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Speaker 1: From Marhart where Innovation, Money and power Collie in Silicon Valley, NBN.

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

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Speaker 3: I'm Carolin Hyde at Bloomberg's Wiltid quarters in New York

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Speaker 3: and I met Lolo in San Francisco.

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Speaker 4: This is Bloomberg Technology coming up.

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Speaker 5: Full coverage of tech earnings ahead.

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Speaker 3: Is of course palents, SOLS and unprecedented AI demand while

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Speaker 3: chipmakers struggle.

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Speaker 4: To wather it, the industry downturn, plus Salesforce expanding its

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Speaker 4: approach to the degenerative AI boom with a new set

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Speaker 4: of tools unveiled. Salesforce co president Sarah Franklin joins us

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Speaker 4: from the Tableau conference in Las Vegas.

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Speaker 3: And we talked the state of fundraising as the startup

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Speaker 3: UBI raises one hundred million dollars for AI powered car inspections,

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Speaker 3: and we speak to the co founder of RX three,

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Speaker 3: which is also raised one hundred and fifty million dollars

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Speaker 3: from athletes and celebrities for its second growth equity fund. First,

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Speaker 3: that's sort of the private money being raised. What's happening

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Speaker 3: with your publicly traded companies today? We're nervous, cautious, and

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Speaker 3: we see a bit of a pullback on the Nasdaq

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Speaker 3: grow off by six tenths percent at the moment.

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Speaker 5: This is all about worries about that debt.

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Speaker 3: Ceiling coming front and center for the United States investor,

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Speaker 3: but also what's happening in China. The worry about the

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Speaker 3: impart demand not being as strong as we anticipated, is

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Speaker 3: that global economy, one of the fire powers of the

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Speaker 3: global economy not returning to growth post COVID as quickly.

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Speaker 5: As we hoped.

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Speaker 3: Golden Dragon therefore off by two point seven percent, and

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Speaker 3: also anxiety around the regional banks once again front and

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Speaker 3: center were off by nine tenths of a percent.

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Speaker 5: So that's your macro picture.

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Speaker 3: Let's move on to what's happening in the world of crypto,

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Speaker 3: because today we see a little bit of caution.

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Speaker 5: Overall.

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Speaker 3: We're just off by about five tenths of a percent.

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Speaker 3: We've had volatility in the og that is bitcoin today.

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Speaker 3: Really this is more a story of where the dollar

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Speaker 3: direction of travel is ahead of that debt ceiling demarcle,

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Speaker 3: whether or not it's more about the crypto.

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Speaker 5: We're just taking a bit of a pause on crypto.

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Speaker 4: It feels on the day, ed Yeah, I'm afraid. The

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Speaker 4: earning story also putting a lot of pressure to the downside.

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Speaker 4: You take a look at PayPal lowering its margins outlook

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Speaker 4: for the year. We're going to dig into the details

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Speaker 4: around that later in the show. Lucid Group softer by

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Speaker 4: eight percent, basically reguiding to the low end of its

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Speaker 4: previously stated forecast. An automaker that's trying to catch up

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Speaker 4: with Tesla but not making a lot of progress. Global

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Speaker 4: Founderies again paying for the chip sector, seems to be

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Speaker 4: in place through the end of the year. We're going

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Speaker 4: to go to Bloomberg's Ian King, the guy you want

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Speaker 4: to talk to when it comes to semiconductors. Global Foundry

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Speaker 4: softer by five percent. The big name, the big mover

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Speaker 4: to the upside is Palenteer up around twenty percent so

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Speaker 4: far in Tuesday session, a couple of percentage points more,

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Speaker 4: and this is a stop that's heading for his biggest

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Speaker 4: jump since January twenty twenty one. They've shown their hand

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Speaker 4: with a new AI tool and talk about talks about

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Speaker 4: unprecedented demand for that AI tool during the earning school.

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Speaker 4: I want to get more on this story and bring

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Speaker 4: in Bloomberg's Lazette Champman, who's here with us in San Francisco.

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Speaker 4: The palentin AI tool is atte what is it? Hey there?

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Speaker 6: Yeah, you know, palent here had a Crackerjack quarter. It

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Speaker 6: had a surprise profit. It said it was going to

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Speaker 6: be profitable not only this current quarter but for the

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Speaker 6: entire year, and they had unprecedented demand for their AI platform,

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Speaker 6: which you know, as the CEO Alex Kark said, is

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Speaker 6: still under construction. They don't exactly have a pricing strategy,

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Speaker 6: but they are in conversations with hundreds of their hundreds

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Speaker 6: of their customers about incorporating this into their into their plans.

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Speaker 3: His turn of phrase, he's not shy of using sometimes

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Speaker 3: more controversial language.

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Speaker 5: He says in large language.

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Speaker 3: Models as a revolution that will raise ships and sinkshit

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Speaker 3: will raise ships and sink ships. I'm just I'm fascinated

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Speaker 3: by the fact how this sits with people ultimately about

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Speaker 3: generative AI studying in large language models helping us in

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Speaker 3: the battlefield, right.

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Speaker 6: I think that there's been a huge demand for that

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Speaker 6: based on the you know, in increased interest both from

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Speaker 6: you know, are the United States Department of Defense as

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Speaker 6: well as our allies, and so it's very much seen

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Speaker 6: as a critical asset in a software first defense scenario

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Speaker 6: given the rising tensions with China and Russia and others

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Speaker 6: that are not necessarily friendly to US interest. So there

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Speaker 6: is definitely a defense application. More than half of Palanteer's

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Speaker 6: revenue does come from the government sector, which includes not

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Speaker 6: only the Department of Defense and all of its branches,

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Speaker 6: but also those of our allies. So it's very much

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Speaker 6: geared toward a defense context, along with some commercial applications.

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Speaker 4: Well, so astonishing about this story. Yeah, the stocks up

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Speaker 4: twenty percent because of AI. Also surprise profit and no

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Speaker 4: one's really talking about.

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Speaker 5: It, right, Well, let's dig into that a little bit more.

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Speaker 2: It's a surprise profit.

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Speaker 6: And one of the things that I think that was

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Speaker 6: interesting was that they achieved this two years before they

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Speaker 6: originally said they would. Originally the plan was for them

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Speaker 6: to hit gap profitability by twenty twenty five. Now they're

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Speaker 6: saying that they will do it for this full year

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Speaker 6: and they will maintain profitability, will continuing to reorient all

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Speaker 6: of their resources. That's thousands of employees around building this

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Speaker 6: AI platform.

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Speaker 5: Absolutely extraordinary, I mean, big move on the stock.

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Speaker 3: Great to have Lizette breaking it all down on the

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Speaker 3: surprise profit side of the equation as well as all

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Speaker 3: in on AI as another company seems to be we

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Speaker 3: thank you so much for coming in and joining the show. Meanwhile,

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Speaker 3: let's turn to another key company that's out with earnings

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Speaker 3: and look, the share price is not having a similar reaction.

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Speaker 3: Global foundryes signaling weakness in its outlook on muted chip demand. More,

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Speaker 3: let's go out to really most in king, the king

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Speaker 3: of all things when it comes to our chip coverage

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Speaker 3: here in what do you make of what this is signaling?

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Speaker 5: More broadly, because we keep on waiting.

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Speaker 3: For there to be some sort of turnaround, Is in

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Speaker 3: any way Global Foundry is a bell weather for the sector?

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Speaker 7: Yeah, one hundred percent.

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Speaker 8: A good way to look at them is a smaller

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Speaker 8: version of TSNC through their customers. Effectively, they're in the

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Speaker 8: auto chip business, they're in the data center business, they're

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Speaker 8: in the mobile phone business. And the outlook that they

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Speaker 8: gave today unfortunately reflects a lot of what's been said

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Speaker 8: throughout this ending season and that's not particularly positive.

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Speaker 3: Next, therefore, are we tending to start to think we

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Speaker 3: can call a bottom on this? Did they in any

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Speaker 3: way say okay, this isn't looking good in the meantime,

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Speaker 3: in the here and the now, but we see some

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Speaker 3: sort of light at the end of the tunnel.

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Speaker 8: Yeah, No, it's a very good question. They're basically effectively

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Speaker 8: speaking out of both sides of their mouth, which a

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Speaker 8: lot of chip companies have been doing, which is and

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Speaker 8: what they've been saying is quarter one that was the worst,

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Speaker 8: that was the absolute bottom, and things will get better

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Speaker 8: from here. But things will not get better at the

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Speaker 8: rate we thought that they would. So that's obviously causing

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Speaker 8: some concern. Can we believe this kind of rose tinted

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Speaker 8: scenario for the second half of the year, And again

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Speaker 8: Global Foundery said, not looking as good as we thought

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Speaker 8: it had.

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Speaker 3: Just on the specifics here in what particular areas of

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Speaker 3: demand When you say it's like a good bell weather

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Speaker 3: or smaller ty SMC or whatever they likes, What particular

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Speaker 3: areas of demand are we so worried about smartphones?

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Speaker 7: Has got to be number one.

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Speaker 8: I mean, they effectively repeated what Qualcom said, which is,

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Speaker 8: China hasn't come back as quick as we thought. The

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Speaker 8: inventory that we said was going to be burned away

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Speaker 8: by the middle of the year looks like it's going

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Speaker 8: to be hanging around into the second half of the year,

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Speaker 8: So they're saying, Look, supply is kind of getting better,

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Speaker 8: that position is improving, but demand whereas demand.

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Speaker 3: It's interesting that when you in video was a big

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Speaker 3: drag today and indeed, as you've pointed out, sort of,

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Speaker 3: this has been a bit of a bell weather for

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Speaker 3: the entire ship sector on the day, and a video

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Speaker 3: actually hit at fifty two week high yesterday.

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Speaker 5: The areas are we going to get both bifurcated market?

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Speaker 3: Are we going to see the chip makers, designers that

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Speaker 3: are all in on AI doing well and those that

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Speaker 3: aren't languishing because they're consumer exposed.

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Speaker 7: Yeah, I mean that would appear to be the way

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Speaker 7: to look at it.

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Speaker 8: Look at the only green dot on my screen today

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Speaker 8: was AMD and that's definitely a play on the future

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Speaker 8: of AI and what investors are expecting to happen.

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Speaker 4: The Bloombergsie and King joining us out of San Francisco,

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Speaker 4: Salesforce expanding its approach to generative AI with the reimagined

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Speaker 4: version of its Tableau suite called Tableau GPT and also

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Speaker 4: Tableau Pulse for more ns. We welcome Salesforce co president

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Speaker 4: Sarah Franklin, who's coming to us from the Tableau conference

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Speaker 4: out in Las Vegas. Let's get straight to the why,

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Speaker 4: why is Salesforce doing this and why now?

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Speaker 9: So big picture, Salesforce has been a pioneer in AI

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Speaker 9: for over a decade. We created Einstein, which brought everyone

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Speaker 9: to have their own data.

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Speaker 2: Scientists about a decade ago, and now today.

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Speaker 9: We're delivering over a trillion prediction every week for all

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Speaker 9: of our hundreds of thousands of customers, which brought them

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Speaker 9: into AI. And now we've moved from predictive to generative,

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Speaker 9: and Salesforce, who has led every seismic shift and technology

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Speaker 9: from going to cloud, to mobile to social, we are

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Speaker 9: here right at the forefront leading all of our customers

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Speaker 9: into dinnerative AI with Tableau GPT and Tableau Pulse.

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Speaker 4: So, Sarah, you're out at the Tableau conference. The other

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Speaker 4: tool announced is Slack GPT. So the question is this

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Speaker 4: is this you trying to get Salesforce customers to use

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Speaker 4: the services of other things you've acquired in recent years.

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Speaker 9: So, Salesforce, we have an incredible suite across the entire

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Speaker 9: customer through sixty sales service marketing commerce lack has been

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Speaker 9: an incredible addition to our portfolio helping everyone have great

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Speaker 9: productive employees. And we ask ourselves a question, how do

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Speaker 9: you make every employee more productive? How do you make

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Speaker 9: every customer more happy? How do you provide incredible customer

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Speaker 9: service and sales and marketing and a fully integrated single.

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Speaker 2: Source of truth of your customers?

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Speaker 9: And so yes, by providing that entire suite of products

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Speaker 9: for our customers, they can all have better customers and

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Speaker 9: better employees. And it's really important that we give them

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Speaker 9: all of their data so they can unlock it and

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Speaker 9: really have that trusted customer and company data to use

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Speaker 9: generative AI and to have tabloa GPT really bring that

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Speaker 9: data to life for everyone that's involved in customer engagement.

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Speaker 4: Caroline data is really the key point, isn't it, Particularly

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Speaker 4: when we're talking about enterprise is a use case for

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Speaker 4: generative AI tools. There's an element of concern about the

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Speaker 4: data it's sourcing and how it's secure.

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Speaker 3: Yeah, and so to that point, you use trusted a

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Speaker 3: number of times there or single source of truth. Is

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Speaker 3: there any concern that generative AI does just make some

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Speaker 3: things up? If there is a hole in the private

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Speaker 3: data that this is being run on the so called

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Speaker 3: hallucinations and many people to take issue with that particular

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Speaker 3: turn of phrase, But is that happening? How do you

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Speaker 3: ensure that people are getting the right insights at the

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Speaker 3: right time.

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Speaker 9: Trust is absolutely paramount, As we've discussed just now, Every

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Speaker 9: company wants to have trusted data.

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Speaker 2: They need to know that they have their data is

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Speaker 2: being trusted.

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Speaker 9: Their customers expect them to trust them with their data

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Speaker 9: and salesforce at our core, we have always had trust

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Speaker 9: other number one value, and so having trusted data is

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Speaker 9: important because your AI is only as good as your data,

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Speaker 9: and so no company wants to bring hallucinations, as you say,

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Speaker 9: into the enterprise.

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Speaker 2: They need to know that they can trust the AI.

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Speaker 9: And that's why our approach is founded on trust and

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Speaker 9: we always have a human in the process because the

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Speaker 9: AI is here to help us, not to not to

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Speaker 9: replace us, and so that's so important that the data

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Speaker 9: is trusted, so that you can also trust the generative

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Speaker 9: AI that's being created from that data.

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Speaker 3: Interesting, so I'm feeling that you're on the AIS here

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Speaker 3: to augment us humans rather than take away our jobs.

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Speaker 3: But you are someone who's built your career on the

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Speaker 3: democratization of technology, or someone who's se passive passionate about

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Speaker 3: how with ease people can change.

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Speaker 5: From a blue collar job to a white college job.

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Speaker 3: Using, for example, the ways in which you've used trailheading

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Speaker 3: for example. But are you brought a picture here thinking

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Speaker 3: AI is going to inevitably take white college jobs at

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Speaker 3: the moment.

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Speaker 9: So I really want to look at generative AI as

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Speaker 9: an incredible opportunity for us.

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Speaker 2: It's really interesting when you rewind back in history and

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Speaker 2: you think of the first computer.

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Speaker 9: The first computer was a person, not a machine, and

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Speaker 9: there's a lot of fear that it would replace us

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Speaker 9: in our jobs. Fast forward to today, we don't have

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Speaker 9: enough skilled talent for all of the jobs that work

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Speaker 9: with computers and work in tech, and so we're already

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Speaker 9: seeing new careers being created such as prompt engineering or

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Speaker 9: AI illustrations.

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Speaker 2: There's just a lot of opportunity.

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Speaker 9: So we as an industry and as salesforce, we do

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Speaker 9: take it as a responsibility to scale people up for

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Speaker 9: the future. We created Trailhead as a free online learning

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Speaker 9: platform to democratize all of this technology so everyone can

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Speaker 9: have access and everyone can learn. There's an incredible opportunity

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Speaker 9: and we want to make it easy and accessible for everyone,

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Speaker 9: and we can also hopefully change the ratios and tech

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Speaker 9: in the process. But yes, we are here to help

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Speaker 9: skill people up and help remove the fear from this

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Speaker 9: incredible new generation of technology we see with generative AI.

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Speaker 4: Sarah, how are these new tools driving sales for Salesforce?

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Speaker 9: So Generative AI is everything that all of our customers

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Speaker 9: are talking about. They are wondering how to future prove

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Speaker 9: their business in the wake of this new technology trend,

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Speaker 9: and it's here to stay. It's not a bad and

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Speaker 9: so every single one of our customers is looking at

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Speaker 9: Salesforce right now and saying, we trust you. We know

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Speaker 9: that you will guide us into this future, just like

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Speaker 9: you guided us into cloud, into mobile, into social. So yes,

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Speaker 9: every single one of our customers wants Salesforce GPT to

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Speaker 9: help them.

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Speaker 2: With sales GPP, service GPT, marketing GPT and more.

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Speaker 9: And Tablot GPT and tablet Pulse are incredible innovations that

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Speaker 9: are going to help fuel all of our customers' success.

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Speaker 4: In your career, as Caroline pointed out, you've been through

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Speaker 4: waves of new technological advancement. This has happened quite quickly.

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Speaker 4: Did Salesforce really plan these tools over a really long

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Speaker 4: period of time, or is this something that you've rushed

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Speaker 4: through in recent weeks in response to what the rest

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Speaker 4: of the industry's done.

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Speaker 2: So this is what's so powerful is.

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Speaker 9: That Salesforce has been a pioneer in AI for over

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Speaker 9: a decade. We've been investing in Einstein, which is our

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Speaker 9: AI platform, and we have seen, as I mentioned earlier,

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Speaker 9: we have over one trillion predictions being done every single

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Speaker 9: week on our AI platform. So this is not something

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Speaker 9: that we're just pulling out of a hat. We have

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Speaker 9: been investing in this for a long time, and we

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Speaker 9: have the world's best data scientists that are here at Salesforce,

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Speaker 9: and they're generating all kinds of incredible large language models

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Speaker 9: that help us create code, that help us create reply response,

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Speaker 9: that help us create.

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Speaker 2: Great engagement and ways for like you.

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Speaker 9: See with Tableau GBT and Tableau Pulse, for people to

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Speaker 9: really bring their data to life, where in the past

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Speaker 9: they haven't been able to really do that easily. So

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Speaker 9: this has been something Salesforce has been doing for a

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Speaker 9: long time and will continue to be a leader in generative.

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Speaker 3: AI, a leader at a time where the macro headwinds

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Speaker 3: for every single industry are tough at the moment, and Sarah,

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Speaker 3: as you talk about the in house talent that you

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Speaker 3: have to keep building, it's at a time where we

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Speaker 3: know companies like you also are having to lay off staff,

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Speaker 3: having to slim down in the face of what has

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Speaker 3: been a slowing economy.

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Speaker 5: Have you got the right mix of talent in the

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Speaker 5: moment you.

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Speaker 9: Think at Salesforce, we have the most talented engineers, marketeers, salespeople.

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Speaker 9: We have the best people in the business at Salesforce,

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Speaker 9: and we are more equipped than ever. Our company is

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Speaker 9: in a great spot set up for the decades to come.

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Speaker 9: We're laser focused on our customers, on our innovation, and

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Speaker 9: really delivering success for everyone.

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Speaker 3: Sarah Franklin, thanks for spending some time with us co

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Speaker 3: president of Salesforce.

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Speaker 10: There.

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Speaker 3: Meanwhile, ed one of the biggest concerns, of course, that

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Speaker 3: comes with using artificial intelligence just in our daily lives, Well,

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Speaker 3: we're just talking about being replaced by it, especially for

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Speaker 3: those that work in the media landscape.

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Speaker 5: Enter GPT zero.

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Speaker 3: It's an app launch to distinguish whether copy was written

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Speaker 3: by a human or by artificial intelligence. More than one

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Speaker 3: million users of registered since January and the brain behind

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Speaker 3: the app is just a twenty two year old from

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Speaker 3: Princeton University. A student is also launching a new program

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Speaker 3: called Origin, which aims to weed out disinformation in the

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Speaker 3: online media generated by AI. It secured three and a

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Speaker 3: half million dollars in funding so far.

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Speaker 4: Ed Yeah, let's stick with AI. IBM introducing a platform

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Speaker 4: for large companies to train and use AI models. When

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Speaker 4: it rains, it pours Caroline, the company leaning in on

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Speaker 4: its Watson legacy to stand out in a crowded field

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Speaker 4: for AI. Tool have to say, not doing much to

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Speaker 4: support the shares this Wednesday Tuesday. Sorry, down one right

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Speaker 4: and at a seven month low. So many headlines in

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Speaker 4: the field of AI now coming up. Regional banks resume

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Speaker 4: their sell off as uncertainty hits the sector. We're going

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Speaker 4: to discuss that next in our weekly Wall Street Beat.

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Speaker 7: This is bloomberg.

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Speaker 4: Time for Wall Street Beat. Pack West and Western Alliance

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Speaker 4: led regional bank stocks lower today as the hard hit

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Speaker 4: sector resumed its decline. The drop comes as investors remain

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Speaker 4: unnerved by a rash of deposit outflows from banks and

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Speaker 4: increasing concerns about general stability. Plus Linked in the latest

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Speaker 4: tech company to join the wave of job cuts. The

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Speaker 4: company plans to shut its jobs app in China and

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Speaker 4: cut about seven hundred and sixteen jobs as the networking

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Speaker 4: service further shrinks its presence in the world's second largest economy,

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Speaker 4: and a group of firms including Goldman, Sachs and Microsoft

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Speaker 4: adjoining a new blockchain system aimed at linking disparate institutional applications,

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Speaker 4: potentially encouraging broader adoption of distributed ledger technology in financial markets.

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Speaker 4: Participants in the Canton network, which will start testing some

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Speaker 4: features in July, say the system offers better privacy and

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Speaker 4: controls than currently available AI. At the same time, it

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Speaker 4: will achieve a scale and standard appropriate for financial institutions.

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Speaker 4: That all according to a quite long statement released by

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Speaker 4: the companies on Tuesday.

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Speaker 3: Yeah, a little one to dig into. Basically, blockchain is back. Meanwhile,

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Speaker 3: we els is back. Celebrities endorsing brands are x three

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Speaker 3: raising one hundred and fifty million dollars from athletes from

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Speaker 3: celebrities were at Second Equity Fund where they really analyze

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Speaker 3: some consumer opportunities.

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Speaker 5: We've got an exclusive interview for you coming up.

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Speaker 3: Nate Robb's going to be joining us managing partner at

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Speaker 3: our ex three ventures that's up next.

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Speaker 5: Meanwhile, another stot that we've got an eye on Nintendo.

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Speaker 3: Wow, the Mario maker is learning and warning a big

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Speaker 3: slowdown in the switch console sales. This is a key concern,

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Speaker 3: but actually Nintendo managing to tread above water at the moment,

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Speaker 3: at least over the last few trading days. But it

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Speaker 3: seems as though maybe you want too many consoles out there.

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Speaker 5: D you know you're the expert on this one.

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Speaker 4: Yeah, look, I am tracking Mobile. I we kind of

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Speaker 4: pared some earlier gains. We're up sort of more than

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Speaker 4: nine percent. After we did an interview with the CEO

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Speaker 4: the company reaching a deal with Porsche to just basically

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Speaker 4: give them their advanced driver technology assistance technology going forward.

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Speaker 4: The CEO telling me that actually we could see the

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Speaker 4: tech in real cars in production sooner than we might think.

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Speaker 4: Have a listen.

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Speaker 11: Normally, when you get a design, when it's between two

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Speaker 11: to three years until you have started off production. So

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Speaker 11: we're talking about the same timeframe. But we started working

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Speaker 11: a few months early before this announcement, so you can

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Speaker 11: do this smath then come up with a start of production.

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Speaker 4: I would say, Caroline, this is a deal that the

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Speaker 4: mobile it's in recent weeks, particularly on the earnings care

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Speaker 4: or wondering who is this mysterious European automaker the mobilized

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Speaker 4: doing businesses. Well, it's a pretty decent one poor show.

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Speaker 4: It'll be interesting to see if this moves the needle

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Speaker 4: for them and they get some more deals. Welcome back

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Speaker 4: to Bloomberg Technology. I'm ed love Low in San Francisco.

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Speaker 3: I'm Caroline Heard in New York. And let's dig into

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Speaker 3: some of this market action. Halfway through the show and

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Speaker 3: I'm looking at what is sentiment a little bit more

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Speaker 3: like luster On the day, we're off by seven ten

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Speaker 3: percent on the NASDAG. We're worried about some key themes

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Speaker 3: here in the US, the debt ceial course, keeping some

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Speaker 3: investors on edge. We're also worrying about China potentially more

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Speaker 3: of a hit to that economy that we're anticipating imports

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Speaker 3: not as fast as we wanted Golden dragons. So some

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Speaker 3: of those Chinese listed companies here in the United States,

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Speaker 3: or Chinese companies listed here in the US, are on

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Speaker 3: the downside. Two and a half percent. KBW bankin nets.

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Speaker 3: Keep an eye on some of these regional lenders. We

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Speaker 3: are still worried about them. Pack westers on the downside

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Speaker 3: once again, so a lot to think about from the

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Speaker 3: macro perspective, but also let's dig into the earnings the micro.

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Speaker 3: Have a quick look at what's on the move in

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Speaker 3: terms of your individual tech names on the day. Look,

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Speaker 3: Amazon manages to outperform and what's actually up modern than this.

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Speaker 3: It's adding in terms of points perspective to the NASDAK

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Speaker 3: and the NASDAQ one hundred to day. It's unveiling the

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Speaker 3: fact that you might be able to buy Amazon products

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Speaker 3: even when you're in a gaming or virtual reality sphere

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Speaker 3: at the moment.

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Speaker 5: So don't worry. You can order that Amazon get you

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Speaker 5: down on a matter where you go.

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Speaker 3: Paleteer, as you mentioned at the top of the show,

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Speaker 3: ed up twenty two percent, absolutely soaring because Moves is

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Speaker 3: twenty twenty one as they say, look this AI app

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Speaker 3: that they're developing, the software they will be used even

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Speaker 3: in the battlefield.

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Speaker 5: That is unprecedented demand for it.

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Speaker 3: PayPal though on the downside after its earnings because operating

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Speaker 3: margin not as strong as wanted to be seen. Even

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Speaker 3: though they're seeing volumes increase in terms of overall payments processing, they're.

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Speaker 5: Doing too much white labeling.

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Speaker 3: People want to see more of the PayPal payments going forward,

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Speaker 3: and I'm looking at fiska off by six tens percent,

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Speaker 3: six percent fully actually, as we worry about the software

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Speaker 3: in its new SUV and whether or not that's looking

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Speaker 3: pretty cunky for the time being.

441
00:22:07,240 --> 00:22:10,159
Speaker 4: At right from the public markets, let's go to the

442
00:22:10,240 --> 00:22:13,440
Speaker 4: private markets. The Venger Fund RX three has just raised

443
00:22:13,440 --> 00:22:16,440
Speaker 4: one hundred and fifty million dollars from athletes and celebrities

444
00:22:16,760 --> 00:22:20,280
Speaker 4: for its second consumer focus growth equity fund, The Farmers,

445
00:22:20,320 --> 00:22:24,560
Speaker 4: co founded by football star Aaron Rodgers, bench catalyst Byron Roth,

446
00:22:24,640 --> 00:22:28,600
Speaker 4: and Nate Raby, who joins us now for an exclusive interview. Nate,

447
00:22:28,680 --> 00:22:35,520
Speaker 4: good morning to you. Why are all of the LPs athletes, actors, celebrities. Yeah,

448
00:22:35,600 --> 00:22:36,920
Speaker 4: thanks Ed Caroline for having me on.

449
00:22:37,720 --> 00:22:40,880
Speaker 12: I think the reason we have a lot of these athletes,

450
00:22:40,920 --> 00:22:45,760
Speaker 12: celebrities and actors as LPs it really provides us access

451
00:22:46,040 --> 00:22:49,679
Speaker 12: to consumer brands across the growth sector.

452
00:22:49,880 --> 00:22:52,080
Speaker 4: And not only we have be able to provide capital,

453
00:22:52,400 --> 00:22:53,560
Speaker 4: but we can provide.

454
00:22:53,359 --> 00:22:55,800
Speaker 12: Value beyond that capital and really move the needle and

455
00:22:55,880 --> 00:22:58,439
Speaker 12: help drive revenue to these brands.

456
00:23:00,040 --> 00:23:03,360
Speaker 4: When you look at the portfolio companies or potential portfolio companies.

457
00:23:04,000 --> 00:23:08,440
Speaker 4: Do you think that having celebrity backing is an investor

458
00:23:08,640 --> 00:23:13,280
Speaker 4: and then endorsement increases the I guess the likelihood that

459
00:23:13,400 --> 00:23:16,840
Speaker 4: you will have success and then a successful exit down

460
00:23:16,880 --> 00:23:17,240
Speaker 4: the road.

461
00:23:18,680 --> 00:23:22,000
Speaker 12: Yeah, I think it definitely can if there's the authentic relationship.

462
00:23:22,520 --> 00:23:26,760
Speaker 12: So we really drive, really strive to align our differentiated

463
00:23:26,840 --> 00:23:30,520
Speaker 12: LPU based with brands when there is that authentic relationship.

464
00:23:31,080 --> 00:23:32,880
Speaker 4: I don't think you can set it up.

465
00:23:32,840 --> 00:23:35,639
Speaker 12: Where the days of where they just get paid to

466
00:23:35,680 --> 00:23:37,760
Speaker 12: do a post, those are kind of long gone. So

467
00:23:37,920 --> 00:23:41,280
Speaker 12: we really try to baster authentic relationships between our differentiated

468
00:23:41,359 --> 00:23:42,520
Speaker 12: LP based in our brands.

469
00:23:43,920 --> 00:23:46,800
Speaker 3: Some VCS that I've been speaking to Nate have said

470
00:23:46,840 --> 00:23:48,760
Speaker 3: the one area that they are not going anywhere near

471
00:23:49,200 --> 00:23:53,720
Speaker 3: a consumer led companies right now, consumer focused companies because

472
00:23:53,760 --> 00:23:54,720
Speaker 3: of the economy that we're in.

473
00:23:54,840 --> 00:23:56,280
Speaker 5: Why is it still the great hit for you?

474
00:23:58,000 --> 00:23:58,200
Speaker 9: Yeah?

475
00:23:58,280 --> 00:24:02,640
Speaker 12: For us, because we have athletes and entertainers. It's easy

476
00:24:02,720 --> 00:24:04,959
Speaker 12: for them to get behind because it's products and brands

477
00:24:05,160 --> 00:24:07,240
Speaker 12: they use on the have a day basis. So we

478
00:24:07,359 --> 00:24:11,320
Speaker 12: invest across help, wellness, active, lifestyle, beauty, pet and these

479
00:24:11,320 --> 00:24:13,920
Speaker 12: are all brands that they can feel, touch and using

480
00:24:13,960 --> 00:24:17,800
Speaker 12: their daily life. We have shifted our focus from kind

481
00:24:17,840 --> 00:24:21,960
Speaker 12: of high growth BTC consumer brands to more consumer essentials,

482
00:24:22,119 --> 00:24:25,639
Speaker 12: profitable brands that have strong fundamentals behind them.

483
00:24:25,800 --> 00:24:26,880
Speaker 5: Always got to feed your pet.

484
00:24:27,119 --> 00:24:28,760
Speaker 3: Talk to us a little bit though about some of

485
00:24:28,840 --> 00:24:31,560
Speaker 3: the overall valuations that you're seeing. Are you getting a

486
00:24:31,760 --> 00:24:35,560
Speaker 3: better entry point when you're starting these conversations and where

487
00:24:35,600 --> 00:24:37,200
Speaker 3: do you think some of the opportunities are and what

488
00:24:37,359 --> 00:24:38,399
Speaker 3: is a dislocated market?

489
00:24:39,840 --> 00:24:42,680
Speaker 12: Yeah, I think there's there's definitely been a healthy reset

490
00:24:42,880 --> 00:24:45,080
Speaker 12: in the market across private equity.

491
00:24:46,359 --> 00:24:47,200
Speaker 4: You know, we're looking at it.

492
00:24:47,240 --> 00:24:49,440
Speaker 12: We've only made one investment out of our second fund,

493
00:24:49,520 --> 00:24:53,560
Speaker 12: and well positioned to kind of take advantage and really

494
00:24:53,600 --> 00:24:56,760
Speaker 12: help provide value to these brands. So we're excited about

495
00:24:56,760 --> 00:25:00,760
Speaker 12: about this vintage because there definitely has been a healthy reset.

496
00:25:01,080 --> 00:25:04,159
Speaker 3: Healthy reset that in many ways ED has not just

497
00:25:04,240 --> 00:25:08,159
Speaker 3: been seen across technology companies and in the private markets,

498
00:25:08,160 --> 00:25:11,000
Speaker 3: but in the public markets as well. But really a

499
00:25:11,080 --> 00:25:13,440
Speaker 3: lot of this is about having technology at its core,

500
00:25:13,520 --> 00:25:15,160
Speaker 3: a way in which you can speak to a mass

501
00:25:15,200 --> 00:25:18,480
Speaker 3: consumer via the power of well social media, and big

502
00:25:18,560 --> 00:25:20,399
Speaker 3: brands that are happened to be big individuals in this

503
00:25:20,520 --> 00:25:20,920
Speaker 3: case ED.

504
00:25:21,640 --> 00:25:24,159
Speaker 4: Yeah, I guess that in that vein Nay, when you

505
00:25:24,240 --> 00:25:27,359
Speaker 4: guys are making an investment decision, a deck hits your desk,

506
00:25:27,840 --> 00:25:30,320
Speaker 4: do you then invite all of these LPs that would

507
00:25:30,320 --> 00:25:33,640
Speaker 4: be involved in the endorsement of this company to participate

508
00:25:33,720 --> 00:25:36,400
Speaker 4: actively in that investment decision or do the three partners

509
00:25:36,840 --> 00:25:38,320
Speaker 4: just make the decision on their behalf.

510
00:25:39,800 --> 00:25:40,560
Speaker 2: No great question.

511
00:25:40,880 --> 00:25:46,120
Speaker 12: So our LPs and our athletes Lebri advessors we're return focused.

512
00:25:46,240 --> 00:25:46,480
Speaker 2: First.

513
00:25:46,840 --> 00:25:49,639
Speaker 12: We don't require anybody to do anything, but rather, if

514
00:25:49,680 --> 00:25:52,280
Speaker 12: there is that natural alignment, we do go out to

515
00:25:52,400 --> 00:25:55,040
Speaker 12: our existing lpbasency if there is interest, and they would

516
00:25:55,640 --> 00:25:57,880
Speaker 12: it is a brand that they would give behind. They're

517
00:25:57,920 --> 00:26:00,200
Speaker 12: not involved in the day to day investment decision and

518
00:26:00,560 --> 00:26:03,200
Speaker 12: not required to do anything for the brand. But we

519
00:26:03,280 --> 00:26:05,680
Speaker 12: do try to align ourselves with brands where there is

520
00:26:05,720 --> 00:26:06,679
Speaker 12: someone in our network that we.

521
00:26:06,680 --> 00:26:07,520
Speaker 2: Can provide value to.

522
00:26:08,760 --> 00:26:11,000
Speaker 4: Nate Ashton Kirsch had told us on the show last

523
00:26:11,080 --> 00:26:13,800
Speaker 4: week he raised two hundred and forty three million for

524
00:26:13,920 --> 00:26:17,760
Speaker 4: his AI fund in just five weeks. How quickly did

525
00:26:17,800 --> 00:26:18,680
Speaker 4: he raise this fund?

526
00:26:19,880 --> 00:26:22,520
Speaker 12: A little more in five five weeks? Ashton Kutcher as

527
00:26:22,840 --> 00:26:26,000
Speaker 12: a strong brand in the investing side. That's very impressive.

528
00:26:26,040 --> 00:26:29,320
Speaker 12: Definitely took us a little longer, so very impressed with

529
00:26:29,520 --> 00:26:32,400
Speaker 12: what he did, but we're happy to say we're oversubscribed

530
00:26:32,880 --> 00:26:33,919
Speaker 12: with our second fund him.

531
00:26:34,080 --> 00:26:35,480
Speaker 5: What about artificial intelligence?

532
00:26:35,520 --> 00:26:37,440
Speaker 3: What a way about the ways in which that is

533
00:26:37,480 --> 00:26:39,520
Speaker 3: seeming uppending every business model?

534
00:26:39,560 --> 00:26:40,639
Speaker 5: Is it something that you're looking at?

535
00:26:41,720 --> 00:26:44,320
Speaker 12: Yeah, I think it's something that all of our brands

536
00:26:44,400 --> 00:26:47,240
Speaker 12: across the consumer spectrum are going to have to take

537
00:26:47,280 --> 00:26:50,720
Speaker 12: a look at and how they can incorporate it into

538
00:26:50,800 --> 00:26:54,800
Speaker 12: their company. I think it's still early days here and

539
00:26:55,400 --> 00:26:58,200
Speaker 12: it's definitely something though that we're looking at and will

540
00:26:58,240 --> 00:27:00,679
Speaker 12: be a part of our our super brands.

541
00:27:01,040 --> 00:27:03,320
Speaker 3: Nate Raby, thanks for the time, managing partner and our

542
00:27:03,520 --> 00:27:06,280
Speaker 3: X three ventures. Meanwhile, coming up, we're going to stick

543
00:27:06,440 --> 00:27:09,520
Speaker 3: on the focus of investment VC firms continuing to tap

544
00:27:09,560 --> 00:27:11,520
Speaker 3: their commitments to AI native companies.

545
00:27:11,760 --> 00:27:13,680
Speaker 5: We're speaking with a partner from Bessemer Venture Partners.

546
00:27:13,720 --> 00:27:16,080
Speaker 3: We're gonna dig in really to the nuance of the portfolio,

547
00:27:16,480 --> 00:27:17,520
Speaker 3: what they're building in AI.

548
00:27:17,720 --> 00:27:18,240
Speaker 5: That's next.

549
00:27:18,440 --> 00:27:43,680
Speaker 1: This is Bloomberg. There's time now for our VC roundup.

550
00:27:43,320 --> 00:27:47,200
Speaker 3: Investment firm processes exploring potential divestments from its emerging markets

551
00:27:47,240 --> 00:27:50,080
Speaker 3: fintech company Pay You Look. Sources are saying it's working

552
00:27:50,119 --> 00:27:52,200
Speaker 3: with Bank of America to gauge interest in pay US

553
00:27:52,240 --> 00:27:54,959
Speaker 3: business outside of India and could fetch as much as

554
00:27:54,960 --> 00:27:58,240
Speaker 3: eight hundred million dollars in the potential deal. Meanwhile, Taiwanese

555
00:27:58,320 --> 00:28:01,879
Speaker 3: battery maker pro Logium Technology is looking into funding an

556
00:28:01,920 --> 00:28:04,400
Speaker 3: evaluation of about two billion dollars to ramp up growth

557
00:28:04,440 --> 00:28:05,280
Speaker 3: in twenty twenty four.

558
00:28:05,520 --> 00:28:08,080
Speaker 5: The ev battery supplier, which is backed by Mercedes.

559
00:28:07,720 --> 00:28:10,280
Speaker 3: Benz, some talks with potential advisors to raise as much

560
00:28:10,280 --> 00:28:13,840
Speaker 3: as three hundred million dollars, according to sources, and Aura,

561
00:28:13,920 --> 00:28:16,600
Speaker 3: the finished company behind some of those pricey health tracking rings,

562
00:28:16,760 --> 00:28:19,639
Speaker 3: says it's buying a little known tech startup called Proxy.

563
00:28:19,840 --> 00:28:22,200
Speaker 5: Proxy makes digital identification tools.

564
00:28:22,200 --> 00:28:27,080
Speaker 4: Said yeah, loving those private startup and venture stories from

565
00:28:27,160 --> 00:28:29,359
Speaker 4: around the world. They're stay in the VC space and

566
00:28:29,480 --> 00:28:33,879
Speaker 4: wait welcome. Samir de La key partner with Besmadventure Partners,

567
00:28:34,200 --> 00:28:35,440
Speaker 4: a billion dollars.

568
00:28:35,600 --> 00:28:39,760
Speaker 13: Billion dollars the AI four AI from an existing fund,

569
00:28:40,000 --> 00:28:42,040
Speaker 13: from an existing fund. We have lots of flexibility with

570
00:28:42,080 --> 00:28:44,280
Speaker 13: our existing funds to be able to deploy it. The

571
00:28:44,400 --> 00:28:47,560
Speaker 13: message is really clear to entrepreneurs out there. We are

572
00:28:47,920 --> 00:28:51,600
Speaker 13: committed to AI in investment in AI native founders.

573
00:28:52,240 --> 00:28:56,520
Speaker 3: Okay, tell us Samir, how you thought week from chaff

574
00:28:56,560 --> 00:28:59,840
Speaker 3: at the moment we had. Of course, many VC come

575
00:29:00,120 --> 00:29:02,600
Speaker 3: on saying there's plenty of opportunities to write checks at

576
00:29:02,640 --> 00:29:05,640
Speaker 3: the moment, but not all of the companies are as

577
00:29:05,640 --> 00:29:07,320
Speaker 3: strong as the other. How do you understand that they're

578
00:29:07,360 --> 00:29:09,080
Speaker 3: really doing something foundational within AI?

579
00:29:10,400 --> 00:29:13,240
Speaker 13: No question, and that is fundamental to our job is

580
00:29:13,280 --> 00:29:15,440
Speaker 13: to be able to sort those I will just say

581
00:29:15,840 --> 00:29:19,280
Speaker 13: I've been in software now for twenty eight years, served

582
00:29:19,320 --> 00:29:23,560
Speaker 13: as CEO of two different companies, joined venture capital recently.

583
00:29:23,600 --> 00:29:27,240
Speaker 13: But I'll tell you I've seen these seminal moments in

584
00:29:27,440 --> 00:29:31,800
Speaker 13: technology history where it becomes clear to the mainstream that

585
00:29:31,880 --> 00:29:34,760
Speaker 13: we have made a technical leap forward and everything about

586
00:29:34,920 --> 00:29:37,600
Speaker 13: life and work will be different. I saw it with

587
00:29:37,680 --> 00:29:40,800
Speaker 13: the Netscape moment in ninety five. I saw it with

588
00:29:40,920 --> 00:29:42,760
Speaker 13: the iPhone moment with.

589
00:29:42,920 --> 00:29:43,800
Speaker 4: Jobs in seven.

590
00:29:44,680 --> 00:29:46,280
Speaker 13: And there's just no question in my mind that we

591
00:29:46,320 --> 00:29:49,320
Speaker 13: will look back at November thirtieth of twenty two and

592
00:29:49,440 --> 00:29:53,640
Speaker 13: say that was the chat GPT moment, and everything about

593
00:29:53,640 --> 00:29:57,680
Speaker 13: the future is going to be different in great ways.

594
00:29:57,800 --> 00:30:01,440
Speaker 13: And I think that in on us as venture capitalists.

595
00:30:01,480 --> 00:30:03,320
Speaker 13: If I take the Netscape example, the first one that

596
00:30:03,400 --> 00:30:05,720
Speaker 13: I lived through. We need to go find the next

597
00:30:05,800 --> 00:30:08,560
Speaker 13: Jeff Bezos and I know he's out there and or

598
00:30:08,680 --> 00:30:10,640
Speaker 13: she's out there, and we would love to talk to her,

599
00:30:10,800 --> 00:30:12,560
Speaker 13: and we want to and we have to be able

600
00:30:12,600 --> 00:30:15,200
Speaker 13: to sort the Jeff Bezos from you know, the next

601
00:30:15,280 --> 00:30:18,320
Speaker 13: Amazon from the next Webvan And that's hard to do,

602
00:30:18,480 --> 00:30:20,239
Speaker 13: but we're excited to go do it, and we want

603
00:30:20,280 --> 00:30:22,480
Speaker 13: a signal to the market. We've got a billion dollars

604
00:30:22,560 --> 00:30:27,040
Speaker 13: of capital here to deploy into this new breakthrough that

605
00:30:27,120 --> 00:30:28,200
Speaker 13: we think is going to change the world.

606
00:30:28,200 --> 00:30:30,320
Speaker 3: And we're looking at some of your portfolio Jasper Dpel,

607
00:30:30,440 --> 00:30:35,120
Speaker 3: for example, Samir. There is currently this discussion about whether

608
00:30:35,560 --> 00:30:39,200
Speaker 3: big tech or indeed all gardens will win out. We see,

609
00:30:39,600 --> 00:30:42,640
Speaker 3: of course everyone talking about open AI and being a

610
00:30:43,040 --> 00:30:45,600
Speaker 3: relationship with Microsoft. We think about the competition with Google,

611
00:30:45,720 --> 00:30:48,840
Speaker 3: but many are also talking about well open source. We're

612
00:30:48,840 --> 00:30:50,920
Speaker 3: also seeing how hugging face makes an impact on that.

613
00:30:51,080 --> 00:30:53,960
Speaker 3: What do you think about that sort of the dichotomy we're.

614
00:30:53,840 --> 00:30:54,480
Speaker 5: Getting at the moment.

615
00:30:55,560 --> 00:30:58,800
Speaker 13: Absolutely, I think you're going to see continued innovation at

616
00:30:58,920 --> 00:31:02,080
Speaker 13: all layers of the staff. We're seeing open source flourish

617
00:31:02,520 --> 00:31:05,840
Speaker 13: costs are coming down really quickly. I do believe if

618
00:31:05,880 --> 00:31:07,240
Speaker 13: you were to ask me as a betting man, I

619
00:31:07,320 --> 00:31:10,720
Speaker 13: think at the foundation model layers would probably see a

620
00:31:10,800 --> 00:31:15,520
Speaker 13: redux of the cloud wars, where the big tech provides

621
00:31:15,920 --> 00:31:19,000
Speaker 13: the biggest platforms. But I think you'll but you will

622
00:31:19,080 --> 00:31:22,800
Speaker 13: also see open source solutions. I think you'll see vertical

623
00:31:23,360 --> 00:31:27,520
Speaker 13: solutions that are smaller lms trained to solve a particular

624
00:31:27,640 --> 00:31:31,120
Speaker 13: problem set in a given vertical industry, et cetera. And

625
00:31:31,200 --> 00:31:32,720
Speaker 13: so I think we're just going to and then of

626
00:31:32,800 --> 00:31:35,440
Speaker 13: course at the application layer, I think you're going to

627
00:31:35,480 --> 00:31:41,720
Speaker 13: see the creativity of the world's entrepreneurs unleashed and problem

628
00:31:41,840 --> 00:31:44,640
Speaker 13: solved in novel ways. And there will be thousands of

629
00:31:44,680 --> 00:31:47,120
Speaker 13: those solutions. So I think this is one of those

630
00:31:47,200 --> 00:31:51,160
Speaker 13: moments where I genuinely would say trillions of dollars of

631
00:31:51,240 --> 00:31:54,560
Speaker 13: market cap will be created from this AI moment. And

632
00:31:54,680 --> 00:31:56,760
Speaker 13: it's not I say that not because my crystal ball

633
00:31:56,840 --> 00:31:59,400
Speaker 13: is any clearer than anybody else's, but because I'm a

634
00:31:59,440 --> 00:32:01,960
Speaker 13: student of his, and I've lived in twenty eight years

635
00:32:02,360 --> 00:32:06,000
Speaker 13: through the previous platform shifts, and every other platform shift

636
00:32:06,080 --> 00:32:11,080
Speaker 13: has led to that level of innovation creation and market

637
00:32:11,520 --> 00:32:13,440
Speaker 13: value creation, which are.

638
00:32:13,440 --> 00:32:15,920
Speaker 4: Is you pulling back from or hitting pause on so

639
00:32:16,040 --> 00:32:18,400
Speaker 4: you can commit a billion dollars to AI Native.

640
00:32:19,200 --> 00:32:22,320
Speaker 13: The fun thing for me about the AI investments is

641
00:32:22,640 --> 00:32:25,440
Speaker 13: AI is not a category. In my humble opinion, I

642
00:32:25,520 --> 00:32:28,360
Speaker 13: think it is going to be embedded everywhere. They're the

643
00:32:28,440 --> 00:32:31,120
Speaker 13: AI natives. We will invest deeply, and that's what this

644
00:32:31,240 --> 00:32:34,800
Speaker 13: fund is all about. Every one of our portfolio companies

645
00:32:34,920 --> 00:32:38,680
Speaker 13: have heard the message, how are you adopting and rethinking

646
00:32:38,760 --> 00:32:41,800
Speaker 13: your solutions in the context of this technical leap forward?

647
00:32:42,760 --> 00:32:45,640
Speaker 13: And so I think we're seeing it everywhere, and so

648
00:32:45,760 --> 00:32:49,840
Speaker 13: I believe will continue to invest meaningfully behind all the

649
00:32:49,920 --> 00:32:56,520
Speaker 13: places we have historically vertical SaaS, horizontal SaaS, and cybersecurity

650
00:32:56,720 --> 00:33:00,120
Speaker 13: or healthcare. We do invest behind crypto as well. Well,

651
00:33:00,240 --> 00:33:03,719
Speaker 13: We've got a Dow where and so I believe crypto

652
00:33:03,800 --> 00:33:07,440
Speaker 13: as well. I think all of these categories will fundamentally

653
00:33:07,960 --> 00:33:10,400
Speaker 13: adopt AI because it's just a great.

654
00:33:10,240 --> 00:33:15,880
Speaker 4: New capability psychologically and mechanically. Is the timeline for exit

655
00:33:16,080 --> 00:33:19,360
Speaker 4: different for an AI company or an AI adjacent company

656
00:33:19,440 --> 00:33:23,200
Speaker 4: or a native AI company AI native and the type.

657
00:33:22,920 --> 00:33:26,960
Speaker 13: Of exit, Yeah, I would say yes, and I think

658
00:33:27,000 --> 00:33:30,800
Speaker 13: it's faster. So the companies that I've invested in so far.

659
00:33:30,880 --> 00:33:33,520
Speaker 13: As an example in AI, Jasper and deep l are

660
00:33:33,600 --> 00:33:36,040
Speaker 13: two of the fastest growing software companies that I have

661
00:33:36,200 --> 00:33:39,120
Speaker 13: ever seen in twenty eight years, I've seen a lot

662
00:33:39,200 --> 00:33:43,360
Speaker 13: of companies. They're rocket ships the adoption because they solve

663
00:33:43,400 --> 00:33:47,040
Speaker 13: a very real problem for customers. They each have tens

664
00:33:47,120 --> 00:33:51,600
Speaker 13: of thousands of paying business customers already, and so I

665
00:33:51,680 --> 00:33:54,600
Speaker 13: think we'll see exits even faster. I think these are

666
00:33:54,680 --> 00:33:58,080
Speaker 13: IPO worthy companies, and so I think that's kind of

667
00:33:58,160 --> 00:34:00,520
Speaker 13: exits will be the same, but I think they'll be

668
00:34:00,560 --> 00:34:02,160
Speaker 13: even faster than what we've seen in the past.

669
00:34:02,520 --> 00:34:05,520
Speaker 3: What we've seen and you just mentioned crypto, there is

670
00:34:05,920 --> 00:34:08,600
Speaker 3: not only talk of a hype cycle, but also some

671
00:34:09,200 --> 00:34:09,480
Speaker 3: talk of.

672
00:34:09,520 --> 00:34:12,920
Speaker 5: Lack of regulation. How are you seeing round corners.

673
00:34:12,960 --> 00:34:14,919
Speaker 3: I know you said your crystal ball isn't good as others,

674
00:34:14,960 --> 00:34:16,480
Speaker 3: but I'm pretty sure it is because that's why you're

675
00:34:16,480 --> 00:34:19,040
Speaker 3: a VC. What are you for seeing in terms of

676
00:34:19,200 --> 00:34:23,200
Speaker 3: regulatory strain and the race for AI being a certain

677
00:34:23,320 --> 00:34:24,000
Speaker 3: and safe one.

678
00:34:25,320 --> 00:34:28,840
Speaker 13: Yeah, First off, I think the hype around AI is

679
00:34:29,000 --> 00:34:31,160
Speaker 13: under hyped given the impact I think it is going

680
00:34:31,239 --> 00:34:33,600
Speaker 13: to have on the way we work and live in

681
00:34:33,719 --> 00:34:37,880
Speaker 13: terms of the regulation. I would say, in my experience

682
00:34:38,000 --> 00:34:41,520
Speaker 13: in business, it is so uncommon for me to see

683
00:34:41,920 --> 00:34:46,400
Speaker 13: all parties agree that regulation is needed and want to

684
00:34:46,520 --> 00:34:52,160
Speaker 13: collaborate together across policy makers, founders, technologists, etc. And so

685
00:34:52,280 --> 00:34:55,200
Speaker 13: I'm very confident that the industry as a whole is

686
00:34:55,239 --> 00:34:57,880
Speaker 13: going to address that. I think there are some obvious

687
00:34:57,960 --> 00:35:00,919
Speaker 13: and no brainer areas where regular will come into play

688
00:35:00,960 --> 00:35:04,280
Speaker 13: that'll be good for everybody. Where I'm focused is gosh,

689
00:35:04,360 --> 00:35:08,320
Speaker 13: the amazing technical lead forward here can solve things in

690
00:35:08,520 --> 00:35:13,320
Speaker 13: healthcare in industries that I think could be an education

691
00:35:13,600 --> 00:35:16,920
Speaker 13: that can be game changing for us as humans across

692
00:35:16,960 --> 00:35:17,239
Speaker 13: the world.

693
00:35:17,800 --> 00:35:21,440
Speaker 4: Caroline, the humble opinion of Samir de Lakia, partner over

694
00:35:21,520 --> 00:35:23,880
Speaker 4: a best of adventures will called twenty billion dollars to

695
00:35:23,920 --> 00:35:24,239
Speaker 4: play with.

696
00:35:24,880 --> 00:35:35,200
Speaker 3: Yeah, quite phenomenal, don't now for what's going viral uvii

697
00:35:35,600 --> 00:35:38,720
Speaker 3: just raised a hundred million dollars from investors including General Motors,

698
00:35:38,840 --> 00:35:42,560
Speaker 3: CarMax and Look the company is using artificial intelligence for

699
00:35:42,719 --> 00:35:45,879
Speaker 3: vehicle inspections. Please to see with us the person who

700
00:35:45,880 --> 00:35:48,560
Speaker 3: can explain exactly how CEO and co founder Emir Heava,

701
00:35:48,680 --> 00:35:50,120
Speaker 3: it is great to have some time with the Amir

702
00:35:50,800 --> 00:35:53,920
Speaker 3: so I drive in and what automatically you can understand

703
00:35:53,960 --> 00:35:54,920
Speaker 3: what's wrong with my vehicle?

704
00:35:55,000 --> 00:35:55,799
Speaker 5: How is this going to work?

705
00:35:56,040 --> 00:35:59,080
Speaker 10: So exactly? At UVII, it's kind of you can think

706
00:35:59,120 --> 00:36:01,840
Speaker 10: of us like MRI for the vehicle. We have a

707
00:36:01,880 --> 00:36:06,239
Speaker 10: few systems. You simply drive through our systems and then

708
00:36:06,320 --> 00:36:09,160
Speaker 10: we're able within a few seconds to really understand the

709
00:36:09,200 --> 00:36:12,840
Speaker 10: full condition of the vehicle. We're taking images of the tires,

710
00:36:12,960 --> 00:36:16,160
Speaker 10: the undercarriage, the whole exterior. So if you have any leakages,

711
00:36:16,400 --> 00:36:19,360
Speaker 10: any expire tires, any issues that were in tear of

712
00:36:19,480 --> 00:36:22,320
Speaker 10: the tires, were simply able to find out everything.

713
00:36:24,360 --> 00:36:28,920
Speaker 4: Hanneko Ventures led the round, but GM did participate through

714
00:36:28,960 --> 00:36:30,560
Speaker 4: its venture round. I thought we'd use that as a

715
00:36:30,680 --> 00:36:34,320
Speaker 4: sort of case study. Do you do business with General Motors?

716
00:36:34,680 --> 00:36:37,280
Speaker 4: What is it that you actually sell to the auto

717
00:36:37,440 --> 00:36:39,160
Speaker 4: makers or to the service shops.

718
00:36:39,960 --> 00:36:43,360
Speaker 10: So we have quite a few partners. It was published

719
00:36:43,360 --> 00:36:45,520
Speaker 10: that we work with General Motors. We work with them

720
00:36:45,760 --> 00:36:48,720
Speaker 10: on mainly on their dealerships to be able to service

721
00:36:48,800 --> 00:36:51,759
Speaker 10: their customers better. It's really important for us to give

722
00:36:52,080 --> 00:36:55,640
Speaker 10: a better customer experience while someone driving into the dealership,

723
00:36:55,920 --> 00:36:58,719
Speaker 10: exposing kind of the issues and really understand the full

724
00:36:58,760 --> 00:36:59,680
Speaker 10: condition of the vehicle.

725
00:37:00,120 --> 00:37:01,600
Speaker 7: We are working with them on the dealerships.

726
00:37:01,640 --> 00:37:04,920
Speaker 10: But also we have more partners like CarMax, like Volvo,

727
00:37:05,920 --> 00:37:09,080
Speaker 10: like Yundai and Tuta that invested us in the previous round.

728
00:37:09,320 --> 00:37:10,920
Speaker 7: We're also working with them as well.

729
00:37:12,640 --> 00:37:16,239
Speaker 4: Bloomberg reported that the deal valued UVI at around eight

730
00:37:16,360 --> 00:37:19,759
Speaker 4: hundred million dollars. How difficult was that to raise the

731
00:37:19,880 --> 00:37:23,520
Speaker 4: funds in this environment from those partners and I guess

732
00:37:24,160 --> 00:37:28,080
Speaker 4: we wanting to hit unicorn status. I think right now

733
00:37:28,160 --> 00:37:32,920
Speaker 4: we're really focusing on building value. Samir just spoke about

734
00:37:33,040 --> 00:37:35,760
Speaker 4: companies that really needs to approve that they have customers

735
00:37:35,800 --> 00:37:38,080
Speaker 4: who are bringing value to their customers, and this is

736
00:37:38,160 --> 00:37:40,719
Speaker 4: exactly what we are doing. We are working with all

737
00:37:40,719 --> 00:37:43,759
Speaker 4: of our partners, where GM and the others, to make

738
00:37:43,840 --> 00:37:47,800
Speaker 4: sure that our products bring value not only to our customers,

739
00:37:48,000 --> 00:37:49,360
Speaker 4: but also to their customers.

740
00:37:49,640 --> 00:37:51,200
Speaker 7: And this is what is important, and this is.

741
00:37:51,200 --> 00:37:54,640
Speaker 10: Why we were still able to raise fairly a lot

742
00:37:54,680 --> 00:37:58,040
Speaker 10: of money, especially right now, which is slightly harder in

743
00:37:58,200 --> 00:38:02,080
Speaker 10: terms of everything that is going on the economics CARO.

744
00:38:02,520 --> 00:38:06,240
Speaker 4: They describe it as the MRI machine for Vehicle inspection,

745
00:38:06,520 --> 00:38:09,360
Speaker 4: but really this is a story about artificial intelligence.

746
00:38:09,600 --> 00:38:12,920
Speaker 3: Yeah, and I'm interested in to that end, how do

747
00:38:12,960 --> 00:38:17,520
Speaker 3: you actually say that this is an artificially intelligent at its.

748
00:38:17,480 --> 00:38:18,960
Speaker 5: Foundation level company.

749
00:38:19,080 --> 00:38:22,200
Speaker 3: Because you're running it through images, I'm assuming to be

750
00:38:22,239 --> 00:38:23,880
Speaker 3: able to understand whether your tiles are looking good or

751
00:38:23,880 --> 00:38:26,600
Speaker 3: whether other parts. But how do how do you prove

752
00:38:26,719 --> 00:38:28,520
Speaker 3: to the investor base that you haven't just tacked on

753
00:38:28,600 --> 00:38:29,880
Speaker 3: AI to make yourself sexy?

754
00:38:30,520 --> 00:38:34,319
Speaker 10: Right, So basically, what we're showing the investors, how does

755
00:38:34,360 --> 00:38:37,160
Speaker 10: it really work right? How do how do we are

756
00:38:37,239 --> 00:38:40,080
Speaker 10: able to really find all the issues at the vehicle?

757
00:38:40,400 --> 00:38:42,120
Speaker 10: How do things work in the back end. The fact

758
00:38:42,160 --> 00:38:44,520
Speaker 10: that we're able to break the vehicle into the different parts,

759
00:38:44,560 --> 00:38:47,120
Speaker 10: the fact that we're able to find different things really

760
00:38:47,200 --> 00:38:49,719
Speaker 10: really quickly. These are the things that are important to

761
00:38:50,160 --> 00:38:52,920
Speaker 10: our investors to make sure we have a really strong

762
00:38:53,040 --> 00:38:56,839
Speaker 10: foundation off models and AI based models. They can really

763
00:38:56,920 --> 00:39:00,080
Speaker 10: work for every vehicle, every type of vehicle, vehicle, and

764
00:39:00,160 --> 00:39:02,800
Speaker 10: any condition of the vehicle that we're seeing. And this

765
00:39:02,960 --> 00:39:04,600
Speaker 10: is kind of why it's really important and kind of

766
00:39:04,640 --> 00:39:09,319
Speaker 10: the strength of your AI because it really helps us

767
00:39:09,400 --> 00:39:13,040
Speaker 10: to even support things we haven't seen before. So if

768
00:39:13,080 --> 00:39:15,600
Speaker 10: there's a new vehicle we haven't seen it before, we're

769
00:39:15,640 --> 00:39:18,560
Speaker 10: still able to find most of the damages on that vehicle,

770
00:39:19,120 --> 00:39:22,560
Speaker 10: even when we didn't see the specific type or model

771
00:39:22,640 --> 00:39:23,240
Speaker 10: off the vehicle.

772
00:39:23,560 --> 00:39:25,640
Speaker 7: And that's kind of the strength of what we're building.

773
00:39:26,120 --> 00:39:29,759
Speaker 3: V I faced Nehir. Well, you're in Jersey, right, you

774
00:39:29,840 --> 00:39:32,080
Speaker 3: came from Israel. Where is your tech talent at the

775
00:39:32,160 --> 00:39:32,719
Speaker 3: moment for this?

776
00:39:33,120 --> 00:39:35,640
Speaker 10: So both here and here in Jersey we have offices

777
00:39:35,719 --> 00:39:39,920
Speaker 10: both in in Jersey but also in Ohio, and we

778
00:39:40,160 --> 00:39:44,480
Speaker 10: also have an office in Israel. We also have offices

779
00:39:44,520 --> 00:39:46,200
Speaker 10: in Germany and the UK.

780
00:39:47,400 --> 00:39:50,160
Speaker 4: Very quick and where will you build and manufactured the

781
00:39:50,280 --> 00:39:51,600
Speaker 4: systems here in North America?

782
00:39:51,719 --> 00:39:57,080
Speaker 10: Where so we're now manufacturing here in Indianapolis and that

783
00:39:57,880 --> 00:40:01,080
Speaker 10: help us to scale a lot quicker and to share

784
00:40:01,239 --> 00:40:02,680
Speaker 10: more systems to our customers.

785
00:40:03,640 --> 00:40:05,960
Speaker 4: All right, Oh, thanks to mere Hava, the CEO and

786
00:40:06,080 --> 00:40:07,880
Speaker 4: co founder of uv I.

787
00:40:08,560 --> 00:40:09,319
Speaker 7: Thank you very much.

788
00:40:10,200 --> 00:40:13,200
Speaker 4: That does it for this edition of Bloomberg Technology. Stay

789
00:40:13,239 --> 00:40:16,799
Speaker 4: with Bloomberg Television because we're speaking to the Nicola CEO,

790
00:40:16,920 --> 00:40:19,200
Speaker 4: Carol Michael Loscheller who's coming up with me and Matt

791
00:40:19,280 --> 00:40:22,239
Speaker 4: Miller and John. I meant in the next hour here

792
00:40:22,280 --> 00:40:24,560
Speaker 4: on Bloomberg TV to.

793
00:40:24,960 --> 00:40:27,400
Speaker 3: Power people that love all things autos. Sitting down with

794
00:40:27,480 --> 00:40:30,440
Speaker 3: Michael Mimmile. Do not forget to check out our podcast.

795
00:40:30,600 --> 00:40:32,560
Speaker 3: You can find it all on the terminal. You can

796
00:40:32,600 --> 00:40:35,120
Speaker 3: be online on Apple, Spotify, iHeart, wherever you like to

797
00:40:35,160 --> 00:40:36,000
Speaker 3: consume your audio.

798
00:40:36,120 --> 00:40:37,440
Speaker 5: Come do it with us and.

799
00:40:37,520 --> 00:40:40,000
Speaker 3: Get your AI fixed, because boy, are we focused on

800
00:40:40,080 --> 00:40:40,600
Speaker 3: it at the moment.

801
00:40:40,680 --> 00:40:43,040
Speaker 5: From New York. From San Francisco, this is a Bloomberg