WEBVTT - Car Dealership Cyberattacks and a New AI Research Lab

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<v Speaker 1>From Marhard where Innovation, Money and Power Collie in Silicon Valley, NBN.

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<v Speaker 1>This is Bloomberg Technology with Caroline Hyde and Ed Ludlow.

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<v Speaker 2>I Med Ludlow in San Francisco. Caroline hides off. This

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<v Speaker 2>is Bloomberg technology coming up. Car dealerships across the US

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<v Speaker 2>Wholt services after a cyber attack. Full coverage ahead class

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<v Speaker 2>Open AI co founder Ilia Sutskiva announces a new AI

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<v Speaker 2>research lab.

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<v Speaker 3>We have that exclusive reporting.

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<v Speaker 2>An AI video startup, hey Jen, hits a half billion

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<v Speaker 2>dollar valuation in its latest funding round. We do discuss

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<v Speaker 2>with the CEO a very quick check in on markets.

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<v Speaker 2>The S and P five hundred very briefly hit the

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<v Speaker 2>fifty five hundred historic mark and then pull back with

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<v Speaker 2>flat on the Nasdaq one hundred. Broadly, we're kind of

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<v Speaker 2>treading water after a US holiday. The story, though, is

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<v Speaker 2>individual names in the AI infrastructure play.

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<v Speaker 3>We are talking about.

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<v Speaker 2>Dell, we are talking about super Micro, and of course

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<v Speaker 2>we're talking about in video. Later in the show, we're

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<v Speaker 2>going to bring you details of what played out twenty

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<v Speaker 2>four hours ago on social media, Michael Dell saying that

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<v Speaker 2>Dell is building an AI factory for groc and Xai

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<v Speaker 2>and Elon Musk. Elon Musk coming back on social media

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<v Speaker 2>and saying super Micro's part of the story as well,

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<v Speaker 2>and you can clearly see super Micro the kind of

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<v Speaker 2>biggest beneficiary of.

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<v Speaker 3>That move that's coming up.

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<v Speaker 2>The top story in terms of newsflow is what we

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<v Speaker 2>were talking about a moment ago. Car dealers across the

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<v Speaker 2>United States were affected by a second cyber attack this

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<v Speaker 2>morning after an initial attack yesterday compromised the CDK software

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<v Speaker 2>platform and halted business. These are some of the publicly

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<v Speaker 2>traded dealerships and auto retailers that are impacted in the

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<v Speaker 2>here and now or moving to the downs. Let's get

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<v Speaker 2>to Bloomberg's Jef Stone on our cyber team. Okay, let's

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<v Speaker 2>start with the latest, because it's moving quite quickly. There

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<v Speaker 2>was a second report of an attack this morning.

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<v Speaker 3>What do we know? That's right.

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<v Speaker 1>This is a big, messy cyber attack. You mentioned there's

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<v Speaker 1>a second incident just reported. That happens as this software

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<v Speaker 1>provider that works with more than fifteen thousand dealerships around

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<v Speaker 1>the country is already trying to recover from what looks

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<v Speaker 1>like is going to be a pretty costly outage. The

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<v Speaker 1>nature of the incident isn't quite clear yet. We know

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<v Speaker 1>that dealers are waiting for more information from the company,

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<v Speaker 1>but we know what looks bad.

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<v Speaker 2>Jesse, as I said, you're kind of a key member

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<v Speaker 2>of our cyber security team. What was the vulnerability here,

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<v Speaker 2>What was the security breach and where did it happen?

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<v Speaker 1>The nature of the breach the point of entry is

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<v Speaker 1>certainly still under investigation, but this incident fits with a

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<v Speaker 1>recent string of attacks, certainly in the healthcare sector that

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<v Speaker 1>our targeting kind of customer service software providers and almost

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<v Speaker 1>innocuous companies that a lot of your viewers won't think

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<v Speaker 1>about on a daily basis. These companies sit at a

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<v Speaker 1>key point in various supply chains, and when they are hit,

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<v Speaker 1>there are ripple effects, costly ripple effects that have major

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<v Speaker 1>impact throughout their supply chain.

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<v Speaker 2>Jeff, as you know, I've covered the automotive industry for

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<v Speaker 2>quite a long time, and I've learned so much about

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<v Speaker 2>CDK fifteen thousand customers, front office, back office. But also

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<v Speaker 2>like the names that have been impacted here on the

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<v Speaker 2>name brand side are big ones like Subaru Toyota. What

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<v Speaker 2>have the responses from the company's been and what have

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<v Speaker 2>they actually been telling customers as well.

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<v Speaker 1>Please give us time and some patients. We know that dealerships,

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<v Speaker 1>like I said, are waiting for more instructions from their

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<v Speaker 1>parent companies from CDK as this continues to unfold. For now,

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<v Speaker 1>a lot of dealers are slower to make sales. We

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<v Speaker 1>know that sales representatives are increasingly working with paper transactions

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<v Speaker 1>rather than the quick automatic stuff that we've all become

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<v Speaker 1>used to, so.

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<v Speaker 3>It's very challenging.

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<v Speaker 1>They're waiting for more information.

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<v Speaker 3>Jeff.

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<v Speaker 2>This is one hack in a series of hacks over

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<v Speaker 2>years that you and I have discussed on the show.

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<v Speaker 2>In terms of its scale, where does it sit in

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<v Speaker 2>those that you've covered in recent years?

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<v Speaker 1>Growing the healthcare sector, like I said, has been the

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<v Speaker 1>main focus over the past year eighteen months or so.

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<v Speaker 1>The cost of this, based on the number of dealerships

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<v Speaker 1>certainly affected, seems to be high.

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<v Speaker 3>We're waiting to see.

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<v Speaker 1>If there will be any government action on this, or

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<v Speaker 1>any guidance from the Department of Homeland Security, for instance,

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<v Speaker 1>in terms of understanding the full scope of the incident,

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<v Speaker 1>But for now it's still.

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<v Speaker 2>Calculating blimbergs Jeffstone on a developing story.

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<v Speaker 3>Thank you.

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<v Speaker 2>Another big story we're tracking is over in China, where

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<v Speaker 2>e commerce giants have been slashing prices and using celebrity

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<v Speaker 2>endorsements to boost enthusiasm for the six one eight shopping festival.

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<v Speaker 2>Bloomberg's Henry Wren joins us for more out of London.

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<v Speaker 2>This is a new one for me, Henry. I've been

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<v Speaker 2>reading about six one eight, But if you were to summarize,

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<v Speaker 2>you'd basically say that the consumer in China is getting

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<v Speaker 2>an unprecedented level of incentive this week from the big

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<v Speaker 2>e commerce names.

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<v Speaker 4>Yes, indeed, so we're seeing scenes that we have been expecting.

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<v Speaker 4>For example, the price cuts. You know, PDD, which is

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<v Speaker 4>known for its budget shopping site pindor Door, has been

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<v Speaker 4>keen to let its customers know that it has been

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<v Speaker 4>putting forward the steeper than ever price discounts. But also

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<v Speaker 4>we've been seeing something that's very unexpected. Let's say, for example,

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<v Speaker 4>JD dot COM's funder Richard Devil is appearing on live

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<v Speaker 4>streaming e commerce and it's not humans actually it's a

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<v Speaker 4>digital avatar of him. But also in the meantime, a

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<v Speaker 4>pop star Rihanna, which is who is pretty famous and

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<v Speaker 4>popular in mainland China, as wells since setting a Chinese

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<v Speaker 4>style off pancakes in front of camera. So basically we've

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<v Speaker 4>been seeing everything here with all sorts of promotions.

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<v Speaker 2>We're talking about the names that we always discussed on

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<v Speaker 2>this program, Baba, Pinduoduo, JD. That's the company side of

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<v Speaker 2>the story, but there's also the Chinese consumer side of

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<v Speaker 2>the story that we track so closely here on Bloomberg Technology.

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<v Speaker 2>Is the idea that they're needing to discount so heavily,

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<v Speaker 2>get so creative, I suppose in their incentive a sign

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<v Speaker 2>that the Chinese consumer needs a bit of help.

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<v Speaker 5>Yes.

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<v Speaker 4>Indeed, so the story that we have been reporting what

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<v Speaker 4>over is the Chinese consumers are still quite cautious in

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<v Speaker 4>terms of picking deals, and this has been a trend

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<v Speaker 4>that has been confirmed by this six to one eight

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<v Speaker 4>event as well. The main messa across the merchants has

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<v Speaker 4>been price cuts, which has been seen across those live

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<v Speaker 4>streaming platforms as well as these three big companies. But

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<v Speaker 4>also in the meantime we see local media reporting that

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<v Speaker 4>some categories, for example, women's superos or luxury goods have

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<v Speaker 4>been seen very high return and cancelation rates rates as

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<v Speaker 4>high as seventy five percent to eighty percent, which really

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<v Speaker 4>shows that consumers aren't quite cautious. Yes, they probably are

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<v Speaker 4>spending because of those price cuts, those promotions, but they're

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<v Speaker 4>pretty keen in terms of picking the cheapest deals, not

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<v Speaker 4>necessarily the best in terms of quality.

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<v Speaker 2>Blynd begs Henry Wren, who is all across the China

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<v Speaker 2>tech beat, thank you so much. It's time now for

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<v Speaker 2>talking tech and first up Masayoshi's Sun maybe on the cusps,

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<v Speaker 2>but making a major investment in AI selling shareholders at

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<v Speaker 2>the annual meeting, the SoftBank says they're looking for their

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<v Speaker 2>quote next big move in tech. The comments come after

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<v Speaker 2>the company saw a string of losses through the startup

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<v Speaker 2>bets plus. Open Ai co founder Ilia Sutskova has announced

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<v Speaker 2>a new venture called Safe super Intelligence. The company aims

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<v Speaker 2>to create a secure, powerful AI system with no intentions

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<v Speaker 2>to sell AI products or services like rivals Open Ai

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<v Speaker 2>and Google currently doing. Satskova left open Ai in May,

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<v Speaker 2>just shortly after the return of Sam Autman and the

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<v Speaker 2>ouster he was involved in. And finally, Dell announced that

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<v Speaker 2>it's building out an AI factory with the help of

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<v Speaker 2>Nvidia to power Elon Musk's XAI with super Microcomputer also

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<v Speaker 2>providing servers. The two companies have been adding server capacity

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<v Speaker 2>in recent months in an effort to win more businesses

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<v Speaker 2>making AI expansions.

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<v Speaker 3>Remember that I sat down with.

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<v Speaker 2>Michael Dell last month, who defined an AI factory as

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<v Speaker 2>the following you.

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<v Speaker 6>Get into the ecosystem of all the software and the

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<v Speaker 6>models that you're hearing about, the small and large models,

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<v Speaker 6>the retrieval augmented generation. Of course, it's not just GPUs,

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<v Speaker 6>it's also the networking by storage and the memory that

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<v Speaker 6>come together.

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<v Speaker 3>So let's be honest. That was a lot of buzzwords.

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<v Speaker 2>But we're about to have a conversation where I think

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<v Speaker 2>we can get to the root of what we're talking about,

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<v Speaker 2>and that's with Nancy Tangler of Laffa Tengler Investments. And

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<v Speaker 2>it's interesting, Nantie, because you actually got into Dell following

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<v Speaker 2>earnings May thirtieth, and there was kind of a mixed

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<v Speaker 2>reception to earnings. You know, there's a growth story there

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<v Speaker 2>about AI infrastructure, and there were some near Turk concerns.

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<v Speaker 2>But let's start with why you looked at Dell and thought, Okay,

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<v Speaker 2>this is the move I'm going to make.

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<v Speaker 7>Well, and thank you for having me a couple of reasons.

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<v Speaker 7>I mean, we were late to the party, and that

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<v Speaker 7>will happen from time to time. We've been late to

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<v Speaker 7>other parties. But the point is that you get there.

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<v Speaker 7>And we saw it as an opportunity to step in

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<v Speaker 7>not just on the data center side of the business,

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<v Speaker 7>but the PC upgrade cycle part of the business. And

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<v Speaker 7>so if you look at the hyperscalers they are they

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<v Speaker 7>are spending or spent about two hundred million dollars two

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<v Speaker 7>hundred billion, sorry dollars on AI in their budgets, and

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<v Speaker 7>so we think the use cases are real, the technology

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<v Speaker 7>is real, the monetization is real, and so this was

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<v Speaker 7>an area we were underweight hardware in our tech exposure,

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<v Speaker 7>and this was an area where we could jump in.

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<v Speaker 2>So you do not hold in Nvidia, which is really interesting.

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<v Speaker 2>The big story we're talking about this morning is what

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<v Speaker 2>played out on social media Wednesday that Michael Dell posted

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<v Speaker 2>they're building an AI factory for Xai to power groc

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<v Speaker 2>and Musk responds and says, well, actually super Micro's involved

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<v Speaker 2>as well, So let's do some math, which actually my

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<v Speaker 2>colleagues are Bloomberg Intelligence kindly walked me through this morning.

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<v Speaker 3>If this deal is for Grock three has.

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<v Speaker 2>Said in the past he'll need one hundred thousand, h

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<v Speaker 2>one hundreds for that. And if you assume the average

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<v Speaker 2>price of a rack a server racks about a million dollars,

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<v Speaker 2>there are thirty six in Vida GPUs in each rack.

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<v Speaker 2>You'll need twenty seven hundred racks. That could mean one

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<v Speaker 2>point five billion dollars in bookings for both Dell and

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<v Speaker 2>sm or super Micro. If BI is right about the

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<v Speaker 2>three billion dollar deal value. So you don't hold in Nvidia,

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<v Speaker 2>but you kind of do indirectly through Dell.

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<v Speaker 3>Is that fair?

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<v Speaker 7>Yes, I'm going to take that because you know, it

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<v Speaker 7>seems silly to not be in Nvidia. We have very

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<v Speaker 7>strict valuation metrics, and so I'm waiting for the hedgies

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<v Speaker 7>to go to the Hamptons and then hoping we'll get

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<v Speaker 7>a pullback an Nvidia. But yeah, I think I think

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<v Speaker 7>that is the important thing to be thinking about. That

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<v Speaker 7>that the investment cycle, as the large language models become larger,

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<v Speaker 7>the power needed to generate the metrics around that that

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<v Speaker 7>is going to augur well, not just for in Video,

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<v Speaker 7>but for Dell and for Broadcom, which is we own

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<v Speaker 7>the poor man's in video, which is which is broad Coom,

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<v Speaker 7>and I'm pretty happy with that holding it's up sixty

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<v Speaker 7>five percent year to date or seventy. But you know

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<v Speaker 7>that's that pales in comparison to in Vidia one hundred

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<v Speaker 7>and seventy percent.

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<v Speaker 2>On the valuation question when last I checked. I don't

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<v Speaker 2>have it in front of me now, but I think

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<v Speaker 2>in video trades is something like forty five times, yes,

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<v Speaker 2>twelve month forward earning something like that. And so so

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<v Speaker 2>it's a rules based issue for you. You just called

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<v Speaker 2>Broadcom the poor man's in video because you just extrapolate

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<v Speaker 2>a bit.

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<v Speaker 3>Why you'd say that.

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<v Speaker 7>Well, it's I mean, it's certainly not as much in

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<v Speaker 7>the sweet spot. But Hoktan, who by the way, is

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<v Speaker 7>the highest paid CEO in corporate America. He is a

0:12:45.600 --> 0:12:48.320
<v Speaker 7>master operator of the business. So they've already made you know,

0:12:48.400 --> 0:12:50.800
<v Speaker 7>VMware has been on the books for a quarter. It's

0:12:50.800 --> 0:12:54.559
<v Speaker 7>a creative It smooths out the hardware cycle, and they

0:12:54.600 --> 0:12:58.720
<v Speaker 7>will be facing some competitions, certainly from in Nvidia in

0:12:58.760 --> 0:13:01.640
<v Speaker 7>the networking side of their business. But we just think

0:13:01.760 --> 0:13:04.360
<v Speaker 7>it's a company that it has paid. I mean, we've

0:13:04.400 --> 0:13:06.400
<v Speaker 7>owned it for a long time. It's a member of

0:13:06.400 --> 0:13:09.720
<v Speaker 7>our twelve Best Ideas portfolio, and we continue to like

0:13:09.760 --> 0:13:13.160
<v Speaker 7>it here it's the cheapest of the group. And I

0:13:13.200 --> 0:13:18.840
<v Speaker 7>love these old economy or old technology names like Broadcom, Oracle, Dell,

0:13:19.240 --> 0:13:22.800
<v Speaker 7>who have remade themselves. And that's thanks to strong management

0:13:22.840 --> 0:13:25.440
<v Speaker 7>teams who pivoted when they should have pivoted, just like

0:13:25.520 --> 0:13:29.280
<v Speaker 7>Satya Nadella did at Microsoft, which is another twelve Best

0:13:29.320 --> 0:13:30.280
<v Speaker 7>Ideas named for us.

0:13:31.240 --> 0:13:34.680
<v Speaker 2>One of the other top top stories on Bloomberg today

0:13:34.800 --> 0:13:38.280
<v Speaker 2>is this research note from City and they argue that

0:13:38.679 --> 0:13:43.000
<v Speaker 2>AI is going to displace more jobs in the banking

0:13:43.120 --> 0:13:46.400
<v Speaker 2>sector than any other sector. And I was looking across

0:13:46.480 --> 0:13:50.920
<v Speaker 2>your portfolio, and you have this twelve Best Ideas portfolio.

0:13:50.160 --> 0:13:51.760
<v Speaker 3>Which includes Goldman Sachs.

0:13:52.040 --> 0:13:54.440
<v Speaker 2>So if we stick with the AI theme, what do

0:13:54.480 --> 0:13:57.080
<v Speaker 2>you make of that City call that it's going to

0:13:57.080 --> 0:14:00.600
<v Speaker 2>be in banking where an impact of the world forces

0:14:00.679 --> 0:14:01.720
<v Speaker 2>most felt from AI.

0:14:02.160 --> 0:14:04.240
<v Speaker 7>Yeah, I don't think it's going to be the Goldman

0:14:04.360 --> 0:14:06.920
<v Speaker 7>side of banking. You know, I've been in this business

0:14:06.960 --> 0:14:09.400
<v Speaker 7>for forty years at and I've heard all sorts of

0:14:09.480 --> 0:14:12.920
<v Speaker 7>prognostications about what will happen that never happens.

0:14:13.320 --> 0:14:13.920
<v Speaker 5>I think.

0:14:15.280 --> 0:14:20.640
<v Speaker 7>Artificial intelligence will augment workers, and particularly the kind of workers,

0:14:20.760 --> 0:14:24.560
<v Speaker 7>professional workers that Goldman employs. So I don't think it's

0:14:24.600 --> 0:14:28.120
<v Speaker 7>a bank teller, robo call, you know, side of the

0:14:28.160 --> 0:14:32.120
<v Speaker 7>business that that will be potentially impacted. But that's not Goldman,

0:14:32.200 --> 0:14:35.040
<v Speaker 7>at least not anymore. When sin Save exited retail banking,

0:14:35.360 --> 0:14:37.560
<v Speaker 7>and we think the M and A activity is certainly

0:14:37.600 --> 0:14:38.920
<v Speaker 7>going to accelerate, So.

0:14:39.520 --> 0:14:40.680
<v Speaker 3>We still like it here.

0:14:40.720 --> 0:14:44.360
<v Speaker 7>It's still very cheap based on our work, and so

0:14:44.840 --> 0:14:46.520
<v Speaker 7>you know, I'm not worried about that.

0:14:48.920 --> 0:14:51.280
<v Speaker 2>Henry Wren, who covers China tech for US, was just

0:14:51.320 --> 0:14:55.520
<v Speaker 2>on talking about the Chinese consumer and how many of

0:14:55.560 --> 0:14:58.960
<v Speaker 2>the big Chinese technology names are doing heavy incentive this

0:14:59.080 --> 0:15:02.760
<v Speaker 2>weight week. If there's one thing that keeps Nancy Tangler

0:15:02.840 --> 0:15:04.640
<v Speaker 2>up at night, I think I'm right in saying that

0:15:04.680 --> 0:15:08.760
<v Speaker 2>it's the consumer broadly. But I guess principally in this country.

0:15:09.120 --> 0:15:11.560
<v Speaker 2>Why is it such a concern to you the state

0:15:11.600 --> 0:15:12.320
<v Speaker 2>of the consumer.

0:15:12.560 --> 0:15:15.760
<v Speaker 7>Well, so I think there's two consumers. There's the baby

0:15:15.760 --> 0:15:19.000
<v Speaker 7>boom consumer, which I'm a member of, who has half

0:15:19.080 --> 0:15:22.360
<v Speaker 7>of the country's net worth, and so they're spending. They're

0:15:22.400 --> 0:15:26.080
<v Speaker 7>retired generally speaking, and they're not being impacted by this.

0:15:26.160 --> 0:15:29.120
<v Speaker 7>They have big stock portfolios, but it's the low end

0:15:29.120 --> 0:15:33.600
<v Speaker 7>consumer that's just getting crushed by you know, sticky inflation,

0:15:33.680 --> 0:15:35.440
<v Speaker 7>which is still with us. You know, only on Wall

0:15:35.440 --> 0:15:37.960
<v Speaker 7>Street do we say, oh, inflation is declining because the

0:15:38.040 --> 0:15:41.120
<v Speaker 7>rate of rate of change is going up less fast

0:15:41.240 --> 0:15:44.560
<v Speaker 7>than it was previously. So I think it's wearing on them.

0:15:45.160 --> 0:15:48.280
<v Speaker 7>The interest expense, the access to credit, all of this

0:15:48.360 --> 0:15:50.840
<v Speaker 7>is declined. And then we know that, you know, full

0:15:50.880 --> 0:15:53.360
<v Speaker 7>time jobs declined in March year over year by two

0:15:53.400 --> 0:15:58.280
<v Speaker 7>hundred and seventy five thousand hours work declined, wages in

0:15:58.360 --> 0:16:02.520
<v Speaker 7>terms of our average hour, the earnings declined. So this

0:16:02.600 --> 0:16:05.520
<v Speaker 7>is a problem spot for the economy. And the low

0:16:05.600 --> 0:16:08.840
<v Speaker 7>end of the consumer is end mass much greater in

0:16:08.920 --> 0:16:11.640
<v Speaker 7>numbers than the baby boomers. So I think we have

0:16:11.720 --> 0:16:13.600
<v Speaker 7>to watch this. And the retail sales numbers that they're

0:16:13.640 --> 0:16:18.240
<v Speaker 7>not comprehensive, we're disappointing, and the revisions down we're also disappointing.

0:16:19.600 --> 0:16:23.000
<v Speaker 2>Earning season is once again around the corner. It's silly

0:16:23.040 --> 0:16:27.359
<v Speaker 2>to say, take that concern and give me your expectations

0:16:27.360 --> 0:16:29.200
<v Speaker 2>to technology earnings in particular.

0:16:29.480 --> 0:16:31.480
<v Speaker 7>Oh, I think tech's going to continue to shine and

0:16:31.600 --> 0:16:35.080
<v Speaker 7>Just for the record, we've been advocating overweighting tech since

0:16:35.120 --> 0:16:37.400
<v Speaker 7>the fall of twenty twenty two, when everyone rode it

0:16:37.440 --> 0:16:41.240
<v Speaker 7>off once again as not the place you wanted to be,

0:16:41.320 --> 0:16:43.880
<v Speaker 7>that the tech trade was over, that higher interest rates

0:16:43.880 --> 0:16:46.800
<v Speaker 7>were going to hurt technology companies, because that was an old,

0:16:47.440 --> 0:16:50.280
<v Speaker 7>old school view of the world. But in fact, most

0:16:50.280 --> 0:16:53.600
<v Speaker 7>of the megacap tech names have benefited from higher interest rates.

0:16:53.760 --> 0:16:55.560
<v Speaker 7>So we think earnings is going to continue to be

0:16:55.600 --> 0:16:58.400
<v Speaker 7>a bright spot through this year and into next. And

0:16:58.840 --> 0:17:02.320
<v Speaker 7>so we want to own, you know, the hyperscalers, We

0:17:02.360 --> 0:17:04.960
<v Speaker 7>want to own the hardware companies. And you know they

0:17:04.960 --> 0:17:08.000
<v Speaker 7>wrote off software a few weeks ago, but just wait

0:17:08.040 --> 0:17:09.840
<v Speaker 7>a few weeks and I think the hedge fund guys

0:17:09.840 --> 0:17:13.760
<v Speaker 7>will be back in buying software. So there's my cynical

0:17:13.840 --> 0:17:15.879
<v Speaker 7>view of the way this world works.

0:17:17.119 --> 0:17:17.600
<v Speaker 3>Cynical.

0:17:17.720 --> 0:17:20.199
<v Speaker 2>Maybe I appreciate the omission that you elate to the

0:17:20.240 --> 0:17:22.840
<v Speaker 2>party on Dell, but in the end, you made it

0:17:22.840 --> 0:17:25.800
<v Speaker 2>to the party, and that is what matters. Nancy Tengler

0:17:25.920 --> 0:17:29.080
<v Speaker 2>of Lappetengler Investments, thank you so much. Stick with us,

0:17:29.080 --> 0:17:48.160
<v Speaker 2>We'll be right back. This is Blimberg Technology. Eight former

0:17:48.200 --> 0:17:51.680
<v Speaker 2>employees of SpaceX who were fired in twenty twenty two

0:17:51.800 --> 0:17:56.200
<v Speaker 2>after writing an open letter criticizing Elon Musk. Have now

0:17:56.240 --> 0:18:01.040
<v Speaker 2>filed a lawsuit against SpaceX and CEO mask edging sexual

0:18:01.080 --> 0:18:04.520
<v Speaker 2>harassment and retaliation. We spoke with one of the plaintiffs

0:18:04.560 --> 0:18:06.560
<v Speaker 2>in the suit, Paige Holland Feelin.

0:18:07.359 --> 0:18:11.679
<v Speaker 8>SpaceX employees are encouraged to follow SpaceX and to follow

0:18:11.680 --> 0:18:15.800
<v Speaker 8>Elon Musk on Twitter, and in my orientation, we were

0:18:15.920 --> 0:18:18.320
<v Speaker 8>encouraged to follow him on Twitter. In the employee handbook,

0:18:18.400 --> 0:18:21.359
<v Speaker 8>it mentions that his Twitter feed is a source of

0:18:21.359 --> 0:18:24.920
<v Speaker 8>official company news that's allowed to be shared with the public.

0:18:25.560 --> 0:18:27.240
<v Speaker 8>So if you if you're not following him on Twitter,

0:18:27.240 --> 0:18:32.160
<v Speaker 8>then you're missing things, and actual delivery dates and deadlines

0:18:32.200 --> 0:18:36.959
<v Speaker 8>and functions of entire teams and departments are impacted day

0:18:37.000 --> 0:18:38.639
<v Speaker 8>to day by what he decides to tweet. In the

0:18:38.640 --> 0:18:42.800
<v Speaker 8>middle of the night, he decided to, you know, put

0:18:42.800 --> 0:18:46.560
<v Speaker 8>out a return to office order and talk about it

0:18:46.600 --> 0:18:52.560
<v Speaker 8>on his Twitter, and that became the law. And you know,

0:18:52.600 --> 0:18:55.800
<v Speaker 8>a friend of mine had a Starship delivery date changed

0:18:55.840 --> 0:18:59.200
<v Speaker 8>overnight because it was on Twitter. So now it's now

0:18:59.200 --> 0:19:02.480
<v Speaker 8>it's law. So it's not just the nonsense, but the

0:19:02.520 --> 0:19:06.680
<v Speaker 8>stuff that impacts people's actual day to day work functionality

0:19:06.840 --> 0:19:10.840
<v Speaker 8>is tweeted about, and then since he's already said it

0:19:10.840 --> 0:19:14.680
<v Speaker 8>and it's public, it's now written into the official plan.

0:19:15.560 --> 0:19:18.840
<v Speaker 9>It was interesting that you said you felt like an

0:19:18.840 --> 0:19:23.480
<v Speaker 9>outside another because that you're female. But many would say, look,

0:19:23.520 --> 0:19:27.360
<v Speaker 9>the person actually running the show, the CEO, Gwyn shotwell,

0:19:27.840 --> 0:19:31.720
<v Speaker 9>female too. How is her voice not allowing your voice.

0:19:31.520 --> 0:19:32.360
<v Speaker 10>To be heard?

0:19:33.600 --> 0:19:35.760
<v Speaker 8>She is very much part of the problem. I think

0:19:35.800 --> 0:19:40.679
<v Speaker 8>that she comes from a generation of just a different

0:19:41.760 --> 0:19:45.600
<v Speaker 8>perspective maybe, but she's so ingrained in the culture there

0:19:45.800 --> 0:19:49.880
<v Speaker 8>and the lifestyle that she's not willing to.

0:19:51.320 --> 0:19:52.760
<v Speaker 11>Rock the boat at all at this point.

0:19:53.920 --> 0:19:56.120
<v Speaker 8>She's very much not the adult in the room that

0:19:56.320 --> 0:19:58.200
<v Speaker 8>the rest of the world kind of makes her out

0:19:58.200 --> 0:20:01.240
<v Speaker 8>to be. She is a huge part of the problem.

0:20:01.359 --> 0:20:04.760
<v Speaker 8>I think it's this brand of kind of I want

0:20:04.760 --> 0:20:08.560
<v Speaker 8>to say, like girl boss feminism that doesn't really uplift

0:20:08.600 --> 0:20:14.120
<v Speaker 8>those around you. Doesn't feel the need to open your

0:20:14.119 --> 0:20:17.159
<v Speaker 8>eyes to the very real concerns of people around you.

0:20:18.640 --> 0:20:21.080
<v Speaker 8>She likes when people have conversations you pay. She will

0:20:21.119 --> 0:20:25.120
<v Speaker 8>focus on a one counterpoint to a valid argument as

0:20:25.119 --> 0:20:29.560
<v Speaker 8>a means of dismissing the entire argument, which is disingenuous

0:20:29.720 --> 0:20:31.200
<v Speaker 8>and really in bad face.

0:20:32.359 --> 0:20:36.000
<v Speaker 9>You have that full suit, and I'm interested to know

0:20:36.080 --> 0:20:39.160
<v Speaker 9>what you hope to get out of this page.

0:20:39.840 --> 0:20:44.840
<v Speaker 8>Accountability most of all. But I think I think accountability

0:20:44.920 --> 0:20:50.520
<v Speaker 8>because the leadership forms the culture so much, and because

0:20:50.560 --> 0:20:55.160
<v Speaker 8>it's such a painful place to work, and having being

0:20:55.200 --> 0:20:57.320
<v Speaker 8>working at SpaceX and open doors for you elsewhere, and

0:20:57.359 --> 0:20:59.399
<v Speaker 8>so it's really amazing opportunity, and I don't think that

0:20:59.400 --> 0:21:04.520
<v Speaker 8>that opportunity should be constrained to the people who are,

0:21:05.880 --> 0:21:12.600
<v Speaker 8>you know, the typical engineering demographic. There are voices and

0:21:13.600 --> 0:21:15.959
<v Speaker 8>perspectives to be heard that can contribute in a meaningful

0:21:15.960 --> 0:21:18.320
<v Speaker 8>way that don't you know, look like the status quo.

0:21:18.400 --> 0:21:23.440
<v Speaker 8>But aside from that, I think speaking up and telling

0:21:23.520 --> 0:21:26.720
<v Speaker 8>my story hopefully will help other people who you know,

0:21:26.800 --> 0:21:28.760
<v Speaker 8>look around them and don't see anyone else that looks

0:21:28.760 --> 0:21:31.920
<v Speaker 8>like them and don't know that their experiences aren't isolated

0:21:31.960 --> 0:21:35.560
<v Speaker 8>to their own experiences, can speak up and share the

0:21:35.600 --> 0:21:37.520
<v Speaker 8>stories around them. I'm hoping to kind of open up

0:21:37.520 --> 0:21:41.760
<v Speaker 8>the platform to let people of all marginalized groups have

0:21:41.800 --> 0:21:44.800
<v Speaker 8>these conversations and feel safe, because I think it's fundamentally

0:21:44.840 --> 0:21:46.280
<v Speaker 8>it should be a human right to feel safe in

0:21:46.280 --> 0:21:46.760
<v Speaker 8>the workplace.

0:21:48.359 --> 0:21:51.639
<v Speaker 2>Bloomberg Technology reached out to SpaceX and Elon Musk for

0:21:51.720 --> 0:21:54.760
<v Speaker 2>comment on the suit and the allegations made by Holland Feelen,

0:21:54.840 --> 0:21:58.400
<v Speaker 2>but they did not respond. SpaceX has previously denied any

0:21:58.400 --> 0:22:01.679
<v Speaker 2>wrongdoing and said that the fired employees involved in the

0:22:01.760 --> 0:22:05.240
<v Speaker 2>case violated policy. It also said Musk himself was not

0:22:05.320 --> 0:22:09.560
<v Speaker 2>involved in those terminations. Gwinshortwell also didn't comment. We continue

0:22:09.600 --> 0:22:11.879
<v Speaker 2>to track the story and if SpaceX want to talk,

0:22:12.160 --> 0:22:24.560
<v Speaker 2>they're always welcome on the show. This is Bloomberg. Welcome

0:22:24.560 --> 0:22:27.679
<v Speaker 2>back to Boomberg Technology. Ed Ludlow in San Francisco. A

0:22:27.720 --> 0:22:29.199
<v Speaker 2>quick check in on the market, So I always go

0:22:29.280 --> 0:22:32.160
<v Speaker 2>to the NAZE one hundred. It's kind of this tech

0:22:32.240 --> 0:22:36.080
<v Speaker 2>heavy index, a lot of higher multiple names AI as

0:22:36.080 --> 0:22:38.479
<v Speaker 2>a story plays out, but we are essentially flat as

0:22:38.480 --> 0:22:40.960
<v Speaker 2>a pancake. Remember it was a market's holiday in the

0:22:41.000 --> 0:22:42.000
<v Speaker 2>US and Wednesday.

0:22:42.440 --> 0:22:45.840
<v Speaker 3>But one real clear mover to the upside is in Vidia.

0:22:46.440 --> 0:22:48.160
<v Speaker 3>In Vidia continuing to push.

0:22:48.040 --> 0:22:52.920
<v Speaker 2>Higher and Nvidia is now the world's most valuable company

0:22:53.359 --> 0:22:56.840
<v Speaker 2>by market cap. A big part of the story in

0:22:56.960 --> 0:22:59.800
<v Speaker 2>Thursday session was something that played out in social media.

0:23:00.040 --> 0:23:02.760
<v Speaker 2>Talked about it earlier in the program. Michael Dell, the

0:23:02.840 --> 0:23:06.359
<v Speaker 2>Dell CEO, taking to x saying that they're making an

0:23:06.400 --> 0:23:11.320
<v Speaker 2>AI factory for Xai to power grock Mask, in response

0:23:11.400 --> 0:23:14.040
<v Speaker 2>to some other user comments, said super Micro is also

0:23:14.119 --> 0:23:19.240
<v Speaker 2>going to be providing server rack and server design to Xai,

0:23:19.280 --> 0:23:22.080
<v Speaker 2>and you can see that actually, in truth, super Micro

0:23:22.640 --> 0:23:25.040
<v Speaker 2>the bigger beneficiary of the two, but both getting a

0:23:25.040 --> 0:23:27.400
<v Speaker 2>push to the upside what they have in common. They

0:23:27.520 --> 0:23:31.480
<v Speaker 2>just provide the integration of that server rack, but it's

0:23:31.520 --> 0:23:34.040
<v Speaker 2>the Nvidia GPU at the heart of it that powers

0:23:34.080 --> 0:23:37.800
<v Speaker 2>it interesting in public markets, we continue to cover what's

0:23:37.800 --> 0:23:41.720
<v Speaker 2>happening in AI and private companies as well. Open ai

0:23:41.800 --> 0:23:45.000
<v Speaker 2>co founder Ilia Sutskova, who took part in the twenty

0:23:45.040 --> 0:23:49.120
<v Speaker 2>twenty three board ouster of Sam Outman, has disclosed plans

0:23:49.200 --> 0:23:53.320
<v Speaker 2>to continue his work at a new research lab focused

0:23:53.480 --> 0:23:57.960
<v Speaker 2>on artificial general intelligence. For more, let's bringing in an

0:23:58.000 --> 0:24:01.560
<v Speaker 2>our AI editor Bloomberg Seffagen and in New York City,

0:24:02.520 --> 0:24:05.639
<v Speaker 2>we have a new startup. The startup has a clear

0:24:06.119 --> 0:24:08.120
<v Speaker 2>mission and remit give us the details.

0:24:08.480 --> 0:24:11.120
<v Speaker 10>Yeah, you know, we actually don't know too many details here.

0:24:11.160 --> 0:24:13.320
<v Speaker 10>For the last six months, everyone has been wondering where

0:24:13.440 --> 0:24:15.119
<v Speaker 10>is Ilia and what is the next thing going to

0:24:15.119 --> 0:24:16.720
<v Speaker 10>be And at this point we seem to have an

0:24:16.760 --> 0:24:20.439
<v Speaker 10>idea he'll have a research lab that is building a

0:24:20.560 --> 0:24:24.120
<v Speaker 10>future theoretical version of a super intelligent AI that would

0:24:24.160 --> 0:24:27.240
<v Speaker 10>be smarter than and outperform humans if it ever comes

0:24:27.280 --> 0:24:30.480
<v Speaker 10>to exist. What they're not doing is trying to commercialize

0:24:30.480 --> 0:24:32.720
<v Speaker 10>those products, at least not yet. So it's a very

0:24:32.760 --> 0:24:36.119
<v Speaker 10>different path than his prior company, open AI, And I

0:24:36.160 --> 0:24:38.960
<v Speaker 10>think that the biggest question is why when when we

0:24:38.960 --> 0:24:41.359
<v Speaker 10>start to see any progress on that front, and two,

0:24:41.440 --> 0:24:44.280
<v Speaker 10>who's going to ultimately end up staffing that company? Will

0:24:44.280 --> 0:24:47.040
<v Speaker 10>we see him and his new company start to hire

0:24:47.400 --> 0:24:50.919
<v Speaker 10>disaffected former colleagues from open ai and other startups in

0:24:50.920 --> 0:24:51.480
<v Speaker 10>the industry.

0:24:52.240 --> 0:24:56.640
<v Speaker 2>The venture is called Safe super Intelligence, And the main

0:24:56.680 --> 0:24:59.040
<v Speaker 2>pledge that I see is is exactly.

0:24:58.640 --> 0:24:59.959
<v Speaker 3>That no commercial product.

0:25:00.080 --> 0:25:04.920
<v Speaker 2>They won't sell anything until they have the definitive I

0:25:04.960 --> 0:25:08.760
<v Speaker 2>don't even want to say product, they have definitive artificial

0:25:08.840 --> 0:25:09.800
<v Speaker 2>general intelligence.

0:25:09.920 --> 0:25:11.359
<v Speaker 3>But the inference is that.

0:25:11.880 --> 0:25:15.560
<v Speaker 2>Ilia didn't share and we've talked so much about this

0:25:15.680 --> 0:25:17.840
<v Speaker 2>seth you know, Sharene's coming up on the show in

0:25:17.880 --> 0:25:19.680
<v Speaker 2>a moment, and she's been on this show talking about

0:25:19.680 --> 0:25:22.600
<v Speaker 2>it a lot. The inference is that Ilia did not

0:25:22.840 --> 0:25:29.400
<v Speaker 2>agree with Sam Autman prioritizing the commercialization of AI technology.

0:25:29.720 --> 0:25:31.480
<v Speaker 2>He's kind of going back to the R and D

0:25:31.880 --> 0:25:33.040
<v Speaker 2>and academic side of this.

0:25:33.320 --> 0:25:33.960
<v Speaker 3>I think that's right.

0:25:34.000 --> 0:25:36.840
<v Speaker 10>There's so much unspoken here, and Ilia has been very

0:25:36.960 --> 0:25:39.760
<v Speaker 10>quiet on how he actually feels about Sam Aulman's leadership

0:25:39.800 --> 0:25:42.040
<v Speaker 10>and the company broadly, but just in the way this

0:25:42.119 --> 0:25:44.960
<v Speaker 10>has been structured. It feels like a repuviation of the

0:25:45.000 --> 0:25:47.200
<v Speaker 10>way that OBAMIAI has been upbreaing of the last year

0:25:47.280 --> 0:25:47.439
<v Speaker 10>or so.

0:25:48.760 --> 0:25:51.720
<v Speaker 2>This was a story that Bloomberg's actually vance broken. Business

0:25:51.760 --> 0:25:54.200
<v Speaker 2>Week highly recommend you go and read the very long

0:25:54.840 --> 0:25:57.399
<v Speaker 2>and detailed, sort of unveiled but Bloomberg seth agmen, we

0:25:57.440 --> 0:25:59.840
<v Speaker 2>really appreciate having you on the program.

0:26:00.080 --> 0:26:00.680
<v Speaker 3>Stick with AI.

0:26:00.840 --> 0:26:04.800
<v Speaker 2>Artificial intelligence startup Anthropic is releasing a new AI model

0:26:04.800 --> 0:26:08.520
<v Speaker 2>that it calls its fastest and most capable yet in

0:26:08.600 --> 0:26:12.080
<v Speaker 2>its rivalry against open ai. A Bloomberg shuring Gafari is

0:26:12.080 --> 0:26:15.040
<v Speaker 2>here on set. You know, we track Anthropic so closely

0:26:15.080 --> 0:26:20.080
<v Speaker 2>because it's so well funded. It is believed by industry

0:26:20.119 --> 0:26:22.400
<v Speaker 2>to be as sort of near incompetence to open AI.

0:26:23.560 --> 0:26:26.600
<v Speaker 2>The specifics of this models, please, its name, what it's

0:26:26.640 --> 0:26:27.600
<v Speaker 2>for sure.

0:26:27.640 --> 0:26:30.840
<v Speaker 5>So the new model is called Claude three point five Sonnet.

0:26:31.040 --> 0:26:34.240
<v Speaker 5>It's coming only three months after Anthropic release its last

0:26:34.359 --> 0:26:37.960
<v Speaker 5>most powerful model, right, Claude three point five, And what

0:26:37.960 --> 0:26:40.440
<v Speaker 5>they're claiming is that it's actually ahead of open ai

0:26:40.600 --> 0:26:44.920
<v Speaker 5>on several key evaluations around reasoning, around things like coding

0:26:44.960 --> 0:26:48.000
<v Speaker 5>and math, and you know, it just shows how quickly

0:26:48.080 --> 0:26:50.480
<v Speaker 5>these companies are really on the heels of each other

0:26:50.520 --> 0:26:53.080
<v Speaker 5>trying to come out with the latest and greatest models.

0:26:53.920 --> 0:26:57.399
<v Speaker 2>How does Anthropic operate in a way that is different

0:26:57.520 --> 0:26:59.560
<v Speaker 2>or similar to open Ai? When I was on social

0:26:59.600 --> 0:27:01.199
<v Speaker 2>media and I saw lots of people say, oh, I

0:27:01.240 --> 0:27:04.400
<v Speaker 2>was involved in early beta access to three point five,

0:27:04.480 --> 0:27:06.600
<v Speaker 2>so on it and I have the following opinions. So

0:27:06.800 --> 0:27:10.360
<v Speaker 2>they appear to do a careful rollout, but it also

0:27:10.400 --> 0:27:13.280
<v Speaker 2>seems very quick to make a product that they I

0:27:13.320 --> 0:27:14.439
<v Speaker 2>assume they can sell.

0:27:15.280 --> 0:27:15.720
<v Speaker 3>That's right.

0:27:15.760 --> 0:27:19.199
<v Speaker 5>So Anthropic has been focusing much more on enterprise customers

0:27:19.240 --> 0:27:22.280
<v Speaker 5>as a number one priority as compared to OpenAI. I

0:27:22.359 --> 0:27:24.960
<v Speaker 5>talked to co founder and president Danielle Amadai have a

0:27:24.960 --> 0:27:27.960
<v Speaker 5>company who told me that they're not distracted quote unquote

0:27:27.960 --> 0:27:31.320
<v Speaker 5>by things like coming up with image generation of a

0:27:31.400 --> 0:27:33.520
<v Speaker 5>cat on a snowboard, and she said that sort of jokingly,

0:27:33.840 --> 0:27:35.600
<v Speaker 5>but it's true that if you compare the two companies,

0:27:35.600 --> 0:27:39.160
<v Speaker 5>Anthropic is a lot more focused on they say, use

0:27:39.160 --> 0:27:41.640
<v Speaker 5>cases that are specific to the business enterprise customer.

0:27:41.840 --> 0:27:44.120
<v Speaker 2>Do we have any sort of case studies of how

0:27:45.119 --> 0:27:47.399
<v Speaker 2>clawed three point fives on it will be used or

0:27:47.440 --> 0:27:50.360
<v Speaker 2>like how it's any different or capable to prior models.

0:27:50.880 --> 0:27:52.920
<v Speaker 5>Yeah, So the company has talked about how it's being

0:27:53.040 --> 0:27:56.480
<v Speaker 5>used more for things like financial analysis. They've also talked

0:27:56.480 --> 0:28:00.080
<v Speaker 5>about partnering with drug companies like Pfizer to help with

0:28:00.119 --> 0:28:02.960
<v Speaker 5>research and discovery, which is also something that open ai

0:28:03.080 --> 0:28:05.000
<v Speaker 5>is starting to do. So we're starting to see more

0:28:05.040 --> 0:28:07.440
<v Speaker 5>kind of close integrations of these tools in the enterprise.

0:28:07.840 --> 0:28:10.919
<v Speaker 2>Bloomberg Shrien Gafari one of the absolute rock stars of

0:28:11.000 --> 0:28:12.280
<v Speaker 2>art Official Intelligence Coverage.

0:28:12.280 --> 0:28:13.320
<v Speaker 3>It's great to have you on set.

0:28:13.440 --> 0:28:15.359
<v Speaker 2>Okay, coming up on the show, we're going to be

0:28:15.440 --> 0:28:18.359
<v Speaker 2>joined by Devon Kirk, a partner at Portage, for a

0:28:18.359 --> 0:28:21.080
<v Speaker 2>look at the global fintech industry. This is something we've

0:28:21.080 --> 0:28:23.119
<v Speaker 2>covered a lot on the show of late the battle

0:28:23.160 --> 0:28:25.840
<v Speaker 2>for talent and the impact of AI on fintech. Stay

0:28:25.880 --> 0:28:27.960
<v Speaker 2>with us they're going to take a short break. We'll

0:28:27.960 --> 0:28:47.680
<v Speaker 2>be right back with you. This is Bloomberg and Technology. Okay,

0:28:47.680 --> 0:28:48.880
<v Speaker 2>We're going to take a look at the world of

0:28:49.040 --> 0:28:52.600
<v Speaker 2>fintech with Devon Kirk, partner at the global fintech focus

0:28:52.680 --> 0:28:55.440
<v Speaker 2>firm Portage, which has two point five billion dollars in

0:28:55.480 --> 0:28:57.800
<v Speaker 2>assets under management. It's also the co head of the

0:28:57.840 --> 0:29:01.760
<v Speaker 2>Portage Capital Solution strategy, where they focus on growth equity,

0:29:01.880 --> 0:29:07.120
<v Speaker 2>structured equity, and special situations investments in financial technology, financial

0:29:07.160 --> 0:29:09.280
<v Speaker 2>services companies that operate globally.

0:29:09.280 --> 0:29:11.040
<v Speaker 3>And I'm really interested had this conversation.

0:29:11.080 --> 0:29:13.680
<v Speaker 2>We've had all kinds of fintech names on the show

0:29:13.720 --> 0:29:16.880
<v Speaker 2>from around the world, actually just in the last few weeks.

0:29:17.280 --> 0:29:19.240
<v Speaker 2>And the sense I get is this kind of a

0:29:19.280 --> 0:29:24.280
<v Speaker 2>bifurcation of how companies are moving in Europe and how

0:29:24.320 --> 0:29:26.920
<v Speaker 2>they're moving in the United States, particularly those that might

0:29:26.960 --> 0:29:31.000
<v Speaker 2>have been venture backed grown rapidly, but now they're trying

0:29:31.000 --> 0:29:34.120
<v Speaker 2>to scale around the world. Would you say that's a

0:29:34.160 --> 0:29:35.320
<v Speaker 2>fair thesis.

0:29:36.680 --> 0:29:37.560
<v Speaker 11>I think that's right.

0:29:37.720 --> 0:29:41.520
<v Speaker 12>Certainly, we're seeing in the US the activity is picking

0:29:41.640 --> 0:29:45.080
<v Speaker 12>up and the fintech space valuations are starting to recover,

0:29:45.280 --> 0:29:49.040
<v Speaker 12>especially in the B two C segment and there's more

0:29:49.080 --> 0:29:54.360
<v Speaker 12>optimism around the IPO markets reopening, but in Europe.

0:29:54.440 --> 0:29:56.080
<v Speaker 11>Things continue to be slower.

0:29:56.120 --> 0:29:58.880
<v Speaker 12>From a growth equity perspective, We're starting to see a

0:29:58.880 --> 0:30:02.560
<v Speaker 12>bit more and activity in Europe, so that's you know,

0:30:02.640 --> 0:30:06.400
<v Speaker 12>one path to liquidity for growth equity investors that helps

0:30:06.400 --> 0:30:10.040
<v Speaker 12>to support that market, but overall it is a more

0:30:10.120 --> 0:30:12.040
<v Speaker 12>viewted environment in Europe right now.

0:30:13.080 --> 0:30:14.240
<v Speaker 3>What are the reasons why?

0:30:14.360 --> 0:30:17.760
<v Speaker 2>You know, I've covered all kinds of industries and sectors

0:30:17.760 --> 0:30:19.840
<v Speaker 2>over the last six years or so that I've been

0:30:19.880 --> 0:30:23.280
<v Speaker 2>in Silicon Valley in the Bay Area in particular, where

0:30:23.320 --> 0:30:27.200
<v Speaker 2>growth equity has been very active and you actually get

0:30:27.800 --> 0:30:31.280
<v Speaker 2>sort of legacy finance names that come in and support

0:30:31.280 --> 0:30:34.760
<v Speaker 2>what we would regard as being technology companies, particularly, you know,

0:30:34.920 --> 0:30:39.000
<v Speaker 2>just prior to IPO. Why is that that activity and

0:30:39.080 --> 0:30:41.160
<v Speaker 2>interest not happening in Europe.

0:30:42.720 --> 0:30:44.160
<v Speaker 11>Well, I think there's a few dynamics.

0:30:44.160 --> 0:30:48.040
<v Speaker 12>As you know, European markets have always been a little

0:30:48.040 --> 0:30:53.240
<v Speaker 12>more fickle in their appetite for growth opportunities within the

0:30:53.880 --> 0:30:54.960
<v Speaker 12>IPO markets.

0:30:55.240 --> 0:30:55.960
<v Speaker 11>But I think there's a.

0:30:55.960 --> 0:31:00.000
<v Speaker 12>Dynamic specific to fintech where there's a much higher prevalence

0:31:00.240 --> 0:31:02.520
<v Speaker 12>of FinTechs with bank charters in Europe.

0:31:02.600 --> 0:31:05.680
<v Speaker 11>Than you see in the US, and that does tie.

0:31:05.480 --> 0:31:07.600
<v Speaker 12>Their hands a little bit in terms of the options

0:31:07.640 --> 0:31:11.320
<v Speaker 12>available for them to raise capital in this market environment

0:31:11.360 --> 0:31:13.040
<v Speaker 12>where valuations have been.

0:31:12.920 --> 0:31:14.280
<v Speaker 11>A bit Whipsod.

0:31:15.600 --> 0:31:15.880
<v Speaker 3>Devin.

0:31:15.920 --> 0:31:18.280
<v Speaker 2>One of the most read stories on Bloomberg this morning

0:31:18.840 --> 0:31:22.600
<v Speaker 2>is about a research note from City who say that

0:31:22.880 --> 0:31:29.120
<v Speaker 2>artificial intelligence will displace the most jobs or in terms

0:31:29.120 --> 0:31:33.200
<v Speaker 2>of displacement, be most felt in banking versus other sectors.

0:31:33.840 --> 0:31:35.720
<v Speaker 3>Is that something that you see happening.

0:31:37.360 --> 0:31:41.360
<v Speaker 12>Yeah, we absolutely see a huge opportunity for AI within

0:31:41.680 --> 0:31:43.000
<v Speaker 12>financial services.

0:31:44.040 --> 0:31:47.000
<v Speaker 11>The volume of activity.

0:31:46.440 --> 0:31:49.880
<v Speaker 12>That is happening in that space, the more repeat nature

0:31:50.440 --> 0:31:55.560
<v Speaker 12>of many interactions and forms of analysis allow for really

0:31:55.680 --> 0:31:59.200
<v Speaker 12>nice use cases for machine learning as well as generative

0:31:59.240 --> 0:32:04.040
<v Speaker 12>at AI. What we are seeing though, is that that

0:32:04.280 --> 0:32:07.400
<v Speaker 12>within the sector we expect, you know, data sets will

0:32:07.400 --> 0:32:12.840
<v Speaker 12>really drive the winners for how AI gets applied and

0:32:13.000 --> 0:32:16.840
<v Speaker 12>AI itself. You know, the strength of your AI capabilities

0:32:17.160 --> 0:32:18.960
<v Speaker 12>is going to be less of a differentiator.

0:32:20.920 --> 0:32:24.880
<v Speaker 2>I like having you on because you are sizable, firm

0:32:24.880 --> 0:32:28.840
<v Speaker 2>at scale and you operate in multiple jurisdictions. So where

0:32:28.880 --> 0:32:31.400
<v Speaker 2>are are you putting money to work and writing checks

0:32:31.440 --> 0:32:31.840
<v Speaker 2>right now?

0:32:33.040 --> 0:32:36.000
<v Speaker 12>So to your point around AI RegTech is an area

0:32:36.000 --> 0:32:38.760
<v Speaker 12>that we're really excited about. We see lots of opportunities

0:32:38.800 --> 0:32:43.320
<v Speaker 12>for technology disruption there. We're also spending you know, increasing

0:32:43.400 --> 0:32:46.120
<v Speaker 12>time around consumer finance. You know, that's an area that's

0:32:46.120 --> 0:32:48.360
<v Speaker 12>been hit hard over the last few years, but we

0:32:48.400 --> 0:32:50.800
<v Speaker 12>think we're at a point now where there's some stronger

0:32:50.840 --> 0:32:54.800
<v Speaker 12>business models that we're excited to back. We're also continuing

0:32:54.840 --> 0:32:58.080
<v Speaker 12>to spend time around vertical SaaS and the opportunities for

0:32:58.200 --> 0:33:04.880
<v Speaker 12>embedded financial services, particularly payments in many more traditional software businesses.

0:33:04.960 --> 0:33:06.840
<v Speaker 11>So, you know, those are some of the themes that

0:33:06.880 --> 0:33:07.680
<v Speaker 11>we're playing with.

0:33:07.800 --> 0:33:11.920
<v Speaker 12>But from a geographic perspective, as you mentioned, we're active

0:33:11.960 --> 0:33:14.640
<v Speaker 12>across North America and Europe.

0:33:15.520 --> 0:33:17.960
<v Speaker 2>I like the idea of reg tech, you know reg

0:33:18.000 --> 0:33:21.640
<v Speaker 2>tech or regulatory tech, but my understanding is that those

0:33:21.640 --> 0:33:26.040
<v Speaker 2>are largely software companies that are focused on process right,

0:33:26.160 --> 0:33:29.720
<v Speaker 2>helping companies make sure they're either compliant or they're adhering

0:33:29.720 --> 0:33:34.320
<v Speaker 2>to whatever sector specific regulatory requirement is in front of them.

0:33:35.200 --> 0:33:40.560
<v Speaker 3>How do you be innovative in a space like that, Well.

0:33:40.400 --> 0:33:42.960
<v Speaker 12>I think the innovation comes from, you know, how you

0:33:43.080 --> 0:33:48.160
<v Speaker 12>drive efficiencies right. Everyone across North America and Europe and

0:33:48.200 --> 0:33:51.160
<v Speaker 12>the traditional financial services world is looking for.

0:33:51.040 --> 0:33:53.720
<v Speaker 11>How they can take out cost.

0:33:53.520 --> 0:33:59.160
<v Speaker 12>And really grow their businesses with fewer regulatory inhibitants. But

0:33:59.240 --> 0:34:04.560
<v Speaker 12>I would also say, you know, regulatory change is one

0:34:04.600 --> 0:34:10.120
<v Speaker 12>of the toughest strategic challenges for financial services businesses to manage,

0:34:10.160 --> 0:34:12.520
<v Speaker 12>and so tools that allow them to do that more

0:34:12.520 --> 0:34:16.000
<v Speaker 12>efficiently are ultimately tools that enable them to be more

0:34:16.120 --> 0:34:19.960
<v Speaker 12>innovative in various elements of their business. And so we

0:34:20.040 --> 0:34:25.040
<v Speaker 12>see reg tech and managing reg elatory environments effectively as

0:34:25.120 --> 0:34:28.040
<v Speaker 12>really an important enabler for innovation for the sector.

0:34:28.960 --> 0:34:32.680
<v Speaker 2>Devin, you join us from Toronto. You've cast your eye

0:34:32.719 --> 0:34:36.480
<v Speaker 2>over Europe. We've talked about the United States. Which jurisdiction

0:34:36.640 --> 0:34:40.239
<v Speaker 2>do you think is the best environment from a regulatory

0:34:40.239 --> 0:34:43.799
<v Speaker 2>standpoint right now that allows for innovation, that allows for

0:34:43.800 --> 0:34:47.280
<v Speaker 2>a market where sort of technology progress is rewarded.

0:34:48.920 --> 0:34:51.680
<v Speaker 12>We can continue to see the US as a leader

0:34:52.400 --> 0:34:54.080
<v Speaker 12>in enabling innovation.

0:34:54.239 --> 0:34:55.760
<v Speaker 11>There's pockets, you know, if you think.

0:34:55.600 --> 0:35:02.480
<v Speaker 12>About account to account transactions, open banking, EUROPN regulators have

0:35:02.600 --> 0:35:05.640
<v Speaker 12>really led the way, But overall we see the US

0:35:05.800 --> 0:35:07.399
<v Speaker 12>environment as being.

0:35:07.440 --> 0:35:08.840
<v Speaker 11>A really attractive one.

0:35:09.520 --> 0:35:12.080
<v Speaker 12>There's pockets right now if you think about banking as

0:35:12.080 --> 0:35:15.520
<v Speaker 12>a service, for example, where there's a lot of regulatory

0:35:15.600 --> 0:35:18.880
<v Speaker 12>dynamics for companies to digest, but overall, we see it

0:35:18.920 --> 0:35:22.640
<v Speaker 12>as a constructive environment and most importantly a large environment

0:35:22.719 --> 0:35:26.720
<v Speaker 12>where there's the market opportunity to support investing in innovation.

0:35:27.280 --> 0:35:30.840
<v Speaker 2>Devin Kirk, Portage Partner and Portage Capital Solution Strategy COHED.

0:35:30.880 --> 0:35:31.319
<v Speaker 3>I like that.

0:35:31.400 --> 0:35:34.280
<v Speaker 2>I can't remember the first time we use the frame

0:35:34.440 --> 0:35:37.440
<v Speaker 2>phrase RegTech. But if you're out there and you're work

0:35:37.480 --> 0:35:39.759
<v Speaker 2>in compliance and you have strong fings about it, get

0:35:39.760 --> 0:35:43.200
<v Speaker 2>in touch. We appreciate it, all right, thank you.

0:35:50.000 --> 0:35:53.640
<v Speaker 13>In the early days of computer programming, a significant historical

0:35:53.719 --> 0:35:55.879
<v Speaker 13>anecdote is known as Grace Hopper and.

0:35:55.920 --> 0:35:59.440
<v Speaker 3>The fuck that was not a real person?

0:36:00.080 --> 0:36:03.960
<v Speaker 2>An avatar of Joshua's You the CEO of hey Jen,

0:36:04.120 --> 0:36:08.719
<v Speaker 2>an ai startup that let's users quickly create realistic looking avatars,

0:36:09.000 --> 0:36:11.600
<v Speaker 2>and the companies just announced a sixty million dollars series

0:36:11.640 --> 0:36:14.879
<v Speaker 2>A led by Benchmark, valuing the company at more than

0:36:15.000 --> 0:36:20.880
<v Speaker 2>five hundred million dollars, and Heygen's real life CEO, Joshua

0:36:20.960 --> 0:36:24.399
<v Speaker 2>ju joins me here on set. It was an interesting video.

0:36:24.400 --> 0:36:27.000
<v Speaker 2>We'll bring it back up again, but just explain what

0:36:27.080 --> 0:36:28.760
<v Speaker 2>it was that we were looking at.

0:36:28.920 --> 0:36:31.799
<v Speaker 13>Sure, Yeah, that was the digital tern boris off me.

0:36:32.120 --> 0:36:35.200
<v Speaker 13>You know, I was always wanted to try the ALVHATA

0:36:35.280 --> 0:36:38.440
<v Speaker 13>technology myself, and then I create a toolbrosup for me

0:36:38.920 --> 0:36:42.320
<v Speaker 13>and then enabling that you know, lip same videos within

0:36:42.360 --> 0:36:43.160
<v Speaker 13>the same audio.

0:36:43.520 --> 0:36:44.200
<v Speaker 3>And that's what we.

0:36:44.280 --> 0:36:47.200
<v Speaker 2>See the main point of it is that it requires

0:36:47.239 --> 0:36:49.759
<v Speaker 2>no camera and no crew or a big studio like

0:36:49.800 --> 0:36:52.600
<v Speaker 2>we're sitting in now. So how does it work in practice?

0:36:52.800 --> 0:36:55.279
<v Speaker 2>Just explain the basics of me wanting to create a

0:36:55.280 --> 0:36:57.040
<v Speaker 2>clip just like that one.

0:36:57.040 --> 0:37:01.040
<v Speaker 13>Sure, sure, you know, I think the whole of hagens

0:37:01.120 --> 0:37:04.880
<v Speaker 13>that we want to produce software to really help to

0:37:05.040 --> 0:37:08.319
<v Speaker 13>you know, simplify the traditional video production. And you know,

0:37:08.719 --> 0:37:12.120
<v Speaker 13>nowadays our audience live at the video first row and

0:37:12.360 --> 0:37:15.680
<v Speaker 13>everyone's like watching lottop videos every day. There's more than

0:37:16.160 --> 0:37:19.439
<v Speaker 13>a billion hours of video being watched on YouTube every day. Great,

0:37:19.760 --> 0:37:23.040
<v Speaker 13>but the problem is that videos really you know, expensive

0:37:23.080 --> 0:37:26.400
<v Speaker 13>to make and businesses are shocking to keep up with demand.

0:37:27.000 --> 0:37:29.560
<v Speaker 13>And there's a better way to solve it ar generation.

0:37:30.000 --> 0:37:32.799
<v Speaker 13>And that's what we do. That we are building an

0:37:33.000 --> 0:37:34.879
<v Speaker 13>AR video platform leveraging.

0:37:34.560 --> 0:37:36.279
<v Speaker 3>The AI technology to do that.

0:37:36.680 --> 0:37:39.799
<v Speaker 13>So in short, in order for a customer to real

0:37:39.840 --> 0:37:43.719
<v Speaker 13>their VATA or a digitwen of themselves. You know, they

0:37:43.760 --> 0:37:47.040
<v Speaker 13>need to submit a footage and then submit the live

0:37:47.160 --> 0:37:50.920
<v Speaker 13>video consent and also read out the Dynamo verbal pascal

0:37:51.280 --> 0:37:53.840
<v Speaker 13>and then our AR model will really verify that and

0:37:53.880 --> 0:37:55.120
<v Speaker 13>create our version of that.

0:37:55.760 --> 0:38:00.279
<v Speaker 2>Some of the use cases that you guys discuss are

0:38:00.400 --> 0:38:02.480
<v Speaker 2>quite interesting. So if you take for example a not

0:38:02.560 --> 0:38:06.960
<v Speaker 2>for profit or even a training video inside of a company.

0:38:07.120 --> 0:38:09.360
<v Speaker 2>You know, think about all the trainings that people have

0:38:09.400 --> 0:38:12.000
<v Speaker 2>to do every quarter. We do them here you sit

0:38:12.080 --> 0:38:15.000
<v Speaker 2>through your kind of videos that I get, But what's

0:38:15.040 --> 0:38:18.640
<v Speaker 2>the market for it? Do you find that businesses are

0:38:18.680 --> 0:38:21.600
<v Speaker 2>willing to pay for this as a service as a

0:38:21.600 --> 0:38:22.359
<v Speaker 2>software tool?

0:38:23.320 --> 0:38:23.600
<v Speaker 3>Sure?

0:38:23.640 --> 0:38:27.000
<v Speaker 13>Sure, you know hay Gen's products help more than four

0:38:27.280 --> 0:38:31.440
<v Speaker 13>thousand paying customers. Like to do three things essentially, create,

0:38:32.200 --> 0:38:36.640
<v Speaker 13>localized and personalized. You know, as you see those from

0:38:36.800 --> 0:38:39.560
<v Speaker 13>some of the product screenshot that customers can create a

0:38:39.640 --> 0:38:44.000
<v Speaker 13>video without a camera basically leddy avata from the template,

0:38:44.760 --> 0:38:46.960
<v Speaker 13>or they can create it on their own and the

0:38:47.160 --> 0:38:49.799
<v Speaker 13>template typing the script and create a video that way.

0:38:50.160 --> 0:38:52.640
<v Speaker 13>And this is great for it's beIN the videos how

0:38:52.680 --> 0:38:56.520
<v Speaker 13>tool videos Toutobio videos chaining content that you just mentioned.

0:38:56.640 --> 0:39:00.640
<v Speaker 2>You just said forty thousand paying customers. See, you've just

0:39:00.719 --> 0:39:03.719
<v Speaker 2>raised sixty million dollars. What do you need the money for?

0:39:04.480 --> 0:39:05.080
<v Speaker 3>Great question.

0:39:05.280 --> 0:39:09.360
<v Speaker 13>So so the primary motivation of the Fairer reason was

0:39:09.400 --> 0:39:12.840
<v Speaker 13>to bring in the world class advisors and investor to

0:39:12.840 --> 0:39:16.600
<v Speaker 13>help us scale. You know, we are accelerating the you

0:39:16.640 --> 0:39:19.320
<v Speaker 13>know product roodmap and growing the go to market teams.

0:39:19.520 --> 0:39:22.520
<v Speaker 13>And the business has been profitable since Q two last year.

0:39:23.200 --> 0:39:26.360
<v Speaker 2>Profitable since Q two last year. What's your biggest cost

0:39:26.800 --> 0:39:32.160
<v Speaker 2>compute computer? Yes, and what does that look like? It's manageable, okay,

0:39:32.880 --> 0:39:37.840
<v Speaker 2>But the underlying model that powers the we're talking basically

0:39:37.880 --> 0:39:41.600
<v Speaker 2>both image and text video. That's what we're discussing here.

0:39:41.880 --> 0:39:44.480
<v Speaker 2>But you built it on in Vidia. You built it

0:39:44.520 --> 0:39:46.399
<v Speaker 2>in partnership with you Sure.

0:39:46.520 --> 0:39:46.759
<v Speaker 3>Yeah.

0:39:46.880 --> 0:39:49.080
<v Speaker 13>We we work with a loss of a you know,

0:39:49.120 --> 0:39:53.400
<v Speaker 13>the cloud provider, uh you know Amazon Ezra to you know,

0:39:53.520 --> 0:39:57.080
<v Speaker 13>power our influenced cluster, and we also have a big

0:39:57.080 --> 0:40:00.640
<v Speaker 13>cluster to chain our models. You know, especially when we

0:40:00.680 --> 0:40:05.000
<v Speaker 13>talk about the video model is very heavy lifting. And

0:40:05.040 --> 0:40:07.440
<v Speaker 13>then you know that's one of the biggest cost area.

0:40:07.840 --> 0:40:10.080
<v Speaker 2>So there is also a concern here we'll bring the

0:40:10.160 --> 0:40:15.120
<v Speaker 2>video back up, which is not you it is AI generated,

0:40:15.719 --> 0:40:20.680
<v Speaker 2>but there's a trust and safety component where your platform

0:40:20.760 --> 0:40:24.480
<v Speaker 2>and tool could be used to create content that is

0:40:24.520 --> 0:40:25.719
<v Speaker 2>not what it purports to be.

0:40:26.160 --> 0:40:27.080
<v Speaker 3>How do you overcome that?

0:40:28.040 --> 0:40:31.120
<v Speaker 13>Those are two main areas that speaking about the trusting

0:40:31.160 --> 0:40:34.000
<v Speaker 13>safety and we do at Hagen. You know, I think

0:40:34.040 --> 0:40:36.960
<v Speaker 13>the first question is around how do we protect a

0:40:37.040 --> 0:40:40.919
<v Speaker 13>digital twin And you know, like I mentioned every time,

0:40:41.040 --> 0:40:43.960
<v Speaker 13>for every customer who wants to create a video avatar

0:40:44.040 --> 0:40:48.520
<v Speaker 13>of themselves, we have an advanced user verification includes you know,

0:40:48.719 --> 0:40:52.960
<v Speaker 13>live video consent dynamit, verbal parsical as well as human

0:40:53.000 --> 0:40:53.839
<v Speaker 13>review in the back.

0:40:54.400 --> 0:40:57.000
<v Speaker 3>And the second piece is about you know the count modulation.

0:40:57.520 --> 0:41:00.239
<v Speaker 3>You know it's posted in the public domain.

0:41:00.120 --> 0:41:03.640
<v Speaker 13>Sure yeah, and you know the content relation pieces about

0:41:03.680 --> 0:41:07.040
<v Speaker 13>whether you know whether where you have the albata and

0:41:07.040 --> 0:41:10.200
<v Speaker 13>what are the content, whether the content complied with our policy.

0:41:10.680 --> 0:41:14.360
<v Speaker 13>So we combine you know, automatic system with AI model

0:41:14.440 --> 0:41:17.920
<v Speaker 13>plus human review, the human moderator in the back to

0:41:18.000 --> 0:41:23.799
<v Speaker 13>really make sure you know there's no you know, misinformation, disinformation, harassment,

0:41:24.080 --> 0:41:28.359
<v Speaker 13>child safety, political or elections specific content you know being

0:41:28.480 --> 0:41:30.400
<v Speaker 13>used for this technology.

0:41:30.640 --> 0:41:33.040
<v Speaker 2>Just very quickly, it is an election here here in

0:41:33.080 --> 0:41:36.160
<v Speaker 2>the United States. This exact topic is a big concern.

0:41:36.560 --> 0:41:41.359
<v Speaker 2>Are you being proactive in specifically the context of the election. Sure,

0:41:41.520 --> 0:41:43.799
<v Speaker 2>you know, first of all, we do not allow any

0:41:43.880 --> 0:41:48.120
<v Speaker 2>political or election specific content on the platform today. Our

0:41:48.239 --> 0:41:52.400
<v Speaker 2>policies and products shot the prohibited you know, creation of

0:41:52.520 --> 0:41:55.640
<v Speaker 2>unauthorized content and you know, chess and safety. It is

0:41:55.719 --> 0:41:59.960
<v Speaker 2>critical to our business and we're working very actively across

0:42:00.080 --> 0:42:03.240
<v Speaker 2>the braw to the industry, you know, continue to developing,

0:42:03.400 --> 0:42:09.000
<v Speaker 2>you know, tooling best purpose to combat missed information and misuse. Hey,

0:42:09.080 --> 0:42:11.839
<v Speaker 2>Jen CEO, Josh Reju, we've had you in person, We've

0:42:11.880 --> 0:42:15.400
<v Speaker 2>had an AI generated version of you. That's good value

0:42:15.600 --> 0:42:18.160
<v Speaker 2>for us here on Bloomberg Technology, and we appreciate it.

0:42:18.560 --> 0:42:21.600
<v Speaker 2>That does it for this edition of the show Bloomberg Technology.

0:42:22.400 --> 0:42:24.760
<v Speaker 2>Remember it's been a shorter week here in the United States.

0:42:24.760 --> 0:42:30.080
<v Speaker 2>We had a holiday Wednesday observing Juneteenth, but recap because

0:42:30.320 --> 0:42:32.600
<v Speaker 2>the news cycle came back in force. You know where

0:42:32.600 --> 0:42:35.799
<v Speaker 2>to find the pod on Apple, Spotify, iHeart, and of

0:42:35.840 --> 0:42:38.560
<v Speaker 2>course if you want to pod with us, we're podding

0:42:38.719 --> 0:42:41.640
<v Speaker 2>on all the Bloomberg platforms. One day left in the

0:42:41.640 --> 0:42:44.040
<v Speaker 2>week to go and I'm looking forward to it.

0:42:44.200 --> 0:42:47.000
<v Speaker 3>See you soon. This is Bloomberg Technology

0:43:00.560 --> 0:43:03.239
<v Speaker 11>At it when you don't help it un