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Speaker 1: From Mahart where Innovation, Money and Power colle in Silicon Valley, NBN.

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Speaker 1: This is Bloomberg Technology with Caroline Hyde and Ed Ludlow.

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Speaker 2: I'm Caroline Heinde at Bluemog's world head quarters in New

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Speaker 2: York and Imed Lovelow in San Francisco.

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Speaker 3: This is Blueberg Technology coming up.

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Speaker 2: The EU gives Microsoft the green light for at sixty

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Speaker 2: nine billion dollar takeover of Activision Blizzard. We'll discuss what

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Speaker 2: this actually means for the gaming industry's biggest ever deal.

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Speaker 4: And we'll talk Twitter, as Linda Yacarino prepares to take

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Speaker 4: the helm at the social media company, how will her

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Speaker 4: experience help nuwer advertisers back to the platform.

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Speaker 2: Plus we'll talk all things artificial intelligence. We sit down

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Speaker 2: with the CEO C three AI as a result Beat

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Speaker 2: and we get the startup AI perspective from the venture

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Speaker 2: firm in Site Park. All that so much more coming up.

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Speaker 2: Before we go into the startups, Let's go into the

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Speaker 2: big caps. Let's go into what's happening in the public markets. Ed, interestingly,

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Speaker 2: I'm stealing your funder. Let's take it back to what's

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Speaker 2: actually more broadly my focus, which is the Nasdaq, which

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Speaker 2: is actually up about half a percentage point. It's outperforming

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Speaker 2: the rest of the industries. On the day, we're outperforming

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Speaker 2: the rest of the benchmarks, even though we're basically a

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Speaker 2: little bit cautious. Volumes are lower, we're worried about a

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Speaker 2: course the debt ceiling, we're worried about some of that

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Speaker 2: New York data that came in in terms of manufacturing

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Speaker 2: look lackluster, and basically we're a little bit more cautious

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Speaker 2: on our outlook. But we are seeing big tech being

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Speaker 2: brought just tentatively on those thinner volumes up five ten percent.

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Speaker 2: The tenure yield push is higher. As we hear from

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Speaker 2: some Fed speakers where afar our boss think being one

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Speaker 2: of them who sits down with might make here a

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Speaker 2: little bit later. But he's talking about look no, and

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Speaker 2: pushing him back against your viewpoint that we're going to

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Speaker 2: be cutting rates here in the US anytime soon. Interesting

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Speaker 2: moves over in Turkey, could we see political upheaval. In fact,

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Speaker 2: we have a down day overall for assets over there,

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Speaker 2: and the dollar strengthens versus the Turkish lira. Moving on,

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Speaker 2: let's look at what's happening in terms of crypto in

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Speaker 2: terms of Bitcoin, and actually as though it actually weekends

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Speaker 2: on the day, just a little bit ed. We are

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Speaker 2: seeing Bitcoin just getting a bit of a bid, but

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Speaker 2: we're still only at twenty seven thousand, so still not

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Speaker 2: managing to push through that thirty thousand dollars level, but

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Speaker 2: get into where I almost took of here a little

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Speaker 2: moment ago.

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Speaker 4: Yeah, we woke up to a quiet Monday right carry

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Speaker 4: this morning, worried about news, but we have had some

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Speaker 4: that's moving markets. Metha now up two point four percent,

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Speaker 4: lou Kappaso upgrading that stock from a hold to a buy.

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Speaker 4: We'll bring you those details later in the program, along

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Speaker 4: with C three AIP eighteen percent early release of results,

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Speaker 4: upgrading modestly it's full year forecast for sales. We're going

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Speaker 4: to speak to the CEO about what's really happening all

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Speaker 4: the investor interests around AI related names. Tesla actually now

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Speaker 4: flat melon. Musk has been in France where he met

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Speaker 4: with President mac quhan. But there was some feel good

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Speaker 4: in that sock. Of course, when we got details of

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Speaker 4: a new Twitter CEO on Friday, the idea being that

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Speaker 4: Elon Musk now will be more focused on Tesla less

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Speaker 4: distracted at Twitter, but we're giving back some of those games,

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Speaker 4: off by around a tenth percent, basically flat. The big

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Speaker 4: story this Monday is that the European Union, through the

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Speaker 4: European Commission, has proved Microsoft's deal to buy Activision Blizzard

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Speaker 4: for sixty nine billion dollars. We're going to get into

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Speaker 4: the details over the analysis and reasoning what it means

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Speaker 4: for the cloud gaming market.

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Speaker 3: In particular, we see the share reaction.

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Speaker 4: It was modest at first, rop a percentage point, highest

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Speaker 4: level in three weeks on Activision, more modest, up just

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Speaker 4: two tens percent on Microsoft separately, completely separately, Bloomberg reporting

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Speaker 4: that Microsoft's cloud unit, as You're is the subject of

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Speaker 4: scrutiny from a U antitrust regulators, according to sources. We'll

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Speaker 4: get those details later in the program. A lot now

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Speaker 4: going on.

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Speaker 2: They've been busy, haven't they, All this focus on competition

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Speaker 2: and pushing back against it.

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Speaker 5: Let's talk about it all.

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Speaker 2: We've got our senior litigation analyst of Bloomberg Intelligence, Jennifer Rye.

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Speaker 2: We've also got Anna London, our legal reporter Kavin Gummel.

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Speaker 2: Catherine starting with you wasn't a surprise to see the

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Speaker 2: EU sort of take a different stance from the UK.

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Speaker 5: Hi, there m nor so, this wasn't a surprise decision.

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Speaker 6: We were intcipating that the European Commission would accept this

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Speaker 6: deal with behavioral remedy. These behavioral remedies include those too

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Speaker 6: late rivals have access to the games for our owns

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Speaker 6: ten years, and the Commission said that with these conditions

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Speaker 6: that will allow the deal to be pro competitive.

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Speaker 4: Jen, I'm going to come to you at Bloomberg Intelligence.

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Speaker 4: In the analysis published by the European Commission, Jen, they

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Speaker 4: say that actually this is going to be pro growth,

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Speaker 4: pro market. How is their analysis so different to that

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Speaker 4: of the UK CMA.

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Speaker 3: Are they just reading two different sets of data?

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Speaker 7: You know, it's really just about a different prediction as

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Speaker 7: to what's going to happen with cloud gaming in the future.

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Speaker 7: And you know, I think it just shows how difficult

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Speaker 7: these merger decisions can be when they're involving tech and

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Speaker 7: when they're involving future markets, because it's really they're looking

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Speaker 7: at a crystal ball and they're speculating about what can happen,

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Speaker 7: and reasonable minds can differ. The European Commission views Microsoft's

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Speaker 7: move to guarantee that these these games Call of Duty

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Speaker 7: and World of Warcraft that it would be acquiring from

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Speaker 7: Activision would be on these other cloud services also in

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Speaker 7: other cloud subscriptions, and that's not the way things are today.

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Speaker 8: Those games aren't available.

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Speaker 7: So the European Commission is looking at this as output

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Speaker 7: expanding or pro competitive, whereas the UK is saying, no,

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Speaker 7: you know, we think Microsoft today has too much power

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Speaker 7: in the cloud and by having these great games, this

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Speaker 7: must have content for some gamers. In the future, they'll

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Speaker 7: be able to push out these other cloud gaming services

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Speaker 7: and these other competitors, and we're trying to prevent that.

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Speaker 7: We're trying to prevent Microsoft from being dominant in this

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Speaker 7: market in the future.

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Speaker 8: So they just sort of saw what was going to

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Speaker 8: happen in the future.

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Speaker 4: Differently, Catherine, we knew this was coming at least the

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Speaker 4: timing of the decision. Now through the twenty second we

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Speaker 4: got it. Bloomberg sources had said that the EU would

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Speaker 4: rule in favor of the deal. So what happens now?

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Speaker 4: What is the process that we're tracking at Bloomberg News.

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Speaker 6: Yes, so that's to say has given a glimmer of

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Speaker 6: hope to Microsoft, but it's not going to change things massively.

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Speaker 6: Microsoft already faced massive challenges in the US with the

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Speaker 6: FTC having blocked to sue, and in the UK the

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Speaker 6: Microsoft will have to lodge its appeal at the Competitional

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Speaker 6: Peel Tribunal by the end of the month, and that

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Speaker 6: will be really difficult because the CAT is a judicial

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Speaker 6: review process, so you know, they'll just look at the

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Speaker 6: legality of the CMA's decision rather than really assessing the

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Speaker 6: merits of that choice.

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Speaker 2: And what is interesting, Jen is that, well, we just

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Speaker 2: heard it from Catherine, a glimmer of hope coming, but

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Speaker 2: realistically this is an uphill battle, even though we do

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Speaker 2: see a share price reaction for activision Brizard, Ultimately, from

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Speaker 2: your analysis, it feels like you don't think the tune

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Speaker 2: is being changed here and what sort of timeline do

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Speaker 2: you think this deal ultimately unwinding.

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Speaker 5: You know, in your perspectivities.

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Speaker 7: See this changing things very much, because at the end

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Speaker 7: of the day, there is a very high standard to

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Speaker 7: overturn a CMA decision. I actually did a little research

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Speaker 7: and I looked at merger decisions by the CMA that

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Speaker 7: had actually been reversed or sent back to the CMA

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Speaker 7: on appeal, and it was about thirty percent, so that's

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Speaker 7: a low percentage, so it's a high standard.

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Speaker 8: It's going to be difficult, and.

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Speaker 7: The European Commission's decision is separate and based on the

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Speaker 7: separate analysis and maybe even different market conditions. So I

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Speaker 7: don't really think it factors in much, and it doesn't

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Speaker 7: change the fact that Microsoft has this very high, difficult

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Speaker 7: standard to meet to overturn that decision.

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Speaker 8: And then timing. You mentioned timing.

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Speaker 7: I think that's so important here because even if Microsoft

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Speaker 7: is successful, let's say.

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Speaker 8: On appeal to in the UK, and even with their.

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Speaker 7: Lawsuit that's coming up in August in the US against

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Speaker 7: the Federal Trade Commission, you're looking at a very very

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Speaker 7: long time period before there could be an actual ultimate

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Speaker 7: final outcome. Because the CMA, let's say, the appeal tribunal

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Speaker 7: doesn't like the decision or thinks the facts need to

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Speaker 7: be reevaluated, I'll send it back to the CMA to'll

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Speaker 7: look at it again. And in the US, even if

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Speaker 7: the administrative large judge that will be hearing this trial

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Speaker 7: rules for Microsoft, the FEC can appeal and the appeal

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Speaker 7: will go back to the Commissioners the very three commissioners

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Speaker 7: that voted to sue to begin with, So there's a

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Speaker 7: good chance that would be reversed. At which point Microsoft

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Speaker 7: an Activision could appeal to a federal report. But we're

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Speaker 7: talking way into the end of twenty twenty four here,

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Speaker 7: so a long time frame if they really want to

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Speaker 7: have success.

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Speaker 4: Jen Catherine Bobby Kotik, the CEO of Activision, is sent

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Speaker 4: through an emailed statement to us and he says that

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Speaker 4: the EC conducted an extremely thorough, deliberate process. But the

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Speaker 4: bit that jumps out at me is although they required

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Speaker 4: stringent remedies, and I think that's a reference to the

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Speaker 4: ten year of access, ten years of access to cloud

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Speaker 4: platforms on call of duty. Catherine, remind us, when they

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Speaker 4: go back to the CMA and make this appeal in

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Speaker 4: the UK, they're not necessarily appealing the decision in and

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Speaker 4: of itself. They're appealing how that decision was made. They're

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Speaker 4: appealing the process. Remind us, what has to happen.

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Speaker 6: Yes, exactly that, so what the cat They don't look

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Speaker 6: at the medus of this decision, They just look at

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Speaker 6: it in a judicial review process, and which would will

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Speaker 6: be the legality of the decisions, so you know, they

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Speaker 6: can look at things whether the CME was irrational or

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Speaker 6: you know, if there was any procedural procedural errors there

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Speaker 6: that they might have got wrong. I mean, I think

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Speaker 6: it's also important to understand with this process that if

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Speaker 6: the CAT does find that there are any errors made,

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Speaker 6: that the CAT will then actually refer that back to

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Speaker 6: the CME itself. So that is another hurdle for Microsoft

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Speaker 6: that it will need to pass.

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Speaker 4: Yes, we should point out that the UKCMA did come

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Speaker 4: out with a response this morning saying they stand by

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Speaker 4: their original decision, so we'll wait and see what happens.

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Speaker 4: Bloombergs Cafferinemol and Jennifer Ree of Bloomberg Intelligence, thank you

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Speaker 4: very much. Sticking with Microsoft and antitrust, we've mentioned it

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Speaker 4: that earlier Microsoft's Azure cloud business has been targeted by

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Speaker 4: the European Union's Anti Trust Arm and MID concerns the

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Speaker 4: US software firm is leveraging its market power to squeeze

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Speaker 4: out rivals as part of an informal probe. Regulators are

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Speaker 4: quizzing competitors and customers about how Microsoft may be using

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Speaker 4: its access to business sensitive information belonging to cloud firms.

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Speaker 4: It has commercial dealings with that all. According to sources.

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Speaker 2: Carrot competition analysts, they're busy, So too is one Linda Yakarino.

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Speaker 2: We know that she's saying she's excited to transform Twitter ed.

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Speaker 2: We're going to be talking about what she brings to

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Speaker 2: the social media platform and more with three past studios

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Speaker 2: Stephen wolf Herrera joining the show. So Twitter's incoming CEO,

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Speaker 2: Linda Yakarina says she's excited to transform the company and

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Speaker 2: achieving La Musk's vision for the platform. In her first

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Speaker 2: few tweets since galning the job, Yacarina said, look, she's

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Speaker 2: committed to the development of the social media company and

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Speaker 2: said feedback from users is vital to that future. I

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Speaker 2: speak to someone who knows her impact, none of for

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Speaker 2: fifteen years. At least three past studios. Chief business Officer

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Speaker 2: Stephen wolf Perrera is in the studio with us. And

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Speaker 2: when you heard that this force that you've worked and

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Speaker 2: seen and interacted with for fifteen years is going to

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Speaker 2: be taking the helm, what did your immediately think?

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Speaker 9: I thought it was a brilliant move.

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Speaker 10: The platform needs a radical transformation. They need to have

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Speaker 10: credibility with the marketplace, with brands with consumers, and Linda

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Speaker 10: has a track record around innovation really putting consumers first.

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Speaker 10: So I think it was a brilliant move for a

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Speaker 10: platform that desperately needed to change.

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Speaker 2: And is it safety first? Is it innovation first? How

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Speaker 2: does she manage to square that circle of a CTO

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Speaker 2: who's going to want to be pushing ahead with innovation

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Speaker 2: and perhaps running fast and breaking things.

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Speaker 10: Look on the technology side, I mean, obviously elans a

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Speaker 10: visionary and he'll be able to certainly figure out the

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Speaker 10: path from Twitter to transform it to the super ad x.

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Speaker 10: But you need to stay biard as the business. I mean,

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Speaker 10: right now, it's been bleeding advertisers. No one wants to

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Speaker 10: be on the platform. There's been all this drama around it.

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Speaker 10: And Linda's a stabilizing force. I mean, she's spent over

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Speaker 10: ten years at NBC Universal really stabilizing that company, growing

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Speaker 10: it over thirteen billion dollars in sales, leading their upfront,

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Speaker 10: leading you know, kind of innovation with data with other

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Speaker 10: TV networks, really trying to bring the community together.

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Speaker 9: And she is a force to be reckoned with.

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Speaker 10: I mean, there's a reason why they have her nickname

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Speaker 10: being developed Hammer because she's able to negotiate with brands.

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Speaker 10: She's tough, she's fair, but or you know, number one

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Speaker 10: is really to bring brands back onto the.

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Speaker 2: Platform, and to do that alongside an executive chair, of course,

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Speaker 2: said and I mean you know a lot about the

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Speaker 2: people that worked alongside Elan over the years.

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Speaker 3: Yeah.

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Speaker 4: Yeah, it's interesting how it works. So at SpaceX you

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Speaker 4: have Gwynn Shotwell as the COO and president running things

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Speaker 4: day to day. At Tesla, particularly in recent courses, Zach

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Speaker 4: Kirk on the CFO is like more visible and other

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Speaker 4: executives like literally appearing on stage. So I guess, even

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Speaker 4: to your mind, how do you see that working. You know,

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Speaker 4: Linda who you know with Elon Musk day to day,

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Speaker 4: do you think that she can get him to see

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Speaker 4: reason or compromise.

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Speaker 9: I think so.

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Speaker 10: I mean we saw a trial run of what their

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Speaker 10: relationship is going to look like about a month ago

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Speaker 10: in Miami there was the Possible Conference, a big marketing event,

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Speaker 10: and she was on stage doing a fireside chat interview

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Speaker 10: with Elon and she didn't pull any punches. I mean,

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Speaker 10: Linda's not a wallflower, right, I mean, she's very tough,

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Speaker 10: she knows her business. You know, she is a good

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Speaker 10: New Yorker, grew up in Long Island, you know, Italian heritage.

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Speaker 9: I mean, she's as tough as they come.

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Speaker 10: And she asked him the tough questions on stage, and

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Speaker 10: so you could see that she didn't shy away from

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Speaker 10: asking him about, Hey, why did Twitter cancel the client

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Speaker 10: council that they had? Are you going to bring that back?

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Speaker 10: Are you going to stop doing tweets at three in

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Speaker 10: the morning. You know that's not good for the platform.

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Speaker 10: So I feel that she knows this space, she knows

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Speaker 10: this industry, and she's beloved by brands and marketers and

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Speaker 10: media agencies. And so if he's smart, he'll really give

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Speaker 10: her the range. Let her be the CEO, let her

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Speaker 10: build this platform, and then bring all the innovation to

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Speaker 10: really help connect content, commerce and community.

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Speaker 4: We go back to it, how does she build this platform?

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Speaker 4: You know Elon sets out his ideas as CTO, many

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Speaker 4: of them.

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Speaker 3: We know about subscription based.

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Speaker 4: Service, algorithm, algorithmically addressing where things appear in the tie timeline.

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Speaker 4: Then what impacts Linda going to have when she comes in?

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Speaker 4: What ideas can she actually install?

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Speaker 10: Well, first, it's about leadership. I mean the company has

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Speaker 10: what lost so many employees. They've obviously let a ton

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Speaker 10: of people go. You know, they are a fraction of

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Speaker 10: what they were before. I feel like there has been

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Speaker 10: this crisis and confidence in Twitter, and here is a

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Speaker 10: real leader who's going to come in and stabilize the

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Speaker 10: business and bring back that confidence, bring back the trust

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Speaker 10: of not just the employees but also the advertising community.

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Speaker 9: And you have to start there.

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Speaker 10: I mean, at the end of the day, this has

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Speaker 10: to be about getting the basics right. And she knows

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Speaker 10: how to build a business. She is a leader, she

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Speaker 10: is inspiring. She will bring talent to the commpany. I mean,

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Speaker 10: she built a data business from scratch for NBCU. She

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Speaker 10: understands e commerce, she understands analytics, and so she had

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Speaker 10: that full span of control on the business side. Again,

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Speaker 10: you have incredible engineers and technologies over at Twitter, certainly

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Speaker 10: at the Helm with you on, but you know, having

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Speaker 10: her really lead the business side, that's what this company needs.

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Speaker 2: It's interesting, of course talking about the Data League, talking

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Speaker 2: about ultimately how you show brands that you're making impacts,

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Speaker 2: the right impact for them converting into sales.

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Speaker 5: But I'm also interested in the grander vision.

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Speaker 2: Many people had to quickly Google or search or chat

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Speaker 2: shipt who.

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Speaker 5: Linda Yacarino is.

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Speaker 2: But behind the scenes, she's really has had a very

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Speaker 2: powerful influence, had a very influential job. What vision do

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Speaker 2: you think she thinks Twitter ultimately is going to be

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Speaker 2: to make this a worth her wild kind of move.

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Speaker 10: Yeah, I mean, look, she was the chairwoman of NBC

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Speaker 10: Universal's ad sales business, right, she had a great job.

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Speaker 10: She was one of the most powerful people in media.

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Speaker 10: So for her to leave, it had to be something

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Speaker 10: really compelling. It had to be a bigger vision. And

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Speaker 10: I think Elance shared the vision for the super app

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Speaker 10: for x and I feel that she got really excited

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Speaker 10: about that.

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Speaker 9: And so again her ability.

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Speaker 10: To innovate, to bring consumers and brands along on this journey.

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Speaker 10: That's a very unique position to be. And she understands content.

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Speaker 10: She actually was a partner for Twitter for years. Think

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Speaker 10: about the Olympics and the Super Bowl and World Cup,

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Speaker 10: all those mega events that truly have global ramifications.

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Speaker 9: She was at the center of that.

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Speaker 10: So now to bring that lens around again, content, commerce

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Speaker 10: and community. Everyone is trying to connect that and as

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Speaker 10: one of the largest media brands on the planet, she

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Speaker 10: understood that an audience, whether it's eighteen to thirty four,

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Speaker 10: eighteen to forty nine, whatever advertisers are looking for, they

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Speaker 10: could find that audience anywhere. The reality means you have

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Speaker 10: to make a compelling to put those dollars on Twitter.

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Speaker 4: Yeah, we reported that there were others involved in that

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Speaker 4: relationship NBC in Twitter, and she was at a macro level.

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Speaker 3: But that's great insight.

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Speaker 4: Three Pass Studios Chief business Officer, Stephen Wolf Pereira, thank

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Speaker 4: you very.

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Speaker 9: Much, Thanks so much.

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Speaker 4: Now coming up, Miguel McKelvey joins to talk about his

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Speaker 4: recent which include his acquisition of clothing brand American Giant

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Speaker 4: and a social network for senior aged users.

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Speaker 3: More on that. Next, this is Bloomberg.

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Speaker 4: In an effort to revitalize manufacturing in the US. Miguel McKelvey,

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Speaker 4: co founder of we Work, says he's buying clothing brand

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Speaker 4: American Giant. There's also plans to build a new social

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Speaker 4: network for users fifty five in older. Miguel McKelvey joins

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Speaker 4: us now for more on what's quite a few announcements.

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Speaker 4: I find manufacturing fascinating. Think about the world of technology

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Speaker 4: on this show we operate in and actually that's a

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Speaker 4: big part of the story, why do you want to

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Speaker 4: revitalize US manufacturing?

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Speaker 1: Well, it started for me with really, you know, the

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Speaker 1: same kind of response that I had to office workers

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Speaker 1: with we work, is that the environment that people are

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Speaker 1: working in just isn't great and isn't a nice.

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Speaker 3: Place to be.

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Speaker 1: Like sitting in a cubicle for ten hours a day

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Speaker 1: to me was seemed terrible. And similarly, I think that

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Speaker 1: the working environments where people make things have really been

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Speaker 1: brought down to the lowest possible, you know, from a design,

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Speaker 1: from an ergonomic, from just a human perspective, And it

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Speaker 1: makes sense because you know, you have to compete with

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Speaker 1: really low labor in other places in the world. But

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Speaker 1: I think in the US, for our future, you know,

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Speaker 1: we can create jobs and places to work that are

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Speaker 1: that are much better, and I think that's what can unlock,

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Speaker 1: you know, a new future for American manufacturer.

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Speaker 4: Miguel across all of your projects, was it difficult to

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Speaker 4: engage with investors? Did you have to do some reputational

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Speaker 4: rebuilding or explain what happened that we work your associations

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Speaker 4: with Adam Are those questions.

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Speaker 9: Yeah, I think they're fair.

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Speaker 1: I mean a lot of the stuff that I worked

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Speaker 1: on was the we Work product and obviously building helping

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Speaker 1: to build an organization that scaled to you know, hundreds

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Speaker 1: of locations around the world, and that is a credibility

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Speaker 1: which I think is lasting. I mean, we were able

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Speaker 1: to do amazing things. And then there's obviously another layer

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Speaker 1: of things at the company that didn't go as well,

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Speaker 1: and you know, people always have questions about that, and

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Speaker 1: oftentimes I would say, you know, people want to know

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Speaker 1: the we Work storty. You know, there's a sort of insatiable,

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Speaker 1: insatiable desire to learn more about what happened that we work.

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Speaker 1: So I don't mind those conversations. You know, for me,

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Speaker 1: it's still a learning process. I still like reflecting on

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Speaker 1: those times because I learned from all those conversations. So yeah,

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Speaker 1: I mean I wouldn't say reputational as much as just

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Speaker 1: people are really curious.

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Speaker 2: People are curious also, of course that you're getting back

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Speaker 2: into the world of commercial real estate. In many ways

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Speaker 2: we're thinking of is it nia how you say it,

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Speaker 2: a focus on a social network but in a real

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Speaker 2: life one for people fifty five years and older. I

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Speaker 2: can see the relevance of the relevancy of this with

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Speaker 2: older parents who complain about noise levels and the way

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Speaker 2: in which one interacts. But ultimately does the real estate

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Speaker 2: arc that we're currently on at the moment mean that

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Speaker 2: you're getting good prices. People are worried about the banks,

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Speaker 2: for example, and their exposure to real estate, particular commercial

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Speaker 2: real estate.

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Speaker 1: Yeah, so there's a parallel to you know, we work.

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Speaker 1: When we first started, we were coming out of that

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Speaker 1: financial crisis back you know, two thousand and seven, two

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Speaker 1: thousand and eight, and then there was a big dip

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Speaker 1: in commercial real estate back then, and that actually helped

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Speaker 1: us acquire, you know, especially in the early days, good

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Speaker 1: deals on our initial buildings. And so I think that

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Speaker 1: opportunity is similar. A lot of people were coming to

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Speaker 1: me with future of work questions, you know, what do

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Speaker 1: you think is going to happen? What role do you

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Speaker 1: want to play in it? And honestly, I have to

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Speaker 1: say I'm a bit not bored. But it's just I've

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Speaker 1: sort of been there, done that, and for me to

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Speaker 1: re enter that market didn't make sense to me. But

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Speaker 1: I do think there are a lot of parallels. I mean,

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Speaker 1: I want to create communities for people where they you know,

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Speaker 1: enter and spend time in spaces that make them feel good.

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Speaker 1: And I think that's where this opportunity became clear, you know,

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Speaker 1: an intersection of what I love to do and the

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Speaker 1: opportunity in real estate.

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Speaker 2: Briefly, Adam Newman, of course, your co foundal We Work,

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Speaker 2: is also back in the way to take game.

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Speaker 5: Would you ever work with him again?

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Speaker 1: You know, for me, my main thing is growth and learning.

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Speaker 1: I like to keep expanding on, you know, the experiences

437
00:21:39,640 --> 00:21:42,040
Speaker 1: that life can offer me. And you know, Adam is

438
00:21:42,080 --> 00:21:45,600
Speaker 1: a CEO, he's a he's a top dog and a leader,

439
00:21:45,720 --> 00:21:48,080
Speaker 1: and and for me, I want to I want to

440
00:21:48,160 --> 00:21:50,359
Speaker 1: learn how to be in that position. I want to

441
00:21:50,400 --> 00:21:52,840
Speaker 1: lead a company. And so it doesn't make sense right

442
00:21:52,880 --> 00:21:55,280
Speaker 1: now for us to work together, but I you know,

443
00:21:55,520 --> 00:21:57,800
Speaker 1: for no reason other than I just want to keep

444
00:21:57,840 --> 00:21:59,000
Speaker 1: growing on my own journey.

445
00:21:59,320 --> 00:22:02,560
Speaker 2: Michael, thanks for telling us your journey. American giant proto

446
00:22:03,200 --> 00:22:05,400
Speaker 2: Naya come on and talk to us about it again.

447
00:22:05,440 --> 00:22:07,000
Speaker 5: Migael mc kelvey, co founder of we.

448
00:22:06,960 --> 00:22:17,040
Speaker 2: Work, welcome back to blue their technology. I'm Caroline Hyde

449
00:22:17,040 --> 00:22:17,720
Speaker 2: in New York.

450
00:22:18,040 --> 00:22:20,479
Speaker 4: And im Ed Lovelow in San Francisco. Caroline, just get

451
00:22:20,520 --> 00:22:23,040
Speaker 4: a check on markets. We're in quite a tight range.

452
00:22:23,359 --> 00:22:25,560
Speaker 4: When it comes to equity markets, look at the NAZET

453
00:22:25,600 --> 00:22:28,240
Speaker 4: one hundred up three ten percent. A lot of focus

454
00:22:28,240 --> 00:22:30,639
Speaker 4: on what's happening with the debt ceiling debate out in DC,

455
00:22:31,160 --> 00:22:34,080
Speaker 4: a little bit of caution outperformance in semiconductors. I look

456
00:22:34,119 --> 00:22:37,080
Speaker 4: at the Philadelphia Semiconductor Index. Every name in the green

457
00:22:37,119 --> 00:22:40,280
Speaker 4: apart from one which is a SML currently flat, a

458
00:22:40,280 --> 00:22:42,440
Speaker 4: lot of upside there, yields climbing a little higher four

459
00:22:42,480 --> 00:22:44,560
Speaker 4: basis points on the ten year three point five percent,

460
00:22:44,560 --> 00:22:47,440
Speaker 4: and as you noted earlier, Bitcoin on its way back

461
00:22:47,520 --> 00:22:50,439
Speaker 4: up again towards or an above twenty seven five hundred

462
00:22:50,720 --> 00:22:53,720
Speaker 4: US dollars per token. In terms of the specific names

463
00:22:53,720 --> 00:22:57,840
Speaker 4: and movers that we're watching, the big newsflow mover is

464
00:22:57,840 --> 00:23:00,919
Speaker 4: obviously Activision and Microsoft, those two names moving to the upside.

465
00:23:00,960 --> 00:23:03,640
Speaker 4: Microsoft basically flat now, but Activision up one point three

466
00:23:03,680 --> 00:23:07,680
Speaker 4: percent after the European Commission approved the deal for Microsoft

467
00:23:07,720 --> 00:23:10,479
Speaker 4: to acquire the video game maker for sixty nine billion

468
00:23:10,760 --> 00:23:13,960
Speaker 4: US dollars. Look at C three AI up nineteen percent,

469
00:23:14,080 --> 00:23:17,080
Speaker 4: carrow biggest Johnpson's the end of March out early with

470
00:23:17,200 --> 00:23:21,800
Speaker 4: results slightly raising full year guidance, but also some response

471
00:23:21,840 --> 00:23:24,600
Speaker 4: from the company to short sellar reports that we'll get

472
00:23:24,640 --> 00:23:29,400
Speaker 4: into with the C three AI CEO Tom Sebel joins us. Now, Tom,

473
00:23:30,040 --> 00:23:33,000
Speaker 4: you modestly raise guidance for the full year. Caroline's been

474
00:23:33,000 --> 00:23:36,080
Speaker 4: doing a great job covering how a lot of the

475
00:23:36,080 --> 00:23:39,000
Speaker 4: equity market activity at the start of this year is

476
00:23:39,119 --> 00:23:43,000
Speaker 4: all AI driven. Was your guidance raised? Just the authoria

477
00:23:43,080 --> 00:23:44,280
Speaker 4: that we've seen in AI.

478
00:23:46,800 --> 00:23:51,240
Speaker 11: High ed Hi, carolinan We with all the planning activity

479
00:23:51,280 --> 00:23:53,879
Speaker 11: that's going on after the end of the year for

480
00:23:53,920 --> 00:23:57,120
Speaker 11: a fiscal year twenty four and twenty five for new products,

481
00:23:57,200 --> 00:23:59,640
Speaker 11: new customers, new growth, and now this is going on

482
00:24:00,200 --> 00:24:02,960
Speaker 11: the world. We had a lot of good news to

483
00:24:03,080 --> 00:24:06,119
Speaker 11: report and we wanted to make sure that there wasn't

484
00:24:06,200 --> 00:24:09,080
Speaker 11: an inadvertent selective.

485
00:24:08,560 --> 00:24:09,920
Speaker 12: Disclosure of this information.

486
00:24:10,200 --> 00:24:12,879
Speaker 11: So we issued this release just to make sure that

487
00:24:12,920 --> 00:24:16,240
Speaker 11: the information was provided to the market in a manner

488
00:24:16,320 --> 00:24:19,959
Speaker 11: that's compliant with all SEC regulations.

489
00:24:20,400 --> 00:24:24,359
Speaker 2: Thomas, it's fascinating C three generative AI for enterprise search.

490
00:24:24,560 --> 00:24:26,600
Speaker 2: I think it was March that you unveiled this. You've

491
00:24:26,640 --> 00:24:29,600
Speaker 2: said at the moment that the addressable market for enterprise

492
00:24:29,720 --> 00:24:32,879
Speaker 2: AI is extraordinarily large, but everyone's fighting for it. We

493
00:24:33,000 --> 00:24:35,399
Speaker 2: just had, of course cause Palenteers saying they want to

494
00:24:35,400 --> 00:24:39,280
Speaker 2: take the whole market for generative AI, and they're particularly

495
00:24:39,400 --> 00:24:41,600
Speaker 2: active in some of the defense areas that you are.

496
00:24:42,280 --> 00:24:45,360
Speaker 5: Can there be multiple players? How are you feeling about competition?

497
00:24:46,640 --> 00:24:48,920
Speaker 11: I think what we look at is so Caroline, As

498
00:24:48,960 --> 00:24:51,960
Speaker 11: you know, for some years now, for over a decade,

499
00:24:52,320 --> 00:24:56,160
Speaker 11: we've been talking about this emerging market for applying artificial

500
00:24:56,200 --> 00:25:00,960
Speaker 11: intelligence the enterprises to improve their business operations. Now, I

501
00:25:01,000 --> 00:25:04,720
Speaker 11: think as we power into twenty twenty three, the whole

502
00:25:04,720 --> 00:25:07,840
Speaker 11: world has come around to seeing that this is a

503
00:25:07,960 --> 00:25:11,119
Speaker 11: huge addressable market and there's no corporation that want doesn't

504
00:25:11,119 --> 00:25:15,840
Speaker 11: want to take advantage of it. This looks like a

505
00:25:15,920 --> 00:25:18,560
Speaker 11: larger than a half a billion half a trillion dollar

506
00:25:18,600 --> 00:25:23,720
Speaker 11: addressable software market growing very rapidly, and I think there's

507
00:25:23,760 --> 00:25:27,280
Speaker 11: going to be an opportunity for many companies to be.

508
00:25:27,320 --> 00:25:29,719
Speaker 12: Quite successful in this space after it's over. This is

509
00:25:29,800 --> 00:25:30,600
Speaker 12: this is a big.

510
00:25:30,440 --> 00:25:34,280
Speaker 2: One, and how are they using your particular offering? How

511
00:25:34,720 --> 00:25:36,720
Speaker 2: you are building for these companies? We just saw a

512
00:25:36,760 --> 00:25:40,040
Speaker 2: load of the names proving different well.

513
00:25:39,840 --> 00:25:44,720
Speaker 11: We use AI to basically make all these enterprise applications

514
00:25:44,720 --> 00:25:48,200
Speaker 11: that have been installed in the last three decades erp

515
00:25:48,480 --> 00:25:52,359
Speaker 11: CRM manufacturing supply chain to make them predictive, so that

516
00:25:52,440 --> 00:25:55,080
Speaker 11: we can predict how many parts we need in each

517
00:25:55,119 --> 00:25:57,639
Speaker 11: component of our supply chain, so we deliver products on

518
00:25:57,720 --> 00:26:01,119
Speaker 11: time in it in full, say air Force, we use

519
00:26:01,160 --> 00:26:05,240
Speaker 11: it to predict device failure or system failure in weapons

520
00:26:05,280 --> 00:26:10,080
Speaker 11: systems like aircraft so that they have increased availability, fraud detection,

521
00:26:10,280 --> 00:26:14,960
Speaker 11: customer churn. So these are the most common applications of

522
00:26:15,119 --> 00:26:18,880
Speaker 11: enterprise AI to business processes, and I think that there

523
00:26:18,920 --> 00:26:21,920
Speaker 11: is no CEO in the world that is not now

524
00:26:21,960 --> 00:26:23,600
Speaker 11: trying to figure out how this is not kind of

525
00:26:23,680 --> 00:26:25,760
Speaker 11: number one on his or her list. You're trying to

526
00:26:25,760 --> 00:26:29,239
Speaker 11: figure out how to use these technologies to advance their

527
00:26:29,280 --> 00:26:29,960
Speaker 11: market position.

528
00:26:31,200 --> 00:26:31,480
Speaker 3: Tom.

529
00:26:31,480 --> 00:26:36,200
Speaker 4: On April fourth, Carrisdale Capital, a known short seller, alleged

530
00:26:36,320 --> 00:26:40,000
Speaker 4: serious accounting and disclosure issues with C three AI. What

531
00:26:40,160 --> 00:26:42,520
Speaker 4: is your latest response to that short seller report.

532
00:26:43,359 --> 00:26:46,560
Speaker 11: Well, you can see on our website that our audit

533
00:26:46,640 --> 00:26:51,639
Speaker 11: committee conducted an impetitive investigation with independent outside council and

534
00:26:51,720 --> 00:26:56,040
Speaker 11: independent accounting firm and determined that all of those allegations

535
00:26:56,040 --> 00:27:00,160
Speaker 11: were a complete bunk, and so we published that this morning.

536
00:27:01,440 --> 00:27:05,199
Speaker 11: It's been well reported that Carrisdale is under investigation by

537
00:27:05,200 --> 00:27:08,480
Speaker 11: the Department of Justice for doing this sort of thing

538
00:27:08,520 --> 00:27:12,639
Speaker 11: to manipulate stock prices to their economic advantage. If this

539
00:27:12,760 --> 00:27:16,560
Speaker 11: is true, it's highly unlawful. We expect to have the

540
00:27:16,560 --> 00:27:20,679
Speaker 11: opportunity to cooperate with the Department of Justice and this activity,

541
00:27:21,080 --> 00:27:24,560
Speaker 11: and hopefully the Department of Justice will do their job

542
00:27:25,200 --> 00:27:29,360
Speaker 11: and if they find that there is wrongdoing, hopefully these

543
00:27:29,400 --> 00:27:33,680
Speaker 11: people will be prosecuted to the full extent of the law.

544
00:27:34,440 --> 00:27:36,359
Speaker 3: Okay, Tom, thank you for the update on that.

545
00:27:37,280 --> 00:27:39,720
Speaker 4: I went to our audience and I said, Tom Siebel's

546
00:27:39,720 --> 00:27:40,359
Speaker 4: coming on the show.

547
00:27:40,400 --> 00:27:42,320
Speaker 3: What do you want to know? One question that caught

548
00:27:42,359 --> 00:27:42,720
Speaker 3: my eye.

549
00:27:43,560 --> 00:27:46,720
Speaker 4: Are there any government or public sector contracts that you

550
00:27:46,800 --> 00:27:51,280
Speaker 4: have turned down for ethics reasons when it relates to AI.

551
00:27:53,160 --> 00:27:57,399
Speaker 11: Yes, there is a government and I won't say which one, Okay.

552
00:27:57,359 --> 00:27:59,400
Speaker 3: Is asked come on, you've got to say which one, now, Tom,

553
00:28:00,119 --> 00:28:01,120
Speaker 3: Which government.

554
00:28:01,400 --> 00:28:02,879
Speaker 12: That has asked us to use AI?

555
00:28:03,200 --> 00:28:07,320
Speaker 11: To a Western government, because that's all we do business with,

556
00:28:07,640 --> 00:28:10,840
Speaker 11: that has asked us to use AI to identify extremists

557
00:28:10,880 --> 00:28:14,000
Speaker 11: in the population, We think that we don't want to

558
00:28:14,000 --> 00:28:19,280
Speaker 11: touch that. On a more less controversial note, Okay, we've

559
00:28:19,280 --> 00:28:21,520
Speaker 11: been asked. We were asked some years ago to build

560
00:28:21,520 --> 00:28:26,040
Speaker 11: an hr AI enabled hr system for the Department of

561
00:28:26,080 --> 00:28:29,400
Speaker 11: the Army. Okay, this would use a AI to determine

562
00:28:29,400 --> 00:28:30,960
Speaker 11: who to promote, who to assign.

563
00:28:31,520 --> 00:28:32,760
Speaker 12: Now we neglect.

564
00:28:32,960 --> 00:28:36,520
Speaker 11: We elected not to do that because what we're doing

565
00:28:36,600 --> 00:28:39,840
Speaker 11: is propagating cultural bias. No matter what the question is,

566
00:28:39,880 --> 00:28:42,200
Speaker 11: the answer will be white male went to West Point

567
00:28:42,600 --> 00:28:45,920
Speaker 11: and in twenty first century, that answer is simply not

568
00:28:45,960 --> 00:28:49,480
Speaker 11: going to fly. And so there are other companies in

569
00:28:49,520 --> 00:28:52,680
Speaker 11: our business who would get a snap of that opportunity

570
00:28:52,720 --> 00:28:55,840
Speaker 11: to a second but but we won't do those things.

571
00:28:56,280 --> 00:29:00,520
Speaker 2: Basically, you're saying yourself regulating Tom, and I'm interested in

572
00:29:00,760 --> 00:29:03,720
Speaker 2: what you make of the guardrails, whether they're being put

573
00:29:03,760 --> 00:29:07,280
Speaker 2: in place enough amid private markets. We just had the

574
00:29:07,360 --> 00:29:11,440
Speaker 2: Credo AI CEO on recently. Navina, who's working along with

575
00:29:11,480 --> 00:29:12,840
Speaker 2: Booz Allen. I know you do a lot of work

576
00:29:12,880 --> 00:29:15,080
Speaker 2: with Booz Allen thinking about how we can have these

577
00:29:15,120 --> 00:29:18,880
Speaker 2: guardrails put in place by the companies themselves. Ultimately, do

578
00:29:18,920 --> 00:29:21,160
Speaker 2: you think government needs to be ahead of the curve here?

579
00:29:21,200 --> 00:29:23,600
Speaker 2: You have a lot of ex government officials on your board.

580
00:29:23,640 --> 00:29:27,600
Speaker 11: For example, Caroline, I think you're raising a very important issue.

581
00:29:27,680 --> 00:29:30,880
Speaker 11: I mean, this matter of the ethical application of AI

582
00:29:31,240 --> 00:29:35,720
Speaker 11: is hugely important. I mean, these technologies are extraordinarily powerful,

583
00:29:36,200 --> 00:29:40,960
Speaker 11: and pretty soon it will be almost virtually impossible for

584
00:29:41,040 --> 00:29:44,440
Speaker 11: a mortal to determine the difference in news in fake news.

585
00:29:44,760 --> 00:29:48,640
Speaker 11: These questions call into the question our ability to conduct

586
00:29:48,840 --> 00:29:51,440
Speaker 11: free and open democratic societies.

587
00:29:51,760 --> 00:29:53,800
Speaker 12: So this is very troubling stuff.

588
00:29:54,440 --> 00:29:58,080
Speaker 11: I don't believe that in the long run that self

589
00:29:58,120 --> 00:30:01,280
Speaker 11: regulation is going to work. We've seen too many private

590
00:30:01,400 --> 00:30:04,640
Speaker 11: enterprises and by the way, too many public sector organizations

591
00:30:04,800 --> 00:30:08,760
Speaker 11: that do not act beneficially. But you know, it is

592
00:30:08,800 --> 00:30:11,920
Speaker 11: an important issue and it does need to be discussed

593
00:30:12,080 --> 00:30:13,880
Speaker 11: or this will go to some.

594
00:30:15,600 --> 00:30:16,480
Speaker 12: Horrible places.

595
00:30:18,280 --> 00:30:20,080
Speaker 4: Tom, I want to come to you and ask about

596
00:30:20,120 --> 00:30:25,280
Speaker 4: your costs. There's a lot of emphasis on particularly chip design,

597
00:30:25,720 --> 00:30:29,320
Speaker 4: you know, finding the most efficient path forward to power cloud,

598
00:30:29,920 --> 00:30:34,600
Speaker 4: the energy costs behind building large language models, training foundational models.

599
00:30:35,120 --> 00:30:37,080
Speaker 4: How are you kind of making sure that in all

600
00:30:37,120 --> 00:30:39,280
Speaker 4: the work you're doing you said you're bringing new products

601
00:30:39,280 --> 00:30:41,960
Speaker 4: in that you're still not letting kind of costs some

602
00:30:42,120 --> 00:30:43,400
Speaker 4: ravel and get out of control.

603
00:30:45,120 --> 00:30:49,440
Speaker 11: Well, our costs, so our cost in operating these these

604
00:30:49,520 --> 00:30:53,240
Speaker 11: large language models and these enterprise AI applications and our

605
00:30:53,280 --> 00:30:58,800
Speaker 11: customer's costs are primarily from these vendors that provide the

606
00:30:58,800 --> 00:31:04,360
Speaker 11: cloud infrastructure, from Google Cloud, from AWS, from microsofts who

607
00:31:04,400 --> 00:31:06,680
Speaker 11: are what have you now? I think that you know

608
00:31:06,760 --> 00:31:10,120
Speaker 11: these guys who operate these companies and those companies that

609
00:31:10,160 --> 00:31:11,640
Speaker 11: are behind them, like in Nvidia.

610
00:31:12,000 --> 00:31:13,880
Speaker 12: These are very smart people and.

611
00:31:13,840 --> 00:31:18,000
Speaker 11: They are I think making amazing kind of breakthroughs in

612
00:31:18,120 --> 00:31:23,640
Speaker 11: chip technology and energy efficiency technology, and I'm confident they

613
00:31:23,680 --> 00:31:28,840
Speaker 11: will be able to provide these massive scale computation on

614
00:31:28,920 --> 00:31:35,320
Speaker 11: storage infrastructures available to governments and private enterprises at more

615
00:31:35,360 --> 00:31:36,480
Speaker 11: than acceptable cost.

616
00:31:37,040 --> 00:31:39,400
Speaker 2: Tom, great to catch up with you. Thanks coming on

617
00:31:39,400 --> 00:31:41,320
Speaker 2: on a busy day. Tom Cwell is C three AI

618
00:31:41,440 --> 00:31:44,840
Speaker 2: CEO in mob blomog News is in touch with Caristale about,

619
00:31:45,040 --> 00:31:46,800
Speaker 2: of course, what Tom has said. If they want to

620
00:31:46,800 --> 00:31:50,400
Speaker 2: make further comment, We appreciate your comments today. Meanwhile, sticking

621
00:31:50,400 --> 00:31:53,320
Speaker 2: with AI, Google is adding two new features in its

622
00:31:53,440 --> 00:31:56,880
Speaker 2: image search to reduce the spread of misinformation, especially now

623
00:31:56,880 --> 00:31:59,640
Speaker 2: that the artificial intelligence tools have made the creation of

624
00:31:59,680 --> 00:32:02,320
Speaker 2: folk so realistic fakes all the more common. That the

625
00:32:02,360 --> 00:32:04,760
Speaker 2: new feature is called about this image, You're going to

626
00:32:04,840 --> 00:32:07,480
Speaker 2: get context with it. You're going to understand when the

627
00:32:07,560 --> 00:32:10,080
Speaker 2: image or similar ones we first index by Google, where

628
00:32:10,080 --> 00:32:12,840
Speaker 2: they first appeared and where else they shown up online?

629
00:32:13,800 --> 00:32:17,280
Speaker 2: Coming up? Guess what we're talking AI? Yes, but this

630
00:32:17,360 --> 00:32:20,600
Speaker 2: time from a venture perspective. How are you starting out

631
00:32:20,760 --> 00:32:23,040
Speaker 2: your investment journey? Where are the startups that you want

632
00:32:23,080 --> 00:32:25,880
Speaker 2: me backing? George Matthew Manage, director of Insight Partners, with

633
00:32:26,120 --> 00:32:29,360
Speaker 2: plenty of expertise in the field of AI and mL

634
00:32:29,640 --> 00:32:30,320
Speaker 2: joining us next.

635
00:32:30,320 --> 00:32:31,160
Speaker 5: This is bringing back.

636
00:32:41,480 --> 00:32:44,400
Speaker 11: I think the hype around AI is under hyped given

637
00:32:44,480 --> 00:32:46,440
Speaker 11: the impact I think is going to have on the

638
00:32:46,480 --> 00:32:47,280
Speaker 11: way we work and live.

639
00:32:47,440 --> 00:32:50,720
Speaker 3: The top of my questions from many of our customers.

640
00:32:50,320 --> 00:32:52,960
Speaker 2: Is you know, how can they continue in a waking

641
00:32:53,040 --> 00:32:56,000
Speaker 2: responsibly or get crushed by this generative AI wa.

642
00:32:56,320 --> 00:32:58,720
Speaker 10: I think it's going to take a while for regulatory

643
00:32:59,400 --> 00:33:02,360
Speaker 10: frameworks come into place, given the lack of knowledge it

644
00:33:02,400 --> 00:33:04,640
Speaker 10: appears and people in Washington.

645
00:33:04,720 --> 00:33:06,880
Speaker 2: I really think it's going to be incumbent on companies

646
00:33:06,920 --> 00:33:09,200
Speaker 2: themselves to be responsible and.

647
00:33:09,280 --> 00:33:12,080
Speaker 13: How they're taking advantage of this technology and putting in

648
00:33:12,080 --> 00:33:13,200
Speaker 13: place those guardrails.

649
00:33:13,280 --> 00:33:16,640
Speaker 1: We train our models to actually understand what is the

650
00:33:16,640 --> 00:33:18,840
Speaker 1: information on the web that corroborates it that backs up

651
00:33:18,880 --> 00:33:21,400
Speaker 1: the information and if we can't corroborate it, then we will.

652
00:33:21,280 --> 00:33:21,960
Speaker 3: Not output it.

653
00:33:22,040 --> 00:33:24,480
Speaker 10: And what we're seeing today is a lot of AI

654
00:33:24,560 --> 00:33:26,480
Speaker 10: tourists pretending to be AI natives.

655
00:33:26,560 --> 00:33:28,200
Speaker 2: You know, there's a lot of companies who are not

656
00:33:28,320 --> 00:33:30,960
Speaker 2: selling solutions, they're ultimately just selling vaporware.

657
00:33:31,040 --> 00:33:33,680
Speaker 10: AI is something that's you know, we actually know a

658
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Speaker 10: lot about our industry.

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Speaker 3: Is no stranger to it.

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Speaker 1: So for almost all of us experience the beauty of

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Speaker 1: a generativ I.

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Speaker 2: There's some of our recent guests and what they had

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Speaker 2: to say about the AI landscape, both from a fauner

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Speaker 2: perspective to an investing one. So let's keep talking about it.

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Speaker 2: We've got our VC Spotlight moment with George matthew Managing

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Speaker 2: director of Insight Partners, who too has had.

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Speaker 5: A journey as a builder as.

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Speaker 2: A ceokspre You were over at Outrix as well, really

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Speaker 2: helping that business go public and now you're on the

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Speaker 2: finding the new vet side of the equation.

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Speaker 5: And George, what do you make of the hype around AI?

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Speaker 9: Is it hype?

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Speaker 5: Is it reality? How you seeing the week from the

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Speaker 5: chaff at the moment?

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Speaker 13: Yeah, Carolyn, question you asked that question. When you think

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00:34:11,280 --> 00:34:14,000
Speaker 13: about what's going on in AI right now, it's very

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00:34:14,080 --> 00:34:16,280
Speaker 13: clear that there is a fair amount of hype today.

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Speaker 13: But when we look at this down the line ten

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00:34:19,160 --> 00:34:22,399
Speaker 13: years from now, we'll realize that absolutely incredible things are

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00:34:22,440 --> 00:34:25,400
Speaker 13: happening right now as we speak in terms of building

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00:34:25,440 --> 00:34:28,040
Speaker 13: this next generation of software. And this is where Insight

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00:34:28,080 --> 00:34:31,160
Speaker 13: has been focused for almost twenty six years, in terms

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Speaker 13: of really helping guide many of the great founders and

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Speaker 13: executives in building great software companies.

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Speaker 2: Do the guidance for a moment, because yes, you're there

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Speaker 2: with your AI, your mL had set on, and I'm

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Speaker 2: sure you're thinking about companies that have that as their

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00:34:44,239 --> 00:34:46,720
Speaker 2: bones to invest in. But when I think of Insight,

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Speaker 2: I'm also thinking the ed tech companies you have, the

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00:34:48,520 --> 00:34:50,839
Speaker 2: e commerce companies that you have, the companies that are

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Speaker 2: being disrupted enormously by artificial intelligence, particularly generative How much

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Speaker 2: are you having to guide those companies to become AI native?

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Speaker 13: In many ways, in my view, every company has an

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Speaker 13: opportunity to become an AI company, And if you think

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Speaker 13: about the opportunity that exists, particularly within the inside portfolio,

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Speaker 13: many of those companies have incredible amounts of private data. Well,

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Speaker 13: what is that opportunity when you look at the market

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Speaker 13: for really building AI companies at scale in the future,

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Speaker 13: It turns out it's our private data. And so when

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Speaker 13: we work with many of our portfolio companies, we really

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00:35:23,280 --> 00:35:26,000
Speaker 13: help them understand the use of that data to be

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00:35:26,040 --> 00:35:28,359
Speaker 13: able to build analytical models, to be able to build

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00:35:28,440 --> 00:35:31,799
Speaker 13: generative models at scale, and be able to support the

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Speaker 13: scale of their existing business being an AI driven one.

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Speaker 2: It really is going back to that Kafe Wood conversation

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00:35:37,440 --> 00:35:40,839
Speaker 2: we had several months ago and again about proprietary data

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Speaker 2: and how important it is.

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Speaker 4: Yeah, I think the thing for me, George is we

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00:35:45,120 --> 00:35:46,840
Speaker 4: have been our coaster on the show a couple of

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00:35:46,880 --> 00:35:50,200
Speaker 4: weeks ago, and he made this claim that ninety percent

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00:35:50,239 --> 00:35:52,440
Speaker 4: of the companies that you guys are putting money into

712
00:35:52,800 --> 00:35:55,400
Speaker 4: is an industry. They're not going to make it. So

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Speaker 4: I wonder what the strategy then is whether you have

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00:35:59,239 --> 00:36:02,359
Speaker 4: to have a much a portfolio of companies now just

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Speaker 4: to make sure that in a crowded field you find

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Speaker 4: the kind of shining star.

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Speaker 13: I think when you look at this market today, there

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Speaker 13: are many companies that are going to struggle in their

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Speaker 13: transition to really deliver AI solutions at scale. We ad

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Speaker 13: Insight really focus on the businesses that really understand a

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Speaker 13: few things really well.

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Speaker 9: One is the ability.

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Speaker 13: To have that private data available to them to be

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Speaker 13: able to build their AI products. Two is to be

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Speaker 13: able to look at user experiences. Three is to be

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00:36:33,280 --> 00:36:36,040
Speaker 13: able to have a great workflow that fits into the

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Speaker 13: rest of the way that that software works inside their

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00:36:39,320 --> 00:36:42,640
Speaker 13: specific industry. When you find the combination of those three

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00:36:42,760 --> 00:36:45,960
Speaker 13: or four things, you have a very interesting, compelling business.

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Speaker 13: For example, if you look at where Jasper is today

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Speaker 13: as a business, they were able to really build a

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Speaker 13: mechsuit for content marketers to be able to drive the

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Speaker 13: scale of which they are able to produce contact at

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Speaker 13: a speed that's ten x greater than any you've seen before.

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Speaker 13: And so that's a great example of a business that

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Speaker 13: can take the combination of the things that I just

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Speaker 13: mentioned and really build an AI driven business at scale.

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Speaker 4: George, why does Insight sit on the debate around regulation

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Speaker 4: and guardrails?

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Speaker 13: At Insight, we're really looking at how the changing regulation

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00:37:18,960 --> 00:37:22,200
Speaker 13: is continuing to evolve. We definitely believe that there's a

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Speaker 13: need to positively regulate the industry, particularly as there's tremendous

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Speaker 13: changes that are occurring.

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Speaker 9: At a boat, societal and a corporate level.

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Speaker 13: We at Insight really focus on really helping our founders

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00:37:34,960 --> 00:37:38,000
Speaker 13: just achieve the scale and their businesses and as they

747
00:37:38,080 --> 00:37:41,560
Speaker 13: think through the opportunities, particularly from an AI standpoint, how

748
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Speaker 13: can they build very competitive modes over time to be

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Speaker 13: able to scale their businesses accordingly.

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Speaker 2: And motes that are international in many ways. I'm interested

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00:37:51,080 --> 00:37:55,000
Speaker 2: in when you look at your previous successes, check interestingly,

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00:37:55,040 --> 00:37:57,200
Speaker 2: an education tech company that's now having to grapple with

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00:37:57,320 --> 00:38:01,720
Speaker 2: AI disrupting this business model, Ali Baba, a Chinese based company.

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00:38:01,800 --> 00:38:04,560
Speaker 2: And actually even O Coster was saying he's more worried

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00:38:04,560 --> 00:38:07,799
Speaker 2: at the moment about China growing AI than he is

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00:38:07,840 --> 00:38:10,080
Speaker 2: really about whether or not a lot of the ones

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Speaker 2: growing here.

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Speaker 5: And we talk chaff how.

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Speaker 2: Do you think about these two ecosystems evolving, whether US

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00:38:15,840 --> 00:38:17,440
Speaker 2: can quote unquote win the race.

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Speaker 13: I think we're at a moment here where there is

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00:38:20,440 --> 00:38:23,920
Speaker 13: a tremendous advantage for US based companies. And why is

763
00:38:23,960 --> 00:38:26,799
Speaker 13: that Because if you think about what comes out of

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00:38:27,040 --> 00:38:31,160
Speaker 13: a AI or generative model, it's the ability to fuel

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Speaker 13: what we think of as reinforcement learning and that feedback

766
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Speaker 13: loop from a reinforcement learning standpoint, whether it be machines

767
00:38:37,920 --> 00:38:41,280
Speaker 13: humans or humans and machines driving it together, really improve

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00:38:41,360 --> 00:38:44,800
Speaker 13: models over time. When you look at certain totalitarian regimes,

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00:38:44,840 --> 00:38:48,080
Speaker 13: it turns out that feedback loop isn't as significant as

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00:38:48,120 --> 00:38:51,200
Speaker 13: when you see the impact of really building a business

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00:38:51,400 --> 00:38:54,640
Speaker 13: inside of Western democracy. So in our view, we see

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Speaker 13: a slight advantage right now for companies that are building

773
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Speaker 13: their corporations in the context of Western democracy, where you

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00:39:02,840 --> 00:39:06,000
Speaker 13: can see a lot of that reinforcement learning really be

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00:39:06,160 --> 00:39:10,040
Speaker 13: impacting the positive reinforcement of building models at scale.

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Speaker 4: George Matthew, Managing director of Insight Partners out there in

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Speaker 4: New York, thank you very much for your time