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Speaker 1: Bloomberg Audio Studios, podcasts, radio news.

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Speaker 2: From the Heart where Innovation, money and power. Collie in Silicon.

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Speaker 3: Valley, NBN.

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Speaker 4: This is Bloomberg Technology with Caroline Hyde and Ed Ludlove.

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Speaker 5: I'm Caroline Heid at Bloomberg's weltad quarters in New York.

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Speaker 5: Ed Ludlow he is off. This is Bloomberg Technology coming up.

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Speaker 1: All eyes on Nvidia as.

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Speaker 5: The one point seven trillion dollar chip company. It gears

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Speaker 5: up for earnings results after the bell. Full coverage ahead,

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Speaker 5: plus we stick with earnings and Palo Alto Networks heading

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Speaker 5: for its biggest drop ever as customers face spending fatigue

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Speaker 5: in cybersecurity will bring you those numbers. And Google looks

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Speaker 5: to build an overen source AI community with the launch

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Speaker 5: of its new model Gemma, built on the same technology

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Speaker 5: as it's Gemini LLM. We'll discuss that and so much

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Speaker 5: more throughout the hour, but first let's check in on

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Speaker 5: these markets, because look, we are seeing a little bit

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Speaker 5: fatigue when we call it in terms of purchasing of

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Speaker 5: tech stocks.

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Speaker 1: Right now.

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Speaker 5: We are all waiting and watching to see whether the

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Speaker 5: AI hype can be borne out in the.

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Speaker 1: Reality of revenue.

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Speaker 5: Uptic over it in video Nazdac off by six tens percent.

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Speaker 5: Interesting Chinese stocks moving a little bit higher on those

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Speaker 5: US traded ones that ultimately is being seen as China

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Speaker 5: is putting in place and restrictions on selling maasbely getting

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Speaker 5: out of certain stocks and the open and the close

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Speaker 5: of their trade.

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Speaker 1: Could this support the market in the stock.

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Speaker 5: Inflow and see some sort of rebound that's been reflected

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Speaker 5: here in the US trade. I'm looking at bitcoin under

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Speaker 5: pressure just by one point eight percent. We're still at

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Speaker 5: about a fifty one thousand dollars handle, but still a

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Speaker 5: little bit of risk aversion today that sinks into that

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Speaker 5: particular area of risk assets.

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Speaker 1: Move on and have a look at one of the

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Speaker 1: individual movers are doing on a.

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Speaker 5: Day like today, because look, I've got to focus on

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Speaker 5: what's been happening more broadly on the world of palle

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Speaker 5: Alt networks as you see twenty six percent lower, a

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Speaker 5: quarter of its market capitalization erased on one day, as

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Speaker 5: they look actually on their fiscal quarter that they just

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Speaker 5: had lived up to expectations, but their forecast is where

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Speaker 5: we're worried about bytes technology. Interesting one traded over in

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Speaker 5: the UK off by more than nine percent as the

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Speaker 5: CEO suddenly steps down as he said, they's been making

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Speaker 5: some trades and not been telling executives or shareholders. That's

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Speaker 5: a UKAI and cyber and software company to keep an

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Speaker 5: eye on. And in Vidia, as we say, down some

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Speaker 5: two percent ahead of their earnings. Look, we are all

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Speaker 5: waiting and watching as to whether this one point seven

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Speaker 5: trillion dollar company can live up to the two hundred

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Speaker 5: percent growth in revenue that market is anticipating. Kunjin Sabani

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Speaker 5: is here with us. I'm so policed to say, Bloomberg

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Speaker 5: Intelligence More and Nvidia and just tell us a little

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Speaker 5: bit ultimately where the warriors. Has the market priced in

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Speaker 5: the right sort of level of growth for this earnings number?

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Speaker 6: Definitely? I mean, look the market the stock is price

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Speaker 6: for perfection, and we again expect a robust print and guide.

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Speaker 6: The supply has come in strong. Lead times have shrunk,

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Speaker 6: but so has the demand and continues to still outface supply,

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Speaker 6: especially as momentum in enterprise AI spending continues to rise,

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Speaker 6: so that increases the odds of another beaten rise.

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Speaker 5: And they are integral to AI infrastructure. They are integral

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Speaker 5: to building out of AI models. What's interesting though, is

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Speaker 5: in the past China has been integral to it.

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Speaker 1: Are we likely to get any guidance.

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Speaker 5: On how much geopolitics still affects the business and how

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Speaker 5: much they can sell ince that country.

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Speaker 6: Yes, I mean recently, you know, Jensen has been sort

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Speaker 6: of on a world whore meeting with heads of different

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Speaker 6: governments and different geographies, including China. So we do expect

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Speaker 6: some kind of commentary on that. The numbers for this

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Speaker 6: quarter have been dealers that China will be significantly lower

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Speaker 6: than what we have seen in the past, but in

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Speaker 6: the near term we think they can offset the demand

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Speaker 6: that they could have shipped to China by shipping to

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Speaker 6: other regions, which again continue to see significant increase in demand.

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Speaker 5: We will see how all of that lives off. I mean, really, Kunjen.

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Speaker 5: What's been so interesting has been some of the take

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Speaker 5: from other analysts out there today, Scott Rubner, Goldman Sachs.

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Speaker 5: What he's saying in Vidio is the most important stock

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Speaker 5: on planet Earth. We'll see how you analyze that stock

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Speaker 5: a little bit later. Being meg Intelligence analyst Punchin Sabani,

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Speaker 5: thank you so much for the breakdown ahead of those

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Speaker 5: numbers after the bell.

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Speaker 1: But let's make this broader.

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Speaker 5: Let's see how this particular stock fits in with the

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Speaker 5: rest of the industry group and indeed markets more generally

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Speaker 5: so pleased to welcome Chris and Bitterly, City Group Wealth,

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Speaker 5: head of Investment Solutions to the show and Kristin. When

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Speaker 5: you think about the most important stock on planet Earth,

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Speaker 5: I mean.

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Speaker 1: Is this the bell weather?

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Speaker 5: Do we sort of throw all the FED concerns and

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Speaker 5: talk and print that we're going to get from FED

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Speaker 5: minutes out the window.

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Speaker 7: This is clearly the key catalyst, at least for today

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Speaker 7: and maybe this week. But I think, look, this is

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Speaker 7: earnings after the close today. It's really about whether or

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Speaker 7: not this AI story has more legs in terms of

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Speaker 7: the momentum that we've seen in the market. I think

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Speaker 7: one of the things that we're looking at though, is

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Speaker 7: we can talk about the Magnificent seven, we can talk

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Speaker 7: about the concentration in market breadth, but it has been

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Speaker 7: backed up by delivering superior earnings. And when you have

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Speaker 7: earnings growth that's in the ballpark of twenty five percent plus,

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Speaker 7: it is something that actually compels the valuations that we

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Speaker 7: see and actually continued inflows into these companies.

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Speaker 5: Some might say actually in Vidio remarkably cheap in comparison

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Speaker 5: to where we've seen in terms of the run up

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Speaker 5: of the overall share price. But the spillover effects here,

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Speaker 5: the fact that people are looking out for anything that

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Speaker 5: has AI in its name. Many have felt that it's

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Speaker 5: kind of a rerun of crypto in some way, But

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Speaker 5: are they justified from your perspective. More broadly, on a

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Speaker 5: macro perspective, Walt productivity is going to be born out

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Speaker 5: for these companies.

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Speaker 7: I think when we look at these very large companies

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Speaker 7: that have performed quite well, we have to remember just

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Speaker 7: going back to twenty twenty two, they did not perform

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Speaker 7: well at all, So you were saying quite the opposite

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Speaker 7: story where you saw declines of fifty sixty plus percent. Now,

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Speaker 7: looking at this, like I said, it is backed up

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Speaker 7: by earnings. You're looking at the Magnificent seven represent close

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Speaker 7: to twenty percent of the earnings contribution of the US

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Speaker 7: equity market. We're only going back to twenty seventeen it

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Speaker 7: was five percent, So they have delivered in earnings growth.

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Speaker 7: I do think though as an investor, it's important to

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Speaker 7: have exposure here, but it's also important to have exposure

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Speaker 7: as to who are the beneficiaries the play when it

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Speaker 7: comes to the technology and the enablers very clear. I

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Speaker 7: think the adopters is where investors are really looking for

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Speaker 7: gains within twenty twenty four.

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Speaker 1: Okay, so dig into that.

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Speaker 5: Is it going for specific names in healthcare, specific names

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Speaker 5: in industry that have managed tool cup a good game

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Speaker 5: in AI or do you have to see the proof

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Speaker 5: in the pudding before you stop audocating money.

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Speaker 7: I think it's a little bit of a show me

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Speaker 7: story in twenty twenty four. I think you know, when

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Speaker 7: you just look at AI in terms of the number

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Speaker 7: of times it's been mentioned in earnings calls, it's come down.

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Speaker 7: I think, like last quarter it was six thousand times

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Speaker 7: and now it's about two thousand. But I do think

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Speaker 7: that when you look at sectors that stand to benefit

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Speaker 7: from this. I know cybersecurity very much in the news

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Speaker 7: based on last night's earnings, But you look at something

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Speaker 7: like cybersecurity and you say, okay, comparing the run up

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Speaker 7: of that sector versus the broader AI magnificent seven, there's

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Speaker 7: a comparative difference there, and evaluation difference actually on a

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Speaker 7: forward pe basis. You're looking at valuations that we haven't

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Speaker 7: seen since twenty twenty within that sector, and when I

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Speaker 7: think of the applications and the adopters of GENAI, not

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Speaker 7: only in an area with cybersecurity, does that increase the

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Speaker 7: total addressable market and the demand side of the equation.

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Speaker 7: But there are real productivity gains when it comes to

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Speaker 7: what used to take a security analyst hours to do

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Speaker 7: can come down to minutes. And we're going to see

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Speaker 7: those productivity gains in twenty twenty four.

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Speaker 1: Maybe not macro.

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Speaker 5: For US, there has been a perspective that the FED

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Speaker 5: is going to stop maybe talking about the productivity gains

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Speaker 5: the AI can bring more broadly to the US labor

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Speaker 5: force and the fact that we do have a tight

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Speaker 5: labor force, people still wanting to be hard. We do

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Speaker 5: seem to see growth within it. Will we see productivity gains?

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Speaker 5: Do you think more broadly in a macro perspective.

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Speaker 7: I think from a macro perspective, we have to go

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Speaker 7: back to even though we've seen volatility and the inflation print,

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Speaker 7: we have to go back to what we know is

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Speaker 7: true and where we're going to see flows from an

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Speaker 7: investing standpoint, So what we to be true right now?

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Speaker 7: We know that there's six trillion dollars sitting on the

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Speaker 7: sidelines in money market funds that has increased by one

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Speaker 7: and a half trillion dollars since the FED started its

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Speaker 7: hiking cycle. We know that we're at peak FED funds rates.

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Speaker 7: The question is when does the FED start cutting. I

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Speaker 7: don't think there's too many arguments that the FED would

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Speaker 7: resume a hiking cycle. Inflation, we knew it was going

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Speaker 7: to be a bumpy ride down to the.

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Speaker 1: Two percent target.

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Speaker 7: We see a path maybe down to two and a

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Speaker 7: half percent by the end of this year. And earnings

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Speaker 7: have troughed, and I think that's an important thing when

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Speaker 7: we look at this broadening, not only just because of

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Speaker 7: inflation coming down, raids coming down, cash on the sidelines,

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Speaker 7: Earnings troughed and Q three of last year and now

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Speaker 7: we're seeing more sectors turn to profitability, So you have

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Speaker 7: a profitability argument in addition to then productivity gains.

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Speaker 5: And it might be an argument therefore, when you come

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Speaker 5: back to your theme of cyber of buying on weakness.

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Speaker 5: What we love about having you on shows across on

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Speaker 5: network is the themes that you bring. Where else are

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Speaker 5: you seeing sort of forces that cannot be argued with

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Speaker 5: even in a Federal Reserve that potentially doesn't stop costing

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Speaker 5: as soon as we anticipate.

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Speaker 7: Another area that we love, and you're probably going to

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Speaker 7: laugh because you've heard me talk about this for years,

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Speaker 7: is longevity and investing in It's very tech.

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Speaker 1: It really does it kind of does work.

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Speaker 7: So we'll bring it full circle in terms of AI

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Speaker 7: gains there as well. But longevity is another area that

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Speaker 7: was left behind last year. So when you look at healthcare,

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Speaker 7: it was really exclusively about GLP one drugs until the

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Speaker 7: last two months of the year, and then biotech started

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Speaker 7: to get a little bit of a bid, med tech

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Speaker 7: started to get a little bit of a bid, and

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Speaker 7: life sciences. And so this is the same type of

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Speaker 7: argument when you think of productivity gains, when you think

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Speaker 7: of enhancements, when you think of what technology can do

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Speaker 7: in bringing down the cost of healthcare, there are a

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Speaker 7: lot of compelling valuation opportunities, both for the short term but.

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Speaker 1: Also for the long term.

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Speaker 5: We love the themes, you love the perspective the macro commentary.

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Speaker 5: Thanks so much, con thank you. Enjoy the healthy dose

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Speaker 5: of an exalt to the bell. Christian Visilicious City Group Wealth,

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Speaker 5: Head of Investment Solutions, Apple it's upgrading the security of

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Speaker 5: as I message app to fend off a looming future threat,

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Speaker 5: advanced quantum computing attacks. Let's bring in blue mugs Mark

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Speaker 5: German for more.

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Speaker 1: And we talk a lot.

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Speaker 5: About quantum computing, but the reality hasn't yet arrived.

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Speaker 1: Blapple wants to front run that.

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Speaker 2: Yeah, thank you so much for having me. That's right,

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Speaker 2: quantum computing. Some estimates indicate that these types of computers,

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Speaker 2: which are super duper computers, not just supercomputers so to speak,

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Speaker 2: won't arrive until the tail end of the decade or

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Speaker 2: deep into the twenty thirties. But Apple's starting to prepare

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Speaker 2: for that with I Message. Let me tell you why.

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Speaker 2: There is something called harvest now decrypt later attacks. Right.

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Speaker 2: What that means is someone could steal some data now,

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Speaker 2: even though it's unbreakable now, quantum computers in the future

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Speaker 2: may be able to break it open.

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Speaker 6: Right.

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Speaker 2: So Apple wants to stop that from happening. They don't

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Speaker 2: want someone to collect or steal someone's IM message data

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Speaker 2: in the year twenty twenty five and then crack it

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Speaker 2: open in twenty thirty two. And so that's what this

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Speaker 2: new I Message PQ three technology is going to do.

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Speaker 2: It's much improved encryption for the platform. It's rolling out

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Speaker 2: next month when Apple releases its next software updates, iOS

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Speaker 2: seventeen point four being the big one, and then it's

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Speaker 2: going to become the default for all I message conversations

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Speaker 2: by the end of this year.

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Speaker 5: And saying it's more efficient of effective at least than

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Speaker 5: the signal, of course than other competitors out there.

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Speaker 1: What's happen?

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Speaker 5: They're like, Mark, I'm interested, and also that you're reporting

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Speaker 5: that you've done overnight on Really some executive changes going

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Speaker 5: on at Apple.

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Speaker 1: This seems to be a never ending story.

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Speaker 2: Yeah, it's interesting. More executive changes at Apple, this one

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Speaker 2: in its audio division. Gary Jeeves, who's their vice president

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Speaker 2: of Acoustics, one of their top executives related to audio,

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Speaker 2: really has been the leader and at the forefront of

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Speaker 2: the development of air pods over the last decade or so,

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Speaker 2: which obviously now is a fifteen to twenty billion dollars

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Speaker 2: a year business for Apple. He has stepped down as

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Speaker 2: of this week from his role. He's given that role

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Speaker 2: to his top deputy. He's going to remain for the

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Speaker 2: next several months at Apple as an advisor, right, so

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Speaker 2: no longer running the team, but an advisor to Apple's

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Speaker 2: executive in charge of Beats, AirPods, now the home Pod

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Speaker 2: and other audio products, so more executive changes. This comes

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Speaker 2: after Dj Navotni, who was a key vice president of

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Speaker 2: hardware engineering there, left to be a senior vice president

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Speaker 2: of program management at Rivian earlier this year. Tang Tan,

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Speaker 2: the vice president of design for the iPhone, the Apple Watch,

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Speaker 2: and AirPods. He's going to join former Apple design chief

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Speaker 2: Johnny I've in his company love from working on new

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Speaker 2: AI products with Sam Altman, and you've seen a large

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Speaker 2: chunk of Apple's industrial design team leave as well. So

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Speaker 2: this is not a departure yet, but key executive stepping

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Speaker 2: down from their role.

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Speaker 5: Changing of the God Matt Gammon always ahead of it

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Speaker 5: with thank you so much for the insights. Now let's

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Speaker 5: turn our attention to talking tech and we're going to

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Speaker 5: stick with the theme of executive reshuffling. SpaceX seeing a

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Speaker 5: rare high level departure in its corporate ranks. According to

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Speaker 5: reporting from CNBC, the company senior vice president of its

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Speaker 5: commercial business is leaving after spending more than a decade

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Speaker 5: working there and was personally responsible for bringing in over

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Speaker 5: a billion dollars of annual revenue. Meanwhile, Samsung has sold

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Speaker 5: its entire remaining stake in ASML. That's as it pushes

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Speaker 5: into new areas of chip making. Now the world's largest

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Speaker 5: memory maker sold its remaining shares in the Dutch company

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Speaker 5: as it really tries to work to catch up with

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Speaker 5: rival s k Heinex in high bend bandwidth memory chips,

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Speaker 5: which are used to help in videos, accelerators, train artificial

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Speaker 5: intelligence plus sam mam and Freed is heading back to

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Speaker 5: court today for the first time since his November conviction.

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Speaker 5: That's over a multi billion dollar fraud in cryptocurrency customers.

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Speaker 1: Of course, Patwan.

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Speaker 5: Freed is slated to answer questions from a federal judge

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Speaker 5: as to whether he is aware of potential conflicts of

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Speaker 5: interest for the lawyers he hired last month to represent

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Speaker 5: him at sentencing in March. His new attorneys also represent

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Speaker 5: another cryptomogul facing criminal charges coming up. Vice president and

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Speaker 5: general manager of Google Workspace going to be joining us

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Speaker 5: a partner, Pabu joining us to talk about how duet

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Speaker 5: ai is turning into Google Workspace and it became Gemini.

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Speaker 1: That's next watching shows of Amazon.

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Speaker 5: Meanwhile, let's have a quick look at what's happening in

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Speaker 5: terms of well up eight nine tenths of the percent why.

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Speaker 1: Centering the Dow Jones Industrial average. What falls out Walgreens?

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Speaker 8: This is Blueberg Technology.

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Speaker 5: Just to talk about Google for a moment, because it's

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Speaker 5: got a lot of announcements. First up, it's introducing new

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Speaker 5: open large language models that's calling GEMMA. This is reversing

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Speaker 5: the company's kind of general strategy and keeping the company's

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Speaker 5: proprietary artificial intelligence technology out of public view. But the

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Speaker 5: models will handle text only have been built from the

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Speaker 5: same research and technology used to create the company's flagship

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Speaker 5: AI model, Gemini and Gemma will be released in two sizes,

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Speaker 5: one targeted at customers who plan to develop AI software

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Speaker 5: using high capacity AI chips and data centers, and then

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Speaker 5: a smaller model for more cost efficient app building. And

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Speaker 5: many would say, actually given them transformers being given to

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Speaker 5: the community in many ways Google has been open sourcing. Meanwhile,

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Speaker 5: let's stick with Google in another way in which you're

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Speaker 5: using it, perhaps at the enterprise. Some more news coming

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Speaker 5: out that's starting today Duet AI for Google Workspace. It's

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Speaker 5: going to have a brand new name, and you guess

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Speaker 5: that it's Gemini Workspace customers will be able to chat

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Speaker 5: with Gemini in a new way, and the chat experience

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Speaker 5: will have enterprise grade data protections as well as copyright

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Speaker 5: in demnification. Here to join a Vice president and General

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Speaker 5: Manager of Google Workspace a pantner PAPU. It is great

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Speaker 5: to have you with us a partner, and number of

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Speaker 5: ways it feels to be using Gemini Now when I'm

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Speaker 5: sat at my work desk, how do you envisage people

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Speaker 5: working with it to improve their productivity?

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Speaker 3: Well, first of all, we're super excited have Workspace center

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Speaker 3: the Gemini era. As you said, workspace comprisers of apps

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Speaker 3: that people use every day in their life, from Gmail,

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Speaker 3: Dark Drive, sheets, Meet, you name it, and so to

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Speaker 3: have Gemini infuse there to make all of your work

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Speaker 3: journeys more productive is fantastic. So we're already seeing people

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Speaker 3: do lots of interesting things like helping them write better,

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Speaker 3: making them sound more professional, perhaps making them sound more playful.

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Speaker 3: And so today's announcement is really exciting because Gemini in

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Speaker 3: Workspace just up levels all of the things that AI

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Speaker 3: can help you do in your work.

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Speaker 5: Life, and not many people might not realize as over

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Speaker 5: three billion people do use Google Workspace, and I'm therefore

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Speaker 5: you can garner so much data as to how it's

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Speaker 5: being effectively deployed, who, what types of people wear geographically,

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Speaker 5: but what are the guardrails that a lot of your

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Speaker 5: clients are going to be asking you for, because that

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Speaker 5: has been almost the nervousness, the reticent about the new

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Speaker 5: world of generative AI.

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Speaker 3: So one of the things that we hold very dear

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Speaker 3: is our promise to users about privacy, security and compliance.

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Speaker 3: And with Workspace, we offer enterprise grade security for all

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Speaker 3: of our Gemini features, which means you're in control of

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Speaker 3: your data. Your data never leaks into the models you get,

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Speaker 3: your data's never used for advertising, and so that level

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Speaker 3: of security and compliance being made available now to all

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Speaker 3: of our Gemini users is something that we're very proud of.

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Speaker 5: What's interesting is, of course, when I think about Workspace,

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Speaker 5: I think of enormous corporations in which I currently sit.

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Speaker 5: But small and medium size enterprises have got to have

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Speaker 5: been wanting to use generative AI in their heart too, right.

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Speaker 3: Absolutely, we just did a survey wag eighty seven percent

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Speaker 3: of small businesses and all medium sized businesses are all

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Speaker 3: ready to use generait of AI and so given our

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Speaker 3: user customer base of over ten million customers, we're excited

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Speaker 3: to bring Gemini today with a brand new launch at

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Speaker 3: a lower price point to businesses of all sizes all

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Speaker 3: over the world. And so with that launch, we now

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Speaker 3: enable small businesses to get more done every single day.

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Speaker 3: As well.

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Speaker 1: Taught to us about ultimately the pricing of this.

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Speaker 5: How does one come up with what real value is

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Speaker 5: worth in this and not be sort of blown around

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Speaker 5: by ultimately well other competitors of pricing that points at.

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Speaker 3: So we feel very strong about our pricing strategy. It's robust,

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Speaker 3: It's based on a number of factors, not just what

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Speaker 3: the market can bear, but also the perceived value of

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Speaker 3: our customers, because ultimately it comes down to customers and

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Speaker 3: what they're willing to pay for. And this is where

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Speaker 3: we started with a thirty dollars version for our enterprise

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Speaker 3: customers and a twenty dollar version for smaller businesses or

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Speaker 3: enterprises who want to get started. But I'm not quite

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Speaker 3: sure where to begin, and I said.

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Speaker 5: At the beginning, So with the breadth of three billion users,

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Speaker 5: how are you seeing it being used differently in different places?

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Speaker 3: Oh, it's so wonderful. It's so creative and clever. People

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Speaker 3: tell us stories all the time of things that they're

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Speaker 3: doing with it. We have small business people who are

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Speaker 3: actually just wanting to focus on their businesses. So, for example,

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Speaker 3: a music teacher really just wants to teach music, but

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Speaker 3: often has to respond to inbound inquiries all the time,

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Speaker 3: and so getting help replying to emails while sounding you know,

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Speaker 3: factual and professional is actually really fantastic.

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Speaker 1: We love the stories where people for.

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Speaker 3: Whom English is the second language, have been you know,

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Speaker 3: their work has been transformed by how it makes them

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Speaker 3: sound at work and gives them more confidence. Creativity unlocked

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Speaker 3: with things like im generation with slides. If you're trying

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Speaker 3: to brainstorm how you might think about a new product,

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Speaker 3: and so on, just coming up with visual aids of

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Speaker 3: like visualize what this idea might look like really helps

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Speaker 3: unlock some of the brainstorming. Banks using it for executive management,

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Speaker 3: event planners using it to get events done.

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Speaker 1: I mean, I could go on and on.

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Speaker 3: It's actually just truly tremendous what our customers are doing

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Speaker 3: with it already.

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Speaker 5: And look, you're a long time Google executive decades under

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Speaker 5: the belt and tell us a little bit about how

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Speaker 5: it's felt when, as we said at the beginning of

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Speaker 5: this conversation, you with of course deep Mind, have been

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Speaker 5: really R and D focused all things artificial intelligence, injecting

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Speaker 5: things like Transformer R and D into the broader ecosystem.

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Speaker 5: But then came this idea that you were behind the

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Speaker 5: curve that you were following on from Microsoft and open

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Speaker 5: Ai teaming together.

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Speaker 1: Have you been able to diffuse that? Have you been

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Speaker 1: able to think that that's not true?

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Speaker 3: I think ultimately customers decide in when customers use our products,

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Speaker 3: and the tell us that they're more helpful, more intuitive,

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Speaker 3: easy to use, and.

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Speaker 1: Actually deliver the value.

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Speaker 3: And it's not just about the hype. I think that's

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Speaker 3: where we need to focus is what are the real

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Speaker 3: users saying as opposed to all of the hype around this.

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Speaker 3: And so we love our partnership with deep Mind because

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Speaker 3: ultimately Google's focus on the user and making sure that

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Speaker 3: we're actually helpful to the user is what differentiates us

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Speaker 3: from everybody else.

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Speaker 5: Okay, so there is a lot of feeling that there's hype.

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Speaker 5: How are you in reality as just someone that uses

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Speaker 5: Gmail and docs and not just someone who's in charge

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Speaker 5: of workspace, is using generative AI on a daily basis.

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Speaker 3: So many people, so many ways. So first of all,

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Speaker 3: both at my work life and my personal life, I

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Speaker 3: often feel overwhelmed with email. Actually in my personal life

440
00:20:40,320 --> 00:20:43,639
Speaker 3: more so these days because schools and businesses and package

441
00:20:43,680 --> 00:20:45,800
Speaker 3: tracking and all of these things. So having Gmail be

442
00:20:45,840 --> 00:20:48,840
Speaker 3: a really helpful assistant to me by showing me the

443
00:20:48,840 --> 00:20:51,639
Speaker 3: summaries of the endless long emails I get has saved

444
00:20:51,680 --> 00:20:53,880
Speaker 3: me a lot of time at work at home, which

445
00:20:53,880 --> 00:20:56,679
Speaker 3: has been helpful. Same thing applies at work as well.

446
00:20:56,800 --> 00:20:59,320
Speaker 3: And you know, for example, I was prepping for an interview,

447
00:20:59,359 --> 00:21:02,000
Speaker 3: how does one your broadcast interview got some really great

448
00:21:02,000 --> 00:21:05,400
Speaker 3: clips from Gemini. Actually is like be confident but yourself.

449
00:21:05,600 --> 00:21:07,560
Speaker 3: There's just all sorts of ways in which it just

450
00:21:07,640 --> 00:21:09,760
Speaker 3: makes you a little bit more confident about what you're doing.

451
00:21:09,840 --> 00:21:12,159
Speaker 3: Freeing up your time to do other things helps you

452
00:21:12,280 --> 00:21:14,160
Speaker 3: be yourself in the best possible way.

453
00:21:14,400 --> 00:21:14,639
Speaker 9: You can.

454
00:21:14,680 --> 00:21:16,640
Speaker 5: Go back and say it to Gemini, you're a pretty

455
00:21:16,680 --> 00:21:18,879
Speaker 5: darn good Thanks very much, your vice president and general

456
00:21:18,880 --> 00:21:21,760
Speaker 5: manager at Google Workspace A Panna papu there on all

457
00:21:21,800 --> 00:21:24,360
Speaker 5: things of its injection into Gemini into the workplace.

458
00:21:31,760 --> 00:21:33,760
Speaker 1: Welcome back to Blue Meg Technology. I'm Karen Hide in

459
00:21:33,760 --> 00:21:35,320
Speaker 1: New York. Let's check in on these markets.

460
00:21:35,080 --> 00:21:36,760
Speaker 5: Because a little bit of a pull back, a little

461
00:21:36,760 --> 00:21:39,359
Speaker 5: bit of caution ahead of course the all important earnings

462
00:21:39,400 --> 00:21:41,000
Speaker 5: after the bell today, have a check in on what's

463
00:21:41,000 --> 00:21:43,080
Speaker 5: happening with the nast that one hundred. More broadly, software

464
00:21:43,200 --> 00:21:45,480
Speaker 5: one of the worst performing benchmarks if you compare it

465
00:21:45,480 --> 00:21:47,200
Speaker 5: to the S and p 'or of by six tenser percent.

466
00:21:47,240 --> 00:21:50,320
Speaker 5: I'm looking what's happening in bond markets right now, calmness.

467
00:21:50,520 --> 00:21:52,800
Speaker 5: Ultimately we're seeing four point twenty nine. Let's call it

468
00:21:52,840 --> 00:21:54,800
Speaker 5: on the tenure at the moment as we all anticipate

469
00:21:54,840 --> 00:21:57,200
Speaker 5: its course. From the macro perspective, the Fed minutes that

470
00:21:57,280 --> 00:21:59,320
Speaker 5: come a little bit later today, looking at Bitcoin just

471
00:21:59,400 --> 00:22:01,600
Speaker 5: off by one point percenters, risk assets sell off. More broadly,

472
00:22:01,680 --> 00:22:03,679
Speaker 5: let's have a look at what's happening on individual names

473
00:22:03,960 --> 00:22:05,080
Speaker 5: and particular stocks.

474
00:22:04,880 --> 00:22:05,720
Speaker 1: That are on the downside.

475
00:22:05,760 --> 00:22:07,560
Speaker 5: And I'm just going to shine a light on the

476
00:22:07,680 --> 00:22:10,280
Speaker 5: story of today as well as we anticipate in video

477
00:22:10,400 --> 00:22:12,080
Speaker 5: has got to sae what's happening with all of these

478
00:22:12,119 --> 00:22:15,600
Speaker 5: cyber stocks. The numbers after the bell are Palo Alto Networks. Yes,

479
00:22:15,640 --> 00:22:17,800
Speaker 5: they managed to meet that nineteen percent growth in revenue

480
00:22:17,840 --> 00:22:20,280
Speaker 5: for their previous fiscal quarter. But the forecast is going

481
00:22:20,320 --> 00:22:22,280
Speaker 5: to be sixteen percent growth. I'm afraid that's nowhere near

482
00:22:22,280 --> 00:22:24,080
Speaker 5: the twenty five percent we've all got rather used to

483
00:22:24,320 --> 00:22:27,720
Speaker 5: Palo Alto fooling the most in its history on record,

484
00:22:27,760 --> 00:22:30,000
Speaker 5: we're currently off by twenty six percent. We're also seeing

485
00:22:30,000 --> 00:22:33,359
Speaker 5: CrowdStrike down and z scala or lower in sympathy today.

486
00:22:33,600 --> 00:22:35,520
Speaker 5: But let's get back to the earnings that we still anticipate.

487
00:22:35,640 --> 00:22:37,760
Speaker 5: Let's get back to Nvidia results coming after the bell.

488
00:22:37,840 --> 00:22:39,840
Speaker 5: And of course here's what some of our guests have

489
00:22:39,880 --> 00:22:41,160
Speaker 5: had to say and what they expect.

490
00:22:41,280 --> 00:22:46,680
Speaker 4: Thank listen, there's seven hundred and seventy one companies announcing

491
00:22:46,720 --> 00:22:49,000
Speaker 4: this week, but there's really only one that matters, isn't

492
00:22:49,040 --> 00:22:50,840
Speaker 4: that and that is in video.

493
00:22:50,920 --> 00:22:53,800
Speaker 3: Of course, the structural side is very exciting, obviously, with

494
00:22:53,920 --> 00:22:56,160
Speaker 3: AI in the key, Driver's Saint.

495
00:22:56,119 --> 00:22:58,919
Speaker 7: In Video's earnings are going to be the story that

496
00:22:58,960 --> 00:23:01,639
Speaker 7: we all anticipate and wait with baited breath.

497
00:23:01,720 --> 00:23:05,960
Speaker 4: Expectations are high, Caroline. I think probably they'll deliver.

498
00:23:06,160 --> 00:23:08,560
Speaker 2: You look at Navida, there's no shortage of the demand.

499
00:23:08,640 --> 00:23:10,560
Speaker 4: I think it's going to be more about what Jensen

500
00:23:10,600 --> 00:23:14,560
Speaker 4: says about the outlook, the growth and the product lineup

501
00:23:14,720 --> 00:23:16,760
Speaker 4: as opposed to what he actually delivers in the earning.

502
00:23:18,600 --> 00:23:21,600
Speaker 5: There is so much hype about what this integral part

503
00:23:21,840 --> 00:23:25,880
Speaker 5: of AI infrastructure can deliver. How are we deploying generative AI?

504
00:23:26,000 --> 00:23:27,360
Speaker 5: How are we using it in our day to day

505
00:23:27,600 --> 00:23:29,520
Speaker 5: deon Nicholas and pleas to say, is at the forefront

506
00:23:29,560 --> 00:23:31,520
Speaker 5: of that is the CEO of fore Thought. It's a

507
00:23:31,520 --> 00:23:34,160
Speaker 5: company that uses generative AI for customer support. You're also

508
00:23:34,200 --> 00:23:36,840
Speaker 5: into the world of agents, which is another key hype

509
00:23:36,880 --> 00:23:37,960
Speaker 5: area at the moment, Dion.

510
00:23:38,200 --> 00:23:40,440
Speaker 1: When we are seeing the whole market.

511
00:23:40,080 --> 00:23:43,320
Speaker 5: Declaring that in Vidia is the most important company on

512
00:23:43,400 --> 00:23:46,120
Speaker 5: the planet or stock at least, how do you think

513
00:23:46,119 --> 00:23:47,399
Speaker 5: about this AI hype cycle?

514
00:23:48,000 --> 00:23:50,399
Speaker 10: No, I agree, Caroline, and thanks for having me back

515
00:23:50,440 --> 00:23:52,879
Speaker 10: on the show. When you think about it, like in

516
00:23:52,920 --> 00:23:55,040
Speaker 10: a gold rush, it's really the picks and shovels that

517
00:23:55,119 --> 00:23:57,439
Speaker 10: make the most money. And I think Nvidia really is

518
00:23:57,720 --> 00:24:00,280
Speaker 10: the picks and shovels business for AI. But at the

519
00:24:00,320 --> 00:24:01,960
Speaker 10: end of the day, we're still in the early innings

520
00:24:02,000 --> 00:24:05,040
Speaker 10: on the application layer, which I'm most excited about. Right

521
00:24:05,119 --> 00:24:07,440
Speaker 10: I actually think about all of the money that's being

522
00:24:07,440 --> 00:24:09,560
Speaker 10: spent on things like outsourcing and things like that in

523
00:24:09,600 --> 00:24:12,520
Speaker 10: the customer support world. And I think AI jen AI

524
00:24:12,600 --> 00:24:15,199
Speaker 10: and particularly AI agents are going to be the future

525
00:24:15,280 --> 00:24:16,679
Speaker 10: of this industry. I think it's going to be one

526
00:24:16,680 --> 00:24:18,960
Speaker 10: of the most massive software categories on the planet.

527
00:24:19,160 --> 00:24:21,480
Speaker 1: To get there, you need access to compute.

528
00:24:21,560 --> 00:24:23,439
Speaker 5: How have you managed to think around that ensure that

529
00:24:23,520 --> 00:24:25,840
Speaker 5: it's not eating so much of your cost that you

530
00:24:26,160 --> 00:24:27,560
Speaker 5: also have to just keep going to the market and

531
00:24:27,640 --> 00:24:29,359
Speaker 5: raising more and more in the VC world.

532
00:24:29,400 --> 00:24:32,199
Speaker 10: Agreed, especially over the last year and a half, call it,

533
00:24:32,320 --> 00:24:35,119
Speaker 10: everything has been about efficiency, right, and so not just

534
00:24:35,200 --> 00:24:36,840
Speaker 10: in terms of people and spend like that, but in

535
00:24:36,960 --> 00:24:39,280
Speaker 10: terms of compute power. And so you think about the

536
00:24:39,280 --> 00:24:41,919
Speaker 10: algorithms that we use every single day, getting smarter and

537
00:24:41,960 --> 00:24:44,199
Speaker 10: smarter not just on the application layer, but using those

538
00:24:44,240 --> 00:24:47,000
Speaker 10: algorithms to be smarter with our compute is how we

539
00:24:47,080 --> 00:24:47,320
Speaker 10: do that?

540
00:24:47,680 --> 00:24:47,920
Speaker 1: Okay?

541
00:24:48,200 --> 00:24:50,240
Speaker 5: Who have you turned to in terms of the ecosystem

542
00:24:50,280 --> 00:24:52,560
Speaker 5: to help you with that? Who have been your hyperscalers

543
00:24:52,560 --> 00:24:54,560
Speaker 5: of choice, who have been your access to GPUs?

544
00:24:54,920 --> 00:24:58,640
Speaker 10: Yeah, so we do a lot with open ai, for example.

545
00:24:58,840 --> 00:25:01,399
Speaker 10: You do a lot with the cloud players. So folks

546
00:25:01,440 --> 00:25:05,399
Speaker 10: like Microsoft, Azure, folks like Amazon AWS and things like that.

547
00:25:05,480 --> 00:25:07,840
Speaker 10: We actually announced a partnership with AWS a few months ago.

548
00:25:08,080 --> 00:25:10,280
Speaker 10: So what we're trying to do is be I would say,

549
00:25:10,320 --> 00:25:13,199
Speaker 10: agnostic to what's going on in the underlying layer and

550
00:25:13,240 --> 00:25:15,479
Speaker 10: make sure that we can have failovers, fallbacks and all

551
00:25:15,520 --> 00:25:17,280
Speaker 10: of that so that we can deliver a robust system

552
00:25:17,280 --> 00:25:17,920
Speaker 10: for our customers.

553
00:25:17,920 --> 00:25:19,679
Speaker 5: And let's talk about what you're delivering at the moment,

554
00:25:19,760 --> 00:25:23,280
Speaker 5: you're with instacll utwork, plenty of other companies turning to

555
00:25:23,320 --> 00:25:26,719
Speaker 5: you to basically make my experience when using those apps

556
00:25:27,119 --> 00:25:29,680
Speaker 5: more joyous. Right, Where are we in the innings of

557
00:25:30,160 --> 00:25:33,119
Speaker 5: development of having general to AI making my experience better?

558
00:25:33,600 --> 00:25:34,240
Speaker 1: Absolutely so.

559
00:25:34,280 --> 00:25:36,840
Speaker 10: At forethought, we've been delivering AI for the past six years,

560
00:25:36,920 --> 00:25:40,080
Speaker 10: and so it's exciting to see this boom so to speak,

561
00:25:40,119 --> 00:25:42,720
Speaker 10: in the genai world. But at the end of the day,

562
00:25:42,880 --> 00:25:45,359
Speaker 10: I think we're still very very early and there's so

563
00:25:45,480 --> 00:25:47,760
Speaker 10: much more to be done in this space. At forethought,

564
00:25:47,760 --> 00:25:50,919
Speaker 10: we're delivering AI agents for customer support. We're already solving

565
00:25:50,920 --> 00:25:54,000
Speaker 10: more than one hundred million issues a year, every single year,

566
00:25:54,359 --> 00:25:56,600
Speaker 10: and we think the technology is only going to get better.

567
00:25:56,720 --> 00:25:59,119
Speaker 10: Lllms are just the beginning and then we saw retrieval

568
00:25:59,160 --> 00:26:02,040
Speaker 10: augmented LLLM or RAGS, and then we saw AI Agents,

569
00:26:02,080 --> 00:26:04,920
Speaker 10: which we actually announced here on Bloomberg about a year

570
00:26:04,960 --> 00:26:07,399
Speaker 10: ago with our auto flows technology. And I think it's

571
00:26:07,400 --> 00:26:08,600
Speaker 10: going to keep getting better and better.

572
00:26:09,160 --> 00:26:11,840
Speaker 5: AI Agents, as I said, has been sort of all

573
00:26:11,840 --> 00:26:14,199
Speaker 5: the talk of the town. And what's so interesting about

574
00:26:14,359 --> 00:26:16,280
Speaker 5: the generative AI space is you all seem to be

575
00:26:16,359 --> 00:26:18,600
Speaker 5: frenemies in some way. You're just talking about how you're

576
00:26:19,080 --> 00:26:21,360
Speaker 5: leaning upon open Ai in some way, but open Ai

577
00:26:21,480 --> 00:26:24,600
Speaker 5: has GPTs itself. You then got Brett Taylor, who's the

578
00:26:24,680 --> 00:26:27,080
Speaker 5: chairman of open Ai, coming in and he's launching of

579
00:26:27,080 --> 00:26:30,960
Speaker 5: course Sierra, which is also all about agents and customers.

580
00:26:31,280 --> 00:26:33,439
Speaker 1: Where do you see the landscape being? How many players

581
00:26:33,440 --> 00:26:33,840
Speaker 1: will there be?

582
00:26:34,760 --> 00:26:36,359
Speaker 10: Again, as I said, I think this is going to

583
00:26:36,400 --> 00:26:39,040
Speaker 10: be one of the largest software categories on Planet Earth,

584
00:26:39,080 --> 00:26:41,040
Speaker 10: mark my words. And so there's going to be room

585
00:26:41,080 --> 00:26:43,919
Speaker 10: for multiple players. And ultimately, I think what's happening is

586
00:26:44,000 --> 00:26:46,359
Speaker 10: there's a shift from the old guard to the new guard.

587
00:26:46,600 --> 00:26:49,919
Speaker 10: You've seen incumbents companies like Zendesk and Salesforce and folks

588
00:26:49,960 --> 00:26:53,800
Speaker 10: like that scrambling to bring AI into their strategy. Because

589
00:26:53,880 --> 00:26:55,800
Speaker 10: being the help desk or being a CRM is not

590
00:26:55,920 --> 00:26:58,720
Speaker 10: necessarily going to cut it in an AI first future, right,

591
00:26:58,760 --> 00:27:01,920
Speaker 10: And so what we're seeing and being validated by folks

592
00:27:02,000 --> 00:27:04,679
Speaker 10: like Brett Taylor entering the space is that Jenai and

593
00:27:04,720 --> 00:27:07,000
Speaker 10: being AI first in this space is going to be

594
00:27:07,080 --> 00:27:07,880
Speaker 10: the way of the future.

595
00:27:08,000 --> 00:27:10,639
Speaker 5: How hard is it, though, when I can understand that

596
00:27:10,720 --> 00:27:13,600
Speaker 5: it work in instacrat A already, a startup is probably

597
00:27:13,600 --> 00:27:16,080
Speaker 5: more willing to go with a startup for its own

598
00:27:16,119 --> 00:27:17,440
Speaker 5: customer delivery.

599
00:27:17,680 --> 00:27:19,440
Speaker 1: But when you've got big, older.

600
00:27:19,119 --> 00:27:23,240
Speaker 5: Institutions, they've just got salesforce within them already. How hard

601
00:27:23,320 --> 00:27:25,119
Speaker 5: is it to say no, no, no, come to this

602
00:27:25,200 --> 00:27:28,800
Speaker 5: different offering untwine yourself from the incumbent.

603
00:27:29,200 --> 00:27:30,320
Speaker 8: I think that's a fair question.

604
00:27:30,400 --> 00:27:32,520
Speaker 10: So what we're seeing is a lot of activity in

605
00:27:32,560 --> 00:27:35,560
Speaker 10: the mid market SMB companies who are embracing the future

606
00:27:35,560 --> 00:27:39,240
Speaker 10: and things like that. A lot of these larger incumbent companies,

607
00:27:39,400 --> 00:27:41,399
Speaker 10: there's a lot of interest, there's a lot of hype,

608
00:27:41,640 --> 00:27:44,040
Speaker 10: but are they actually making the changes that's soon to

609
00:27:44,080 --> 00:27:46,040
Speaker 10: be seen? And that's actually another thing is we talk

610
00:27:46,080 --> 00:27:49,320
Speaker 10: about things like Nvidia, A lot of the use cases

611
00:27:49,320 --> 00:27:52,280
Speaker 10: seem to be experimental today, right, and so I'm curious

612
00:27:52,280 --> 00:27:53,840
Speaker 10: what's going to happen, what Jensen's going to say in

613
00:27:53,920 --> 00:27:56,040
Speaker 10: terms of the outlook for the future as we start

614
00:27:56,040 --> 00:27:58,320
Speaker 10: to see more of these technologies become put into production,

615
00:27:58,520 --> 00:28:00,680
Speaker 10: who's going to keep and truly be an AI first

616
00:28:00,720 --> 00:28:03,000
Speaker 10: company and who's just experimenting.

617
00:28:03,520 --> 00:28:06,840
Speaker 5: And then I'm sure Jensen might pay some lip service

618
00:28:06,880 --> 00:28:09,080
Speaker 5: to the fact that it's hard to get talent as

619
00:28:09,119 --> 00:28:10,719
Speaker 5: well and to scale at the spies that you want

620
00:28:10,800 --> 00:28:12,800
Speaker 5: to what are some of the things that hold back

621
00:28:12,840 --> 00:28:14,679
Speaker 5: forthought or what are some of the things that are

622
00:28:14,720 --> 00:28:15,280
Speaker 5: helping you grow.

623
00:28:15,680 --> 00:28:17,920
Speaker 10: Absolutely, I think talent is first and foremost the most

624
00:28:17,920 --> 00:28:21,480
Speaker 10: important thing. We were founded on this generative aivision, leveraging

625
00:28:21,720 --> 00:28:23,960
Speaker 10: both our own research as well as research from folks

626
00:28:23,960 --> 00:28:27,359
Speaker 10: like Chris Manning at Stanford, the godfather of NLP. And

627
00:28:27,480 --> 00:28:29,760
Speaker 10: in terms of holding us back, I mean, the sky's

628
00:28:29,760 --> 00:28:31,639
Speaker 10: the limit. In terms of this market, one of the

629
00:28:31,680 --> 00:28:34,040
Speaker 10: things is that it's a very noisy market. Everyone is

630
00:28:34,040 --> 00:28:36,680
Speaker 10: calling themselves a GENAI player, everyone is throwing AI into

631
00:28:36,680 --> 00:28:39,680
Speaker 10: their name, but in a lot of ways, again, we've

632
00:28:39,680 --> 00:28:42,160
Speaker 10: been at this for many years. We've stayed at the forefront,

633
00:28:42,320 --> 00:28:45,280
Speaker 10: and so it's really about showing customers what is true AI,

634
00:28:45,440 --> 00:28:47,760
Speaker 10: what you can actually deliver, and what that means for

635
00:28:47,840 --> 00:28:48,640
Speaker 10: their customers.

636
00:28:49,200 --> 00:28:51,440
Speaker 5: Deon, it's great to have you in town passing through

637
00:28:51,480 --> 00:28:53,160
Speaker 5: New York. Glad that you could stop by the show

638
00:28:53,400 --> 00:28:57,000
Speaker 5: for thoughts. CEO co founder Dion Nicholas, of course, talking

639
00:28:57,040 --> 00:28:59,360
Speaker 5: all things as we anticipate in video and were broadly

640
00:28:59,560 --> 00:29:01,440
Speaker 5: the impact generator A. I mean while coming up, but

641
00:29:01,480 --> 00:29:04,320
Speaker 5: we're going to be joined by Darren Abrahamson from Baine

642
00:29:04,320 --> 00:29:06,000
Speaker 5: Capital's techn Opportunities team.

643
00:29:05,800 --> 00:29:07,760
Speaker 1: To talk about where he's placing his bets.

644
00:29:07,760 --> 00:29:10,360
Speaker 5: Everyone's in town today, He's coming over from Boston to

645
00:29:10,400 --> 00:29:12,520
Speaker 5: be here in New York. Meanwhile, let's have quick check

646
00:29:12,520 --> 00:29:14,120
Speaker 5: on what's happening in terms of one of the AI

647
00:29:14,240 --> 00:29:16,239
Speaker 5: darlings of choice of late, which has been selling off

648
00:29:16,240 --> 00:29:17,480
Speaker 5: pretty hard over the last three.

649
00:29:17,360 --> 00:29:19,200
Speaker 1: Training days, super micro Computer.

650
00:29:19,560 --> 00:29:21,800
Speaker 5: Now actually short sellers have been notching about one point

651
00:29:21,840 --> 00:29:24,280
Speaker 5: two billion dollars of late as we've seen shares full

652
00:29:24,280 --> 00:29:26,320
Speaker 5: we're down another seven and three quarters of percent, but

653
00:29:26,880 --> 00:29:29,120
Speaker 5: remember this is a company that's up more than seven

654
00:29:29,240 --> 00:29:32,360
Speaker 5: hundred percent, and then last year this is a Bloomberg technology.

655
00:29:48,080 --> 00:29:50,880
Speaker 5: Let's returned to shares of Palo Altera Networks. Why because

656
00:29:50,880 --> 00:29:53,200
Speaker 5: they're heading for the biggest drop ever. That's after the

657
00:29:53,200 --> 00:29:56,360
Speaker 5: company cut its forecast amid a pullback in cybersecurity spending.

658
00:29:56,720 --> 00:29:59,200
Speaker 5: Joining us now is man leep seeing a bloomberg intelligence

659
00:29:59,240 --> 00:30:01,320
Speaker 5: and Mandat. The lie that caught me from the CEO

660
00:30:01,960 --> 00:30:03,760
Speaker 5: was that there's spending fatigue.

661
00:30:03,960 --> 00:30:04,840
Speaker 1: It says this is new.

662
00:30:06,480 --> 00:30:10,200
Speaker 11: Yeah, well, I think when you look at security, it's

663
00:30:10,280 --> 00:30:12,840
Speaker 11: one of those things that has worked really well along

664
00:30:12,880 --> 00:30:15,680
Speaker 11: with generative AI for the past few quarters. So it

665
00:30:15,800 --> 00:30:19,480
Speaker 11: makes you wonder what change in the last ninety days.

666
00:30:19,480 --> 00:30:22,600
Speaker 11: And they gave a prior guidance of about you know,

667
00:30:22,680 --> 00:30:25,080
Speaker 11: high teens growth for the full year and now they

668
00:30:25,120 --> 00:30:28,840
Speaker 11: cut it to loteins. So clearly, you know they are

669
00:30:28,920 --> 00:30:32,640
Speaker 11: seeing a change in environment. They tried to explain that with,

670
00:30:32,880 --> 00:30:35,840
Speaker 11: you know, a new go to market strategy, but you know,

671
00:30:36,040 --> 00:30:38,760
Speaker 11: pow Alta is the largest cybersecurity vendor and they have

672
00:30:38,920 --> 00:30:42,479
Speaker 11: had a lot of success with bundling their products. So

673
00:30:42,560 --> 00:30:45,320
Speaker 11: the fact that they are changing the go to market

674
00:30:45,720 --> 00:30:49,480
Speaker 11: in an environment that should favor cybersecurity, it is a

675
00:30:49,520 --> 00:30:51,960
Speaker 11: little bit of a surprise, and that's why you see

676
00:30:51,960 --> 00:30:53,080
Speaker 11: that kind of stock reaction.

677
00:30:53,360 --> 00:30:55,000
Speaker 5: And we've seen a run up of about one hundred

678
00:30:55,000 --> 00:30:57,320
Speaker 5: and twenty percent in the last year, which maybe is

679
00:30:57,320 --> 00:31:00,120
Speaker 5: why we've see the significant pullback Man Deep, But when

680
00:31:00,280 --> 00:31:03,040
Speaker 5: you went on to sort of outline that people don't

681
00:31:03,040 --> 00:31:04,920
Speaker 5: want to spend at the moment unless they see a

682
00:31:05,000 --> 00:31:09,600
Speaker 5: significant improvement, Well, the pole point of cybersecurity is ultimately

683
00:31:09,600 --> 00:31:11,640
Speaker 5: to be a defense. How do you think that they

684
00:31:11,840 --> 00:31:15,080
Speaker 5: and other competitors cloud strike can convince people to keep

685
00:31:15,160 --> 00:31:17,240
Speaker 5: on spending that you need to in this environment.

686
00:31:17,520 --> 00:31:20,360
Speaker 11: Yeah, it's a great point. Because the hyper scale cloud

687
00:31:20,400 --> 00:31:24,320
Speaker 11: providers are all giving you security. It's bundled security that

688
00:31:24,320 --> 00:31:28,280
Speaker 11: they are giving you. So these companies have to convince

689
00:31:28,400 --> 00:31:31,640
Speaker 11: the customers that it's something extra. They're supporting a multi

690
00:31:31,640 --> 00:31:35,600
Speaker 11: cloud strategy and the defenses that the hyperscalers give are

691
00:31:35,640 --> 00:31:38,000
Speaker 11: not enough. And in this case, I think Powell Alta

692
00:31:38,040 --> 00:31:42,000
Speaker 11: has to make that shift from firewalls to new subscriptions

693
00:31:42,080 --> 00:31:45,680
Speaker 11: cloud based revenue, which is at multi year transition. They

694
00:31:45,680 --> 00:31:49,200
Speaker 11: were doing well so far, but clearly the deceleration in

695
00:31:49,320 --> 00:31:53,480
Speaker 11: top line growth is definitely spooking a few investors over here.

696
00:31:53,640 --> 00:31:55,800
Speaker 5: As for sure, Man, name's saying so great to have

697
00:31:55,840 --> 00:31:58,440
Speaker 5: you on the show. Thank you of Bloomberg Intelligence. Now

698
00:31:58,440 --> 00:32:00,920
Speaker 5: we're going to turn our attention to the NUER landscape,

699
00:32:00,920 --> 00:32:02,920
Speaker 5: talk a little bit about cyber within it. I'm a

700
00:32:02,960 --> 00:32:05,440
Speaker 5: peace to Welcome to the show, Darren Abramson, he's partner

701
00:32:05,520 --> 00:32:09,120
Speaker 5: at Bain Capital's Tech Opportunities team on today's VC Spotlight.

702
00:32:09,160 --> 00:32:13,080
Speaker 5: Traveling in from Boston and I'm interested, Darren, and whether

703
00:32:13,560 --> 00:32:15,640
Speaker 5: you're hearing or seeing this from some of the startups

704
00:32:15,640 --> 00:32:17,400
Speaker 5: that you've been investing in. I know cyber has been

705
00:32:17,440 --> 00:32:19,880
Speaker 5: a theme, but all of us are talking about how

706
00:32:19,880 --> 00:32:22,440
Speaker 5: GENATVAI means that we need more cyber protection, not a

707
00:32:22,480 --> 00:32:23,440
Speaker 5: pullback or less.

708
00:32:24,080 --> 00:32:24,280
Speaker 6: Yeah.

709
00:32:24,280 --> 00:32:26,760
Speaker 12: I think it's really important that you sort of put

710
00:32:26,800 --> 00:32:28,320
Speaker 12: things in context. I think you pointed out on the

711
00:32:28,320 --> 00:32:30,479
Speaker 12: prior segment. You know, pale Alto's had a phenomenal run

712
00:32:30,560 --> 00:32:34,760
Speaker 12: up and a lot of the cyber companies really outperformed.

713
00:32:34,160 --> 00:32:35,000
Speaker 8: Over the last year.

714
00:32:35,160 --> 00:32:37,960
Speaker 12: As CFOs and customers look to cut back spend in

715
00:32:38,000 --> 00:32:40,200
Speaker 12: other areas of technology, cyber was one of those areas

716
00:32:40,200 --> 00:32:43,120
Speaker 12: that remain very resilient. But when we talked to chief

717
00:32:43,120 --> 00:32:45,800
Speaker 12: information security officers, what we're hearing a lot now is

718
00:32:45,840 --> 00:32:49,240
Speaker 12: particularly in the enterprise, that they don't want another solution.

719
00:32:49,320 --> 00:32:50,920
Speaker 12: They don't want to buy more. They need to actually

720
00:32:50,960 --> 00:32:53,480
Speaker 12: figure out how to integrate what they've got and patch

721
00:32:53,520 --> 00:32:56,120
Speaker 12: the holes that pop up inevitably when you integrate and

722
00:32:56,120 --> 00:32:59,440
Speaker 12: implement a lot of new technologies. That being said, to

723
00:32:59,480 --> 00:33:02,640
Speaker 12: your point, underlying threats persist, and I think AI is

724
00:33:02,680 --> 00:33:05,360
Speaker 12: going to accelerate that. Just the ease at which a

725
00:33:05,360 --> 00:33:08,000
Speaker 12: hacker can now you know, spoo for fish or spam

726
00:33:08,120 --> 00:33:10,120
Speaker 12: or do other things in a much more sophisticated way,

727
00:33:10,560 --> 00:33:13,280
Speaker 12: I think makes the cyber attack surface ever more dangerous.

728
00:33:13,600 --> 00:33:15,240
Speaker 12: And so we do see a lot of innovative new

729
00:33:15,280 --> 00:33:17,960
Speaker 12: companies that are solving those problems as well as in

730
00:33:18,000 --> 00:33:19,880
Speaker 12: other segments of the market, you know, down market. We

731
00:33:19,920 --> 00:33:22,560
Speaker 12: made an investment last year in a company called Blackpoint,

732
00:33:23,320 --> 00:33:26,080
Speaker 12: which has an MDR solution and they bring it sort

733
00:33:26,080 --> 00:33:28,760
Speaker 12: of all in one way to solve cyber problems for

734
00:33:28,800 --> 00:33:32,040
Speaker 12: smaller customers, and they're probably the highest growing company in

735
00:33:32,080 --> 00:33:34,800
Speaker 12: our portfolio right now because the demand is still clearly there.

736
00:33:34,800 --> 00:33:36,760
Speaker 12: So I think it very much depends on the segment

737
00:33:36,760 --> 00:33:38,560
Speaker 12: of the market the types of tools you're selling into.

738
00:33:39,160 --> 00:33:41,440
Speaker 5: Interesting that you point out that black Point Cyber was

739
00:33:41,720 --> 00:33:44,120
Speaker 5: a check you wrote last year where else have you

740
00:33:44,160 --> 00:33:45,040
Speaker 5: been deploying.

741
00:33:44,720 --> 00:33:45,440
Speaker 1: Your capital there?

742
00:33:45,480 --> 00:33:48,840
Speaker 5: For in this whole environment where generative AI suck the

743
00:33:48,840 --> 00:33:51,680
Speaker 5: oxygen down the room, have you just been leaning into

744
00:33:51,760 --> 00:33:53,240
Speaker 5: that theme or finding other ways?

745
00:33:53,560 --> 00:33:56,120
Speaker 12: Yeah, So our fund is really more sort of late

746
00:33:56,120 --> 00:33:59,320
Speaker 12: stage growth equity and even into some small growth her buyouts,

747
00:33:59,360 --> 00:34:01,560
Speaker 12: and so we're not we have a separate venture capital fund.

748
00:34:01,560 --> 00:34:03,160
Speaker 12: I think you've spoken to some of my partners from

749
00:34:03,200 --> 00:34:05,560
Speaker 12: that team before. You know, we really were born to

750
00:34:05,600 --> 00:34:07,640
Speaker 12: sit in between our venture effort and our large cap

751
00:34:07,640 --> 00:34:09,680
Speaker 12: private equity effort and sort of fill that gap for

752
00:34:09,840 --> 00:34:12,759
Speaker 12: later stage companies. And so for us, the generative I

753
00:34:13,160 --> 00:34:16,719
Speaker 12: sort of theme, which is obviously pervasive across the tech ecosystem,

754
00:34:17,200 --> 00:34:19,520
Speaker 12: is less of a direct investment opportunity. I think that's

755
00:34:19,840 --> 00:34:22,280
Speaker 12: earlier stage, you know, more risky, more venture capital.

756
00:34:23,000 --> 00:34:23,160
Speaker 9: You know.

757
00:34:23,200 --> 00:34:26,680
Speaker 12: For us, what we're looking for is established businesses, often

758
00:34:26,680 --> 00:34:30,200
Speaker 12: founder owned and led, who have reached some scale and

759
00:34:30,239 --> 00:34:32,560
Speaker 12: are looking for not just capital but support to kind

760
00:34:32,560 --> 00:34:34,440
Speaker 12: of help get to the next level. So, you know,

761
00:34:34,440 --> 00:34:36,280
Speaker 12: how do they get from fifty seventy five one hundred

762
00:34:36,280 --> 00:34:38,839
Speaker 12: million of revenue to two three four hundred million. And

763
00:34:38,880 --> 00:34:41,520
Speaker 12: that may be things like we need some outside help

764
00:34:41,560 --> 00:34:44,600
Speaker 12: in thinking about how to leverage generative AI to drive

765
00:34:44,600 --> 00:34:47,319
Speaker 12: our own process efficiency and find ways to innovate in

766
00:34:47,320 --> 00:34:49,920
Speaker 12: our product segment. It may be going to do their

767
00:34:49,960 --> 00:34:52,400
Speaker 12: first scale acquisition, it may be entering a new market,

768
00:34:52,640 --> 00:34:54,480
Speaker 12: and so we tend to be more focused right now

769
00:34:54,560 --> 00:34:57,000
Speaker 12: on how we can help our portfolio companies as well

770
00:34:57,040 --> 00:34:59,879
Speaker 12: as new investments leverage generatve AI as opposed to sort

771
00:34:59,880 --> 00:35:02,680
Speaker 12: of trying to back the next model or sort of

772
00:35:02,960 --> 00:35:03,719
Speaker 12: pure AI.

773
00:35:03,560 --> 00:35:04,279
Speaker 1: Company, if you will.

774
00:35:04,320 --> 00:35:07,080
Speaker 12: Now, over time that will evolve, but for now that

775
00:35:07,200 --> 00:35:08,560
Speaker 12: just feels to us a little bit early and a

776
00:35:08,560 --> 00:35:10,880
Speaker 12: little more sort of speculative than our focus.

777
00:35:11,400 --> 00:35:15,759
Speaker 5: And in that less speculative, more mature business, there has

778
00:35:15,840 --> 00:35:18,759
Speaker 5: been sort of a tough environment ultimately, people not wanting

779
00:35:18,800 --> 00:35:20,960
Speaker 5: to write such bigger checks to such big up companies

780
00:35:21,040 --> 00:35:25,120
Speaker 5: or indeed seed being very active other areas still slightly

781
00:35:25,160 --> 00:35:26,640
Speaker 5: concerned amid the economic environment.

782
00:35:26,840 --> 00:35:27,839
Speaker 1: Has that changed at all?

783
00:35:27,880 --> 00:35:29,560
Speaker 5: Have you actually found that, No, there was this real

784
00:35:29,600 --> 00:35:33,320
Speaker 5: sweet spot where companies are actually revenue generating, profit generating,

785
00:35:33,360 --> 00:35:34,799
Speaker 5: and that's where you want to be writing the checks.

786
00:35:34,960 --> 00:35:37,160
Speaker 12: Yeah, I think you've Again, I think there's different segments

787
00:35:37,200 --> 00:35:39,440
Speaker 12: of the market where we play. So what we did

788
00:35:39,480 --> 00:35:41,560
Speaker 12: see in the back half of last year. Is activity

789
00:35:41,560 --> 00:35:43,920
Speaker 12: really start to pick out on the buy outside of

790
00:35:43,960 --> 00:35:46,840
Speaker 12: our business. So growth your sort of mid market buyouts.

791
00:35:47,680 --> 00:35:51,360
Speaker 12: You know, companies that are high quality businesses of scale,

792
00:35:51,480 --> 00:35:54,400
Speaker 12: have some profitability, and in many cases have existing investors

793
00:35:54,440 --> 00:35:56,880
Speaker 12: who are starting to think about liquidity after a period

794
00:35:56,880 --> 00:35:59,160
Speaker 12: of the environment where it was tougher to do so.

795
00:35:59,200 --> 00:36:01,160
Speaker 12: And so that part of our business has picked up

796
00:36:01,239 --> 00:36:02,160
Speaker 12: quite significantly.

797
00:36:02,200 --> 00:36:04,880
Speaker 5: He's doing the buying, who are they tending to go

798
00:36:04,920 --> 00:36:07,120
Speaker 5: with other smaller companies? Are they being bought by larger companies,

799
00:36:07,160 --> 00:36:08,240
Speaker 5: Because it's a combination.

800
00:36:08,680 --> 00:36:10,759
Speaker 12: I'd say in many cases where where we're looking, it's

801
00:36:10,840 --> 00:36:13,680
Speaker 12: new financial investors coming in with a new thesis and

802
00:36:13,719 --> 00:36:16,319
Speaker 12: you know, providing some liquidity. In other cases, some of

803
00:36:16,360 --> 00:36:19,680
Speaker 12: our portfolio companies, you know, bigger, better capitalized businesses are

804
00:36:19,680 --> 00:36:22,560
Speaker 12: looking to take advantage and drive M and A as well.

805
00:36:22,800 --> 00:36:24,960
Speaker 12: And then you're seeing some activity from larger strategic So

806
00:36:25,160 --> 00:36:27,360
Speaker 12: i'd say that's still you know, less active. Obviously, the

807
00:36:27,400 --> 00:36:29,880
Speaker 12: IPO markets haven't been a real path for this. So

808
00:36:30,080 --> 00:36:32,120
Speaker 12: the buy outside of our business has been quite active

809
00:36:32,120 --> 00:36:34,080
Speaker 12: and really picked up over the last quarter or two.

810
00:36:35,160 --> 00:36:37,960
Speaker 12: The growth side I'd say is a tale of two worlds.

811
00:36:38,000 --> 00:36:40,640
Speaker 12: If you were one of the companies that raised you know,

812
00:36:40,800 --> 00:36:43,360
Speaker 12: at peak multiples very you know, at the top of

813
00:36:43,360 --> 00:36:46,200
Speaker 12: the market in twenty twenty one, it's still difficult to.

814
00:36:46,160 --> 00:36:47,000
Speaker 1: Go back to market.

815
00:36:47,600 --> 00:36:50,760
Speaker 12: People are still you know, somewhat stigmatic about down rounds,

816
00:36:50,800 --> 00:36:52,640
Speaker 12: and we're seeing a little bit more of that ease up,

817
00:36:53,640 --> 00:36:55,240
Speaker 12: but that part of the market, I think those companies

818
00:36:55,239 --> 00:36:58,440
Speaker 12: still need to grow into those valuations. For the most part. However,

819
00:36:58,560 --> 00:37:00,960
Speaker 12: where we tend to focus is a lot of founder

820
00:37:01,000 --> 00:37:03,040
Speaker 12: owned businesses who didn't raise money during that period of

821
00:37:03,040 --> 00:37:05,760
Speaker 12: time and where we're sort of the first institutional capital

822
00:37:05,800 --> 00:37:08,640
Speaker 12: coming in, and that's very different. The dynamics there are

823
00:37:08,800 --> 00:37:12,120
Speaker 12: around relationship and partnership, and it's less about what's going

824
00:37:12,160 --> 00:37:14,360
Speaker 12: on in the macro and more about when that specific

825
00:37:14,400 --> 00:37:17,480
Speaker 12: founder identifies an opportunity to do something different with their

826
00:37:17,520 --> 00:37:20,120
Speaker 12: business and wants the right partner to help them do that.

827
00:37:20,200 --> 00:37:22,239
Speaker 12: And that tends to be a pretty active segment of

828
00:37:22,239 --> 00:37:24,400
Speaker 12: the market where we've found, actually all of our investments

829
00:37:24,440 --> 00:37:25,600
Speaker 12: last year were a flavor of that.

830
00:37:25,680 --> 00:37:27,799
Speaker 5: For example, and those founders who are by them in

831
00:37:27,800 --> 00:37:29,920
Speaker 5: bootstrapped or have had wealth to be able to invest

832
00:37:29,920 --> 00:37:34,280
Speaker 5: in sales beforehand. I think coming from East coast of America,

833
00:37:34,320 --> 00:37:36,840
Speaker 5: are they generally US? Are you looking more further afield

834
00:37:36,880 --> 00:37:37,400
Speaker 5: and globally.

835
00:37:37,520 --> 00:37:39,400
Speaker 12: It's a great question. You know, we're big believers that

836
00:37:39,440 --> 00:37:41,480
Speaker 12: there are great companies being built all over the world.

837
00:37:41,520 --> 00:37:44,760
Speaker 12: So we have investments in Japan and Brazil and Europe

838
00:37:44,800 --> 00:37:48,440
Speaker 12: and Israel and all over the US. Interestingly, only one

839
00:37:48,480 --> 00:37:50,640
Speaker 12: of our portfolio companies is actually from the Bay Area.

840
00:37:50,840 --> 00:37:54,640
Speaker 12: We have two from Nebraska to phenomenal software companies all

841
00:37:54,719 --> 00:37:56,279
Speaker 12: up and down the East Coast, and so I think

842
00:37:56,320 --> 00:38:00,360
Speaker 12: it really speaks this idea of there's talent everywhere andnology

843
00:38:00,480 --> 00:38:03,640
Speaker 12: is transforming industries around the world. And so our job

844
00:38:03,680 --> 00:38:06,239
Speaker 12: is to go find those founders. And often they're not

845
00:38:06,280 --> 00:38:08,480
Speaker 12: in places you might expect, but they're building, you know,

846
00:38:08,520 --> 00:38:12,239
Speaker 12: phenomenal businesses kind of under the radar, and eventually we'll

847
00:38:12,239 --> 00:38:13,800
Speaker 12: get to a size and scale where they want to

848
00:38:13,840 --> 00:38:15,919
Speaker 12: partner like us to help them sort of scale and grow.

849
00:38:16,040 --> 00:38:19,040
Speaker 1: And how do you find those founders? What is your

850
00:38:19,040 --> 00:38:19,920
Speaker 1: pipeline look like?

851
00:38:20,040 --> 00:38:22,400
Speaker 5: Is it introductions of one found and on business turning

852
00:38:22,400 --> 00:38:23,960
Speaker 5: to another fun in their business, saying they've been a

853
00:38:24,000 --> 00:38:26,919
Speaker 5: great partner is it people that you know have been

854
00:38:27,440 --> 00:38:29,359
Speaker 5: backed to with I mean, how have you found these

855
00:38:29,360 --> 00:38:29,799
Speaker 5: sorts of.

856
00:38:30,160 --> 00:38:33,279
Speaker 12: So this is where I think being part of a

857
00:38:33,360 --> 00:38:36,399
Speaker 12: firm and a platform like being capital is really advantageous.

858
00:38:36,719 --> 00:38:38,960
Speaker 12: You know, we've been investing in the tech ecosystem for

859
00:38:39,320 --> 00:38:40,239
Speaker 12: really our history.

860
00:38:40,280 --> 00:38:41,080
Speaker 1: This is our forty year.

861
00:38:40,960 --> 00:38:43,520
Speaker 12: Anniversary, and so there's a huge amount of relationships and

862
00:38:43,560 --> 00:38:46,760
Speaker 12: networks around the world. We obviously have a venture capital business,

863
00:38:47,000 --> 00:38:48,440
Speaker 12: and so they're seeing a lot of companies at the

864
00:38:48,480 --> 00:38:51,560
Speaker 12: earlier stages, some of which they invest in, many they don't,

865
00:38:51,600 --> 00:38:54,480
Speaker 12: but those relationships persist and ultimately may grow into things

866
00:38:54,520 --> 00:38:56,759
Speaker 12: that are relevant for us. And then there's a lot

867
00:38:56,800 --> 00:38:59,799
Speaker 12: of just proactive sort of outreach. You know, our team

868
00:38:59,840 --> 00:39:01,760
Speaker 12: is traveling all over the world, all over the country

869
00:39:02,520 --> 00:39:05,040
Speaker 12: in very targeted sectors. We like to really focus on

870
00:39:05,440 --> 00:39:07,719
Speaker 12: sub segments of the market that we know well, specific

871
00:39:07,760 --> 00:39:11,759
Speaker 12: pockets of cybersecurity, vertical software, healthcare, IT, fintech, and so

872
00:39:11,840 --> 00:39:14,120
Speaker 12: within those we're trying to be very thematic around Okay,

873
00:39:14,160 --> 00:39:16,560
Speaker 12: these are the segments, these are the companies, these are

874
00:39:16,560 --> 00:39:18,120
Speaker 12: the founders, and how do we get in front of

875
00:39:18,120 --> 00:39:20,880
Speaker 12: them build those relationships which in many cases take you know,

876
00:39:20,880 --> 00:39:23,440
Speaker 12: four or five six years until they result in any

877
00:39:23,520 --> 00:39:26,080
Speaker 12: kind of transaction opportunity, until a lot of our time

878
00:39:26,120 --> 00:39:27,320
Speaker 12: and effort is really spent there.

879
00:39:27,800 --> 00:39:30,279
Speaker 5: So relationship business, thanks for spending some of that time

880
00:39:30,320 --> 00:39:33,640
Speaker 5: with us today, darn Abramsen, his partner at Bain Capital's

881
00:39:33,640 --> 00:39:44,880
Speaker 5: tech opportunities team. Universal Music it snapped up a minority

882
00:39:44,920 --> 00:39:47,560
Speaker 5: stake in coren Music Partners. That's a company that owns

883
00:39:47,600 --> 00:39:50,080
Speaker 5: one than sixty thousand songs by the likes of John

884
00:39:50,160 --> 00:39:52,080
Speaker 5: Legend or Lord or The Weekend and more. And the

885
00:39:52,160 --> 00:39:54,200
Speaker 5: music giant is actually paying two hundred and forty million

886
00:39:54,239 --> 00:39:56,560
Speaker 5: dollars for a twenty five point eight per cent steak

887
00:39:56,680 --> 00:40:00,080
Speaker 5: in the business here with more on why Murkes Michelle Davis,

888
00:40:00,160 --> 00:40:03,320
Speaker 5: and the reason is well, sort of exposure to music

889
00:40:03,400 --> 00:40:05,880
Speaker 5: rights to them bring to the masses, How do they benefit?

890
00:40:06,320 --> 00:40:09,560
Speaker 9: So? Universal Music already owns a ton of music rights.

891
00:40:09,920 --> 00:40:11,560
Speaker 9: You'll remember a big deal they did a couple of

892
00:40:11,600 --> 00:40:13,560
Speaker 9: years ago was buying Bob Dylan's whole catalog.

893
00:40:15,000 --> 00:40:16,319
Speaker 1: But this by being a.

894
00:40:16,280 --> 00:40:18,759
Speaker 9: Minority of investor, they're gonna have exposure to these music

895
00:40:18,800 --> 00:40:22,000
Speaker 9: rights in this particular catalog without being a direct owner.

896
00:40:22,719 --> 00:40:24,520
Speaker 9: Universal Music as well as a lot of other big

897
00:40:24,560 --> 00:40:27,319
Speaker 9: media music companies. Media companies are under pressure right now

898
00:40:27,320 --> 00:40:30,120
Speaker 9: to show returns to their shareholders, and this is kind

899
00:40:30,120 --> 00:40:31,640
Speaker 9: of an indirect way for them to do that without

900
00:40:31,680 --> 00:40:34,680
Speaker 9: spending too much, you know, dipping their toes into this

901
00:40:34,719 --> 00:40:38,239
Speaker 9: particular catalog, without just putting too much of their balance

902
00:40:38,280 --> 00:40:40,160
Speaker 9: sheet behind it. But I think it all speaks to

903
00:40:40,200 --> 00:40:43,279
Speaker 9: a much bigger trend within the music industry where some

904
00:40:43,360 --> 00:40:46,960
Speaker 9: of the traditional you know, Wall Street firms like Kkar, Apollo,

905
00:40:47,000 --> 00:40:50,160
Speaker 9: Blackstone that really poured money into the industry a few

906
00:40:50,200 --> 00:40:53,040
Speaker 9: years ago when music valuations were surging, they've all been

907
00:40:53,080 --> 00:40:56,040
Speaker 9: looking for an exit because you know, private equity, even

908
00:40:56,160 --> 00:41:00,279
Speaker 9: outside of music, outside of entertainment, Their LPs want them

909
00:41:00,320 --> 00:41:03,279
Speaker 9: to show some returns, to returns some money. As it's

910
00:41:03,280 --> 00:41:05,400
Speaker 9: gotten more expensive to them for them to invest in

911
00:41:05,480 --> 00:41:08,480
Speaker 9: stuff with rates going up, they've been under pressure to

912
00:41:08,520 --> 00:41:10,800
Speaker 9: show that that money to them. And this for Kkar,

913
00:41:11,080 --> 00:41:12,840
Speaker 9: you know, exiting, this is one way for them to

914
00:41:13,200 --> 00:41:13,480
Speaker 9: do that.

915
00:41:13,960 --> 00:41:18,239
Speaker 5: So Dundee Partners takes the other seventy odd percent of it,

916
00:41:18,400 --> 00:41:21,680
Speaker 5: and that's run by the Handel family. Ultimately, what does

917
00:41:21,800 --> 00:41:26,000
Speaker 5: Universal Music benefited shareholders with right with rights ownership. Is

918
00:41:26,000 --> 00:41:27,440
Speaker 5: it that they think the value will go up on

919
00:41:27,480 --> 00:41:29,040
Speaker 5: the rights to the music or they can use it.

920
00:41:29,000 --> 00:41:30,440
Speaker 1: In different and more interesting manners.

921
00:41:30,680 --> 00:41:32,359
Speaker 9: I think that's part of the assumption is you have

922
00:41:32,440 --> 00:41:34,600
Speaker 9: to expect if the value will go up, and it's

923
00:41:34,640 --> 00:41:36,920
Speaker 9: also a predictable revenue stream for them.

924
00:41:36,960 --> 00:41:40,080
Speaker 1: You know, you know right now a lot of the music.

925
00:41:39,880 --> 00:41:42,799
Speaker 9: Industry has recovered because we've figured out streaming. Compared to

926
00:41:42,800 --> 00:41:45,279
Speaker 9: twenty years ago, when you know, the music industry didn't

927
00:41:45,280 --> 00:41:47,560
Speaker 9: know what to do with everyone pirating music. Streaming is

928
00:41:47,560 --> 00:41:49,760
Speaker 9: a thing now, but they're still facing a lot of disruption.

929
00:41:50,760 --> 00:41:53,680
Speaker 9: There's questions around what will happen with TikTok and ai,

930
00:41:53,760 --> 00:41:55,919
Speaker 9: how that will affect everything. So this just gives them

931
00:41:56,000 --> 00:41:59,840
Speaker 9: a predictable revenue stream to build as show investors.

932
00:42:00,239 --> 00:42:01,760
Speaker 1: Well said Michelle Davis.

933
00:42:01,840 --> 00:42:04,080
Speaker 5: We thank you for a time on all those transactions

934
00:42:04,080 --> 00:42:06,480
Speaker 5: within the music industry. Meanwhile, how does it for this

935
00:42:06,640 --> 00:42:08,600
Speaker 5: edition of bloombig Technology. You do not want to forget

936
00:42:08,600 --> 00:42:10,880
Speaker 5: to check out our podcast. Got so much more to

937
00:42:10,920 --> 00:42:13,960
Speaker 5: wrap up, and of course stay braced from video earnings

938
00:42:14,000 --> 00:42:16,480
Speaker 5: after the bell we'll be digesting that tomorrow.

939
00:42:16,520 --> 00:42:17,640
Speaker 1: This is bluebad Technology