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Speaker 1: Bloomberg Audio Studios, Podcasts, radio News.

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Speaker 2: We're from Mahard.

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Speaker 1: Where innovation, money and power Collie in Silicon Valley NBN.

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Speaker 1: This is Bloomberg Technology with Caroline Hyde and Ed lud Love.

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Speaker 3: Live from New York.

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Speaker 4: This is Bloomberg Technology coming up. Tech charges higher as

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Speaker 4: the NASDAC is sept for its best week of the year.

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Speaker 4: We dig into the AI drivers as even as Adobe.

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Speaker 4: This is the mark a mutant forecast on AI growth,

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Speaker 4: overshadowing better than expected third quarter results. And Uber it

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Speaker 4: powers ahead as it expands its partnership with Weimo, bringing

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Speaker 4: autonomous right hailing to Austin and Atlanta. But let's look

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Speaker 4: into what's happening with Uber because we are driving higher

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Speaker 4: the putt four point nine percent. This is all surrounding,

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Speaker 4: of course, a deal that it's making with Waymo.

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Speaker 3: It really wants the owning autonomous driving.

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Speaker 4: Let's dig into that news that it will basically be

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Speaker 4: the only app offering driverless rides in waymow cars in

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Speaker 4: Austin and Atlanta.

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Speaker 3: So good news for this stock. Natalie Lung is with us.

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Speaker 4: To break it all down, and Natalie overall, I am

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Speaker 4: wandering more broadly about well what Uber.

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Speaker 3: Is seeing here.

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Speaker 4: Is it the challenge coming from robo taxes, challenge coming

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Speaker 4: from Tesla, or is it something else that drives us?

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Speaker 5: He couldn't be a combination of all these things. And

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Speaker 5: Uber wants to make early innings into being the platform

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Speaker 5: that people go to, that regular people go to to

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Speaker 5: get these consumer that get these driverless rides. So that's

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Speaker 5: why they're making partnerships with Weimo, as with Cruise as

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Speaker 5: well as byd for ride experiences outside the US. And

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Speaker 5: it wants to be that so called indispensable partner to

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Speaker 5: all these manufacturers who are looking to put their driverers

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Speaker 5: cars to use.

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Speaker 4: It's going to bring on board all electric Jaguar Ipace

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Speaker 4: vehicles the way mo offering how quickly am I going

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Speaker 4: to be able to get in one at the moment?

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Speaker 4: Where which cities? How fast will this expand?

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Speaker 6: Right?

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Speaker 5: So, Uber and Waimo currently has a collaboration in Phoenix,

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Speaker 5: so that's happening there now, but starting early next year,

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Speaker 5: Uber will be offering those way more rides exclusively in

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Speaker 5: Austin and Atlanta.

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Speaker 3: It really is a good day for the Uber stock.

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Speaker 4: We're popping first days since August the eighth, but up

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Speaker 4: almost five percent. Natalie Lung breaks down, we appreciate it

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Speaker 4: so much. Meanwhile, Adobe ches doing the opposite, whipsawing to

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Speaker 4: the lower side today after the company reported earnings yesterday,

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Speaker 4: after the bell outlook really failed to quell investor impatience

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Speaker 4: for new AI tools to start generating cash. Bradie Ford

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Speaker 4: pointed us toward it yesterday and is here with the

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Speaker 4: results today, and it does seem to be the digital media.

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Speaker 3: Side that is letting the side down.

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Speaker 2: Yeah, Well, here's the big question for these software companies

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Speaker 2: that were the big winners over the last decade. Is

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Speaker 2: AI a meaningful new product that will unlock new revenue?

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Speaker 2: Are Is it just kind of like a cool feature

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Speaker 2: that you add in and it's a nice to have,

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Speaker 2: but it doesn't really move the needle. And that's the

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Speaker 2: question that investors been batting back and forth with Adobe.

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Speaker 2: And what we saw last night is just that that

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Speaker 2: incremental revenue they were hoping to see from new AI

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Speaker 2: products at least isn't materializing yet. We have executives talking

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Speaker 2: about we are optimizing for use and adoption rather than

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Speaker 2: really driving monetization on these products.

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Speaker 7: Yet.

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Speaker 4: Yeah, what did Chantanu have to say, to quell investors

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Speaker 4: nerves because this is a heavy sell off in the stock.

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Speaker 3: But they seem to be.

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Speaker 4: Trying to show that, yes, they're driving profitability, they're driving

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Speaker 4: forward in terms of their offerings, but not really speaking

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Speaker 4: to this weakness.

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Speaker 1: Yeah.

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Speaker 2: Their defense, as I read it, and it was a

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Speaker 2: bit of a subtle one, is that AI is still

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Speaker 2: a value ad because it keeps folks from going to

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Speaker 2: our competitors and it allows us to increase prices. Right,

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Speaker 2: so it's not that I'm paying an additional ten dollars

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Speaker 2: for the new AI tools, but it's that, well, I'm

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Speaker 2: not going to go install Canva, and if you raise

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Speaker 2: my prices ten percent, I'm not going to cancel, and

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Speaker 2: I'm not going to fight you either. And so they

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Speaker 2: said that it's it's kind of an indirect monetization story

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Speaker 2: at this point, with more direct monetization to come in

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Speaker 2: the future.

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Speaker 4: What levers, therefore, can they pull to monetize in the future.

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Speaker 2: In the future, the idea would be that you know

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Speaker 2: generation saying photoshop, click here, make a picture of a

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Speaker 2: dog doing a backflip. Every time you do that, you

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Speaker 2: have let's say a thousand credit standard for generations you

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Speaker 2: go above that, you start getting charged. That's one method.

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Speaker 2: In more resource intensive models such as video, which they're

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Speaker 2: working on, they said that could be a whole different

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Speaker 2: monetization mechanism, in part because the compute would probably be

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Speaker 2: so much higher. So general credit packs, consumption and additional

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Speaker 2: productiers would be the general way folks would expect. And

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Speaker 2: they've spoken about.

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Speaker 4: One area of focus that we have for Adobe going

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Speaker 4: forward has been the investment that they're having to make

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Speaker 4: as well. The partnerships are striking where they're trying. You

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Speaker 4: were on yesterday just talking through how these businesses are

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Speaker 4: trying to delve into the three D modeling side of things.

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Speaker 4: How expensive is the artificial intelligence offering for them.

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Speaker 2: The beauty of being a giant company like Adobe. Some

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Speaker 2: folks have told me that Adobe Suite of Creative Tools

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Speaker 2: is one of the most profitable products ever and so

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Speaker 2: they have a bit of a mountain of cash and

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Speaker 2: so they're definitely able to train these things and throw

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Speaker 2: some money around without it being too diluted at this point.

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Speaker 2: So it's a big expense, especially for the startups. We

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Speaker 2: hear about it being a you know, it can be

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Speaker 2: even inhibiting factor. Adobe has really tried to message that, look,

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Speaker 2: we have a diversified business. We are willing to pull

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Speaker 2: some cash over here and put it over here to

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Speaker 2: make sure we're able to keep on doing this and

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Speaker 2: keep getting adoption. And they generally think that they're best

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Speaker 2: set by centralizing users on Adobe and keeping them there

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Speaker 2: by keeping AI accessible for a little longer before jacking

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Speaker 2: up the prices.

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Speaker 4: Ready, Ford, we thank you, thank you. Let's talk aviation

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Speaker 4: tech right now. Boeing factory workers walked off the job

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Speaker 4: for the first time in sixteen years today, halting manufacturing

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Speaker 4: across the plane maker's Seattle hub. This after members of

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Speaker 4: its largest union voted overwhelmingly to reject a contract offer

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Speaker 4: angle on strike. While both parties have expressed a desire

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Speaker 4: to get back to the bargaining table to move ads

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Speaker 4: to the strain on Boeing, let's just stick with the

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Speaker 4: airline industry now, because United Airlines has announced a deal

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Speaker 4: with Starlink. The airline is set to offer in flight

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Speaker 4: Wi Fi through SpaceX's Internet service for free. Winimberg's Nongrasch

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Speaker 4: joins us now, Wow, no more five dollars ninety nine

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Speaker 4: minimum spends when if you get on the plane. What

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Speaker 4: does it say about Starlink's reliability in the air right.

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Speaker 8: I think a lot of people were wondering when, you know,

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Speaker 8: they would strike a big deal with one of the

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Speaker 8: major airlines, and I think what it's showing is that

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Speaker 8: all right. You know, there were some questions about whether

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Speaker 8: or not it could handle the capacity earlier, but now

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Speaker 8: I think at least one of these airlines says all right,

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Speaker 8: I think they're ready to handle our fleet of vehicles.

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Speaker 4: When you say one of these airlines one of the

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Speaker 4: big carriers in the US, they've already got to deal

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Speaker 4: with Hawaiian airlines, right, They've.

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Speaker 8: Got JSX, which is a smaller airline you know, predominantly

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Speaker 8: based out of Texas. But yes, this is one of

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Speaker 8: the big four, if you will. And so now they

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Speaker 8: finally have I think the bragging rights that they need

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Speaker 8: to say, all right, we are here for the big time,

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Speaker 8: the big players.

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Speaker 3: Just look at this deal.

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Speaker 4: Scott Kirby really talking about how you're gonna be able

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Speaker 4: to just walk straight on the plane from the lounge.

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Speaker 4: Everything will be seamless. Ultimately you'll be connected devices. Also,

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Speaker 4: what you're going to be using on the aircraft itself.

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Speaker 4: What in terms of market shared. Do analysts think that

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Speaker 4: they're able to get his Scott Kirby the first guy

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Speaker 4: to go and everyone else follows.

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Speaker 3: I think so.

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Speaker 8: I think a lot of people think this might be like.

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Speaker 3: A watershed moment for them, you.

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Speaker 8: Know, because it's a big advertising get right. They can say,

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Speaker 8: all right, here we have one of the major players.

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Speaker 8: When are the other ones going to follow suit? And

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Speaker 8: so that's I think really the big get for them.

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Speaker 4: The technology is what we love to hear from you

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Speaker 4: and ultimately, how hard is this? We all understand how

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Speaker 4: glitchy the airline Wi Fi is at the moment, why

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Speaker 4: is that?

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Speaker 3: What does starting offer?

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Speaker 8: Well, one of the big advantages that starlink has over

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Speaker 8: its competitors for other Internet satellites is that they're closer. Right,

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Speaker 8: So the incumbents that a lot of the airlines use

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Speaker 8: use satellites that are in much higher orbits and so

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Speaker 8: there's a latency. There's that lag that I'm sure everybody

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Speaker 8: has been frustrated with on their planes from time to time.

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Speaker 8: But what starlink offers their satellites are much closer to

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Speaker 8: the Earth and so you can have that cut down

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Speaker 8: in latency. Of course, that comes with more satellites in orbit.

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Speaker 8: They need to launch more and more so that they

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Speaker 8: can have that global coverage because when you're closer to

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Speaker 8: the Earth, the satellites are moving a lot quicker, and

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Speaker 8: so in order to have a satellite overhead at any

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Speaker 8: given time, they just have to keep launching satellites. It's

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Speaker 8: basically a numbers game. But if they are able to

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Speaker 8: have enough satellites in orbit, then you cut down down

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Speaker 8: that latency and it's a more seamless experience.

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Speaker 4: Willumbre analyst Luis de Palmas, he's to be saying Stalin

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Speaker 4: is in no oppositioned to have the highest aviation mock

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Speaker 4: show in the next decade, but he's not saying in

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Speaker 4: the next two or three years.

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Speaker 3: This takes time run.

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Speaker 8: Yeah, it's definitely going to take time. And as we've seen,

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Speaker 8: you know, in terms of where Starlink has excelled, they've

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Speaker 8: really gone up in numbers. When it comes to individual subscribers,

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Speaker 8: maritime deals. They're definitely very popular over the ocean right

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Speaker 8: because there's less demand there, But when it comes to

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Speaker 8: the you know, over land and with bigger airlines, you

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Speaker 8: know that's going to take some time.

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Speaker 3: Also, you know, you have.

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Speaker 8: To get certain approvals, you have to re outfit the planes,

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Speaker 8: so it's going to be a slow process.

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Speaker 3: But this is just the first step.

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Speaker 8: And well it'll be interesting to see if any of

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Speaker 8: the other airlines follow.

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Speaker 4: I'm crush, what joy to have you in the studio

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Speaker 4: in New York. Watch this here traveling thank you so

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Speaker 4: much in a busy week in space elsewhere and transportation,

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Speaker 4: Amazon says it will invest more than two billion dollars

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Speaker 4: in its delivery service partner program, especially in an effort

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Speaker 4: to raise driver pay to a national average about twenty

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Speaker 4: two dollars an hour. Bloomberg's Matt Day reporting across this.

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Speaker 4: Why do it, Matt Well?

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Speaker 9: Why?

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Speaker 10: The first and kind of obvious context behind this is

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Speaker 10: a pressure from labor groups. You know, Amazon's contract delivery

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Speaker 10: drivers are a focused for the team Stais in particular,

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Speaker 10: they put a big target on Amazon's back, saying we're

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Speaker 10: going after them. Famously, these folks represent ups and have

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Speaker 10: said they think they can organize an Amazon worker. So

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Speaker 10: Amazon playing a little bit of defense here.

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Speaker 4: Defense Ultimately, why do they go for contractors? To begin with?

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Speaker 4: Why don't they hire their own drivers?

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Speaker 10: You know, the argument they make is that it's about

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Speaker 10: empowering small businesses. I think labor experts would maybe bat

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Speaker 10: an eye at that, but it is. It is a

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Speaker 10: relatively common model, right, FedEx uses you know, versions of this.

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Speaker 10: Uber you know, famously doesn't employ its own folks either.

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Speaker 10: So for Amazon, this gives them, you know, a bit

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Speaker 10: of a best of both worlds.

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Speaker 4: Right.

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Speaker 10: They don't have to provide you know, the perks of

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Speaker 10: employees to these folks directly. You know, at the same time,

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Speaker 10: they can exert a relatively high degree of control over independent,

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Speaker 10: often bespoke contract outfits.

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Speaker 3: How does it look abroad?

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Speaker 4: Is it this model in the US?

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Speaker 3: Same elsewhere? Different?

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Speaker 10: There are versions of it, and obviously, you know, in

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Speaker 10: countries with stricter labor laws, you know, they have to

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Speaker 10: comply with those. The US has fewer of those when

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Speaker 10: it comes to last mile drivers, but there are versions

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Speaker 10: of their Delivery Service Partner program abroad. They say there's

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Speaker 10: something like three hundred and ninety thousand drivers employed by

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Speaker 10: DSP's worldwide, So it's a it's a huge portion of

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Speaker 10: their you know, kind of workforce that does not accrue

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Speaker 10: to their books.

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Speaker 4: And let's talk about that books because I think Ultimately,

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Speaker 4: this is a business that has been cutting jobs, has

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Speaker 4: been getting leaner and meaner in areas it can, while

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Speaker 4: it's splurges an awful lot on artificial intelligence and compute.

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Speaker 4: What does this say a two billion dollar investment, what

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Speaker 4: does that in the context of Amazon's overall spending.

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Speaker 10: I think it's a reminder that, you know, as people

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Speaker 10: talk about them as a technology company, you know, their

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Speaker 10: core business of getting you things you know by by

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Speaker 10: delivery is still growing, even if it's slower than it

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Speaker 10: was during the boom years, and it still requires a

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Speaker 10: whole lot of bodies to make it work.

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Speaker 1: Right.

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Speaker 10: We're going to see surely from them announcements about their

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Speaker 10: seasonal hiring coming up for the fall, for the the

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Speaker 10: peak holiday season, something they do every year about this time.

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Speaker 10: So just a reminder I think that, you know, listen,

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Speaker 10: while they're they is getting all the headlines, they still

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Speaker 10: are moving a whole lot of stuff and require a

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Speaker 10: lot of partners to make that happen that day.

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Speaker 4: All things Amazon, we appreciate it, Thank you so much. Now,

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Speaker 4: coming up with the dirt bag of the Internet, who

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Speaker 4: happens to be behind the Crypto project promoted by Donald Trump?

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Speaker 3: That's next. This is Blouly Big Technology Revolute.

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Speaker 4: It's seeking licenses to start operating in the Middle East.

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Speaker 4: This is the London fintech giant hunts for growth beyond.

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Speaker 3: Its home market.

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Speaker 4: Now the firm has submitted applications to the Central Bank of.

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Speaker 3: The UAE reporting.

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Speaker 4: Shows to become an electronic money institution and offer remittiscences

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Speaker 4: in the country they of course. The sources currently speaking

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Speaker 4: to Bloomberg say that the goal is to eventually apply

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Speaker 4: for a full banking license similar to the one that

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Speaker 4: it recently received from regulators in the UK after years

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Speaker 4: of work. Now let's stick with the world of fintech,

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Speaker 4: but the crypto side of it. In the last year,

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Speaker 4: Donald Trump has fashioned himself into a friend to the

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Speaker 4: cryptocurrency crowd. He and his two older sons now have

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Speaker 4: been particularly good friends to World Liberty Finance, the crypto

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Speaker 4: project they've been promoting on social media. Here to tell

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Speaker 4: us more about well, the deal maker behind the project,

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Speaker 4: Sloomberg Investigative reporters Fox. You're also the author of book

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Speaker 4: Number Go Up Inside Crypto's Wild Rise and Staggering four,

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Speaker 4: which is up for a few awards. So congratulations on

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Speaker 4: that Zeke, you start your story focused on Chase Hero.

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Speaker 3: What can you tell about this guy?

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Speaker 9: Yeah, so Chase is an unknown in the crypto world,

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Speaker 9: but I dug it into his career and he's been

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Speaker 9: a marijuana dealer. He says he went to prison for that.

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Speaker 9: He sold weight loss calling cleanses online. He had one

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Speaker 9: hundred and forty nine dollars a month Get Rich Quick class.

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Speaker 9: And then now he appears to be the main deal

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Speaker 9: maker behind World Liberty Financial, which is this defive startup

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Speaker 9: the Trumps are promoting, and President Trump himself posted a

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Speaker 9: video saying, you know this is going to challenge the

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Speaker 9: big banks. So it's really bizarre to see that this

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Speaker 9: is the person they're partnering with.

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Speaker 4: I'm sorry, the guy behind this DeFi project isn't even

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Speaker 4: known in the crypto world.

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Speaker 9: No, and I mean he calls himself in videos. He

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Speaker 9: likes to call himself the dirt bag of the Internet.

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Speaker 9: I found in another video he said regulators should kick

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Speaker 9: people like him out of the industry, and not in

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Speaker 9: those words. He seems to have a very cynical, to

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Speaker 9: say the least, attitude towards crypto and this project World Liberty.

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Speaker 9: You know it might sound kind of impressive if you

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Speaker 9: didn't know about crypto, but it appears to be kind

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Speaker 9: of a copy of an existing project that didn't go

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Speaker 9: anywhere and then lost a lot of money in a hack.

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Speaker 4: Yeah, you're talking about the Dough project, right, Dough. That

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Speaker 4: seems to be what's got actually industry inside. Is the

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Speaker 4: crypto industry a little worried is ultimately that the people

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Speaker 4: behind Well Liberty Financial have come across from a much

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Speaker 4: smaller project that didn't manage to raise that many funds

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Speaker 4: and actually got hacked.

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Speaker 9: Yes, and I mean we don't know the details of

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Speaker 9: World Liberty. I obtained a white paper that lays out

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Speaker 9: some of them, but I'm sure it's all subject of change.

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Speaker 9: But this is supposed to be defile like decentralized finance.

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Speaker 9: The white paper says that seventy percent of the tokens

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Speaker 9: will be reserved for insiders. So talking to people in crypto,

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Speaker 9: they said, this looks like it could be more of

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Speaker 9: a cash grab than an innovative project.

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Speaker 4: Okay, And there in lies the issue that this could

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Speaker 4: be some sort of cash grab.

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Speaker 3: Some of the.

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Speaker 4: Details in your story and that might hint that there's

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Speaker 4: a slight difference in how this DeFi project is run

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Speaker 4: compared to others is that the people behind the cut

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Speaker 4: the overall project keep what of issue tokens.

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Speaker 3: That's a lot.

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Speaker 9: Yeah, And I mean like we're talking about this like

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Speaker 9: I think we're talking about this even a little bit

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Speaker 9: too seriously. Like you should go go read what this

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Speaker 9: guy says about crypto. I mean, I can't, I can't

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Speaker 9: repeat it. The language to this is a family TV channel,

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Speaker 9: I guess, but the way he talks about it doesn't

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Speaker 9: give you any confidence that this is a serious project

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Speaker 9: that's going to challenge big banks.

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Speaker 4: He says, basically, you can sell us a rubbish and

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Speaker 4: anyone will buy it in crypto. He happened to say

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Speaker 4: that in a twenty eighteen YouTube video recorded as he

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Speaker 4: drove his rolls Royce.

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Speaker 9: Yes, and I mean, I'm thinking deep to try and

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Speaker 9: find his crypto resume, and I found that he appeared

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Speaker 9: on influencer Logan Paul's podcast, and during the podcast, the

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Speaker 9: two of them promoted a token called Omi, which I

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Speaker 9: had also never heard of before since they promoted it

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Speaker 9: a couple of years ago. Is down ninety six percent

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Speaker 9: and another YouTuber, a scam busting YouTuber named coffee Zilla

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Speaker 9: posted this expose that appeared to show the two of

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Speaker 9: them coordinating ahead of the show their plan to talk

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Speaker 9: about OMI.

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Speaker 4: I mean, it seems that someone else listed in the

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Speaker 4: white paper who's responsible as operations lead used to run

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Speaker 4: a service called Date Hotter Girls, where he taught seminars

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Speaker 4: on how to pick up women. All of this just

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Speaker 4: feels like a real risk ultimately for the person who

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Speaker 4: is running to be president of the United States again

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Speaker 4: to be associating himself with Why do it?

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Speaker 9: I mean, it's pretty bizarre, and the crypto industry, to

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Speaker 9: the people I've spoke to from it, are not happy

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Speaker 9: about it. They like that Trump has flip flopped and

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Speaker 9: has endorsed crypto. He said that he's going to fire

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Speaker 9: the head of the SEC and provide looser regulations that

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Speaker 9: he says will make the US the crypto capital of

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Speaker 9: the world. They're like, that all sounds great, but then

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Speaker 9: why are you starting this pretty silly sounding new venture,

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Speaker 9: a for profit venture just before the election. It almost

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Speaker 9: discredits the I raises questions about his motivations for deregulating

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Speaker 9: the industry.

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Speaker 4: What has ultimately the world liberty financial spokespeople said to you,

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Speaker 4: have you tried to get in touch, What have they

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Speaker 4: said ultimately about the real underlying necessity of this project?

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Speaker 9: So I did contact them, and I received an email

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Speaker 9: back from a man who said he was not a spokesperson,

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Speaker 9: but then he spoke for World Liberty and said that

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Speaker 9: he could see where I was going with all these questions,

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Speaker 9: and it was painting an inaccurate portrait of this company,

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Speaker 9: and that time will tell that this is a serious

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Speaker 9: project that's doing cool stuff. And Donald Trump has said

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Speaker 9: he's going to unveil the details on Monday at eight

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Speaker 9: pm on a Twitter spaces So I guess we'll see

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Speaker 9: if what he says is consistent with the white paper.

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Speaker 9: If they've they've made some changes, I'll certainly be listening

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Speaker 9: whether or.

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Speaker 4: Not it will indeed move away from the old banks,

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Speaker 4: as former President Trump has discussed zep Fox. We might

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Speaker 4: need to come back to you on Monday. Thank you

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Speaker 4: so much, extraordinary peace.

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Speaker 3: Meanwhile, some news.

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Speaker 4: From a company that used to be associated with crypto

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Speaker 4: much more in the AI world now core Weave.

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Speaker 3: It's a cloud computing provider.

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Speaker 4: Now that's among the hottest startups in the artificial intelligence race,

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Speaker 4: and as in talks to a range of sale of

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Speaker 4: existing shares, valuing it to get this twenty three billion dollars,

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Speaker 4: according to sources. The sources say that the company is

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Speaker 4: discussing a transaction that would allow existing shareholders such as employees,

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Speaker 4: to tender between four hundred million and five hundred million

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Speaker 4: dollars worth of their holdings. Welcome back to Bloomberg Technology.

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Speaker 4: I'm Caroin Hide in New York. Let's get your check

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Speaker 4: on these markets, because they are higher, and in fact

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Speaker 4: they've been higher for five straight training days. And then

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Speaker 4: as that one hundred, if we've added more than a

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Speaker 4: trillion dollars in market cap, we're up and another four

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Speaker 4: tenths of percent. Maybe the panic of last week becomes

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Speaker 4: the past, and we start to once again factor in

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Speaker 4: maybe a forty percent chance at least that the Fed

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Speaker 4: could indeed cut rates to the tune of fifty basis

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Speaker 4: points as soon as September. That's what the market is

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Speaker 4: currently trying to digest. We see that reflected in the

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Speaker 4: bond market, the yields just falling on the two year yield.

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Speaker 4: I'm saying this because actually equities worldwide are seeing buoyancy

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Speaker 4: from their stock six hundred over in Europe. It finishes

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Speaker 4: the trading week also on the higher side, and it

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Speaker 4: adds some three quarters percent on the day. As we've

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Speaker 4: finished trade, let's move on to some of the individual

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Speaker 4: movers trading here in the United States. At least, look

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Speaker 4: chips have been on fire. We've made up so much

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Speaker 4: of last week's real panic selling that we saw. The

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Speaker 4: socks is currently up one point four percent. In fact,

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Speaker 4: every single name and been trading in the green on

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Speaker 4: the day, and largely we've got some meteoric moves over

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Speaker 4: the last five days.

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Speaker 3: Arm is up some twenty five percent.

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Speaker 4: This of course a chip design company that Raymond James

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Speaker 4: is saying.

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Speaker 3: They're now rating it and outperform.

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Speaker 4: They see it growth few particularly when it comes to

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Speaker 4: AI on the edge, and we're looking at Adobe though

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Speaker 4: despite managing two live up to expectations in its fiscal

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Speaker 4: third quarter, it's dragged lower.

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Speaker 3: It's forecasts not good enough. Where have we heard that

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Speaker 3: before in video broadcon.

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Speaker 4: And we've heard this a theme in the earning season,

443
00:22:14,560 --> 00:22:16,600
Speaker 4: and Adobe once again just not managing to show the

444
00:22:16,680 --> 00:22:20,240
Speaker 4: generation of revenue from AI, even though they do add

445
00:22:20,280 --> 00:22:21,280
Speaker 4: generative AI.

446
00:22:21,080 --> 00:22:21,760
Speaker 3: To their offering.

447
00:22:22,280 --> 00:22:25,360
Speaker 4: Let's just stick with AI now because AI pioneer faith

448
00:22:25,440 --> 00:22:27,800
Speaker 4: A Lee has raised two hundred and thirty million dollars

449
00:22:28,000 --> 00:22:30,520
Speaker 4: from a star studied list of investors for a new

450
00:22:30,560 --> 00:22:34,480
Speaker 4: AI startup called world Labs, which officially launches today. The

451
00:22:34,560 --> 00:22:37,159
Speaker 4: company aims to build software that can use images and

452
00:22:37,240 --> 00:22:37,960
Speaker 4: other data.

453
00:22:37,760 --> 00:22:39,159
Speaker 3: To make decisions about.

454
00:22:38,880 --> 00:22:43,200
Speaker 4: The three dimensional world, building what it calls large world models.

455
00:22:43,520 --> 00:22:46,439
Speaker 4: Here to talk about what exactly that means, and indeed

456
00:22:46,440 --> 00:22:49,680
Speaker 4: the fundraise doctor Fai Failee alongside Bloemug's Rachel Myths.

457
00:22:49,760 --> 00:22:52,240
Speaker 3: It is wonderful to have you both here and well,

458
00:22:52,560 --> 00:22:53,240
Speaker 3: doctor Lee.

459
00:22:53,680 --> 00:22:56,280
Speaker 4: I asked, first and foremost, what was it like raising

460
00:22:56,320 --> 00:22:59,280
Speaker 4: funds as an academic now entering this private world to

461
00:22:59,320 --> 00:22:59,960
Speaker 4: be raising money.

462
00:23:00,040 --> 00:23:02,639
Speaker 3: You've been in private well before, but to raise funds?

463
00:23:02,680 --> 00:23:04,840
Speaker 3: Was it easy? From the starstut a list.

464
00:23:06,240 --> 00:23:09,320
Speaker 1: Good morning, Carolyn, it's really good to be here. Well,

465
00:23:09,400 --> 00:23:12,560
Speaker 1: nothing is easy, but what's really really hard is make

466
00:23:12,680 --> 00:23:17,160
Speaker 1: spatial intelligence happen. I'm just so excited that we've brought

467
00:23:17,160 --> 00:23:23,080
Speaker 1: together a incredible group of pixel AI talents to work

468
00:23:23,119 --> 00:23:26,480
Speaker 1: on this really, really hard problem that we now call

469
00:23:26,840 --> 00:23:28,000
Speaker 1: spatial intelligence.

470
00:23:30,520 --> 00:23:34,320
Speaker 6: Explain to us what you mean when you say spatial intelligence,

471
00:23:34,359 --> 00:23:35,960
Speaker 6: And what is it that you're building exactly?

472
00:23:36,480 --> 00:23:40,520
Speaker 1: Yeah, Rachel, Well, look, humans have spatial intelligence. It's actually

473
00:23:40,520 --> 00:23:44,000
Speaker 1: a very ancient ability. We have evolved over millions and

474
00:23:44,040 --> 00:23:49,120
Speaker 1: millions of years. It's the ability to understand, to reason,

475
00:23:49,720 --> 00:23:54,040
Speaker 1: to generate, and to even interact in a three D world,

476
00:23:54,640 --> 00:23:58,520
Speaker 1: whether you're looking at a beautiful flower or trying to

477
00:23:58,520 --> 00:24:03,639
Speaker 1: touch a butterfly or building a city. All this is

478
00:24:03,720 --> 00:24:06,080
Speaker 1: part of the capability of spatial intelligence.

479
00:24:07,680 --> 00:24:10,240
Speaker 6: We see that with humans, and we see that with animals.

480
00:24:10,400 --> 00:24:13,280
Speaker 6: How do you expect that we'll see that with computers.

481
00:24:14,200 --> 00:24:17,360
Speaker 1: Well, that's the problem we're working on. We're already starting

482
00:24:17,400 --> 00:24:21,960
Speaker 1: to make tremendous progress. The past decade of AI has

483
00:24:22,000 --> 00:24:26,720
Speaker 1: been pretty exhilarating, and people hear a lot about language recently,

484
00:24:26,800 --> 00:24:30,000
Speaker 1: but truly in the world of pixels and vision and

485
00:24:30,040 --> 00:24:34,920
Speaker 1: spatial intelligence, we've been making progress such as understanding what's

486
00:24:34,960 --> 00:24:37,720
Speaker 1: in the picture, to be able to tell a story

487
00:24:37,800 --> 00:24:41,560
Speaker 1: of what's in the picture, to even prompting a sentence

488
00:24:41,600 --> 00:24:45,080
Speaker 1: and get to the image out of it. But what's

489
00:24:45,240 --> 00:24:48,600
Speaker 1: really the next frontier, which is such a hard problem

490
00:24:48,640 --> 00:24:51,280
Speaker 1: to crack, is to bring all this into three D

491
00:24:51,520 --> 00:24:55,360
Speaker 1: because the real world is three D and humans. Spatial

492
00:24:55,359 --> 00:25:01,119
Speaker 1: intelligence is built upon this very native capability of understanding

493
00:25:01,560 --> 00:25:03,720
Speaker 1: and working with three D.

494
00:25:04,000 --> 00:25:08,480
Speaker 4: So let's put into real world contexts that working with

495
00:25:08,560 --> 00:25:12,760
Speaker 4: three D the applications. Is it robotics, is it manufacturing?

496
00:25:12,920 --> 00:25:15,640
Speaker 4: Is it just us interacting with the real world when

497
00:25:15,680 --> 00:25:17,919
Speaker 4: we put our AI function glasses on.

498
00:25:19,480 --> 00:25:23,480
Speaker 1: You're not wrong, Carolyn. This is such a foundational technology.

499
00:25:23,520 --> 00:25:30,600
Speaker 1: It's a foundational ability for computers that it has implications

500
00:25:30,840 --> 00:25:35,400
Speaker 1: in a wide range of use cases. To start with, right, creators.

501
00:25:35,680 --> 00:25:43,000
Speaker 1: Creators includes not only artists and VFX creators, but also designers,

502
00:25:43,040 --> 00:25:49,000
Speaker 1: in developers, builders, and this technology has a profound implication

503
00:25:49,119 --> 00:25:52,639
Speaker 1: for them. But in the long arc of this, of course,

504
00:25:53,880 --> 00:25:56,560
Speaker 1: robotics manufacturing.

505
00:25:55,960 --> 00:25:57,080
Speaker 3: A r v R.

506
00:25:57,600 --> 00:26:01,160
Speaker 1: This is you know, there's a reason that Apple calls

507
00:26:01,280 --> 00:26:05,400
Speaker 1: their vision pros spacial computing. Well, in my opinion, spacial

508
00:26:05,400 --> 00:26:09,600
Speaker 1: computing needs spacial intelligence, so does many other use cases.

509
00:26:09,920 --> 00:26:16,280
Speaker 4: Why does spatial computing need VC money, private sector action?

510
00:26:16,960 --> 00:26:20,400
Speaker 4: What couldn't you achieve in academia?

511
00:26:20,760 --> 00:26:23,840
Speaker 1: So this is a whole ecosystem.

512
00:26:23,880 --> 00:26:26,399
Speaker 3: We've been seeing this in AI.

513
00:26:26,480 --> 00:26:29,200
Speaker 1: We've been seeing this for years now, and this dates

514
00:26:29,240 --> 00:26:33,600
Speaker 1: back to any technology that our society our country is

515
00:26:33,640 --> 00:26:40,800
Speaker 1: building right. This ecosystem needs upstream fundamental curiosity driven research,

516
00:26:40,920 --> 00:26:45,280
Speaker 1: which I have spent many years of my life in,

517
00:26:45,640 --> 00:26:50,640
Speaker 1: but it also needs very focused drive industry. We've got

518
00:26:50,800 --> 00:26:55,040
Speaker 1: great big tech companies working on related problems, but we

519
00:26:55,200 --> 00:27:00,600
Speaker 1: also what's beautiful about our ecosystem, our startups that has

520
00:27:00,720 --> 00:27:05,080
Speaker 1: a toll dream has the ability to call on the

521
00:27:05,200 --> 00:27:09,719
Speaker 1: believers who believing cracking such a hard problem, and we

522
00:27:09,800 --> 00:27:14,520
Speaker 1: come together and focus all of our allergy in solving

523
00:27:14,600 --> 00:27:18,960
Speaker 1: this truly hard problem that needs to be scaled, needs

524
00:27:18,960 --> 00:27:22,359
Speaker 1: to be productionized, and needs to be delivered in the

525
00:27:22,440 --> 00:27:24,280
Speaker 1: hands of users and customers.

526
00:27:26,880 --> 00:27:28,960
Speaker 6: Doctor Lee, One of the things that you're most well

527
00:27:28,960 --> 00:27:33,280
Speaker 6: known for is image net, on big database of millions

528
00:27:33,280 --> 00:27:35,919
Speaker 6: of images that really help push forward the field of

529
00:27:36,080 --> 00:27:39,960
Speaker 6: object recognition and images. I'm curious how your work on

530
00:27:40,040 --> 00:27:42,960
Speaker 6: that played into your decision to start World Labs.

531
00:27:42,960 --> 00:27:44,880
Speaker 3: How do you see those two things as related?

532
00:27:45,240 --> 00:27:47,720
Speaker 1: Yeah, thanks for asking that question, Rachel. I think they're

533
00:27:47,800 --> 00:27:50,639
Speaker 1: related into two ways.

534
00:27:50,680 --> 00:27:51,200
Speaker 3: At least.

535
00:27:51,800 --> 00:27:55,640
Speaker 1: One is that image net is one of the earlier

536
00:27:55,680 --> 00:27:59,000
Speaker 1: work in the field of computer vision, which is in

537
00:27:59,040 --> 00:28:04,000
Speaker 1: the pixel space. Granted, in that time, you know more

538
00:28:04,040 --> 00:28:07,919
Speaker 1: than ten years ago what image net and the derivative

539
00:28:08,040 --> 00:28:10,640
Speaker 1: algorithms were able to do. Are still in a two

540
00:28:10,720 --> 00:28:16,760
Speaker 1: D space right, recognizing objects in photos and eventually telling

541
00:28:16,880 --> 00:28:21,800
Speaker 1: stories of pictures. But now this is an intellectual continuation

542
00:28:22,400 --> 00:28:27,240
Speaker 1: of the early working computer vision. Now we're into the

543
00:28:27,280 --> 00:28:31,600
Speaker 1: next really difficult chapter, which is spatial intelligence. So intellectually,

544
00:28:32,080 --> 00:28:36,840
Speaker 1: I feel it's my life's work in continuation and zooming

545
00:28:36,880 --> 00:28:41,600
Speaker 1: out one layer image that was my more than fifteen

546
00:28:41,680 --> 00:28:44,840
Speaker 1: years ago. It was my intellectual bet on a big

547
00:28:44,880 --> 00:28:47,520
Speaker 1: north star problem, a north star problem that can really

548
00:28:47,640 --> 00:28:51,800
Speaker 1: change the course of AI. I do believe spatial intelligence

549
00:28:51,960 --> 00:28:54,640
Speaker 1: is the next north star for me and for my team,

550
00:28:54,760 --> 00:28:57,000
Speaker 1: that it will change the course of AI.

551
00:28:57,960 --> 00:29:02,200
Speaker 6: One of the things I'm wondering about with the funding

552
00:29:02,240 --> 00:29:04,800
Speaker 6: for this company is there are a number of big

553
00:29:04,880 --> 00:29:08,120
Speaker 6: names in AI in particular that invested in this. We've

554
00:29:08,160 --> 00:29:12,000
Speaker 6: got Jeff Dean and Jeffrey Hinton and Dracopathy. Some of

555
00:29:12,040 --> 00:29:15,040
Speaker 6: them you've worked with previously. I know several you were

556
00:29:15,040 --> 00:29:17,560
Speaker 6: at Google at the same time. How did you pitch

557
00:29:17,600 --> 00:29:18,120
Speaker 6: them on it?

558
00:29:19,560 --> 00:29:22,520
Speaker 1: Well, that's the beauty of our field. The first of all,

559
00:29:22,600 --> 00:29:26,200
Speaker 1: these people have been friends and colleagues for years or

560
00:29:26,240 --> 00:29:31,040
Speaker 1: former students. I think they share my belief. I think

561
00:29:31,080 --> 00:29:35,720
Speaker 1: they see this as such a big problem and they

562
00:29:35,760 --> 00:29:39,040
Speaker 1: believe in my team that when they hear my co

563
00:29:39,120 --> 00:29:45,080
Speaker 1: founders been Mildenhall, Christophe Lassner, Justin Johnson, and really the

564
00:29:45,280 --> 00:29:50,120
Speaker 1: entire funding team, they recognize that while this is a

565
00:29:50,160 --> 00:29:53,920
Speaker 1: tough problem, it needs people who really can have the

566
00:29:53,960 --> 00:29:57,800
Speaker 1: ability and believe to crack this, and I think that's

567
00:29:57,800 --> 00:30:00,160
Speaker 1: why they support.

568
00:30:01,120 --> 00:30:05,960
Speaker 4: You've got money from big name vcs as well, Andrewson

569
00:30:06,040 --> 00:30:10,400
Speaker 4: and Horowitz, to name just one. I'm interested more broadly

570
00:30:10,440 --> 00:30:13,960
Speaker 4: about the rallying call you've had for money to go

571
00:30:14,040 --> 00:30:15,120
Speaker 4: towards academia.

572
00:30:15,160 --> 00:30:18,000
Speaker 3: You went to President Biden himself saying.

573
00:30:17,760 --> 00:30:19,960
Speaker 4: That there needs to be more funding in the public

574
00:30:20,000 --> 00:30:22,000
Speaker 4: sector as well as the private sector when it comes

575
00:30:22,000 --> 00:30:26,040
Speaker 4: to AI, R and D ultimately so universities can access

576
00:30:26,080 --> 00:30:30,200
Speaker 4: GPU and compute. Are you still feeling that necessity that

577
00:30:30,640 --> 00:30:32,480
Speaker 4: public sector needs money or have.

578
00:30:32,480 --> 00:30:34,320
Speaker 3: You just sort of given up and gone to the private.

579
00:30:34,040 --> 00:30:40,000
Speaker 1: Sector here, Carolyn, I actually believe even more so now

580
00:30:40,080 --> 00:30:43,920
Speaker 1: that I'm traversing both the private and the public sector

581
00:30:44,400 --> 00:30:48,800
Speaker 1: that's seeing the access to compute, access to support in

582
00:30:48,840 --> 00:30:52,440
Speaker 1: the private sector. I believe none of us will be

583
00:30:52,560 --> 00:30:55,840
Speaker 1: here in the private sector without the public sector, you know,

584
00:30:55,960 --> 00:31:02,400
Speaker 1: imaged net convolution on your network back probably gay transformer models.

585
00:31:02,880 --> 00:31:08,200
Speaker 1: Maining of these seminal work in AI came from public

586
00:31:08,240 --> 00:31:12,880
Speaker 1: sector first. So I think this ecosystem is so critical

587
00:31:13,000 --> 00:31:18,680
Speaker 1: and missing or the imbalance of any component is harmful

588
00:31:18,720 --> 00:31:21,960
Speaker 1: for the ecosystem. And now I have personal experience to

589
00:31:22,080 --> 00:31:25,640
Speaker 1: see the access we have to resources. It makes me

590
00:31:25,760 --> 00:31:29,160
Speaker 1: believe even more that our country needs to invest in

591
00:31:29,200 --> 00:31:33,440
Speaker 1: our public sector, in academia in this kind of moonshop

592
00:31:33,520 --> 00:31:40,320
Speaker 1: mentality to support students and faculty and researchers in basic science.

593
00:31:40,040 --> 00:31:43,960
Speaker 4: Research, academics backing you financially, as well as as I

594
00:31:44,000 --> 00:31:47,640
Speaker 4: say A sixteen z Nea Radical Ventures, as well as

595
00:31:47,640 --> 00:31:50,480
Speaker 4: many others and some celebrities in the mix as well.

596
00:31:50,640 --> 00:31:53,840
Speaker 4: We thank you so much. World Labs co founder Faith

597
00:31:53,840 --> 00:31:56,360
Speaker 4: Ailey and Brinibad's Rachel Metz appreciate it.

598
00:31:57,440 --> 00:31:59,080
Speaker 3: Now let's just talk about elsewhere.

599
00:31:58,800 --> 00:32:01,480
Speaker 4: And AI Open AI see Sam Altman and Video CEO

600
00:32:01,600 --> 00:32:05,040
Speaker 4: Jensen Wang and other industry leaders have actually just been

601
00:32:05,160 --> 00:32:08,360
Speaker 4: meeting with senior Biden administration officials at the White House

602
00:32:08,440 --> 00:32:12,360
Speaker 4: just yesterday, where they discussed steps to address massive infrastructure

603
00:32:12,400 --> 00:32:13,680
Speaker 4: means for AI projects.

604
00:32:13,960 --> 00:32:15,480
Speaker 3: Following the talks, the White House.

605
00:32:15,280 --> 00:32:19,600
Speaker 4: Announced an interagency they're calling it an Interagency Task Force

606
00:32:19,920 --> 00:32:22,719
Speaker 4: to help promote data center development in the US and

607
00:32:22,760 --> 00:32:27,880
Speaker 4: initiatives to support accelerator permitting for those facilities coming up.

608
00:32:27,960 --> 00:32:30,000
Speaker 3: I'm going to be joined by Dylan Cox, had.

609
00:32:29,840 --> 00:32:33,000
Speaker 4: A private market's research at Pitchbook for the firm's latest

610
00:32:33,000 --> 00:32:36,320
Speaker 4: report on private money going into startups like we've just

611
00:32:36,320 --> 00:32:39,800
Speaker 4: been talking about. And then we've got Rethink Impact founder

612
00:32:39,960 --> 00:32:42,640
Speaker 4: and managing partner Jenny Abranson on.

613
00:32:42,600 --> 00:32:44,840
Speaker 3: The firm's latest fundraise. It's a lot.

614
00:32:45,280 --> 00:33:03,880
Speaker 4: This is reallymog technology. This week, Pitchbook released it's quarterly

615
00:33:03,920 --> 00:33:07,280
Speaker 4: private market fundraising report. Not that pretty a reading. Funding

616
00:33:07,360 --> 00:33:09,800
Speaker 4: was down in the second quarter, with bench capitals seeing

617
00:33:09,840 --> 00:33:12,680
Speaker 4: a thirty three percent drop in fundraising year over year.

618
00:33:13,200 --> 00:33:15,520
Speaker 4: As discussed at All with Pitchbook head and private markets

619
00:33:15,520 --> 00:33:19,680
Speaker 4: research Dylan Cox, Dylan, we know that it's been hard

620
00:33:19,720 --> 00:33:22,400
Speaker 4: to raise funds for some who particularly is it.

621
00:33:22,360 --> 00:33:22,800
Speaker 3: Hard for.

622
00:33:24,480 --> 00:33:27,360
Speaker 11: Well, thanks for having me on over the last twelve months.

623
00:33:27,360 --> 00:33:31,280
Speaker 11: Our data shows it's been particularly hard for venture investors

624
00:33:31,400 --> 00:33:35,800
Speaker 11: as well as private real estate funds on the flip side.

625
00:33:35,840 --> 00:33:39,040
Speaker 11: Of things. We've seen some strategies have success, such as

626
00:33:39,080 --> 00:33:43,479
Speaker 11: private equity secondarias, which provides liquidity to private markets and

627
00:33:43,880 --> 00:33:47,040
Speaker 11: mitigates the jcre of impact for newer investors, as well

628
00:33:47,040 --> 00:33:50,240
Speaker 11: as private real assets which a lot of people don't expect.

629
00:33:50,480 --> 00:33:53,080
Speaker 11: There's a lot of money right now flowing into infrastructure,

630
00:33:53,440 --> 00:33:56,440
Speaker 11: kind of along the lines of decarbonization of the economy.

631
00:33:57,040 --> 00:34:01,640
Speaker 4: What about well, data center and digitalization, and we're seeing

632
00:34:01,680 --> 00:34:05,320
Speaker 4: that in terms of the real asset allocation we are.

633
00:34:05,400 --> 00:34:09,280
Speaker 11: That's another big piece of it. It's decarbonization, it's data centers.

634
00:34:09,280 --> 00:34:12,800
Speaker 11: But not to be forgotten are sort of traditional infrastructure

635
00:34:12,880 --> 00:34:16,520
Speaker 11: like roads, bridges, ports and airports. And then something that

636
00:34:16,760 --> 00:34:19,759
Speaker 11: also catches a lot of folks by surprise is the

637
00:34:20,560 --> 00:34:24,280
Speaker 11: sort of slow but study chugging along of more traditional

638
00:34:24,400 --> 00:34:27,240
Speaker 11: natural resources in that bucket, things like oil and gas

639
00:34:27,280 --> 00:34:30,319
Speaker 11: and timber. Funds I think have proved to be a

640
00:34:30,320 --> 00:34:33,000
Speaker 11: bit more resilient than a lot of investors would have expected,

641
00:34:33,080 --> 00:34:34,640
Speaker 11: maybe five or ten years ago.

642
00:34:35,280 --> 00:34:39,560
Speaker 4: Less on our tech theme of things, but important to acknowledge.

643
00:34:40,800 --> 00:34:42,799
Speaker 4: Talk to us a little bit about what's happening in BC.

644
00:34:43,480 --> 00:34:47,120
Speaker 4: What are the funds having to say to former LPs

645
00:34:47,200 --> 00:34:49,600
Speaker 4: to get them to commit to new funds. Where are

646
00:34:49,640 --> 00:34:54,320
Speaker 4: we seeing outlies raise big new funds to allocate.

647
00:34:55,440 --> 00:34:58,520
Speaker 11: Well, AI is certainly the name of the game, which

648
00:34:58,560 --> 00:35:01,920
Speaker 11: will of course surprise no. We're seeing much larger AI

649
00:35:02,000 --> 00:35:04,799
Speaker 11: focused funds as well as AI focused deals right now,

650
00:35:04,920 --> 00:35:07,600
Speaker 11: many of them you know, household names at this point.

651
00:35:08,120 --> 00:35:10,640
Speaker 11: But in terms of the asset class as a whole,

652
00:35:10,760 --> 00:35:14,560
Speaker 11: I think the single most important issue right now is liquidity.

653
00:35:14,920 --> 00:35:19,600
Speaker 11: That's distributions back to investors of venture capital funds viewed

654
00:35:19,640 --> 00:35:22,040
Speaker 11: as a proportion of the size of the fund or

655
00:35:22,040 --> 00:35:25,520
Speaker 11: of the assets and the fund. We're reaching decade lows

656
00:35:25,560 --> 00:35:28,680
Speaker 11: in terms of trailing twelve month distributions, which of course

657
00:35:28,760 --> 00:35:32,520
Speaker 11: means that investors in those venture funds have fewer dollars

658
00:35:32,520 --> 00:35:37,200
Speaker 11: on hand to recommit into the next vintage of venture vehicles.

659
00:35:38,280 --> 00:35:39,800
Speaker 4: Love that you talk us through the secondaries and the

660
00:35:39,880 --> 00:35:42,680
Speaker 4: liquidity side of things as well. Dylan Cox's pitchbook, head

661
00:35:42,680 --> 00:35:43,920
Speaker 4: of Private Markets Research.

662
00:35:44,120 --> 00:35:45,040
Speaker 3: Great to have your take.

663
00:35:45,440 --> 00:35:48,400
Speaker 4: We're actually going to now pinpoint a complete outlier to

664
00:35:48,440 --> 00:35:51,000
Speaker 4: the conversation that we've just been having because we think

665
00:35:51,120 --> 00:35:54,160
Speaker 4: Impact is now one of the largest VC firms dedicated

666
00:35:54,160 --> 00:35:56,920
Speaker 4: to funding female CEOs, and it's just announced the whopping

667
00:35:56,920 --> 00:35:58,440
Speaker 4: two hundred and fifty million dollar.

668
00:35:58,239 --> 00:36:01,440
Speaker 3: Fund, it's third and largest raised to date, any.

669
00:36:01,320 --> 00:36:03,680
Speaker 4: Doubling the firm's assets under management to more than half

670
00:36:03,680 --> 00:36:07,319
Speaker 4: a billion. Founder and managing partner Jenny Abramson joins us.

671
00:36:07,360 --> 00:36:08,360
Speaker 3: Now, So, Jenny, we're.

672
00:36:08,239 --> 00:36:11,799
Speaker 4: Just hearing that it's dire out there for venture but

673
00:36:11,880 --> 00:36:12,319
Speaker 4: not for you.

674
00:36:13,000 --> 00:36:15,120
Speaker 3: Who did you have to come on board? Which LPs

675
00:36:15,160 --> 00:36:15,800
Speaker 3: are interested?

676
00:36:17,360 --> 00:36:19,239
Speaker 7: Well, first of all, thank you for having me on

677
00:36:19,280 --> 00:36:22,319
Speaker 7: behalf of my partner Heidi Patel and the rest of

678
00:36:22,360 --> 00:36:25,360
Speaker 7: our everythinking back team. Yeah, we're very excited to have

679
00:36:25,440 --> 00:36:28,520
Speaker 7: announced more than two hundred and fifty million dollar raise,

680
00:36:28,920 --> 00:36:32,800
Speaker 7: the largest fund backing female CEOs. And we were fortunate,

681
00:36:33,120 --> 00:36:36,239
Speaker 7: despite the trends that Dylan shared, to be able to

682
00:36:36,280 --> 00:36:40,920
Speaker 7: do this in this market. And it was a large

683
00:36:40,960 --> 00:36:43,640
Speaker 7: part due to major institutions who came on board to

684
00:36:43,680 --> 00:36:44,480
Speaker 7: support the fund.

685
00:36:45,040 --> 00:36:49,839
Speaker 4: What sort of institutions are willing to almost take what

686
00:36:50,120 --> 00:36:53,160
Speaker 4: now feels that the pendulum has swung on a more

687
00:36:53,239 --> 00:36:54,680
Speaker 4: d I focused to investing.

688
00:36:56,280 --> 00:36:59,480
Speaker 7: Yeah, I think people major institutions. We had more than

689
00:36:59,600 --> 00:37:03,520
Speaker 7: ten university endowments, we had more than ten major foundations,

690
00:37:03,600 --> 00:37:07,200
Speaker 7: We had, for example, a hospital, and others that really

691
00:37:07,239 --> 00:37:10,360
Speaker 7: do care about returns, and I think have realized that

692
00:37:10,560 --> 00:37:14,319
Speaker 7: investing in women and gender lens investing is not just

693
00:37:14,680 --> 00:37:18,200
Speaker 7: something that feels good, but is actually good business. And

694
00:37:18,280 --> 00:37:21,680
Speaker 7: so they came on board along with many individuals self

695
00:37:21,680 --> 00:37:25,319
Speaker 7: made billionaires like Sarah Blakeley of Spanks and Sneaks, to

696
00:37:26,080 --> 00:37:30,120
Speaker 7: Melinda Frenchgates, the major philanthropists, and to many others. And

697
00:37:30,160 --> 00:37:34,080
Speaker 7: we think the combination of big institutions that I named

698
00:37:34,160 --> 00:37:38,840
Speaker 7: a global bank like UBS, Cambridge Associates and their LPs,

699
00:37:39,840 --> 00:37:42,800
Speaker 7: these kinds of institutions have realized that this is now

700
00:37:42,920 --> 00:37:44,319
Speaker 7: a mainstream opportunity.

701
00:37:44,520 --> 00:37:46,799
Speaker 4: We were just looking at some of your previous portfolio

702
00:37:46,800 --> 00:37:51,760
Speaker 4: from the first fund. The vintage is good, the billions.

703
00:37:51,400 --> 00:37:52,839
Speaker 3: That you've managed to raise it well.

704
00:37:53,040 --> 00:37:56,720
Speaker 4: These founders have now managed themselves valuable at Guild Education

705
00:37:56,880 --> 00:37:58,319
Speaker 4: for example, Spring.

706
00:37:58,080 --> 00:37:59,320
Speaker 3: Health, l Avest.

707
00:38:00,040 --> 00:38:02,879
Speaker 4: But these companies haven't yet exited per se some of them.

708
00:38:03,360 --> 00:38:05,040
Speaker 4: When do you think that that might occur in the

709
00:38:05,080 --> 00:38:07,200
Speaker 4: first fund? How is the IPO pipeline?

710
00:38:07,200 --> 00:38:07,359
Speaker 3: Look?

711
00:38:07,360 --> 00:38:09,799
Speaker 4: If you do these female founders want to go to

712
00:38:09,880 --> 00:38:11,919
Speaker 4: IPO or are they looking at M and A opportunities?

713
00:38:13,080 --> 00:38:14,759
Speaker 7: Yeah, it's a great question. I mean, I think the

714
00:38:14,920 --> 00:38:18,800
Speaker 7: data has shown that female entrepreneurs do deliver higher revenue,

715
00:38:18,920 --> 00:38:22,000
Speaker 7: more than twice as much per dollar invested, and tend

716
00:38:22,000 --> 00:38:25,520
Speaker 7: to exit on average a year faster than their male counterparts.

717
00:38:26,040 --> 00:38:28,759
Speaker 7: And these companies, you know, like all companies, there's been

718
00:38:28,800 --> 00:38:32,800
Speaker 7: a slower IPO market, but we invest sometimes as early

719
00:38:32,840 --> 00:38:35,480
Speaker 7: as a late seed, and so it can take companies

720
00:38:35,520 --> 00:38:39,120
Speaker 7: typically eight ten years as long as well as an

721
00:38:39,160 --> 00:38:42,600
Speaker 7: open IPO market. Of course, there's also M and A opportunities,

722
00:38:43,040 --> 00:38:46,000
Speaker 7: pe buys and others, and so depending on the company,

723
00:38:46,040 --> 00:38:48,000
Speaker 7: different different outcomes will occur.

724
00:38:48,600 --> 00:38:50,400
Speaker 4: We were just hearing from the people who've jumped on

725
00:38:50,440 --> 00:38:53,440
Speaker 4: board to commit capital in and what I kind of

726
00:38:53,520 --> 00:38:57,000
Speaker 4: already referenced of this moment where the pendulum has one,

727
00:38:57,520 --> 00:39:01,360
Speaker 4: we are hearing more pushback against that focus on women,

728
00:39:01,400 --> 00:39:05,040
Speaker 4: people of color, minority founders rather than wanting to embrace them.

729
00:39:05,400 --> 00:39:08,600
Speaker 4: We've seen the Fearless Fund, for example, actually have legal

730
00:39:08,640 --> 00:39:12,320
Speaker 4: issues being able to allocate its grants to women of color.

731
00:39:12,640 --> 00:39:14,640
Speaker 4: Was that anything that you heard of when you were

732
00:39:14,719 --> 00:39:17,759
Speaker 4: out this summer raising the money?

733
00:39:17,840 --> 00:39:22,440
Speaker 7: You know, we really mostly heard that people were excited

734
00:39:22,640 --> 00:39:26,760
Speaker 7: by the opportunity that investing in women is no longer

735
00:39:26,880 --> 00:39:29,120
Speaker 7: just a passing trend, and in the wake of the

736
00:39:29,160 --> 00:39:32,280
Speaker 7: me too movement, and I think this raise makes clear

737
00:39:32,600 --> 00:39:35,640
Speaker 7: that this is good business, good for the economy, and

738
00:39:35,680 --> 00:39:39,000
Speaker 7: certainly here to stay. So that's mostly what we heard.

739
00:39:39,080 --> 00:39:41,960
Speaker 7: Male founding companies continue to get ninety eight percent of

740
00:39:41,960 --> 00:39:45,439
Speaker 7: investment capital, and almost all of our companies have men

741
00:39:45,560 --> 00:39:48,440
Speaker 7: and women in the top team, and we think gender

742
00:39:48,480 --> 00:39:51,920
Speaker 7: diverse teams outperform. And our goal is to you know,

743
00:39:52,000 --> 00:39:54,200
Speaker 7: grow the pie here and grow the economy, which is

744
00:39:54,280 --> 00:39:57,320
Speaker 7: which is what we're doing by backing these great female leaders.

745
00:39:57,440 --> 00:40:00,520
Speaker 4: Oh boy, Jenny, but you say that stop two percent

746
00:40:00,600 --> 00:40:04,440
Speaker 4: basically a VC money going to female founded companies and

747
00:40:04,560 --> 00:40:08,239
Speaker 4: it isn't changing. And I'm interested as to why you

748
00:40:08,280 --> 00:40:10,440
Speaker 4: think that is occurring. If you give us all the

749
00:40:10,480 --> 00:40:15,160
Speaker 4: statistics that they're managing to exit quicker, they're building revenue faster,

750
00:40:15,280 --> 00:40:16,799
Speaker 4: we're seeing better outcomes.

751
00:40:18,360 --> 00:40:20,480
Speaker 7: Yeah, you know, I think this is the moment where

752
00:40:20,480 --> 00:40:23,200
Speaker 7: it's starting to turn to us. This raise from Rethink

753
00:40:23,239 --> 00:40:28,040
Speaker 7: Impact that we announced, it really shows that these mainstream investors,

754
00:40:28,040 --> 00:40:32,400
Speaker 7: these institutional investors, see the opportunity and that the opportunity

755
00:40:32,520 --> 00:40:35,640
Speaker 7: between the data and now examples of companies like many

756
00:40:35,680 --> 00:40:38,040
Speaker 7: that you held up. You know, a company like Spring

757
00:40:38,080 --> 00:40:41,080
Speaker 7: getting a three point three billion dollar valuation last month

758
00:40:41,320 --> 00:40:43,600
Speaker 7: and many others. We think that's going to be the

759
00:40:43,719 --> 00:40:48,360
Speaker 7: turn that leads to capital being more allocated in ways

760
00:40:48,400 --> 00:40:51,359
Speaker 7: that grow the pie. So we're excited. We think this

761
00:40:51,400 --> 00:40:53,680
Speaker 7: is that moment that things are going to finally unlock

762
00:40:54,000 --> 00:40:56,480
Speaker 7: and change that data point that's been stuck for a while.

763
00:40:57,200 --> 00:41:01,840
Speaker 4: Wow, Heidi, patl and yourself leading this and raising a

764
00:41:01,920 --> 00:41:05,560
Speaker 4: huge round, wreathing Impact founder and managing partner Jenny Abramson,

765
00:41:05,800 --> 00:41:08,600
Speaker 4: We thank you for your time. One other VC story

766
00:41:08,600 --> 00:41:11,600
Speaker 4: that we're watching, AI startup Paul Side is in talks

767
00:41:11,640 --> 00:41:14,000
Speaker 4: for a new round of funding, giving an evaluation.

768
00:41:13,560 --> 00:41:16,000
Speaker 3: Of three billion dollars or this before.

769
00:41:15,719 --> 00:41:18,840
Speaker 4: The company even released an initial product. According to sources,

770
00:41:18,840 --> 00:41:20,919
Speaker 4: the company is set to raise five hundred million dollars

771
00:41:20,960 --> 00:41:23,759
Speaker 4: in new financing with being Capital and talks to lead

772
00:41:23,880 --> 00:41:27,000
Speaker 4: the investment round. And that does it for this edition

773
00:41:27,000 --> 00:41:29,320
Speaker 4: of Blomberg Technology. You do not want to forget our podcast.

774
00:41:29,360 --> 00:41:31,000
Speaker 4: You can find it on the terminal as well as

775
00:41:31,000 --> 00:41:32,840
Speaker 4: online on Apple, Spotify, and iHeart.

776
00:41:33,160 --> 00:41:34,920
Speaker 3: And it'll be back with me next week.

777
00:41:35,360 --> 00:41:41,200
Speaker 4: Have a wonderful weekend. This is Bloomberg Technology