WEBVTT - Instacart IPO Pricing and Klaviyo to Go Public

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<v Speaker 1>From Marhart where Innovation, Money and Power Collie in Silicon Valley, NBN.

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<v Speaker 2>This is Bloomberg Technology with Caroline Hide and Ed Ludlow.

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<v Speaker 3>Live from Bloomberg's World headquarters in New York. I'm Caroline High.

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<v Speaker 4>And Amed Ludlow reunited in New York City. This is

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<v Speaker 4>Blueboy Technology.

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<v Speaker 5>Coming our full IPO coverage.

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<v Speaker 3>You have Instacart pricing tonight as Clavio prepares to go

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<v Speaker 3>public this week as well.

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<v Speaker 5>Will bring you everything you need to know, and we'll get.

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<v Speaker 4>The inside look into the digital asset industry with Boxchain Capital.

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<v Speaker 4>As the VC firm announces it's raise five hundred and

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<v Speaker 4>eighty million dollars for new funds.

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<v Speaker 3>Prus AI startup writer it raises one hundred million dollars

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<v Speaker 3>to further grow its business.

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<v Speaker 5>We'll have an exclusive conversation with the CEO.

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<v Speaker 3>It is an ip week. The New York Stock Exchange

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<v Speaker 3>and now ZAC are going to be busy. Let's think

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<v Speaker 3>about Instacart first and foremost, because it's finally set to

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<v Speaker 3>take that plunge into public markets, pricing later today, training tomorrow,

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<v Speaker 3>joining us now as Bloomberg's Katie Roofin. It's kind of

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<v Speaker 3>interesting timing. We don't often see IPOs price on a Monday.

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<v Speaker 6>Right, Yeah, it's it's kind of unusual. Usually they debut Wednesday, Thursday, Friday,

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<v Speaker 6>and they praise the night before, so big ones. Yeah,

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<v Speaker 6>not typically on pricing Monday night, but hey why not?

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<v Speaker 5>Why not? Officially?

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<v Speaker 3>Maple Bear Inc. Is of course the name overall.

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<v Speaker 5>Oh dear, we just have some people walking in front

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<v Speaker 5>of the camera. It's Monday madness.

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<v Speaker 3>We're new to this particular studio at the moment, But

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<v Speaker 3>I'm interested in what you think. Ultimately, this is a

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<v Speaker 3>test of there's a test of interest for tech assets

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<v Speaker 3>at this moment.

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<v Speaker 5>But is it a test of kind of the pivot.

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<v Speaker 3>That CEO FGMO has made to focus more on sort

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<v Speaker 3>of an e commerce bellweather player.

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<v Speaker 5>Not just of course delivery.

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<v Speaker 6>Sure, yeah, I mean the market's looking at a lot

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<v Speaker 6>of different things here.

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<v Speaker 5>I mean, first of.

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<v Speaker 6>All, I think it's a big test of whether the

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<v Speaker 6>market cares more about profitability or growth. There's been so

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<v Speaker 6>much that's been said about why all these tech stocks

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<v Speaker 6>went down in the last few years, and a lot

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<v Speaker 6>of people are under the impression that public investors, public

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<v Speaker 6>tech investors care more about the rate of growth than

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<v Speaker 6>they did. They cared more about the rate of growth

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<v Speaker 6>before and now they care about profitability. So instacar has

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<v Speaker 6>a slowed rate of growth, but they've focused on being

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<v Speaker 6>profitable and they've been focusing on new business segments.

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<v Speaker 5>Remind us who's set to benefit. Who are the vcs

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<v Speaker 5>that back to curly so Sequoia.

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<v Speaker 6>Back to early and a lot has been said. You

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<v Speaker 6>know that there have been vcs that invested at a

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<v Speaker 6>thirty nine billion dollar valuation and that the top of

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<v Speaker 6>the range instacart might just be ten billion dollars. But

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<v Speaker 6>you know, i'd keep in mind that Sequoia invested maybe.

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<v Speaker 5>Around a dollar a share.

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<v Speaker 6>A lot of venture firms invested early, so I would

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<v Speaker 6>say the average cost per share was going to be

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<v Speaker 6>meaningful for a lot of vcs. There are some venture

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<v Speaker 6>firms that, you know, maybe invested too much at the

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<v Speaker 6>pre IPO stage. Actually a lot of them are like

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<v Speaker 6>crossover investors, like hedge funds like d One, although they

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<v Speaker 6>had invested in several rounds prior to the thirty nine

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<v Speaker 6>billion dollar evaluation as well. So yeah, there are some

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<v Speaker 6>investors that will be underwater.

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<v Speaker 3>Okay, we've branking it down for us. We thank you

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<v Speaker 3>and look, it's not the only IPO ed.

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<v Speaker 4>Yeah, yeah, look, I'm not making it up. It is

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<v Speaker 4>a mad Monday. Let's keep the IPO conversation going. Marketing

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<v Speaker 4>and data automation provider clavey O gears up for its

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<v Speaker 4>IPO joining us. Now is the man you saw run

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<v Speaker 4>across set. I've never met anyone as keen to break

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<v Speaker 4>news as Bloomberg's Ryan Gord, who's only a few weeks

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<v Speaker 4>into his time in the Bloomberg newsroom.

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<v Speaker 7>Clavio. Interesting.

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<v Speaker 4>Let's respectfully say that the names we waited for, it

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<v Speaker 4>was the less talked about. But what's going to happen

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<v Speaker 4>in the next twenty four hours or so?

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<v Speaker 8>Yeah? Do you know what's interesting? I think is that

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<v Speaker 8>you say was the one that was less talked about.

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<v Speaker 8>But actually, if you look on paper and think about

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<v Speaker 8>you know, size and profile, Instacard is very similar to Clavier.

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<v Speaker 8>They're both you know, pushing a nine billion dollar valuation.

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<v Speaker 8>Clavier has followed Instacart's lead. Just yesterday we reported that

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<v Speaker 8>they were looking to boost the IPO price range two

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<v Speaker 8>dollars either side of the bottom and top end, So

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<v Speaker 8>they're now pushing a twenty seven to twenty nine price range.

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<v Speaker 8>The SEC finning came out this morning, and I think,

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<v Speaker 8>you know, this just confirms what we what we learned

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<v Speaker 8>last week that you know, this is still a pretty

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<v Speaker 8>tentative time for markets, but you know there's been a

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<v Speaker 8>shot in the arm, so to speak for you know,

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<v Speaker 8>companies who are perhaps thinking, all right, we've got you know,

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<v Speaker 8>a good amount sort of backed up by cornerstones, both

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<v Speaker 8>in instacarts and Klavio's case, and so you know, let's

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<v Speaker 8>play it safe, let's play it smart. And they know

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<v Speaker 8>they're they're put they're pushing that they're going to raise,

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<v Speaker 8>they're raising their range.

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<v Speaker 7>Give me some of their names behind Clavier.

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<v Speaker 4>Some of the existing back is in which banks are

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<v Speaker 4>going to help us take this company public.

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<v Speaker 8>Yeah, so partners is behind Clavio. And actually eleven percent

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<v Speaker 8>of Clavio's revenue comes from Shopify. And you know, I

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<v Speaker 8>think when you start thinking about, you know, how does

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<v Speaker 8>the consumer respond, you know, what's the sort of retail appetite,

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<v Speaker 8>it's pretty interesting to think about the insights that these

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<v Speaker 8>these these guys are sort of giving us across the spectrum.

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<v Speaker 8>But I think, you know, I would caution and say

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<v Speaker 8>that Clavio and instagart are very different businesses. I think

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<v Speaker 8>it's probably good not to draw too many comparisons, but

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<v Speaker 8>you know, come come tomorrow, we would have had both,

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<v Speaker 8>you know, instacart pricing today, trading tomorrow, and then Clavio

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<v Speaker 8>pricing tomorrow afternoon too for trading on Wednesday.

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<v Speaker 3>There are some similar larities across all the IPOs of

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<v Speaker 3>having some cornerstone investors involved. But focus on the difference

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<v Speaker 3>for a minute. What is a marketing and data automation provider?

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<v Speaker 3>What what is Clavio up to from a business model perspective.

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<v Speaker 8>Yeah, I mean, you know, it's really getting down and

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<v Speaker 8>down into the weeds as to what people want to

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<v Speaker 8>or what they think people are interested in. How they

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<v Speaker 8>can better vie that those insights to those who are

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<v Speaker 8>ultimately looking to.

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<v Speaker 7>Make the most the most money.

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<v Speaker 8>You know, I think when you think about Instacart, it's

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<v Speaker 8>you know, grocery delivery. How do you provide them with

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<v Speaker 8>the best insights into what people are wanting to give

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<v Speaker 8>a moment And you know, I think even outside of

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<v Speaker 8>the IPO, you know IPO candidates, there are even quite

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<v Speaker 8>a few companies on the on the sort of strict

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<v Speaker 8>MNA side who are you know, exploring options so to

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<v Speaker 8>speak for businesses that are exposed to marketing, data, information services,

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<v Speaker 8>insights across the piece.

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<v Speaker 5>We're making us.

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<v Speaker 3>Buy the right thing at the right time. You need

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<v Speaker 3>data that wrangled, Thank you very much. Indeed, all things IPOs. Meanwhile,

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<v Speaker 3>coming out, we'll talk look.

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<v Speaker 5>A bit more about the world of crypto to digital assets.

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<v Speaker 3>There's some fundraising going on friends, block Chain Capital General

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<v Speaker 3>Partners to go that his firms just raise five h

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<v Speaker 3>eighty million dollars in some fresh funds. We'll get into

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<v Speaker 3>it as a remote technology Chinese fintech joint and I

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<v Speaker 3>was planning to unwind its investment in A and T Capital,

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<v Speaker 3>pulling back from one hundred million dollar fund there was

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<v Speaker 3>actually central to it's bet on digital assets. Anti Capital

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<v Speaker 3>is losing one of its biggest financial backers. It seems

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<v Speaker 3>unclear if actually the bench firm will continue to operate

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<v Speaker 3>or well snag a new key investor. But meanwhile, bucking

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<v Speaker 3>that particular trend and the down rounds and concerns about crypto,

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<v Speaker 3>we've got crypto focused Blockchain Capital joining us, who's actually

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<v Speaker 3>raise funds five and eighteen million dollars of them cost

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<v Speaker 3>two new funds. We understand one of the biggest raises

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<v Speaker 3>for the asset class this year, not just ever for

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<v Speaker 3>the bench firm in its tenure history. So please to

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<v Speaker 3>welcome to the show. Spenzer Boga Blockchain Capital General Partner,

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<v Speaker 3>and are you bucking a trend or is there more interest,

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<v Speaker 3>more LP interest in coming into crypto.

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<v Speaker 9>There's certainly plenty of LP interests.

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<v Speaker 10>Listen, we're doing what we've always done, which is continue

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<v Speaker 10>to double down on the industry.

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<v Speaker 9>That we have long term conviction in.

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<v Speaker 10>The middle of a bear market, and so we're looking

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<v Speaker 10>forward to to deploy this capital into some fresh opportunities.

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<v Speaker 3>Okay, so talk about the fresh opportunities. Where in the

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<v Speaker 3>space do you think that valuations aren't elevated, that people

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<v Speaker 3>are really proving some disruption in this moment.

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<v Speaker 10>Sure, so we see opportunities at both the early stage

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<v Speaker 10>and the later stage.

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<v Speaker 9>You know, if we go back to twenty twenty to

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<v Speaker 9>twenty twenty two, I'd.

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<v Speaker 10>Say that the industry was mostly characterized by an influx

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<v Speaker 10>of new large allocators that were deploying very large sums

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<v Speaker 10>of capital to the mid and late stage segment.

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<v Speaker 9>Of the market.

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<v Speaker 10>All of those capital allocators have walked off the playing field.

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<v Speaker 9>Right, they're no longer active in the industry. But meanwhile,

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<v Speaker 9>during this.

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<v Speaker 10>Last kind of market cycle that we saw from twenty

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<v Speaker 10>twenty to twenty twenty two, we did have a lot

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<v Speaker 10>of early stage companies that were funded, and a few

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<v Speaker 10>of those are growing up into that kind of mid

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<v Speaker 10>stage of the market.

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<v Speaker 9>And that's what we're keeping a close eye on.

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<v Speaker 4>Because I just want to check some of the mechanics

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<v Speaker 4>with you, because you guys already had two billion dollars

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<v Speaker 4>of assets, right, is it that that capito had already

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<v Speaker 4>been committed and now you're bringing new funds because you've

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<v Speaker 4>got opportunities to write new checks.

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<v Speaker 10>Correct, So our assets under management grew to two billion

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<v Speaker 10>over the past decade that we've been doing this. So

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<v Speaker 10>we're now to pointing capital out of our sixth to

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<v Speaker 10>early stage fund and again our first opportunity fund, so

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<v Speaker 10>that's doing Series B in later.

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<v Speaker 9>Okay, so that two billion came from the prior five funds.

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<v Speaker 4>The focus decentralized finance and gaming. Just explain how the

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<v Speaker 4>focus of the sort of target startups changed.

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<v Speaker 7>Then with this new fund.

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<v Speaker 10>You know, it continues to cover a lot of the

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<v Speaker 10>opportunities in the space, but I'd say early on in

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<v Speaker 10>our first fund vintages, we're really focused on, if you

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<v Speaker 10>think from a sequencing perspective, which opportunities.

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<v Speaker 9>Need to work first.

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<v Speaker 10>And that's largely thinking about things that we broadly bucket

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<v Speaker 10>under centralized finance.

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<v Speaker 9>So these are largely on ramps right and off ramps.

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<v Speaker 10>So it's things like coinbase and crack and bitco anchorage,

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<v Speaker 10>you know, the largest exchanges and custodians, because nothing else

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<v Speaker 10>can really work unless you have robust, reliable on ramps

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<v Speaker 10>and off ranks.

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<v Speaker 9>Now, over time we've blended and moved.

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<v Speaker 10>More towards the I characterized them maybe as more crypto

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<v Speaker 10>native opportunities. So these are things like decentralized infrastructure, decentralized finance,

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<v Speaker 10>and then especially gaming has been on the horizon for

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<v Speaker 10>the past couple of years and we've made a select

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<v Speaker 10>few investments in that category.

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<v Speaker 3>I'm just interested in aside from the investments you're making.

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<v Speaker 5>You had an interesting ton of phrase.

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<v Speaker 3>You said, these big players who are adding big checks

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<v Speaker 3>have walked off the field. I mean a systems still

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<v Speaker 3>out there with a massive crypto fund. I think a

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<v Speaker 3>Katie Hahn. I mean these players are not writing checks

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<v Speaker 3>at the moment, Are they not deploying the capital they raised?

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<v Speaker 10>No, those are not the large allocators that I'm thinking of.

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<v Speaker 10>So I think most of the crypto native investors have

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<v Speaker 10>stayed true to the industry and continue to deploy capital.

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<v Speaker 10>The ones that I'm thinking about are more of the

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<v Speaker 10>large late stage private equity or hedge funds even that

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<v Speaker 10>were building some pockets of illquid private investments. Several of

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<v Speaker 10>them kind of came in and they said, listen, we

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<v Speaker 10>have zero percent exposure to this sector.

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<v Speaker 9>We'd like to get it up to ten percent in

0:11:04.480 --> 0:11:07.360
<v Speaker 9>a twelve month period. And naturally that.

0:11:07.720 --> 0:11:12.960
<v Speaker 10>Resulted in clearing prices that were above and beyond our appetite.

0:11:12.400 --> 0:11:15.640
<v Speaker 11>That has though been still this potion pull, this tension

0:11:15.920 --> 0:11:19.440
<v Speaker 11>of institutional appetite when we think about more broadly a

0:11:19.480 --> 0:11:23.480
<v Speaker 11>spot etf for bitcoin, but then at the same time

0:11:23.600 --> 0:11:27.000
<v Speaker 11>nervousness from institutional money, from all the guard money because

0:11:27.040 --> 0:11:29.480
<v Speaker 11>of ultimately regulation, particularly here in the US.

0:11:29.520 --> 0:11:29.959
<v Speaker 5>How is that.

0:11:29.960 --> 0:11:33.839
<v Speaker 3>Affecting startups, founders, the companies that are managing to scale

0:11:33.840 --> 0:11:34.319
<v Speaker 3>at the moment.

0:11:35.440 --> 0:11:38.640
<v Speaker 10>Look, I think across whether it's the large institutional allocators

0:11:38.640 --> 0:11:40.760
<v Speaker 10>that are looking at the space or its early stage

0:11:40.760 --> 0:11:42.960
<v Speaker 10>startup founders. I think they're looking at the same thing,

0:11:43.360 --> 0:11:46.080
<v Speaker 10>which is the actual metrics on the ground.

0:11:46.480 --> 0:11:48.679
<v Speaker 9>So, yes, it is a bear market. Yes it's a

0:11:48.720 --> 0:11:51.080
<v Speaker 9>so called crypto winter and the industry speak.

0:11:51.440 --> 0:11:52.880
<v Speaker 10>But if you look at the numbers on the ground,

0:11:52.880 --> 0:11:56.880
<v Speaker 10>we've seen stable coins process over six trillion dollars of

0:11:56.960 --> 0:12:00.520
<v Speaker 10>volume in the past twelve months alone, and that's accounting

0:12:00.559 --> 0:12:03.760
<v Speaker 10>only for transactions in the Ethereum network. If we expanded,

0:12:04.040 --> 0:12:06.880
<v Speaker 10>it'd probably be closer to nine or ten trillion. That's

0:12:06.920 --> 0:12:10.440
<v Speaker 10>just stable coins. Within DeFi, We've got seven hundred million

0:12:10.520 --> 0:12:14.880
<v Speaker 10>dollars of protocol revenue that's been generated by these DeFi applications.

0:12:15.480 --> 0:12:19.400
<v Speaker 10>We've got seven hundred billion dollars of volume going across

0:12:19.440 --> 0:12:23.280
<v Speaker 10>decentralized exchanges in the past twelve months. All of which

0:12:23.320 --> 0:12:25.520
<v Speaker 10>is to say that actually, on the ground, there's a

0:12:25.520 --> 0:12:28.040
<v Speaker 10>lot of healthy things happening. It is not the way

0:12:28.040 --> 0:12:30.000
<v Speaker 10>that I think most people perceive it that in these

0:12:30.240 --> 0:12:33.800
<v Speaker 10>bear markets or crypto winters, that activity just disappears.

0:12:33.480 --> 0:12:35.560
<v Speaker 4>Suspends it a little quickly about gaming, and when I think

0:12:35.640 --> 0:12:39.880
<v Speaker 4>about the use of blockchaining gaming, it's about monetizing right

0:12:39.920 --> 0:12:44.440
<v Speaker 4>in game customization, skins, character shares. Is it limited to

0:12:44.520 --> 0:12:48.320
<v Speaker 4>that though the opportunities you see so no, it's.

0:12:48.200 --> 0:12:51.199
<v Speaker 9>Not limited to that. I would largely characterize the opportunity.

0:12:50.679 --> 0:12:53.040
<v Speaker 10>In gaming is the same as most of the applications

0:12:53.040 --> 0:12:55.840
<v Speaker 10>of blockchain technology, which is to put users at the

0:12:55.880 --> 0:12:57.760
<v Speaker 10>center and to disintermediate some of.

0:12:57.679 --> 0:12:59.240
<v Speaker 9>The economics associated with it.

0:12:59.880 --> 0:13:02.400
<v Speaker 10>The case of gaming, we have, you know, tens of

0:13:02.440 --> 0:13:05.760
<v Speaker 10>millions of people around the world that invest maybe dozens

0:13:05.800 --> 0:13:08.880
<v Speaker 10>or not hundreds of hours a week into acquiring.

0:13:08.440 --> 0:13:09.400
<v Speaker 9>In game assets.

0:13:10.120 --> 0:13:12.080
<v Speaker 10>They spend their time, they spend their money to acquire

0:13:12.120 --> 0:13:14.520
<v Speaker 10>these assets, and the promise from a lot of these

0:13:14.520 --> 0:13:17.720
<v Speaker 10>blockchain startups is that within a gaming context, they can

0:13:17.760 --> 0:13:21.160
<v Speaker 10>give users actual ownership of these assets in the same

0:13:21.160 --> 0:13:22.960
<v Speaker 10>way that they would in the real world or the

0:13:22.960 --> 0:13:23.640
<v Speaker 10>physical world.

0:13:24.240 --> 0:13:27.040
<v Speaker 4>Spencer Bogot Blockchain Capital always good to catch up and

0:13:27.120 --> 0:13:33.199
<v Speaker 4>have you on the shape.

0:13:35.920 --> 0:13:37.400
<v Speaker 7>Time for talking tech and first up.

0:13:37.440 --> 0:13:40.160
<v Speaker 4>Bob van Dyke, CEO of Process, is stepping down from

0:13:40.160 --> 0:13:42.680
<v Speaker 4>his role is head of the tech investment firm Vendi.

0:13:43.040 --> 0:13:45.240
<v Speaker 4>Will remain as a consultant to the board and its

0:13:45.280 --> 0:13:48.840
<v Speaker 4>parently company, Naspers until the end of September twenty twenty four.

0:13:49.120 --> 0:13:52.360
<v Speaker 4>His departure comes after a complicated shareholder structure that was

0:13:52.480 --> 0:13:56.360
<v Speaker 4>highly criticized by some investors and government regulators, and Ali

0:13:56.400 --> 0:13:59.680
<v Speaker 4>Baba's unveiling plans to beef up its investments in Turkey.

0:14:00.120 --> 0:14:03.320
<v Speaker 4>A meeting Friday with Turkey's President Erdawan, the Chinese internet

0:14:03.360 --> 0:14:06.880
<v Speaker 4>company pledged two billion dollars. Ali Baba has already invested

0:14:06.920 --> 0:14:10.640
<v Speaker 4>over one billion dollars through its Turkish unit, Trendill, Turkey's

0:14:10.640 --> 0:14:14.720
<v Speaker 4>biggest e commerce platform. Plus investment firm KKR has agreed

0:14:14.720 --> 0:14:18.559
<v Speaker 4>to buy twenty percent of Singapore Telecommunications Regional Data Center

0:14:18.600 --> 0:14:22.080
<v Speaker 4>business for more than eight hundred million US Singapore's largest

0:14:22.080 --> 0:14:25.720
<v Speaker 4>telecoms provider. We use the capitol to bankroll in expansion

0:14:25.960 --> 0:14:28.760
<v Speaker 4>across Southeast age to The deal also allows KKR to

0:14:28.800 --> 0:14:31.560
<v Speaker 4>take up to two seats on the unit's board, further

0:14:31.600 --> 0:14:34.320
<v Speaker 4>expanding its rees into the server and networks that power

0:14:34.600 --> 0:14:37.920
<v Speaker 4>the Internet. Now, speaking of investing, ours, official intelligence startup

0:14:38.000 --> 0:14:41.320
<v Speaker 4>Writer is planning to invest more in its AI models.

0:14:41.320 --> 0:14:44.120
<v Speaker 4>Writers raised one hundred million dollars in a Series B round,

0:14:44.320 --> 0:14:47.120
<v Speaker 4>the round valuing the company at more than five hundred

0:14:47.320 --> 0:14:51.160
<v Speaker 4>million dollars, joining US now from San Francisco. Writers CEO

0:14:51.280 --> 0:14:54.800
<v Speaker 4>and co founder may have been been may very simple

0:14:54.880 --> 0:14:56.920
<v Speaker 4>question to start for it start with what do you

0:14:57.000 --> 0:14:57.920
<v Speaker 4>use those funds for?

0:14:58.800 --> 0:14:59.000
<v Speaker 7>Oh?

0:14:59.080 --> 0:15:01.560
<v Speaker 12>Thanks so much, Ed, great to be here. While we're

0:15:01.760 --> 0:15:05.000
<v Speaker 12>using the funds to further invest in our large language

0:15:05.000 --> 0:15:10.480
<v Speaker 12>model technologies and our full stack generative AI platform. Enterprises

0:15:10.560 --> 0:15:13.120
<v Speaker 12>are ready to move from you know, all the talk

0:15:13.160 --> 0:15:16.920
<v Speaker 12>of the promise of generative AI to real impactful applications

0:15:16.960 --> 0:15:19.120
<v Speaker 12>they can put into production. And we're going to keep

0:15:19.160 --> 0:15:20.600
<v Speaker 12>beefing up our platform to do that.

0:15:21.400 --> 0:15:24.520
<v Speaker 3>Talk about real impactful revenue for you as well, because

0:15:24.520 --> 0:15:28.320
<v Speaker 3>there is so much optimism, dare I say hype around

0:15:28.400 --> 0:15:29.960
<v Speaker 3>how much revenue this is going to bring in for

0:15:30.040 --> 0:15:31.480
<v Speaker 3>the key public companies already?

0:15:31.520 --> 0:15:33.440
<v Speaker 5>What about you? What are you seeing in times of growth?

0:15:34.280 --> 0:15:34.480
<v Speaker 8>Oh?

0:15:34.480 --> 0:15:37.160
<v Speaker 12>Thanks so much, Caroline. So we are four x, you

0:15:37.200 --> 0:15:39.880
<v Speaker 12>know since the beginning of the year, so absolutely an

0:15:39.880 --> 0:15:43.080
<v Speaker 12>influx of folks who you know, have gotten their hands

0:15:43.080 --> 0:15:45.560
<v Speaker 12>already working with large language models, but are kind of

0:15:45.560 --> 0:15:49.200
<v Speaker 12>stuck in poc purgatar, you know, proofs of concepts that

0:15:49.320 --> 0:15:51.880
<v Speaker 12>don't make it to production. And so we succeed and

0:15:51.920 --> 0:15:55.160
<v Speaker 12>our customers succeed when we can really help them realize

0:15:55.160 --> 0:15:59.600
<v Speaker 12>that promise building applications that people actually use that involve

0:15:59.720 --> 0:16:03.240
<v Speaker 12>you know, their data and are secure and their environments.

0:16:03.000 --> 0:16:08.120
<v Speaker 3>And their employees becoming ultimately more productive. May this comes

0:16:08.160 --> 0:16:11.560
<v Speaker 3>at a tough time, doesn't it, just from the mentality

0:16:11.600 --> 0:16:13.960
<v Speaker 3>of yes's productivity to be had. But boy, or we

0:16:14.040 --> 0:16:17.560
<v Speaker 3>worried about the dislocation, the disruption it caused for labor

0:16:17.600 --> 0:16:19.680
<v Speaker 3>in particularly, I'm thinking the strikes happening over on the

0:16:19.680 --> 0:16:22.240
<v Speaker 3>West coast down here on the East coast for writers,

0:16:22.240 --> 0:16:24.720
<v Speaker 3>for actors AI as a worry there. How much are

0:16:24.760 --> 0:16:28.040
<v Speaker 3>you thinking you might end up displacing workers.

0:16:28.880 --> 0:16:31.320
<v Speaker 12>Yeah, it was a big concern of a lot of

0:16:31.320 --> 0:16:34.000
<v Speaker 12>the executives that you know took a chance on us

0:16:34.040 --> 0:16:38.400
<v Speaker 12>and executives who have joined this round, customers like Vanguard

0:16:38.440 --> 0:16:42.160
<v Speaker 12>and Loreal and Eccentria, And you know, those executives aren't

0:16:42.360 --> 0:16:46.000
<v Speaker 12>there promoting AI to displace jobs at all. We're really

0:16:46.040 --> 0:16:48.880
<v Speaker 12>all in concert to help transform work, to make it

0:16:48.960 --> 0:16:53.400
<v Speaker 12>more creative, more interesting, and really take away the kind

0:16:53.400 --> 0:16:56.720
<v Speaker 12>of cognitive manual labor in a lot of these workflows.

0:16:56.760 --> 0:16:59.000
<v Speaker 12>So you know, I would say we're quite different in

0:16:59.000 --> 0:17:01.760
<v Speaker 12>that regard in the way that writer is use case

0:17:01.840 --> 0:17:04.960
<v Speaker 12>based and workflow based people are the heart of making

0:17:05.000 --> 0:17:06.119
<v Speaker 12>generative AI work.

0:17:06.400 --> 0:17:08.720
<v Speaker 4>May you've got that access to capital, but I think

0:17:08.720 --> 0:17:11.040
<v Speaker 4>I'm right saying you're also in the h one hundred club,

0:17:11.440 --> 0:17:15.040
<v Speaker 4>aren't you. How important is it to have that compute

0:17:15.080 --> 0:17:17.120
<v Speaker 4>access you have a cluster in the thousands.

0:17:17.200 --> 0:17:19.800
<v Speaker 7>I think I'm right in saying so.

0:17:20.000 --> 0:17:22.639
<v Speaker 12>Nvidia is a close partner. They're a customer of Writer

0:17:22.800 --> 0:17:25.239
<v Speaker 12>as well. You know, we really wouldn't be where we

0:17:25.280 --> 0:17:28.080
<v Speaker 12>are if we didn't have that partnership. And I think,

0:17:28.080 --> 0:17:32.200
<v Speaker 12>you know, very importantly a philosophy of smaller models are

0:17:32.200 --> 0:17:35.000
<v Speaker 12>more agile, they're easier to manage, they're easier for our

0:17:35.000 --> 0:17:38.280
<v Speaker 12>customers to put in their virtual private clouds. And you know,

0:17:38.400 --> 0:17:39.840
<v Speaker 12>bigger isn't always better.

0:17:40.920 --> 0:17:43.240
<v Speaker 4>That is a good point you raised, Caroline, and I

0:17:43.240 --> 0:17:46.560
<v Speaker 4>have covered a lot of these raises foundation models that

0:17:46.600 --> 0:17:50.760
<v Speaker 4>are raising increments of hundreds of millions and at high valuation.

0:17:50.960 --> 0:17:54.199
<v Speaker 4>And do you worry about the sort of hype around it?

0:17:54.240 --> 0:17:57.280
<v Speaker 4>Do you think that your own valuation was fair in

0:17:57.320 --> 0:17:59.200
<v Speaker 4>this round in terms of your potential?

0:18:00.440 --> 0:18:04.000
<v Speaker 12>Yeah, Ed, we could have done this at a billion's evaluation,

0:18:04.119 --> 0:18:06.480
<v Speaker 12>which I think is absolutely absurd. I think some of

0:18:06.520 --> 0:18:10.400
<v Speaker 12>what is happening is not good for the industry. We

0:18:10.440 --> 0:18:17.040
<v Speaker 12>want you know, unhyped use cases. We want unhyped you know, transformations, augmentations.

0:18:17.119 --> 0:18:20.239
<v Speaker 12>You know, the real use cases here are when you

0:18:20.280 --> 0:18:23.600
<v Speaker 12>put people in AI together and I think of over

0:18:23.720 --> 0:18:27.400
<v Speaker 12>focus on the large language models, the size of them,

0:18:27.520 --> 0:18:30.840
<v Speaker 12>the you know, valuations of the companies. It's really distracting

0:18:30.920 --> 0:18:32.320
<v Speaker 12>from actually getting valued.

0:18:32.600 --> 0:18:35.400
<v Speaker 5>What about the way in which that built, that constructed.

0:18:35.480 --> 0:18:37.800
<v Speaker 3>May we come off a week where a lot of

0:18:37.880 --> 0:18:41.200
<v Speaker 3>ke CEOs thought leaders were out there in Washington thinking

0:18:41.200 --> 0:18:43.960
<v Speaker 3>about future regulation. How do you think about your role

0:18:44.320 --> 0:18:44.879
<v Speaker 3>informing that.

0:18:45.800 --> 0:18:49.000
<v Speaker 12>Yeah, well we already get RFPs that ask us about

0:18:49.000 --> 0:18:51.960
<v Speaker 12>the EU AI Act, Caroline, and it's not even law yet,

0:18:52.280 --> 0:18:54.399
<v Speaker 12>and so you know, we are enterprise first.

0:18:54.560 --> 0:18:55.280
<v Speaker 5>Bottoms up.

0:18:55.320 --> 0:18:59.760
<v Speaker 12>We've built for customers being able to audit our training

0:19:00.520 --> 0:19:03.359
<v Speaker 12>and really look at you know, if there is copyrighted

0:19:03.400 --> 0:19:06.560
<v Speaker 12>information in there, there isn't. I think the companies that

0:19:06.680 --> 0:19:09.960
<v Speaker 12>really make it in the enterprise have to think about

0:19:09.960 --> 0:19:13.240
<v Speaker 12>a world where regulation is here, and it's here pretty globally,

0:19:13.600 --> 0:19:14.359
<v Speaker 12>not just in Europe.

0:19:14.600 --> 0:19:17.199
<v Speaker 4>May really quickly what kind of roles are priority for

0:19:17.280 --> 0:19:17.840
<v Speaker 4>you to hire?

0:19:17.880 --> 0:19:19.200
<v Speaker 7>What kind of people do you need?

0:19:20.640 --> 0:19:23.680
<v Speaker 12>Ed literally everything. If you're in tech and you want

0:19:23.680 --> 0:19:25.800
<v Speaker 12>to work in AI, please email me.

0:19:27.520 --> 0:19:29.760
<v Speaker 3>Well, we won't ask you to give us your email

0:19:29.800 --> 0:19:31.879
<v Speaker 3>address on live television, but maybe you can go to

0:19:32.080 --> 0:19:33.680
<v Speaker 3>your Twitter and social media accounts.

0:19:33.680 --> 0:19:34.400
<v Speaker 5>We thank you so much.

0:19:34.440 --> 0:19:36.679
<v Speaker 3>May it be great to have you on today on

0:19:36.720 --> 0:19:39.000
<v Speaker 3>the round of course, CEO and co founder of.

0:19:39.000 --> 0:19:50.520
<v Speaker 4>Writer, welcome back to Bloombay Technology, Ed Ludlow here in

0:19:50.560 --> 0:19:52.680
<v Speaker 4>New York City, Caroen, Yeah, it's so good to.

0:19:52.640 --> 0:19:54.480
<v Speaker 5>Have you here. Let's have a quick check on these markets.

0:19:54.520 --> 0:19:56.600
<v Speaker 5>I'm Caroline High. Let's get a quick look.

0:19:56.359 --> 0:19:59.240
<v Speaker 3>At as we get through midday training, Nasdaq actually turning

0:19:59.240 --> 0:20:00.639
<v Speaker 3>a little bit to the high. And that's that one

0:20:00.720 --> 0:20:04.560
<v Speaker 3>hundred in particular when in this nervous macro period where

0:20:04.560 --> 0:20:06.520
<v Speaker 3>we get not only the Federal Reserve come Wednesday, you

0:20:06.560 --> 0:20:08.199
<v Speaker 3>get the Bank of England on Thursday, the Bank of

0:20:08.560 --> 0:20:11.600
<v Speaker 3>to round out the week, where is well the pressure

0:20:11.600 --> 0:20:13.480
<v Speaker 3>point's going to be for some of these central bankers

0:20:13.520 --> 0:20:15.600
<v Speaker 3>to the upside. It feels like on the two year

0:20:15.640 --> 0:20:18.359
<v Speaker 3>yield we're up against just about two basis points overall

0:20:18.359 --> 0:20:20.800
<v Speaker 3>because we're worrying again about whether we pause this time,

0:20:20.840 --> 0:20:22.320
<v Speaker 3>but have to keep on raising in the fight of

0:20:22.359 --> 0:20:23.639
<v Speaker 3>inflation that you see.

0:20:23.480 --> 0:20:25.240
<v Speaker 5>Prices are oil on the rise and seeing.

0:20:25.080 --> 0:20:28.040
<v Speaker 3>Bitcoin actually interestingly managed to shake off some of this anxiety.

0:20:28.080 --> 0:20:29.160
<v Speaker 5>We're up almost three percent.

0:20:29.600 --> 0:20:31.960
<v Speaker 3>Ask not the reason why many people are saying like

0:20:32.040 --> 0:20:33.040
<v Speaker 3>this is thin liquidity at the.

0:20:33.040 --> 0:20:35.560
<v Speaker 5>Moment, but we're above that twenty seven thousand level. Moving on,

0:20:35.640 --> 0:20:37.320
<v Speaker 5>go to some of the individual movers that are on

0:20:37.800 --> 0:20:38.359
<v Speaker 5>our minds.

0:20:38.480 --> 0:20:40.760
<v Speaker 3>Of course, Apple actually managing to make up some of

0:20:40.760 --> 0:20:41.840
<v Speaker 3>that sell off on Friday.

0:20:41.880 --> 0:20:43.679
<v Speaker 5>This is we see some good moon.

0:20:43.600 --> 0:20:47.360
<v Speaker 3>Music coming around the early sales and interest at least

0:20:47.440 --> 0:20:49.560
<v Speaker 3>in the IFM fifteen in all of the array. Tesla

0:20:49.560 --> 0:20:51.639
<v Speaker 3>on the downside, off by two point six percent. Some

0:20:51.720 --> 0:20:54.240
<v Speaker 3>analysts writing that they're concerned about the future earnings potential

0:20:54.240 --> 0:20:56.000
<v Speaker 3>of this particular company, so keep an eye on some

0:20:56.000 --> 0:20:57.120
<v Speaker 3>of the analyst notes there today.

0:20:57.119 --> 0:20:59.120
<v Speaker 5>And Microsoft, this was an interesting.

0:20:58.800 --> 0:21:01.400
<v Speaker 3>One, maybe a bit of a revolving door, but ultimately

0:21:01.400 --> 0:21:03.320
<v Speaker 3>they had a product who I might add has been

0:21:03.359 --> 0:21:05.439
<v Speaker 3>at the business for a very long time driving the

0:21:05.520 --> 0:21:08.160
<v Speaker 3>likes of the surface and indeed Microsoft Windows of late,

0:21:08.200 --> 0:21:11.440
<v Speaker 3>but panas Pane will be staying long enough to help replacements.

0:21:11.520 --> 0:21:14.679
<v Speaker 3>We understand transition into the role. But after more decades,

0:21:14.720 --> 0:21:17.600
<v Speaker 3>having joined since two thousand and four, panas Panee is

0:21:17.720 --> 0:21:18.720
<v Speaker 3>leaving Microsoft ED.

0:21:18.920 --> 0:21:21.320
<v Speaker 4>Yeah, speaking of departures and returns, it's been a pretty

0:21:21.400 --> 0:21:24.800
<v Speaker 4>rough year for Meta employees after twenty thousand of their

0:21:24.800 --> 0:21:26.720
<v Speaker 4>teammates were laid off over.

0:21:26.520 --> 0:21:27.280
<v Speaker 7>The past year.

0:21:27.480 --> 0:21:30.760
<v Speaker 4>But now they're starting to enjoy coming back into the office.

0:21:30.800 --> 0:21:33.320
<v Speaker 4>One reason is the company has revived a number of

0:21:33.359 --> 0:21:38.119
<v Speaker 4>popular pre pandemic perks, from branded T shirts to happy hours.

0:21:38.119 --> 0:21:40.439
<v Speaker 4>That's bringing in Boxatia counts out of SF for more

0:21:40.480 --> 0:21:42.359
<v Speaker 4>and ah. This is interesting because when you and I

0:21:42.400 --> 0:21:44.240
<v Speaker 4>reported the rounds of layoffs at the end of last

0:21:44.320 --> 0:21:47.000
<v Speaker 4>year and beginning of this year, we covered how deep

0:21:47.040 --> 0:21:50.520
<v Speaker 4>and sudden and wide they were, and many people were upset.

0:21:51.240 --> 0:21:53.760
<v Speaker 4>Talk to us about some of the cultural fixes that

0:21:53.840 --> 0:21:54.920
<v Speaker 4>Meta's bringing back in.

0:21:56.400 --> 0:21:58.800
<v Speaker 13>Yeah, as you mentioned around the time of the layouse,

0:21:58.840 --> 0:22:00.840
<v Speaker 13>I mean, people were anxious, they were scared that they

0:22:00.880 --> 0:22:02.399
<v Speaker 13>could lose their jobs at any moment.

0:22:02.720 --> 0:22:03.199
<v Speaker 5>They started to.

0:22:03.200 --> 0:22:05.720
<v Speaker 13>Scale back perks, and now those are coming back. Some

0:22:05.720 --> 0:22:08.399
<v Speaker 13>employees I was talking to were saying happy hours on

0:22:08.440 --> 0:22:11.199
<v Speaker 13>Thursdays are happening again. Dinner time, which used to be

0:22:11.359 --> 0:22:13.080
<v Speaker 13>like six thirty or seven, is now at six and

0:22:13.080 --> 0:22:14.439
<v Speaker 13>people are super excited about that.

0:22:14.520 --> 0:22:15.800
<v Speaker 5>The restaurants are opening.

0:22:15.640 --> 0:22:17.440
<v Speaker 13>Up again, and even some of the more sort of

0:22:17.520 --> 0:22:20.760
<v Speaker 13>luxurious ferks like laundry services and haircuts are back. So

0:22:20.760 --> 0:22:22.919
<v Speaker 13>people are excited that things are actually coming back, and

0:22:22.920 --> 0:22:24.360
<v Speaker 13>it's definitely boosting spirits.

0:22:24.680 --> 0:22:27.480
<v Speaker 5>There's enough Lacroix to go around a show. What about though,

0:22:27.880 --> 0:22:31.800
<v Speaker 5>enough jobs to go around. I'm actually in the detail

0:22:31.800 --> 0:22:32.480
<v Speaker 5>of your story.

0:22:32.600 --> 0:22:35.120
<v Speaker 3>People are actually being brought back they've previously been laid off.

0:22:36.240 --> 0:22:39.400
<v Speaker 13>I talked to Yeah, some employees that had been rehired,

0:22:39.600 --> 0:22:41.520
<v Speaker 13>and there are other people that are in the process.

0:22:42.119 --> 0:22:43.840
<v Speaker 13>It's slow and they have to sort of go through

0:22:43.880 --> 0:22:46.800
<v Speaker 13>the application process again. But Meta is rehiring and they

0:22:46.840 --> 0:22:48.399
<v Speaker 13>said this too on the earnings call right, that they

0:22:48.400 --> 0:22:51.240
<v Speaker 13>want to hire more people in hot areas like AI,

0:22:51.480 --> 0:22:54.199
<v Speaker 13>especially generative AI. So yeah, they are slowly starting to

0:22:54.200 --> 0:22:55.120
<v Speaker 13>bring some people back.

0:22:55.320 --> 0:22:57.800
<v Speaker 4>I think what's so interesting now issues we're in a

0:22:57.960 --> 0:23:00.480
<v Speaker 4>time where we're not really either talking at about the

0:23:00.520 --> 0:23:03.920
<v Speaker 4>metaverse and the sort of losses that that unit was

0:23:03.960 --> 0:23:06.480
<v Speaker 4>going on. We are talking more about the work that

0:23:06.560 --> 0:23:10.560
<v Speaker 4>Meta is doing in AI Lama to open source. What

0:23:10.720 --> 0:23:13.119
<v Speaker 4>is the latest signal we're getting out of matter of

0:23:13.160 --> 0:23:16.200
<v Speaker 4>what the priority is for Mark Zuckerberg.

0:23:17.040 --> 0:23:17.960
<v Speaker 5>It's still AI.

0:23:18.200 --> 0:23:20.320
<v Speaker 13>I mean, they'll tell you on the earnings call that

0:23:20.480 --> 0:23:22.600
<v Speaker 13>you know, the meta versus is still a priority and

0:23:22.640 --> 0:23:25.720
<v Speaker 13>the company is still putting money there, but it really

0:23:25.760 --> 0:23:27.520
<v Speaker 13>is AI. Even employees that I've talked to you said

0:23:27.560 --> 0:23:29.800
<v Speaker 13>like everyone wants to be on the generative AI teams.

0:23:29.840 --> 0:23:32.720
<v Speaker 13>That's sort of like the hot team that's doing well,

0:23:32.760 --> 0:23:36.000
<v Speaker 13>that's getting money. So even just from where employees are

0:23:36.000 --> 0:23:37.200
<v Speaker 13>going on what teams they want to be on, you

0:23:37.240 --> 0:23:39.080
<v Speaker 13>can see that. And then of course, as you mentioned,

0:23:39.200 --> 0:23:42.399
<v Speaker 13>they have code Lama, Lama one, Lama two. They're really

0:23:42.400 --> 0:23:44.600
<v Speaker 13>sort of pushing to be a leader in the AI space.

0:23:45.000 --> 0:23:46.520
<v Speaker 5>As counts brilliantly.

0:23:46.560 --> 0:23:48.800
<v Speaker 3>Thank you for that story, and we are and I mean,

0:23:49.400 --> 0:23:52.760
<v Speaker 3>ultimately here you are in New York with all your

0:23:52.800 --> 0:23:55.320
<v Speaker 3>knowledge of really the anxiety that has been in the

0:23:55.359 --> 0:23:59.119
<v Speaker 3>past for San Francisco, Silicon Valley more broadly but meta.

0:23:59.200 --> 0:24:01.359
<v Speaker 3>It is notable that they had a long way to

0:24:01.400 --> 0:24:02.159
<v Speaker 3>work to get back that.

0:24:02.200 --> 0:24:02.480
<v Speaker 5>Marah.

0:24:02.600 --> 0:24:02.760
<v Speaker 7>Yeah.

0:24:02.800 --> 0:24:04.120
<v Speaker 4>The way it was described to me at the time

0:24:04.200 --> 0:24:06.080
<v Speaker 4>is like at first they used a scalpol and they

0:24:06.080 --> 0:24:08.359
<v Speaker 4>were like, Okay, let's very clearly work out what we

0:24:08.440 --> 0:24:11.200
<v Speaker 4>need to do. But the year of efficiency was the priorities.

0:24:11.240 --> 0:24:13.480
<v Speaker 4>So they later chucked out the scalpel and they brought

0:24:13.480 --> 0:24:16.640
<v Speaker 4>the sledgehammer, which is one way that some executives put

0:24:16.680 --> 0:24:18.560
<v Speaker 4>it to me, and they realized, well, hold on, we

0:24:18.560 --> 0:24:21.119
<v Speaker 4>actually need some of these people. And it's amazing to

0:24:21.160 --> 0:24:24.360
<v Speaker 4>see Asia report they're now as individuals being high back

0:24:24.720 --> 0:24:25.159
<v Speaker 4>and at.

0:24:25.000 --> 0:24:27.040
<v Speaker 3>The time where share prices on the rise, that's always

0:24:27.040 --> 0:24:29.720
<v Speaker 3>helpful for your new music as well. But there is

0:24:29.720 --> 0:24:33.720
<v Speaker 3>still this ongoing concern about really the future of social media.

0:24:33.760 --> 0:24:35.520
<v Speaker 5>It's bread and butter, the future.

0:24:35.160 --> 0:24:38.480
<v Speaker 3>Direction of WhatsApp, of Messenger, but notably of Instagram and

0:24:38.520 --> 0:24:41.760
<v Speaker 3>of Facebook, the og the blue and how we regulate

0:24:41.840 --> 0:24:43.760
<v Speaker 3>that going forward, how we make it a safer space.

0:24:43.800 --> 0:24:45.760
<v Speaker 3>And we want to stick on that particular point because

0:24:45.800 --> 0:24:48.040
<v Speaker 3>we understand that more than one hundred parents of transgender

0:24:48.080 --> 0:24:50.840
<v Speaker 3>kids have signed an open letter urging the US Senate

0:24:50.920 --> 0:24:53.640
<v Speaker 3>to oppose the Kids Online Safety Act or KOSOS.

0:24:53.640 --> 0:24:55.400
<v Speaker 5>It's known the legislation aims to.

0:24:55.320 --> 0:24:58.159
<v Speaker 3>Make the Internet safer for kids, but look, some LGBTQ

0:24:58.280 --> 0:25:01.200
<v Speaker 3>advocates are raising some concerns against particularly a CeNAT to

0:25:01.240 --> 0:25:03.840
<v Speaker 3>Marshal Black Friends the legislation that could give new power

0:25:03.880 --> 0:25:07.399
<v Speaker 3>to state attorneys general to dictate what children can access

0:25:07.400 --> 0:25:10.520
<v Speaker 3>online and perhaps that cuts trans children off from what

0:25:10.560 --> 0:25:13.399
<v Speaker 3>the parents are saying is life saving online resources and community.

0:25:13.840 --> 0:25:16.160
<v Speaker 3>Let's be again someone who's trying to find the nuance

0:25:16.240 --> 0:25:18.879
<v Speaker 3>within all of this. Frank McCourt junior is a founder

0:25:18.880 --> 0:25:21.440
<v Speaker 3>of Project Liberty Action Network and Project Liberty and Organization,

0:25:21.480 --> 0:25:23.840
<v Speaker 3>which strives to address the harms of social media and

0:25:23.880 --> 0:25:24.919
<v Speaker 3>technology on society and.

0:25:25.080 --> 0:25:26.160
<v Speaker 5>Especially for children.

0:25:26.359 --> 0:25:28.359
<v Speaker 3>You've been a proponent of the kids online safety, but

0:25:28.440 --> 0:25:30.920
<v Speaker 3>at the heart of it, Frank, you're someone who wants

0:25:30.960 --> 0:25:32.240
<v Speaker 3>technology to be the answer.

0:25:32.280 --> 0:25:32.399
<v Speaker 6>Here.

0:25:32.640 --> 0:25:35.800
<v Speaker 3>Can technology, when we talk about AI and the folks

0:25:36.040 --> 0:25:39.080
<v Speaker 3>ever solve for the nuance, for the ability to get

0:25:39.119 --> 0:25:41.520
<v Speaker 3>this very difficult context satisfied.

0:25:41.760 --> 0:25:42.840
<v Speaker 5>Yeah, I think it can.

0:25:43.560 --> 0:25:46.000
<v Speaker 14>And yeah I'm glad you mentioned AI because all this

0:25:46.040 --> 0:25:49.280
<v Speaker 14>is moving very quickly now, right, and we, I think

0:25:49.320 --> 0:25:53.320
<v Speaker 14>need to really focus on the infrastructure. And I'm a

0:25:54.400 --> 0:25:56.960
<v Speaker 14>builder at heart, right, I'm from a family of fifth

0:25:57.000 --> 0:25:59.200
<v Speaker 14>generation builder one hundred and thirty years. We've been building

0:25:59.359 --> 0:26:02.880
<v Speaker 14>large infrastruction projects and when we look at the design,

0:26:03.080 --> 0:26:07.480
<v Speaker 14>the current design of big tech, in particular our social

0:26:07.520 --> 0:26:09.440
<v Speaker 14>media platforms are being.

0:26:09.280 --> 0:26:10.600
<v Speaker 5>Used and being brought forward.

0:26:10.960 --> 0:26:13.879
<v Speaker 14>We have a design problem and an infrastructure problem, and

0:26:14.200 --> 0:26:17.359
<v Speaker 14>fortunately now we have the technology to actually fix it right.

0:26:17.520 --> 0:26:21.520
<v Speaker 14>We can provide a digital identity, we can provide ownership

0:26:21.560 --> 0:26:24.879
<v Speaker 14>and data control to individuals. We can actually share value

0:26:24.880 --> 0:26:27.320
<v Speaker 14>within individuals. So I think we need to fix the

0:26:27.359 --> 0:26:30.479
<v Speaker 14>tech to fix the problem. But fixing the tech alone

0:26:30.720 --> 0:26:31.400
<v Speaker 14>once solved.

0:26:31.160 --> 0:26:33.560
<v Speaker 4>Because that's the thing, Frank, that you just heard Karen

0:26:33.600 --> 0:26:35.840
<v Speaker 4>and I talking there to Asha about what Meta is

0:26:35.960 --> 0:26:39.280
<v Speaker 4>working on. It's good at artificial intelligence, the cutting edge

0:26:39.280 --> 0:26:42.760
<v Speaker 4>of foundation models. From a regulatory perspective, their position was

0:26:42.800 --> 0:26:46.560
<v Speaker 4>always that we don't know who should have oversight. We

0:26:46.640 --> 0:26:48.920
<v Speaker 4>just don't think we should do ourselves. But why do

0:26:49.040 --> 0:26:52.600
<v Speaker 4>we not talk more about them finding technological fixes for

0:26:52.680 --> 0:26:55.239
<v Speaker 4>their own the problems on their own platforms.

0:26:54.880 --> 0:26:57.400
<v Speaker 14>Because they don't want to fix it. Because these big

0:26:57.440 --> 0:27:02.040
<v Speaker 14>platforms have our data, they aggregate it, and they exploit

0:27:02.080 --> 0:27:03.679
<v Speaker 14>it and monetize it.

0:27:03.720 --> 0:27:05.360
<v Speaker 9>And we need a new.

0:27:05.440 --> 0:27:09.240
<v Speaker 14>Design for the technology where individuals ownly control their data.

0:27:09.359 --> 0:27:12.040
<v Speaker 14>You mentioned regulation. I think regulation is part of it,

0:27:12.080 --> 0:27:14.080
<v Speaker 14>but it's not going to solve the entire problem. And

0:27:15.040 --> 0:27:18.879
<v Speaker 14>for me, what's very interesting about this COOSA. Uh, you know,

0:27:18.960 --> 0:27:22.240
<v Speaker 14>the Kids Online Safety Act is we've seen the level

0:27:22.280 --> 0:27:25.400
<v Speaker 14>of concerned parents have with the current tech architecture. We

0:27:25.480 --> 0:27:29.959
<v Speaker 14>know it's broken. KOSA is an effort in the right direction,

0:27:30.080 --> 0:27:32.320
<v Speaker 14>right to let big techno We're not going to We're

0:27:32.320 --> 0:27:33.960
<v Speaker 14>not going to live with this any longer.

0:27:34.000 --> 0:27:35.080
<v Speaker 5>We're going to we're going to fix it.

0:27:35.160 --> 0:27:37.320
<v Speaker 14>So I think it's not the bi all end all,

0:27:37.480 --> 0:27:38.760
<v Speaker 14>but it's a step in the right direction.

0:27:39.400 --> 0:27:42.600
<v Speaker 7>So what is the technological fix? Is it algorithmic? Is it?

0:27:42.920 --> 0:27:45.160
<v Speaker 4>You know I've asked that question to the companies many

0:27:45.200 --> 0:27:47.720
<v Speaker 4>times over the years, and I'm yet to hear aim

0:27:47.800 --> 0:27:48.719
<v Speaker 4>straightforward answer.

0:27:48.920 --> 0:27:50.800
<v Speaker 14>Yeah, because they don't want to give you an answer,

0:27:50.800 --> 0:27:53.720
<v Speaker 14>because what is your answer fr return ownership and control

0:27:53.720 --> 0:27:54.320
<v Speaker 14>of data.

0:27:54.119 --> 0:27:54.840
<v Speaker 5>To the individual.

0:27:55.240 --> 0:27:59.600
<v Speaker 14>Well, I'm saying using blockchain, but it's not a think

0:27:59.640 --> 0:28:02.000
<v Speaker 14>about it. First, at the infrastructure level, I mentioned that

0:28:02.320 --> 0:28:04.679
<v Speaker 14>we're in the third generation of the Internet now. The

0:28:04.760 --> 0:28:09.480
<v Speaker 14>first generation was enabled by a protocol called TCPIP, the

0:28:09.600 --> 0:28:14.040
<v Speaker 14>second generation by a protocol HTTP. We need a third

0:28:14.200 --> 0:28:17.679
<v Speaker 14>generation of the Internet now enabled by another protocol. We

0:28:17.680 --> 0:28:22.320
<v Speaker 14>would suggest it's DSNP, a decentralized social networking protocol which

0:28:22.560 --> 0:28:26.440
<v Speaker 14>enables people individuals to own and control their data and

0:28:26.760 --> 0:28:30.600
<v Speaker 14>by deploying blockchain, derive value from their data.

0:28:30.720 --> 0:28:34.000
<v Speaker 3>We of course come into this conversation talking about meta

0:28:34.640 --> 0:28:36.359
<v Speaker 3>But first I want to push back at that. I

0:28:36.359 --> 0:28:38.000
<v Speaker 3>think a lot of people who work at the company

0:28:38.600 --> 0:28:40.680
<v Speaker 3>do want to see a fix. They never built this

0:28:40.840 --> 0:28:44.480
<v Speaker 3>because they thought this would be a negative to in

0:28:44.520 --> 0:28:46.040
<v Speaker 3>any way. They want to be able to try and

0:28:46.120 --> 0:28:48.960
<v Speaker 3>ensure that kids aren't in any way exposed to harmful content.

0:28:49.000 --> 0:28:51.960
<v Speaker 3>But also there's this conversation that this is just about

0:28:52.040 --> 0:28:54.880
<v Speaker 3>US companies and US regulations. This is about Chinese players

0:28:54.880 --> 0:28:57.640
<v Speaker 3>for example, and TikTok of course owned by Bykedance. I

0:28:57.680 --> 0:28:58.800
<v Speaker 3>just want you to take a listen to what Mike

0:28:58.800 --> 0:29:00.560
<v Speaker 3>Pence had to say about the regulation.

0:29:00.360 --> 0:29:03.600
<v Speaker 15>Of TikTok, and we will to be banning TikTok. TikTok

0:29:03.720 --> 0:29:07.440
<v Speaker 15>is a platform of the communist Chinese government. They're collecting

0:29:07.520 --> 0:29:11.200
<v Speaker 15>data on Americans every single day. What young Americans deserve

0:29:11.280 --> 0:29:15.160
<v Speaker 15>to know is that their privacy is being compromised with

0:29:15.320 --> 0:29:19.480
<v Speaker 15>participation in the TikTok platform.

0:29:19.680 --> 0:29:24.640
<v Speaker 3>Does self regulation, technological regulation, or indeed, in the end

0:29:24.840 --> 0:29:27.920
<v Speaker 3>regulation coming from the US ever solve for international players

0:29:27.920 --> 0:29:28.400
<v Speaker 3>at this point.

0:29:28.480 --> 0:29:33.320
<v Speaker 14>Well, I think this TikTok example is a good one. Right.

0:29:34.320 --> 0:29:40.600
<v Speaker 14>Autocratic technology is awesome if you're an autocracy. So autocratic

0:29:40.680 --> 0:29:43.400
<v Speaker 14>technology is going to work very very well for China.

0:29:44.040 --> 0:29:46.640
<v Speaker 14>But I would argue that you can't have a democracy

0:29:46.800 --> 0:29:48.600
<v Speaker 14>with autocratic technology.

0:29:48.080 --> 0:29:49.360
<v Speaker 7>In this circumstance. Right.

0:29:49.880 --> 0:29:53.880
<v Speaker 4>The proposal from TikTok and Oracle was a technological solution.

0:29:54.360 --> 0:29:59.200
<v Speaker 4>How's the data in a US data center with oversight

0:29:59.240 --> 0:30:02.160
<v Speaker 4>from the US governm, then not have any data locally

0:30:02.200 --> 0:30:05.320
<v Speaker 4>housed in China? Why was that your mind, Frank not

0:30:05.640 --> 0:30:09.080
<v Speaker 4>an Well, was it, to your mind a good enough solution? I?

0:30:09.120 --> 0:30:10.640
<v Speaker 14>No, it's not a good enough solution. I think we're

0:30:10.680 --> 0:30:13.760
<v Speaker 14>playing around the edges. It's you know, bug, mister Fuller

0:30:14.400 --> 0:30:16.120
<v Speaker 14>had a great saying, and I'm going to paraphrase it.

0:30:16.200 --> 0:30:18.160
<v Speaker 14>When the model is so broken, don't waste your time

0:30:18.200 --> 0:30:20.480
<v Speaker 14>trying to fix it. Build a new model and make

0:30:20.480 --> 0:30:23.600
<v Speaker 14>the old one obsolete. That's where we're at right now.

0:30:23.880 --> 0:30:26.400
<v Speaker 14>Twenty thirty years ago, there wasn't the ability to store

0:30:26.480 --> 0:30:29.560
<v Speaker 14>data in a decentralized way, so we needed these large

0:30:29.920 --> 0:30:34.280
<v Speaker 14>centralized server farms gathering up this data. And you're right, Carolin,

0:30:34.320 --> 0:30:36.040
<v Speaker 14>I don't think people went out of their way thinking

0:30:36.040 --> 0:30:39.080
<v Speaker 14>that they were going to do something. You know, most

0:30:39.080 --> 0:30:41.080
<v Speaker 14>of the employees from Meta or these other companies do

0:30:41.160 --> 0:30:43.720
<v Speaker 14>something bad with all this data. But just look at

0:30:43.760 --> 0:30:46.200
<v Speaker 14>where we are now. Just look at where we are right,

0:30:46.720 --> 0:30:52.120
<v Speaker 14>kids anxious, depressed, attempting to kill themselves or killing themselves.

0:30:52.720 --> 0:30:57.240
<v Speaker 14>Our society generally, we can't have conversations anymore, highly polarized.

0:30:57.440 --> 0:31:00.960
<v Speaker 14>Our democracy struggling to survive. And I would argue even

0:31:00.960 --> 0:31:03.560
<v Speaker 14>our economy is going to struggle if the bulk of

0:31:03.600 --> 0:31:05.920
<v Speaker 14>the of the of the value resides in five or

0:31:05.920 --> 0:31:09.080
<v Speaker 14>six platforms. There's a moment here where we can change

0:31:09.080 --> 0:31:11.400
<v Speaker 14>all this, and we need to. It does not have

0:31:11.480 --> 0:31:13.480
<v Speaker 14>to be this way, Frank, can.

0:31:13.400 --> 0:31:16.120
<v Speaker 5>I ask a personal questions to why you're doing this?

0:31:16.360 --> 0:31:18.000
<v Speaker 3>You are a father of six, and I'm sure they're

0:31:18.000 --> 0:31:21.040
<v Speaker 3>grown but to a large extent. But bid you go

0:31:21.120 --> 0:31:23.400
<v Speaker 3>back from a nineteenth century business that's built You say

0:31:23.440 --> 0:31:24.120
<v Speaker 3>you were builders.

0:31:24.520 --> 0:31:25.880
<v Speaker 5>Why turn your attention hand?

0:31:25.920 --> 0:31:27.840
<v Speaker 3>Why do you so, Galvan I so focus on this

0:31:27.880 --> 0:31:30.760
<v Speaker 3>particular part of infrastructure, even though it's not bricks and mortar.

0:31:31.040 --> 0:31:34.440
<v Speaker 14>Well, it started a decade ago, and we started with

0:31:34.480 --> 0:31:36.040
<v Speaker 14>Georgetown Public Policy.

0:31:35.680 --> 0:31:37.280
<v Speaker 9>School in Washington, d C.

0:31:37.480 --> 0:31:42.320
<v Speaker 14>Brand new school and thought that maybe we could contribute

0:31:42.480 --> 0:31:46.440
<v Speaker 14>in that way. Learn very quickly and by the way,

0:31:46.480 --> 0:31:49.000
<v Speaker 14>inside this the public Policy School something we call the

0:31:49.040 --> 0:31:52.920
<v Speaker 14>Massive Data Institute, we learn very quickly that the data

0:31:52.960 --> 0:31:55.960
<v Speaker 14>that these policy makers need is not available to them.

0:31:56.120 --> 0:31:58.920
<v Speaker 14>It's in these large platforms. So that's where we began

0:31:59.000 --> 0:32:03.240
<v Speaker 14>to use our skills as builders, as infrastructure specialists to

0:32:03.320 --> 0:32:05.960
<v Speaker 14>look at the design of the technology and came to

0:32:06.040 --> 0:32:10.320
<v Speaker 14>just a very simple conclusion, why is our data being

0:32:10.400 --> 0:32:14.200
<v Speaker 14>scraped and aggregated by a few platforms. It just doesn't

0:32:14.240 --> 0:32:18.440
<v Speaker 14>feel correct to me. We should own our digital DNA.

0:32:19.200 --> 0:32:22.280
<v Speaker 14>This is our digital this is our lived life. There's

0:32:22.320 --> 0:32:26.720
<v Speaker 14>no separation between now your biological identity and your digital identity.

0:32:26.960 --> 0:32:29.000
<v Speaker 14>Somehow we've let them be separated, but the fact of

0:32:29.000 --> 0:32:31.480
<v Speaker 14>the matter, they're one and the same. And by the way,

0:32:31.480 --> 0:32:33.560
<v Speaker 14>there's a lot of value to be derived from this data.

0:32:33.560 --> 0:32:35.560
<v Speaker 14>So there's a lot of companies that are going to

0:32:35.560 --> 0:32:38.160
<v Speaker 14>be built and innovation that's going to occur. I think

0:32:38.200 --> 0:32:42.080
<v Speaker 14>we should lean into innovation and of course regulate things

0:32:42.080 --> 0:32:45.280
<v Speaker 14>to buy the time, but this is not a regulatory fix. Ultimately,

0:32:45.360 --> 0:32:47.680
<v Speaker 14>this is going to be a tech fix for a

0:32:47.680 --> 0:32:50.840
<v Speaker 14>tech problem. And then this time let's get it right

0:32:51.240 --> 0:32:53.680
<v Speaker 14>by optimizing for the right things, the things that are

0:32:53.720 --> 0:32:57.000
<v Speaker 14>good for kids, good for society, good for democracy.

0:32:57.680 --> 0:33:01.080
<v Speaker 4>Thank Recur, junior founder of the project the Action Network.

0:33:01.200 --> 0:33:04.000
<v Speaker 4>Just terrific conversation here, and actually it's good to be

0:33:04.000 --> 0:33:05.680
<v Speaker 4>out here on the West Coast in New York City.

0:33:05.680 --> 0:33:07.960
<v Speaker 4>But up next we're going to discuss the health of

0:33:08.040 --> 0:33:11.840
<v Speaker 4>the Boston startup ecosystem. That's with Lily Lyman from Underscore

0:33:11.960 --> 0:33:15.400
<v Speaker 4>VC and our VC Spotlight segment coming up next, this

0:33:15.560 --> 0:33:29.239
<v Speaker 4>is Bloomberg Technology. It is good to be on the

0:33:29.280 --> 0:33:31.600
<v Speaker 4>East coast. I know where I am, New York City,

0:33:31.640 --> 0:33:34.600
<v Speaker 4>Reunited Carrow. But on today's VC Spotlight, we're gonna be

0:33:34.640 --> 0:33:38.000
<v Speaker 4>taking a look at the Boston startup ecosystem in full swing.

0:33:38.240 --> 0:33:40.560
<v Speaker 4>And who better to talk to about that than Lily Lyman,

0:33:40.640 --> 0:33:44.280
<v Speaker 4>general partner at Underscore VC, early stage VC firm based

0:33:44.320 --> 0:33:47.840
<v Speaker 4>in Boston, two hundred and forty six million dollars in assets.

0:33:47.840 --> 0:33:49.680
<v Speaker 4>And I want to go straight to Klaviyo, you know,

0:33:49.840 --> 0:33:53.000
<v Speaker 4>potentially a big IPO, a tech company from your neck

0:33:53.040 --> 0:33:55.680
<v Speaker 4>of the woods this week. How excited does that get

0:33:55.720 --> 0:33:56.800
<v Speaker 4>people in your community?

0:33:56.800 --> 0:33:57.280
<v Speaker 7>In Boston.

0:33:58.440 --> 0:34:00.760
<v Speaker 2>Yeah, well, thanks for thanks for having me. You know,

0:34:00.800 --> 0:34:03.760
<v Speaker 2>we're very excited for the Clavio IPO, and I think

0:34:03.760 --> 0:34:06.560
<v Speaker 2>it's in part because it's the type of company that

0:34:06.600 --> 0:34:09.719
<v Speaker 2>gets built here in Boston. It's a great team, it's

0:34:09.760 --> 0:34:12.799
<v Speaker 2>a huge market. They've been very capital efficient in how

0:34:12.840 --> 0:34:16.880
<v Speaker 2>they've built, and I think that's reflected in the ownership

0:34:16.880 --> 0:34:19.080
<v Speaker 2>of Andrew a moment of IPO be over a third

0:34:19.080 --> 0:34:21.120
<v Speaker 2>of the company, and so I think overall it's just

0:34:21.160 --> 0:34:23.680
<v Speaker 2>the type of type of business that's built here in Boston.

0:34:23.800 --> 0:34:25.120
<v Speaker 2>I think to note, you know, there's also not a

0:34:25.120 --> 0:34:27.319
<v Speaker 2>lot of puffery around it. They've just done a good

0:34:27.360 --> 0:34:29.880
<v Speaker 2>job building and I think they've earned the right to

0:34:30.480 --> 0:34:31.439
<v Speaker 2>have success this week.

0:34:31.520 --> 0:34:33.439
<v Speaker 3>I maybe know that much puffery, as you say, because

0:34:33.480 --> 0:34:35.160
<v Speaker 3>it's b to be Ultimately, it's.

0:34:34.960 --> 0:34:37.279
<v Speaker 5>Not b to see. So the retail investors are not

0:34:37.320 --> 0:34:39.040
<v Speaker 5>aware of it. But this is your sweet spot. You

0:34:39.120 --> 0:34:40.640
<v Speaker 5>are b to be investor largely.

0:34:40.719 --> 0:34:43.880
<v Speaker 3>And how much is Boston the ecosystem for that, particularly

0:34:43.920 --> 0:34:46.280
<v Speaker 3>as we start to see the world shift towards AI

0:34:46.360 --> 0:34:48.600
<v Speaker 3>and well San Francisco seems to be sucking a lot

0:34:48.600 --> 0:34:49.600
<v Speaker 3>of the oxygen.

0:34:49.200 --> 0:34:52.120
<v Speaker 2>That Yeah, so as you mentioned, we are B to

0:34:52.239 --> 0:34:54.520
<v Speaker 2>B and vertical SaaS investors, and I think you know,

0:34:54.560 --> 0:34:58.160
<v Speaker 2>Boston's typically known for its biotech and healthcare, but what

0:34:58.239 --> 0:35:00.280
<v Speaker 2>we see is that there are a variety of actors

0:35:00.320 --> 0:35:02.480
<v Speaker 2>that are thriving here in the B to B space,

0:35:02.520 --> 0:35:06.080
<v Speaker 2>whether it's commerce with companies like Salsify, or in sure

0:35:06.200 --> 0:35:11.000
<v Speaker 2>tech with companies like Himari. Also areas like supply chain logistics,

0:35:11.320 --> 0:35:14.280
<v Speaker 2>and then as you mentioned, increasingly in AI and machine learning,

0:35:14.360 --> 0:35:17.000
<v Speaker 2>and we've had the pleasure to back several great companies

0:35:17.000 --> 0:35:20.000
<v Speaker 2>in that space, a company like Tetrascience, which is you know,

0:35:20.080 --> 0:35:23.600
<v Speaker 2>snowflake for scientific data. You know, I think in part

0:35:23.680 --> 0:35:26.360
<v Speaker 2>what makes this ecosystem unique is the universities that we

0:35:26.400 --> 0:35:28.640
<v Speaker 2>have in our backyard and a lot of the leading

0:35:28.719 --> 0:35:32.400
<v Speaker 2>edge technology and also talent coming out of those ecosystems

0:35:32.440 --> 0:35:36.200
<v Speaker 2>consistently fuels what is now powering the AI and machine

0:35:36.239 --> 0:35:40.080
<v Speaker 2>learning revolution that we're seeing across the board. So, you know,

0:35:40.080 --> 0:35:42.279
<v Speaker 2>we continue to expect to see a lot of great

0:35:42.360 --> 0:35:46.000
<v Speaker 2>both tech and talent coming through this ecosystem here and

0:35:46.040 --> 0:35:47.760
<v Speaker 2>fueling a lot of what people are excited about.

0:35:47.840 --> 0:35:49.120
<v Speaker 5>When you're in LP and.

0:35:49.080 --> 0:35:52.680
<v Speaker 3>The Haavid Fund and an MIT Fund, how are you

0:35:52.800 --> 0:35:55.520
<v Speaker 3>seeing a desire to build and what is a pretty

0:35:55.600 --> 0:35:59.320
<v Speaker 3>unstable economic environment. It was meant to be the silver

0:35:59.400 --> 0:36:01.960
<v Speaker 3>lining that we had Joe blofs they would go out

0:36:02.000 --> 0:36:04.480
<v Speaker 3>and build things. Is that happening even coming out of

0:36:04.480 --> 0:36:05.479
<v Speaker 3>the universities at the moment.

0:36:06.400 --> 0:36:08.759
<v Speaker 2>Yeah, As you mentioned, you know, we're we are investors

0:36:08.800 --> 0:36:11.680
<v Speaker 2>in some of the on campus funds, so Harvard's Austin Fund,

0:36:11.880 --> 0:36:14.240
<v Speaker 2>MIT Sandbox Fund, and the dorm Room Fund.

0:36:14.719 --> 0:36:16.520
<v Speaker 5>And what that partnership.

0:36:16.040 --> 0:36:18.520
<v Speaker 2>Allows us to see is the most exceptional entrepreneurs coming

0:36:18.560 --> 0:36:21.840
<v Speaker 2>out of those ecosystems as soon as they graduate, and

0:36:21.880 --> 0:36:25.000
<v Speaker 2>we're seeing a lot of thriving ideas and opportunities. Over

0:36:25.040 --> 0:36:28.200
<v Speaker 2>twenty six percent of our portfolio actually comes from that ecosystem,

0:36:28.600 --> 0:36:31.759
<v Speaker 2>and you know, I think in part that's because you know,

0:36:31.800 --> 0:36:35.000
<v Speaker 2>people continue to see opportunities. Yes, this market is difficult,

0:36:35.000 --> 0:36:36.960
<v Speaker 2>but one of the things that we're excited about is

0:36:37.000 --> 0:36:39.080
<v Speaker 2>the caliber of founders. I think you have to be

0:36:39.200 --> 0:36:41.880
<v Speaker 2>bold and you have to have grit to found companies

0:36:41.920 --> 0:36:45.520
<v Speaker 2>in this in this market, and we're continuing to see that. Actually,

0:36:45.520 --> 0:36:48.440
<v Speaker 2>Pitchbog recently did a study that showed the number of

0:36:48.480 --> 0:36:51.200
<v Speaker 2>founders and the amount of capital that they've raised, and

0:36:51.239 --> 0:36:54.360
<v Speaker 2>if you look at Harvard and MIT graduate programs compared

0:36:54.360 --> 0:36:56.799
<v Speaker 2>to that of Stanford and Berkeley's, it's actually higher here

0:36:56.800 --> 0:36:59.160
<v Speaker 2>in Boston. Another way to think about that is, at

0:36:59.160 --> 0:37:02.520
<v Speaker 2>any given moment, between one and four founders of future

0:37:02.600 --> 0:37:06.280
<v Speaker 2>unicorn companies walking around campus and walking around the halls

0:37:06.320 --> 0:37:10.160
<v Speaker 2>here in the Boston ecosystem. So we're certainly seeing that

0:37:10.320 --> 0:37:14.399
<v Speaker 2>entrepreneurial spirit continued to be to be thriving, and it's

0:37:14.440 --> 0:37:16.440
<v Speaker 2>one of the areas we're most excited to invest it.

0:37:16.480 --> 0:37:18.759
<v Speaker 4>That is an interesting data point. And you know the

0:37:18.800 --> 0:37:20.760
<v Speaker 4>story that we hear all the time in San Francisco.

0:37:20.880 --> 0:37:23.239
<v Speaker 4>I'm in New York this week that in San Francisco's

0:37:23.400 --> 0:37:25.920
<v Speaker 4>I went to Stamford, I studied computer science, and I

0:37:26.000 --> 0:37:27.680
<v Speaker 4>dropped out and I started a company. I did it

0:37:27.680 --> 0:37:30.400
<v Speaker 4>in San Francisco because despite the problem of San Francisco

0:37:30.520 --> 0:37:33.200
<v Speaker 4>is a great place to live and work. If you

0:37:33.280 --> 0:37:35.719
<v Speaker 4>were going to pitch Boston, what is it that's keeping

0:37:35.800 --> 0:37:38.600
<v Speaker 4>those founders in the city where they either studied or

0:37:38.680 --> 0:37:40.160
<v Speaker 4>raised their money from.

0:37:40.719 --> 0:37:43.319
<v Speaker 2>Yeah, there's a lot of this ecosystem to like, you know,

0:37:43.440 --> 0:37:46.359
<v Speaker 2>there's access to world class talent both coming out of

0:37:46.400 --> 0:37:49.200
<v Speaker 2>the university systems, but also coming out of some of

0:37:49.200 --> 0:37:53.839
<v Speaker 2>these homegrown tech giants that I mentioned, like the HubSpot's Toast, Cleavio, Salsafies,

0:37:54.440 --> 0:37:56.680
<v Speaker 2>and some of the big tech giants from the West

0:37:56.680 --> 0:37:58.920
<v Speaker 2>Coast have big offices here, so there's no shortage of

0:37:59.360 --> 0:38:02.000
<v Speaker 2>great talent. And then as I said, you know, it's

0:38:02.000 --> 0:38:03.759
<v Speaker 2>hard to find anywhere else in the world that has

0:38:03.880 --> 0:38:06.240
<v Speaker 2>as much R and D coming out of the labs

0:38:06.239 --> 0:38:09.240
<v Speaker 2>and the ecosystems here. So overall, I think the combination

0:38:09.320 --> 0:38:12.200
<v Speaker 2>of those things, plus there's a thriving ecosystem of accelerators

0:38:12.239 --> 0:38:14.920
<v Speaker 2>and incubators and angels, and I think it has all

0:38:14.960 --> 0:38:18.400
<v Speaker 2>the ingredients you need to be successful. One of the

0:38:18.440 --> 0:38:20.640
<v Speaker 2>things that was interesting is, you know, Boston was thriving

0:38:20.680 --> 0:38:24.080
<v Speaker 2>pre pandemic, but I think post pandemic it's accelerated even more.

0:38:24.120 --> 0:38:26.319
<v Speaker 2>And in part is because we learn you know, West

0:38:26.320 --> 0:38:28.920
<v Speaker 2>Coast investors, I think learned that they could invest outside

0:38:28.920 --> 0:38:31.560
<v Speaker 2>of their backyard. So we're actually seeing more later stage

0:38:31.600 --> 0:38:35.200
<v Speaker 2>investment come into Boston. And actually some of these multi

0:38:35.239 --> 0:38:38.120
<v Speaker 2>geography firms are setting people on the ground here.

0:38:37.920 --> 0:38:40.640
<v Speaker 5>To cover this ecosystem. As a result, for.

0:38:40.600 --> 0:38:42.839
<v Speaker 3>The companies, as you see them to have that lates

0:38:42.880 --> 0:38:45.479
<v Speaker 3>stage funding to Linny Lyman, great has in time general

0:38:45.520 --> 0:38:48.279
<v Speaker 3>panner on the school benure capital on a school VC.

0:38:56.760 --> 0:38:59.400
<v Speaker 1>No, we're not fundamentally worried. We have a very strong

0:38:59.440 --> 0:39:03.040
<v Speaker 1>business in China that has grown significantly over the last

0:39:03.480 --> 0:39:08.120
<v Speaker 1>ten years, and we'll continue to invest in China to

0:39:08.200 --> 0:39:10.200
<v Speaker 1>make sure that we bring the product that the Chinese

0:39:10.200 --> 0:39:11.680
<v Speaker 1>customers are expecting for us.

0:39:13.080 --> 0:39:16.040
<v Speaker 4>There was Mercedes Benz CEO Laclenius there. I was being

0:39:16.040 --> 0:39:19.640
<v Speaker 4>asked whether he's worried about China's automakers and pricing wars,

0:39:19.640 --> 0:39:22.959
<v Speaker 4>which were all global threats. Legacy automakers here like Ford

0:39:23.000 --> 0:39:26.160
<v Speaker 4>Stilantis and Geral Motors have been focusing on as work,

0:39:26.160 --> 0:39:28.320
<v Speaker 4>except that now they also need to contend with another

0:39:28.400 --> 0:39:34.000
<v Speaker 4>internal challenge, auto workers striking for better wages and working conditions.

0:39:34.000 --> 0:39:34.719
<v Speaker 7>It has been going viral.

0:39:34.800 --> 0:39:36.600
<v Speaker 4>Everyone has been talking about it through the weekend in

0:39:36.640 --> 0:39:39.440
<v Speaker 4>the largest auto workers striking years and Caroline. What it

0:39:39.440 --> 0:39:41.440
<v Speaker 4>comes down to and what I hear is like this

0:39:41.520 --> 0:39:45.320
<v Speaker 4>transition to ev the Inflation Reduction Act, money money, money,

0:39:46.080 --> 0:39:48.920
<v Speaker 4>does that money protect? The jobs will then be the

0:39:48.920 --> 0:39:50.880
<v Speaker 4>same number of jobs when we all go electric as

0:39:50.880 --> 0:39:51.879
<v Speaker 4>there are now It's the.

0:39:51.800 --> 0:39:55.440
<v Speaker 3>Same conversation we're having around artificial intelligences. Wells Ultimately that

0:39:55.719 --> 0:40:00.480
<v Speaker 3>technological innovation and investment ends up hurting the work, does it?

0:40:00.480 --> 0:40:00.920
<v Speaker 5>In this case?

0:40:00.920 --> 0:40:01.600
<v Speaker 7>What did you yeah?

0:40:01.640 --> 0:40:04.239
<v Speaker 4>I mean? In the writers and actors strike, it's all

0:40:04.280 --> 0:40:07.719
<v Speaker 4>about their copyright, their intellectual property. The funny thing is

0:40:07.719 --> 0:40:09.080
<v Speaker 4>is that no one gives a straight answer from the

0:40:09.080 --> 0:40:11.960
<v Speaker 4>car side. Doesn't ev need fewer people to build than

0:40:11.960 --> 0:40:14.680
<v Speaker 4>a combustion engine car? And we're still working that one out.

0:40:14.760 --> 0:40:17.759
<v Speaker 3>Kara meanwhile, plenty to debate, and luckily we're here for

0:40:17.800 --> 0:40:18.200
<v Speaker 3>the whole week.

0:40:18.239 --> 0:40:20.400
<v Speaker 5>That does it For this edition of Bloomberg Techology, then check.

0:40:20.280 --> 0:40:22.640
<v Speaker 4>Out the podcast wherever you get yours on the terminal

0:40:22.800 --> 0:40:24.440
<v Speaker 4>and other platforms Apples, Spotify.

0:40:24.560 --> 0:40:26.719
<v Speaker 7>iHeart this, It's Bloomberg Technology