WEBVTT - Broadcom Soars Most Since 2020 to Top $1 Trillion Valuation

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<v Speaker 1>Bloomberg Audio Studios, podcasts, radio news. This is Bloomberg Business

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<v Speaker 1>Wait inside from the reporters and editors who bring you

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<v Speaker 1>and Tim Stenebeck from Bloomberg.

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<v Speaker 2>Radio shows a Broadcom did give some juice to the trade,

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<v Speaker 2>and it continues to soar. It's pretty much saying at

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<v Speaker 2>its best levels of the session of twenty two percent,

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<v Speaker 2>the stock hitting a one trillion dollar valuation for the

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<v Speaker 2>first time after predicting a boom in demand for its

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<v Speaker 2>artificial intelligence chips. So with what you need to know,

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<v Speaker 2>we've got an incredible duo. We lean on them so much.

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<v Speaker 3>Really, the most popular guys today.

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<v Speaker 2>I don't even know if they got any sleep.

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<v Speaker 4>Man.

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<v Speaker 2>I've just seen every time I look up at Bloomberg

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<v Speaker 2>TV or I look at the radio studio, they are

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<v Speaker 2>talking to folks. Kun John Sabani, senior semi Coonductor alys

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<v Speaker 2>at Bloomberg Intelligence and also with us is Ian King,

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<v Speaker 2>US Semiconductor and Networking reporter at Bloomberg is. We are

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<v Speaker 2>so lucky to call them hours. So we get to

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<v Speaker 2>lean on them both. Joining us from our San Francisco bureau. Ian,

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<v Speaker 2>I do want to start with you Broadcoms quarter. What

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<v Speaker 2>is the nut that investors are so excited about? Is

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<v Speaker 2>it the outlook? Is it the AI? What is it?

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<v Speaker 5>Well, I mean, I'm suretent will give you better analysis

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<v Speaker 5>than I could, but really the report was kind of okay,

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<v Speaker 5>the forecast was okay. But what happened on the call

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<v Speaker 5>was that the CEO gave a long term projection for

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<v Speaker 5>its kind of most important AI product that is kind

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<v Speaker 5>of off the charts, and that really got everybody very

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<v Speaker 5>excited about the future of this company and kind of

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<v Speaker 5>pointed to it as a whole different company in terms

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<v Speaker 5>of the scale that it can achieve.

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<v Speaker 6>Cujohn, come on in here, because we spoke to you

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<v Speaker 6>yesterday after the numbers came out. Chairs we're kind of

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<v Speaker 6>all over the place. Actually fell for a second, but

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<v Speaker 6>about up about two percent, nothing like what we're seeing

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<v Speaker 6>this morning.

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<v Speaker 3>Certainly, there were.

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<v Speaker 6>Some price targets that were raised, but it was all

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<v Speaker 6>about what was said on the call, right.

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<v Speaker 7>Yeah, it was all about AI.

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<v Speaker 8>I mean, just to put things in perspective, they did

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<v Speaker 8>twelve billion in AI revenues, I mean beyond Nvidia. When

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<v Speaker 8>we look at the size of AI chip revenues, there's

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<v Speaker 8>nobody else. Even AMD is lagging if you just look

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<v Speaker 8>at pure AI numbers. Right, and we've been talking about

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<v Speaker 8>A and D for a while as the number two

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<v Speaker 8>GPU provider when they gave all this guide. Now estimates

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<v Speaker 8>are going somewhere between twenty five to thirty billions in

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<v Speaker 8>three years. Again, that size of that growth for a

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<v Speaker 8>company like this, that's something we have only seen happen

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<v Speaker 8>just with one name so far.

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<v Speaker 2>So Coon John, you know, and I know we talked

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<v Speaker 2>about this with you and Ian I believe yesterday, but

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<v Speaker 2>I want you to put it out for the Bloomberg

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<v Speaker 2>audience again. Where is Broadcom in the AI chip puzzle?

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<v Speaker 7>Yeah, so they have two big AI businesses.

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<v Speaker 8>One is called the custom asex or the custom silicon,

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<v Speaker 8>where they helped these large cloud and hyperscale customers like Google, Meta, Amazon,

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<v Speaker 8>Microsoft designed their own chips, which we have seen a

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<v Speaker 8>trend that everyone is adopting. And the second piece is

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<v Speaker 8>the AI networking and connectivity. So think of the iOS,

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<v Speaker 8>the basically highways and the pipeline that connects all of

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<v Speaker 8>these GPU and CPUs together. In the data center.

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<v Speaker 6>Hey, Ian, come on in here, because, as you point

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<v Speaker 6>out in your story, Broadcom got to where it is

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<v Speaker 6>today by making a series of acquisitions.

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<v Speaker 3>Over the last few years.

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<v Speaker 6>More acquisitions in the future now that we're seeing the

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<v Speaker 6>value of Broadcom continue to surge, give us a brief

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<v Speaker 6>history of how it got to where it is today,

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<v Speaker 6>and then what you think could come next when it

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<v Speaker 6>comes to acquisitions.

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<v Speaker 5>Yeah, I mean Hogtan started off this company by basically

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<v Speaker 5>with the small division of what was spun off from

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<v Speaker 5>originally HP years ago and sort of made this kind

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<v Speaker 5>of sequence of deals where he got bigger and bigger

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<v Speaker 5>and bigger, and that eventually even branched out into software.

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<v Speaker 5>And now we've got one of the world's largest chip

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<v Speaker 5>companies on it's pretty high ranks of software makers as well.

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<v Speaker 5>And as we learn yesterday, he's not finished.

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<v Speaker 4>You know.

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<v Speaker 2>It makes me think about you know, and I know,

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<v Speaker 2>and we've talked about this with you a lot, Kunjan Tuo,

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<v Speaker 2>just like what's going on with Intel, and then you

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<v Speaker 2>look at some of these other chip companies. Having said that,

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<v Speaker 2>I feel like we've started to talk about Nvidiom people

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<v Speaker 2>going after that. Who does Kunjohn let me bring you

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<v Speaker 2>back in here. Who does Broadcom have to be worried

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<v Speaker 2>about or do they not have to be worried about?

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<v Speaker 2>Is their position in a pretty good place ahead of

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<v Speaker 2>maybe their competition at this point.

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<v Speaker 8>Yeah, so specific to AI, I mean it has been

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<v Speaker 8>usually a diopoly in this market between Broadcom and Marvel.

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<v Speaker 8>Broadcom has usually held somewhere between say sixty to eighty

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<v Speaker 8>percent market share. We think that's going to stay in

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<v Speaker 8>the same rage in the future. Again, Marvel is another

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<v Speaker 8>up and comer here who is making strides with the

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<v Speaker 8>same customers that Broadcom is announcing, or the same set

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<v Speaker 8>of customers, I should say. So we expect these two

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<v Speaker 8>to continue dominating the AI customs and the AI networking

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<v Speaker 8>space going forward.

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<v Speaker 2>And yeah, go ahead, Well I come on in on

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<v Speaker 2>that too, like how you see it in terms of

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<v Speaker 2>you know what I asked Kunjan as well, if you

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<v Speaker 2>have anything to kind of add to that.

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<v Speaker 5>Yeah, no, there was a it was a that was

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<v Speaker 5>a key part of the call yesterday. I mean, they

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<v Speaker 5>gave this market size as well, maybe as much as

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<v Speaker 5>ninety billion, And people are like, okay, so you've got

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<v Speaker 5>these two new customers that you're not telling us who

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<v Speaker 5>they are, How does this all fit factor together? Is

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<v Speaker 5>this happening on your existing customers, You've got two new customers.

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<v Speaker 5>Are you going to have one hundred percent of this?

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<v Speaker 5>And all of these kind of flurry of questions, and

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<v Speaker 5>hot Tan was basically that the CEO is basically smiling

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<v Speaker 5>and saying, well, there's a room for everybody, but we

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<v Speaker 5>think we're going to do quite well within that. And

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<v Speaker 5>he's right. I mean, as Kunjin said, they are the

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<v Speaker 5>best game in town, the kind of default choice. If

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<v Speaker 5>you want a custom chip for your own data centers,

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<v Speaker 5>you're going to go and ask them to help you

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<v Speaker 5>to do it right now.

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<v Speaker 6>Yeah, we should not Marvel Technology upright now by nine

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<v Speaker 6>point three percent in sympathy with Broadcast results, but Marvell

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<v Speaker 6>only about a one hundred billion dollar company, still about

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<v Speaker 6>neck and neck when it comes to performance this year.

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<v Speaker 6>Both companies up about one hundred percent so far this year.

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<v Speaker 6>Kon John Wighan on the idea of acquisitions moving forward

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<v Speaker 6>for broadcom Ian mentioned that, and he mentioned in the

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<v Speaker 6>story too that this is a company that got where

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<v Speaker 6>it is today as a result of making acquisitions.

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<v Speaker 3>At Bloomberg Intelligence, are.

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<v Speaker 6>There any names that are on your radar about companies

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<v Speaker 6>that could be acquired by Broadcom in the future.

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<v Speaker 8>Not at this moment. I mean, look, Ian answered it

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<v Speaker 8>spot on. I also come originally from Broadcom. I was

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<v Speaker 8>part of the acquisition mahan Hawk acquired Broadcom. So I

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<v Speaker 8>mean we do expect him to continue staying acquisitive. That's

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<v Speaker 8>how he's really made his name. But when you look

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<v Speaker 8>at the size of the past acquisition, each larger than

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<v Speaker 8>the previous one, they don't tend to go and do

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<v Speaker 8>small tuckins, right, so they I think at this moment,

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<v Speaker 8>like Ian said, they are going to focus on paying

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<v Speaker 8>down debt first and then start collecting a bigger pile

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<v Speaker 8>of cash, which which they can then go out and

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<v Speaker 8>do a bigger deal. Now, when you think about candidates

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<v Speaker 8>with that size, there's not a loft left in the

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<v Speaker 8>semi space, and regulation, at least in the semi so far,

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<v Speaker 8>has not been as generous.

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<v Speaker 2>Hey, So Kunjan, wait a minute, did you just drop

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<v Speaker 2>a ball on us? Like, did you work for Broadcom?

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<v Speaker 2>How did we not know this?

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<v Speaker 7>I did in my past life.

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<v Speaker 8>I was an engineer and I used to work for

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<v Speaker 8>broad Com.

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<v Speaker 2>So what do we need to know? Any inside stories?

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<v Speaker 7>Here not anymore fair enough?

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<v Speaker 2>Fair enough, Hey guys, what are the things I thought

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<v Speaker 2>about after this quarter? And this is what we do, right,

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<v Speaker 2>We get one earnings that we get an outlook, we

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<v Speaker 2>get a call and they were like, okay, next quarter.

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<v Speaker 2>So Ian, does what we got from this company make

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<v Speaker 2>the next quarter or next couple of quarters even tougher

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<v Speaker 2>in terms of expectations.

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<v Speaker 5>He was very careful to set expectations appropriately and said, look,

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<v Speaker 5>these are just big customers, and these big projects take

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<v Speaker 5>time and they are frankly lumpy. So that's why they

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<v Speaker 5>gave this twenty twenty seven target. And then he kind

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<v Speaker 5>of gave us sort of a soft target for the

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<v Speaker 5>whole of next year, which wasn't a massive increase from

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<v Speaker 5>you know, sort of fifteen to twenty in terms of

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<v Speaker 5>the available market. It was very vague, but there was

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<v Speaker 5>some very careful signaling there to sort of say, hey, look,

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<v Speaker 5>you need to keep your eyes on the long term

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<v Speaker 5>gross potential here, not get sort of too tied up

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<v Speaker 5>in the quarterly sort of machinations that we're going to

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<v Speaker 5>see going forward.

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<v Speaker 2>We never do that. We never do that, Kunjan, just

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<v Speaker 2>saving you twenty seconds here, how are you thinking about

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<v Speaker 2>what's going to be on your radar when it comes

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<v Speaker 2>to this company in particular.

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<v Speaker 8>I mean, like Ian said, I don't think investors should

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<v Speaker 8>look at this quarter to quarter. I think we've just

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<v Speaker 8>gotten a bad habit of what Nvidia has said a precedent.

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<v Speaker 8>I mean, these these are again handful of customers, like

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<v Speaker 8>you can count on your one hand, right, their buying

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<v Speaker 8>patterns will go through, which is very normal, through some

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<v Speaker 8>kind of timing and digestion. So we should look at

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<v Speaker 8>it again from a year to year milestone.

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<v Speaker 2>All right, some good advice, because it's true we get

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<v Speaker 2>kind of caught up in day to day stuff and

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<v Speaker 2>sometimes you have to do the longer term perspective. Guys,

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<v Speaker 2>thank you so much. Have a wonderful weekend. Kun John Sabani,

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<v Speaker 2>senior Semiconductor analyst at Bloomberg Intelligence, along with Ian King,

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<v Speaker 2>US semiconductor and networking reporter at Bloomberg News. Incredible on

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<v Speaker 2>the space, both of them and joining us there from

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<v Speaker 2>our San Francisco bureau.

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<v Speaker 1>You're listening to the Bloomberg Business Week podcast. Catch us

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<v Speaker 1>live weekday afternoons from two to five pm Eastern Listen

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<v Speaker 1>Business app or want us live on YouTube?

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<v Speaker 2>All right, we do want to get to today's Bloomberg

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<v Speaker 2>Big Take. It's a story that is part of several

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<v Speaker 2>on the global fertility industry that our Bloomberg News team

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<v Speaker 2>has been looking into. To tell it, it took an

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<v Speaker 2>editorial village of Bloomberg reporters. The tale. The reality included

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<v Speaker 2>following a teenage girl in India lord into selling her eggs,

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<v Speaker 2>a model in Argentina whose genetic makeup is prized, a

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<v Speaker 2>mother in Greece told by police that our eggs were stolen,

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<v Speaker 2>and two girls from Taiwan who have put themselves at

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<v Speaker 2>risk to earn money in the United States. We had

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<v Speaker 2>a lot of questions, and I bet so do.

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<v Speaker 6>You Yeah, so stop what you're doing because you know

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<v Speaker 6>you want to know more. The entire read it is

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<v Speaker 6>a long one, It is worth it, and it is

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<v Speaker 6>with good reason. It can be found on the Bloomberg

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<v Speaker 6>terminal and at Bloomberg dot com slash BusinessWeek. Here with

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<v Speaker 6>us is Bloomberg BusinessWeek Senior investigative reporter, Susan Burfield in

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<v Speaker 6>our Los Angeles bureau. Susan, We're living in really interesting

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<v Speaker 6>times because the whole idea that this medical process can

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<v Speaker 6>be undertaken is actually relatively new. Here, let's take a

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<v Speaker 6>step back and just give us an idea of the

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<v Speaker 6>fertility industry here in the US globally and what it is,

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<v Speaker 6>how big it is, and then we'll get into some

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<v Speaker 6>of the details in the story.

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<v Speaker 9>Yeah, thanks so much. So the fertility industry globally is

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<v Speaker 9>worth about thirty five billion dollars and it's growing. And

0:10:53.480 --> 0:10:57.520
<v Speaker 9>you know that's in part because there is new technology

0:10:57.840 --> 0:11:03.040
<v Speaker 9>that allows eggs, in particular, to be frozen, to be stored,

0:11:03.160 --> 0:11:06.599
<v Speaker 9>to be transplanted, to be transported, and to be transplanted.

0:11:07.240 --> 0:11:10.120
<v Speaker 9>And at the same time, as you know, probably a

0:11:10.200 --> 0:11:14.880
<v Speaker 9>lot of people know, women are delaying having kids and

0:11:14.920 --> 0:11:18.280
<v Speaker 9>that makes it harder to get pregnant. And that's because

0:11:19.559 --> 0:11:24.120
<v Speaker 9>human eggs decline in number and quality in a woman

0:11:24.360 --> 0:11:28.000
<v Speaker 9>as she ages, and so that is one reason that

0:11:28.080 --> 0:11:33.040
<v Speaker 9>the demand for eggs from younger fertile women has been growing.

0:11:33.480 --> 0:11:35.720
<v Speaker 9>And that's what we set out to try to capture.

0:11:36.480 --> 0:11:40.319
<v Speaker 9>Who's you know, who's providing those eggs, who's buying those eggs,

0:11:40.960 --> 0:11:43.599
<v Speaker 9>and how the flows work transnationally.

0:11:43.800 --> 0:11:46.400
<v Speaker 2>All right, So I am curious about how you guys

0:11:46.400 --> 0:11:48.720
<v Speaker 2>went about finding these individuals and when you talk about

0:11:48.880 --> 0:11:52.000
<v Speaker 2>you know, eggs, when you're younger, you know, being much

0:11:52.000 --> 0:11:55.959
<v Speaker 2>more productive. Right. This story gets into though, tapping into

0:11:56.040 --> 0:12:02.000
<v Speaker 2>or accessing very young women girls right to get access

0:12:02.000 --> 0:12:03.920
<v Speaker 2>to their eggs. I mean this has become a commodity,

0:12:03.920 --> 0:12:06.560
<v Speaker 2>and as you guys say, a premium commodity.

0:12:07.840 --> 0:12:10.560
<v Speaker 9>Yeah, I think you know, one way to think about this,

0:12:10.720 --> 0:12:13.920
<v Speaker 9>and it probably you know, makes some people uncomfortable, and

0:12:14.200 --> 0:12:18.319
<v Speaker 9>I think that's fair because this is a really emotional

0:12:18.480 --> 0:12:22.680
<v Speaker 9>issue where people, especially you know, those trying to get pregnant,

0:12:23.080 --> 0:12:26.640
<v Speaker 9>are at their most vulnerable. These aren't easy decisions to

0:12:26.679 --> 0:12:30.800
<v Speaker 9>make for anybody involved. But you know, what we found

0:12:30.880 --> 0:12:35.000
<v Speaker 9>is that because there is an increasing demand for eggs,

0:12:35.000 --> 0:12:39.480
<v Speaker 9>you could consider them a very precious and scarce resource.

0:12:40.080 --> 0:12:45.680
<v Speaker 9>And as with any resource, that presents opportunities for both

0:12:45.760 --> 0:12:48.640
<v Speaker 9>people to benefit, you know, and by that I mean

0:12:48.720 --> 0:12:53.560
<v Speaker 9>both the women who voluntarily sell their eggs to make

0:12:53.640 --> 0:12:57.480
<v Speaker 9>money to help people. Obviously they would be parents who

0:12:57.520 --> 0:13:00.240
<v Speaker 9>are getting the eggs and the chance to have a bite,

0:13:00.679 --> 0:13:05.240
<v Speaker 9>but it also presents opportunity for exploitation and that's also

0:13:05.280 --> 0:13:08.360
<v Speaker 9>what we documented well. And when you're talking about young girls.

0:13:08.360 --> 0:13:09.240
<v Speaker 9>That's what you're talking.

0:13:09.080 --> 0:13:10.840
<v Speaker 2>About exactly, and I want to get into and to

0:13:10.880 --> 0:13:12.760
<v Speaker 2>be fair, I think we've all been on a subway

0:13:12.880 --> 0:13:15.520
<v Speaker 2>and seen the posters that said, you know, you can

0:13:15.520 --> 0:13:17.520
<v Speaker 2>sell your eggs essentially, and we were actually having a

0:13:17.559 --> 0:13:22.960
<v Speaker 2>conversation in the newsroom around your story. So to be fair,

0:13:23.080 --> 0:13:26.400
<v Speaker 2>there's a legal you know, everything's on the up and up,

0:13:26.400 --> 0:13:28.480
<v Speaker 2>and then there's some that you get a little bit questionable.

0:13:28.559 --> 0:13:31.480
<v Speaker 2>Let's go into because it does seem like often when

0:13:31.520 --> 0:13:35.199
<v Speaker 2>we're looking at i don't know, tapping a precious resource,

0:13:35.679 --> 0:13:38.200
<v Speaker 2>it often leads us to emerging markets. And that's one

0:13:38.200 --> 0:13:39.880
<v Speaker 2>of the things that struck me about this story because

0:13:39.920 --> 0:13:40.640
<v Speaker 2>this does as well.

0:13:42.520 --> 0:13:46.800
<v Speaker 9>That's right. So you know, what we found is that

0:13:48.160 --> 0:13:53.840
<v Speaker 9>for some clinics, for some parents, for some agents, you know,

0:13:53.880 --> 0:13:58.360
<v Speaker 9>the people who are connecting these donors, we call them donors,

0:13:58.360 --> 0:14:00.720
<v Speaker 9>though you know most of them are getting paid, but

0:14:01.480 --> 0:14:04.240
<v Speaker 9>the term the industry prefers is donors.

0:14:05.280 --> 0:14:08.920
<v Speaker 2>And you know, because people can.

0:14:08.800 --> 0:14:13.840
<v Speaker 9>Make money selling their eggs in the US and elsewhere,

0:14:14.240 --> 0:14:17.200
<v Speaker 9>you know, it opens up the possibilities for what you

0:14:17.200 --> 0:14:20.920
<v Speaker 9>could say is like economic coercion. And I think what

0:14:20.960 --> 0:14:23.320
<v Speaker 9>we were trying to look at is you know, how

0:14:23.360 --> 0:14:27.320
<v Speaker 9>does that play out in countries where you know, the

0:14:27.360 --> 0:14:31.040
<v Speaker 9>both the chance or the necessity to sell your eggs

0:14:31.520 --> 0:14:34.640
<v Speaker 9>can bring more money than women might be able to

0:14:34.720 --> 0:14:38.200
<v Speaker 9>make in lots of other ways, and that brings a

0:14:38.280 --> 0:14:40.400
<v Speaker 9>pressure that you know, we wanted to explore.

0:14:40.760 --> 0:14:42.880
<v Speaker 6>Can you talk a little bit about how the story

0:14:42.920 --> 0:14:46.760
<v Speaker 6>opens and the one of the first chapters about a

0:14:46.800 --> 0:14:51.440
<v Speaker 6>young girl in India and her story, and then we

0:14:51.480 --> 0:14:53.840
<v Speaker 6>can talk a little bit about how this story totally

0:14:53.880 --> 0:14:57.320
<v Speaker 6>spans the globe and the Bloomberg newsroom and how a

0:14:57.360 --> 0:14:59.440
<v Speaker 6>global newsroom is able to capture stories.

0:14:59.200 --> 0:14:59.600
<v Speaker 4>Such as this.

0:15:00.920 --> 0:15:05.840
<v Speaker 9>Sure, so you know, the the young really teen, the

0:15:05.880 --> 0:15:12.600
<v Speaker 9>teen in India who we write about, agreed to sell

0:15:12.640 --> 0:15:16.280
<v Speaker 9>her eggs but really was too young to understand what

0:15:16.320 --> 0:15:21.760
<v Speaker 9>she was doing even still doesn't quite you know, understand

0:15:21.800 --> 0:15:25.560
<v Speaker 9>that there, you know, could be children out there who

0:15:25.880 --> 0:15:27.400
<v Speaker 9>were born from her eggs.

0:15:28.840 --> 0:15:30.920
<v Speaker 2>She h you know herself says that.

0:15:31.320 --> 0:15:37.640
<v Speaker 9>You know, she wanted a mobile phone and was offered

0:15:37.680 --> 0:15:41.440
<v Speaker 9>a way to make the money by other women who

0:15:41.480 --> 0:15:45.320
<v Speaker 9>were agents and who were recruiting women or young women

0:15:45.520 --> 0:15:49.760
<v Speaker 9>like her to sell their eggs. And you know, this

0:15:50.880 --> 0:15:55.280
<v Speaker 9>is I think a pretty egregious case. You know, teenagers

0:15:55.280 --> 0:15:58.720
<v Speaker 9>are not supposed to be donating eggs in India or

0:15:58.760 --> 0:16:02.320
<v Speaker 9>where she lives. You know, the law requires women to

0:16:02.320 --> 0:16:05.920
<v Speaker 9>be twenty three. But she was kind of recruited into

0:16:05.920 --> 0:16:11.480
<v Speaker 9>a network of women mostly who had set up an

0:16:11.640 --> 0:16:17.360
<v Speaker 9>entire way to almost fool the clinics. It was probably

0:16:17.360 --> 0:16:20.080
<v Speaker 9>also incumbent upon the clinics to ask more questions than

0:16:20.120 --> 0:16:24.280
<v Speaker 9>they might have or to probe the answers a little

0:16:24.320 --> 0:16:27.280
<v Speaker 9>bit more than they were getting from the young woman.

0:16:27.560 --> 0:16:29.520
<v Speaker 9>But you know, you know, she didn't do this.

0:16:29.720 --> 0:16:32.440
<v Speaker 2>On her own. She was recruited into a network.

0:16:33.360 --> 0:16:33.560
<v Speaker 4>You know.

0:16:33.600 --> 0:16:35.800
<v Speaker 2>One of the other stories that you get to is

0:16:35.880 --> 0:16:38.520
<v Speaker 2>and I feel like this is where Bloomberg and BusinessWeek

0:16:38.520 --> 0:16:40.320
<v Speaker 2>does so well, is that you get very specific and

0:16:40.360 --> 0:16:42.800
<v Speaker 2>you tell what has happened to these individuals. You talk

0:16:42.840 --> 0:16:46.880
<v Speaker 2>about a woman in Greece, Maria, she goes by a pseudonym,

0:16:47.080 --> 0:16:51.120
<v Speaker 2>but again was harvesting eggs for herself, right right, And

0:16:51.160 --> 0:16:53.680
<v Speaker 2>then it turned out she found out that wasn't just

0:16:53.720 --> 0:16:54.120
<v Speaker 2>the case.

0:16:55.760 --> 0:17:00.720
<v Speaker 9>Yeah, this was you know, Maria, as you said, was

0:17:01.120 --> 0:17:06.040
<v Speaker 9>seeking IVF treatment for herself. You know that included, as

0:17:06.080 --> 0:17:10.440
<v Speaker 9>it often does, the kind of stimulation process that egg

0:17:10.480 --> 0:17:14.600
<v Speaker 9>donors go through, which is, you know, about ten twelve

0:17:14.720 --> 0:17:20.119
<v Speaker 9>days of regular hormonal shots to increase the number of

0:17:20.280 --> 0:17:24.359
<v Speaker 9>eggs that a woman can produce, called superovulation. So Maria

0:17:24.400 --> 0:17:28.919
<v Speaker 9>went through that, went through the retrieval process which you

0:17:29.119 --> 0:17:34.720
<v Speaker 9>requires going under Anesesia and her eggs were extracted. She

0:17:34.840 --> 0:17:37.760
<v Speaker 9>was told that she produced a certain number of eggs,

0:17:39.000 --> 0:17:43.320
<v Speaker 9>and ultimately she did give birth as a result of

0:17:43.359 --> 0:17:47.919
<v Speaker 9>this extraction and the retrieval and the IVF. But later

0:17:48.440 --> 0:17:51.080
<v Speaker 9>she was told by the police that some of her

0:17:51.160 --> 0:17:58.920
<v Speaker 9>eggs were given to another woman, and the clinic at

0:17:58.920 --> 0:18:06.640
<v Speaker 9>the center of this is under an investigation. So Maria

0:18:06.760 --> 0:18:10.440
<v Speaker 9>doesn't know and doesn't know who the woman is, doesn't

0:18:10.480 --> 0:18:13.000
<v Speaker 9>know the result of it, but she knows that some

0:18:13.080 --> 0:18:15.960
<v Speaker 9>of her eggs were given to another woman without her consent.

0:18:16.760 --> 0:18:19.199
<v Speaker 6>You know, when I was reading this story, Susan, I

0:18:19.240 --> 0:18:22.960
<v Speaker 6>was thinking about the different regulations in different parts of

0:18:22.960 --> 0:18:26.679
<v Speaker 6>the world when it comes to this medical procedure. I mean,

0:18:26.720 --> 0:18:29.240
<v Speaker 6>at the end of the day, we're talking about medical procedures. Here,

0:18:29.480 --> 0:18:34.800
<v Speaker 6>we're talking about drugs, and the way that the industry

0:18:34.840 --> 0:18:38.080
<v Speaker 6>is regulated is different in many parts of the world.

0:18:38.520 --> 0:18:42.040
<v Speaker 6>Here in the US, what do we look at with

0:18:42.080 --> 0:18:45.560
<v Speaker 6>the regulatory environment and what should people think about here

0:18:45.560 --> 0:18:49.800
<v Speaker 6>in the US who are listening to this, watching this

0:18:50.040 --> 0:18:53.960
<v Speaker 6>have read this story when they learn about procedures such

0:18:53.960 --> 0:18:54.240
<v Speaker 6>as these.

0:18:54.520 --> 0:18:56.480
<v Speaker 2>Yeah, like how do you trust your doctor who is

0:18:56.640 --> 0:18:59.960
<v Speaker 2>doing the extraction he or she to trust that they're

0:19:00.240 --> 0:19:02.720
<v Speaker 2>just taking eggs for yourself?

0:19:05.520 --> 0:19:11.159
<v Speaker 9>Well, so, you know, as you said, different countries do

0:19:11.240 --> 0:19:16.200
<v Speaker 9>have different regulations both about what's allowed overall and you know,

0:19:16.280 --> 0:19:21.239
<v Speaker 9>how donors are treated. You know, in some places, in

0:19:21.240 --> 0:19:25.399
<v Speaker 9>some countries, donors must remain anonymous. In other places donors

0:19:25.480 --> 0:19:29.960
<v Speaker 9>must be identified. In the US, you know, the f

0:19:30.040 --> 0:19:35.880
<v Speaker 9>d AH does have some restrictions and on who can

0:19:35.920 --> 0:19:40.720
<v Speaker 9>donate and requirements for them. There is an industry trade

0:19:40.760 --> 0:19:45.119
<v Speaker 9>group that puts forth guidelines for how, you know, for

0:19:45.200 --> 0:19:49.120
<v Speaker 9>how care overall is supposed to be provided, how egg

0:19:49.160 --> 0:19:53.439
<v Speaker 9>donors and sperm donors are supposed to be treated. You know,

0:19:53.480 --> 0:19:56.200
<v Speaker 9>what we found is that you know, those are guidelines.

0:19:57.119 --> 0:20:02.440
<v Speaker 9>They are widely accepted, but there isn't really a way

0:20:02.600 --> 0:20:04.680
<v Speaker 9>to enforce those guidelines.

0:20:05.359 --> 0:20:07.840
<v Speaker 2>So we don't want to suggest that.

0:20:07.840 --> 0:20:11.520
<v Speaker 9>You know, the industry in the US is is dangerous

0:20:11.560 --> 0:20:14.280
<v Speaker 9>in any way. What you know, what we were looking

0:20:14.320 --> 0:20:19.800
<v Speaker 9>at is you know, cases where there had been problems abroad,

0:20:19.960 --> 0:20:25.280
<v Speaker 9>and and just we want people to think about how

0:20:25.320 --> 0:20:28.960
<v Speaker 9>this is all happening. Sometimes it's happening quickly. Sometimes you know,

0:20:29.359 --> 0:20:34.159
<v Speaker 9>as rules or circumstances change in one country, you know,

0:20:34.200 --> 0:20:37.320
<v Speaker 9>the entire market might shift to another country. And so

0:20:37.680 --> 0:20:40.480
<v Speaker 9>I think probably we're all familiar with people who might

0:20:40.640 --> 0:20:44.760
<v Speaker 9>travel elsewhere more fertility services. You know, in part maybe

0:20:44.800 --> 0:20:47.159
<v Speaker 9>it's cheaper, you know, in part because maybe they do

0:20:47.240 --> 0:20:50.680
<v Speaker 9>have more access to eggs or to surrogates.

0:20:51.200 --> 0:20:54.639
<v Speaker 2>And so, you know, our our aim.

0:20:54.680 --> 0:20:59.920
<v Speaker 9>Is to kind of reveal this global network that exists

0:21:00.720 --> 0:21:05.239
<v Speaker 9>and to how people think about you know, where you know,

0:21:05.320 --> 0:21:08.840
<v Speaker 9>where this most precious resource comes from and.

0:21:08.840 --> 0:21:12.120
<v Speaker 2>Goes to an incredible read. You and the Gang Bloomberg

0:21:12.119 --> 0:21:16.520
<v Speaker 2>BusinessWeek Senior investigative Reporter Susan Burfield. Check it out Bloomberg

0:21:16.520 --> 0:21:18.679
<v Speaker 2>BusinessWeek dot com and on the Bloomberg terminal.

0:21:20.680 --> 0:21:24.560
<v Speaker 1>You're listening to the Bloomberg Business Week Podcast. Listen live

0:21:24.640 --> 0:21:27.480
<v Speaker 1>each weekday starting at two pm Eastern on Apple car

0:21:27.560 --> 0:21:30.520
<v Speaker 1>Play and Android Auto with the Bloomberg Business Ad. You

0:21:30.560 --> 0:21:33.840
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0:21:33.880 --> 0:21:38.480
<v Speaker 1>New York station just say Alexa playing Bloomberg eleven thirty.

0:21:39.000 --> 0:21:40.840
<v Speaker 2>So we've been talking a lot about big tech this week.

0:21:40.840 --> 0:21:42.720
<v Speaker 2>We did see quite a rally as a result of

0:21:42.760 --> 0:21:45.359
<v Speaker 2>the big megacap tech names tech. Also, we've been talking

0:21:45.400 --> 0:21:49.119
<v Speaker 2>a lot about AI. Cisco is also an important company

0:21:49.119 --> 0:21:51.080
<v Speaker 2>that we keep checking in with. It's the biggest maker

0:21:51.119 --> 0:21:54.679
<v Speaker 2>of computer networking equipment of Bellweather for corporate tech spending.

0:21:54.760 --> 0:21:57.760
<v Speaker 2>Last month, when it reported earnings, the company CFO saying

0:21:57.760 --> 0:21:59.959
<v Speaker 2>that the company is seeing a strong rebound and spending

0:22:00.440 --> 0:22:04.400
<v Speaker 2>by corporations across all sectors and geographies. It's also benefiting

0:22:04.440 --> 0:22:07.440
<v Speaker 2>from spending on the machinery needed to support AI computing.

0:22:07.720 --> 0:22:09.479
<v Speaker 2>And then earlier this week we cut up with one

0:22:09.480 --> 0:22:12.959
<v Speaker 2>of the senior members of the Cisco executive team, Francus Suitis.

0:22:13.000 --> 0:22:15.800
<v Speaker 2>Today we have another member of that team joining us

0:22:15.800 --> 0:22:18.399
<v Speaker 2>from San Jose, California, where the company is based, is

0:22:18.440 --> 0:22:21.840
<v Speaker 2>Lilis san Toni, executive EVP and Chief Customer Experience Officer

0:22:21.880 --> 0:22:24.880
<v Speaker 2>at Cisco Systems. Liz, good to have you back with us.

0:22:24.880 --> 0:22:25.359
<v Speaker 2>How are you.

0:22:26.600 --> 0:22:28.760
<v Speaker 10>I'm doing great. Carol, good to be back as well.

0:22:28.800 --> 0:22:29.239
<v Speaker 10>How are you.

0:22:29.440 --> 0:22:31.639
<v Speaker 2>I'm doing well. Trying to keep up with the news flow.

0:22:31.720 --> 0:22:33.720
<v Speaker 2>There's a lot of AI stuff this week, which we're

0:22:33.720 --> 0:22:36.080
<v Speaker 2>going to talk about with you in a moment. You

0:22:36.160 --> 0:22:39.280
<v Speaker 2>do have a job change. You recently served as executive

0:22:39.320 --> 0:22:43.120
<v Speaker 2>EP Chief Strategy Officer. You also GM of Applications at Cisco.

0:22:43.520 --> 0:22:45.320
<v Speaker 2>You've been at the company a long time. You've got

0:22:45.320 --> 0:22:48.640
<v Speaker 2>a new job. Tell us about it and what kind

0:22:48.680 --> 0:22:52.200
<v Speaker 2>of vantage point this job now gives you and kind

0:22:52.200 --> 0:22:55.320
<v Speaker 2>of builds on your other experiences.

0:22:55.480 --> 0:22:59.399
<v Speaker 10>Yeah, I almost twenty five years at Cisco and always

0:22:59.400 --> 0:23:02.479
<v Speaker 10>in product of So this is absolutely new in terms

0:23:02.480 --> 0:23:06.200
<v Speaker 10>of going into customer experience where it's not just developing

0:23:06.280 --> 0:23:08.960
<v Speaker 10>a product, but it's also around how do we take

0:23:09.040 --> 0:23:12.160
<v Speaker 10>the customer through their entire journey from how they use

0:23:12.200 --> 0:23:15.760
<v Speaker 10>our product or how we support them. Customer experience is

0:23:15.800 --> 0:23:19.160
<v Speaker 10>about a third of Cisco's revenue. Probably not as well known,

0:23:19.640 --> 0:23:23.080
<v Speaker 10>but we are involved in every stage of the customer journey,

0:23:23.160 --> 0:23:26.080
<v Speaker 10>right right from when they purchase it to adopt it,

0:23:26.280 --> 0:23:29.359
<v Speaker 10>to the renewal life cycle to supporting it as well.

0:23:29.960 --> 0:23:33.399
<v Speaker 10>So I am, I would say, is bringing in the

0:23:34.880 --> 0:23:38.880
<v Speaker 10>product of opmini expertise, the relationship from product, bringing that

0:23:39.160 --> 0:23:43.919
<v Speaker 10>into this phase of customer experience and going back as

0:23:43.960 --> 0:23:45.919
<v Speaker 10>a full loop in terms of it gives me an

0:23:45.960 --> 0:23:50.760
<v Speaker 10>opportunity to bring that experience but also be an advocate

0:23:50.840 --> 0:23:53.280
<v Speaker 10>for the customer as they use our product and through

0:23:53.640 --> 0:23:57.000
<v Speaker 10>you know, kind of the full life cycle, something usually

0:23:57.280 --> 0:23:59.080
<v Speaker 10>I didn't get to see as much when I was

0:23:59.119 --> 0:23:59.920
<v Speaker 10>in productive oppment.

0:24:00.240 --> 0:24:01.959
<v Speaker 2>I have to say, I remember when I first met you.

0:24:02.359 --> 0:24:03.800
<v Speaker 2>What I loved about you is that you were in

0:24:03.840 --> 0:24:07.560
<v Speaker 2>product development too, that you understood the product right, what

0:24:07.680 --> 0:24:11.400
<v Speaker 2>goes into it, what's needed, you understand the core business,

0:24:11.520 --> 0:24:13.840
<v Speaker 2>and then being able to now talk with you know,

0:24:13.960 --> 0:24:16.240
<v Speaker 2>customers about what they need. What I want to ask

0:24:16.280 --> 0:24:19.199
<v Speaker 2>you is how often when you have a conversation with

0:24:19.280 --> 0:24:22.320
<v Speaker 2>customers does something AI related come up?

0:24:23.800 --> 0:24:26.480
<v Speaker 10>Pretty much all the time, because I was just I

0:24:26.560 --> 0:24:29.320
<v Speaker 10>just got back from New York late last night and

0:24:29.560 --> 0:24:32.800
<v Speaker 10>spend a week with customers, mostly in the financial sector,

0:24:33.359 --> 0:24:37.160
<v Speaker 10>and it really was, you know, every conversation is around

0:24:37.240 --> 0:24:40.760
<v Speaker 10>AI because what they want is they want us to

0:24:41.680 --> 0:24:44.040
<v Speaker 10>know them better than they know themselves, right, So what

0:24:44.080 --> 0:24:46.400
<v Speaker 10>does that mean? It's almost like, hey, Cisco, you've got

0:24:46.440 --> 0:24:48.800
<v Speaker 10>all of my data. We trust you with our data.

0:24:49.440 --> 0:24:51.600
<v Speaker 10>You've got this massive amount of data and you know

0:24:51.680 --> 0:24:54.960
<v Speaker 10>I'm paraphrasing them, Carol, But they're looking for us to

0:24:55.040 --> 0:24:59.879
<v Speaker 10>deliver like meaningful, curated and personal kind of purposeful experience

0:25:00.760 --> 0:25:04.400
<v Speaker 10>that accelerate the value of the technology that they purchased

0:25:04.440 --> 0:25:08.160
<v Speaker 10>from us. Right, So they're looking at us and going, yes,

0:25:08.240 --> 0:25:11.280
<v Speaker 10>you've got chatbots, you've got AI assistance, but now with

0:25:11.359 --> 0:25:15.760
<v Speaker 10>jen Ai, those can get a lot more sophisticated. And

0:25:16.440 --> 0:25:19.280
<v Speaker 10>they how do we enable them to get immediate and

0:25:19.359 --> 0:25:22.359
<v Speaker 10>maximize the value from the technology, but also how we

0:25:22.520 --> 0:25:25.720
<v Speaker 10>use this data that they have to keep their environments

0:25:25.800 --> 0:25:30.320
<v Speaker 10>highly resilient and secure as well. So they're looking for, Hey,

0:25:30.359 --> 0:25:34.400
<v Speaker 10>take the data, analyze in real time, contextualize it, give

0:25:34.440 --> 0:25:38.120
<v Speaker 10>me a personalized, tailored experience just for me. Now, think

0:25:38.119 --> 0:25:41.520
<v Speaker 10>about doing that across hundreds of thousands of customers, right, So,

0:25:41.560 --> 0:25:45.560
<v Speaker 10>a personalized experience, and that's what I hear from. You know,

0:25:45.600 --> 0:25:49.400
<v Speaker 10>go beyond transactional, be more proactive, get ahead of my issues.

0:25:49.920 --> 0:25:55.199
<v Speaker 10>You know, make the promise of predictive insights and recommendations work.

0:25:55.560 --> 0:25:57.960
<v Speaker 10>Those are all the things you know, when we talk

0:25:58.000 --> 0:26:02.080
<v Speaker 10>about the AI party. There's some real ROI driven both

0:26:02.119 --> 0:26:05.160
<v Speaker 10>for customers and us well in terms of real use

0:26:05.200 --> 0:26:05.840
<v Speaker 10>cases in AI.

0:26:06.080 --> 0:26:07.720
<v Speaker 2>Let me ask you what the financial folks that you

0:26:07.760 --> 0:26:10.639
<v Speaker 2>are talking to certainly are bread and butter here at Bloomberg,

0:26:10.720 --> 0:26:12.920
<v Speaker 2>and we think about the financial community so much. But

0:26:13.040 --> 0:26:16.679
<v Speaker 2>having said that, are they starting to see return on

0:26:16.840 --> 0:26:21.480
<v Speaker 2>investment in AI related purchases? Are they seeing it already?

0:26:22.840 --> 0:26:23.480
<v Speaker 2>It depends.

0:26:23.600 --> 0:26:27.600
<v Speaker 10>It depends on the on the technology, on the use cases.

0:26:27.880 --> 0:26:30.679
<v Speaker 10>And I would say it's a it's a mix, Carol,

0:26:30.840 --> 0:26:33.840
<v Speaker 10>because you know, we did this. We did an AI

0:26:33.960 --> 0:26:38.080
<v Speaker 10>readiness index last year. We just release or we will

0:26:38.119 --> 0:26:41.320
<v Speaker 10>release the new one a year later. And what we're

0:26:41.359 --> 0:26:45.720
<v Speaker 10>seeing is that in the six areas of strategy infrastructure,

0:26:45.960 --> 0:26:49.560
<v Speaker 10>whether it's data, governance, talent, and culture, only thirteen percent

0:26:49.600 --> 0:26:52.879
<v Speaker 10>of companies are really were really prepared for AI in

0:26:52.920 --> 0:26:56.199
<v Speaker 10>twenty twenty four, and that was a decrease from you

0:26:56.200 --> 0:26:58.600
<v Speaker 10>can say, you know, it's a little bit of a

0:26:58.680 --> 0:27:01.720
<v Speaker 10>decrease from twenty twenty three. So there is a gap

0:27:01.840 --> 0:27:05.960
<v Speaker 10>between the needs and the expectations. And it's not just

0:27:06.040 --> 0:27:10.199
<v Speaker 10>about the use cases. The networks are not equipped to

0:27:10.200 --> 0:27:14.480
<v Speaker 10>meet the AI workloads, so you've got to upgrade. Only

0:27:14.560 --> 0:27:17.200
<v Speaker 10>twenty one percent of organizations say they have the necessary

0:27:17.240 --> 0:27:20.560
<v Speaker 10>GPUs to meet the current and future AI demand, So

0:27:20.640 --> 0:27:24.560
<v Speaker 10>it feels like there's intent there, but it's taking a

0:27:24.680 --> 0:27:28.200
<v Speaker 10>lot longer to be able to implement it.

0:27:29.160 --> 0:27:31.320
<v Speaker 3>Hey Liz, good to see you again.

0:27:31.359 --> 0:27:31.560
<v Speaker 4>Tim.

0:27:31.600 --> 0:27:35.560
<v Speaker 6>Here I say, Tim, I'm curious about where you think

0:27:35.600 --> 0:27:38.239
<v Speaker 6>we are in this tech cycle. Given your more than

0:27:38.240 --> 0:27:41.920
<v Speaker 6>two decades of experience at Cisco. You weren't necessarily there,

0:27:42.200 --> 0:27:44.920
<v Speaker 6>you know, in the in the bulk of the nineties

0:27:44.960 --> 0:27:46.800
<v Speaker 6>when we saw the run up, but you were there

0:27:46.880 --> 0:27:49.200
<v Speaker 6>during part of when the bubble popped.

0:27:49.520 --> 0:27:51.280
<v Speaker 3>And I'm wondering if you can see any.

0:27:51.080 --> 0:27:54.680
<v Speaker 6>Parallels to right now with AI or if you think

0:27:54.680 --> 0:27:55.960
<v Speaker 6>this is something completely different.

0:27:57.600 --> 0:28:00.960
<v Speaker 10>I feel like this is quite different in terms of

0:28:01.000 --> 0:28:04.000
<v Speaker 10>the pace at which the technology is being developed and

0:28:04.040 --> 0:28:08.240
<v Speaker 10>being put out there. I haven't seen anything move at

0:28:08.280 --> 0:28:13.359
<v Speaker 10>this level of speed. You know. I'm constantly experimenting with

0:28:13.440 --> 0:28:16.240
<v Speaker 10>different kind of tools and capabilities, and I still feel

0:28:16.560 --> 0:28:19.240
<v Speaker 10>I'm far behind and I'm in the in the depth

0:28:19.280 --> 0:28:22.040
<v Speaker 10>of it it. But what I've seen is like with

0:28:22.280 --> 0:28:25.719
<v Speaker 10>the vast majority of our customers, there is a gap

0:28:25.760 --> 0:28:31.439
<v Speaker 10>between the technology that's available and going from experimenting with

0:28:31.560 --> 0:28:34.760
<v Speaker 10>something to real use cases. And I think that for

0:28:34.800 --> 0:28:38.000
<v Speaker 10>the vast majority of our customers, they're still in that

0:28:38.200 --> 0:28:42.680
<v Speaker 10>early part of the real use cases and does go on.

0:28:42.640 --> 0:28:43.200
<v Speaker 4>For a while.

0:28:43.280 --> 0:28:45.840
<v Speaker 2>List do you think there's this kind of experimental phase

0:28:46.400 --> 0:28:48.040
<v Speaker 2>goes on for a while.

0:28:49.240 --> 0:28:52.360
<v Speaker 10>I would say twenty twenty five we should see some

0:28:52.520 --> 0:28:55.000
<v Speaker 10>a little bit more of a you know, where there's

0:28:55.040 --> 0:28:58.080
<v Speaker 10>a curated set of use cases, whether that's revenue generation,

0:28:58.240 --> 0:29:01.240
<v Speaker 10>whether that's automation or efficient and see I would expect

0:29:01.320 --> 0:29:05.320
<v Speaker 10>that to pick up Carol in twenty twenty five. Will

0:29:05.360 --> 0:29:08.040
<v Speaker 10>it reach like a big hockey stick? I don't think so.

0:29:08.760 --> 0:29:12.120
<v Speaker 10>I think it's now where we need to show kind

0:29:12.160 --> 0:29:15.400
<v Speaker 10>of how do we how we actually measured this? And

0:29:15.440 --> 0:29:18.000
<v Speaker 10>not everything is quantifiable, but you need to have some

0:29:18.200 --> 0:29:21.560
<v Speaker 10>quantifiable use cases along with the others.

0:29:21.760 --> 0:29:25.040
<v Speaker 2>And it's also the pressure from.

0:29:25.160 --> 0:29:27.720
<v Speaker 10>C suite and our boards as well, right they expect

0:29:27.720 --> 0:29:30.080
<v Speaker 10>a lot of this to happen immediately, and some of

0:29:30.120 --> 0:29:32.880
<v Speaker 10>this is long term, you know, return on investment?

0:29:33.720 --> 0:29:34.240
<v Speaker 3>How long?

0:29:34.600 --> 0:29:37.280
<v Speaker 6>Like are we talking years here? We talk a lot

0:29:37.320 --> 0:29:40.080
<v Speaker 6>about CAPEX, especially with the hyperscalers, but when you think

0:29:40.080 --> 0:29:43.240
<v Speaker 6>about other infrastructure investments, like you know, making an investment

0:29:43.240 --> 0:29:45.160
<v Speaker 6>with a company like Cisco, how long does it take

0:29:45.160 --> 0:29:46.920
<v Speaker 6>for something like that to pay off for your clients?

0:29:48.080 --> 0:29:50.840
<v Speaker 10>I would say in the areas of what we're talking

0:29:50.880 --> 0:29:55.280
<v Speaker 10>about around customer support, for example, and how we're able

0:29:55.360 --> 0:29:59.120
<v Speaker 10>to help keep their environments much more resilient. I see

0:29:59.120 --> 0:30:02.200
<v Speaker 10>that in more for twelve to twenty four months, if

0:30:02.200 --> 0:30:05.800
<v Speaker 10>you're looking at revenue generation and you know kind of

0:30:05.840 --> 0:30:08.959
<v Speaker 10>how do you get more competitive for their end customers.

0:30:09.160 --> 0:30:11.440
<v Speaker 10>I think that's a little bit longer. That's more in

0:30:11.560 --> 0:30:12.920
<v Speaker 10>like two plus years out.

0:30:14.040 --> 0:30:14.560
<v Speaker 2>Hey, can I.

0:30:14.560 --> 0:30:17.160
<v Speaker 10>Ask you automation and efficiency? Yeah, I would say twelve

0:30:17.240 --> 0:30:18.480
<v Speaker 10>to twenty four months for sure.

0:30:18.560 --> 0:30:20.720
<v Speaker 2>You know, Tim and I were recently at the Schwab

0:30:21.240 --> 0:30:26.080
<v Speaker 2>Impact Massive financial conference out in San Francisco, and it

0:30:26.120 --> 0:30:28.960
<v Speaker 2>was all with registered investment advisors and all of the

0:30:28.960 --> 0:30:32.160
<v Speaker 2>companies that service them, and I was involved in a

0:30:32.200 --> 0:30:34.080
<v Speaker 2>panel that was all on AI and one of the

0:30:34.080 --> 0:30:37.240
<v Speaker 2>things that came up was autonomous agents, which is something

0:30:37.280 --> 0:30:39.840
<v Speaker 2>I haven't heard about, and I feel like this is

0:30:39.880 --> 0:30:41.120
<v Speaker 2>going to be something that's going to be a big

0:30:41.160 --> 0:30:43.720
<v Speaker 2>part of our conversation in twenty twenty five. We've got

0:30:43.720 --> 0:30:45.320
<v Speaker 2>about a minute or so a minute and a half

0:30:45.400 --> 0:30:48.200
<v Speaker 2>left here. What do we need to know about what

0:30:48.280 --> 0:30:52.440
<v Speaker 2>that is in terms of AI and how that kind

0:30:52.440 --> 0:30:53.080
<v Speaker 2>of fits it?

0:30:53.760 --> 0:30:56.840
<v Speaker 10>So think about use cases like summarizations very easy, right,

0:30:56.960 --> 0:31:00.600
<v Speaker 10>Those are AI assisted. Think about like checkbots for example,

0:31:00.720 --> 0:31:03.760
<v Speaker 10>those are augmented AI. Think about in the future where

0:31:03.880 --> 0:31:05.680
<v Speaker 10>some of not just some of the tasks, but some

0:31:05.720 --> 0:31:09.560
<v Speaker 10>of the jobs that are being done can be where

0:31:09.600 --> 0:31:12.280
<v Speaker 10>you can where an agent can think, reason and make

0:31:12.320 --> 0:31:16.320
<v Speaker 10>independent decisions, not doesn't need to necessarily say that you've

0:31:16.400 --> 0:31:18.920
<v Speaker 10>trained it to make that it's almost human like and

0:31:19.000 --> 0:31:22.240
<v Speaker 10>could take actions. So I think that's an example would

0:31:22.280 --> 0:31:24.600
<v Speaker 10>be is you know, we've talked about self heeling networks

0:31:24.600 --> 0:31:28.160
<v Speaker 10>for a long time. You can identify potential issues and

0:31:28.720 --> 0:31:33.920
<v Speaker 10>resolve them autonomously without any human intervention. We're experimenting with

0:31:33.960 --> 0:31:34.600
<v Speaker 10>that right now.

0:31:35.120 --> 0:31:35.760
<v Speaker 2>How's it going?

0:31:37.960 --> 0:31:42.480
<v Speaker 10>I would say, is accuracy ethical AI? All of those

0:31:42.960 --> 0:31:46.680
<v Speaker 10>become a much bigger deal when you're talking about autonomous

0:31:46.720 --> 0:31:50.960
<v Speaker 10>agent without any human intervention. So I think that would

0:31:51.040 --> 0:31:53.720
<v Speaker 10>take a little bit longer because we want to make

0:31:53.760 --> 0:31:56.360
<v Speaker 10>sure that ethical AI plays a big part of it

0:31:56.440 --> 0:31:59.680
<v Speaker 10>so that we can continue to keep what customers you know,

0:32:00.400 --> 0:32:03.480
<v Speaker 10>to do. We want to hold their trust in us.

0:32:04.120 --> 0:32:06.080
<v Speaker 2>Yeah, listen, I just got chills up my spine. But

0:32:06.080 --> 0:32:07.720
<v Speaker 2>I think about we had a conversation with our Linda

0:32:07.720 --> 0:32:11.000
<v Speaker 2>Wanner earlier about the importance of an abundance of the

0:32:11.080 --> 0:32:14.480
<v Speaker 2>right data to keep AI development moving forward, and especially

0:32:14.520 --> 0:32:17.760
<v Speaker 2>when we talk about agents and AI. I think that's

0:32:17.760 --> 0:32:19.720
<v Speaker 2>going to be super important. I know we'll be coming

0:32:19.760 --> 0:32:23.000
<v Speaker 2>back to you. Congratulations on the new job, and look

0:32:23.040 --> 0:32:26.280
<v Speaker 2>forward to next time. Listen, Tony executivice President, chief Customer

0:32:26.520 --> 0:32:29.760
<v Speaker 2>Experience Officer at Cisco Systems. Tim, we're driving towards the clothes.

0:32:30.040 --> 0:32:33.000
<v Speaker 6>I want a little chatbot that can kind of automatically

0:32:33.000 --> 0:32:34.680
<v Speaker 6>do our script that we do every day.

0:32:34.720 --> 0:32:37.160
<v Speaker 2>I want that one. I'm hoping that I don't want

0:32:37.160 --> 0:32:39.160
<v Speaker 2>one that can be oh, breaking news. Let me break

0:32:39.160 --> 0:32:40.600
<v Speaker 2>it for you.

0:32:40.080 --> 0:32:43.680
<v Speaker 3>Exactly read us. We got to break the news.

0:32:44.560 --> 0:32:47.840
<v Speaker 2>Stick around everybody. You're watching Bloomberg Business Week. This is Bloomberg.

0:32:49.360 --> 0:32:53.960
<v Speaker 8>Mack journal about you.

0:32:54.000 --> 0:32:58.880
<v Speaker 10>Let me drive none please, I.

0:33:01.360 --> 0:33:02.080
<v Speaker 2>Don't want to drive.

0:33:02.080 --> 0:33:06.200
<v Speaker 4>It's a good question, a good time.

0:33:09.000 --> 0:33:15.600
<v Speaker 7>This is the drive to the Globe. Well on Bloomberg Radio.

0:33:15.960 --> 0:33:19.440
<v Speaker 2>All right, everybody, we are just under all about eighteen

0:33:19.440 --> 0:33:22.680
<v Speaker 2>eighteen and a half minutes left in today's trading, So

0:33:22.720 --> 0:33:26.200
<v Speaker 2>she's getting ready to wrap up the trade and the week. Yeah,

0:33:26.240 --> 0:33:28.760
<v Speaker 2>we are, as Denise just mentioned, well, off our highs

0:33:28.760 --> 0:33:31.240
<v Speaker 2>of the session. Still the Nasdaq one hundred the standout,

0:33:31.280 --> 0:33:34.240
<v Speaker 2>thank you very much, Broadcom really giving the juice to

0:33:34.680 --> 0:33:35.720
<v Speaker 2>certainly that name.

0:33:35.800 --> 0:33:36.400
<v Speaker 3>Marvel too.

0:33:36.680 --> 0:33:38.680
<v Speaker 2>Yeah, well everybody, right, the peers.

0:33:38.800 --> 0:33:41.040
<v Speaker 6>Well they're peers, yes, But as I will say in

0:33:41.080 --> 0:33:44.640
<v Speaker 6>my decliners today, not everybody in this space is having

0:33:44.640 --> 0:33:45.040
<v Speaker 6>a good day.

0:33:45.160 --> 0:33:47.240
<v Speaker 2>And some of the popped initially and then kind.

0:33:47.120 --> 0:33:48.920
<v Speaker 6>Of yeah, and media popped initially, but now it's down

0:33:48.960 --> 0:33:51.520
<v Speaker 6>more than two percent. Marvel is up ten point six percent.

0:33:51.560 --> 0:33:53.720
<v Speaker 6>This is a one hundred billion dollar company that has

0:33:53.720 --> 0:33:57.960
<v Speaker 6>basically performed the same as a Broadcom this year.

0:33:58.040 --> 0:34:00.000
<v Speaker 3>Marvel interesting, right, Yeah, it's.

0:33:59.840 --> 0:34:01.640
<v Speaker 2>Really I feel like all of a sudden, there's like

0:34:01.880 --> 0:34:05.000
<v Speaker 2>Chip related, AAR related company we haven't in the show,

0:34:05.040 --> 0:34:06.280
<v Speaker 2>but that we haven't talked about a lot, and then

0:34:06.320 --> 0:34:08.640
<v Speaker 2>all of a sudden, the Shepley front and center. Hey,

0:34:08.680 --> 0:34:11.120
<v Speaker 2>another thing that's been front and center is private markets.

0:34:11.239 --> 0:34:14.560
<v Speaker 6>Yeah, kind of understanding what's happening with the private markets

0:34:14.560 --> 0:34:17.440
<v Speaker 6>as we get into a new year, a new regime.

0:34:18.400 --> 0:34:21.080
<v Speaker 6>Understanding interest rates next year, because that certainly has a

0:34:21.080 --> 0:34:24.440
<v Speaker 6>big effect. Let's get to Eric Hirsh, co CEO at

0:34:24.480 --> 0:34:28.640
<v Speaker 6>the investment management firm Hamilton Lane. It specializes in private markets.

0:34:28.760 --> 0:34:31.560
<v Speaker 6>Eric joins us from Pennsylvania. Eric, good to have you

0:34:31.600 --> 0:34:32.440
<v Speaker 6>with us this afternoon.

0:34:32.440 --> 0:34:34.520
<v Speaker 3>How are you great?

0:34:34.520 --> 0:34:35.799
<v Speaker 4>Tim Carrol, Nice to be with you.

0:34:36.000 --> 0:34:37.400
<v Speaker 2>Nice to see you and hear you again.

0:34:37.600 --> 0:34:40.880
<v Speaker 6>Hey, Eric, how are you thinking about what was the

0:34:40.920 --> 0:34:42.880
<v Speaker 6>year before we get to twenty twenty five? What was

0:34:42.920 --> 0:34:45.439
<v Speaker 6>the year that was twenty twenty four when it came

0:34:45.520 --> 0:34:50.600
<v Speaker 6>to the alternative investments the private markets, Given that we

0:34:50.640 --> 0:34:53.360
<v Speaker 6>didn't get as many interest rate cuts as many investors

0:34:53.400 --> 0:34:53.759
<v Speaker 6>a year.

0:34:53.680 --> 0:34:57.480
<v Speaker 11>Ago thought we would, I think it was a mixed year.

0:34:57.520 --> 0:34:59.440
<v Speaker 11>So I think if you look across the asset class,

0:35:00.080 --> 0:35:03.000
<v Speaker 11>the private credit sector had a very strong year, a

0:35:03.040 --> 0:35:05.800
<v Speaker 11>lot of capital raise, a lot of capital deployed.

0:35:05.960 --> 0:35:07.520
<v Speaker 4>Very very strong performance.

0:35:07.880 --> 0:35:10.480
<v Speaker 11>The equity side of the business has sort of lagged

0:35:10.480 --> 0:35:13.200
<v Speaker 11>sort of the public markets. When the public markets are

0:35:13.239 --> 0:35:15.320
<v Speaker 11>kind of on fire, as they've really been for the

0:35:15.360 --> 0:35:19.040
<v Speaker 11>most of this year, private equity, again, longer asset class,

0:35:19.080 --> 0:35:22.080
<v Speaker 11>longer duration, kind of struggles to keep pace. And you

0:35:22.120 --> 0:35:24.359
<v Speaker 11>certainly saw that. So performance on a year to year

0:35:24.400 --> 0:35:26.719
<v Speaker 11>basis relative to the public markets, I think was a

0:35:26.719 --> 0:35:30.839
<v Speaker 11>little bit disappointing. Infrastructure posted some good results, and so

0:35:30.920 --> 0:35:33.239
<v Speaker 11>again if you look across the totality a little bit

0:35:33.239 --> 0:35:34.200
<v Speaker 11>of a mixed situation.

0:35:34.840 --> 0:35:37.000
<v Speaker 2>Hey, you know, I think about this column especially when

0:35:37.040 --> 0:35:39.359
<v Speaker 2>it comes to private equity, which has been under some

0:35:39.440 --> 0:35:41.279
<v Speaker 2>pressure over the last couple of years because it hasn't

0:35:41.280 --> 0:35:44.279
<v Speaker 2>been able to exit right. The exit strategy and the

0:35:44.320 --> 0:35:48.640
<v Speaker 2>ability to return you know, money and returns to investors.

0:35:48.880 --> 0:35:51.960
<v Speaker 2>Our Allison Schreeger wrote a Bloomberg column over the summer,

0:35:52.040 --> 0:35:54.440
<v Speaker 2>the private equity Bubble us about to deflate again, an

0:35:54.440 --> 0:35:58.040
<v Speaker 2>opinion column, but she talked about, you know, whether valuations

0:35:58.040 --> 0:35:59.960
<v Speaker 2>fall suddenly or gradually the industries do for a rect

0:36:00.320 --> 0:36:02.759
<v Speaker 2>and the consequences for the economy or dire I mean,

0:36:02.800 --> 0:36:06.120
<v Speaker 2>when you can't really price something in a market, that's

0:36:06.120 --> 0:36:08.240
<v Speaker 2>a problem.

0:36:08.680 --> 0:36:11.080
<v Speaker 11>So let's break it down. I think the exit piece

0:36:11.160 --> 0:36:14.759
<v Speaker 11>has been a little bit misunderstood. So why haven't we

0:36:14.800 --> 0:36:17.680
<v Speaker 11>seen a lot of assets trading? The reality is is

0:36:17.719 --> 0:36:20.640
<v Speaker 11>that because most of the assets are still relatively young.

0:36:21.040 --> 0:36:23.200
<v Speaker 11>If you think back when we saw a huge surge

0:36:23.239 --> 0:36:25.719
<v Speaker 11>in deal volume, it was right in the middle of

0:36:25.760 --> 0:36:28.960
<v Speaker 11>COVID and pricing wasn't cheap then, So you had a

0:36:28.960 --> 0:36:32.040
<v Speaker 11>lot of assets that were acquired at fairly full valuations

0:36:32.360 --> 0:36:34.680
<v Speaker 11>and if you think about our industry over a long

0:36:34.760 --> 0:36:39.240
<v Speaker 11>time period, it's averaging about five year duration from time

0:36:39.280 --> 0:36:42.560
<v Speaker 11>to buy to time to sell. So we really are

0:36:42.680 --> 0:36:45.480
<v Speaker 11>now just kind of coming into that window. And if

0:36:45.520 --> 0:36:48.640
<v Speaker 11>you think about how private equity is actually generating returns

0:36:48.719 --> 0:36:51.320
<v Speaker 11>right now, it's not that they're buying super cheap and

0:36:51.360 --> 0:36:54.799
<v Speaker 11>it's definitely not that they're super leveraging these assets. They

0:36:54.800 --> 0:36:57.920
<v Speaker 11>have to fundamentally grow earnings and that takes some time.

0:36:58.360 --> 0:37:01.160
<v Speaker 11>So that, to me is really the biggest issue of

0:37:01.440 --> 0:37:03.920
<v Speaker 11>why haven't we seen a lot of liquidity. It's because

0:37:03.960 --> 0:37:07.359
<v Speaker 11>the assets just simply haven't fully ripened yet. I think

0:37:07.400 --> 0:37:09.640
<v Speaker 11>we will start to see more of that next year. Now,

0:37:09.680 --> 0:37:12.839
<v Speaker 11>the second part I would say is you want more stability.

0:37:13.239 --> 0:37:15.799
<v Speaker 11>This year has not been a particularly stable year. So

0:37:16.160 --> 0:37:19.480
<v Speaker 11>let's leave aside where the public equity markets have performed strong.

0:37:19.920 --> 0:37:22.600
<v Speaker 11>We've had tremendous amount of geopolitical uncertainty. We've had a

0:37:22.600 --> 0:37:25.680
<v Speaker 11>whole uncertainty in this country around the election. What was

0:37:25.719 --> 0:37:28.360
<v Speaker 11>going to happen with that, and so buyers and sellers

0:37:28.360 --> 0:37:30.200
<v Speaker 11>we're kind of having a bit of a standoff on

0:37:30.800 --> 0:37:33.560
<v Speaker 11>is today today the pulled trigger and what you saw

0:37:33.800 --> 0:37:36.400
<v Speaker 11>was no it's not. I think now that we at

0:37:36.440 --> 0:37:39.359
<v Speaker 11>least know the election outcome, now that you see some

0:37:39.480 --> 0:37:43.040
<v Speaker 11>real signs that are encouraging on potentially ending some of

0:37:43.080 --> 0:37:46.680
<v Speaker 11>the geopolitical instability, I think you're gonna see buyers and

0:37:46.719 --> 0:37:49.920
<v Speaker 11>sellers get more aligned, and so I think you kind

0:37:49.960 --> 0:37:53.440
<v Speaker 11>of combine all that together, coupling with the aging of

0:37:53.480 --> 0:37:55.160
<v Speaker 11>the assets, and I think you're going to see a

0:37:55.160 --> 0:37:56.759
<v Speaker 11>lot more exit activity next year.

0:37:56.840 --> 0:37:59.040
<v Speaker 2>All right. Interesting, you know we have heard about maybe

0:37:59.040 --> 0:38:03.160
<v Speaker 2>an opticket M and a overall and getting out. Having

0:38:03.200 --> 0:38:05.080
<v Speaker 2>said that, I mean we've had a you know, you

0:38:05.160 --> 0:38:07.120
<v Speaker 2>look at the gains that we've seen in the major

0:38:07.560 --> 0:38:11.359
<v Speaker 2>equity averages. I mean, it's been a really strong year.

0:38:12.040 --> 0:38:14.120
<v Speaker 2>If that doesn't happen, and that's two strong years for

0:38:14.160 --> 0:38:16.520
<v Speaker 2>the S and P five hundred and that doesn't continue

0:38:16.880 --> 0:38:19.440
<v Speaker 2>in twenty twenty five, is that problematic for the exit.

0:38:21.040 --> 0:38:22.680
<v Speaker 11>I think one of the things we hear from investors

0:38:22.760 --> 0:38:25.440
<v Speaker 11>is that everyone's getting a little bit more sophisticated, and

0:38:25.520 --> 0:38:28.200
<v Speaker 11>so they're saying, well, the S and P five hundred, Yes,

0:38:28.280 --> 0:38:32.320
<v Speaker 11>is an index, had an amazing run, but it's really

0:38:32.400 --> 0:38:34.799
<v Speaker 11>driven by still a small number of businesses.

0:38:35.200 --> 0:38:36.880
<v Speaker 4>And I think when you look at kind of this.

0:38:37.080 --> 0:38:43.120
<v Speaker 11>Over reliance on index passive sort of cheap public equity strategies.

0:38:43.400 --> 0:38:45.399
<v Speaker 11>I think a lot of investors are getting a little

0:38:45.400 --> 0:38:49.080
<v Speaker 11>bit more sober on how concentrated their portfolios are on

0:38:49.120 --> 0:38:53.120
<v Speaker 11>an underlying basis, and so I think the driving of

0:38:53.160 --> 0:38:57.480
<v Speaker 11>the performance notwithstanding, I think there's some real hesitancy about

0:38:57.520 --> 0:38:58.600
<v Speaker 11>the concentration.

0:38:59.520 --> 0:38:59.840
<v Speaker 4>That is.

0:39:00.000 --> 0:39:01.760
<v Speaker 11>One of the things we're seeing is a real drive

0:39:01.880 --> 0:39:04.960
<v Speaker 11>into the private markets is that they're simply looking for diversity.

0:39:05.280 --> 0:39:07.200
<v Speaker 11>It's not even so much that they believe that they're

0:39:07.239 --> 0:39:10.400
<v Speaker 11>going to make way better returns. It's just simply they

0:39:10.400 --> 0:39:12.000
<v Speaker 11>don't want all their eggs in one basket.

0:39:12.320 --> 0:39:13.960
<v Speaker 2>I will point out about three hundred and sixty two

0:39:14.040 --> 0:39:15.520
<v Speaker 2>names in the S and P five hundred though or

0:39:15.600 --> 0:39:17.200
<v Speaker 2>higher this year, and it's pretty broad. You know, we

0:39:17.239 --> 0:39:18.680
<v Speaker 2>did see some broadening out of the market.

0:39:18.920 --> 0:39:21.600
<v Speaker 3>Yeah, we did. I wonder what things look like.

0:39:21.600 --> 0:39:24.640
<v Speaker 6>You already mentioned a new administration and some potential effects

0:39:24.640 --> 0:39:28.440
<v Speaker 6>of that starting January twentieth. What about on the regulatory

0:39:28.480 --> 0:39:30.400
<v Speaker 6>front and on the interest rate front? How does that

0:39:30.440 --> 0:39:33.080
<v Speaker 6>look for your world in the privates.

0:39:34.800 --> 0:39:36.240
<v Speaker 4>So let's take those pieces.

0:39:36.280 --> 0:39:40.279
<v Speaker 11>I think on the interest rate side, I'm not expecting

0:39:40.320 --> 0:39:43.399
<v Speaker 11>to see a ton of movement either way. I think

0:39:43.440 --> 0:39:46.800
<v Speaker 11>you still are seeing some inflationary signs. Yes, it's cooling,

0:39:46.880 --> 0:39:49.319
<v Speaker 11>but I don't think any of us would argue that

0:39:49.719 --> 0:39:53.120
<v Speaker 11>the world has gotten cheap today, and so I'm not

0:39:53.160 --> 0:39:55.759
<v Speaker 11>sure that we're going to see enormous pressure to kind

0:39:55.800 --> 0:39:57.160
<v Speaker 11>of further cut rates or.

0:39:57.160 --> 0:39:58.319
<v Speaker 4>Cut them dramatically.

0:39:58.440 --> 0:40:00.719
<v Speaker 11>So I think that feels like we're in a bit

0:40:00.719 --> 0:40:04.759
<v Speaker 11>of a status quo situation. On the regulatory side, I

0:40:04.800 --> 0:40:07.560
<v Speaker 11>think where you could see some potential easing up, yes,

0:40:07.640 --> 0:40:11.640
<v Speaker 11>around the M and a market. Yes, potentially around sort

0:40:11.680 --> 0:40:16.759
<v Speaker 11>of a less onerous sort of merger doctrine that could

0:40:16.800 --> 0:40:19.680
<v Speaker 11>certainly do a little bit around the edges. I think

0:40:19.719 --> 0:40:22.880
<v Speaker 11>the space to watch is really what the administration does,

0:40:22.920 --> 0:40:26.160
<v Speaker 11>if anything, as it relates to sort of opening up

0:40:26.239 --> 0:40:30.160
<v Speaker 11>access to the asset class even more to the individual investor.

0:40:30.600 --> 0:40:32.200
<v Speaker 4>So I'm not even talking sort of.

0:40:32.160 --> 0:40:34.959
<v Speaker 11>A four to h one k access side, but even

0:40:34.960 --> 0:40:37.040
<v Speaker 11>think about lightening up a little bit so that you

0:40:37.040 --> 0:40:40.400
<v Speaker 11>could see a much more easy inclusion of private markets

0:40:40.440 --> 0:40:41.960
<v Speaker 11>and things like target date funds.

0:40:44.360 --> 0:40:46.759
<v Speaker 2>Yeah, now, listen, you know people are constantly seeking for

0:40:46.800 --> 0:40:49.600
<v Speaker 2>some outperformance. I think many would argue we a little

0:40:49.600 --> 0:40:53.040
<v Speaker 2>bit more oversight too though, in transparency within the private markets,

0:40:53.080 --> 0:40:56.160
<v Speaker 2>to make sure that you know everything is is clear,

0:40:56.239 --> 0:40:58.160
<v Speaker 2>especially when you're talking about retirement.

0:40:58.400 --> 0:41:00.200
<v Speaker 6>Yeah, and I don't know if there's necessary you know,

0:41:01.239 --> 0:41:03.360
<v Speaker 6>who is it. Warren Buffett always says, only invest in

0:41:03.400 --> 0:41:05.920
<v Speaker 6>what you can understand. Yeah, and I think there are

0:41:05.920 --> 0:41:07.319
<v Speaker 6>some concerns, Sir Peter want you to.

0:41:07.280 --> 0:41:10.040
<v Speaker 2>Say that, like a right fidelity too right? Yeah, interesting

0:41:10.080 --> 0:41:13.160
<v Speaker 2>stuff that always appreciate his perspective. Eric Kirsh, co Chief

0:41:13.160 --> 0:41:14.520
<v Speaker 2>executive Officer at Hamilton Lane.

0:41:15.040 --> 0:41:19.680
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