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Speaker 1: Welcome to the Bloomberg Markets Podcast. I'm Paul Sweeney, alongside

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Speaker 1: my co host Matt Miller.

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Speaker 2: Every business day we bring you interviews from CEOs, market pros,

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Speaker 2: and Bloomberg experts, along with essential market moving news.

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Speaker 1: Find the Bloomberg Markets Podcast on Apple Podcasts or wherever

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Speaker 1: you listen to podcasts, and at Bloomberg dot com slash podcast.

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Speaker 3: All right, some big.

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Speaker 1: News out of City Group. Are good friends over there

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Speaker 1: at Citygroup, former employer of mine. Big restructuring, so give

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Speaker 1: me some headcount reductions. Let's break it down with two

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Speaker 1: people who really know this stuff, and that is Shananibossk,

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Speaker 1: she covers all Wall Street for Bloomberg News, and of

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Speaker 1: course Alison Williams. She is our senior bank's analyst at

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Speaker 1: Bloomberg Intelligence. Alison, thanks you joined us zoom chanaledge here

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Speaker 1: in studio. Ali to start with you. How big of

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Speaker 1: a deal is this for City You've covered this stock forever,

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Speaker 1: so I think.

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Speaker 4: You know, I recharacterize it as a reorganization perhaps versus

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Speaker 4: a restructuring, where I think they're just really trying to,

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Speaker 4: you know, clean up the reporting lines and maybe help

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Speaker 4: management to be a bit more focused and also you

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Speaker 4: know showcase. You know, as an analyst, I'm excited to

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Speaker 4: get cleaner reporting where we can you know, finally see

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Speaker 4: what's happening with their private bank, with their wealth unit.

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Speaker 4: You know, there was some hints at this over the

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Speaker 4: summer just and you know even prior, I guess with

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Speaker 4: some of the hires that they made, and I just

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Speaker 4: think it's you know, another step in James's journey, if

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Speaker 4: you will, in terms of just making this a cleaner,

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Speaker 4: more focused banks and bank and hopefully getting to the

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Speaker 4: efficiency that investors have long wanted them to get to.

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Speaker 2: So yeah, Shanali, I mean, is this going to help

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Speaker 2: Jane Fraser boost the stock price? Because that's bottom line, right,

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Speaker 2: And I'm looking at you know, over the last five years,

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Speaker 2: they're down thirty percent, whereas Goldman's up sixty three percent,

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Speaker 2: Morgan Stanley's more than doubled.

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Speaker 5: It's certainly a time story for Citygroup. We have had

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Speaker 5: her first set of restructurings here, if you will, where

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Speaker 5: she let go of certain consumer businesses around the world.

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Speaker 5: And now what is difficult for Jane Fraser and their

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Speaker 5: investors of Citygroup is that there are still a lot

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Speaker 5: of unquestioned a lot of unanswered questions about this reorganization,

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Speaker 5: one being how many jobs will be lost. Underneath the surface,

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Speaker 5: our sources say that there could be significant had count

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Speaker 5: reductions here because what City Group is doing is removing

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Speaker 5: layers of management, and this only this announcement only addresses

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Speaker 5: the top two layers. The reality is is they're going

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Speaker 5: to be looking across management around the world, across divisions.

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Speaker 5: One of the things they did in this reorg is

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Speaker 5: they got rid of many of their regional divisions here.

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Speaker 5: So the way you think about Citygroup now is that

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Speaker 5: their Citygroup North America and their City Group International, and

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Speaker 5: you now have five main business lines. It's no longer

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Speaker 5: just the main two, which is institutional client group as

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Speaker 5: well as the consumer offerings. Most of that can zoomer

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Speaker 5: business now is the United States North America. Okay, So

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Speaker 5: there was a real reason that they needed to do this.

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Speaker 5: City Group today does not look the same as City

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Speaker 5: Group two decades ago, when the initial set of current

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Speaker 5: structure is.

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Speaker 6: What you see.

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Speaker 5: In a way, you can see this as the most

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Speaker 5: significant reorganization in two decades because this is really getting

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Speaker 5: rid of the groups that we have known for so

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Speaker 5: long as.

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Speaker 2: A day, Well, it strikes me, Allison, as it came

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Speaker 2: out of my mouth, I realized, probably Golden Sachs and

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Speaker 2: Morgan Stanley aren't the best comparison to City in terms

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Speaker 2: of stock price performance. You know, WELLS Fargo over the

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Speaker 2: last five years is also down only ten percent, not

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Speaker 2: thirty percent, but also down. Bank America over the last

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Speaker 2: five years is only up eight percent, So not down

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Speaker 2: thirty percent, but up eight percent.

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Speaker 3: Are those better comparisons for City?

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Speaker 7: I think they are.

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Speaker 4: I think at the end of the day, when we

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Speaker 4: look at all of these banks, you know, the way

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Speaker 4: that investors think about it is, you know, the valuation

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Speaker 4: is going to be tied to returns as it should be, right,

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Speaker 4: and so someone like someone like Morgan Stanley that you

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Speaker 4: refer to, the comparison could you make, could that you

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Speaker 4: could make is they've improved their structural returns through moving

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Speaker 4: towards the wealth business. You know, looking at someone like

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Speaker 4: JP Morgan, who's a very different bank, they're actually executing,

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Speaker 4: you know, above all of their peers. You know, part

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Speaker 4: of that is the scale that helps the profitability across

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Speaker 4: their businesses, and they have leading returns. And so the

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Speaker 4: struggle with City and I think, you know, part of

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Speaker 4: the reason why it's been tough for the stock is

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Speaker 4: they just have not been able to improve the returns.

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Speaker 4: And if you look across the group, their returns are

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Speaker 4: the worst. You know, wells Fargo, you know, during certain

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Speaker 4: periods of times with all their big charges, had had

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Speaker 4: some weaker returns. But they're sort of on the on

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Speaker 4: the path to better profitability and so that's really what

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Speaker 4: needs to deliver on at the end of the day,

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Speaker 4: it is those returns. And I think why this is

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Speaker 4: important is, you know, as you clear the structure, and

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Speaker 4: you know that's been one of the biggest issues of

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Speaker 4: City is all the bureaucracy and really sort of a

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Speaker 4: massive organization. But if you can get that cleaner and

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Speaker 4: you can improve the efficiency of those core businesses, they

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Speaker 4: do have some good businesses to work with, some higher

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Speaker 4: returning what should be high returning businesses, Chanalie, what.

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Speaker 1: Do you think Jane Fraser wants the message to be

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Speaker 1: about City group? And I think, like Morgan Stanley, I

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Speaker 1: think if James Gorman pivot towards wealth management so successful,

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Speaker 1: what do you think Jane Fraser would like that view

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Speaker 1: of City to be?

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Speaker 5: You know, On one hand, it's simpler for James Gorman

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Speaker 5: to sit there and say we're an investment bank and

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Speaker 5: we're a wealth and asset manager. For Jane Fraser, it's

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Speaker 5: a different story. Her goal here is to have all

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Speaker 5: of her managers essentially get one message, which is get leaner.

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Speaker 5: They have one of the largest investment banks in the world.

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Speaker 5: But just take the M and A business for example.

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Speaker 5: The reason I bring up the M and A business

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Speaker 5: is you are sitting there. They are sitting at it

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Speaker 5: at number six and the lead tales. Actually I just

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Speaker 5: looked at it and got kind of stunned because they're

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Speaker 5: behind cent of you, which is a lot, you know,

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Speaker 5: and that is in terms of deal volumes, and that

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Speaker 5: you know, a year, two years, three years ago is

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Speaker 5: just the stunning thing to see this late in the year.

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Speaker 5: And so the share that they need to gain to

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Speaker 5: keep those fees up as well as squeeze every dollar

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Speaker 5: out of the costs that they have. You know, it's

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Speaker 5: a twofold story. It's one, get competitive and win two,

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Speaker 5: be more efficient with every dollar we have to improve profitability.

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Speaker 5: And so you know, the investment bank is a really

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Speaker 5: good example because in this reorg one open question among

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Speaker 5: those five business leaders is who will run the investment

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Speaker 5: bank over at City the banking business. Currently they have

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Speaker 5: tapped an interim head, Peter Bubbey, who is the CEO

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Speaker 5: at the Asia business. You have to consider this. This

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Speaker 5: is one of the top five M and A businesses

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Speaker 5: in the world. It is one of the hottest jobs

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Speaker 5: on Wall Street.

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Speaker 6: And guess what.

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Speaker 5: They have a huge IPO business, a huge det unready business,

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Speaker 5: and that person, you can't imagine wouldn't one day be

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Speaker 5: the successor for Jane Fraser herself.

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Speaker 7: You know.

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Speaker 5: Again, they have a consumer business that's quite large as well,

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Speaker 5: but they have a massive investment bank and it is

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Speaker 5: a seriously competitive spot.

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Speaker 1: And my buddy Tyler Dixon still running the investment bank over.

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Speaker 5: There, and he is under the new banking I.

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Speaker 1: Know that's interesting, but Tyler is just one of the

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Speaker 1: smartest guys in the room, every room he's in. Shanali Bassett,

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Speaker 1: thank you so much. We got Allison Williams, thank you

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Speaker 1: so much as well.

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Speaker 8: You're listening to the Team Ken's are Live program Bloomberg

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Speaker 8: Markets weekdays at ten am Eastern on Bloomberg dot com,

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Speaker 8: the iHeartRadio app, and the Bloomberg Business app or listen

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Speaker 8: on demand wherever you get your podcasts.

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Speaker 1: Lots going on here today. We want to pivot hard

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Speaker 1: here and we want to talk pharmaceuticals and we want

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Speaker 1: to talk drugs and all that kind of stuff. And

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Speaker 1: we can do that well.

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Speaker 3: And one of the biggest winners the day, biggest.

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Speaker 1: Winners of the day, Stefan Bonsel, CEO of Moderna that

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Speaker 1: is a Nasdaq traded stock. Mr NA is the ticker

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Speaker 1: to put into your Bloomberg terminal. You know nobody. I

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Speaker 1: guess when you sit around your Thanksgiving table, everybody likes

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Speaker 1: to just complain about drug prices, right, everybody does it.

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Speaker 1: It's crossed the aisle. But I turned it around a

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Speaker 1: couple of years ago and said, okay, we can do

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Speaker 1: that because we always like to complain about drug prices.

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Speaker 1: But these guys in the farmer, in the biotech industry, mandad,

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Speaker 1: they come through with COVID.

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Speaker 7: Yeah.

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Speaker 2: I think actually, as a society, we were all a

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Speaker 2: little bit relieved.

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Speaker 1: I'm like, in twelve months, these guys came up with

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Speaker 1: a vaccine. I mean, who does that, But you guys did.

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Speaker 1: Thank you very much. Thank you to the five for

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Speaker 1: folks and all the other farmer and biotech folks out there,

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Speaker 1: that mandad they come through with that vaccine. Appreciate it. Now,

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Speaker 1: what are you doing modern now? Tell us that you

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Speaker 1: guys have your R and D day today, you bring

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Speaker 1: out all your new stuff for your investors, for your stakeholders.

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Speaker 1: What's the big message for your R and D day today?

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Speaker 9: That's well, not the COVID company, yes for the kind

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Speaker 9: of word yes, thank you though, and the money platform

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Speaker 9: company and the platform is firing on every cylinders today

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Speaker 9: went on seeing positive fluid data in phase three. So

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Speaker 9: if you think about it in terms of vaccines, we

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Speaker 9: are free out of free COVID working URSV file to

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Speaker 9: VFDA and to the positive flugh data. In cancer, we

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Speaker 9: are now products showing forty four percent improvement versus the

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Speaker 9: best drug available to patients today, which is immunotherapy in

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Speaker 9: melanomas kin cancer. And we're going to start before the

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Speaker 9: end of the year a phase free study in learn

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Speaker 9: cancer cancer.

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Speaker 10: We really going to transform as well.

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Speaker 2: First that is that, by the way, because of MR

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Speaker 2: and A technology. And I'll just remind listeners we are

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Speaker 2: talking with Stephan Bansel right now. He's the chief executive

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Speaker 2: officer of Moderna. And as you said, you're not just

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Speaker 2: a COVID company. You did have have an mRNA vaccine

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Speaker 2: for COVID that maybe save the world a lot more

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Speaker 2: pain than it would have seen. But you also have

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Speaker 2: a flu vaccine that is driving the stock up today

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Speaker 2: six and a half percent, and cancer treatments that we hope,

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Speaker 2: we all hope, I think are going to be successful

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Speaker 2: and could drive revenue another fifteen billion starting in twenty

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Speaker 2: twenty eight. So tell us about the mRNA technology that

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Speaker 2: we all kind of learned about a couple of years ago.

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Speaker 11: Sure.

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Speaker 9: So, Emmania, as you learned about, is an information molecule.

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Speaker 9: We basically code in that molecule what protein we want

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Speaker 9: your body to make. That would be your drug, your medicine.

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Speaker 9: And in cancer, now what we have shown is a

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Speaker 9: huge impact on survival and being able to not have

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Speaker 9: recurrence of disease compared to the best drugs available to

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Speaker 9: the two patients. And the third chapter for us after

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Speaker 9: infictio zas, vaccine and cancer is real genetic disease. We

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Speaker 9: are now free out of free real genetic disease, showing

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Speaker 9: positive data in kids with those diseases.

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Speaker 10: That have no hope today, zero hope.

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Speaker 1: All right, So back to the flu, because it's we're

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Speaker 1: getting into flu season. What is your flu vaccine? What

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Speaker 1: is new, what is different? It just tell us about

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Speaker 1: what you start today. Why are people so excited about

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Speaker 1: the flu vaccine?

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Speaker 9: Because first we're going to be able to participate and

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Speaker 9: provide a very high efficacy flu vaccine. What we've showed

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Speaker 9: in actually over studies is that actually it's as good as.

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Speaker 10: The best vaccine on the market for flu.

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Speaker 9: But what people I think I excited about is the

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Speaker 9: idea of combination, Meaning we're going to show before the

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Speaker 9: end of the year flu and covid combine in the

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Speaker 9: single shots, so in the following years you won't have

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Speaker 9: to go and get a flu shot in one arm

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Speaker 9: and the covid shot in ther arm.

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Speaker 10: They'll be combined.

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Speaker 9: And then over time we're going to keep adding more

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Speaker 9: and more respiratory virus like RSV to the combination as well,

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Speaker 9: so that you can have only one shot early in

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Speaker 9: the four at the pharmacy, and then you have a

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Speaker 9: happy follower in winter you're not sick.

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Speaker 1: So but this is for next year, This is not

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Speaker 1: for this cournflusing Okay, got it. I just want to get

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Speaker 1: clear on the timing.

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Speaker 3: You can still get your flu vaccine for this. I'm

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Speaker 3: gonna go.

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Speaker 1: Down to LL two and get my flu vaccine. I mean,

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Speaker 1: who doesn't do that? So with mr mRNA tech technology,

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Speaker 1: what's it three to five years down the road, what

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Speaker 1: do you expect that technology to tackle next?

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Speaker 10: Maybe?

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Speaker 9: So we're announcing today at Adiday that we should launch

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Speaker 9: fifteen new drug in the next five years.

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Speaker 1: Fifteen new drugs in the next five that's.

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Speaker 9: How incredible across cancer, infect disease, and genetic disease. We're

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Speaker 9: also working on an autoimmune disease I think althatries, chron

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Speaker 9: disease and so on. We believe we're going to bring

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Speaker 9: fifteen more drugs on top of forty we have in

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Speaker 9: development fifty five zero okay from the lab into the

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Speaker 9: clinic in the next five years, or around ten new

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Speaker 9: drugs per year moving from the labs into developments. So

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Speaker 9: what you see here is a true platform. There has

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Speaker 9: never been platform in the biotech far my industry. As

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Speaker 9: you know, most drugs go to the clinic. Yep, they're

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Speaker 9: fair ninety percent of drug starting a phase one will

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Speaker 9: never get launched Okay, I look at Moderna because of

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Speaker 9: our platform, because am money is an information molecule. We

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Speaker 9: are three out of three in vaccines, we have three

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Speaker 9: out of three in real genetic disease cancer. Incredible improvements

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Speaker 9: and it's just the beginning.

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Speaker 2: All right, this is all because of the mRNA technology.

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Speaker 2: And I have a funding question. Then what happens if

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Speaker 2: you know the COVID vaccine revenues don't meet your expectations?

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Speaker 2: Can you still fund that kind of growth?

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Speaker 7: Sure?

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Speaker 9: I mean, if you look at it, we say that

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Speaker 9: this year we should be six to eight billion dollars

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Speaker 9: of cells, which is still a very significant number.

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Speaker 10: For turnover.

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Speaker 9: We are fourteen billion dollar on a balanch sheet that

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Speaker 9: we got through the COVID sales over the last two years,

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Speaker 9: and so we can fund around we think twenty five

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Speaker 9: billion dollar of RD growth by cash directing, by the

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Speaker 9: business and the balance sheet. And we will also not

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Speaker 9: be shy to partner if we have to. We're obsessed

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Speaker 9: about getting those drugs to patients to be finish line.

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Speaker 9: But if you look at for example, with Vertex, we

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Speaker 9: partnered for cistic fibrosi, it's for inhale. The money getting

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Speaker 9: to the long of a kid that have cistic fibrosis

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Speaker 9: by inhalation, we develop that technology yet another fourth cylinder

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Speaker 9: for moderna to develop a new family of drugs. And

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Speaker 9: so that's what we're trying to do is push a

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Speaker 9: boundary of science, get more and more drugs and if

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Speaker 9: we have to partner, and we'll partner.

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Speaker 3: But it's expensive to do.

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Speaker 2: And you know, because of recent legislation the United States,

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Speaker 2: the bidance strategs past, the United States is going to

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Speaker 2: not only negotiate prices with drug makers, but set prices

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Speaker 2: with drug makers.

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Speaker 3: Is that a concern to you very much?

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Speaker 9: So as the rest of the industry as voiced, you

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Speaker 9: cannot set prices because ird is risky. As we just

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Speaker 9: talked about ninety percent of drugs entering the clinic failure,

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Speaker 9: very high failure rate of the industry as a whole.

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Speaker 10: If you start to set.

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Speaker 9: Price and not look at value that is bringing by

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Speaker 9: the drugs, you're going to reduce the ability of pharmasty,

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Speaker 9: core and biotech companies to invest in innovation.

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Speaker 10: And that's a big worry.

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Speaker 2: But they're going to set prices, So how are you

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Speaker 2: going to deal with it?

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Speaker 9: So we just need to keep innovating and figure out

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Speaker 9: ways to go after smaller disease type selling around the world,

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Speaker 9: because again the US of course is the number one

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Speaker 9: market in the world, but other markets are also very important,

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Speaker 9: like Europe, you know, Japan, and so we're going to

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Speaker 9: have to grow internationally as well.

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Speaker 10: But it's a big issue. I'm worried about it, all right.

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Speaker 1: How about I always joke that in my next life

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Speaker 1: I want to come back as a healthcare m and

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Speaker 1: a banker because every Monday we come in and there's

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Speaker 1: another healthcare deal that you are one of your competitors.

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Speaker 1: Do is there something that you need to buy in

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Speaker 1: the next couple of years to get to where you

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Speaker 1: want to go that maybe is not in your pipeline

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Speaker 1: right now.

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Speaker 7: No.

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Speaker 9: What is cool about Amani is we are the world

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Speaker 9: leader in AMANI. Even BioNTech, which is a great company,

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Speaker 9: they are doing small molecule, a lot of molecule, a

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Speaker 9: lot of different technologies. We are only doing AMMONI. What

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Speaker 9: we're doing through obed activity is ever buying. We bought

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Speaker 9: a company in Japan over the Christmas breaks a cool

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Speaker 9: technology to make our EMMANI operating system stronger and bigger.

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Speaker 10: So we can do more drugs.

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Speaker 9: We are nowso mon there dealing cancer with a company

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Speaker 9: in Germany that has very cool science and biology that

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Speaker 9: we can code into the EMANI molecule to do new drugs.

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Speaker 9: So this will do to expand the potential of impacting patients.

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Speaker 3: All right, excellent to have you in here.

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Speaker 2: I really appreciate it, and I know you're going to

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Speaker 2: go on television in just a moment, so our listeners

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Speaker 2: will be able to watch you with Alex Steel and

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Speaker 2: Guy Johnson on the European clothes. Just a fascinating discussion

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Speaker 2: and also a fascinating move in the stock up six

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Speaker 2: point seven percent.

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Speaker 1: Yeah about that, Stefan Bansel, thank you so much for

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Speaker 1: joining Usteffan as the CEO of Momoderna again the taker

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Speaker 1: symbol free stock Jockey's out there, mr Na. We appreciate that.

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Speaker 1: Thank you so much. All right, looking ahead here at

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Speaker 1: this market here we are pretty much unchanged, so you know,

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Speaker 1: we're gonna be very interesting to see how this market.

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Speaker 1: But you know Moderna that again, that's stock, as you mentioned,

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Speaker 1: Matt up six percent today, down thirty seven percent year

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Speaker 1: to date.

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Speaker 8: You're listening to the tape cans are live program Bloomberg

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Speaker 8: Markets weekdays at ten am Eastern on Bloomberg Radio, the

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Speaker 8: tune in app, Bloomberg dot Com, and.

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Speaker 11: The Bloomberg Business App.

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Speaker 8: You can also listen live on Amazon Alexa from our

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Speaker 8: flagship New York station Just Say Alexa playing Bloomberg eleven thirty.

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Speaker 1: Uncle Crawford joins us. She's a portfolio manager and executive

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Speaker 1: VP at Aldre. Encour thank you so much for joining

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Speaker 1: us here in our Bloomberg Interactive Broker studio. I just

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Speaker 1: love looking at people's you know, kind of how they

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Speaker 1: kind of came up through the business. So, but you've

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Speaker 1: been at Alger since September two thousand and four, so

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Speaker 1: you've seen some market movements. What are you telling? What

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Speaker 1: are you guys at Aldre doing now? Stock market's up

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Speaker 1: double digits this year, We've had a little bit of

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Speaker 1: a bounce back off of an ugly twenty twenty two.

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Speaker 1: Now what do we do?

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Speaker 12: Yeah, I think it's not going to be quite as

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Speaker 12: easy as it has been over the last nine months. Okay,

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Speaker 12: and we're going into chop your waters, and in part

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Speaker 12: because we're just waiting for the economy to respond and

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Speaker 12: we just don't know the magnitude of how it's going

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Speaker 12: to respond. Is it going to be a soft landing,

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Speaker 12: hard landing, no landing? And I think no landing is

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Speaker 12: coming off the table. I think the expectation is now

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Speaker 12: for soft landing, and there's arguments for hard landing. So

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Speaker 12: I think because of that uncertainty in the market right now,

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Speaker 12: the consumer resilience is starting to taper. The job market

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Speaker 12: is starting to come off a boil. We're going to

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Speaker 12: see you chop your market.

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Speaker 3: Does landing imply cuts?

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Speaker 2: I mean in hard landing, clearly think the fed's going

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Speaker 2: to cut because that means we're in a bad recession.

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Speaker 2: I don't totally know what soft landing means in terms

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Speaker 2: of a FED reaction, and do they cut or you know,

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Speaker 2: I know what the soft landing is like in terms

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Speaker 2: of an airplane.

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Speaker 3: I'm just saying, like.

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Speaker 2: When you come down right and just set it down gently.

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Speaker 2: I guess growth doesn't contract, but it's also not expanding

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Speaker 2: at a massive pace. And does the FED then cut

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Speaker 2: or do they leave rate higher for longer?

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Speaker 12: You know what? And that's the risk they could actually

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Speaker 12: leave rates higher for longer in that scenario. So it's

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Speaker 12: funny because the people that believe that the FED is

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Speaker 12: going to cut, and they're excited about the FED cuts.

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Speaker 12: I look at them and say, well, you know what, first,

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Speaker 12: the economy has to get really bad if they're going

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Speaker 12: to cut at this pace.

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Speaker 2: I will warn you that Paul thinks that we're going

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Speaker 2: to have a nice soft landing and the Fed's gonna cut.

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Speaker 1: The former equity analys I'm always on Freggre optimistic.

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Speaker 2: Yes, a former equity analyst with a floating rate mortgage.

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Speaker 3: So he would like to rEFInd you.

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Speaker 12: Know, maybe that's wishful thinking.

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Speaker 1: I know, I know, I couldn't accuse that before. All Right,

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Speaker 1: you know we're just talking to Kaylee Lines from Bloomberg Television.

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Speaker 1: She's done a DC kind of reporting on this AI

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Speaker 1: thing in Congress. How do you guys alter review AI

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Speaker 1: because you could argue that's been a big driver of

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Speaker 1: the performance this year.

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Speaker 12: Yeah, we are very very bullish on AI. We've been

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Speaker 12: bullish on AI, and we think that jen AI and

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Speaker 12: what we're seeing with these LLM models, large language models,

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Speaker 12: the large language models that are democratizing.

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Speaker 1: Sing your PhD in engineering, I like it, see I.

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Speaker 12: Like it that it's basically democratizing technology and it's going

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Speaker 12: to create a step function up in adoption rates for

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Speaker 12: all kinds of businesses through healthcare, industrials, tech. So highly

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Speaker 12: bullish on AI. The adoption is going to be we

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Speaker 12: think thirty to forty percent by the end of this decade,

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Speaker 12: which is in any kind of industrial revolution that we've seen.

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Speaker 12: It's the fastest adoption rate we're going to see.

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Speaker 3: But will it hit the labor market?

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Speaker 2: I mean, right now, we saw unemployment come up to

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Speaker 2: like three point eight percent, right but that was all

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Speaker 2: because more people were coming back in.

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Speaker 3: So it's still a very tight, very strong labor market.

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Speaker 3: That's what we hear.

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Speaker 2: Is AI going to displace a lot of jobs in

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Speaker 2: the by the end of the decade.

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Speaker 12: I think it's hard to say. But just on the

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Speaker 12: before we move on to AI, on the unemployment and employment,

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Speaker 12: Walmart and best Buy both the conferences this week indicated

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Speaker 12: that Walmart, we know, is taking down starting wages for jobs.

442
00:21:25,480 --> 00:21:26,800
Speaker 1: They're taking down they're.

443
00:21:26,600 --> 00:21:30,280
Speaker 12: Taking down wages really. Best Buy indicated that you know,

444
00:21:30,400 --> 00:21:33,399
Speaker 12: maybe they would do low single digits or worse than

445
00:21:33,440 --> 00:21:35,600
Speaker 12: low single digits, which would be you know, we we

446
00:21:35,680 --> 00:21:39,199
Speaker 12: think that means zero. So wage growth is now starting

447
00:21:39,240 --> 00:21:42,320
Speaker 12: to come off a boil, which is the first indication

448
00:21:42,480 --> 00:21:44,880
Speaker 12: in the economy that employments starting.

449
00:21:44,560 --> 00:21:48,040
Speaker 2: To turn interesting to see the labor market kind of

450
00:21:48,359 --> 00:21:49,400
Speaker 2: flagging a little bit.

451
00:21:49,880 --> 00:21:52,680
Speaker 12: Yeah, So if you look at ours worked, ours worked

452
00:21:52,720 --> 00:21:55,120
Speaker 12: is coming off its peaks. It's been declining for a year,

453
00:21:55,200 --> 00:21:59,520
Speaker 12: year and a half hourly wages. Right now it's still rising.

454
00:21:59,640 --> 00:22:02,480
Speaker 12: I think we start to see a moderation. But that's

455
00:22:02,520 --> 00:22:05,800
Speaker 12: just on the employment side. So as for GENAI and

456
00:22:05,840 --> 00:22:08,560
Speaker 12: what the impact will be, what we're hearing right now

457
00:22:08,680 --> 00:22:13,360
Speaker 12: is companies that are deploying GENAI inside of their own

458
00:22:13,440 --> 00:22:17,280
Speaker 12: businesses today, they're not firing people, but they don't have

459
00:22:17,320 --> 00:22:20,439
Speaker 12: to hire as many people because productivity is increasing. So

460
00:22:20,520 --> 00:22:23,119
Speaker 12: does it change the composition of the labor market and

461
00:22:23,200 --> 00:22:26,360
Speaker 12: the demand for labor. It might. But what it means

462
00:22:26,400 --> 00:22:27,919
Speaker 12: that we're going to have to retool. We're going to

463
00:22:27,920 --> 00:22:30,320
Speaker 12: have to retool our economy and our workforce.

464
00:22:30,480 --> 00:22:32,320
Speaker 1: Oh boy, that's just what a lot of folks want

465
00:22:32,320 --> 00:22:32,480
Speaker 1: to hear.

466
00:22:32,560 --> 00:22:32,639
Speaker 7: Right.

467
00:22:32,800 --> 00:22:36,600
Speaker 1: First they got and mean by people going across jobs

468
00:22:36,600 --> 00:22:37,960
Speaker 1: going across seas and now they have to do this

469
00:22:37,960 --> 00:22:39,960
Speaker 1: whole worry about AI. All right, When I think of

470
00:22:40,040 --> 00:22:43,800
Speaker 1: Fred alger Asset management or algie. I think growth investors.

471
00:22:46,320 --> 00:22:48,439
Speaker 1: Where are you guys looking what sectors are kind of

472
00:22:48,480 --> 00:22:50,600
Speaker 1: interesting to you? We mentioned maybe tech and AI and

473
00:22:50,600 --> 00:22:52,160
Speaker 1: that type of thing, or else are you guys looking

474
00:22:52,160 --> 00:22:52,920
Speaker 1: for opportunities?

475
00:22:53,240 --> 00:22:56,560
Speaker 12: You know, I think when people think of AI and

476
00:22:56,600 --> 00:23:00,680
Speaker 12: investors think of AI, they automatically say Nvidia or Microsoft,

477
00:23:00,760 --> 00:23:03,040
Speaker 12: and yes, we are investing. We are big holders of

478
00:23:03,040 --> 00:23:07,040
Speaker 12: both Microsoft and Video and the common AI platforms. But

479
00:23:07,200 --> 00:23:10,160
Speaker 12: what they forget is that in order to deploy all

480
00:23:10,200 --> 00:23:14,119
Speaker 12: of this AI, we also need to be you know,

481
00:23:14,160 --> 00:23:16,679
Speaker 12: we need to build data centers. Okay, there are no

482
00:23:16,760 --> 00:23:19,760
Speaker 12: data centers. Data centers are full. We need electricity.

483
00:23:20,240 --> 00:23:24,200
Speaker 1: So data centers are full. Where are the data centers

484
00:23:24,240 --> 00:23:25,080
Speaker 1: and why are they full?

485
00:23:25,720 --> 00:23:28,480
Speaker 12: Well, in part, they're full because there's no electricity going

486
00:23:28,480 --> 00:23:30,639
Speaker 12: to the data centers, and so there's going to have

487
00:23:30,680 --> 00:23:34,280
Speaker 12: to be this CAPEX cycle that supports the utilities to

488
00:23:34,320 --> 00:23:38,119
Speaker 12: provide electricity to the data center. And so, you know,

489
00:23:38,160 --> 00:23:42,480
Speaker 12: there's a lot of interesting names the like Quanta, Quanta,

490
00:23:42,520 --> 00:23:45,960
Speaker 12: PWR or you know, we have an investment in a

491
00:23:45,960 --> 00:23:50,080
Speaker 12: company called Vertice, which is a cooling company and so

492
00:23:50,119 --> 00:23:54,679
Speaker 12: they basically they provide widgets into a data center and

493
00:23:54,760 --> 00:23:57,760
Speaker 12: one of those widgets is the new cooling mechanism that

494
00:23:57,800 --> 00:23:59,960
Speaker 12: you're going to need for these GENAI servers.

495
00:24:00,520 --> 00:24:01,919
Speaker 3: So there's digital bridge.

496
00:24:02,240 --> 00:24:06,399
Speaker 12: There's different ways. Yeah, there's different ways to play this

497
00:24:06,560 --> 00:24:10,080
Speaker 12: trend in industrials and other parts of the economy that

498
00:24:10,080 --> 00:24:11,200
Speaker 12: we're also focused on.

499
00:24:12,040 --> 00:24:12,720
Speaker 3: That's interesting.

500
00:24:12,800 --> 00:24:14,720
Speaker 2: You know, we did a big story about Mexico and

501
00:24:14,720 --> 00:24:17,000
Speaker 2: how difficult it is to be reshoring there because they

502
00:24:17,040 --> 00:24:20,520
Speaker 2: just don't have the infrastructure. Okay, right, and I guess

503
00:24:20,520 --> 00:24:24,399
Speaker 2: the same problem faces Generative AI because you need to

504
00:24:24,440 --> 00:24:28,320
Speaker 2: have a lot more giant server farms set up to

505
00:24:28,400 --> 00:24:30,560
Speaker 2: run all the Nvidia chips that are getting ordered.

506
00:24:30,800 --> 00:24:32,600
Speaker 1: Well don't we have a lot of you fly over

507
00:24:32,680 --> 00:24:35,600
Speaker 1: territory that put a big server farm out there.

508
00:24:35,680 --> 00:24:37,400
Speaker 2: Yeah, but you got to put it up. I mean

509
00:24:37,440 --> 00:24:40,000
Speaker 2: it takes money, right. You need the bulldozers, you need

510
00:24:40,040 --> 00:24:42,600
Speaker 2: all the cat equipment, you know, that's what we're talking about,

511
00:24:43,119 --> 00:24:44,840
Speaker 2: and you got to put in the computers.

512
00:24:44,880 --> 00:24:48,400
Speaker 1: So are you concerned about valuation in this marketplace because

513
00:24:48,440 --> 00:24:49,800
Speaker 1: a lot of folks say, hey, if you strip out

514
00:24:49,800 --> 00:24:52,560
Speaker 1: the magnificent seven, this market's not so expensive. How do

515
00:24:52,600 --> 00:24:53,680
Speaker 1: you guys think about valuation?

516
00:24:54,080 --> 00:24:56,240
Speaker 12: So we kind of do it as a sum of

517
00:24:56,280 --> 00:24:59,199
Speaker 12: the parts, and we look at the components. So you

518
00:24:59,200 --> 00:25:02,560
Speaker 12: look at Microsoft. Microsoft currently trades at you know, on

519
00:25:02,720 --> 00:25:04,399
Speaker 12: a grunt you have to look out to twenty twenty

520
00:25:04,400 --> 00:25:07,520
Speaker 12: five when they have a full blossoming of their AI

521
00:25:07,760 --> 00:25:10,399
Speaker 12: or least they're on way to that. It trades at

522
00:25:10,400 --> 00:25:16,080
Speaker 12: a high teens multiple. You look at Meta, Meta trades

523
00:25:16,119 --> 00:25:18,840
Speaker 12: at a mid teams multiple. Google at a mid to

524
00:25:18,920 --> 00:25:23,040
Speaker 12: high teens multiple on twenty twenty four numbers. So you know,

525
00:25:23,040 --> 00:25:25,439
Speaker 12: there are portions of the market, big portions of the

526
00:25:25,440 --> 00:25:30,639
Speaker 12: market that actually don't screen as having necessarily an incregious valuation.

527
00:25:32,240 --> 00:25:34,720
Speaker 12: Look now there's other portions of the market that you know,

528
00:25:34,800 --> 00:25:38,640
Speaker 12: one can say, you know, the growthier stuff that has

529
00:25:38,760 --> 00:25:40,960
Speaker 12: worked this year, could it pulled back?

530
00:25:41,240 --> 00:25:43,479
Speaker 1: It could, Okay? On Core Crawfit, thank you so much

531
00:25:43,520 --> 00:25:46,040
Speaker 1: for joining us, Really appreciate it. On Core Crawford, she's

532
00:25:46,040 --> 00:25:49,280
Speaker 1: a portfolio management and executive vice president at Alger the

533
00:25:49,320 --> 00:25:51,320
Speaker 1: asset management folks. Some good folks there.

534
00:25:51,359 --> 00:25:53,240
Speaker 3: I've known a doctor and an engineer.

535
00:25:53,240 --> 00:25:57,320
Speaker 8: I know you're listening to the Team Cancer Live program

536
00:25:57,440 --> 00:26:00,280
Speaker 8: Bloomberg Markets weekdays at ten am Eastern.

537
00:26:00,080 --> 00:26:02,880
Speaker 11: On Bloomberg dot com. The iHeartRadio app and.

538
00:26:02,840 --> 00:26:05,760
Speaker 8: The Bloomberg Business app or listen on demand wherever you

539
00:26:05,800 --> 00:26:06,800
Speaker 8: get your podcasts.

540
00:26:08,720 --> 00:26:10,359
Speaker 1: All right, let's talk to IPOs because we got the

541
00:26:10,359 --> 00:26:13,240
Speaker 1: IPO market. Actually have a little interest out there. We're

542
00:26:13,240 --> 00:26:15,680
Speaker 1: gonna we got the belly Lipscholtzho covers all the markets

543
00:26:15,920 --> 00:26:19,560
Speaker 1: for us. And then Kunjohn Sabani, he leads semiiconductor analysts

544
00:26:19,600 --> 00:26:23,560
Speaker 1: for Bloomberg Intelligencies, based out there in the beautiful San

545
00:26:23,560 --> 00:26:26,920
Speaker 1: Francisco awes on peer three. Uh down there in the Embarcadero.

546
00:26:27,440 --> 00:26:30,000
Speaker 1: Great stuff out there, he joins us via zoom Belly.

547
00:26:30,040 --> 00:26:32,439
Speaker 1: I want to start with you, uh, Birkenstock. When I

548
00:26:32,440 --> 00:26:36,480
Speaker 1: think Birkenstock, I think Matt Miller, you know, and they're

549
00:26:36,480 --> 00:26:38,359
Speaker 1: going public. Talk to us about this company and what

550
00:26:38,400 --> 00:26:38,919
Speaker 1: this deal is.

551
00:26:39,119 --> 00:26:39,320
Speaker 11: Yeah.

552
00:26:39,359 --> 00:26:40,359
Speaker 1: The company filed for.

553
00:26:40,280 --> 00:26:44,000
Speaker 13: Their IPO yesterday evening, kind of an anticipated Bloomberg had

554
00:26:44,000 --> 00:26:46,840
Speaker 13: been all over that expecting that they will target an

555
00:26:46,920 --> 00:26:49,280
Speaker 13: initial evaluation about eight billion dollars.

556
00:26:49,480 --> 00:26:50,800
Speaker 1: Looking at some of the results.

557
00:26:50,520 --> 00:26:53,880
Speaker 13: That they laid out, though profitable, growing, the two things

558
00:26:53,880 --> 00:26:56,639
Speaker 13: that investors are really looking for their el Caterton backed.

559
00:26:56,720 --> 00:27:01,240
Speaker 13: So uh, interesting deal l out for this company when

560
00:27:01,240 --> 00:27:03,639
Speaker 13: you look at kind of where we are talking to

561
00:27:03,680 --> 00:27:05,840
Speaker 13: some of the analysts and investors. Latest in a string

562
00:27:05,840 --> 00:27:08,959
Speaker 13: of consumer facing companies that have filed. So consumer, if

563
00:27:09,000 --> 00:27:11,679
Speaker 13: you're profitable, if you're growing, and you have durability, some

564
00:27:11,800 --> 00:27:15,560
Speaker 13: insight into where you're going going forward, seems to be

565
00:27:16,080 --> 00:27:18,880
Speaker 13: one of the areas alongside tech that there is interest

566
00:27:19,080 --> 00:27:21,320
Speaker 13: both from the company and from investors.

567
00:27:21,800 --> 00:27:25,639
Speaker 2: All right, So that's that's nothing that Kunjon cares about. No,

568
00:27:25,960 --> 00:27:30,920
Speaker 2: he's a lead semiconductor analyst. Maybe you're wearing birkenstocks, Kunjohn,

569
00:27:30,960 --> 00:27:33,360
Speaker 2: but you're focused I guess primarily on ARM.

570
00:27:33,440 --> 00:27:35,720
Speaker 7: Right, Yeah, all right, right.

571
00:27:35,640 --> 00:27:38,159
Speaker 1: Talk to us about this this ipo ARM is a

572
00:27:38,280 --> 00:27:40,159
Speaker 1: tell us what ARM is and tell us kind of

573
00:27:40,160 --> 00:27:41,720
Speaker 1: what the pitch is from your perspective.

574
00:27:42,720 --> 00:27:45,600
Speaker 7: Yeah, So ARM is a semiconductor design IP company. They

575
00:27:45,600 --> 00:27:48,720
Speaker 7: don't make chips. They make an IP which other chip

576
00:27:48,760 --> 00:27:53,240
Speaker 7: makers can use and create for creating chips. Historically, the

577
00:27:53,280 --> 00:27:56,240
Speaker 7: because they have been they have the largest i mean

578
00:27:56,480 --> 00:27:58,560
Speaker 7: entire market when it comes to a smartphone, ninety nine

579
00:27:58,600 --> 00:28:01,760
Speaker 7: percent market share, so that what they wear historically. Then

580
00:28:01,800 --> 00:28:05,040
Speaker 7: when Software bought them, the play was that IoT is

581
00:28:05,040 --> 00:28:07,560
Speaker 7: supposed to be this big thing, so they got into IoT.

582
00:28:07,880 --> 00:28:11,879
Speaker 7: They have their Internet of Things, yes, and they're still

583
00:28:11,880 --> 00:28:14,400
Speaker 7: a dominant player in that market. The pitch right now

584
00:28:14,400 --> 00:28:17,280
Speaker 7: for the IPO is really on AI, as is for

585
00:28:17,359 --> 00:28:21,919
Speaker 7: every sevilconnector company these days. Right now they have single

586
00:28:21,960 --> 00:28:26,040
Speaker 7: digit market share in data center and AI, but the

587
00:28:26,119 --> 00:28:28,480
Speaker 7: pitches that that market share will grow and they are

588
00:28:28,720 --> 00:28:31,320
Speaker 7: expected to be the fastest growing in that.

589
00:28:32,760 --> 00:28:35,120
Speaker 1: But but Kunjin, you've been around. We hired you away

590
00:28:35,160 --> 00:28:39,280
Speaker 1: from Deutsche Bank, so major upgrade there, Kunjin, You've seen

591
00:28:39,280 --> 00:28:40,040
Speaker 1: this stuff come and go.

592
00:28:40,160 --> 00:28:41,239
Speaker 6: You know what the real deal is.

593
00:28:41,400 --> 00:28:44,040
Speaker 1: They're asking me at the IPO to buy a phone

594
00:28:44,120 --> 00:28:47,560
Speaker 1: chip design company, but pay an AI multiple? Is that?

595
00:28:47,640 --> 00:28:51,760
Speaker 7: Is that the gig that is almost yes, okay, are

596
00:28:51,760 --> 00:28:55,040
Speaker 7: you buying it? So when they came out with the

597
00:28:55,120 --> 00:28:58,120
Speaker 7: initial target of sixteen seventy, we wrote that this seems

598
00:28:58,200 --> 00:29:01,080
Speaker 7: very ambitious even exactly one of the reasons what you

599
00:29:01,080 --> 00:29:04,200
Speaker 7: pointed out. But the pricing with they came out, which

600
00:29:04,200 --> 00:29:07,280
Speaker 7: is midpoint of fifty, we like that as a starting point.

601
00:29:07,800 --> 00:29:11,239
Speaker 7: We thought that would invite some attractive positive discussions from

602
00:29:11,280 --> 00:29:13,320
Speaker 7: the investors, and it seems from the data we have

603
00:29:13,400 --> 00:29:16,479
Speaker 7: heard that get their numerous times over subscribed, so that

604
00:29:16,680 --> 00:29:19,280
Speaker 7: seem to have worked. But yes, to answer your question,

605
00:29:19,320 --> 00:29:22,200
Speaker 7: I mean, look, this happens. I was also in banking before,

606
00:29:22,200 --> 00:29:24,680
Speaker 7: so I've done IPOs for semi companies and this is

607
00:29:24,680 --> 00:29:28,080
Speaker 7: how usually the conversion goes. During IPOs, people are pitching

608
00:29:28,320 --> 00:29:30,880
Speaker 7: way far out, like what this can be in five years.

609
00:29:31,160 --> 00:29:33,720
Speaker 7: And the theory is, if you believe that thesis, you're

610
00:29:33,760 --> 00:29:37,000
Speaker 7: buying it today for lower because once it gets there,

611
00:29:37,040 --> 00:29:39,640
Speaker 7: once they have a lot of data center revenues, they're

612
00:29:39,640 --> 00:29:41,920
Speaker 7: going to get a lot more premium for their evaluation

613
00:29:42,000 --> 00:29:44,120
Speaker 7: and that's where investors can generate their return.

614
00:29:45,120 --> 00:29:45,560
Speaker 11: Very good.

615
00:29:45,640 --> 00:29:50,960
Speaker 1: Hey, Billy Birkenstock, I mean it's is what's the pitch

616
00:29:50,960 --> 00:29:53,000
Speaker 1: here is is this going to be a lifestyle kind

617
00:29:53,000 --> 00:29:53,320
Speaker 1: of are.

618
00:29:53,320 --> 00:29:54,320
Speaker 3: Going to be five years out?

619
00:29:54,400 --> 00:29:54,560
Speaker 11: Yeah?

620
00:29:54,800 --> 00:29:57,240
Speaker 2: I mean the same thing as there were fifty years before.

621
00:29:57,560 --> 00:29:59,720
Speaker 2: I mean what's changed?

622
00:30:00,120 --> 00:30:01,760
Speaker 13: No, I mean they were in the Barbie movie, so

623
00:30:01,800 --> 00:30:06,200
Speaker 13: that reinventiated interest with the youths. When you look at

624
00:30:06,240 --> 00:30:08,239
Speaker 13: their sales, they're one of the things that stood out

625
00:30:08,280 --> 00:30:10,600
Speaker 13: in the filing is kind of this push towards direct

626
00:30:10,600 --> 00:30:13,120
Speaker 13: to consumer sales, so trying to cut out the cost

627
00:30:13,160 --> 00:30:14,760
Speaker 13: of going through a traditional.

628
00:30:14,280 --> 00:30:16,760
Speaker 1: Brick and mortar or other kind of website.

629
00:30:16,960 --> 00:30:19,520
Speaker 13: When you look at it though, eight billion dollar price

630
00:30:19,600 --> 00:30:24,120
Speaker 13: about eighteen times forecasted adjusted EBITDAH, so in line with

631
00:30:24,880 --> 00:30:29,160
Speaker 13: the Nikes of the world, though margins are typically higher

632
00:30:29,200 --> 00:30:32,040
Speaker 13: for Birkenstock. It is going to be interesting though what

633
00:30:32,080 --> 00:30:34,600
Speaker 13: they pitch comps at. Though you look at Decker's brands,

634
00:30:34,680 --> 00:30:36,720
Speaker 13: one that comes to mind talking to a couple, ay us,

635
00:30:36,880 --> 00:30:39,840
Speaker 13: maybe a Lulu could be really seen as the high end.

636
00:30:40,200 --> 00:30:44,120
Speaker 13: But it's going to be an interesting, more kind of

637
00:30:44,800 --> 00:30:48,680
Speaker 13: typical IPO in terms of consumer facing company that doesn't

638
00:30:48,680 --> 00:30:51,760
Speaker 13: have these ambitious kind of pitch in terms of AI

639
00:30:51,960 --> 00:30:53,840
Speaker 13: or massive hockey stick growth.

640
00:30:53,880 --> 00:30:58,240
Speaker 2: But do they have to pull back their pricing ambition

641
00:30:58,360 --> 00:31:01,600
Speaker 2: the same as we've seen with ARM and others. I mean,

642
00:31:02,760 --> 00:31:04,840
Speaker 2: are the is this a down round for everybody?

643
00:31:05,400 --> 00:31:08,720
Speaker 13: No, because this was bought by el Caddatan Private Equity

644
00:31:08,840 --> 00:31:12,880
Speaker 13: House back by Luxury Group LVMH for essentially four point

645
00:31:12,880 --> 00:31:15,920
Speaker 13: three billion US dollars. So this is actually kind of

646
00:31:15,960 --> 00:31:18,959
Speaker 13: on the growthier side, which at least in terms of

647
00:31:19,000 --> 00:31:21,480
Speaker 13: the ARM deal where SoftBank bought the MAT which right

648
00:31:21,480 --> 00:31:23,720
Speaker 13: now would be implied about it's seventy percent return, they're

649
00:31:23,720 --> 00:31:26,800
Speaker 13: actually seeing marks up to the positive as opposed to

650
00:31:27,080 --> 00:31:29,640
Speaker 13: Instacart Claviow the two IPOs that are set to price

651
00:31:29,760 --> 00:31:30,480
Speaker 13: sometime next week.

652
00:31:30,480 --> 00:31:31,800
Speaker 1: Who are taking White the haircut?

653
00:31:31,880 --> 00:31:32,320
Speaker 3: Kunjohn?

654
00:31:32,360 --> 00:31:34,000
Speaker 2: It is a down round for ARM in a way,

655
00:31:34,080 --> 00:31:38,880
Speaker 2: right because SoftBank just bought a twenty five percent stake

656
00:31:39,200 --> 00:31:41,240
Speaker 2: from itself for much more.

657
00:31:41,480 --> 00:31:44,040
Speaker 7: Yes, exactly, yes, So so if you take that as

658
00:31:44,040 --> 00:31:45,280
Speaker 7: a benchmarket is a down row.

659
00:31:45,400 --> 00:31:46,840
Speaker 3: Yeah, but why what?

660
00:31:46,840 --> 00:31:47,040
Speaker 7: What?

661
00:31:47,040 --> 00:31:49,000
Speaker 3: What happened there? What's the deal?

662
00:31:50,280 --> 00:31:54,160
Speaker 7: I mean they didn't publicly say a lot, but it

663
00:31:54,320 --> 00:31:58,040
Speaker 7: seemed to what being for from it is two things

664
00:31:58,080 --> 00:32:01,840
Speaker 7: that ARM doesn't think, that Softman thinks that ARM is

665
00:32:01,880 --> 00:32:03,760
Speaker 7: just getting started. So there will be a lot of

666
00:32:03,800 --> 00:32:06,320
Speaker 7: more opportunities for them to come on with follow on

667
00:32:06,400 --> 00:32:09,760
Speaker 7: offerings at much higher valuation, especially when that data center

668
00:32:09,840 --> 00:32:12,040
Speaker 7: part becomes a larger portion of the revenues.

669
00:32:12,680 --> 00:32:17,360
Speaker 1: All right, thirty seconds, Kunjohn, what's what's your feeling about AI?

670
00:32:17,440 --> 00:32:19,120
Speaker 1: Are you drinking kool aid like everybody else?

671
00:32:21,360 --> 00:32:27,160
Speaker 7: Fundamentally, it definitely seems to be here to stay. I

672
00:32:27,240 --> 00:32:29,720
Speaker 7: don't know, it's too soon to talk about valuation, right,

673
00:32:29,880 --> 00:32:33,400
Speaker 7: So it's barely been seven months we started talking about it,

674
00:32:33,520 --> 00:32:38,480
Speaker 7: But fundamentally we definitely see real activity and sustainable demand

675
00:32:38,560 --> 00:32:39,000
Speaker 7: going here.

676
00:32:39,120 --> 00:32:41,680
Speaker 1: All right, Kunjohn, next time you're in New York, you

677
00:32:41,760 --> 00:32:43,360
Speaker 1: have to stop by here and see Matt and I

678
00:32:43,520 --> 00:32:44,920
Speaker 1: in the studio. We haven't met yet, so.

679
00:32:44,840 --> 00:32:46,840
Speaker 2: You got But since you're out there in San Francisco,

680
00:32:46,920 --> 00:32:47,920
Speaker 2: are you on Peer three?

681
00:32:47,960 --> 00:32:48,560
Speaker 1: Is that where you are?

682
00:32:48,640 --> 00:32:48,920
Speaker 7: Yes?

683
00:32:48,960 --> 00:32:50,960
Speaker 3: There, Yes, you got to go over.

684
00:32:51,240 --> 00:32:54,520
Speaker 2: There's a market down the street that has a Slocum

685
00:32:55,200 --> 00:32:58,120
Speaker 2: and Humphrey or Humphrey and Slocum ice cream place.

686
00:32:58,400 --> 00:32:59,120
Speaker 1: Yep, right, Daniel.

687
00:32:59,200 --> 00:33:01,520
Speaker 2: They have a flavor called Secret Breakfast, and I'm gonna

688
00:33:01,520 --> 00:33:04,840
Speaker 2: go ahead and recommend that Secret Breakfast all right, so.

689
00:33:04,800 --> 00:33:07,680
Speaker 1: We got that go and tattage grill as well for

690
00:33:08,080 --> 00:33:11,400
Speaker 1: the eats. Kun John Sabanik tech analysts for BIA in

691
00:33:11,440 --> 00:33:15,560
Speaker 1: San Francisco, Belly Lipshots covering the markets for Bloomberg News.

692
00:33:15,600 --> 00:33:18,680
Speaker 8: You're listening to the tape cans are live program Bloomberg

693
00:33:18,800 --> 00:33:22,400
Speaker 8: Markets weekdays at ten am Eastern on Bloomberg Radio, the

694
00:33:22,440 --> 00:33:24,400
Speaker 8: tune in app, Bloomberg dot Com, and.

695
00:33:24,360 --> 00:33:25,680
Speaker 11: The Bloomberg Business app.

696
00:33:25,720 --> 00:33:28,520
Speaker 8: You can also listen live on Amazon Alexa from our

697
00:33:28,560 --> 00:33:32,960
Speaker 8: flagship New York station, Just say Alexa play Bloomberg eleven thirty.

698
00:33:34,560 --> 00:33:36,239
Speaker 1: Well, a lot of folks I think probably came up

699
00:33:36,520 --> 00:33:39,080
Speaker 1: in the business kind of thinking about that sixty forty

700
00:33:39,120 --> 00:33:42,360
Speaker 1: portfolios being kind of ideal stocks and bonds. But a

701
00:33:42,400 --> 00:33:44,560
Speaker 1: lot of folks, you know, over the last decade plus

702
00:33:44,600 --> 00:33:46,239
Speaker 1: I have been saying, hey, you can juice returns if

703
00:33:46,280 --> 00:33:49,600
Speaker 1: you go with alternatives. Put that into your mix somewhere,

704
00:33:49,920 --> 00:33:51,840
Speaker 1: you know, maybe ten percent or something like that. But

705
00:33:51,880 --> 00:33:55,280
Speaker 1: one of the risks of alternatives is the less lower

706
00:33:55,320 --> 00:33:58,880
Speaker 1: liquidity and sometimes you know illiquidity. Our next guest tries

707
00:33:58,920 --> 00:34:01,320
Speaker 1: to address that issue. Ryan King. He's the see of

708
00:34:01,480 --> 00:34:05,920
Speaker 1: Lotus Markets. He joined us here in our Bloomberg Interactive

709
00:34:05,880 --> 00:34:08,320
Speaker 1: Broker studio. Brian, welcome, talk to us about Lotus markets.

710
00:34:08,360 --> 00:34:10,760
Speaker 1: What do you guys do there, What are you trying?

711
00:34:10,800 --> 00:34:12,520
Speaker 1: What market demand are you trying to meet?

712
00:34:13,160 --> 00:34:15,799
Speaker 6: Yeah, thank you so much for having me. We are

713
00:34:16,360 --> 00:34:20,000
Speaker 6: essentially a stock exchange for alternative investments. We're actually registered

714
00:34:20,040 --> 00:34:23,000
Speaker 6: as an ATS, which functions a lot like a stock exchange.

715
00:34:23,680 --> 00:34:27,480
Speaker 6: But to the point that you just made, most alternative

716
00:34:27,480 --> 00:34:31,880
Speaker 6: investments are largely ill liquid and we're seeing this massive

717
00:34:31,960 --> 00:34:37,080
Speaker 6: shift of where most alternative investments have historically been invested

718
00:34:37,520 --> 00:34:41,880
Speaker 6: in by major institutions, and the pendulum is is moving

719
00:34:41,920 --> 00:34:45,040
Speaker 6: more to individual investors, and you know, the closer you

720
00:34:45,040 --> 00:34:48,680
Speaker 6: get to a true retail investor, the more important liquidity becomes.

721
00:34:48,719 --> 00:34:51,360
Speaker 6: And so that's really what we're doing, is we're allowing

722
00:34:51,400 --> 00:34:53,480
Speaker 6: the opportunity to match buyers and sellers of these I

723
00:34:53,560 --> 00:34:54,360
Speaker 6: liquid assets.

724
00:34:55,040 --> 00:34:58,560
Speaker 1: All right, so how is it done before? Like, how

725
00:34:58,600 --> 00:35:00,719
Speaker 1: did you could I just not get quity in the past,

726
00:35:00,800 --> 00:35:02,840
Speaker 1: or how does how does this work? Give me an example,

727
00:35:02,880 --> 00:35:05,960
Speaker 1: maybe a trade or the types of trades you guys facilitate.

728
00:35:06,280 --> 00:35:10,160
Speaker 6: Yeah, so we started our market in the registered fund business.

729
00:35:10,200 --> 00:35:13,520
Speaker 6: So they're registered filing ks and ques, but they aren't

730
00:35:14,239 --> 00:35:17,520
Speaker 6: listed on an exchange. In many cases, these funds were

731
00:35:17,520 --> 00:35:20,799
Speaker 6: completely illiquid, so you couldn't have a liquidity event until

732
00:35:20,840 --> 00:35:24,080
Speaker 6: the fund decided that there was one. In some cases,

733
00:35:24,120 --> 00:35:26,839
Speaker 6: maybe you could pledge your shares into a redemption queue

734
00:35:26,840 --> 00:35:30,480
Speaker 6: and then they would buy back your shares. But for

735
00:35:30,560 --> 00:35:33,600
Speaker 6: the most part, though, if you needed you had like

736
00:35:33,640 --> 00:35:36,800
Speaker 6: an urgent need for liquidity, you would call up a broker.

737
00:35:36,880 --> 00:35:38,640
Speaker 6: The broker would try to find the other side of

738
00:35:38,640 --> 00:35:41,440
Speaker 6: the trade. They'd give you a dramatically deep discount of

739
00:35:41,920 --> 00:35:44,120
Speaker 6: you know, fifty sixty percent and you would pay a

740
00:35:44,160 --> 00:35:45,600
Speaker 6: ten percent commission to do that.

741
00:35:45,640 --> 00:35:46,560
Speaker 3: So you get ripped off.

742
00:35:47,040 --> 00:35:49,000
Speaker 6: Yes, your face is literally ripped off.

743
00:35:48,840 --> 00:35:51,080
Speaker 2: And you I mean, and that's part of what drove

744
00:35:51,120 --> 00:35:54,040
Speaker 2: you to create this, right because what happened? Did you

745
00:35:54,080 --> 00:35:55,960
Speaker 2: get ripped off before or you didn't want to get

746
00:35:56,040 --> 00:35:58,480
Speaker 2: ripped off when you needed liquidity or what happened?

747
00:35:58,880 --> 00:36:02,040
Speaker 6: Yeah, so i'd do. You have some very specific experiences

748
00:36:02,080 --> 00:36:04,680
Speaker 6: in my past, not me directly, but family members and

749
00:36:04,760 --> 00:36:08,560
Speaker 6: others that that were kind of locked up into alternative

750
00:36:08,600 --> 00:36:15,040
Speaker 6: investments and so for them situations specifically during the financial crisis,

751
00:36:15,360 --> 00:36:17,080
Speaker 6: they were looking to get out, they wanted to be

752
00:36:17,160 --> 00:36:20,040
Speaker 6: able to get in front of it, and ultimately some

753
00:36:20,080 --> 00:36:23,200
Speaker 6: of these funds went completely belly up. And so you know,

754
00:36:23,320 --> 00:36:25,560
Speaker 6: you you you live with those moments and you see

755
00:36:25,560 --> 00:36:28,040
Speaker 6: that type of a situation occur and you want to

756
00:36:28,040 --> 00:36:29,520
Speaker 6: be able to say there there's got to be a

757
00:36:29,520 --> 00:36:30,399
Speaker 6: solution for it.

758
00:36:30,680 --> 00:36:34,040
Speaker 1: Okay, So if you, if you, you know, facilitate a

759
00:36:34,080 --> 00:36:37,200
Speaker 1: trade on your exchange, how do you get paid? What's

760
00:36:37,239 --> 00:36:38,400
Speaker 1: kind of your business model?

761
00:36:38,719 --> 00:36:41,520
Speaker 6: So we right now, it doesn't the sponsor doesn't get

762
00:36:41,560 --> 00:36:44,560
Speaker 6: charged anything, the buyer doesn't get charged anything. But we

763
00:36:44,640 --> 00:36:47,120
Speaker 6: do charge the seller of three percent commission, so it's

764
00:36:47,120 --> 00:36:50,799
Speaker 6: not nothing, but these are a liquid so that's that's

765
00:36:50,840 --> 00:36:52,879
Speaker 6: the charge that we typically takes two point nine.

766
00:36:52,800 --> 00:36:54,120
Speaker 1: And how do you find the buyer? How do you

767
00:36:54,120 --> 00:36:56,239
Speaker 1: find the other side? You just you have relationships with

768
00:36:56,280 --> 00:36:59,320
Speaker 1: people that buy and sell these types of investments.

769
00:36:59,400 --> 00:37:01,960
Speaker 6: Yeah, there's a lot of natural buyers of alternative investments.

770
00:37:02,000 --> 00:37:05,200
Speaker 6: You can think of a lot of institutions like insurance companies,

771
00:37:05,280 --> 00:37:09,640
Speaker 6: hedge funds, size for you, so it can range, so

772
00:37:10,120 --> 00:37:11,839
Speaker 6: it can be all the way. We're an ATS. It's

773
00:37:11,840 --> 00:37:16,239
Speaker 6: actually sorry. ATS is an alternative trading system, so if

774
00:37:16,239 --> 00:37:18,280
Speaker 6: you think so. My background, I was part of BATS

775
00:37:18,320 --> 00:37:21,360
Speaker 6: as a startup company. BATS was an ATS before it

776
00:37:21,400 --> 00:37:25,240
Speaker 6: became in exchange. It functions a lot like a stock exchange,

777
00:37:25,239 --> 00:37:27,520
Speaker 6: but isn't regulated in the same way. It's a little

778
00:37:27,520 --> 00:37:27,960
Speaker 6: bit different.

779
00:37:27,960 --> 00:37:30,040
Speaker 2: And this is how you have a lot of experience

780
00:37:30,120 --> 00:37:35,200
Speaker 2: at BATS at n y C. And this is how

781
00:37:35,360 --> 00:37:38,080
Speaker 2: you not only know how to find buyers and sellers,

782
00:37:38,120 --> 00:37:40,320
Speaker 2: but how to put the infrastructure together, because that, I

783
00:37:40,719 --> 00:37:42,920
Speaker 2: have to guess is also an important part of it.

784
00:37:43,080 --> 00:37:45,759
Speaker 6: That's exactly right. So we're a technology company at our core,

785
00:37:46,440 --> 00:37:49,160
Speaker 6: so you build the technology, you build the framework. You know,

786
00:37:49,160 --> 00:37:52,680
Speaker 6: we're highly regulated both by FENRA and the SEC, and

787
00:37:52,719 --> 00:37:55,200
Speaker 6: so there is a lot that goes into it. But yeah,

788
00:37:55,239 --> 00:37:58,200
Speaker 6: we're you know, my background comes in helping to match

789
00:37:58,200 --> 00:38:00,839
Speaker 6: buyers and sellers and finding those in institutions. And then

790
00:38:01,000 --> 00:38:03,400
Speaker 6: we also have a lot of rias and family offices

791
00:38:03,440 --> 00:38:06,080
Speaker 6: that say, hey, we've already invested some of our clients

792
00:38:06,120 --> 00:38:08,040
Speaker 6: money in this and so we would be in many

793
00:38:08,080 --> 00:38:10,040
Speaker 6: cases wanting to buy more of it, and if you

794
00:38:10,040 --> 00:38:11,839
Speaker 6: could buy it at a discount, that's even better.

795
00:38:11,920 --> 00:38:15,160
Speaker 2: So I mean, I've read you're the third biggest ats

796
00:38:15,560 --> 00:38:17,719
Speaker 2: in the country and you've got some big players on

797
00:38:17,760 --> 00:38:19,840
Speaker 2: your platform.

798
00:38:20,360 --> 00:38:22,439
Speaker 3: Let's just look into list Blackstone.

799
00:38:21,880 --> 00:38:26,920
Speaker 2: Starward, Deutsche Bank Funds. How big is the platform if

800
00:38:26,920 --> 00:38:28,320
Speaker 2: you put all those assets together.

801
00:38:28,920 --> 00:38:31,320
Speaker 6: Yeah, so I think if you added up all the

802
00:38:31,719 --> 00:38:34,120
Speaker 6: assets that are on the platform, and'd be around two

803
00:38:34,239 --> 00:38:37,680
Speaker 6: hundred billion that we're trading today. But we made an

804
00:38:37,719 --> 00:38:40,200
Speaker 6: announcement a week ago, so you know, I talked about

805
00:38:40,280 --> 00:38:43,400
Speaker 6: registered funds is where we started. But we just launched

806
00:38:43,480 --> 00:38:48,400
Speaker 6: our first private real estate fun group, Walton Global is

807
00:38:48,440 --> 00:38:51,839
Speaker 6: now listed on our marketplace. We had four different you know,

808
00:38:52,000 --> 00:38:55,480
Speaker 6: large transactions in that but that was our first foray

809
00:38:55,520 --> 00:38:58,880
Speaker 6: into private real estate. Private real estate is a fourteen

810
00:38:58,960 --> 00:39:02,080
Speaker 6: trillion dollar marketplace, so it's a it's a it's a

811
00:39:02,120 --> 00:39:03,600
Speaker 6: wide addressable market.

812
00:39:03,640 --> 00:39:05,920
Speaker 2: But what do you mean by private real estate. It's

813
00:39:05,960 --> 00:39:10,040
Speaker 2: not like the Sweeney the Sweeney ranch on the Jersey Shore.

814
00:39:10,080 --> 00:39:11,040
Speaker 2: I mean, what are you talking about.

815
00:39:11,280 --> 00:39:13,000
Speaker 6: Yeah, So a lot of times you have sponsors that

816
00:39:13,040 --> 00:39:18,279
Speaker 6: put together private real estate deals. They raise capital from,

817
00:39:18,560 --> 00:39:21,239
Speaker 6: you know, large investors. Typically you have to be accredited

818
00:39:21,280 --> 00:39:25,120
Speaker 6: to invest in those types of investments, and so they

819
00:39:25,120 --> 00:39:28,200
Speaker 6: put those deals together, and typically you have to wait

820
00:39:28,239 --> 00:39:30,279
Speaker 6: for the sponsor to have a liquidity event before you

821
00:39:30,280 --> 00:39:32,279
Speaker 6: yourself can find one. So we're now starting to work

822
00:39:32,280 --> 00:39:35,560
Speaker 6: with sponsors to help them find liquidity for their shareholders

823
00:39:35,600 --> 00:39:36,040
Speaker 6: that wanted early.

824
00:39:36,160 --> 00:39:37,879
Speaker 1: Right, if i were a shareholder in one of those

825
00:39:37,920 --> 00:39:41,799
Speaker 1: things and I'm looking around Manhattan, I need to get

826
00:39:41,800 --> 00:39:44,040
Speaker 1: out of this thing because I think when XYZ Building

827
00:39:44,040 --> 00:39:45,799
Speaker 1: on Third Avenue trades, it's going to trade a fifty

828
00:39:45,840 --> 00:39:49,040
Speaker 1: cents on the dollar. So you're getting into a marketplace

829
00:39:49,080 --> 00:39:52,160
Speaker 1: that is going to have incredible volatility, I would say

830
00:39:52,160 --> 00:39:53,600
Speaker 1: over the next five to ten years.

831
00:39:53,960 --> 00:39:56,839
Speaker 6: So I mean, yeah, I do agree that there are

832
00:39:57,040 --> 00:40:00,680
Speaker 6: some segments of commercial real estate that are going to

833
00:40:00,719 --> 00:40:04,040
Speaker 6: be very volatile, and there's they're definitely if you're looking

834
00:40:04,080 --> 00:40:08,280
Speaker 6: at New York, you're looking at It's San Francisco, those places.

835
00:40:08,280 --> 00:40:11,799
Speaker 6: When you're looking at commercial real estate, office buildings, they're

836
00:40:11,960 --> 00:40:15,040
Speaker 6: they're really in a tough spot. I think the biggest

837
00:40:15,080 --> 00:40:17,160
Speaker 6: thing that they have right now is the financing right

838
00:40:17,840 --> 00:40:21,719
Speaker 6: the sponsors themselves trying to find the ability to refinance

839
00:40:21,760 --> 00:40:24,200
Speaker 6: those deals. It's going to be really challenging.

840
00:40:23,880 --> 00:40:25,160
Speaker 3: But not a lot of volatility.

841
00:40:25,480 --> 00:40:29,000
Speaker 2: If you're looking in like the Columbus, Ohio metropolitan area

842
00:40:29,040 --> 00:40:32,520
Speaker 2: of course, looking at student housing, looking at medical offices,

843
00:40:32,600 --> 00:40:35,319
Speaker 2: looking at movie theaters, multi families Okay.

844
00:40:35,640 --> 00:40:38,560
Speaker 6: Yeah, multi family is having like some real success though

845
00:40:38,600 --> 00:40:39,160
Speaker 6: too as well.

846
00:40:39,280 --> 00:40:41,400
Speaker 1: Yeah, exactly who do you compete against?

847
00:40:42,000 --> 00:40:45,600
Speaker 6: There aren't any There aren't many direct competitors. You know,

848
00:40:45,880 --> 00:40:51,200
Speaker 6: Nasdaq has a private funds division that they are they're successful,

849
00:40:51,239 --> 00:40:53,480
Speaker 6: but we don't compete head to head right now. The

850
00:40:53,480 --> 00:40:55,839
Speaker 6: things that they do we don't, and most of the

851
00:40:55,840 --> 00:41:00,000
Speaker 6: things that we do they don't. So there's so there's

852
00:40:59,840 --> 00:41:02,520
Speaker 6: it's just now people starting to move into this space.

853
00:41:02,560 --> 00:41:04,560
Speaker 6: So it's a great opportunity right to be kind of

854
00:41:04,560 --> 00:41:05,440
Speaker 6: the first to do it.

855
00:41:05,680 --> 00:41:08,719
Speaker 1: Now, do you put up capital to facilitate facilitate these

856
00:41:08,760 --> 00:41:10,880
Speaker 1: trades or you just simply a broker.

857
00:41:10,960 --> 00:41:14,960
Speaker 6: We're agentcy, we're agency. Yeah, so we're not buyers, we're

858
00:41:15,040 --> 00:41:16,120
Speaker 6: sellers of the asset.

859
00:41:16,120 --> 00:41:18,520
Speaker 1: We're matching and get an average transaction sise for you

860
00:41:18,640 --> 00:41:19,600
Speaker 1: on average.

861
00:41:19,760 --> 00:41:23,520
Speaker 6: Let's say one hundred to five hundred thousand dollars. It's

862
00:41:23,560 --> 00:41:27,600
Speaker 6: probably the average. And the more private it gets, the

863
00:41:27,680 --> 00:41:29,920
Speaker 6: larger the size of the transaction.

864
00:41:30,200 --> 00:41:32,800
Speaker 1: And how many trades do you do a day or

865
00:41:32,840 --> 00:41:33,480
Speaker 1: something like that.

866
00:41:34,239 --> 00:41:36,640
Speaker 6: It varies because it's an ill liquid market. It varies.

867
00:41:36,920 --> 00:41:39,200
Speaker 6: You could have a couple a day or you could have,

868
00:41:39,560 --> 00:41:40,680
Speaker 6: you know, twenty a day.

869
00:41:41,239 --> 00:41:43,080
Speaker 1: But it's how long does it take you to kind

870
00:41:43,080 --> 00:41:45,640
Speaker 1: of execute a trade? I mean, it's not like me

871
00:41:45,760 --> 00:41:48,040
Speaker 1: back at Paineweber pushing my button for Alliance and I'm

872
00:41:48,080 --> 00:41:50,080
Speaker 1: dumping my four and one thousand shares of you know,

873
00:41:50,200 --> 00:41:51,560
Speaker 1: XYZ stock to Alliance.

874
00:41:52,040 --> 00:41:52,279
Speaker 11: Yeah.

875
00:41:52,320 --> 00:41:55,799
Speaker 6: So it's actually we do We've set our marketplace up

876
00:41:55,840 --> 00:41:57,239
Speaker 6: in a very traditional way.

877
00:41:57,400 --> 00:41:59,960
Speaker 1: All Right, thanks so much for you're listening to the

878
00:42:00,600 --> 00:42:01,720
Speaker 1: Cat's Are Live program.

879
00:42:01,760 --> 00:42:05,720
Speaker 8: Bloomberg Markets weekdays at ten am Eastern on Bloomberg Radio,

880
00:42:05,880 --> 00:42:08,040
Speaker 8: the tune in app, Bloomberg dot Com.

881
00:42:07,800 --> 00:42:09,239
Speaker 11: And the Bloomberg Business app.

882
00:42:09,280 --> 00:42:12,080
Speaker 8: You can also listen live on Amazon Alexa from our

883
00:42:12,120 --> 00:42:17,160
Speaker 8: flagship New York station, Just say Alexa play Bloomberg eleven thirty.

884
00:42:18,120 --> 00:42:20,359
Speaker 1: We're talking a lot about AI and for a good reason.

885
00:42:20,360 --> 00:42:22,399
Speaker 1: We've got as we have just heard from Elon Musk.

886
00:42:22,440 --> 00:42:25,440
Speaker 1: Elon Musk and a lot of other tech leaders CEO

887
00:42:25,560 --> 00:42:28,440
Speaker 1: types down in Washington, d C. Meeting with a select

888
00:42:28,440 --> 00:42:32,360
Speaker 1: group of senators talking about AI. Kind of an education process,

889
00:42:32,440 --> 00:42:36,280
Speaker 1: if you will. So you know, AI in the overnight

890
00:42:36,440 --> 00:42:40,000
Speaker 1: has become the front and center for global Wall Street

891
00:42:40,040 --> 00:42:42,760
Speaker 1: and global regulators as well, and we want to continue

892
00:42:42,760 --> 00:42:45,880
Speaker 1: that conversation today with Ashley Still, Senior vice president and

893
00:42:45,960 --> 00:42:50,680
Speaker 1: general manager for Creative Cloud and document Cloud at Adobe. Ashley,

894
00:42:50,680 --> 00:42:53,120
Speaker 1: thanks so much for joining us here. Again, a lot

895
00:42:53,160 --> 00:42:56,759
Speaker 1: of attention on AI now today down to Washington, d C.

896
00:42:56,920 --> 00:42:59,839
Speaker 1: Some of the regulators trying and some of the politicians

897
00:42:59,840 --> 00:43:01,520
Speaker 1: and are trying to get a little bit educated by

898
00:43:01,520 --> 00:43:04,640
Speaker 1: some of the tech leaders. How do you folks at

899
00:43:04,680 --> 00:43:08,360
Speaker 1: Adobe approach AI in your business.

900
00:43:09,800 --> 00:43:12,040
Speaker 14: Well, first, Paul, thank you so much for having me.

901
00:43:12,280 --> 00:43:13,680
Speaker 14: It's great to be with you today.

902
00:43:14,800 --> 00:43:15,440
Speaker 3: And as you.

903
00:43:15,400 --> 00:43:21,680
Speaker 14: Said, AI just has huge power to enable many things.

904
00:43:21,960 --> 00:43:25,520
Speaker 14: At Adobe, what we're really focused on is how AI

905
00:43:25,680 --> 00:43:30,760
Speaker 14: can accelerate creativity. We believe every human is creative, everybody

906
00:43:30,760 --> 00:43:36,400
Speaker 14: has a story to tell, and we're using AI to

907
00:43:36,560 --> 00:43:41,120
Speaker 14: enable anyone to create content and to share their story.

908
00:43:41,520 --> 00:43:43,840
Speaker 14: The way that we do that is through Adobe Firefly,

909
00:43:44,000 --> 00:43:48,319
Speaker 14: which is our family of creative, generative AI models, and

910
00:43:48,360 --> 00:43:52,040
Speaker 14: we are announced today that Firefly is now generally available

911
00:43:52,360 --> 00:43:56,440
Speaker 14: after very successful beta. It's available both as a standalone

912
00:43:56,480 --> 00:43:59,480
Speaker 14: web application, so anyone that has access to a browser

913
00:44:00,040 --> 00:44:03,440
Speaker 14: and can type into simple text prompt can create content.

914
00:44:03,920 --> 00:44:07,279
Speaker 14: But it's also now built into the fabric of our

915
00:44:07,360 --> 00:44:11,680
Speaker 14: incredibly powerful creative tools like Photoshop and Illustrator, so that

916
00:44:12,160 --> 00:44:18,040
Speaker 14: professional creators and designers can use AI to add expressiveness

917
00:44:18,160 --> 00:44:21,279
Speaker 14: and bring their ideas to life in even richer ways.

918
00:44:21,719 --> 00:44:25,800
Speaker 1: And actually, one of the concerns, early concerns of AI

919
00:44:25,840 --> 00:44:28,040
Speaker 1: and its applications, we're seeing a play out in Hollywood

920
00:44:28,080 --> 00:44:31,640
Speaker 1: a little bit. A lot of the writers are concerned

921
00:44:31,719 --> 00:44:33,520
Speaker 1: about AI. They're concerned about a number of things, but

922
00:44:33,560 --> 00:44:36,280
Speaker 1: one of them is AI. How do you think about

923
00:44:36,320 --> 00:44:41,640
Speaker 1: just how the protections around the content that can be

924
00:44:41,760 --> 00:44:44,720
Speaker 1: created through AI, how do you expect that to evolve?

925
00:44:44,760 --> 00:44:47,759
Speaker 1: Does Adobe have a point of view on that?

926
00:44:49,280 --> 00:44:49,880
Speaker 3: Absolutely?

927
00:44:50,400 --> 00:44:54,720
Speaker 14: So, first, we've been really thoughtful about how we even

928
00:44:55,160 --> 00:44:58,440
Speaker 14: train our models, and they're different approaches out there with

929
00:44:58,520 --> 00:45:02,120
Speaker 14: different AI services. The approach that we take is we

930
00:45:02,280 --> 00:45:05,560
Speaker 14: only train our models on content that we have licensed

931
00:45:05,640 --> 00:45:09,960
Speaker 14: to as well as content that has an open license

932
00:45:10,120 --> 00:45:13,560
Speaker 14: on the Internet. And this is different than going out

933
00:45:13,600 --> 00:45:17,080
Speaker 14: and kind of scraping the Internet, which has a lot

934
00:45:17,120 --> 00:45:22,799
Speaker 14: of implications for artists rights and their protections.

935
00:45:22,920 --> 00:45:23,120
Speaker 7: Right.

936
00:45:23,160 --> 00:45:27,640
Speaker 14: So, obviously Adobe, we are very passionate about our role

937
00:45:28,000 --> 00:45:32,200
Speaker 14: in advancing creativity and being a part of the creative community,

938
00:45:32,719 --> 00:45:36,280
Speaker 14: and it really starts with how we're going about training

939
00:45:36,920 --> 00:45:41,920
Speaker 14: our models. It doesn't stop there. We build those protections

940
00:45:41,960 --> 00:45:47,160
Speaker 14: into our services, right So, for example, artist's style is

941
00:45:47,160 --> 00:45:51,240
Speaker 14: something that is very concerning right now to the creative community,

942
00:45:51,280 --> 00:45:56,960
Speaker 14: and you reference Hollywood. People spend you know, a decade

943
00:45:57,080 --> 00:46:01,040
Speaker 14: or more developing their style, whether they're in, whether they're

944
00:46:01,040 --> 00:46:05,520
Speaker 14: an advertising, whatever it might be, and there's real concern

945
00:46:05,640 --> 00:46:10,040
Speaker 14: about AI's ability to transfer that style instantaneously.

946
00:46:11,000 --> 00:46:11,920
Speaker 3: We build that.

947
00:46:11,880 --> 00:46:16,560
Speaker 14: Protection into our products and we also are supporting regulation

948
00:46:17,400 --> 00:46:19,200
Speaker 14: to protect artist style as well.

949
00:46:19,600 --> 00:46:22,960
Speaker 1: So what at Adobe and Firefly give us us some

950
00:46:23,040 --> 00:46:27,080
Speaker 1: examples of kind of how your technology is used, maybe

951
00:46:27,080 --> 00:46:28,879
Speaker 1: who uses and what and what do they use it for?

952
00:46:30,640 --> 00:46:35,360
Speaker 14: So we are building Firefly across our family of applications

953
00:46:35,560 --> 00:46:40,800
Speaker 14: and our mission, Adobe's Creativity for all. We have applications

954
00:46:40,920 --> 00:46:45,520
Speaker 14: that anyone can use. Again I referenced Firefly dot Adobe

955
00:46:45,560 --> 00:46:48,799
Speaker 14: dot com. That's a new web application that is a

956
00:46:48,840 --> 00:46:53,480
Speaker 14: playground for anyone that wants to explore creative expression using AI.

957
00:46:54,120 --> 00:46:56,840
Speaker 14: All you need is a browser and the ability to

958
00:46:57,520 --> 00:47:00,319
Speaker 14: write simple text prompts and you can create images, you

959
00:47:00,360 --> 00:47:04,839
Speaker 14: can create text effects and really anyone can use that.

960
00:47:05,800 --> 00:47:10,120
Speaker 14: But we also have Adobe Express, which is an all

961
00:47:10,200 --> 00:47:15,800
Speaker 14: in one creativity application where you can create text image

962
00:47:15,840 --> 00:47:21,240
Speaker 14: as well as text effects, create posters, flyers, social media posts. Again,

963
00:47:21,320 --> 00:47:26,799
Speaker 14: so people that want to generate content easily can use

964
00:47:26,840 --> 00:47:30,840
Speaker 14: Adobe Express. And as I mentioned before, we are really

965
00:47:30,920 --> 00:47:36,200
Speaker 14: deeply building AI into our professional workflows across Photoshop, Illustrator

966
00:47:36,719 --> 00:47:40,600
Speaker 14: and more applications will be coming soon. What this does

967
00:47:40,719 --> 00:47:45,120
Speaker 14: for our creative professional community is increase the value of

968
00:47:45,160 --> 00:47:48,759
Speaker 14: our applications that enables them to idate faster and be

969
00:47:48,920 --> 00:47:49,680
Speaker 14: more productive.

970
00:47:50,360 --> 00:47:53,360
Speaker 1: And who's a typical user of your products? Is it?

971
00:47:53,440 --> 00:47:55,799
Speaker 1: I mean, like, how much of your customers are they

972
00:47:56,320 --> 00:47:59,200
Speaker 1: individuals versus corporate that kind of thing. Who's a typical

973
00:47:59,280 --> 00:48:00,880
Speaker 1: user and who do you think I think that'll evolve?

974
00:48:01,840 --> 00:48:08,480
Speaker 14: It ranges right, we have we're in We're very fortunate

975
00:48:08,600 --> 00:48:12,920
Speaker 14: that we have an incredibly broad customer base, whether it's students,

976
00:48:13,360 --> 00:48:18,320
Speaker 14: our products are used in K twelve schools, of course,

977
00:48:18,520 --> 00:48:22,839
Speaker 14: creative professionals and creative professionals they often work for themselves

978
00:48:23,040 --> 00:48:26,160
Speaker 14: or they can work for the largest companies in the world.

979
00:48:27,239 --> 00:48:31,120
Speaker 14: And what we're really seeing across the board is whether

980
00:48:31,160 --> 00:48:34,920
Speaker 14: you're a consumer or whether you're a professional, the demand

981
00:48:35,120 --> 00:48:40,000
Speaker 14: to create content to tell your story is continuing to

982
00:48:40,120 --> 00:48:44,799
Speaker 14: explode businesses. Every business is a digital business, and they

983
00:48:44,840 --> 00:48:50,000
Speaker 14: need content to power how they're engaging with customers across channels,

984
00:48:50,040 --> 00:48:54,040
Speaker 14: whether it's TikTok or YouTube or their own website. And

985
00:48:54,080 --> 00:48:56,759
Speaker 14: certainly from a consumer standpoint, I mean, I just look

986
00:48:56,800 --> 00:48:59,640
Speaker 14: at my own kids. They create content all the time,

987
00:48:59,800 --> 00:49:03,320
Speaker 14: and it's to make people laugh, it's to express an idea,

988
00:49:03,760 --> 00:49:06,239
Speaker 14: whether it's with friends or at school. And so we

989
00:49:06,280 --> 00:49:10,720
Speaker 14: serve all of those needs. And what's incredibly exciting about

990
00:49:10,760 --> 00:49:15,080
Speaker 14: Firefly and AI, it's enabling us to serve all of

991
00:49:15,120 --> 00:49:18,480
Speaker 14: those needs in unique and new ways, and so it

992
00:49:18,600 --> 00:49:21,960
Speaker 14: really expands the tent of who can create.

993
00:49:22,880 --> 00:49:25,560
Speaker 1: So what's the next step do you think, what's the

994
00:49:25,600 --> 00:49:28,080
Speaker 1: next new thing? You guys are working on an Adobe

995
00:49:28,120 --> 00:49:28,959
Speaker 1: as it relates to AI.

996
00:49:30,680 --> 00:49:35,320
Speaker 14: Absolutely, so we continue to advance our core models and

997
00:49:36,280 --> 00:49:39,520
Speaker 14: you know, it's still early days right in the era

998
00:49:39,600 --> 00:49:43,759
Speaker 14: of generative AI, and so the quality, the breadth, and

999
00:49:43,840 --> 00:49:47,960
Speaker 14: the depth of those models continues to evolve, and that

1000
00:49:48,080 --> 00:49:51,680
Speaker 14: just gives us the ability to bring rich capabilities across

1001
00:49:51,719 --> 00:49:56,080
Speaker 14: all of our applications. We also are working on new

1002
00:49:56,120 --> 00:50:01,200
Speaker 14: media right, so we're we're doing great search in video

1003
00:50:01,480 --> 00:50:04,920
Speaker 14: and three D and how again, we bring the power

1004
00:50:04,960 --> 00:50:08,120
Speaker 14: of AI to all of the types of media that

1005
00:50:08,440 --> 00:50:13,560
Speaker 14: people create through our applications. So stay tuned for more

1006
00:50:13,600 --> 00:50:14,359
Speaker 14: on those all.

1007
00:50:14,360 --> 00:50:16,080
Speaker 1: Right, Ashley, thank you so much for joining us. Really

1008
00:50:16,080 --> 00:50:20,120
Speaker 1: appreciate it. Fascinating stuff ever changing, that's for sure, Ashley

1009
00:50:20,160 --> 00:50:23,480
Speaker 1: Still she's a senior vice president and general manager at

1010
00:50:23,640 --> 00:50:26,960
Speaker 1: the creative cloud and document cloud business over there at

1011
00:50:27,040 --> 00:50:30,319
Speaker 1: our good friends at Adobe. So interesting stuff there and

1012
00:50:30,360 --> 00:50:33,000
Speaker 1: again AI kind of hitting pretty much every part of

1013
00:50:33,040 --> 00:50:34,680
Speaker 1: the economy, it seems like when you listen to some

1014
00:50:34,719 --> 00:50:37,560
Speaker 1: of the use cases, but certainly when it comes to

1015
00:50:37,640 --> 00:50:41,879
Speaker 1: content creation, that's where the opportunities are and that's where

1016
00:50:41,920 --> 00:50:44,200
Speaker 1: for a lot of people the potential risk are. And

1017
00:50:44,239 --> 00:50:47,840
Speaker 1: we're seeing that again play out with the Hollywood writers.

1018
00:50:48,040 --> 00:50:49,719
Speaker 1: One of the things we're looking at is maybe some

1019
00:50:49,800 --> 00:50:55,080
Speaker 1: protections from AI impacting their business and getting credit for

1020
00:50:55,280 --> 00:50:59,640
Speaker 1: what they actually create. So keep an eye on that.

1021
00:51:00,080 --> 00:51:03,120
Speaker 2: Thanks for listening to the Bloomberg Markets podcast. You can

1022
00:51:03,160 --> 00:51:06,920
Speaker 2: subscribe and listen to interviews at Apple Podcasts or whatever

1023
00:51:07,040 --> 00:51:10,760
Speaker 2: podcast platform you prefer. I'm Matt Miller. I'm on Twitter

1024
00:51:10,960 --> 00:51:12,879
Speaker 2: at Matt Miller nineteen seventy three.

1025
00:51:13,320 --> 00:51:15,680
Speaker 1: And I'm Faul Sweeney. I'm on Twitter at pt Sweeney.

1026
00:51:15,840 --> 00:51:18,480
Speaker 1: Before the podcast, you can always catch us worldwide at

1027
00:51:18,520 --> 00:51:20,280
Speaker 1: Bloomberg Radio.