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Speaker 1: From Marhard where Innovation of Money and Power Collie in

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Speaker 1: Silicon Valley, NBN.

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Speaker 2: This is Bloomberg Technology with Caroline Hyde and Ed loved Love.

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Speaker 3: I'm Caroline Heide of Bloomberg's World headquarters in New York

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Speaker 3: and I Mad Lovelow in San Francisco.

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Speaker 4: This is Bloomberg Technology.

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Speaker 5: Coming up.

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Speaker 3: We'll talk the state of the digital consumer as inflation shoes.

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Speaker 5: Some signs of moderation, with a founder of course, joining us.

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Speaker 3: CEO of Mickmac, a global e commerce analytics platform.

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Speaker 6: Plass will sit down for an exclusive conversation with the

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Speaker 6: CEO of Data Breaks, one of the fastest growing software companies,

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Speaker 6: to discuss how they're utilizing AI to power their business.

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Speaker 3: And sticking with AI, we break down the earning some

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Speaker 3: oracle as the AI frenzy spurs cloud demand. Plus we

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Speaker 3: look at how salesforce so focusing in on artificial intelligence.

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Speaker 3: But first let's focus in on these markets because we

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Speaker 3: have some calling some signs of calling in inflation. If

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Speaker 3: you look at not the core CPI, but look at

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Speaker 3: the main overall print, we're back at four percent low

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Speaker 3: as that we've had since March twenty twenty one. So

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Speaker 3: we are seeing some optimism the FED will holds and

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Speaker 3: stand steady for the month of June. We're seeing Na's

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Speaker 3: that cup about five tens percent, benefiting from that risk

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Speaker 3: on feel. But look, this inflationary pressure is being felt elsewhere.

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Speaker 3: We think about the UK at the moment, yields absolutely

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Speaker 3: spiking and I want to show what asset is still

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Speaker 3: trading there, the pound versus the US dollar, higher versus

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Speaker 3: US dollars. We think the FED might pause, but all

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Speaker 3: eyes on maybe even a six percent level when you're

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Speaker 3: thinking of central bank policy over at the Bank of England.

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Speaker 3: Interesting of course, moves coming from China. They're going to

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Speaker 3: the opposite direction. Instead of curtailing inflation, they're looking to

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Speaker 3: speed up their economy. They're cutting rates that were surprise

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Speaker 3: overnight that really boid some of the commodities markets. We're

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Speaker 3: seeing up more than three percent in oil. But moving

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Speaker 3: on to one of our favorite more risk assets in

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Speaker 3: the world of technology, let's look at what's happening in

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Speaker 3: the world of crypto. Look, not dramatic moves, but ill

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Speaker 3: pressure remaining on bitcoin. We're atwred and seventy seven right now.

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Speaker 3: This is even with a weaker dollar ed so clearly

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Speaker 3: some of this regulatory our anxiety is still pressuring the

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Speaker 3: main crypto asset ed.

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Speaker 6: Yeah, when it comes to individual movers, that CPI print

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Speaker 6: and the idea around the FED is having some impact here.

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Speaker 6: But there's one name I'm looking at, which is Tesla,

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Speaker 6: up for a thirteenth consecutive session, longest streak of gains

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Speaker 6: on record trading at a September high. One of the

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Speaker 6: kind of news events of the last twenty four hours

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Speaker 6: was all those charging names coming out all at once,

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Speaker 6: basically Yessay afternoon saying yep, you know what, we're going

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Speaker 6: to adopt the NCACS standard, kind of pivoting to profressure

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Speaker 6: and momentum in that space. A few stories that we're

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Speaker 6: going to cover throughout the show playing out in equity markets.

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Speaker 6: When it comes to movers as well, you mentioned Oracle

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Speaker 6: and Salesforce. Oracle moving to the upside one point three percent.

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Speaker 6: AI is driving cloud momentum. We'll get deep into those

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Speaker 6: numbers with bion this Anna Ragrana, but interesting AI story

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Speaker 6: with Salesforce as well, it's moving to the downside one

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Speaker 6: and a half percent. They had this event where they

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Speaker 6: kind of explained in real terms how their work in

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Speaker 6: AI is going to better their existing suite of products.

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Speaker 6: Remember there was also a referendum essentially on Mark Benioff's

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Speaker 6: popularity with investors, which we can talk about. We're about

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Speaker 6: to go to Miami to Florida and talk about Trump.

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Speaker 6: So I just note this stock rumble. The conservative or

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Speaker 6: right leaning social platform down four and a half percent.

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Speaker 6: With the president in focus, and what's happening in court?

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Speaker 3: Yeah, former President Donald Trump is in focus. Let's go

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Speaker 3: straight there, just for an update really on what's happening.

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Speaker 3: We're expecting the appearance in the Miami court today after

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Speaker 3: being indicted on thirty seven counts of allegedly mishandling classified documents.

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Speaker 3: As of course, after leaving the White House, Bloomberg's Kaylee

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Speaker 3: Lines is outside the courthouse. And when are we anticipating

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Speaker 3: in arrival Kayley.

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Speaker 7: Well, three pm Eastern time is when he is due

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Speaker 7: to report here at the Federal Courthouse. We may not

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Speaker 7: actually see him arrive, though, it's expected that he will

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Speaker 7: enter the Fort House via the underground garage, but once

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Speaker 7: inside he will be arrested and processed just like anyone

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Speaker 7: else who has been indicted on federal criminal charges. Its

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Speaker 7: potential that he could have his fingerprint and mugshot taken.

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Speaker 7: He may even need to surrender his passport. Then he

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Speaker 7: will go up to the thirteenth floor of this building

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Speaker 7: behind me a pear before a judge and is expected

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Speaker 7: to plead not guilty. Of course this this indictment came

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Speaker 7: down last week. The president has maintained that he is innocent,

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Speaker 7: said that this is a witch hunt, election interference at

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Speaker 7: the highest level, and that is likely the kind of

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Speaker 7: messaging he is likely to take with him from Miami

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Speaker 7: back up to Bedminster, New Jersey this evening, where he

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Speaker 7: will be speaking at his golf club at eight fifteen

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Speaker 7: pm Eastern Time, addressing his supporters, supporters and holding a

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Speaker 7: donor event. His campaign expects that he could raise two

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Speaker 7: million dollars at that event tonight, which is taking place

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Speaker 7: just hours after he will become the first former president

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Speaker 7: in history ever to be arranged on federal criminal charges.

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Speaker 6: Kaylee, local police, one of which has just walked past

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Speaker 6: you in that shot, and authorities preparing for some demonstration

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Speaker 6: right what's the scene like on the ground right now

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Speaker 6: where you are? Well?

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Speaker 7: The police chief ahead of today has sent from five

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Speaker 7: thousand up to as many as fifty thousand demonstrators could

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Speaker 7: be here today and as a result, there is a

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Speaker 7: pretty heavy security presence. There is a lot of police,

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Speaker 7: There are perimeters set up all around, and there have

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Speaker 7: been I would say several dozen of both pro Trump

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Speaker 7: and anti Trump demonstrators here today. There is a lot

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Speaker 7: of Trump flags, people wearing Make America Great Again gear,

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Speaker 7: a couple that have T shirts on that indicate Trump

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Speaker 7: is not guilty, that Trump won the election, but there

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Speaker 7: are some anti Trump people as well, holding up signs

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Speaker 7: like lock him Up. So far, though, it does seem peaceful.

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Speaker 7: President Trump, of course, had called for his supporters to

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Speaker 7: show up and peacefully protest. It doesn't seem like there

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Speaker 7: is too much disruptive activity that is taking place here

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Speaker 7: today at this point.

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Speaker 6: All right, Bloombergs Katie Lines will be bringing us the

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Speaker 6: latest throughout the day from Miami, Florida. But just gave

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Speaker 6: us the latest here on Bloomberg Technology. Thank you so much.

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Speaker 6: Now elsewhere in the world of eco head line CPI

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Speaker 6: numbers inflation easing to the lowest levels since March with

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Speaker 6: twenty twenty one. Let's get to the view from the

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Speaker 6: founder of mickmac a global e commerce enablement and an

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Speaker 6: analytics platform for multichannel brands showing us now Rachel Tippograph,

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Speaker 6: who is the MICKMAC founder and CEO, at the street

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Speaker 6: level or the online level, what does that inflation print

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Speaker 6: tell you about the direction of travel right now?

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Speaker 4: Rachel?

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Speaker 8: Yeah, And you know, with the results just coming out,

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Speaker 8: it's really interesting to think about why we're saying inflation

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Speaker 8: might be going down. If we look at food and

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Speaker 8: consumer good categories like appliances, those have been relatively flat.

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Speaker 8: But when we remove that from the equation, inflation is

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Speaker 8: still going up. And the reason why we're seeing categories

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Speaker 8: like food and appliances stay relatively flat is that for

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Speaker 8: the last few quarters, brand manufacturers have been raising praises,

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Speaker 8: and the reason why they've been reached prices is that

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Speaker 8: it's more extensive than ever before to bring consumer goods

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Speaker 8: to market, to keep them on the shelf, and to

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Speaker 8: market them to consumers. To offset those margins, they've been

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Speaker 8: raising prices, which is why at NCKMAC we feel core

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Speaker 8: inflation is more indicative of what's happening in the general economy,

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Speaker 8: and when we look at that inflation continuing to go

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Speaker 8: up against e commerce conversion rates. What we're seeing at

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Speaker 8: Mickmac is that year over year e commerce conversion rates

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Speaker 8: have been declining since twenty twenty And to put it

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Speaker 8: into context, in twenty twenty one, the average e comm

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Speaker 8: conversion rate we saw at Mickmac was seven point four percent.

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Speaker 8: We're now halfway through twenty twenty three and the average

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Speaker 8: e comm conversion rate is at four point eight percent.

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Speaker 8: So it's showing that consumers are more trepidacious to buying

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Speaker 8: right now.

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Speaker 3: Yeah, what does that mean in terms of companies trepidation

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Speaker 3: about marketing? An interesting headline just across the Brimberg is

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Speaker 3: going to open a pop up restaurant of Parery call

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Speaker 3: Netflix bytes in La. I mean, of course that's a

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Speaker 3: marketing focus. It's itself a company that's taking in advertising,

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Speaker 3: in fact dolos from other companies. Now, how willing and

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Speaker 3: able are companies to experiment in this environment if the

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Speaker 3: conversion rates up pretty low?

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Speaker 9: Yeah?

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Speaker 8: I think for most big brands and brands that understand

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Speaker 8: what it takes to stand the test of time, you

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Speaker 8: have to advertise during trying economic times. Look in Procter Gamble,

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Speaker 8: they've proven that over one hundred years that being said,

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Speaker 8: every dollar is being scrutinized right now by folks that

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Speaker 8: hold the title like CFO, and they're holding the marketing

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Speaker 8: teams accountable to driving business results, which has created a

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Speaker 8: perfect tailwind for the rise of retail media. Meaning meta's

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Speaker 8: biggest competitor isn't just Snap or TikTok, it's also Amazon,

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Speaker 8: Target Walmart. And what the retailers have at their advantage

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Speaker 8: is consumer purchase data and their ability to monetize that

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Speaker 8: data and say, hey, we know who needs to replenish

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Speaker 8: diapers right now, So if you have one dollar to

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Speaker 8: spend to market diapers, you should give it to us

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Speaker 8: over a platform that may not know that. So from

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Speaker 8: a marketing standpoint, we're continuing to see brands spend, but

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Speaker 8: they're spending in more strategic channels that have more visibility

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Speaker 8: into the end sales data so they can understand marketing effectiveness.

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Speaker 6: Rachel, we're showing on the screen, you know, the difference

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Speaker 6: in direction of travel between goods and services inflation, and

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Speaker 6: you learn in a recessionary and in inflation re environment that.

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Speaker 4: Who is leading who.

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Speaker 6: You know that there's a response to the consumer and

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Speaker 6: their change in behavior, but there's also the reaction from

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Speaker 6: the retailers themselves based on what you see.

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Speaker 4: In the market.

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Speaker 6: Who moves more quickly, you know, the consumer to change

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Speaker 6: habits or the online retailer to respond to them.

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Speaker 8: Yeah, it's it's a given a take per your point.

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Speaker 8: But right now, what we're seeing into in terms of

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Speaker 8: how consumers are spending is they're really spending on essentials.

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Speaker 8: At Nickmac, we have over three thousand retailers in the

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Speaker 8: network and we collect basket level sales data, and so

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Speaker 8: we can tell you right now what America's buying bottled water,

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Speaker 8: granola bars, teeth whitening kits, press on nails, and weed killers.

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Speaker 8: And what that shows you is, hey, these are essential items.

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Speaker 8: But when it comes to things like beauty, for example,

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Speaker 8: you could go to the salon to get your nails done,

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Speaker 8: or you could buy on press on nails at Walmart.

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Speaker 8: And so in some of these discretionary categories, we are

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Speaker 8: seeing consumers be more choosy with the things that they're

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Speaker 8: willing to do on their own versus go to a

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Speaker 8: more service oriented place.

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Speaker 3: A boy, if I served one more press on nail

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Speaker 3: kit Instagram marketing, I'm going to explode, so clearly that's

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Speaker 3: the place this is right now, mus you got them

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Speaker 3: all on Rachel Pohograph. Thank you so much spending some

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Speaker 3: time with us. I think mac founder and CEO really interesting.

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Speaker 3: Their weekkiller sexy stuff. Meanwhile, coming up and we're going

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Speaker 3: to be sitting down for an exclusive conversation this year

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Speaker 3: of Data Bricks as they acquire Rubicon to stealth infrastructure startup.

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Speaker 5: It's focusing on storage systems that's key for AI. So

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Speaker 5: that's the CEO. Meanwhile, watching shares of Apple.

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Speaker 3: The company's stock is been downgraded to neutral from buy

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Speaker 3: by UBS, which.

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Speaker 5: The analysts is citing soft demand.

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Speaker 3: Outlook for the iPhone and in particular for services growth

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Speaker 3: as well. And it's notable that this downgrade is pushing

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Speaker 3: bullish analysts ratings on the stock to a two year

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Speaker 3: low of three ten percent. Remember it was a record

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Speaker 3: high yesterday.

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Speaker 9: This's Atlmberg.

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Speaker 6: Data Bricks is announcing it's acquired Rubicon, a stealth infrastructure

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Speaker 6: startup focusing on storage systems for AI. Data Bricks is

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Speaker 6: used by more than nine thousand organizations worldwide who rely

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Speaker 6: on the companies lake House platform to unify their data,

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Speaker 6: analytics and AI. The startup also hit key milestones for

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Speaker 6: revenue and top line growth. Joining us now Data Brick

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Speaker 6: CEO Ali Godzi a lot to go over.

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Speaker 4: I'm learning a lot.

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Speaker 6: About data breaks this morning. Let's start with the top line.

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Speaker 6: You've just closed out a financial year at the end

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Speaker 6: of jen hit a billion dollars of revenue, which is

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Speaker 6: a milestone. But the growth is really interesting. That makes

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Speaker 6: you one of the fastest growing software names out there.

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Speaker 4: What's driving it?

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Speaker 2: Yeah, it's really tailwinds.

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Speaker 10: By the way, it's the fastest growing software if according

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Speaker 10: to our records. But what is driving it is really

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Speaker 10: we're seeing tailwinds. One around AI. Everyone wants AI now one.

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Speaker 10: We've been saying it for ten years that data innai

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Speaker 10: is going to be the future, that in every industry

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Speaker 10: the winners are going to be data ANAI companies. But

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Speaker 10: something happened in November last year and everyone kind of

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Speaker 10: realized after chat GPT that this is the future. And

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Speaker 10: the second thing is tcoor reduction. People want to cut

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Speaker 10: down their costs of data spend and our Lakehouse platform

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Speaker 10: helps that.

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Speaker 6: Data warehousing SQL is the product. You also sharing some

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Speaker 6: financials on that particular product. So I remember when you

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Speaker 6: announced it, you know, it's a domain you compete with

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Speaker 6: snowflake in. What's driving this growth? Is this a market

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Speaker 6: share gain for you?

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Speaker 10: Yeah, So we've announced that we now passed one hundred

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Speaker 10: million ARR on our data warehousing product that we just

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Speaker 10: frankly launched just a year ago. So what's going on

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Speaker 10: here is that this Lakehouse paradigm helps organizations cut down

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Speaker 10: their cost of data warehousing significantly. And you know, there's

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Speaker 10: a tale of two cities. On the one hand side,

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Speaker 10: everybody wants AI and they want to spend on AI.

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Speaker 10: On the other hand, everyone wants to reduce their cost

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Speaker 10: and they want to reduce the spend on data warehousing.

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Speaker 10: So it's really that cost tco optimization that's driving that

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Speaker 10: tail went behind data.

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Speaker 6: Warehousing spent caroline from organic growth to inorganic growth. Ali,

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Speaker 6: godseeing data breaks who have been outshot.

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Speaker 3: Yeah, I'm interested in that deal, Rubicon. This is all

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Speaker 3: about storage systems. You say, it's the backbone of AI. Ali,

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Speaker 3: did you have to pay up? I mean, this isn't

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Speaker 3: a cheap time to be trying to buy a company

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Speaker 3: related to AI.

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Speaker 5: Right now?

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Speaker 10: Yeah, right now, you have to pay up. That's just

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Speaker 10: as simple as it is. And everyone that's doing anything

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Speaker 10: with AI. And this was a team that can build

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Speaker 10: storage for all kinds of unstructured data. This is the

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Speaker 10: oil that fuels AI.

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Speaker 2: You know, those are not cheap right now. And this

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Speaker 2: is the team that.

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Speaker 10: Actually has built it previously at drop.

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Speaker 2: Box and before that at Google.

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Speaker 10: So this is a team that really knows how to

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Speaker 10: build this kind of sort of data systems for AI.

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Speaker 10: You know, Sergay and team are really really experienced. So

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Speaker 10: we're excited to have them as part of Data Bricks.

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Speaker 3: Of course, you, as you said, for the last decade,

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Speaker 3: have been telling people the future is data, it's AI.

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Speaker 3: Your own well experience two decades in this particular field

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Speaker 3: and in particular with deep routes not only in R

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Speaker 3: research ALI, but also in open source software, and I'm

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Speaker 3: interested in your take and just sort of theoretically at

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Speaker 3: the moment, as everyone Warren debates as to whether open AI,

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Speaker 3: Microsoft Google going to eat the entire lunch when it

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Speaker 3: comes to large language models when it comes to application,

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Speaker 3: and whether the open source is actually already showing that

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Speaker 3: they aren't any modes.

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Speaker 5: Where do you stand on this divide?

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Speaker 2: Yeah, I would say two things. I would say. On

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Speaker 2: the one hand, We absolutely.

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Speaker 10: Want open source to flourish because as AI becomes more

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Speaker 10: and more powerful, we want the researchers around the world

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Speaker 10: to understand this technology. We don't want just one or

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Speaker 10: two companies to sit on top of this and there

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Speaker 10: are only ones that know if.

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Speaker 2: It's going wrong or right.

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Speaker 10: We want researchers the whole world to understand the models.

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Speaker 10: What can go around well, you know, how do we

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Speaker 10: align them with US US one. The second thing is

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Speaker 10: I actually think it's impossible for one or two companies

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Speaker 10: to keep up with the competition. Every university on the planet,

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Speaker 10: every researcher now in the data field, in the tech field,

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Speaker 10: is focused on llm's generative AI.

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Speaker 2: I've never seen anything like it before.

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Speaker 10: So it's going to be very hard for one company

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Speaker 10: to keep a proprietary model that they say is ahead

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Speaker 10: of everybody else, and it's ahead of open source. So

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Speaker 10: and we've seen this every day we're having new results

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Speaker 10: in open source. You know, I follow it very closely.

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Speaker 10: It's no longer months, it's no longer weeks, it's every day,

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Speaker 10: multiple times a day, there's a new breakthrough result. So

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Speaker 10: I think it's going to be very hard for proprietary

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Speaker 10: closed companies to say, ahead, what is.

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Speaker 6: The Alley Gods view on when and why data breaks

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Speaker 6: would go public?

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Speaker 4: And I just want to caveat that.

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Speaker 6: You know, there's reports that you kind of trim the

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Speaker 6: valuation on the company. Didn't slash the trimmed, but what

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Speaker 6: would push you to do that?

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Speaker 10: Yeah, So look, I've always said that IPO is something

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Speaker 10: we will do in the future for us. We think

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Speaker 10: that we're going to be a really successful, sustainable business

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Speaker 10: in the long run, in you know, next decade or so.

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Speaker 10: So this is just a milestone right now. The markets

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Speaker 10: are shut down, We're not over optimizing for this IPO event.

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Speaker 10: We'll get there, you know, whenever the time is right.

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Speaker 10: There's just so much demand for our business right now.

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Speaker 10: And Frank, we want to be able to invest in AI.

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Speaker 10: We want to be able to do the investment set

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Speaker 10: we're allowed to do us private companies. It would be

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Speaker 10: actually hard to do that as a public company. So

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Speaker 10: actually right now it's really helping us to stay for

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Speaker 10: private data.

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Speaker 3: Brix CEO, Annie Gods there, We thank you for bringing

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Speaker 3: us the update on some of the revenue numbers and

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Speaker 3: the acquisition.

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Speaker 5: Time Now for.

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Speaker 3: Talking tech Kathy Wood is making new bets on other

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Speaker 3: tech stocks after of course, dropping in video from her funds. Largely,

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Speaker 3: two Ark invest funds purchased roughly one hundred and seventy

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Speaker 3: five thousand shares Meta, while the Ark Autonomous Technology and

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Speaker 3: Robotic etf IT picked up more than ninety eight thousand

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Speaker 3: shares the chip maker TSMC. Meanwhile, TSMC also regaining it's

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Speaker 3: five hundred billion dollar market cap as investors buy into

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Speaker 3: artificial intelligence and looks sift through which stock's the best

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Speaker 3: place to thrive during this AI boom. While TSMC toilted

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Speaker 3: its potential role within AI, has expressed some caution over

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Speaker 3: the outlook for the smartphone market, in particular that of course,

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Speaker 3: comprises a significant chunk of its revenue so far. And

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Speaker 3: let's look at arm So software back chip designer. It's

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Speaker 3: in talks with potential investors, including Intel, to be an

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Speaker 3: anchor in its New York listing later this year. Sources

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Speaker 3: are saying that the company has held talks with other

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Speaker 3: firms about funding. The IPO was expected to be one

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Speaker 3: of the most significant IPOs of the year.

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Speaker 6: Ed Yeah, let's chip away all this story further Bloomberg

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Speaker 6: Deals reporter Katie Ruth joining us from Los Angeles. An

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Speaker 6: anchor investor, you and I have been across many IPOs

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Speaker 6: in years. An anchor investor gives you a bit of

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Speaker 6: confidence appear in your industry.

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Speaker 1: That's very interesting, Yeah, exactly, And investors like this SoftBank

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Speaker 1: stock traded up on the news. Yes, a lot of

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Speaker 1: times you'll see an anchor investor of about one hundred

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Speaker 1: to two hundred million in size to help shore up confidence.

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Speaker 1: You know, it's a vote of confidence, a bit you know,

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Speaker 1: from a competitor and also a partner that shows that

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Speaker 1: they're serious and excited about arms technology.

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Speaker 3: I mean they have a relationship already a technical one.

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Speaker 3: The fact that it would become a financial one, I

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Speaker 3: mean remind us of in the past when this has

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Speaker 3: happened because sort.

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Speaker 5: Of Qualcomm is underpin previous listings as well.

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Speaker 1: Yeah, yeah, it's happened with Qualcom and then Mobile I.

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Speaker 1: There have been other anchor investors in the past. Mobile

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Speaker 1: I was spun out from Intel last year, and so

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Speaker 1: not just in this category, but in general. It's something

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Speaker 1: that you sometimes see with IPOs ahead of the roadshow,

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Speaker 1: ahead of drumming up interest from institutional investors to have

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Speaker 1: this strategic anchor investor to shore up confidence.

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Speaker 6: So Katie, you are the name on the Deals newsletter

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Speaker 6: publishing this morning. A big focus on all the talk

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Speaker 6: out in LA and LA Tech Week and Karen and I,

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Speaker 6: you know, we look at each of these tech Weeks LA,

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Speaker 6: New York, San Francisco. Sometimes a lot comes out of it,

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Speaker 6: sometimes very little does. What did you learn on the ground, Well.

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Speaker 1: I had fun?

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Speaker 2: What what did I learn?

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Speaker 1: I chatted with Mantis, the Chainsmokers, the band. They have

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Speaker 1: a venture fund and they they threw events uh uh

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Speaker 1: djayed by Travis Barker. I mean, it wouldn't be LA

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Speaker 1: Tech Week without participation from Hollywood. I spoke to Will

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Speaker 1: i Am, who my editor joke should be called will

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Speaker 1: A i Am, because he's been into interested in AI

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Speaker 1: for uh really the past decade. He's had multiple AI startups.

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Speaker 1: He has a new one, and he spoke to me

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Speaker 1: about you know, why he's excited about AI, but also

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Speaker 1: how he thinks that you know, it could provide an

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Speaker 1: opportunity for there to be a reset, uh for for

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Speaker 1: new jobs. And you know he's going back to his

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Speaker 1: home community to help, you know, prepare them for the

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Speaker 1: changing job market. There were you know a lot of

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Speaker 1: different events, sometimes at Hollywood mansions and you know, sometimes

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Speaker 1: featuring pizza robots. But you know, it's exciting to catch

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Speaker 1: up with the LA's tech industry.

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Speaker 3: I'm not sure there's any tech reporter that hasn't spoken

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Speaker 3: to me. I have now, I think you've aired you.

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Speaker 3: He turned up a Mercedes events for you. I think

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Speaker 3: I interviewed them Mobile Will Congress or Viva Tech or something. Meanwhile,

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Speaker 3: these events are going thick and fast, and think gets

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Speaker 3: London Technik on at the moment. So maybe he's over

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Speaker 3: there right now. Katie Ruth, we thank you so much for.

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Speaker 5: Telling us about all the NA parties so she has.

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Speaker 3: Been at as well as all the deals that are

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Speaker 3: being done there. Go check out her MNA deals discussion.

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Speaker 3: It's in the latest newsletter on the Bloomberg terminal. Welcome

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Speaker 3: back to Bloomberg Technology. I'm Caroline Hyde.

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Speaker 6: In New York and I Mad Ludlow in San Francisco.

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Speaker 6: It's going to check in on the market. Stocks pushing higher,

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Speaker 6: including the technology sector, driven by the inflation print.

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Speaker 4: That we got.

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Speaker 6: The idea being that the chances of a hike in

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Speaker 6: twenty four hours time at the FED meeting increasingly lower.

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Speaker 6: That's not to say the market thinks that the FED

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Speaker 6: is done, but we are now a little more certain

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Speaker 6: about a June meeting pause or however you want to phrase.

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Speaker 6: It's SP five hundred and seven tens to one percent,

438
00:22:19,040 --> 00:22:22,479
Speaker 6: the tech heavy NAZDA one hundred slightly underperforming that, but

439
00:22:22,560 --> 00:22:25,160
Speaker 6: basically in line that's HISS yields push higher, the US

440
00:22:25,200 --> 00:22:27,760
Speaker 6: ten year three point seven eight percent, up by about

441
00:22:27,800 --> 00:22:30,879
Speaker 6: five basis points. And we talked about our sort of

442
00:22:30,960 --> 00:22:34,160
Speaker 6: favorite risk asset that Bitcoin actually did start to move

443
00:22:34,200 --> 00:22:36,480
Speaker 6: a little lower, down just three tens percent in the

444
00:22:36,560 --> 00:22:39,760
Speaker 6: session to twenty five eight hundred and nine.

445
00:22:39,640 --> 00:22:40,840
Speaker 4: US dollars per token.

446
00:22:41,359 --> 00:22:45,000
Speaker 6: Two kind of mover stories out there this Tuesday morning,

447
00:22:45,359 --> 00:22:49,400
Speaker 6: Oracle and Salesforce, Oracle and earning story where cloud momentum

448
00:22:49,440 --> 00:22:53,879
Speaker 6: being driven by compute demand for AI. Also kind of

449
00:22:53,920 --> 00:22:57,560
Speaker 6: granularity coming from Larry Ellison, the chairman, about two billion

450
00:22:57,600 --> 00:23:01,879
Speaker 6: dollars of bookings fueled by LA compute demand. And then

451
00:23:01,960 --> 00:23:06,800
Speaker 6: Salesforce demonstrating its competence CARO in the field of generative AI,

452
00:23:07,160 --> 00:23:09,520
Speaker 6: how the work they're doing there is going to boost

453
00:23:09,520 --> 00:23:12,480
Speaker 6: their existing offerings in the world of CRM and other

454
00:23:12,560 --> 00:23:15,560
Speaker 6: software suite and tools. But of course we also had

455
00:23:15,560 --> 00:23:18,960
Speaker 6: this kind of soft referendum on Mark Benioff's popularity, which

456
00:23:19,000 --> 00:23:20,920
Speaker 6: he did better on this year than last.

457
00:23:21,040 --> 00:23:23,439
Speaker 3: And it's worth reminding ourselves just how far both of

458
00:23:23,480 --> 00:23:24,800
Speaker 3: these stocks have rallied this year.

459
00:23:24,880 --> 00:23:26,160
Speaker 5: I think Oracle's up more.

460
00:23:26,040 --> 00:23:29,119
Speaker 3: Than fifty percent salesforce giving away a little bit today,

461
00:23:29,160 --> 00:23:30,960
Speaker 3: but at more than sixty percent on the year. Let's

462
00:23:31,000 --> 00:23:33,680
Speaker 3: dive deeper into just what's behind the share price momentum,

463
00:23:33,720 --> 00:23:36,920
Speaker 3: and of course it's cloud momentum, mainly across both Anna

464
00:23:36,960 --> 00:23:40,120
Speaker 3: Ragranaz with us Bloomberg Intelligence senior tech analyst, and let's

465
00:23:40,119 --> 00:23:42,960
Speaker 3: start on Oracle because a lot of notes coming out

466
00:23:43,040 --> 00:23:46,639
Speaker 3: that they loved, in particular Oracle's cloud infrastructure that they

467
00:23:46,680 --> 00:23:48,679
Speaker 3: seem to be seeing a key highlight for you as

468
00:23:48,720 --> 00:23:49,600
Speaker 3: well as for Jeffries.

469
00:23:50,920 --> 00:23:52,359
Speaker 9: Yeah, this is I mean it was.

470
00:23:52,600 --> 00:23:55,920
Speaker 11: The acceleration in infrastructure as a service was a bit

471
00:23:56,280 --> 00:23:57,119
Speaker 11: surprising to us.

472
00:23:57,200 --> 00:23:58,720
Speaker 9: It was quite a bit sharper.

473
00:23:58,440 --> 00:24:01,560
Speaker 11: Only because in the whole world is slowing down right

474
00:24:01,560 --> 00:24:04,640
Speaker 11: now in terms of consumption, and here is Oracle, even

475
00:24:04,680 --> 00:24:06,920
Speaker 11: though it's a smaller base, you know, but improving their

476
00:24:06,920 --> 00:24:09,359
Speaker 11: growth rates. Now this is where we you know, wrote

477
00:24:09,400 --> 00:24:11,879
Speaker 11: this morning that this is going to do, you know,

478
00:24:11,920 --> 00:24:14,560
Speaker 11: get some work done from both Amazon and Microsoft in

479
00:24:14,640 --> 00:24:17,040
Speaker 11: terms of explaining to the market that they are not

480
00:24:17,160 --> 00:24:20,080
Speaker 11: losing market share and everybody is going to benefit from

481
00:24:20,119 --> 00:24:23,080
Speaker 11: both the AI boom and people moving more workloads to

482
00:24:23,119 --> 00:24:26,440
Speaker 11: the cloud. Now, remember, Oracle is very good at marketing itself,

483
00:24:26,520 --> 00:24:28,600
Speaker 11: and I think they did a phenomenal job over the

484
00:24:28,640 --> 00:24:31,720
Speaker 11: last few quarters and we can see the results of that.

485
00:24:33,320 --> 00:24:38,720
Speaker 6: Speaking of marketing oneself, Salesforce set out, it's still in

486
00:24:38,800 --> 00:24:41,240
Speaker 6: terms of what it's doing in the field of generative AI.

487
00:24:41,800 --> 00:24:44,600
Speaker 6: Where does Salesforce sit in the AI wars from the

488
00:24:44,640 --> 00:24:46,040
Speaker 6: BI perspective an RAG.

489
00:24:47,200 --> 00:24:49,199
Speaker 11: So one of the things that we have talked a

490
00:24:49,240 --> 00:24:53,120
Speaker 11: lot about is when you look at generative AI, consumer

491
00:24:53,160 --> 00:24:54,440
Speaker 11: applications are going.

492
00:24:54,240 --> 00:24:55,720
Speaker 9: To be the first one to embrace this.

493
00:24:55,800 --> 00:24:58,440
Speaker 11: And we have seen that already with our GPT and

494
00:24:58,480 --> 00:25:00,440
Speaker 11: you know being including some of that stuff.

495
00:25:00,480 --> 00:25:03,040
Speaker 9: You're going to get more of that in the coming months.

496
00:25:03,680 --> 00:25:05,760
Speaker 11: A large portion of that is because the data, the

497
00:25:05,760 --> 00:25:08,120
Speaker 11: consumer data is a little bit easier to get than

498
00:25:08,520 --> 00:25:11,840
Speaker 11: enterprise data. When you look at a company like Salesforce,

499
00:25:12,080 --> 00:25:16,080
Speaker 11: the number one concern for corporations right now is are

500
00:25:16,119 --> 00:25:18,239
Speaker 11: they going to use my data to come up with

501
00:25:18,320 --> 00:25:22,440
Speaker 11: some new algorithm and then you start divulging those data

502
00:25:22,440 --> 00:25:23,399
Speaker 11: sources out there.

503
00:25:23,560 --> 00:25:24,200
Speaker 9: And I think what.

504
00:25:24,280 --> 00:25:27,440
Speaker 11: Salesforce data yesterday was very smart. They're there to explain

505
00:25:27,480 --> 00:25:30,479
Speaker 11: to people that your personal data will remain private.

506
00:25:30,640 --> 00:25:33,040
Speaker 9: As a company, we're not going to use it.

507
00:25:33,080 --> 00:25:34,639
Speaker 11: If you're going to use it, it's only going to

508
00:25:34,640 --> 00:25:36,840
Speaker 11: be for you. So I think it's a first good

509
00:25:36,880 --> 00:25:40,520
Speaker 11: step in explaining to people what it means. I think

510
00:25:40,600 --> 00:25:43,879
Speaker 11: Salesforce is a big beneficiary in the long run because

511
00:25:43,880 --> 00:25:46,679
Speaker 11: at both their cloud products, whether it's Sales Cloud or

512
00:25:46,720 --> 00:25:51,960
Speaker 11: Customer Relationship Management or the Customer Service Cloud, both are

513
00:25:52,040 --> 00:25:54,760
Speaker 11: three times bigger than the nearest rival in the cloud.

514
00:25:54,960 --> 00:25:56,440
Speaker 11: And I think they are sitting on top of a

515
00:25:56,520 --> 00:25:58,440
Speaker 11: lot of data and they're going to benefit from that.

516
00:26:00,040 --> 00:26:02,120
Speaker 6: All right, Oh, thanks to Ana rag Rana or Bloomberg

517
00:26:02,200 --> 00:26:05,440
Speaker 6: Intelligence reacting to what's been a busy twenty four hours

518
00:26:05,440 --> 00:26:08,439
Speaker 6: in newsflow, let's get more perspective on AI and cloud

519
00:26:08,520 --> 00:26:13,400
Speaker 6: software from Manny Medinao Outreach. Outreach is a Salesforce partner

520
00:26:13,400 --> 00:26:16,119
Speaker 6: and an AI driven sales platform which is used by

521
00:26:16,160 --> 00:26:19,879
Speaker 6: thousands of enterprises to increase sales rep productivity. And it's

522
00:26:19,920 --> 00:26:22,359
Speaker 6: a great place to start because the question Caroline and

523
00:26:22,440 --> 00:26:25,879
Speaker 6: I constantly pose Nanny is how does the introduction of

524
00:26:25,920 --> 00:26:30,520
Speaker 6: generative AI tools not just change sales function but does

525
00:26:30,560 --> 00:26:32,000
Speaker 6: it eliminate some as well.

526
00:26:35,040 --> 00:26:38,000
Speaker 12: Let's think I step back, so where are the very

527
00:26:38,040 --> 00:26:42,000
Speaker 12: early innings of what jenai and JIAI in.

528
00:26:41,920 --> 00:26:43,879
Speaker 9: General can do for a sales rep and for a

529
00:26:43,920 --> 00:26:44,600
Speaker 9: sales manager.

530
00:26:45,200 --> 00:26:47,520
Speaker 12: And the winners of this race are going to be

531
00:26:47,560 --> 00:26:49,560
Speaker 12: called out in the next two years, if you would.

532
00:26:49,880 --> 00:26:52,600
Speaker 12: But what's important is that if you go to the future,

533
00:26:53,240 --> 00:26:56,240
Speaker 12: can you imagine you know what is it non negotiable?

534
00:26:56,240 --> 00:26:58,280
Speaker 12: So if you think for first principles back and what's

535
00:26:58,280 --> 00:27:00,159
Speaker 12: going to happen in the future, that we need to

536
00:27:00,200 --> 00:27:02,800
Speaker 12: do today is that in the future, there is no rep.

537
00:27:02,880 --> 00:27:05,359
Speaker 12: There's no manager that doesn't have an AI dedicated to

538
00:27:05,440 --> 00:27:07,960
Speaker 12: their work. That is not helping them, you know, close

539
00:27:07,960 --> 00:27:10,640
Speaker 12: deals faster, That is not helping them prioritize their day,

540
00:27:10,640 --> 00:27:13,639
Speaker 12: that is not helping them figure out what accounts to pursue,

541
00:27:13,680 --> 00:27:15,600
Speaker 12: what accunts not for to pursue, who who to follow

542
00:27:15,680 --> 00:27:17,720
Speaker 12: up with and sort of get the aggregate of those

543
00:27:17,760 --> 00:27:20,240
Speaker 12: reports to a manager and making sure that the team

544
00:27:20,280 --> 00:27:23,479
Speaker 12: is moving forward and delivering. So in that future, if

545
00:27:23,520 --> 00:27:25,040
Speaker 12: you work it back to today, the things that are

546
00:27:25,080 --> 00:27:26,879
Speaker 12: important is how do you lay.

547
00:27:26,720 --> 00:27:27,520
Speaker 9: Out that data?

548
00:27:27,640 --> 00:27:30,080
Speaker 12: How do you make you know your your your partner

549
00:27:30,119 --> 00:27:32,600
Speaker 12: in the enterprise trustworthy, which is what seales for today.

550
00:27:32,960 --> 00:27:34,720
Speaker 12: How do you make sure that you are accumulating data

551
00:27:34,760 --> 00:27:36,800
Speaker 12: and processing in such a way that you are increasingly

552
00:27:36,840 --> 00:27:39,800
Speaker 12: helping the reps work close and making them more successful.

553
00:27:40,240 --> 00:27:43,560
Speaker 9: Now will doubt this displaced jobs?

554
00:27:43,680 --> 00:27:46,400
Speaker 12: I doubt it because people, you know, organizations will get

555
00:27:46,400 --> 00:27:49,119
Speaker 12: greedy and they will see that with higher efficiency they

556
00:27:49,119 --> 00:27:50,760
Speaker 12: can actually drive higher results.

557
00:27:50,920 --> 00:27:53,800
Speaker 9: So they will continue to hire reps that use GENI

558
00:27:53,840 --> 00:27:54,320
Speaker 9: as part.

559
00:27:54,160 --> 00:27:56,200
Speaker 12: Of their day to day workflow and that will continue

560
00:27:56,200 --> 00:27:59,920
Speaker 12: to drive you know, efficient returns and efficient compounding outcomes

561
00:27:59,920 --> 00:28:01,040
Speaker 12: for organizations.

562
00:28:01,080 --> 00:28:03,160
Speaker 9: So it's a very exciting time right now.

563
00:28:03,200 --> 00:28:05,840
Speaker 3: Exciting as long as you're happy to be augmented, as

564
00:28:05,840 --> 00:28:07,960
Speaker 3: long as you're ensuring you're up in your skill set

565
00:28:08,240 --> 00:28:10,800
Speaker 3: to work alongside this AI manny, What did you hear

566
00:28:10,840 --> 00:28:13,880
Speaker 3: that was different out of salesforce? That ultimately is being

567
00:28:13,920 --> 00:28:16,520
Speaker 3: said by everyone else who's trying to help you with

568
00:28:16,560 --> 00:28:20,639
Speaker 3: your CRM, with your interactions with your customers, with marketing

569
00:28:21,160 --> 00:28:22,040
Speaker 3: when it comes to AI.

570
00:28:23,359 --> 00:28:25,080
Speaker 12: I think what we're seeing right now is an even

571
00:28:25,160 --> 00:28:29,720
Speaker 12: played in field among all the systems of record players.

572
00:28:29,800 --> 00:28:33,240
Speaker 12: So you're seeing Dynamics in Microsoft coming out with a

573
00:28:33,280 --> 00:28:35,520
Speaker 12: setup announcements. You see an Oracle coming up with a

574
00:28:35,560 --> 00:28:39,000
Speaker 12: setup announcements. You seeing Salesforce coming up with sort of announcements.

575
00:28:38,680 --> 00:28:39,440
Speaker 9: Three weeks ago.

576
00:28:39,760 --> 00:28:42,600
Speaker 12: Service now layout there rotema for AI and I gonna

577
00:28:42,600 --> 00:28:43,960
Speaker 12: mean for IDSM and the rest of the year.

578
00:28:43,880 --> 00:28:46,320
Speaker 5: Differct maney manny. That's really overwhelming for me.

579
00:28:46,480 --> 00:28:48,480
Speaker 3: I mean, as the journalists, you're speaking to, all these

580
00:28:48,520 --> 00:28:51,520
Speaker 3: companies getting you onto, and it feels as though there's

581
00:28:51,520 --> 00:28:54,040
Speaker 3: too many announcements, everyone suddenly trying to make themselves out

582
00:28:54,080 --> 00:28:59,040
Speaker 3: to be some AI efficient company. How can you discern

583
00:28:59,240 --> 00:29:00,720
Speaker 3: which one's doing the right things?

584
00:29:00,720 --> 00:29:01,320
Speaker 5: And when.

585
00:29:02,600 --> 00:29:04,600
Speaker 12: There is no way to go wrong? Right now, see

586
00:29:04,600 --> 00:29:06,960
Speaker 12: that players who are going to win. They set out

587
00:29:06,960 --> 00:29:10,000
Speaker 12: the AI strategy ten years ago. So if you read

588
00:29:10,160 --> 00:29:12,000
Speaker 12: you know the sell sorces of full service announcement, they

589
00:29:12,040 --> 00:29:13,920
Speaker 12: actually have been working on a number of things for

590
00:29:13,960 --> 00:29:16,240
Speaker 12: a while. And this is just the culmination and the

591
00:29:16,600 --> 00:29:19,080
Speaker 12: and the and another turn of the flywheel.

592
00:29:18,640 --> 00:29:21,320
Speaker 9: Of getting their AI on on the onto the market

593
00:29:21,400 --> 00:29:22,760
Speaker 9: now with the help of Generative AI.

594
00:29:22,960 --> 00:29:25,600
Speaker 12: So General VII is just another flavor of a bunch

595
00:29:25,600 --> 00:29:27,480
Speaker 12: of AI that has been built over the past ten years.

596
00:29:27,560 --> 00:29:28,640
Speaker 9: It's the same thing for outreach.

597
00:29:28,680 --> 00:29:31,480
Speaker 12: We've been working with workflows and we've been looking at

598
00:29:31,600 --> 00:29:33,520
Speaker 12: what the what is the rep doing or the manager doing,

599
00:29:33,600 --> 00:29:35,440
Speaker 12: what is the outcome of the workflows and fitting that

600
00:29:35,480 --> 00:29:37,640
Speaker 12: into models so that we can make people more productive.

601
00:29:37,760 --> 00:29:39,960
Speaker 12: General VAI is just another gear into that, into that

602
00:29:40,040 --> 00:29:44,000
Speaker 12: flight wheel. So everyone is going to have enhancements to

603
00:29:44,120 --> 00:29:47,280
Speaker 12: the user experience on their platforms and that is just

604
00:29:47,320 --> 00:29:49,040
Speaker 12: good news for everybody.

605
00:29:49,920 --> 00:29:53,440
Speaker 6: MANNY to the enterprises you work with have the technical

606
00:29:53,520 --> 00:29:58,320
Speaker 6: expertise and the personnel necessary to understand what's happening and

607
00:29:58,360 --> 00:29:59,840
Speaker 6: then implement it on their end.

608
00:30:01,120 --> 00:30:03,360
Speaker 9: That is exactly the right question to ask.

609
00:30:03,480 --> 00:30:07,160
Speaker 12: So the main the main funnel through which AI is

610
00:30:07,160 --> 00:30:11,320
Speaker 12: going to have to go through the main uh, the mechanism,

611
00:30:11,400 --> 00:30:13,920
Speaker 12: but which AI gets deployed and gets useful is through

612
00:30:13,920 --> 00:30:16,160
Speaker 12: the human being. It's through the worker, it's through the

613
00:30:16,240 --> 00:30:19,560
Speaker 12: project and through the workflow. And we need to spend

614
00:30:19,600 --> 00:30:23,280
Speaker 12: more time thinking about how does that AI impact, the

615
00:30:23,360 --> 00:30:28,760
Speaker 12: rep impact, the customer success manager impact, the support UH

616
00:30:28,920 --> 00:30:33,320
Speaker 12: person or professional and managers out there to make sure

617
00:30:33,320 --> 00:30:36,680
Speaker 12: that we are fitting the AI to the benefit of

618
00:30:36,720 --> 00:30:38,720
Speaker 12: the human being, because only then you're going to get

619
00:30:38,720 --> 00:30:42,720
Speaker 12: the compound and effect of AI plus human delivers drastic results.

620
00:30:43,080 --> 00:30:45,960
Speaker 12: So we need to spend more time a locating that

621
00:30:46,360 --> 00:30:48,400
Speaker 12: our team members and the and the recipients into the

622
00:30:48,440 --> 00:30:50,680
Speaker 12: new into the new workflows, into the new possibilities that

623
00:30:51,000 --> 00:30:51,960
Speaker 12: i I bring to the table.

624
00:30:52,160 --> 00:30:54,000
Speaker 9: Without it, you're not going to get adoption.

625
00:30:54,600 --> 00:30:56,080
Speaker 12: So that that is the part that we all need

626
00:30:56,120 --> 00:30:57,560
Speaker 12: to be talking about, is what are you doing to

627
00:30:57,640 --> 00:31:00,760
Speaker 12: drive adoption of AI out your customer's point, not in

628
00:31:00,800 --> 00:31:01,800
Speaker 12: the technology delivery.

629
00:31:01,920 --> 00:31:04,040
Speaker 9: Now, your delivery is very easy right now is customer

630
00:31:04,200 --> 00:31:04,959
Speaker 9: after right?

631
00:31:05,920 --> 00:31:06,239
Speaker 2: All right?

632
00:31:06,400 --> 00:31:09,360
Speaker 6: Thanks to our reco Manny Medina, who's reacting carried to

633
00:31:09,400 --> 00:31:12,240
Speaker 6: salesforce setting out what they're doing in the field of

634
00:31:12,280 --> 00:31:14,840
Speaker 6: AI in the last twenty four hours. Now coming up

635
00:31:14,920 --> 00:31:17,200
Speaker 6: the state of the venture industry and what will be

636
00:31:17,240 --> 00:31:20,840
Speaker 6: the next big thing enabled by AI. More on that

637
00:31:20,920 --> 00:31:23,600
Speaker 6: with four runners Brian O'Malley, that's next.

638
00:31:24,200 --> 00:31:36,719
Speaker 4: This is Bloomberg all right, Time for the VC roundup.

639
00:31:36,760 --> 00:31:39,920
Speaker 6: First up, Insight Partners has cut the target size of

640
00:31:39,960 --> 00:31:42,960
Speaker 6: its latest fund to fifteen billion dollars from the earlier

641
00:31:43,000 --> 00:31:46,000
Speaker 6: target of twenty billion dollars. Is it sees quote a

642
00:31:46,000 --> 00:31:49,640
Speaker 6: great reset in tech. That's according to the Financial Time,

643
00:31:49,760 --> 00:31:53,160
Speaker 6: citing a letter to institutional investors. The firm is so

644
00:31:53,240 --> 00:31:57,560
Speaker 6: far raised about two billion dollars for its thirteenth fund. Similarly,

645
00:31:57,600 --> 00:32:02,200
Speaker 6: Technology Crossover Ventures or TEAC has raised fifty to seventy

646
00:32:02,200 --> 00:32:05,640
Speaker 6: five percent less capital for his flagship fund, down from

647
00:32:05,640 --> 00:32:08,240
Speaker 6: the planned five point five billion target set last year.

648
00:32:08,280 --> 00:32:11,960
Speaker 6: That's according to the Information, citing securities filings and a

649
00:32:12,040 --> 00:32:15,719
Speaker 6: document compiled by one of tcb's A limited partners. TCV

650
00:32:16,000 --> 00:32:19,440
Speaker 6: has raised one point four billion for its flagship fund. Finally,

651
00:32:19,800 --> 00:32:23,120
Speaker 6: wafer producer Cubic PV says it secured over one hundred

652
00:32:23,160 --> 00:32:26,400
Speaker 6: million dollars in new firm equity commitments for its US

653
00:32:26,440 --> 00:32:29,760
Speaker 6: factory plans and product ROMAC, SCG, Hunt Energy, and break

654
00:32:29,800 --> 00:32:33,520
Speaker 6: Through Energy all committed capital, with the first thirty three

655
00:32:33,640 --> 00:32:36,720
Speaker 6: million dollars to be released immediately.

656
00:32:37,040 --> 00:32:38,440
Speaker 4: Caroline, let's stick.

657
00:32:38,240 --> 00:32:40,200
Speaker 3: With this world of VC. We're very pleased to welcome

658
00:32:40,240 --> 00:32:42,040
Speaker 3: to the show. Brian and Valley, managing partner at four

659
00:32:42,080 --> 00:32:44,920
Speaker 3: Run Adventures two billion dollars in assets under management and

660
00:32:45,400 --> 00:32:47,960
Speaker 3: really ran you state your claim, and some of the

661
00:32:48,160 --> 00:32:50,640
Speaker 3: key companies you back before are very consumer focused. I'm

662
00:32:50,640 --> 00:32:54,160
Speaker 3: thinking in the glossiers him and hers Aura. At the moment,

663
00:32:54,240 --> 00:32:56,400
Speaker 3: you seem to be looking at a lot at the

664
00:32:56,440 --> 00:32:59,360
Speaker 3: platforms that empower gig economy workers, and I'm interested as

665
00:32:59,400 --> 00:33:02,360
Speaker 3: to how much time is currently helping your portfolio companies

666
00:33:02,680 --> 00:33:05,200
Speaker 3: basically ensure that they're empowered with AI, then they're not

667
00:33:05,240 --> 00:33:06,640
Speaker 3: having their lunch, eat and elsewhere.

668
00:33:08,760 --> 00:33:08,920
Speaker 2: Yeah.

669
00:33:08,920 --> 00:33:11,560
Speaker 13: Absolutely, I think AI is on everyone's mind these days.

670
00:33:11,600 --> 00:33:13,600
Speaker 13: It's something that I've been hearing you guys talk about

671
00:33:13,640 --> 00:33:16,000
Speaker 13: all morning. It's something we're talking about in our offices

672
00:33:16,080 --> 00:33:18,600
Speaker 13: all day long. And so we did a survey recently

673
00:33:18,680 --> 00:33:21,480
Speaker 13: of our portfolio to really understand where they're exploring. And

674
00:33:21,840 --> 00:33:24,200
Speaker 13: it's not surprising that about eighty to ninety percent of

675
00:33:24,200 --> 00:33:27,360
Speaker 13: the portfolio companies are already leveraging AI in some fashion

676
00:33:27,880 --> 00:33:30,160
Speaker 13: and the rest are thinking about it and starts with marketing,

677
00:33:30,320 --> 00:33:32,360
Speaker 13: it starts with their product, and then they're really thinking

678
00:33:32,360 --> 00:33:35,320
Speaker 13: about internal processes and how they can automate internal processes

679
00:33:35,360 --> 00:33:35,640
Speaker 13: as well.

680
00:33:36,320 --> 00:33:39,160
Speaker 6: Full your portfolio companies and the founders you invest in.

681
00:33:39,440 --> 00:33:42,600
Speaker 6: What is the single biggest factor that would push them

682
00:33:42,640 --> 00:33:43,480
Speaker 6: to invest in AI?

683
00:33:43,600 --> 00:33:44,560
Speaker 4: Why do they need it?

684
00:33:45,400 --> 00:33:47,600
Speaker 13: Well, everyone is trying to be both more efficient as

685
00:33:47,600 --> 00:33:50,320
Speaker 13: well as provide more value to their end customers. And

686
00:33:50,360 --> 00:33:52,400
Speaker 13: we're finding ways where if they can put their people

687
00:33:52,840 --> 00:33:55,719
Speaker 13: first and then enable some of the back end processes

688
00:33:56,080 --> 00:33:58,960
Speaker 13: to be leveraged through AI, that enables them to have

689
00:33:59,080 --> 00:34:01,440
Speaker 13: more human element even though they're taking advantage of these

690
00:34:01,520 --> 00:34:02,280
Speaker 13: new technologies.

691
00:34:03,840 --> 00:34:07,320
Speaker 6: I think it poses the question Carrie, going back to consumer,

692
00:34:07,520 --> 00:34:10,319
Speaker 6: because I was getting ready for this segment and I

693
00:34:10,360 --> 00:34:12,399
Speaker 6: was kind of looking forward to not talking about AI,

694
00:34:12,640 --> 00:34:14,120
Speaker 6: and we're two and a half minutes in and we've

695
00:34:14,160 --> 00:34:19,800
Speaker 6: already ruined that. But traditionally, for vcs, the consumer segment

696
00:34:19,960 --> 00:34:24,400
Speaker 6: is risky. You're against giant global conglomerates who are also innovating.

697
00:34:24,800 --> 00:34:27,760
Speaker 6: Why do you want to focus there in more consumer

698
00:34:27,800 --> 00:34:30,120
Speaker 6: facing startups in their platforms.

699
00:34:30,680 --> 00:34:30,960
Speaker 2: Sure?

700
00:34:31,000 --> 00:34:33,719
Speaker 13: Well, we believe that when you focus at something, you

701
00:34:33,760 --> 00:34:35,080
Speaker 13: can be the best in the world at it, and

702
00:34:35,080 --> 00:34:37,040
Speaker 13: that's what we're trying to do in terms of understanding

703
00:34:37,080 --> 00:34:39,160
Speaker 13: both what consumers want. Right now, we spend a lot

704
00:34:39,200 --> 00:34:42,200
Speaker 13: of our time not pontificating, but really listening. So we

705
00:34:42,239 --> 00:34:44,240
Speaker 13: do a fair amount of focus groups, a fair amount

706
00:34:44,239 --> 00:34:46,360
Speaker 13: of surveys. I understand what is top of mind for people.

707
00:34:46,719 --> 00:34:48,879
Speaker 13: And even though there's all this innovation, people are still

708
00:34:48,960 --> 00:34:51,919
Speaker 13: left wanting more. They've got challenges in their personal lives,

709
00:34:52,239 --> 00:34:55,279
Speaker 13: looking for community and connection, and they're also thinking about

710
00:34:55,360 --> 00:34:58,160
Speaker 13: how they can get better purpose, better self reliance. And

711
00:34:58,200 --> 00:35:00,759
Speaker 13: so we feel like as much as there's dollars going

712
00:35:00,800 --> 00:35:03,879
Speaker 13: into the ecosystem, there's a lot of needs still being

713
00:35:03,960 --> 00:35:06,279
Speaker 13: unmet for consumers, and we believe the founders we work

714
00:35:06,320 --> 00:35:07,439
Speaker 13: QUI can help solve those needs.

715
00:35:07,480 --> 00:35:10,279
Speaker 6: You know, Caroline, We've had vcs and founders on the

716
00:35:10,320 --> 00:35:14,400
Speaker 6: show that are making something for the consumer, and valuing

717
00:35:14,480 --> 00:35:16,120
Speaker 6: that offering is really hard.

718
00:35:16,440 --> 00:35:19,200
Speaker 3: Yeah, I mean, Brian, I'm having a lot of conversations

719
00:35:19,239 --> 00:35:23,880
Speaker 3: with vcs who've primarily backed consumer focused companies and at

720
00:35:23,920 --> 00:35:25,239
Speaker 3: the moment they say they're not touching them with a

721
00:35:25,239 --> 00:35:25,719
Speaker 3: barge pole.

722
00:35:25,880 --> 00:35:28,000
Speaker 5: In terms of new checks to be written.

723
00:35:28,480 --> 00:35:31,240
Speaker 3: How much is the valuations the companies that you currently

724
00:35:31,280 --> 00:35:33,880
Speaker 3: have had and just having to write size still at

725
00:35:33,880 --> 00:35:34,560
Speaker 3: the moment.

726
00:35:36,200 --> 00:35:39,200
Speaker 13: Sure, Well, there's a combination that portfolio, as there always is,

727
00:35:39,239 --> 00:35:41,319
Speaker 13: and the ratio may change a little bit, but our

728
00:35:41,360 --> 00:35:44,879
Speaker 13: best companies are still finding dollars available to them, they're

729
00:35:44,880 --> 00:35:47,920
Speaker 13: still raising capital, and they're able to do what they

730
00:35:47,960 --> 00:35:50,680
Speaker 13: need to do. The companies that are struggling, they continue

731
00:35:50,719 --> 00:35:52,400
Speaker 13: to struggle, and a lot of that comes down to

732
00:35:52,480 --> 00:35:54,520
Speaker 13: just this question around whether they found product market fit

733
00:35:54,840 --> 00:35:57,400
Speaker 13: and whether they're timing is right for what they're ultimately offering.

734
00:35:57,480 --> 00:35:59,399
Speaker 13: And so we look at a time where a lot

735
00:35:59,400 --> 00:36:01,799
Speaker 13: of other consumer we're investors or left scratching their head

736
00:36:01,800 --> 00:36:05,080
Speaker 13: because they found themselves chasing some of these shiny objects.

737
00:36:05,400 --> 00:36:08,600
Speaker 13: We find that when we're grounded talking to people, talking

738
00:36:08,600 --> 00:36:10,680
Speaker 13: about what their needs are and looking at how that

739
00:36:11,000 --> 00:36:14,680
Speaker 13: is juxtaposed against new business models and new technologies, we

740
00:36:14,719 --> 00:36:16,640
Speaker 13: find that there's more than an opportunity to invest in.

741
00:36:16,680 --> 00:36:18,480
Speaker 13: It's just about finding the right ones, where we have

742
00:36:18,560 --> 00:36:21,000
Speaker 13: the right founder fit based on our ambition and based

743
00:36:21,040 --> 00:36:21,839
Speaker 13: on what they're trying to.

744
00:36:21,760 --> 00:36:23,439
Speaker 5: Do talk to us about the founder fit.

745
00:36:23,719 --> 00:36:26,800
Speaker 3: Of course, there was a lot of concern that as

746
00:36:27,320 --> 00:36:30,560
Speaker 3: you know, that sucking feeling, sucking noise started to happen

747
00:36:30,560 --> 00:36:32,200
Speaker 3: in terms of the money coming out of the situation,

748
00:36:32,280 --> 00:36:36,360
Speaker 3: it was going to leave particularly diverse founders.

749
00:36:35,120 --> 00:36:36,759
Speaker 5: Sort of most hard hit.

750
00:36:36,920 --> 00:36:39,480
Speaker 3: But then now what I'm hearing is actually the diverse

751
00:36:39,480 --> 00:36:42,600
Speaker 3: founders have been used to being scrappy ultimately, and they're

752
00:36:42,640 --> 00:36:45,080
Speaker 3: actually better at weathering these sorts of downturns because they

753
00:36:45,120 --> 00:36:48,080
Speaker 3: know how to have a sort of nimble business. And

754
00:36:48,080 --> 00:36:50,120
Speaker 3: you're seeing that how much you were able to continue

755
00:36:50,160 --> 00:36:53,560
Speaker 3: to support founders who perhaps wouldn't have had checks previously.

756
00:36:55,239 --> 00:36:58,440
Speaker 13: Yeah, absolutely, we're looking for founders today to be scrappier

757
00:36:58,440 --> 00:36:59,560
Speaker 13: than they've ever been before.

758
00:36:59,600 --> 00:37:01,040
Speaker 2: But scared city is.

759
00:37:00,960 --> 00:37:03,560
Speaker 13: An important trait for these startup companies. When you have

760
00:37:03,680 --> 00:37:07,239
Speaker 13: too many things going on, it enables you took to

761
00:37:07,440 --> 00:37:10,799
Speaker 13: lose your focus. And when there's less resources, when there's

762
00:37:10,840 --> 00:37:12,680
Speaker 13: less people on the team, it's easier to pick what's

763
00:37:12,719 --> 00:37:15,239
Speaker 13: the one priority we need to get accomplished now. And

764
00:37:15,239 --> 00:37:16,879
Speaker 13: that's what we're working with our teams on to help

765
00:37:16,920 --> 00:37:19,880
Speaker 13: them pick that priority and help them execute against it.

766
00:37:20,120 --> 00:37:22,920
Speaker 6: Brian, what's your exit strategy when you're in this space?

767
00:37:23,880 --> 00:37:26,440
Speaker 13: Our access strategy is really simple. We try to build

768
00:37:26,480 --> 00:37:29,600
Speaker 13: great businesses, and those great businesses tend to have lots

769
00:37:29,640 --> 00:37:32,600
Speaker 13: of opportunities come towards them, and that window might be.

770
00:37:32,600 --> 00:37:33,319
Speaker 4: Changing a little bit.

771
00:37:33,360 --> 00:37:35,560
Speaker 13: It might be harder to sell a company, I'd be

772
00:37:35,600 --> 00:37:37,600
Speaker 13: harder to take a public right now. But if you're

773
00:37:37,600 --> 00:37:41,319
Speaker 13: building a durable, sustainable business where the customers love what

774
00:37:41,320 --> 00:37:44,240
Speaker 13: you're doing, time is actually your friend versus your enemy,

775
00:37:44,360 --> 00:37:44,800
Speaker 13: and that's.

776
00:37:44,640 --> 00:37:45,840
Speaker 4: What we're trying to help our companies do.

777
00:37:45,920 --> 00:37:49,120
Speaker 6: All right, full run Avenches managing partner Brian O'Malley, thank

778
00:37:49,160 --> 00:37:52,960
Speaker 6: you very much. Federal Prosecutes is in the Fharaanos case.

779
00:37:53,000 --> 00:37:55,480
Speaker 6: They're asking for Elizabeth Holmes to pay two hundred and

780
00:37:55,520 --> 00:37:59,760
Speaker 6: fifty dollars every month in restitution once she's released from prison.

781
00:38:00,080 --> 00:38:03,320
Speaker 6: Lawyers for the former Pharaoh CEO say she has quote

782
00:38:03,440 --> 00:38:06,719
Speaker 6: limited financial resources and should not have to make the

783
00:38:06,760 --> 00:38:09,759
Speaker 6: monthly payment. Holmes had said she can't afford to pay

784
00:38:09,800 --> 00:38:12,600
Speaker 6: the nine figure sum demanded by the US over four

785
00:38:12,719 --> 00:38:25,640
Speaker 6: hundred and fifty two million dollars. Twitter's former CEO, Jack

786
00:38:25,680 --> 00:38:29,120
Speaker 6: Dorsey says authorities had threatened the platform during the farmer

787
00:38:29,200 --> 00:38:35,240
Speaker 6: protests unless Twitter removed certain politically sensitive posts. Now India's

788
00:38:35,280 --> 00:38:39,960
Speaker 6: Minister of State for Electronics and it fired back at Dorsey, saying, quote,

789
00:38:40,000 --> 00:38:43,600
Speaker 6: that's a lie. Bloomberg's Technology editor Sarah Fryer joins US

790
00:38:43,600 --> 00:38:44,959
Speaker 6: on set with more.

791
00:38:46,520 --> 00:38:47,040
Speaker 4: Let's start.

792
00:38:47,040 --> 00:38:49,520
Speaker 6: I guess with the retort, what is it that that

793
00:38:49,600 --> 00:38:53,080
Speaker 6: India is saying Twitter is lying or Jack Dorsey specifically

794
00:38:53,160 --> 00:38:53,840
Speaker 6: is lying about.

795
00:38:54,480 --> 00:38:56,840
Speaker 14: Well, they're saying that they never shut Twitter down and

796
00:38:56,880 --> 00:38:59,640
Speaker 14: then nobody went to jail. That's not what Dorsey was saying.

797
00:39:00,080 --> 00:39:03,120
Speaker 14: He was saying that there were threats that the company

798
00:39:03,160 --> 00:39:06,000
Speaker 14: would be shut down and that employees would be threatened. So,

799
00:39:06,800 --> 00:39:08,759
Speaker 14: I mean, what you're seeing here this is just a

800
00:39:08,800 --> 00:39:12,359
Speaker 14: microcosm of what's happening with Twitter across the world, which

801
00:39:12,400 --> 00:39:17,400
Speaker 14: is governments are realizing that they can ask for the

802
00:39:17,440 --> 00:39:20,600
Speaker 14: company to do certain things to take down a posts

803
00:39:20,600 --> 00:39:23,920
Speaker 14: from dissidents, from people who are criticizing the government and

804
00:39:24,200 --> 00:39:28,240
Speaker 14: say they're in violation of law, and if they don't comply,

805
00:39:28,960 --> 00:39:31,560
Speaker 14: they could lose their market power in that country. And

806
00:39:31,600 --> 00:39:33,560
Speaker 14: that is something that I think is going to be

807
00:39:34,040 --> 00:39:39,000
Speaker 14: even more difficult under the new CEO, Lindia Karino and

808
00:39:39,360 --> 00:39:43,160
Speaker 14: new owner of Twitter, Elon Musk. We're talking about with Dorisy.

809
00:39:43,239 --> 00:39:48,560
Speaker 14: Happened in twenty twenty one, and now Twitter has so

810
00:39:48,680 --> 00:39:53,240
Speaker 14: many fewer of those global legal policy employees who really

811
00:39:53,320 --> 00:40:00,239
Speaker 14: understand a local government and enlarge governments like India, how

812
00:40:00,280 --> 00:40:04,320
Speaker 14: to navigate those different political stumbling blocks that come about.

813
00:40:04,960 --> 00:40:08,880
Speaker 3: I mean, I'm thinking of Linda Acarino's recent tweet thread,

814
00:40:08,960 --> 00:40:13,120
Speaker 3: and she really wants to make Twitter the open place

815
00:40:13,400 --> 00:40:17,040
Speaker 3: for discussion, and ultimately certain countries are going to find

816
00:40:17,040 --> 00:40:20,360
Speaker 3: that difficult. We know India, of course, does tend to

817
00:40:20,400 --> 00:40:23,080
Speaker 3: fight back against social media. I mean they've banned TikTok,

818
00:40:23,120 --> 00:40:25,200
Speaker 3: for example, one of the any key countries to do that.

819
00:40:25,239 --> 00:40:28,160
Speaker 5: How do you think you can navigate that?

820
00:40:28,880 --> 00:40:30,520
Speaker 6: So, Cara, I'm going to jump in here because I

821
00:40:30,520 --> 00:40:33,239
Speaker 6: think Sarah lost you in her ear. But basically the

822
00:40:33,320 --> 00:40:35,839
Speaker 6: question is what do we know about how Twitter is

823
00:40:35,960 --> 00:40:40,600
Speaker 6: now handling it's global relationships with regulators in different jurisdictions.

824
00:40:40,920 --> 00:40:43,839
Speaker 14: What we know is that a lot of the executives

825
00:40:43,840 --> 00:40:45,839
Speaker 14: who were in charge of trust and safety at Twitter,

826
00:40:45,880 --> 00:40:48,520
Speaker 14: who are in charge of ensuring that the side is

827
00:40:48,920 --> 00:40:53,239
Speaker 14: complying with laws is taking down hate, reature, misinformation and

828
00:40:53,400 --> 00:40:59,759
Speaker 14: violent content that they are, you know, losing a lot

829
00:40:59,800 --> 00:41:02,600
Speaker 14: of the top executives who were in charge. And I

830
00:41:02,640 --> 00:41:05,359
Speaker 14: think that that makes it very difficult because when you're

831
00:41:05,400 --> 00:41:08,600
Speaker 14: working with governments and negotiating with governments, basically this is

832
00:41:08,640 --> 00:41:11,040
Speaker 14: against the law Twitter, you used to fight those cases,

833
00:41:11,320 --> 00:41:13,560
Speaker 14: they used to fight Turkey, they used to fight in

834
00:41:13,640 --> 00:41:16,439
Speaker 14: Egypt and say like no, like we're gonna we're gonna

835
00:41:16,480 --> 00:41:17,880
Speaker 14: keep those posts up. We're not going to give you

836
00:41:17,880 --> 00:41:20,680
Speaker 14: information on those people. What's going to be really interesting

837
00:41:20,960 --> 00:41:28,000
Speaker 14: is to see how how Twitter's changes and fights adjusts.

838
00:41:28,040 --> 00:41:30,680
Speaker 14: Given that their owner, Elon Musk, also has other business

839
00:41:30,719 --> 00:41:34,080
Speaker 14: interests in the countries where Twitter is operating with Tesla,

840
00:41:34,239 --> 00:41:38,680
Speaker 14: with SpaceX was with Starlink, it could get very complicated.

841
00:41:38,440 --> 00:41:41,400
Speaker 6: All right, Bloomberg, Sarah Fryer, thank you here on SF

842
00:41:41,600 --> 00:41:42,600
Speaker 6: all thanks Twitter, Carrot.

843
00:41:43,080 --> 00:41:45,799
Speaker 3: Yeah, notable that that town square that the New York

844
00:41:45,800 --> 00:41:48,839
Speaker 3: from talks about currently talking about, well a football club

845
00:41:48,880 --> 00:41:50,520
Speaker 3: close to our home and at the moment when it

846
00:41:50,520 --> 00:41:52,920
Speaker 3: comes to Manchester United. But we don't have time to

847
00:41:52,920 --> 00:41:54,759
Speaker 3: talk about that because it's the end of this edition

848
00:41:54,760 --> 00:41:55,680
Speaker 3: of a New Bow Technology.

849
00:41:56,480 --> 00:41:57,919
Speaker 4: It's second day of the week.

850
00:41:58,160 --> 00:42:00,640
Speaker 6: Busy week so far, so don't forget you recap with

851
00:42:00,680 --> 00:42:04,320
Speaker 6: the podcast wherever you get your podcasts, Apple, Spotify, iHeart

852
00:42:04,360 --> 00:42:07,719
Speaker 6: and of course on all of the core Bloomberg platforms.

853
00:42:07,760 --> 00:42:13,840
Speaker 6: From New York and from San Francisco. This is Bloomberg technology,