --> 0:39:15.009
<v Speaker 5>fun than any green screen has ever been. And the

0:39:15.090 --> 0:39:16.450
<v Speaker 5>end result is fantastic.

0:39:17.469 --> 0:39:21.469
<v Speaker 2>Luma AI, COO, Caroline Ingeborn, it's been great to catch up.

0:39:21.610 --> 0:39:23.570
<v Speaker 2>Thank you very much for being with us here on

0:39:23.590 --> 0:39:27.330
<v Speaker 2>Bloomberg Tech. Okay, coming up, as AI transforms Hollywood, who

0:39:27.350 --> 0:39:32.010
<v Speaker 2>controls your image, voice, creative work? Familio CEO Dan Neely

0:39:32.050 --> 0:39:35.910
<v Speaker 2>joins us to discuss protecting creators in the age of...

0:39:36.270 --> 0:39:39.250
<v Speaker 2>of AI. Take a quick look at shares of Micron.

0:39:39.310 --> 0:39:43.110
<v Speaker 2>Fourth quarter results after the bell last night. The story

0:39:43.150 --> 0:39:46.290
<v Speaker 2>is momentum in the memory space with AI. The stock

0:39:46.330 --> 0:39:49.930
<v Speaker 2>is down. There is like some stock-based comp issues. There

0:39:49.989 --> 0:39:52.620
<v Speaker 2>are some questions on, is there a cycle for memory

0:39:52.700 --> 0:39:54.739
<v Speaker 2>as there's traditionally been? And where are we in that

0:39:54.800 --> 0:39:57.520
<v Speaker 2>cycle as it relates to HBM and AI? But the

0:39:57.540 --> 0:39:59.680
<v Speaker 2>stock off two percentage points or so on a strong

0:39:59.719 --> 0:40:02.700
<v Speaker 2>set of numbers. This is Bloomberg Tech. Bye.

0:40:02.800 --> 0:40:02.880
<v Speaker 4>Bye.

0:40:11.750 --> 0:40:15.239
<v Speaker 2>As AI reshapes the entertainment industry, who controls and gets

0:40:15.340 --> 0:40:17.760
<v Speaker 2>paid for the use of a creator's work and likeness?

0:40:18.280 --> 0:40:21.820
<v Speaker 2>Vermilio is tackling that question with technology designed to track

0:40:21.980 --> 0:40:26.529
<v Speaker 2>and license AI-generated content. Joining us is Vermilio co-founder and

0:40:26.590 --> 0:40:29.930
<v Speaker 2>CEO Dan Neely. And what was so interesting, copyright was

0:40:29.969 --> 0:40:32.640
<v Speaker 2>the first fight in AI, in this town at least.

0:40:33.560 --> 0:40:36.460
<v Speaker 2>I'm trying to understand the distinction between copyright and likeness.

0:40:36.780 --> 0:40:39.340
<v Speaker 4>Certainly, yeah. I mean, if you think about copyright, it's

0:40:39.440 --> 0:40:43.120
<v Speaker 4>a well-understood topic. Likeness is who you are. It's your voice,

0:40:43.280 --> 0:40:45.940
<v Speaker 4>how you might move. It's your name in and of itself.

0:40:46.520 --> 0:40:48.280
<v Speaker 4>All those things make up who you are as an individual.

0:40:48.540 --> 0:40:50.480
<v Speaker 4>And if you are a famous person, that's ultimately who

0:40:50.520 --> 0:40:52.310
<v Speaker 4>you are. That's how your fans recognize who you are.

0:40:52.320 --> 0:40:55.080
<v Speaker 4>It's who they relate to. But it's this unique right

0:40:55.440 --> 0:40:58.420
<v Speaker 4>that has existed for a long time, but AI has

0:40:58.440 --> 0:40:59.440
<v Speaker 4>really brought it to the forefront.

0:41:00.060 --> 0:41:03.360
<v Speaker 2>Dan, Familia exists for a reason. You're solving for a problem,

0:41:03.540 --> 0:41:06.860
<v Speaker 2>but how has that problem sort of manifested itself with time?

0:41:07.360 --> 0:41:11.410
<v Speaker 2>You know, as AI has, more AI-generated content has hit

0:41:11.660 --> 0:41:12.819
<v Speaker 2>the market and the world.

0:41:13.090 --> 0:41:15.550
<v Speaker 4>When we started this business back in, we started thinking

0:41:15.590 --> 0:41:19.049
<v Speaker 4>about it back in 2020, there were about 19,000 deepfake creations.

0:41:19.070 --> 0:41:19.510
<v Speaker 14>Pre-ChatGPT.

0:41:19.530 --> 0:41:22.509
<v Speaker 4>Pre-ChatGPT, yeah. So we started thinking about the problem because

0:41:22.530 --> 0:41:24.549
<v Speaker 4>we'd seen a couple of things happen. But there were

0:41:24.570 --> 0:41:27.190
<v Speaker 4>about 19,000 deepfake creations back there. Today, there are about

0:41:27.210 --> 0:41:28.930
<v Speaker 4>a trillion. And so just to give you the kind

0:41:28.950 --> 0:41:31.569
<v Speaker 4>of context of how much the scale has happened, it's

0:41:31.590 --> 0:41:35.110
<v Speaker 4>just a gigantic problem. And reality is people are fans

0:41:35.170 --> 0:41:37.069
<v Speaker 4>of things. And because they're fans of things, they want

0:41:37.090 --> 0:41:38.940
<v Speaker 4>to create with things, and they also want to engage

0:41:38.960 --> 0:41:41.820
<v Speaker 4>with things. And so when that fake stuff starts existing,

0:41:42.060 --> 0:41:43.560
<v Speaker 4>fans go and engage with it. They don't know who

0:41:43.600 --> 0:41:45.000
<v Speaker 4>created it. They don't know if it's actually from the

0:41:45.040 --> 0:41:47.020
<v Speaker 4>person they're a fan of. But that likeness right is

0:41:47.040 --> 0:41:48.180
<v Speaker 4>something that needs to be protected.

0:41:48.500 --> 0:41:53.410
<v Speaker 2>It's so multifaceted and complicated, you know, a deepfake. to

0:41:53.450 --> 0:41:58.610
<v Speaker 2>all intents and purposes, is often unauthorized use of someone's likeness.

0:41:59.590 --> 0:42:03.109
<v Speaker 2>And then the question is, to who does the value accrue?

0:42:03.910 --> 0:42:05.840
<v Speaker 2>How do you solve for that issue?

0:42:06.000 --> 0:42:08.460
<v Speaker 4>Yeah, so it's ultimately two things. First is let's identify

0:42:08.540 --> 0:42:11.180
<v Speaker 4>all the unauthorized stuff. So our technology identifies across the

0:42:11.219 --> 0:42:12.200
<v Speaker 4>entire internet.

0:42:12.219 --> 0:42:12.840
<v Speaker 2>It finds it.

0:42:12.960 --> 0:42:15.100
<v Speaker 4>Finds it. Let's make sure we understand what it is.

0:42:15.219 --> 0:42:17.120
<v Speaker 4>Then our choices are, do we want to take it

0:42:17.180 --> 0:42:18.739
<v Speaker 4>down or do we want to leave it? So taking

0:42:18.760 --> 0:42:20.620
<v Speaker 4>it down is there's a bunch of bad stuff that's happening.

0:42:20.860 --> 0:42:22.180
<v Speaker 4>Leaving it is, oh, my fans might have created something

0:42:22.200 --> 0:42:22.819
<v Speaker 4>that's actually kind of cool.

0:42:22.840 --> 0:42:24.120
<v Speaker 2>But now it becomes a fight for the lawyers?

0:42:24.420 --> 0:42:26.839
<v Speaker 4>It used to become a fight for the lawyers, but

0:42:26.880 --> 0:42:30.460
<v Speaker 4>now it's technology, where our technology can just automatically ask

0:42:30.480 --> 0:42:31.950
<v Speaker 4>for it to be removed. And so we're doing that

0:42:31.989 --> 0:42:35.230
<v Speaker 4>at scale today. And then it's about monetization. It's about attribution.

0:42:35.430 --> 0:42:37.590
<v Speaker 4>How much of that is that new output that is

0:42:37.630 --> 0:42:39.890
<v Speaker 4>a piece of music, is a new video, is just

0:42:39.989 --> 0:42:41.770
<v Speaker 4>using my name to create an account? How much should

0:42:41.790 --> 0:42:43.069
<v Speaker 4>I be compensated for that as well?

0:42:43.310 --> 0:42:47.130
<v Speaker 2>Okay, so then there is the motivation or enthusiasm of

0:42:47.170 --> 0:42:50.790
<v Speaker 2>an individual to license their likeness. You know, what do

0:42:50.830 --> 0:42:56.160
<v Speaker 2>you see in the world of celebrity, creative, different artists

0:42:56.200 --> 0:42:57.520
<v Speaker 2>in wanting to do this?

0:42:58.080 --> 0:43:00.160
<v Speaker 4>I think we're in what I would describe as the

0:43:00.200 --> 0:43:00.759
<v Speaker 4>messy middle.

0:43:01.060 --> 0:43:01.779
<v Speaker 2>The messy middle.

0:43:01.800 --> 0:43:04.480
<v Speaker 4>The messy middle. So it's a gigantic issue. So if

0:43:04.520 --> 0:43:08.680
<v Speaker 4>we think about permission at scale is AI's issue, right?

0:43:08.719 --> 0:43:11.990
<v Speaker 4>The entire infrastructure of AI, permission at scale is the problem.

0:43:12.230 --> 0:43:15.569
<v Speaker 4>Because doing one-on-one deals is really not that complex. But

0:43:15.590 --> 0:43:17.770
<v Speaker 4>they have to do it at a gigantic scale. They've

0:43:17.790 --> 0:43:19.529
<v Speaker 4>got to get hundreds of thousands of people to opt

0:43:19.550 --> 0:43:21.950
<v Speaker 4>into this thing. They can't just think about, hey, it's

0:43:22.050 --> 0:43:24.290
<v Speaker 4>one-off here, here, there, and somewhere else.

0:43:24.570 --> 0:43:28.410
<v Speaker 2>I get where we're talking about where the value accrues, right?

0:43:28.790 --> 0:43:33.739
<v Speaker 2>Who pays the artist? You know, is it the AI studio?

0:43:34.110 --> 0:43:36.820
<v Speaker 2>We've had Luma on. We've had Promise on the show today.

0:43:37.340 --> 0:43:41.259
<v Speaker 2>Is it the traditional Hollywood studio? Then there's the creator economy, right?

0:43:41.800 --> 0:43:44.460
<v Speaker 2>Who do they get paid by? What do you see?

0:43:44.480 --> 0:43:46.759
<v Speaker 4>I see two things. I see certainly the platforms are

0:43:46.780 --> 0:43:48.480
<v Speaker 4>going to start paying because they're going to have content.

0:43:48.500 --> 0:43:51.049
<v Speaker 4>They already have content on their platforms that uses likeness

0:43:51.090 --> 0:43:53.290
<v Speaker 4>in an unauthorized manner. So we have to get to

0:43:53.330 --> 0:43:55.810
<v Speaker 4>a place where that gets company. Think of YouTube, think

0:43:55.830 --> 0:43:59.610
<v Speaker 4>of Meta's platforms. It exists across every major distribution platform. Spotify,

0:43:59.850 --> 0:44:01.430
<v Speaker 4>it's in all the places. So let's make sure people

0:44:01.450 --> 0:44:03.600
<v Speaker 4>are getting compensated in the right way. Then there is,

0:44:03.900 --> 0:44:05.740
<v Speaker 4>how do we think about you have an authorized model?

0:44:05.980 --> 0:44:07.399
<v Speaker 4>So let's say all of the people that are building

0:44:07.420 --> 0:44:09.799
<v Speaker 4>models get likeness to actually be something that they have

0:44:09.840 --> 0:44:11.719
<v Speaker 4>a right to in the same way they are with copyright.

0:44:12.140 --> 0:44:13.989
<v Speaker 4>That compensation is going to come from the amount of

0:44:14.010 --> 0:44:17.410
<v Speaker 4>compute revenue that's been driven for those companies, not just, hey,

0:44:17.430 --> 0:44:19.549
<v Speaker 4>I've got an interesting piece of content that someone's happened

0:44:19.590 --> 0:44:22.170
<v Speaker 4>to engage with that I put advertising next to. The

0:44:22.190 --> 0:44:25.160
<v Speaker 4>compute opportunity is actually the larger opportunity for these businesses

0:44:25.360 --> 0:44:26.420
<v Speaker 4>and also for individual creators.

0:44:26.440 --> 0:44:28.520
<v Speaker 2>Very quick, how does Vermilio work? make money it takes

0:44:28.780 --> 0:44:29.640
<v Speaker 2>a royalty or.

0:44:29.700 --> 0:44:32.200
<v Speaker 4>So um we have roughly a hundred thousand customers today

0:44:32.280 --> 0:44:34.460
<v Speaker 4>they pay us a monthly fee to protect them and

0:44:34.480 --> 0:44:36.359
<v Speaker 4>then we also take a we have a transaction fee

0:44:36.380 --> 0:44:38.640
<v Speaker 4>associated with uh when someone.

0:44:38.460 --> 0:44:42.440
<v Speaker 2>Does a licensing and very quickly what happens next yeah.

0:44:42.280 --> 0:44:44.160
<v Speaker 4>What happens next we're in this moment where we have

0:44:44.200 --> 0:44:46.520
<v Speaker 4>to get to permission at scale it is the issue

0:44:46.540 --> 0:44:48.100
<v Speaker 4>it is the issue that needs to be unlocked we

0:44:48.120 --> 0:44:50.500
<v Speaker 4>built this business to solve the permission at scale problem

0:44:50.920 --> 0:44:53.549
<v Speaker 4>that exists so that we can say okay everyone has

0:44:53.610 --> 0:44:55.759
<v Speaker 4>a chance to say i'm in or i'm out Once

0:44:55.780 --> 0:44:58.370
<v Speaker 4>that gets managed, then ultimately that's where we'll end.

0:44:58.430 --> 0:45:01.350
<v Speaker 2>Now, do the people you work with feel positive about AI? Or,

0:45:01.370 --> 0:45:02.790
<v Speaker 2>you know, you said the messy middle.

0:45:03.190 --> 0:45:06.150
<v Speaker 4>I think that, so for us, our customers are very concerned.

0:45:06.550 --> 0:45:08.830
<v Speaker 4>Then they get protected. Once they're protected, they're like, oh,

0:45:08.890 --> 0:45:10.210
<v Speaker 4>now I can start thinking about what else to do.

0:45:10.350 --> 0:45:13.230
<v Speaker 4>Because the optionality is mine. It's not controlled by platforms.

0:45:13.390 --> 0:45:14.610
<v Speaker 4>It's controlled by me as an individual.

0:45:14.969 --> 0:45:17.009
<v Speaker 2>Dan Neely of Emilio. Thanks so much for being with

0:45:17.070 --> 0:45:17.260
<v Speaker 2>us here.

0:45:17.280 --> 0:45:17.610
<v Speaker 4>Thanks so much.

0:45:18.640 --> 0:45:21.760
<v Speaker 2>And on Bloomberg Tech. That does it for this edition

0:45:21.820 --> 0:45:25.460
<v Speaker 2>of Bloomberg Tech, live from Hollywood, live from Bloomberg Screen Time.

0:45:25.500 --> 0:45:28.969
<v Speaker 2>But tomorrow, we are actually going to go somewhere pretty

0:45:29.070 --> 0:45:34.030
<v Speaker 2>unique for our defense tech special, coverage live from Skunk Works,

0:45:34.469 --> 0:45:39.390
<v Speaker 2>Lockheed Martin's advanced aircraft development facility. in Southern California, you

0:45:39.410 --> 0:45:41.710
<v Speaker 2>do not want to miss it. It includes a conversation

0:45:42.130 --> 0:45:46.480
<v Speaker 2>with Lockheed CEO, Jim Ty Clare. So many fascinating conversations

0:45:46.880 --> 0:45:49.739
<v Speaker 2>here at the intersection of media, entertainment, and capital at

0:45:50.160 --> 0:45:54.360
<v Speaker 2>Bloomberg Screen Time. Don't forget to check out our podcast.

0:45:54.640 --> 0:45:56.620
<v Speaker 2>So many of you have been in touch about the

0:45:56.650 --> 0:45:58.969
<v Speaker 2>way you engage with Bloomberg Tech, how you listen, how

0:45:59.010 --> 0:46:01.489
<v Speaker 2>you watch, We're really grateful to those that do go

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<v Speaker 2>to the podcast. You can find it on the Bloomberg

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<v Speaker 2>Terminals as well as on Spotify, iHeart, and on Apple.

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<v Speaker 2>The conclusion, kind of interesting there from Dan Neely, the

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<v Speaker 2>messy middle. Hollywood meets AI, and they're trying to work

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<v Speaker 2>out how to work together in a way that everyone wins.

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<v Speaker 2>But there are a lot more conversations to come from

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<v Speaker 2>here in LA and here in Hollywood. Thanks for being

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<v Speaker 2>with us. This is Bloomberg Tech.

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<v Speaker 1>Thanks for watching!