WEBVTT - Meta's Revenue Beats, Boosts Buybacks

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<v Speaker 1>This is Bloomberg Business Week inside from the reporters and

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<v Speaker 1>editors who bring you America's most trusted business magazine, plus

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<v Speaker 1>global business, finance and tech news. The Bloomberg Business Week

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<v Speaker 1>Podcast with Carol Manser and Tim Stinebec from Bloomberg Radio.

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<v Speaker 1>All right, everybody you're listening in watching Bloomberg Business Week,

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<v Speaker 1>what are you thinking. I'm thinking that Romaine is like

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<v Speaker 1>ready to go at it about meta earnings. I keep

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<v Speaker 1>staying with climate change. We're all going to be living

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<v Speaker 1>in the metaverse because you're not gonna be able to

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<v Speaker 1>go outside. But having said that, who knows? I know

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<v Speaker 1>someone who knows everything? Does she? Yeah, we've got Alex.

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<v Speaker 1>We're very pleased with her with us. In fact, she

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<v Speaker 1>was in here before these earnings even came out. She's

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<v Speaker 1>furiously typing away getting to the bottom of what's happening

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<v Speaker 1>with shares of Facebook. It is formally, of course Facebook

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<v Speaker 1>now it's metal platforms just out with earnings. I want

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<v Speaker 1>to get back to uh these right now. And we

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<v Speaker 1>got Bloomberg Technology Report Alex Brinka here in our Bloomberg

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<v Speaker 1>Interactor Broker's studio to do it. Okay, So Alex, I

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<v Speaker 1>know you weren't paying attention to what Carol remained. Katie

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<v Speaker 1>and I were all yelling about because you're actually doing important,

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<v Speaker 1>real work. But now that you've had a good six

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<v Speaker 1>minutes to give I was we were what are you

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<v Speaker 1>seeing what sticks out here? I'll tell you what jumping

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<v Speaker 1>out to me in six minutes that we're also sharing

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<v Speaker 1>on the blog on the terminal revenue beat for the

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<v Speaker 1>fourth quarter um they also seem to have some pretty

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<v Speaker 1>strong revenue estimates for the first quarter. First quarter revenue

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<v Speaker 1>estimates of billion to twenty and a half billion straddle

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<v Speaker 1>what analysts were estimating. So that's exciting. I bring that

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<v Speaker 1>add dollars. That is the majority of their revenue is

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<v Speaker 1>AD dollars, so close to upwards of that is AD dollars.

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<v Speaker 1>So that to me is saying that what we heard

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<v Speaker 1>from Snap yesterday that the malaise in the AD market

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<v Speaker 1>is leveling off, at least to the level of folks expect.

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<v Speaker 1>That seems to kind of play out that narrative. Who

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<v Speaker 1>knows what we'll hear on the call. We're looking for

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<v Speaker 1>some more clues on where the AD market is going,

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<v Speaker 1>but that top line number is really jumping out at me.

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<v Speaker 1>Another number that the back. The buy back was my

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<v Speaker 1>number two forty billion dollars in share buy backs. Look,

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<v Speaker 1>last year two was the worst year on record for

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<v Speaker 1>Meta They fell what six um on the year, So

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<v Speaker 1>we've had a little bit of recovering the stock. Definitely

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<v Speaker 1>a jump of the stock this um this afternoon up.

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<v Speaker 1>But clearly the company thinks that the shares are undervalued now.

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<v Speaker 1>Investors sold off last year basically because they're concerned about

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<v Speaker 1>where this company is going in terms of strategy. You

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<v Speaker 1>have the ad business, like we said, makes up a

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<v Speaker 1>majority of revenue, but a lot of the focus and

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<v Speaker 1>the renaming of the company has been on this kind

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<v Speaker 1>of far flung virtual reality future that the company calls

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<v Speaker 1>the Metaverse. Now, when it comes to earnings, the Metaverse

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<v Speaker 1>sits in a business unit called Reality Labs. Reality Labs

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<v Speaker 1>is a big loser. They lost four point to eight

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<v Speaker 1>billion dollars in the fourth quarter, more than analysts estimated.

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<v Speaker 1>So when it comes to the hard questions that will

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<v Speaker 1>be on costs, and Reality Labs seem to be the

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<v Speaker 1>big cost suck with a big question mark these days.

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<v Speaker 1>But Mark Zuckerbert coming out in a statement saying that

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<v Speaker 1>three the management theme is quote year of efficiency focused

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<v Speaker 1>on becoming a stronger and more nimble organization. Is it

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<v Speaker 1>a nod to the thousands of people who were laid

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<v Speaker 1>off just a few weeks ago of the workforce laid

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<v Speaker 1>off in the end of last year. So yes, it

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<v Speaker 1>needs to be. And it seems like he's projecting that

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<v Speaker 1>it's not just a change in the cost structure, but

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<v Speaker 1>it's a change in how the company is thinking going forward.

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<v Speaker 1>Remember this is a company that's only seen growth up

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<v Speaker 1>into the right right. We we've seen now sales declines

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<v Speaker 1>for the first time a few quarters in the row

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<v Speaker 1>ever for Meta or when it was called Facebook. So

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<v Speaker 1>it seems like they're trying to kind of um at

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<v Speaker 1>least project to the street a reason to give patients,

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<v Speaker 1>which is what he was asking for last quarter. And

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<v Speaker 1>he wasn't afforded by the market when the stock fell

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<v Speaker 1>on the last earnings day, So it seems like he

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<v Speaker 1>is needing to change his tune a little bit more

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<v Speaker 1>from trust us. We know what the future is going

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<v Speaker 1>to look like too. Oh look, we're actually going to

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<v Speaker 1>be efficient now and kind of drive towards running a

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<v Speaker 1>more kind of priority focus business. Is that first quote

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<v Speaker 1>revenue outlook was a miss or disappointing, would we be

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<v Speaker 1>having a much different conversation right now. Absolutely, that's what

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<v Speaker 1>we saw hopping with Snap yesterday. So if that first

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<v Speaker 1>quarter was a miss, I think you can continue to

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<v Speaker 1>have kind of questions around. Look, if you want to

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<v Speaker 1>build a decades of virtual reality future, you've got to

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<v Speaker 1>fund it somehow. Don't forget to forget about the bread

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<v Speaker 1>and butter with the caveat that. This is an impossible

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<v Speaker 1>question to answer. I'm gonna ask you anyway, is the

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<v Speaker 1>sixteen point six percent rise in Facebook stock right now

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<v Speaker 1>about the share buy back or about the revenue number?

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<v Speaker 1>I would guess it's a mix of both. Um, if

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<v Speaker 1>this comes back down to earth, I will say it's

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<v Speaker 1>the share buy back. If it continues to say stay high,

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<v Speaker 1>I would say it's the revenue number and not to

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<v Speaker 1>throw it to tomorrow. But we get Alphabet earnings tomorrow

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<v Speaker 1>as well. Alphabet and Meta are the two kind of

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<v Speaker 1>monsters in the digital ad space. They've really traded all

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<v Speaker 1>off as there's been kind of economic uncertainty and marketers

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<v Speaker 1>pulling back on spending. So if that stays up and

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<v Speaker 1>Alphabet hits, then I think, Um, this is more about

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<v Speaker 1>about the first not necessarily scientific, but just doing our

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<v Speaker 1>g I P O aftermarket you know function on the terminal.

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<v Speaker 1>It looks like as soon as the revenue number hit,

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<v Speaker 1>the stock shot up. I'm not saying that it didn't

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<v Speaker 1>go a tiny bit higher on the buy back news,

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<v Speaker 1>but as soon as that revenue number and I would

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<v Speaker 1>agree that if they're able to fund it right, people

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<v Speaker 1>are going to invest in and say, okay, go ahead,

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<v Speaker 1>because you're still making a ton of money. So Facebook,

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<v Speaker 1>Facebook is an advertising company now that that sells ads

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<v Speaker 1>in Instagram and in Facebook always it has, but you know,

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<v Speaker 1>over the last year, Mark Zuckerberger said, we are a

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<v Speaker 1>metaverse company. We changed the ticker name. We're investing in

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<v Speaker 1>Reality Labs, which, as you noted, lost billions of dollars

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<v Speaker 1>in the fourth quarter. Uh, aleo remain two point Oh well,

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<v Speaker 1>I'm Facebook stock up seventeen point seven percent right now, Alex. Okay,

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<v Speaker 1>So a lot of so many questions for you. Um,

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<v Speaker 1>if we think about this from the perspective of Snap,

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<v Speaker 1>what they get right and Snap get wrong? Meta got

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<v Speaker 1>right not taking a big hit to kind of change

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<v Speaker 1>its ad product in the first start of the year.

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<v Speaker 1>Meta's ad ad ads on Facebook and Instagram are really

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<v Speaker 1>focused on direct response, so that's where you are selling

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<v Speaker 1>products immediately. That's the slice of the digital ad world

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<v Speaker 1>where marketers are still spending because it is seeing their

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<v Speaker 1>dollars go to work immediately. Snap had some very snap

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<v Speaker 1>focus changes yesterday where they said, we're actually rolling out

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<v Speaker 1>a lot of technology updates to our ad product and

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<v Speaker 1>we're going to take a big hit in the first quarter.

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<v Speaker 1>That being said, Meta's the giant right aside techically, so

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<v Speaker 1>Meta carries a lot more weight. They have a much

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<v Speaker 1>larger chunk um. They had to do woppolie them and

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<v Speaker 1>and Google, which they lost um last year, but they're

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<v Speaker 1>still kind of the strongest ones out there. So I

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<v Speaker 1>think again some leveling off in terms of some of

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<v Speaker 1>this malaise in the ad market seems to be positive

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<v Speaker 1>news and that's reading through and at least the revenue

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<v Speaker 1>projection to you. I think on the blog we're saying,

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<v Speaker 1>I think that's the first time that they've hit two

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<v Speaker 1>billion in daily active users. I mean, the behemoth cool stuff.

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<v Speaker 1>Alex Brinka, thank you so much. She covers a lot

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<v Speaker 1>of the technology world for us here at Bloomberg joining

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<v Speaker 1>us in studio. This is Bloomberg business Week Inside from

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<v Speaker 1>the reporters and editors who bring you America's most trusted

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<v Speaker 1>business magazine, plus global business, finance and tech news. The

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<v Speaker 1>Bloomberg Business Week Podcast with Carol Messer and Tim stinebec

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<v Speaker 1>from Bloomberg Radio. All Right, so maybe you've heard of it,

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<v Speaker 1>the nonprofit Core Response started by actor Sean Penn. That's

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<v Speaker 1>really stepped up when it comes to helping people in

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<v Speaker 1>Haiti that after the earthquake, for saving American lives during

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<v Speaker 1>the pandemic and doing so much more so, Tim sounds

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<v Speaker 1>like a lot of good deeds. I'm really coming into

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<v Speaker 1>help up, clean up messy and difficult situations, right and well.

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<v Speaker 1>And yet, as a Bloomberg Business Week investigation has found out,

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<v Speaker 1>what was going on in the inside of the nonprofit,

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<v Speaker 1>according to employees, was another mess as well. It's an

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<v Speaker 1>exclusive story. It's in the upcoming new issue with Bloomberg

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<v Speaker 1>Business Week. It's out on news stands tomorrow. It's already

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<v Speaker 1>online at Bloomberg dot com, slash business Week and of

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<v Speaker 1>course on the Bloomberg terminal. We've got with Bloomberg News

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<v Speaker 1>Wealth Team reporter Sophie Alexander along with the editor of

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<v Speaker 1>Bloomberg Business with Joe Webber, both in our Bloomberg Interactive

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<v Speaker 1>Broker Studio. Joel, I, I I know this charity because they

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<v Speaker 1>did so much work in the in Haiti and so

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<v Speaker 1>much work during the pandemic. What happened, well, when when

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<v Speaker 1>they were when core U was getting started UH in

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<v Speaker 1>places like Haiti really was disaster relief response, right, and

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<v Speaker 1>it was actually fairly modest um not you know, dozens

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<v Speaker 1>of employees, not you know, millions upon millions of dollars.

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<v Speaker 1>But COVID really changed that. And what the Sean penn

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<v Speaker 1>Uh nonprofit did was really doubled down in Los Angeles

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<v Speaker 1>and it became effectively like a de facto healthcare operation.

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<v Speaker 1>But with that growth and this massive influx of money

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<v Speaker 1>that it saw there also created some chaos. And think

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<v Speaker 1>that chaos led to um so if he's reporting? Um so, so,

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<v Speaker 1>if you what did you hear and where did that

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<v Speaker 1>lead you? Yeah? So, like you said, they grew incredibly

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<v Speaker 1>quickly during the pandemic. They were just about a dozen

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<v Speaker 1>employees beforehand, and then they grew to thousands over the

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<v Speaker 1>matter over a matter of months and less than seven

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<v Speaker 1>million dollars in revenue in two million dollars, so that's

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<v Speaker 1>enormous growth. And so I started reaching out to employees

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<v Speaker 1>after I heard about this, and basically they were saying, yeah,

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<v Speaker 1>it was a total mess inside. A lot of employees

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<v Speaker 1>said there were a lot of financial issues, a lot

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<v Speaker 1>of employees told me about sexual harassment, and so some

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<v Speaker 1>of the testing sites, including the one at Dodger Stadium,

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<v Speaker 1>which was the one of the largest, if not the

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<v Speaker 1>largest testing site in the US during the pandemic. What

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<v Speaker 1>I found so remarkable about this was the way head

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<v Speaker 1>count exploded. You point out in your piece that head

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<v Speaker 1>count went to three thousand plus people and some context

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<v Speaker 1>there as you write, Sophie, it's larger in the bill

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<v Speaker 1>and Melinda Gates Foundation at one point, that's right. They're

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<v Speaker 1>an operating nonprofits, so you know, like they had all

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<v Speaker 1>these people on the ground, and they started out just

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<v Speaker 1>by getting volunteers to respond to the pandemic, but quickly

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<v Speaker 1>started turning them into full time employees. And a lot

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<v Speaker 1>of these were young people working their first jobs. Um.

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<v Speaker 1>But then later on they brought also very experienced nonprofit

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<v Speaker 1>employees for from other organizations who knew what how this

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<v Speaker 1>was supposed to go? Okay, So the story starts um

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<v Speaker 1>with the fundraiser and to just give a sense of

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<v Speaker 1>the star power in the setting and where you know

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<v Speaker 1>money money gets raised for a nonprofit like core response

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<v Speaker 1>like take us there, take us to Miami. Sure, so

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<v Speaker 1>nonprofit like this, you know it's a celebrity nonprofit. They

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<v Speaker 1>spend a good amount of time and money on fundraisers.

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<v Speaker 1>And these fundraisers are home to Seam Penn and a

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<v Speaker 1>lot of his rich and famous friends like Leonardo DiCaprio.

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<v Speaker 1>The one um in the story at art Bosel in

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<v Speaker 1>Miami was hosted by the pop singer Anita Delphine or No,

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<v Speaker 1>the heir to the world's largest fortune, was also there,

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<v Speaker 1>and everyone was told that this was going to raise

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<v Speaker 1>money for Latin America COVID response. Um, that's what was

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<v Speaker 1>on the invitations that were shared with Business Week, That's

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<v Speaker 1>what was on the marketing materials. And I spoke with

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<v Speaker 1>employees who said it took a lot of nagging of

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<v Speaker 1>the CEO to hey, why hasn't this money reached Brazil yet?

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<v Speaker 1>Because that was basically the only place they were doing

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<v Speaker 1>such work at the time. And why hasn't gone to

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<v Speaker 1>Brazil yet? Why hasn't gone to Brazil yet? And the

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<v Speaker 1>CEO was essentially like, you know, it doesn't matter if

0:11:36.360 --> 0:11:38.880
<v Speaker 1>we actually spend it in Brazil. Um. That's what these

0:11:38.880 --> 0:11:42.600
<v Speaker 1>employees were telling me. And so according to an email

0:11:42.600 --> 0:11:45.160
<v Speaker 1>that we saw, it ultimately took almost six months to

0:11:45.240 --> 0:11:47.600
<v Speaker 1>make it to Brazil and that's ultimately where all the

0:11:47.600 --> 0:11:50.240
<v Speaker 1>money was allocated. But it's kind of a confusing mess

0:11:50.280 --> 0:11:52.800
<v Speaker 1>in between. So fisis about like an organization, like when

0:11:52.800 --> 0:11:54.839
<v Speaker 1>you talk about the money, how it started out, and

0:11:54.880 --> 0:11:57.600
<v Speaker 1>then you know, you're talking about raising two million dollars.

0:11:57.800 --> 0:11:59.880
<v Speaker 1>Is it a case of an organization and nonprofit that

0:12:00.000 --> 0:12:02.240
<v Speaker 1>all of a sudden just ran really quickly and they

0:12:02.280 --> 0:12:05.160
<v Speaker 1>didn't have the people, the infrastructure, the systems in place.

0:12:05.280 --> 0:12:08.440
<v Speaker 1>Or is this about an organization that maybe internally had

0:12:08.480 --> 0:12:13.160
<v Speaker 1>some really bad eggs. Well, yeah, that that Their response

0:12:13.240 --> 0:12:15.800
<v Speaker 1>to our reporting is basically, you know, they responded really

0:12:15.840 --> 0:12:18.480
<v Speaker 1>quickly to the pandemic. It was a huge challenge and

0:12:19.080 --> 0:12:22.320
<v Speaker 1>an unprecedented one, and they rose their hands and said

0:12:22.360 --> 0:12:24.400
<v Speaker 1>we're going to do this, and they did it well,

0:12:24.400 --> 0:12:26.559
<v Speaker 1>to be fair, and and they did it well. They

0:12:26.600 --> 0:12:31.559
<v Speaker 1>did you know, respond to the to the pandemic. Well, um,

0:12:31.600 --> 0:12:34.079
<v Speaker 1>and that's what they're saying. But you know, I'm talking

0:12:34.080 --> 0:12:36.360
<v Speaker 1>to people who are saying, we're almost three years on

0:12:36.480 --> 0:12:40.400
<v Speaker 1>now and it's still internally a problem, financially a problem.

0:12:40.520 --> 0:12:43.120
<v Speaker 1>And they're saying that a lot of this runs up

0:12:43.160 --> 0:12:46.440
<v Speaker 1>to leadership basically not wanting to do much and so

0:12:46.520 --> 0:12:48.560
<v Speaker 1>walk us through some of the financial problems that some

0:12:48.640 --> 0:12:51.360
<v Speaker 1>of the employees flagged to you and your reporting. Sure,

0:12:51.400 --> 0:12:53.960
<v Speaker 1>so it's a lot of you know, kind of mundane

0:12:54.080 --> 0:12:57.880
<v Speaker 1>stuff that's kind of technical, but like payroll stuff. For example,

0:12:58.080 --> 0:13:00.480
<v Speaker 1>I spoke with an employee who was getting paid months

0:13:00.520 --> 0:13:03.280
<v Speaker 1>after they had quit and they had raised the issue

0:13:03.360 --> 0:13:05.760
<v Speaker 1>with the nonprofit and didn't hear anything. I was going

0:13:05.800 --> 0:13:12.360
<v Speaker 1>to say, beats the alternative, Okay, thank you, you know, no,

0:13:12.520 --> 0:13:18.040
<v Speaker 1>but it sounds like like oversight financially coming in, dollars

0:13:18.040 --> 0:13:20.720
<v Speaker 1>coming in and then somebody who's not even employed anymore

0:13:20.760 --> 0:13:24.880
<v Speaker 1>is still getting paid. It's federal dollars to taxpair dollars,

0:13:25.000 --> 0:13:29.360
<v Speaker 1>right exactly. Um, what about like, who do you hearing

0:13:29.440 --> 0:13:33.840
<v Speaker 1>from beyond the employees, anybody from senior management? They did

0:13:34.000 --> 0:13:38.360
<v Speaker 1>sean calling up, you know, they declined to make Sean

0:13:38.679 --> 0:13:41.880
<v Speaker 1>available for an interview, the CEO and the CEO available

0:13:41.880 --> 0:13:43.840
<v Speaker 1>for an interview. Well, Carol makes a good point. What

0:13:44.040 --> 0:13:47.360
<v Speaker 1>is Sean Penn's involvement. So he's the chair of the board,

0:13:47.559 --> 0:13:50.960
<v Speaker 1>which basically means he's responsible for the thing. If there

0:13:51.000 --> 0:13:54.240
<v Speaker 1>are problems, he's responsible for making sure that leadership is

0:13:54.280 --> 0:13:57.320
<v Speaker 1>doing their job and doing it well and responsibly. UM.

0:13:57.360 --> 0:13:59.280
<v Speaker 1>But on a day to day what people telling me,

0:13:59.679 --> 0:14:01.839
<v Speaker 1>he's not really involved all that much except for kind

0:14:01.840 --> 0:14:04.600
<v Speaker 1>of as a figurehead. And who is Who's who's running point?

0:14:04.920 --> 0:14:08.000
<v Speaker 1>It's the CEO and Lee and and tell us more

0:14:08.040 --> 0:14:11.760
<v Speaker 1>about her and Sean and how they came to basically

0:14:11.840 --> 0:14:14.880
<v Speaker 1>co lead this organization. Sure, so they met in Haiti

0:14:15.320 --> 0:14:19.040
<v Speaker 1>in the wake of the two earthquake. UM. She has

0:14:19.360 --> 0:14:22.600
<v Speaker 1>been had been working in nonprofits in Haiti specifically for

0:14:22.640 --> 0:14:25.480
<v Speaker 1>a while. UM. She kind of bounced around until ultimately

0:14:25.920 --> 0:14:30.320
<v Speaker 1>she was brought into Core made CEO in and people

0:14:30.360 --> 0:14:33.360
<v Speaker 1>say that Sehn and her close, you know, like they

0:14:33.480 --> 0:14:36.200
<v Speaker 1>told us that they meet monthly. UM. People said that

0:14:36.280 --> 0:14:38.240
<v Speaker 1>it seems like a lot of what Anne does is

0:14:38.280 --> 0:14:40.200
<v Speaker 1>to try to make Sean look good and to try

0:14:40.240 --> 0:14:43.960
<v Speaker 1>to keep Sean happy. UM. And a lot of people

0:14:44.040 --> 0:14:48.520
<v Speaker 1>said that, you know, like it ultimately runs up to her.

0:14:48.640 --> 0:14:50.280
<v Speaker 1>Everything runs up to her. She's the one who makes

0:14:50.280 --> 0:14:53.000
<v Speaker 1>their decisions. And if there's an issue and it's ultimately

0:14:53.040 --> 0:14:55.920
<v Speaker 1>run up to her, she's the one who's saying it's

0:14:56.240 --> 0:15:00.640
<v Speaker 1>it's not our problem. Okay. So obviously corn At this

0:15:01.080 --> 0:15:05.320
<v Speaker 1>response to covid um as those test sites and vaccine

0:15:05.360 --> 0:15:10.280
<v Speaker 1>sites have wound down, curious what's happened since uh they

0:15:10.320 --> 0:15:14.480
<v Speaker 1>made those that that initiative. Now they're in Ukraine. UM.

0:15:14.520 --> 0:15:18.680
<v Speaker 1>Sean Penn was with Zelenski the day Russia invaded UM

0:15:18.760 --> 0:15:22.240
<v Speaker 1>and so that really opened up an opportunity for CORE

0:15:22.360 --> 0:15:24.200
<v Speaker 1>at a time when it was kind of hard for

0:15:24.280 --> 0:15:28.720
<v Speaker 1>other international nonprofits to get involved. UM. They're also responding

0:15:28.760 --> 0:15:33.960
<v Speaker 1>to domestic hurricanes, so in Puerto Rico, in Florida, UM.

0:15:34.200 --> 0:15:37.120
<v Speaker 1>And what I've been hearing from not just employees but

0:15:37.200 --> 0:15:39.240
<v Speaker 1>also some partners who are seeing Corps work on the

0:15:39.240 --> 0:15:42.440
<v Speaker 1>ground is that, you know, it seems like they're showing

0:15:42.520 --> 0:15:45.000
<v Speaker 1>up to these disasters, they're taking a bunch of photos,

0:15:45.080 --> 0:15:47.400
<v Speaker 1>they're fundraising a bunch of money, and then they're paying

0:15:47.480 --> 0:15:50.600
<v Speaker 1>less attention to how that money gets spent to actually

0:15:50.600 --> 0:15:52.560
<v Speaker 1>respond to the disasters. Yeah, one of the things that

0:15:52.560 --> 0:15:55.360
<v Speaker 1>sticks with me is like they're known in this world

0:15:55.440 --> 0:15:58.920
<v Speaker 1>for showing up with cameras before almost anything else, right,

0:15:59.040 --> 0:16:02.360
<v Speaker 1>like be seeing in the dollars keep flowing that way,

0:16:02.400 --> 0:16:05.440
<v Speaker 1>but maybe maybe there's not that much impact after the fact.

0:16:05.560 --> 0:16:07.960
<v Speaker 1>That's what felt like one common denominator. They made sure

0:16:08.040 --> 0:16:10.600
<v Speaker 1>that there was good visuals, even if they weren't necessarily

0:16:10.720 --> 0:16:14.600
<v Speaker 1>very involved UM seconds and net net takeaway of kind

0:16:14.600 --> 0:16:19.240
<v Speaker 1>of whirreness is where it stands. It's complicated. I know,

0:16:19.320 --> 0:16:22.280
<v Speaker 1>it's never well one thing that I think it boils

0:16:22.280 --> 0:16:25.360
<v Speaker 1>down to this California All this rolls up to a G.

0:16:25.520 --> 0:16:27.360
<v Speaker 1>So if AG is gonna look at anything, you know,

0:16:27.440 --> 0:16:31.680
<v Speaker 1>they've we've clearly spoken enough current and former employees that

0:16:32.200 --> 0:16:33.800
<v Speaker 1>there's some stuff to look into here. Yeah, and I

0:16:33.800 --> 0:16:35.960
<v Speaker 1>would say definitely do a read through because the sexual

0:16:36.000 --> 0:16:39.440
<v Speaker 1>harassment concerns um which were also brought to the attention

0:16:39.440 --> 0:16:42.080
<v Speaker 1>at the top, that seemed to have been dismissed, at

0:16:42.120 --> 0:16:45.240
<v Speaker 1>least according to the employees accounts. Great story. Sophie Alexander Wealth,

0:16:45.280 --> 0:16:48.320
<v Speaker 1>team reporter at Bloomberg News here in our Interactive Broker studio,

0:16:48.640 --> 0:16:50.800
<v Speaker 1>the story and the upcoming new issue of Bloomberg Business Week,

0:16:50.840 --> 0:16:52.640
<v Speaker 1>or thanks to Joe Webber, the editor of Business Week.

0:16:52.680 --> 0:16:54.640
<v Speaker 1>You can also find it at Bloomberg dot com and

0:16:54.680 --> 0:16:58.440
<v Speaker 1>always on the Bloomberg terminal. You're listening to the Bloomberg

0:16:58.520 --> 0:17:01.840
<v Speaker 1>Business Week podcast. Catch us live week days from two

0:17:01.880 --> 0:17:05.399
<v Speaker 1>to five pm Easter on Bloomberg Radio, the Bloomberg Business

0:17:05.480 --> 0:17:08.240
<v Speaker 1>a band you do. You can also listen live to

0:17:08.280 --> 0:17:12.399
<v Speaker 1>our flagship New York station, Just Say Alexa, Play Bloomberg,

0:17:12.440 --> 0:17:17.760
<v Speaker 1>Elove and Dirty I focused on but just a few

0:17:17.760 --> 0:17:20.639
<v Speaker 1>weeks ago, we were focused on Microsoft, their interests and

0:17:20.640 --> 0:17:25.359
<v Speaker 1>then subsequent further investment in open aies chat GPT, which

0:17:25.440 --> 0:17:28.160
<v Speaker 1>is really kicked off, safe to say, Tim another round

0:17:28.160 --> 0:17:31.040
<v Speaker 1>of euphoria when it comes to all things artificial intelligence.

0:17:31.320 --> 0:17:33.320
<v Speaker 1>You add dot AI to the end of your name,

0:17:33.440 --> 0:17:35.080
<v Speaker 1>or you say that you're you know a company that's

0:17:35.119 --> 0:17:38.600
<v Speaker 1>working with AI or chat GPT like BuzzFeed, and you

0:17:38.640 --> 0:17:40.880
<v Speaker 1>see what investors do. It certainly set the investment world

0:17:40.920 --> 0:17:44.000
<v Speaker 1>scrambling to figure out who will benefit. Carol, our next guest,

0:17:44.000 --> 0:17:46.720
<v Speaker 1>has some thoughts on how chat GPT could change voice

0:17:46.800 --> 0:17:49.399
<v Speaker 1>first products and services. Very pleased to have with us.

0:17:49.520 --> 0:17:53.200
<v Speaker 1>Nitti the Donni CEO at the voice technology software company Rain,

0:17:53.440 --> 0:17:56.160
<v Speaker 1>joining us via zoom in New York City. If you're

0:17:56.160 --> 0:17:57.959
<v Speaker 1>good to have you with us this afternoon. How are you.

0:17:58.920 --> 0:18:01.160
<v Speaker 1>I'm great, Thank you so much. It's good to be here.

0:18:01.280 --> 0:18:03.320
<v Speaker 1>It's good to have you with us. Explain how RAIN works.

0:18:04.480 --> 0:18:08.919
<v Speaker 1>So Rain is a conversational AI company. We build voice

0:18:09.040 --> 0:18:12.560
<v Speaker 1>products for desk less workers. So if you think about

0:18:13.080 --> 0:18:17.560
<v Speaker 1>um Alexa or Google Assistant, we build professional grade versions

0:18:17.640 --> 0:18:21.480
<v Speaker 1>of those assistants specifically for an audience called deskless workers.

0:18:21.520 --> 0:18:23.800
<v Speaker 1>So these are workers who do not work, you know,

0:18:23.960 --> 0:18:27.080
<v Speaker 1>at a desk literally every day. They're moving around in

0:18:27.160 --> 0:18:32.960
<v Speaker 1>their jobs. So in industries like construction, automotive, healthcare, professionals

0:18:33.040 --> 0:18:35.240
<v Speaker 1>moving around in their jobs and they don't you know,

0:18:35.440 --> 0:18:39.040
<v Speaker 1>they need information and data at their fingertips. So we

0:18:39.320 --> 0:18:42.439
<v Speaker 1>are able to give that to them through voice, critical

0:18:42.520 --> 0:18:45.040
<v Speaker 1>information that they need at their fingertips. How fast is

0:18:45.080 --> 0:18:49.399
<v Speaker 1>your business growing? Um? You know, we just raised a

0:18:49.520 --> 0:18:52.119
<v Speaker 1>recent round of funding, so we have fifteen million total

0:18:52.240 --> 0:18:55.440
<v Speaker 1>and funding UM and you know, we're really excited for

0:18:55.520 --> 0:18:57.399
<v Speaker 1>what the next eighteen months is going to bring. But

0:18:57.680 --> 0:18:59.439
<v Speaker 1>but what does that mean in terms of how much

0:18:59.440 --> 0:19:01.280
<v Speaker 1>your business has grown. I don't know, give us the

0:19:01.359 --> 0:19:04.719
<v Speaker 1>last twelve months or so. Yeah, I mean we are

0:19:04.920 --> 0:19:08.399
<v Speaker 1>so right now. Our core product is called ortho UM.

0:19:08.640 --> 0:19:11.439
<v Speaker 1>It is a product for the automotive industry. So if

0:19:11.480 --> 0:19:15.239
<v Speaker 1>you think about technicians who are working on vehicles, UM,

0:19:15.440 --> 0:19:19.520
<v Speaker 1>we essentially provide them o EM data at their fingertips.

0:19:19.560 --> 0:19:22.520
<v Speaker 1>So instead of having to get out from under a vehicle,

0:19:22.640 --> 0:19:26.520
<v Speaker 1>go over to a computer, search a database for specifications

0:19:26.640 --> 0:19:29.520
<v Speaker 1>like fluid type and whatever, you know, whatever whatever else

0:19:29.560 --> 0:19:32.439
<v Speaker 1>they might need in the moment um, they can get

0:19:32.480 --> 0:19:34.560
<v Speaker 1>that at their fingertips. So right now, our products is

0:19:34.600 --> 0:19:37.640
<v Speaker 1>actually you know, we we are piloting in a number

0:19:37.680 --> 0:19:41.320
<v Speaker 1>of different shops UM and and pre revenue at the

0:19:41.359 --> 0:19:45.560
<v Speaker 1>moment is the technology that you have at RAIN? Is

0:19:45.640 --> 0:19:48.800
<v Speaker 1>it about the database? Is about where where things are

0:19:49.160 --> 0:19:51.520
<v Speaker 1>being found, where the answers are being found? Or is

0:19:51.560 --> 0:19:54.480
<v Speaker 1>it about the voice recognition technology? Or is it both?

0:19:55.480 --> 0:19:58.960
<v Speaker 1>It's both right UM. So it's essentially taking what is

0:19:59.600 --> 0:20:03.240
<v Speaker 1>you know, number of different databases that exist today O E.

0:20:03.440 --> 0:20:06.840
<v Speaker 1>M data that then feeds into another database called MOTOR

0:20:07.119 --> 0:20:10.680
<v Speaker 1>for example, where these these technicians typically get their information

0:20:11.280 --> 0:20:13.960
<v Speaker 1>and making that data conversational. And I know we're going

0:20:14.000 --> 0:20:16.440
<v Speaker 1>to talk about chat GPT, but there are just so

0:20:16.560 --> 0:20:21.200
<v Speaker 1>many parallels between that kind of conversational nature of the interaction. UM.

0:20:21.359 --> 0:20:24.359
<v Speaker 1>So you know it's it's it's UM taking this data,

0:20:24.440 --> 0:20:27.520
<v Speaker 1>making it conversational, but also making it domain specific. And

0:20:27.640 --> 0:20:30.119
<v Speaker 1>what I mean by that is a lot of the

0:20:30.359 --> 0:20:33.600
<v Speaker 1>AI that's out there today is generalist. So if you

0:20:33.680 --> 0:20:36.000
<v Speaker 1>think of Alexa, or you think of even chat GPT,

0:20:36.119 --> 0:20:39.000
<v Speaker 1>you're asking a question and you're getting a you know,

0:20:39.359 --> 0:20:42.639
<v Speaker 1>they want to serve the general public, so you're getting

0:20:42.800 --> 0:20:45.920
<v Speaker 1>a response back. UM. When you go really deep into

0:20:45.960 --> 0:20:49.240
<v Speaker 1>an industry like automotive or healthcare, as we are, you

0:20:50.200 --> 0:20:53.600
<v Speaker 1>really need to understand the nuances of that specific industry.

0:20:53.760 --> 0:20:57.480
<v Speaker 1>So I'll give you a little bit of an example here.

0:20:57.920 --> 0:21:00.840
<v Speaker 1>If you were to say we'll hut, which is a

0:21:01.080 --> 0:21:04.800
<v Speaker 1>very common term to a auto technicians who who's repairing

0:21:04.880 --> 0:21:07.760
<v Speaker 1>a car, to our assistant, they'll understand it, as we

0:21:07.840 --> 0:21:10.240
<v Speaker 1>all not. If you were to say that to a

0:21:10.359 --> 0:21:13.639
<v Speaker 1>general assistant like Alexa or Google assistant, they'll hear it

0:21:13.720 --> 0:21:16.720
<v Speaker 1>as will not, and that's because they they're not trained

0:21:16.920 --> 0:21:20.280
<v Speaker 1>to hear we'll not, right. So what we're doing is

0:21:20.400 --> 0:21:24.960
<v Speaker 1>really training our assistance for the way that professionals speak

0:21:25.000 --> 0:21:27.240
<v Speaker 1>to one another. What is the lingo that they use

0:21:27.320 --> 0:21:29.359
<v Speaker 1>every day and how do we make sure that they

0:21:29.480 --> 0:21:33.040
<v Speaker 1>understand that so that they're not changing the way they speak. So,

0:21:33.119 --> 0:21:35.240
<v Speaker 1>in other words, if if they want information or something,

0:21:35.280 --> 0:21:37.080
<v Speaker 1>they're speaking into something and then getting it on some

0:21:37.200 --> 0:21:39.320
<v Speaker 1>kind of devices, that kind of the back and forth

0:21:39.440 --> 0:21:42.600
<v Speaker 1>that ultimately is happening and will happen in your view

0:21:42.760 --> 0:21:46.920
<v Speaker 1>a lot more yes, so they're in in this case.

0:21:47.080 --> 0:21:49.320
<v Speaker 1>You know, the modality can be a tablet, it can

0:21:49.400 --> 0:21:52.439
<v Speaker 1>be a mobile phone, um, but you are essentially kind

0:21:52.480 --> 0:21:54.800
<v Speaker 1>of asking for information. And it can also be a

0:21:55.040 --> 0:21:57.399
<v Speaker 1>you know, a device that doesn't have a screen on it,

0:21:57.560 --> 0:22:01.600
<v Speaker 1>but a microphone, um, but you're essentially asking for information

0:22:01.800 --> 0:22:04.880
<v Speaker 1>in the moment and you're getting an answer back rather

0:22:04.960 --> 0:22:07.480
<v Speaker 1>than kind of getting us a number of links or

0:22:07.880 --> 0:22:10.800
<v Speaker 1>more databases that you have to look into. Again, a

0:22:10.920 --> 0:22:14.800
<v Speaker 1>lot of similarities to chat, GPT and that you know,

0:22:14.960 --> 0:22:18.240
<v Speaker 1>it's kind of taking away the layers of searching that

0:22:18.359 --> 0:22:20.480
<v Speaker 1>you would do on your own and giving you a

0:22:20.640 --> 0:22:23.440
<v Speaker 1>distilled answer. To be fair, like, I walk into the

0:22:23.480 --> 0:22:25.400
<v Speaker 1>house or walk out of the house, and I'm constantly

0:22:25.480 --> 0:22:27.440
<v Speaker 1>like or especially when I'm leaving. Hey, Google, you know

0:22:27.560 --> 0:22:29.760
<v Speaker 1>what's the temperature? Like I am, I'm definitely having a

0:22:29.840 --> 0:22:33.920
<v Speaker 1>conversation increasingly, not just inside my head, but increasingly with

0:22:34.000 --> 0:22:37.320
<v Speaker 1>the devices in my home. And and they're useful, whether

0:22:37.359 --> 0:22:40.000
<v Speaker 1>it's time, whether it's information. So you know, you take

0:22:40.040 --> 0:22:43.199
<v Speaker 1>that on a professional level, and I get where you're going. Um,

0:22:43.720 --> 0:22:46.520
<v Speaker 1>you did say you were pre revenue. Um, talk to

0:22:46.640 --> 0:22:49.239
<v Speaker 1>us though a little bit about chat GPT and all

0:22:49.280 --> 0:22:51.480
<v Speaker 1>the developments that have come out about it. How is

0:22:51.560 --> 0:22:53.960
<v Speaker 1>that impacting how you're thinking about your business and the

0:22:54.000 --> 0:22:58.520
<v Speaker 1>growth of it? Sure? Absolutely, I mean, listen, this, this

0:22:58.720 --> 0:23:03.120
<v Speaker 1>chatbot is kind of truly transformational, right. You've got, um, suddenly,

0:23:03.920 --> 0:23:06.360
<v Speaker 1>something that allows you to ask any question on any

0:23:06.400 --> 0:23:09.920
<v Speaker 1>subject or topic in natural language. So how you and

0:23:10.000 --> 0:23:11.520
<v Speaker 1>I would speak to one another and you're going to

0:23:11.560 --> 0:23:15.720
<v Speaker 1>get an answer back instantaneously in seconds, um, And so

0:23:16.400 --> 0:23:19.399
<v Speaker 1>you know you can ask for you know, the history

0:23:19.440 --> 0:23:21.240
<v Speaker 1>of pop music, and you're going to get an answer

0:23:21.320 --> 0:23:23.880
<v Speaker 1>back within moments, probably faster than you could have asked

0:23:23.960 --> 0:23:27.159
<v Speaker 1>that question. And that's exciting and interesting to us for

0:23:27.240 --> 0:23:31.199
<v Speaker 1>two reasons. Number one is it's not pulling that answer,

0:23:31.400 --> 0:23:33.840
<v Speaker 1>it's generating it, right, It's almost as though the AI

0:23:34.040 --> 0:23:37.720
<v Speaker 1>is reading a number of different information sourcing sources and

0:23:38.000 --> 0:23:40.480
<v Speaker 1>coming up with its own perspective. That's why it's called

0:23:40.560 --> 0:23:44.800
<v Speaker 1>generative AI. But the more interesting thing is that, um,

0:23:45.160 --> 0:23:48.160
<v Speaker 1>it's really doing that in a human and conversational way.

0:23:48.600 --> 0:23:51.200
<v Speaker 1>Uh So, Carol, if you know someone would ask you

0:23:51.280 --> 0:23:54.480
<v Speaker 1>a question and you didn't know that person, you would

0:23:54.520 --> 0:23:57.480
<v Speaker 1>not answer robotically or kind of in a singular way.

0:23:57.680 --> 0:24:00.960
<v Speaker 1>You would make inferences about the person based on the

0:24:01.040 --> 0:24:03.959
<v Speaker 1>context where you are, you know, how they're asking the question,

0:24:04.359 --> 0:24:07.840
<v Speaker 1>who they are, And that's what chat GPT is really doing.

0:24:08.000 --> 0:24:12.119
<v Speaker 1>They are understanding human language, both written and spoken, and

0:24:12.200 --> 0:24:14.520
<v Speaker 1>the nuances of it, and they're trying to mimic that.

0:24:14.720 --> 0:24:17.600
<v Speaker 1>So as that technology kind of moves forward, it's really

0:24:17.640 --> 0:24:20.960
<v Speaker 1>exciting for us, you know, in this conversational way industry,

0:24:21.080 --> 0:24:23.920
<v Speaker 1>to see more and more people engaging in that kind

0:24:23.960 --> 0:24:26.680
<v Speaker 1>of human AI way. Totally can see it. It just

0:24:26.800 --> 0:24:30.439
<v Speaker 1>makes a lot of sense. Um really nice, um Nthia

0:24:30.560 --> 0:24:32.600
<v Speaker 1>to check in with you really appreciate it. She is

0:24:32.640 --> 0:24:35.840
<v Speaker 1>the CEO at the voice technology software company Rain, joining

0:24:35.920 --> 0:24:38.800
<v Speaker 1>us be assum in New York City. Just quick back

0:24:38.880 --> 0:24:41.560
<v Speaker 1>to I guess safe to say, our top headline at

0:24:41.560 --> 0:24:44.439
<v Speaker 1>this hour. Certainly when it comes to earnings, Meta shares

0:24:44.760 --> 0:24:48.880
<v Speaker 1>off and running up eighteen after the first quarter revenue outlook,

0:24:49.359 --> 0:24:59.640
<v Speaker 1>definitely Rosie and a huge share by back authorization a journal. Yeah,

0:24:59.680 --> 0:25:01.480
<v Speaker 1>but you're let me drive? Oh no, no, no, no,

0:25:01.720 --> 0:25:11.240
<v Speaker 1>who's leaves? I want to drive. It's a good question.

0:25:15.000 --> 0:25:21.840
<v Speaker 1>This is the drive to the clothes on Bloomberg Radio. Alright,

0:25:21.880 --> 0:25:25.679
<v Speaker 1>a kill many times everything is awesome. You look at

0:25:25.720 --> 0:25:28.639
<v Speaker 1>the market reaction because we have a rally underways. You

0:25:28.720 --> 0:25:31.399
<v Speaker 1>just heard from Charlie Rocklom everybody. Of course, this is

0:25:31.400 --> 0:25:35.240
<v Speaker 1>Bloomberg Business Week on this FED Wednesday, first FED Meeting

0:25:35.320 --> 0:25:38.720
<v Speaker 1>of three cow Master Tim Stanivic live in our Bloomberg Interact,

0:25:38.760 --> 0:25:41.520
<v Speaker 1>a broker studio streaming on YouTube and Bloomberg Quicktake and

0:25:41.640 --> 0:25:44.879
<v Speaker 1>yields backing off, I mean markets, investors traders saying we

0:25:44.960 --> 0:25:47.120
<v Speaker 1>think the Feds just about done. Yeah. The big question

0:25:47.240 --> 0:25:49.879
<v Speaker 1>is just FED chair j Powell think what this is awesome?

0:25:49.920 --> 0:25:51.760
<v Speaker 1>What he's seeing in markets right now? Well, it was

0:25:51.840 --> 0:25:54.199
<v Speaker 1>interesting and I thought, you know, Jeff Rosenberger black Rock

0:25:54.320 --> 0:25:57.560
<v Speaker 1>making a comment and stressing uh in reaction with our

0:25:57.560 --> 0:25:59.760
<v Speaker 1>TV colleagues as the FED made its decision and we

0:25:59.800 --> 0:26:03.240
<v Speaker 1>went of the pressor certainty is not appropriate. Certainty is

0:26:03.280 --> 0:26:06.320
<v Speaker 1>not appropriate. That's what J Powell said. So you know,

0:26:06.560 --> 0:26:09.200
<v Speaker 1>there is no exact science in all of this. And

0:26:10.000 --> 0:26:12.680
<v Speaker 1>J Powell yes, saying we're making progress on inflation, but

0:26:12.840 --> 0:26:15.600
<v Speaker 1>also saying, hey, folks, we've got some more moves ahead

0:26:15.600 --> 0:26:17.760
<v Speaker 1>of us. Here's some other things that stuck out to me. Carroll,

0:26:17.960 --> 0:26:21.679
<v Speaker 1>further rate hikes will be appropriate. It's premature to declare victory.

0:26:22.240 --> 0:26:24.359
<v Speaker 1>We have a lot of work to do, and if

0:26:24.400 --> 0:26:26.560
<v Speaker 1>our outlook turns true, then I don't see us cutting

0:26:26.600 --> 0:26:29.000
<v Speaker 1>rates this year. I think that's really key. And yet

0:26:29.040 --> 0:26:31.680
<v Speaker 1>the markets saying differently. They just ignore all that. I

0:26:31.800 --> 0:26:34.440
<v Speaker 1>don't know, but the traders have been thinking differently. Despite

0:26:34.480 --> 0:26:37.080
<v Speaker 1>the dot plot that we got in the last updata projections,

0:26:37.119 --> 0:26:40.119
<v Speaker 1>which shows the Fed continuing to raise rates further along

0:26:40.520 --> 0:26:43.440
<v Speaker 1>and above five percent, traders have been saying differently. I

0:26:43.520 --> 0:26:45.720
<v Speaker 1>do think it was interesting that J. Powell said the

0:26:45.760 --> 0:26:47.840
<v Speaker 1>Fed is strongly committed to bring inflation to that two

0:26:47.920 --> 0:26:50.000
<v Speaker 1>percent call. He's not backing off of it. He thinks

0:26:50.080 --> 0:26:52.680
<v Speaker 1>it's doable, and yet we continue to get data that

0:26:52.760 --> 0:26:54.600
<v Speaker 1>point in the other direction. I point no further than

0:26:54.600 --> 0:26:57.280
<v Speaker 1>the Drolts data that we got earlier today one point

0:26:57.480 --> 0:27:00.359
<v Speaker 1>nine jobs available for every unemployed per in here in

0:27:00.359 --> 0:27:02.480
<v Speaker 1>the United States. Well, it's kind in the rock direction.

0:27:02.600 --> 0:27:05.000
<v Speaker 1>And he highlighted that as you know, we're still continuing

0:27:05.040 --> 0:27:08.520
<v Speaker 1>to see some strength, significant strength, if you will, in

0:27:08.640 --> 0:27:10.920
<v Speaker 1>terms of the labor market, and talking about you know,

0:27:11.080 --> 0:27:14.920
<v Speaker 1>reducing inflation likely to require blow trend growth um and

0:27:15.080 --> 0:27:18.240
<v Speaker 1>also talking about you know, the FED having to stay

0:27:18.280 --> 0:27:20.520
<v Speaker 1>the course, but also talking about let's see the base

0:27:20.600 --> 0:27:22.920
<v Speaker 1>cases return to two percent inflation without a big job

0:27:23.000 --> 0:27:26.720
<v Speaker 1>list jump. That's the fingers crossed hopeful that's the soft landing.

0:27:27.680 --> 0:27:29.760
<v Speaker 1>You know, we shall see we you know, we talked

0:27:29.760 --> 0:27:32.159
<v Speaker 1>about living in different times and maybe that will be it.

0:27:32.400 --> 0:27:34.480
<v Speaker 1>All right, So let's get to the markets, because it's

0:27:34.480 --> 0:27:36.600
<v Speaker 1>been an interesting day, no doubt about it. A lot

0:27:36.680 --> 0:27:38.840
<v Speaker 1>of risk on trade here, and we've got a good

0:27:38.880 --> 0:27:41.199
<v Speaker 1>guest who has to make some investment decisions and put

0:27:41.240 --> 0:27:44.040
<v Speaker 1>money to work in specific names and entities. Sandy Hillary

0:27:44.119 --> 0:27:46.359
<v Speaker 1>as portfolio manager at Villary and Co. We got a

0:27:46.400 --> 0:27:48.600
<v Speaker 1>billion and a half dollars in assets under management. They're

0:27:48.600 --> 0:27:50.960
<v Speaker 1>based in New Orleans. On the phone from there, this afternoon.

0:27:51.040 --> 0:27:53.399
<v Speaker 1>The Villary Equity fund. We should note, well this was

0:27:53.760 --> 0:27:56.320
<v Speaker 1>you know, as of this morning, up ten percent so

0:27:56.440 --> 0:27:58.720
<v Speaker 1>far this year. It's beating the S and P five hundred,

0:27:59.000 --> 0:28:00.960
<v Speaker 1>putting it in eighth for centile. When it comes to

0:28:01.000 --> 0:28:05.000
<v Speaker 1>other funds in the category, top holding has included Freeport mcmuren, Visa, J. B.

0:28:05.160 --> 0:28:07.719
<v Speaker 1>Hunt and more. Carol, all right, so let's get to it. Uh.

0:28:07.880 --> 0:28:09.920
<v Speaker 1>He is based in New Orleans and we find him

0:28:10.320 --> 0:28:14.159
<v Speaker 1>uh there on this FED Wednesday. So Sandy, good to

0:28:14.240 --> 0:28:16.280
<v Speaker 1>have you here with us. Um. We do like to

0:28:16.320 --> 0:28:18.880
<v Speaker 1>talk names and stocks with you, but let's talk macro

0:28:19.040 --> 0:28:21.480
<v Speaker 1>first of all. FED decision a bit of surprise or

0:28:22.480 --> 0:28:24.280
<v Speaker 1>the market reaction a bit of a surprise. How do

0:28:24.359 --> 0:28:26.720
<v Speaker 1>you see it? Yeah, and Carol, thanks for having me.

0:28:26.880 --> 0:28:28.800
<v Speaker 1>So you know, when we we looked at, uh, we

0:28:28.880 --> 0:28:32.119
<v Speaker 1>looked at Powell today when he's definitely sounded hawkish. You know,

0:28:32.200 --> 0:28:34.840
<v Speaker 1>he starts saying that rate increases would would be ongoing.

0:28:34.880 --> 0:28:36.399
<v Speaker 1>He gave little indication there at the end of the

0:28:36.480 --> 0:28:39.080
<v Speaker 1>rate hike cycle. You know. But when I look at

0:28:39.160 --> 0:28:41.200
<v Speaker 1>some of the devish language which you all refer in

0:28:41.240 --> 0:28:43.920
<v Speaker 1>too earlier, I mean he said they are acknowledging the

0:28:43.960 --> 0:28:46.760
<v Speaker 1>inflations easing, you know, and they are making progress. So

0:28:46.800 --> 0:28:48.560
<v Speaker 1>I mean he's in a tough spot because he knows

0:28:48.640 --> 0:28:51.680
<v Speaker 1>historically the FED tends to overdo it. They raised too much,

0:28:52.000 --> 0:28:53.280
<v Speaker 1>and he's just trying to keep us out of a

0:28:53.360 --> 0:28:55.880
<v Speaker 1>deeper recession, you know. But he really doesn't want to

0:28:55.920 --> 0:28:58.400
<v Speaker 1>pivot too soon, and then inflation just heats right back

0:28:58.480 --> 0:29:00.360
<v Speaker 1>up again, you know, like it did in the set andice,

0:29:00.400 --> 0:29:02.560
<v Speaker 1>and then we're in all sorts of trouble. So it's, uh,

0:29:02.680 --> 0:29:04.440
<v Speaker 1>it's the cross currents. While you I guess saw the

0:29:04.520 --> 0:29:07.200
<v Speaker 1>market you know, down sharply this morning, then rallying hard

0:29:07.360 --> 0:29:09.760
<v Speaker 1>that people are trying to figure out, you know, which direction.

0:29:09.840 --> 0:29:11.480
<v Speaker 1>And I think the bond market is smarter than the

0:29:11.520 --> 0:29:13.720
<v Speaker 1>stock market, and it is telling you with with the

0:29:13.800 --> 0:29:16.480
<v Speaker 1>ten uere you know falling, the yield falling. Um, I

0:29:16.520 --> 0:29:18.240
<v Speaker 1>think it's telling you that that even though he's saying

0:29:18.280 --> 0:29:20.000
<v Speaker 1>he won't cut by the end of the year, that

0:29:20.080 --> 0:29:22.440
<v Speaker 1>you possibly could see a cut maybe as you know,

0:29:22.480 --> 0:29:25.640
<v Speaker 1>in November December. Well we know they're always dated dependent

0:29:25.760 --> 0:29:28.800
<v Speaker 1>and you know, nothing is certain. J Powell did say

0:29:28.800 --> 0:29:31.400
<v Speaker 1>the FETE is not exploring pausing them restarting rate hikes.

0:29:31.440 --> 0:29:33.120
<v Speaker 1>I think that's a big one, Tim, you know, because

0:29:33.160 --> 0:29:35.920
<v Speaker 1>it's it's not it's that idea of okay, we're not

0:29:35.960 --> 0:29:38.400
<v Speaker 1>going to pause and thinking we're gonna have to raise again.

0:29:38.440 --> 0:29:40.080
<v Speaker 1>So I don't know whether he's just saying, hey, folks,

0:29:40.080 --> 0:29:42.240
<v Speaker 1>we're gonna get it all up now, so we're going

0:29:42.280 --> 0:29:45.960
<v Speaker 1>to continue, or he's just so certain that things inflation

0:29:46.000 --> 0:29:48.720
<v Speaker 1>will continue to trend lower. Why did the mark Why

0:29:48.760 --> 0:29:53.000
<v Speaker 1>did the markets though, uh, Sandy latch onto the Dovish

0:29:53.080 --> 0:29:55.480
<v Speaker 1>language rather than the Hawkish language, because there there was

0:29:55.560 --> 0:29:58.920
<v Speaker 1>certainly some Dovish language in there, but the Hawkish language

0:29:58.920 --> 0:30:01.040
<v Speaker 1>was there as well, and they're choosing to focus on

0:30:01.080 --> 0:30:04.240
<v Speaker 1>the Davish language. It's incredible. But I think maybe they're

0:30:04.240 --> 0:30:06.360
<v Speaker 1>focused on, you know, simply the bond market, and when

0:30:06.400 --> 0:30:08.640
<v Speaker 1>you see those yields fall, it's it's telling you're either

0:30:08.680 --> 0:30:11.000
<v Speaker 1>going as some sort of you know, shallow recession or

0:30:11.080 --> 0:30:13.440
<v Speaker 1>rates are going lower. And so I think they're they're

0:30:13.480 --> 0:30:15.560
<v Speaker 1>looking at the way that that's acting, and then I

0:30:15.640 --> 0:30:18.719
<v Speaker 1>think that's carrying forward into the into the stock market. Um,

0:30:18.840 --> 0:30:21.880
<v Speaker 1>it was interesting. We got that Joelt survey this morning,

0:30:21.920 --> 0:30:24.480
<v Speaker 1>and you look at November, we had ten point four

0:30:24.600 --> 0:30:26.960
<v Speaker 1>four you know, million job openings, and and now we've

0:30:26.960 --> 0:30:29.040
<v Speaker 1>got a little bit over eleven million job openings and

0:30:29.080 --> 0:30:31.680
<v Speaker 1>as you said earlier, one point nine jobs available for

0:30:31.760 --> 0:30:34.880
<v Speaker 1>every every person looking. So I think he's got to

0:30:34.920 --> 0:30:36.760
<v Speaker 1>be a little bit cautious that, you know, you could

0:30:36.760 --> 0:30:39.120
<v Speaker 1>get some wage inflation. But at the end of the day,

0:30:39.160 --> 0:30:42.080
<v Speaker 1>the market, Uh, the market went with the bond market

0:30:42.160 --> 0:30:44.360
<v Speaker 1>and and and started to rally as as you know,

0:30:44.400 --> 0:30:46.040
<v Speaker 1>as yields fell on the tenure. How do you feel

0:30:46.040 --> 0:30:49.520
<v Speaker 1>about valuations right now? You know, I think, uh, I

0:30:49.600 --> 0:30:51.560
<v Speaker 1>think it's a tale of two different markets. If you

0:30:51.600 --> 0:30:54.000
<v Speaker 1>look at two thousand and in twenty two, you saw

0:30:54.360 --> 0:30:57.520
<v Speaker 1>you know, growth stocks off over thirty percent um as

0:30:57.600 --> 0:30:59.840
<v Speaker 1>interest rates went up and and growth stocks tend to

0:30:59.840 --> 0:31:02.680
<v Speaker 1>move of inversely, and and you saw value only down

0:31:02.720 --> 0:31:06.320
<v Speaker 1>about two So clearly last year people hid in the

0:31:06.480 --> 0:31:09.640
<v Speaker 1>large gap dividend value stocks that Johnson and Johnson's, etcetera,

0:31:10.120 --> 0:31:12.760
<v Speaker 1>and uh, and it just left growth, you know, sort

0:31:12.800 --> 0:31:15.520
<v Speaker 1>of for dead, which is what we really do as

0:31:15.560 --> 0:31:18.400
<v Speaker 1>an active stock picker. We tend to try to, you know,

0:31:18.560 --> 0:31:21.480
<v Speaker 1>find these these high quality growth companies that are trading

0:31:21.520 --> 0:31:24.200
<v Speaker 1>at really reasonable prices, and I think there's plenty of

0:31:24.280 --> 0:31:28.600
<v Speaker 1>great valuations in in individual stocks and so UM we

0:31:28.920 --> 0:31:31.120
<v Speaker 1>you know, we like growth. Um. We were you know,

0:31:31.240 --> 0:31:33.440
<v Speaker 1>adding to some of it in some of the lows

0:31:33.520 --> 0:31:36.200
<v Speaker 1>last year and and it's picked up, you know, sharply

0:31:36.320 --> 0:31:38.640
<v Speaker 1>this year. Um. We've seen growth already up you know,

0:31:38.760 --> 0:31:40.720
<v Speaker 1>twelve percent year to date and values only up a

0:31:40.720 --> 0:31:43.800
<v Speaker 1>little bit over too. So there's been a great rotation.

0:31:44.280 --> 0:31:46.200
<v Speaker 1>But I would be fishing in the UH in the

0:31:46.320 --> 0:31:49.080
<v Speaker 1>growth pond rather than the the value pond. Give us

0:31:49.120 --> 0:31:51.000
<v Speaker 1>some of those growth stocks that you'd be fishing for

0:31:51.120 --> 0:31:54.000
<v Speaker 1>in that growth pond. Yeah. So, UM, one of the

0:31:54.040 --> 0:31:57.560
<v Speaker 1>ones we like is is On Semiconductor, a great play

0:31:57.640 --> 0:31:59.840
<v Speaker 1>on the five G build out. Um. They've also got

0:31:59.920 --> 0:32:03.160
<v Speaker 1>a lot of demand from electric vehicles, things like alternative energy,

0:32:03.240 --> 0:32:07.880
<v Speaker 1>industrial automation. UM. We tend to follow great CEOs and

0:32:07.960 --> 0:32:10.479
<v Speaker 1>Hassano Cory UM. He used to run a company called

0:32:10.560 --> 0:32:14.440
<v Speaker 1>Cyper Semiconductor that we were a large shareholder in, and

0:32:14.520 --> 0:32:17.280
<v Speaker 1>he's come over to on Semi some years ago. He's

0:32:17.320 --> 0:32:20.480
<v Speaker 1>already transforming it from you know, a higher growth, higher

0:32:20.600 --> 0:32:23.560
<v Speaker 1>margin business from you know, something that was more commodity

0:32:23.640 --> 0:32:25.800
<v Speaker 1>orient if he's getting. You know, he wanted to have

0:32:25.960 --> 0:32:29.600
<v Speaker 1>gross margins near fort you know, basically two years from now.

0:32:29.680 --> 0:32:33.120
<v Speaker 1>He's already he's already there and he's moving to because

0:32:33.120 --> 0:32:36.680
<v Speaker 1>they're growing an area called silicon carbide um, which is

0:32:37.040 --> 0:32:40.720
<v Speaker 1>which is just growing extremely uh quickly. Um. You know

0:32:40.880 --> 0:32:44.800
<v Speaker 1>this is for things like electric vehicle batteries. And you know,

0:32:44.880 --> 0:32:47.920
<v Speaker 1>Goldman will tell you thirteen million electric vehicle batteries will

0:32:47.960 --> 0:32:50.680
<v Speaker 1>will use silicon carbide by two thousand thirty and that's

0:32:50.680 --> 0:32:53.840
<v Speaker 1>only a one million today. So he's just a great manager.

0:32:54.000 --> 0:32:55.880
<v Speaker 1>It's a great business. And I think this is why

0:32:55.960 --> 0:32:58.400
<v Speaker 1>you're seeing, you know, things like On do quite well

0:32:58.440 --> 0:33:00.800
<v Speaker 1>when you have you know, competitor, maybe like an Intel.

0:33:00.840 --> 0:33:02.720
<v Speaker 1>They can't get out of their own way. So even

0:33:02.760 --> 0:33:05.840
<v Speaker 1>though it's up something like so far, oh forgive me,

0:33:06.640 --> 0:33:09.479
<v Speaker 1>because we've seen in uptick, if you will, in today's

0:33:09.520 --> 0:33:12.240
<v Speaker 1>trade kind of pushing everything higher. I mean alone today

0:33:12.280 --> 0:33:15.560
<v Speaker 1>it's up another six percent here. Valuation feels about right

0:33:15.600 --> 0:33:20.320
<v Speaker 1>here based on the outlook. Yeah, I mean I still see, um,

0:33:20.480 --> 0:33:22.960
<v Speaker 1>I still see these guys making over four dollars and

0:33:23.160 --> 0:33:26.680
<v Speaker 1>in fifty cents uh in in earnings. Um. You know,

0:33:26.800 --> 0:33:29.240
<v Speaker 1>basically this year. So you're looking at Stuck that's under

0:33:29.480 --> 0:33:33.560
<v Speaker 1>sixteen times earnings UM, which is um. You know my opinion, Uh,

0:33:34.440 --> 0:33:36.600
<v Speaker 1>you know, I would say it's fair value or undervalued,

0:33:36.960 --> 0:33:41.240
<v Speaker 1>given the the the transformation of a more profitable business,

0:33:41.320 --> 0:33:44.239
<v Speaker 1>higher margins, and and just growing much more quickly as

0:33:44.240 --> 0:33:46.760
<v Speaker 1>they get into the non commodity side of their of

0:33:46.840 --> 0:33:48.720
<v Speaker 1>their of their business. All right, can I leave it

0:33:48.760 --> 0:33:51.040
<v Speaker 1>on that note. Listen, Sandy, thank you so much, appreciate it.

0:33:51.080 --> 0:33:54.280
<v Speaker 1>Sandy Villery, portfolio manager at Villery and Company, joining us

0:33:54.600 --> 0:33:58.200
<v Speaker 1>on the phone from New Orleans. This is the Bloomberg

0:33:58.280 --> 0:34:02.600
<v Speaker 1>Business Week podcast, little on Apple, Spotify, and anywhere else

0:34:02.640 --> 0:34:06.200
<v Speaker 1>you get your podcast. Listen live each weekday starting a

0:34:06.280 --> 0:34:09.239
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0:34:09.320 --> 0:34:12.160
<v Speaker 1>Radio app, tune In, and the Bloomberg Business App. You

0:34:12.239 --> 0:34:15.360
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0:34:15.600 --> 0:34:17.240
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